2023 Joint WRF and MPAS Workshop Abstracts

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WRF-MOSIT: A modular and Cross-Platform tool for configuring and installing the WRF model

William Hatheway (1), Hosni Snoun (2)

(1) Texas, USA, (2) Numthaja Co., Ltd. Jeddah, Kingdom of Saudi Arabia

The WRF-MOSIT is a set of scripting packages primarily developed for the automation, configuration, and installation of the Weather Research and Forecasting model (WRF), but which is also of more general use in the hurricane (HWRF), hydrological (WRF-Hydro) and chemical (WRF-Chem) components of the model. The package consists of many tools for importing, configuring, and installing libraries, and undertaking a wide range of analyses to enhance scalability, performance, interoperability, and ease of use within a parallel computing environment. WRF-MOSIT is a cross-platform tool for installing the WRF model on multi-operational systems. This modular tool simplifies the installation process, automates configuration, and reduces the risk of errors during installation. It provides a simple and intuitive interface, which makes it easier for users who are not familiar with the installation process.

This toolkit can be installed on the four main computer systems used in the atmospheric community: Debian Kernels, Darwin Kernels, Fedora & CentOS Kernels, and Window Sub-System Linux Kernels, allowing users to install WRF on different systems without having to manually configure the system.

The WRF-MOSIT toolkit is freely available on GitHub (https://github.com/HathewayWill/WRF-MOSIT). The tool improves efficiency by automating many of the steps involved in the installation process, enabling users to spend less time on the installation process and more time on their research. Finally, insights are given for future developments.

Equatorial Waves and Tropical Rainfall Variability in MPAS Simulations with Resolutions of 3.75 km, 15 km, and 120 km

Falko Judt (NCAR/MMM)

Numerical weather and climate models continue to struggle with simulating equatorial waves and tropical rainfall variability. This study presents a potential remedy—high-resolution global models with explicitly resolved convection. A series of MPAS simulations was produced with horizontal cell spacings between 3.75 km, 15 km, and 120 km. The share of resolved precipitation in these simulations ranged from 88% (3.75 km mesh) to 2% (120 km mesh). The simulations in which convection was mostly resolved produced much more realistic equatorial waves than the simulations in which convection was mostly parameterized. Consequently, the simulations with resolved convection produced more realistic precipitation patterns and precipitation variances. The results demonstrate that high-resolution global models with explicitly resolved convection are a promising tool to improve tropical weather forecasts and climate projections.

A New Warm-Rain Scheme for WRF and MPAS

Cliff Mass (1), Robert Conrick (2)

(1) University of Washington, (2) The Boeing Corporation

This talk will describe a highly promising new warm-rain microphysics scheme for WRF and MPAS. Current bulk microphysical parameterization schemes possess deficiencies during periods of warm rain, poorly simulating drop size distributions (DSDs) and producing DSDs more characteristic of cold rain. Furthermore, there is growing evidence that precipitation is underpredicted upwind of coastal terrain when warm rain is present. To help address an apparent deficiency in warm rain physics, this study introduces a new warm rain microphysical parameterization. Central to the new scheme is the use of a lognormal cloud water DSD in place of the gamma distribution. The need for a lognormal distribution was determined through analysis of simulations from a spectral bin microphysics scheme. The lognormal distribution better matches cloud DSDs produced by spectral bin microphysics and produces a more realistic and continuous transition from cloud to rain drops. Several other model improvements were made, including the adjustment of rain-to-cloud autoconversion to account for the new cloud DSD. Evaluation of the new scheme is performed during a heavy warm rain event and for an extended period from the Olympic Mountains Experiment (OLYMPEX) field campaign of winter 2015-16. During the period of heavy warm rain, the new scheme performed well, matching observed precipitation distributions and reproducing observed rain DSDs at disdrometer sites. For the multi-month OLYMPEX campaign period, the new scheme increased rain rates, rain-water mixing ratios, and rain drop number concentrations, while decreasing rain drop diameters in liquid-phase clouds. These effects are consistent with an increase in simulated warm rain.

Updates to the MYNN-EDMF PBL Scheme to Improve Operational Forecasting Applications

Joseph B. Olson (1), Wayne M. Angevine (2,3), Dave Turner (1), Xia Sun (1,3), Franciano S. Puhales (4), Timothy W. Juliano (5)

(1) NOAA/Global Systems Laboratory, Boulder, Colorado, (2) NOAA/Chemical Science Laboratory, Boulder, Colorado, (3) Cooperative Institute for Research in Environmental Sciences, Boulder, Colorado, (4) Universidade Federal de Santa Maria - Federal University of Santa Maria, Brazil, (5) National Center for Atmospheric Research, Boulder, Colorado

The Mellor–Yamada–Nakanishi–Niino (MYNN) Eddy Diffusivity-Mass Flux (EDMF) moist-turbulence parameterization scheme has been an important component of the Rapid Refresh (RAP), High-Resolution Rapid Refresh (HRRR), and has been slated for the first version of the Rapid Refresh Forecast System (RRFS). More recently, its development focus has expanded to include global applications. Most of the recent updates have been developed within the CCPP/FV3 framework but recent attempts to unify the scheme for non-CCPP frameworks allows for more easy and frequent updates in the future.

The long-overdue updates for WRF-ARWv4.5 help alleviate several concerns that have been noticed by some colleagues and some that have escaped the eye of the novice. One of the most crucial improvements has been to improve the conservation properties, which were a primary cause of poor performance in initial testing for medium-range forecasting in the global framework. These conservation issues were well hidden in short-range regional applications. The MYNN-EDMF has recently received focused attention for hurricane applications in hurricane forecasting, and has shown reasonable skill. Other improvements have come through the refinement of the subgrid-cloud representation of both stratus and shallow-convective regimes. A new closure level “2.6” was added to improve the representation of stratus clouds, while new relationships derived from large-eddy simulation analysis have improved the shallow-cumulus clouds. Furthermore, the MYNN-EDMF has recently received focused attention for hurricane applications in hurricane forecasting, and has shown reasonable skill. Several bugs have been removed to allow for an accurate TKE budget analysis and additional capabilities have been added, such as the capability to mix snow, black-carbon aerosols, and new surface stability functions. These recent developments will be overviewed and some examples of improvements will be given. Further development plans will be outlined.

Comparisons of Marine Boundary Layer Clouds simulated by the MYNN-EDMF PBL Scheme in both WRF-ARW and FV3: Exploring Dynamical Core Dependence

Xia Sun (1,2), Joseph Olson (2) , David Turner (2), Wayne Angevine (1,3)

(1) Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder CO, United States, (2) NOAA Global Systems Laboratory, Boulder CO, United States, (3) NOAA Chemical Sciences Laboratory, Boulder CO, United States

Tropical shallow-cumulus clouds, which are the most abundant cloud on Earth, have a notable impact on Earth’s shortwave radiation budget. To precisely model cloud feedback in weather models, it is imperative to accurately represent marine tropical shallow cumulus as well as organized forms of shallow cumuli. Towards a unified planetary boundary layer (PBL) scheme that can effectively operate when coupled with various dynamic cores (dycores), our research delves into the sensitivity of Mellor-Yamada-Nakanishi-Niino (MYNN) Eddy Diffusivity-Mass Flux (EDMF) scheme to different dycores and explore the sensitivities in dynamic and thermodynamic aspects. Specifically, this study assesses the impacts of two different dycores on simulated marine boundary layer (MBL) structure and marine clouds morphology using MYNN-EDMF PBL scheme. Simulations are conducted using the Weather Research & Forecasting (WRF) Model with Advanced Research WRF (ARW) dycore and the Unified Forecast System (UFS) Short-Range-Weather (SRW) application with Finite-Volume Cubed-Sphere (FV3) dycore. A regional domain near Barbados with operational horizontal resolutions was set up covering the region where the Elucidating the Role of Cloud-Circulation Coupling in Climate (EUREC4A) field campaign took place in Jan-Feb 2020. Simulated MBL vertical profiles are examined using drop sondes launched from aircraft. Cloud morphologies simulated in the two models are compared with satellite products. The probability density functions (PDFs) of the simulated cloud liquid water path (LWP) derived from the two model simulations are compared with cloud retrievals obtained from GOES-16.

Subgrid cloud performance in MYNN-EDMF

Wayne M. Angevine (1,2), Joseph Olson (3), Julia Simonson (1,3)

(1) Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder CO, United States, (2) NOAA Chemical Sciences Laboratory, Boulder CO, United States, (3) NOAA Global Systems Laboratory, Boulder CO, United States

Shallow cumulus and stratocumulus cloud is subgrid even at convection-permitting (O(1-10 km)) scales. Clouds rooted in the boundary layer are handled by the mass flux portion of Eddy-Diffusivity Mass Flux (EDMF) schemes. However, subgrid clouds can arise from other processes instead of or in addition to surface-based convection. These processes are grossly non-linear. In this presentation, we show results from 30+ cases of shallow convection, clear skies, and stratus at the ARM SGP site. Baseline simulations were conducted with the SAM LES model using forcing derived from the operational RAP model. The current formulation is tested within the MYNN-EDMF boundary layer turbulence and cloud scheme used in the operational RAP and HRRR models. We also show performance for a wider range of cloud regimes from the ARM MAGIC campaign in the Pacific Ocean. Characteristics of stratocumulus, trade wind cumulus, and the transition between them will be shown. These results can be compared with those of Sun et al. for the Atlantic (EUREC4A).

An Explicit Microphysical and Electrical Charging Model to Study the Effects of Changing Aerosol Composition on the Electric Field and Lightning Distribution.

Barry H. Lynn (1), Yoav Yair (2), Edward Mansell (3), Eyal Ilotoviz (4), Alexandre Fierro (5), and Alexander P. Khain (6)

(1) The Hebrew University of Jerusalem, Department of Earth Sciences and Weather It Is, LTD., (2)Reichman University (IDC, Herzliya), (3) NOAA/National Severe Storms Laboratory, (4) Israel Meteorological Service, (5) Central Institute for Meteorology and Geodynamics (ZAMG, Vienna). Department of Forecasting Models., (6) The Hebrew University of Jerusalem, Department of Earth Sciences

As climate changes, so will likely the aerosol composition of the atmosphere, possibly leading to substantial changes in cloud-aerosol interactions and associated charging of the atmosphere (including lightning intensity). A bin microphysical model is ideally suited to study such possible interactions. For these purposes, the aerosol distribution of the Hebrew University Cloud Model (HUCM) was altered to account for the impact of desert dust and urban aerosols on nucleation. The microphysics part of HUCM, also known as Spectral (bin) Microphysics (SBM), has been coupled to the Weather Research and Forecasting Model (WRF). Additionally, SBM (in WRF) was coupled with the Takahashi and Saunders charging scheme (bin by bin) to explicitly account for charging during collisions between small ice and large ice particles in the presence of supercooled liquid water. It uses the electrical solver of WRF-ELEC to compute the electric field from bulk (integrated) charge concentrations within each grid point. The model accounts for collisions between charged hydrometeors, diffusional growth, break-up of charged particles, their advection and sedimentation, and dissipation of the electric field through lightning discharges as both Intracloud and Cloud-to-Ground Lightning. The energy of the discharges is also calculated. Because droplet and ice concentrations depend on background aerosol conditions, the coupled model accounts for the effect of changes in aerosol composition on electrical charge distribution and resultant lightning. The model was used to a (real) squall-line as well as eastern Mediterranean storm (with a number of superbolt lightning events) . Results are described and compared to those obtained with the WRF-ELEC with NSSL microphysics.

Incorporating advanced snow microphysics and lateral transport into the Noah-MP land surface model

Theodore Letcher (1), Julie Parno (1)

(1) USACE-Cold Regions Research and Engineering Lab

The Noah-MP land surface model is a key part of the greater NCAR community model suite. It is often used as the lower boundary condition for WRF and MPAS, however, it also valuable as a stand-alone model. To support the simulation of snow, soil moisture, and hydrology at the watershed scale, we have incorporated several snow physics upgrades to the snow model component of Noah-MP. These upgrades include a blowing snow overlay to simulate lateral redistribution of snow by the wind, as well as the addition of new prognostic snow microstructure variables, namely grain size and bond radius. These upgrades are demonstrated in both idealized and real-world applications. The test simulations performed here are promising and show that the newly added snow physics replicate observed behavior with physical realism. We hope that these upgrades enable and facilitate ongoing and future research aimed at characterizing the impacts of the integrated snow/soil land surface at high-resolution scales.

Recent updates in WRF urban and land surface models

Cenlin He (1), Fei Chen (1), Matthias Demuzere (2), Andrea Zonato (3), Alberto Martilli (4)

(1) National Center for Atmospheric Research, Boulder, CO, (2) Ruhr-Universität Bochum, Germany, (3) University of Trento, Italy, (4) CIEMAT, Spain

In this presentation, I will present some recent updates in the WRF urban and land surface models.

A Double-Moment Cloud Parameterization with In-Cloud Microphysical Processes for Use in Weather Forecasting

Songyou Hong (1,2), Haiqin Li1 (3), Jian-Wen Bao (2), and Jimy Dudhia (4)

(1) Cooperative Institute of Research in Environmental Science, University of Colorado, Boulder, Colorado, (2) Physical Science Laboratory, Earth System Research Laboratory, NOAA, Boulder, Colorado, (3) Global System Laboratory, Earth System Research Laboratory, NOAA, Boulder, Colorado, (4) MMM, NCAR, Boulder, Colorado

A double moment cloud microphysics parameterization scheme with in-cloud microphysical processes is developed for use in weather forecasting. A main ingredient of the scheme utilizes a concept to represent the partial cloudiness effect on the microphysical processes, following the study of Kim and Hong (2018). The underlying assumption is that all the microphysical processes occur in a cloudy part of the grid box. Based on the long-term evaluation of the WRF Single-Moment (WSM) and WRF Double-Moment (WDM) schemes by WRF community, several revisions are made in microphysics terms, along with a newly introduced aerosol effect in ice processes. A mass-conserving Semi-Lagrangian sedimentation is re-configured for double-moment physics, which is superior to the conventional Eulerian algorithm in the context of the computational accuracy and numerical accuracy. Results using WRF and UFS global models will be presented.

MPAS-JEDI-based Variable-Resolution Global Data Assimilation Systems with ~3-km Cell Spacing over North America

Craig Schwartz (1), Jamie Bresch (1), Byoung-Joo Jung (1), Jonathan Guerrette (1), Junmei Ban (1), Yonggang Yu (1), Zhiquan Liu (1), and Chris Snyder (1)

(1) National Center for Atmospheric Research, Boulder, Colorado

Using the Joint Effort for Data Assimilation Integration (JEDI) software interfaced with NCAR’s Model for Prediction Across Scales (MPAS), we performed three experiments with ensemble–variational (EnVar) data assimilation (DA) systems using a variable-resolution model configuration. Specifically, MPAS’s grid mesh possessed ~3-km horizontal cell spacing over most of North America and smoothly transitioned to ~15-km cell spacing over the rest of the globe. Continuously cycling EnVar analyses were produced every 6 hours for 35 days in Spring 2019. All experiments assimilated conventional observations and clear-sky radiances from AMSU-A sensors, and 0000 UTC analyses initialized 8-day forecasts over the global variable-resolution mesh. The three experiments differed either in terms of the physics suites used within the MPAS model or the horizontal resolution of the flow-dependent, ensemble-based background error covariances (BECs) used within EnVar DA (provided by either 15- or 30-km MPAS-based ensemble Kalman filters).

The EnVar systems appeared to perform appropriately, as DA statistics indicated the model climate was stable over the cycling period and biases were generally small. All experiments initialized forecasts with diurnal cycles of precipitation over the conterminous United States (CONUS) that generally agreed with those observed throughout the 8-day forecasts. Precipitation forecast skill over the CONUS was sensitive to the physical parameterization suite but insensitive to whether 15- or 30-km ensembles provided BECs for EnVar DA. These findings reinforce the importance of a well-performing physics suite for effective DA and suggest that coarser, cheaper ensembles can potentially be leveraged within high-resolution global EnVar DA systems.

Our EnVar systems are likely the first demonstrations of continuously cycling global DA on a mesh with an area of convection-allowing cell spacing and look toward future operational models. In addition to describing our experiments, longer-term plans at NCAR to develop and demonstrate a global convection-allowing ensemble-based DA system with MPAS will be discussed.

Moisture Sensitivity in the Formation of an Atlantic Tropical Cyclone: A Case Study

Kelly M. Núñez Ocasio (1) and Chris A. Davis (1)

(1) National Center for Atmospheric Research, Boulder, Colorado

In a recent model evaluation of the African Easterly Wave (AEW) that became Helene (pre-Helene; 2006) over the Atlantic, the wave was categorized as a mixed-off-equatorial moisture mode during tropical cyclogenesis as it evolved under weak temperature gradient balance. The growth and propagation of the wave were related to the position of the convection with respect to the center of the wave vortex. The influence of environmental moisture on wave propagation before and during genesis however, remains an open question. Motivated by the recent findings, in this study, moisture sensitivity experiments are performed with a convection-permitting model to further evaluate the moisture dependency of the pre-Helene wave and later tropical cyclogenesis. The Model for Prediction Across Scales (MPAS) regional configuration is used to allow altering initial and lateral boundary conditions of relative humidity (RH) through the entire atmospheric column using ERA5 pressure-level data. Preliminary results reveal that over land the strength of the wave-trough meridional flow is related to mid-to-upper-level diabatic heating tendencies from clouds located in the northerly phase of the wave and to the lack of shallow convection within the vortex. In MOIST (RH x 1.2 experiment), the wave moves slower, yet organized convection propagates out of phase with the wave speed, ultimately weakening the wave and subsequent tropical cyclogenesis. In CONTROL, where the wave propagates faster, the phasing between wave and convection supports a stronger wave prior to genesis and ultimately genesis when compared to MOIST. A moister atmosphere (MOIST) favors a larger fraction of shallow convection (bottom heavy and weaker updrafts) at the center and ahead of the vortex, detraining the mid-troposphere and weakening the mid-tropospheric vorticity. This leads to a wave that weakens prior to genesis compared to CONTROL as well as a more abrupt decrease in speed prior to genesis. An analysis of the energetics of the AEW as it relates to the mean state reveals that more moisture does not necessarily result in a more favorable dynamic and thermodynamic zonal mean state nor in a more intense wave or tropical cyclogenesis event. A wave that propagates more slowly (‘moist wave’ versus ‘dry wave’), does not necessarily favor growth. For further growth, convection that is in phase with the vortex should be deep moist convection.

A method for producing limited-area MPAS meshes with one-to-one cell matching to global quasi-uniform meshes at the boundary

Orren Russell (Russ) Bullock Jr. (1)

(1) U.S. EPA - Atmospheric Dynamics and Meteorology Branch

The U.S. Environmental Protection Agency (EPA) is developing an Advanced Air Quality Modeling System (AAQMS) using the MPAS model framework to conduct state-of-the-science air quality modeling. Most EPA applications of AAQMS will involve simulating air quality over the continental United States with anticipated modeling domains focused on North America and surrounding waters. We hope to use regional modeling domains with high resolution over the focus area with boundary values obtained from previous global simulations performed on quasi-uniform meshes. Spatial interpolation is often used to provide boundary values for regional simulations of physical meteorology. However, spatial interpolation of pollutant concentrations has been shown to create troublesome chemical imbalances in air quality model simulations. Unfortunately, using a variable-resolution regional mesh with a boundary cell size matching the cell size of the global uniform domain does not eliminate the need for spatial interpolation. The standard method for generating variable-resolution meshes is based on Lloyd’s method which adjusts the location and size of mesh elements around the entire globe. Thus, there is no one-to-one cell correspondence between a uniform mesh and any variable-resolution mesh. To avoid spatial interpolation, a new technique has been developed to combine a selected sub-domain from a variable-resolution mesh with its complimentary background from a global quasi-uniform mesh. The resulting discontinuous mesh is adjusted using a variation of Lloyd’s method within a specified zone near the interface to produce a valid MPAS mesh with no obtuse triangles in the dual mesh. This provides a global variable-resolution mesh from which a regional domain can be selected where boundary zone cells will have one-to-one correspondence with the global background mesh. An explanation of the mesh blending technique will be provided along with recommendations to the prospective user to avoid known pitfalls.

Adapting the MPAS Dynamical Core for Applications Extending into the Thermosphere

Joseph Klemp (1), William Skamarock (1)

(1) National Center for Atmospheric Research, Boulder, Colorado

Typically weather and climate models focus on simulating the atmosphere throughout the troposphere and stratosphere. However, atmospheric disturbances in these regions can also impact important physical processes at much higher altitudes, even extending into the upper thermosphere (∼500 km). The Model for Prediction Across Scales (MPAS) was designed to simulate a broad range of atmospheric phenomena, from cloud scale up to global scale. Recently, we have been modifying the model and testing its viability for deep-atmosphere applications that include the thermosphere. This raises new challenges for the model numerics due to the extreme variation in the atmospheric parameters, such as density, for example, that deceases by ∼12 orders of magnitude between the surface and the upper thermosphere. The variability of the constituents of the atmosphere must now be included in the dynamical model as well as influences such as molecular viscosity and thermal conductivity, which are negligible in the lower atmosphere. Because significant vertical expansion/contraction of the atmosphere occurs due to deep radiative heating/cooling, the rigid lid upper boundary employed in MPAS is not well suited for applications extending into the thermosphere. We have developed and tested a simple modification to the height-based coordinate formulation that allows the height of the upper boundary to adaptively follow a constant pressure surface, without significant retooling of the model numerics. In simulating idealized test cases in a simplified 2-D slab version of MPAS, we demonstrate that numerical integration of the model equations continues to provide a stable and efficient nonhydrostatic framework for applications in the thermospheric environment.

Multi-Scale Interactions of Tropical Weather Systems in MPAS-A Aquaplanet Simulations

Rosimar Rios-Berrios (1)

(1) National Center for Atmospheric Research, Boulder, Colorado

Tropical weather systems are important components of Earth’s climate system—from being key players in redistributing heat and moisture from the tropics to the high latitudes to manifesting into powerful high-impact phenomena (e.g., hurricanes). Despite being so important, the representation of tropical weather systems and their interactions is deficient in most climate and weather prediction models. This study tackles this issue by examining the multi-scale variability of tropical weather systems in a hierarchy of idealized model experiments with varying horizontal cell spacing—from 120 km to 3 km. All experiments were produced with the Model for Prediction Across Scales-Atmosphere (MPAS-A). In the first part of this talk, I will introduce a set of MPAS-A aquaplanet simulations and will demonstrate that the simulations capture tropical rainfall variability driven by equatorial waves. In the second part, I will show an example of multi-scale interactions between tropical weather systems—the modulation of tropical cyclogenesis by convectively coupled Kelvin waves. I will conclude with a discussion of these results, along with examples of other science topics that could be explored with the MPAS-A aquaplanet simulations.

The configuration and evaluation of the WRF-Chem air quality model in Thailand

Worapop Thongsame (1), Daven K. Henze (1), Rajesh Kumar (2), Mary Barth (2), Gabriele Pfister (2)

(1) University of Colorado Boulder, (2) National Center for Atmospheric Research, Boulder, Colorado

In recent years, Thailand has experienced a significant increase in air pollution, primarily due to population and economic growth, as well as biomass burning from wildfires and residual crop burning. The resulting increase in emissions has led to high concentrations of PM2.5. An accurate air pollution forecasting and monitoring system are necessary for the government to determine the direction of policy to improve air quality in Thailand. Currently, the Pollution Control Department (PCD) of Thailand provides a ground-based air quality station dataset of roughly 60 stations that report hourly aerosol concentration. Meanwhile, Aerosol Optical Depth (AOD) from MODIS satellite data provides information on the total PM concentration over Thailand, however, the overpass time of the satellite is twice a day. Therefore, air quality models have become essential tools for monitoring PM2.5 concentrations as they provide both temporal and spatial information on PM2.5.

The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is a widely used tool for simulating air pollution in Southeast Asia, facilitating our understanding of atmospheric transport and chemistry. Our study focuses on the configuration and evaluation of the WRF-Chem air quality model to simulate PM2.5 concentrations in Thailand. The aim of the study is to enhance the accuracy of air quality model in predicting PM2.5 concentrations, while providing insights into pollution sources in Thailand. We use the MOZART-MOSAIC scheme and the model is run at a spatial resolution of 9 km. The model's performance is evaluated using ground-based observations and satellite data, such as MODIS AOD and MOPITT CO. The performance of anthropogenic emission inventories (CAMS, ECLIPSE, REAS, and EDGAR) was evaluated during the off-haze season in October 2019. We found that CAMS and ECLIPSE provide comparable PM2.5 concentrations, while REAS and EDGAR overestimate PM levels. Biomass burning inventories (QFED, FINN1.5, and FINN2.5) were evaluated during the haze season in March 2019, and FINN1.5 demonstrated the highest performance with a correlation coefficient of 0.75 when simulated PM2.5 concentrations are compared to air quality station data. In comparison to MODIS in the Northern part of the domain, FINN2.5 overestimated AOD while QFED underestimated it. FINN1.5 appeared to provide the best performance with a correlation coefficient of 0.63 compared to MODIS AOD in all domains. However, evaluation with MOPITT CO showed that FINN2.5 had better performance than FINN1.5, with correlation coefficients of 0.64 and 0.48, respectively. Overall, the combination of CAMS and FINN1.5 was identified as most suitable for the WRF-Chem model with the MOZART-MOSAIC scheme to simulate PM2.5 concentrations in Thailand.

Track Evolution of Typhoon Chanthu (2021) past Taiwan as Investigated Using a High-Resolution Global Model

Ya-Shin Chi (1), Ching-Yuang Huang (1), and William C. Skamarock (2)

(1) Department of Atmospheric Sciences, National Central University, Jhong-Li, Taiwan, (2) National Center for Atmospheric Research, Boulder, Colorado, USA

Typhoon Chanthu (2021) moved northwestward toward southeastern Taiwan but took a northward (rightward) track deflection during the offshore movement along east Taiwan and then an inland westward movement near the northeastern Taiwan. In this study, the global model MPAS with multiple resolution (60–15–1–km) is used to simulate such track deflection. Sensitivity experiments are conducted to identify the mechanism for the induced track changes. The results indicate that the MJO large-scale component plays an important role in the typhoon movement, while a rightward track deflection near Taiwan is mainly induced by the recirculating flow resulting from the effect of Taiwan topography. In the presence of the Taiwan terrain, the radial inflow in the inner typhoon is considerably intensified to provide stronger northward asymmetric flow. Analysis of the wavenumber–1 potential vorticity (PV) budget signifies the dominance of the horizontal PV advection before the track deflection, which is also somewhat affected by the vertical PV advection as the deflection takes place. Differential diabatic heating appears to retard the typhoon translation, opposite to that of horizontal PV advection. For the northward typhoon toward Taiwan, a pair of cyclonic and anticyclonic wavenumber–1 gyres induced by the Taiwan terrain are rotating with time in the vicinity of the typhoon center to produce different track evolution. The idealized WRF is also used to aid an illustration of the track deflection under varying steering conditions. Idealized simulations confirm the track deflection mechanism in the real case and indicate the sensitivity of the track deflection with respect to the steering flow intensity and direction as discussed in this study.

The Weather Research and Forecasting Model: 2023 Annual Update

Jimy Dudhia (1), Wei Wang (1), and Ming Chen (1)

(1) National Center for Atmospheric Research, Boulder, Colorado

Since WRF Version 4.4 in April 2022, there have been minor releases 4.4.1 and 4.4.2 in August and December, and a new major release in April 2023. The talk will outline the major updates in the last year and show some verification test results.

New features include                                             
(a) A new k-epsilon PBL option that predicts tke, dissipation and tpe (turbulent potential energy) from Zonato et al. (2022) (University of Trento, Italy). This is bl_pbl_physics=17.                                             
(b) An extension to the Thompson microphysics (mp_physics=38) that includes double-moment graupel category with its density making it graupel/hail.                                             
(c) Reorganized MYNN PBL to single switch bl_pbl_physics=5 with closure options bl_mynn_closure (2.5, 2.6, 3.0) and also significant updates for consistency with operational codes.                                             
(d) A scale-aware extension to allow the new Tiedtke cumulus scheme to be scale-aware below 15 km grid lengths. Tested with cloud-permitting grids. This is cu_physics=16.                                             
(e) The P3 microphysics scheme has been updated.                                             
(f) WPS includes a new global dataset for Local Climate Zones in urban areas for use with the LSM urban options providing better urban morphology maps at 100 m resolution. Provided by Ruhr University, Bochum, Germany.                                             
Other changes and bug-fixes will also be described. Changes to NoahMP land-surface, chemistry, and data assimilation will be described elsewhere.

Regional Arctic Cyclone Prediction with MRI-4DVAR and Polar WRF

David H. Bromwich (1), Zhiquan Liu (2), Junmei Ban (2), Lesheng Bai (1)

(1) Byrd Polar and Climate Research Center, The Ohio State University, (2) National Center for Atmospheric Research, Boulder, Colorado, USA

The recently developed Multi-Resolution Incremental 4DVAR (MRI-4DVAR) together with the polar optimized version of the Weather Research and Forecasting (Polar WRF) model are used to explore the regional predictive skill for intense cyclones over the Arctic Ocean that often cause substantial disintegration of the sea ice cover. In comparison to global prediction systems (ECMWF and NCEP), enhanced forecast skill for up to 5 days ahead is demonstrated for extreme summer (August 2016) and winter (January 2022) cases. This forecast improvement is traced to better representation of the stratospheric polar vortex in the initial conditions as a result of satellite radiance assimilation. During August-September 2021, an extensive campaign of Windborne drifting radiosondes was conducted by the Office of Naval Research to explore the causality of summer cyclones especially the role of tropopause polar vortices. The assimilation of these 10-minute observations of basic upper tropospheric meteorological variables (T, RH, Winds) by MRI-4DVAR over the data sparse Arctic Ocean is found to significantly enhance the extended forecast of a major summer cyclone on the Eurasian side of the Arctic Ocean.

Sensitivity of the February 2021 U.S. Cold-Air Outbreak to Tropopause Polar Vortex Intensity

Tomer Burg (1), Steven Cavallo (1)

(1) University of Oklahoma

Tropopause Polar Vortices (TPVs) are coherent long-lived vortices along the tropopause, with cyclonic TPVs identified by a local minimum in temperature and local maximum in potential vorticity along the dynamic tropopause. TPVs are most common poleward of 60ºN but can be transported into the midlatitudes, where they can impact a wide variety of synoptic-scale phenomena. One common TPV pathway out of the high latitudes is via Canada, where TPVs and their associated cold pools can then contribute to major midlatitude Cold Air Outbreaks (CAOs).

February 2021 featured a historic CAO across the United States, both in terms of magnitude and duration. This CAO and associated winter storms resulted in substantial societal impacts, with extensive power and water outages across Texas and parts of Oklahoma, record cold, and multiple snow and ice events. This CAO was associated with multiple TPVs transported southward into southern Canada, lingering over the same region for multiple days before merging, building a reservoir of cold air continually advected southward into the South Plains leeward of the Rockies. It is hypothesized here that the magnitude and southward extent of the CAO is sensitive to the intensity and subsequent evolution and merging of the TPVs.

A series of numerical modeling experiments using the Model for Prediction Across Scales (MPAS) is used to assess the sensitivity of the CAO evolution to the antecedent TPVs. A 60-km global simulation is used, with a 15-km refinement region covering North America. Experiments are designed to weaken and strengthen the TPV by imposing heating and cooling rates of 5, 10, and 15 K per day near the tropopause, respectively. The stronger TPVs merged more quickly but farther east with a smaller CAO spatial extent, while the weaker TPVs took longer to merge and subsequently merged farther east. Results show a non-linear relationship exists between TPV intensity and track with the southward extent and magnitude of the cold air outbreak. We conclude that the optimal balance maximizing the impacts of the February 2021 CAO in the Southern Plains is the rate at which multiple TPVs merge and subsequently move eastward.

A New Boundary Layer Parameterization for WRF: A Heat Flux Budget Approach.

Rafael Maroneze (1), Felipe D. Costa (1), Luiz Eduardo Medeiros (1), Franciano S. Puhales (2), Otávio C. Acevedo (3)

(1) Universidade Federal do Pampa, Alegrete, RS, Brazil, (2) Universidade Federal de Santa Maria (UFSM), Santa Maria, RS, Brazil, (3) University of Oklahoma, Norman, OK, USA

The atmospheric boundary layer (ABL) flow is directly affected by mechanical drag and thermal effects that arise from the interaction with the Earth surface. Hence, a good representation of the interaction between the ABL and the surface is essential for all atmospheric applications. Recently, a new turbulence closure scheme, for a stable boundary layer (SBL), was proposed. It solves prognostic equations for both the heat flux and temperature variance. The addition of a prognostic equation for the heat flux allows the model to represent the two SBL regimes adequately. Furthermore, the stratification dependence on other characteristics of the mean and turbulent flows arises naturally, not being necessary to use an empirical stability function. On the other hand, the development of the new turbulence closure scheme for the convective boundary layer (SBL) is still in progress. The main goal of the present work is to develop and to validate such a parameterization for unstable conditions. Moreover, it aims to investigate how the mixed layer and the entertainment zone are affected by the different mixing length scales. For doing so, an entire daily cycle was simulated by considering the geostrophic forcing constant and the surface temperature is estimated by the Unified Noah land-surface model. The radiation is given by the rapid radiative transfer model longwave parametrization and Dudhia shortwave parametrization, respectively. All simulations were performed with WRF (version 4.4.2) single-column mode, with 120 levels between the surface (z=0) and the domain top (z= 12 km) and the timestep used was 10 s. The results show that the ratio between the minimum value of the vertical sensible heat flux and its surface value shows sensitivity to the choice of the reference length scale. The next steps of the present work is to validate the results against both observational and Large Eddy Simulations, in both single column mode and real case.

Evaluation of cloud microphysics schemes in WRF for Hokuriku winter clouds using videosonde observation

Yuki Kanno (1), Soichiro Sugimoto (1)

(1) Central Research Institute of Electric Power Industry, Japan

We have evaluated the simulated microphysics in Hokuriku winter clouds, which are maritime clouds that frequently produce lightnings, based on data from the Videosonde. The Videosonde makes it possible to directly identify precipitation particle type. The Weather Research and Forecasting (WRF) model (version 4.0) is used to simulate 19 cold air outbreaks occurred for three winter periods over 2010-2012. The cloud-resolving simulations have a horizontal resolution of 1.5 km. In these periods, about 60 times of videosonde observations are carried out in Kashiwazaki, a coastal city in Hokuriku distinct facing the Sea of Japan, and they were used to evaluate the six cloud microphysics schemes, including WSM6, WDM6, Thompson, Morrison, Milbrandt-Yau, and NSSL. All of six schemes simulated reasonably well the spatial distributions of accumulated precipitation intensity during the events, but they tend to overestimate the precipitation amount. Comparisons with the videosonde observations showed that the kind of ice hydrometers in Hokuriku winter clouds was not correctly reproduced by the six schemes. No scheme has significant performance to simulate the vertical profiles of mass density of ice hydrometers consistent with observations across all events. The number density of ice hydrometers was better reproduced than the mass density.

Graupel was dominant in most of the observation cases, whereas snow dominates in the five schemes across all cases except for Milbrandt-Yau scheme. Milbrandt-Yau scheme outperforms to simulate the kind of solid state of precipitation particle that varies from case to case.

MPAS-A with Hierarchical Timestepping and Customized Mesh Generation: 2023 Updates

Chi-Chiu Cheung (1), Ka-Ki Ng (1), Wai-Pang Sze (1), Jimmy Tat Chi Wong (1)

(1) ClusterTech Limited, Hong Kong

We intend to report some development and applications of the CPAS model since our last presentation back in 2019.

Firstly, the HCP cloud-computing platform (https://cpas.earth/) is maintained to be operational over years and served a 2-credit summer course in the Chinese University of Hong Kong in 2022. Students learned NWP hands-on, performed re-forecasting for typhoon scenarios with customized meshes and analysed the simulated typhoon tracks on the online platform. I hope more students over the world can use this online HPC tool to learn MPAS.

Secondly, we evaluated the use of a 60km-0.2km global mesh (x256 resolution variation) with the Shin-Hong PBL scheme. The advantage is that, being a global model rather than a limited area model, the validity of forecasts can be as long as 9 days (as we tried) while it produces high-resolution NWP direct model output for small regions. There are 9 timestepping levels, with timestep 0.8 second for the finest resolution zone (minimum grid spacing 0.17km), to 200.0 second for the coarsest resolution (maximum grid spacing 59.7 km), doubling timestep length between levels. The resolving of complex terrain, coastline and landuse by the customized grid in 200m resolution from 3s (∼90 m)-resolution static data sources for Hong Kong is great. The result shows that wind flow patterns due to detailed orography and sheltering effect by hills are realistically simulated, in addition to improved local forecast statistics. A baroclinic wave test was also conducted for a 100km-0.2km mesh (x512). The result is comparable with those in other Jablonowski-Williamson tests, showing the validity of the dynamical core of CPAS with Hierarchical Timestepping. These results were published in a journal paper.

Thirdly, we strengthen the application of variable-resolution model to city-sized microclimate modelling. We are in progress of enabling the urban canopy model in CPAS. For large and dense cities like Hong Kong, the high-intensity residential landuse type is defined with specified anthropogenic heating. Simulation results show t2m error in the diurnal cycle is reduced.

Lastly, for evaluating location-specific building safety, we tried applying CPAS 200m simulation data as inlet to drive Computational Fluid Dynamics (CFD) runs for urban buildings. The CFD run contains real 3D buildings models for a street block and the NWP data replaces idealized inlet profile usually used in CFD. We simulated super Typhoon Mangkhut (2018) which was hazardous to Hong Kong. The CFD result shows very reasonable patterns of streamlines in the gaps between buildings and pressures on glass curtains of buildings. With fine wind patterns corresponding to near-by sheltering hills / opening valleys simulated by NWP as driving data, CFD may hopefully give more meaningful analysis.

Nocturnal boundary layer height uncertainty in particulate matter simulations during the KORUS-AQ campaign

Hyo-Jung Lee (1), Hyun-Young Jo (1), Jong-Min Kim (1), Juseon Bak (1), Moon-Soo Park (2), Jung-Kwon Kim (3), Yu-Jin Jo (4), Min-Jun Park (1), Seung-Hee Baek (1), Sang-Seok Oh (1), Cheol-Hee Kim (1)

(1) Pusan National University, South Korea, (2) Sejong University, (3) Dong-Eui University, (4) University of Florida

Vertical mixing in the planetary boundary layer (PBL) is an important factor in the prediction of particulate matter (PM) concentrations; however, PBL height (PBLH) in the stable atmosphere remains poorly understood. In particular, the assessment of uncertainties related to nocturnal PBLH (nPBLH) is challenging due to the absence of stable atmosphere observations. In this study, we explored nPBLH–PM2.5 interactions by comparing model results and observations during the Korea–United States Air Quality Study (KORUS-AQ) campaign (1–31 May 2016). Remote sensing measurements (e.g., aerosol and wind Doppler lidar) and on-line WRF-Chem modeling results were used by applying three different PBL parameterizations: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), and Asymmetrical Convective Model v2 (ACM2). Our results indicated that the uncertainties of PBLH–PM interactions were not large in daytime, whereas the uncertainties of nPBLH–PM2.5 interactions were significant. All WRF-Chem experiments showed a clear tendency to underestimate nighttime nPBLH by a factor of ~3 compared with observations, and shallow nPBLH clearly led to extremely high PM2.5 peaks during the night. These uncertainties associated with nPBLH and nPBLH–PM2.5 simulations suggest that PM2.5 peaks predicted from nighttime or next-morning nPBLH simulations should be interpreted with caution. Additionally, we discuss uncertainties among PBL parameterization schemes in relation to PM2.5 simulations.

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2020R1I1A2075417) and funded by the Korean government(MSIT)(NRF-2022R1A2C1008132).

Development and Assessment of Lightning Data Assimilation in a Grid-scale Microphysical Scheme

Daiwen Kang (1), Robert Gilliam (1), Kiran Alapaty (1), Alan Vette (1), Xiaoliang Song (2), Guang Zhang (2), Wei Wang (3), Nicholas Heath (4)

(1) United States Environmental Protection Agency, Research Triangle Park, North Carolina, (2) Scripps Institute of Oceanography, San Diego, California, (3) National Center for Atmospheric Research, Boulder, Colorado, (4) Heath Consulting, Satellite Beach, Florida

Measurement data for lightning flashes are available at global and continental scales from ground-based lightning detection networks. Using such data, a Lightning Data Assimilation (LDA) technique has been implemented previously using the Kain-Fritsch (KF) cumulus scheme to improve subgrid-scale precipitation simulations in the Weather Research and Forecasting (WRF) model for medium-to-low grid resolutions (>=12 km horizontal grid resolutions). For high-resolution simulations (=< 4 km grid spacing) when a scale aware cumulus parameterization (CP) scheme is not used, model precipitation is then solely dependent on a grid-scale microphysical (GMP) scheme. In this study, we developed, implemented, and tested an LDA technique using the Morrison GMP scheme to alleviate common issues associated with GMP schemes.

A cloud parcel model was implemented within the Morrison GMP scheme to estimate lifting condensation level (LCL), equilibrium level (EL), and convective available potential energy that includes entrainment (eCAPE) of environmental air. For each grid column when a lightning flash is detected, we nudge the water vapor mixing ratio towards saturation (with respect to water and ice) for all layers between the LCL and EL with a relaxation timescale of 30 minutes when saturation is less than 0.9. To avoid grid-scale storms associated with GMP schemes, we implemented a method that introduces an eCAPE factor to modulate moisture nudging. This way, all types of cumulus clouds, which stabilize the atmosphere due to both strong and weak large-scale advection, are well represented. Thus, the eCAPE factor helps to capture both weak and strong precipitation events realistically. Furthermore, for air columns where lightning flashes were not observed, we nudge the air mixing ratio towards saturation (if it is < 0.9) when eCAPE >100 m2/s2. However, since eCAPE can potentially exist for most of the days during warmer periods and to avoid generation of spurious precipitation, we implemented a convection trigger into the GMP scheme (similar to that available in the KF scheme) to filter out non-convective air columns irrespective of the magnitude of eCAPE.

Lightning flash data from the World-Wide Lightning Location Network (WWLLN) are used to improve Morrison GMP precipitation simulations. The daily precipitation from the Parameter-elevation Regressions on Independent Slopes Model (PRISM)’s high-resolution spatial climate data for the United States is employed to assess the impact of the LDA technique on the simulated precipitation fields from WRF simulations using 12, 4, and 1 km grid spacings, respectively. The impact of LDA on other meteorological variables, such as 2-m temperature and water vapor mixing ratio, will also be presented. This research also provides the impetus for implementing a scale-aware CP scheme directly into a GMP scheme.

Disclaimer: The views expressed in this paper are those of the authors and do not necessarily represent the view or policies of the U.S. Environmental Protection Agency.

EURO1k – a rapid refresh model for Europe

Johannes Rausch (1), Martin Fengler (1)

(1) Meteomatics AG, Switzerland

Accurate and precise weather forecasting is essential for a wide range of applications and industries, from agriculture to transportation to renewable energy. However, current weather models often struggle to represent the weather accurately due to limitations in spatial resolution. Global models with broad resolution are unable to represent small-scale weather features, such as convective thunderstorms or local wind patterns, while regional high resolution models are highly dependent on boundary conditions and typically provide forecasts for a small domain. To fill this gap, Meteomatics has developed the WRF-based EURO1k model, the first rapid refresh pan-European weather model with 1km resolution.

The EURO1k model is run on 4500x4500 grid 24 times per day, with a forecast horizon of 27 hours. It is based on the WRF (Weather Research and Forecasting) model and uses global ECMWF-IFS model data for boundary conditions.

In addition to standard data sources such as weather stations, radiosondes, weather radar and satellite data the EURO1k model also assimilates data from a network of Meteodrones, small unmanned aircraft systems (UAS) developed by Meteomatics which collect vertical atmospheric profiles up to 6000m in altitude. The high resolution of the EURO1k model allows it to accurately represent small-scale weather patterns, resulting in highly accurate and precise forecasts. This is evident in verifications against weather station observations, which show a very good agreement between model output and a range of weather variables including wind, temperature, and radiation. Statistical analyses of EURO1k model output against observations from all weather stations in Europe demonstrate better accuracy compared to other global and regional models. This has important implications for industry and the public. The EURO1k model can improve the forecasting of extreme weather events, allowing for better preparation and response. It can also enhance the prediction of renewable energy production, which depends on weather conditions. And, most importantly, it provides a more accurate and reliable weather forecast for communities across Europe. Overall, the EURO1k model represents a major advance in numerical weather prediction, bringing improved understanding and forecasting of the weather to a wide range of users.

Evaluation of MPAS-A microphysics and convection schemes for Hurricane Catarina (Brazil, 2004) simulations

Danilo Couto de Souza (1), Pedro Leite da Silva Dias (1), Ricardo de Camargo (1)

(1) Institute of Astronomy, Geophysics and Atmospheric Science, University of São Paulo, Brazil

Hurricane Catarina, the first recorded hurricane in the South Atlantic basin, remains a challenging event for atmospheric models due to inaccurate track and intensity representation in the oceanic region near Southern Brazil. In this study, we evaluate the performance of the MPAS-A model's microphysics and convection parameterization schemes to determine which set of options can better represent the atmospheric circulation related to the Catarina tropical transition and its subsequent development. We construct a global grid with 250 km grid spacing, which increases to 8 km in the study region, encompassing the time span between the Catarina genesis, tropical transition, and landfall. Two sets of experiments are performed: 48-hour simulations of all possible combinations of microphysics and convection schemes, and four-day extended simulations where sea surface temperature (SST) is updated every hour using the best-performing options from the first experiment. We evaluate the simulations using a score table matrix that includes the normalized root of square mean error (RMSE) for distinct atmospheric variables, such as the wind components u and v, wind speed, minimum pressure, distance of the simulated track from the estimated track, accumulated precipitation, and Lorenz Energetic Cycle (LEC) terms. The wind and LEC terms are compared to the ECMWF Reanalysis v5, the minimum pressure and track to the estimations by Cowan et al., (2006), and the precipitation to the Integrated Multi-satellitE Retrievals for GPM (IMERG). The best-performing options from the first experiment are thompson_ntiedtke, thompson_tiedtke, and wsm6_tiedtke, with thompson_ntiedtke showing the best results in the second experiment. These options accurately represent the system track during its tropical transition, although they show a positive bias in the minimum pressure. The simulated accumulated precipitation is slightly displaced southward but its main structure is represented by the simulations, despite being underestimated by approximately 50%. The LEC analysis indicates that the main limitations in the simulations are the zonal jet, with higher RMSE values in the terms related to zonal kinetic energy (energy content, conversion, boundary, budget, and residuals), and the eddy kinetic energy. The central minimum pressure is below the ERA5 value but still higher than that estimated by Cowan et al., (2006). The surface winds are better represented, with RMSE ranging from 2 to 2.5 m/s for both wind components and wind speed. Future experiments will couple the MPAS-A with the MPAS-O model for better representation of SST, which plays a major role in the system's intensification and explore the role of the boundary layer parameterizations.

Effect of single and double moment microphysics schemes and change in CCN, latent heating rate structure associated with severe convective system over Korean Peninsula

A Madhulatha (1,2), Jimy Dudhia (3)

(1) Korea Institute of Atmospheric Prediction Systems (KIAPS), Seoul, South Korea, (2) India Meteorological Department (IMD), New Delhi, India, (3) National Center for Atmospheric research, Colorado, USA

Cloud microphysics plays important role on the storm dynamics. To investigate the impact of advanced microphysics schemes, using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted for a severe convective system that formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation linked with the convective system are improved in WDM6. During developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with mixing ratio of hydrometeors (cloud, rain, graupel, snow and ice), number concentration of cloud and rainwater are also predicted in WDM6. To understand the differences in vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with Nr readily available in WDM6. Varied vertical distribution and large differences in rain number concentration, rain particle mass are evident between the schemes. Inclusion of number concentration of rain and cloud, CCN along with mixing ratio of different hydrometers have improved the storm morphology in WDM6. In order, to investigate the cloud-aerosol interactions, numerical simulation has been conducted using an increase in CCN (aerosol) in WDM6 which has shown an improved rainfall distribution with intense hydrometer distribution. The latent heating (LH) rates of different phase change processes (condensation, evaporation, freezing, melting, sublimation and deposition) are also computed using various transformation rate terms in the microphysics modules. It is inferred that the change in aerosol has increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution and subsequent rainfall.

EarthWorks for Weather

David Randall (1)

(1) Colorado State University, Fort Collins, Colorado

EarthWorks is a high-resolution, coupled, global storm-resolving Earth System Model, derived from CESM, and aimed at both weather and climate applications. The atmospheric dynamical core is MPAS-A. The atmosphere, ocean, and land surface share the same geodesic grid, which can be regionally refined. The target grid spacing is 3.75 km for all components. The target computational performance is half a simulated year per wall clock day by summer 2025, on a DOE leadership-class machine. I will give an update on recent progress, including presentation of some results.

Simulating the Water Cycle over the Third Pole Region - A Multi-Model, Multi-Physics Framework

Andreas F. Prein (1), Nikolina Ban (2), Tinghai Ou (7), Jianping Tang† Koichi Sakaguchi (3), Emily Collier (2), Sanjay Jayanarayanan (4), Lu Li (5), Stefan Sobolowski (5), Xingchao Chen (6), Xu Zhou (8), Hui-Wen Lai (7), Shiori Sugimoto (9), Liwei Zou (12), Shabeh ul Hasson (13), Marie Ekstrom (14), Praveen Kumar Pothapakula (16,17), Bodo Ahrens (16), Romilly Stuart (15,18), Hans Christian Steen-Larsen (15), Ruby Leung (3), Danijel Belusic (10), Julia Kukulies (7), Julia Curio (7), and Deliang Chen (7)

(1) MMM Laboratory, National Center for Atmospheric Research, (2) Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, (3) Pacific Northwest National Laboratory, (4) Centre for Climate Change Research, Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, (5) NORCE Norwegian Research Centre, Bjerknes Centre Climate Research, (6) Department of Meteorology and Atmospheric Science, and Center for Advanced Data Assimilation, (7) Department of Earth Sciences, University of Gothenburg, (8) National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resource Environment, Institute of Tibetan Plateau Research, (9) Japan Agency for Marine-Earth Science and Technology, (10) Swedish Meteorological and Hydrological Institute (SMHI), (11) Nanjing University (NJU), (12) Institute of Atmospheric Physics, Chinese Academy of Sciences, (13) HAREME Lab, Institute of Geography, Center for Earth System Research and Sustainability (CEN), Universit ̈at Hamburg, (14) Cardiff University, (15) University of Bergen, (16) Institute for Atmospheric and Environmental Sciences, Goethe University, (17) Now at: Karlsruhe Institute of Technology (KIT), (18) Laboratoire des Sciences du Climat et de l’Environnement

The Tibetan Plateau and its surrounding mountains have an average elevation of 4,400 m and a glaciated area of ~100,000 km2 giving it the name "Third Pole (TP) region". The TP is the headwater of many major rivers in Asia that provide fresh water to hundreds of millions of people. Climate change is altering the energy and water cycle of the TP at a record pace but the future of this region is highly uncertain due to major challenges in simulating weather and climate processes in this complex area. The Convection-Permitting Third Pole (CPTP) project is a Coordinated Regional Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) that aims to revolutionize our understanding of climate change impacts on the TP through ensemble-based, kilometer-scale climate modeling. Here we present the experimental design and first results from multi-model, multi-physics ensemble simulations of three case studies and simulations of the 2020 water year. The five participating modeling systems show high performance across a range of meteorological situations and are close to having ''observational quality'' in simulating precipitation and near-surface temperature. This is partly due to the large differences between observational datasets in this region, which are the leading source of uncertainty in model evaluations. However, a systematic cold bias above 2,000 m exists in most modeling systems. Model physics sensitivity tests performed with the Weather Research and Forecasting (WRF) model show that planetary boundary layer (PBL) physics and microphysics contribute equally to model uncertainties. Simulations with the Model for Prediction Across Scale (MPAS) are performing as well as the best WRF model physics configurations and we see benefits in using global MPAS configurations with a stretched grid over using the regional version of the model.

Physics Updates

Laura D. Fowler (1), Michael G. Duda (1), William C. Skamarock (1)

(1) National Center for Atmospheric Research, MMM Laboratory

We summarize updates implemented in MPAS-v8.0. Updates include corrections from earlier comparisons between regional MPAS and WRF forecasts over CONUS, and from recent WRF releases. We describe our ongoing implementation of shared physics between WRF and MPAS using the Common Community Physics Package (CCPP) framework. Finally, we list additional physics that will be made available over the summer of 2023.

Wind and humidity forecasts during downslope windstorm events

Robert Fovell (1)

(1) University at Albany

Many public utilities use in-house WRF simulations, in conjunction with publicly available operational products and weather information from the National Weather Service, to anticipate weather events and threats. Particularly in the western US, challenges include forecasting fire weather conditions, including winds and humidities associated with windstorms in complex terrain. These forecasts are used in making Public Safety Power Shutoff (PSPS) decisions: when and where to switch power off and when to re-energize power lines. As decisions need to be made on a station-by-station and circuit-by-circuit basis, careful verification of forecasts is necessary and an understanding of model strengths and biases is crucial.

This talk will focus on the assessment of WRF forecast skill during fire season in Southern California, where Santa Ana and Sundowner winds elevate the danger of wildfire. Of particular importance are sustained wind and dewpoint forecasts, as these factor directly and indirectly into indices used to assess the fire threat.

Facilitating Physics Interoperability in SIMA: Updates of CCPP SCM and Effort to Connect MMM Shared Physics with CCPP

Weiwei Li (1), Lulin Xue (1), Dustin Swale (2), Jimy Dudhia (3), Laura Fowler (4), Louisa Nance (1)

(1) Developmental Testbed Center and National Center for Atmospheric Research - RAL, (2) National Oceanic and Atmospheric Administration - OAR, GSL, (3) Developmental Testbed Center and National Center for Atmospheric Research - MMM, (4) National Center for Atmospheric Research - MMM

NCAR’s System for Integrated Modeling of the Atmosphere (SIMA) is in the process of adopting the Common Community Physics Package (CCPP) to provide functionality for interoperable physics. The Developmental Testbed Center (DTC) node at NCAR is expanding the capabilities in CCPP and its companion single-column model (CCPP SCM), and connecting the MMM Shared Physics (parameterizations sharable and operable across MPAS, WRF and CM1) to the CCPP Framework by using the CCPP SCM. In this presentation, we will introduce the new capabilities to be included in the next public release of the CCPP SCM, for example, “Replay” using output from a full model to create the CCPP SCM cases and the “CCPP Scheme Simulator” using data-driven tendencies to replace process schemes. These capabilities will enhance physics testing, evaluation and development when implementing and using the CCPP in a host model. In addition, we will present progress of a pilot project recently launched by the DTC of making the MPAS’ mesoscale_reference physics suite from the MMM Shared Physics technically and scientifically functional in the CCPP SCM. The team has connected the YSU planetary boundary layer (PBL) scheme from the MMM Shared Physics to the CCPP SCM, and initiated implementing the MM5 surface layer scheme. A series of testing and evaluation was conducted to ensure that the schemes work reasonably with the CCPP SCM. Using the Rapid Refresh physics suite in the CCPP as a code base, we investigated roles of surface conditions and clouds leading to differences between an older version of YSU PBL and the one from the MMM Shared Physics. Real cases driven by observation-constrained large-scale forcing were simulated and evaluated by comparing experiments with interactive and prescribed surface fluxes, and under cloudy and cloud-free conditions.

Development of a whole atmosphere model with the non-hydrostatic MPAS-A dynamical core

Soudeh Kamali (1), Hanli Liu (2), William Skamarock (3), Joseph Klemp (3), Peter Lauritzen (4), Francis Vitt (5)

(1) National Center for Atmospheric Research - ASP, (2) National Center for Atmospheric Research- HAO, (3) National Center for Atmospheric Research - MMM, (4) National Center for Atmospheric Research - CGD, (5) National Center for Atmospheric Research - ACOM

The need for ground-to-exosphere General Circulation Models (GCMs) were specified for the first time by Roble in 2000. These models, commonly known as the whole atmosphere models, are needed for a more accurate study of the relevant physical and chemical interactions, climate change, climate response to solar variability, space weather, and the interpretation of global observations. Two decades following the work of Roble, whole atmosphere modeling has developed into an active and fast-growing area of research. Currently, there is a strong push for representation of the lower atmosphere in space weather models of the upper atmosphere. Geospace applications require atmospheric models with tops in excess of 500 km, well into the upper thermosphere. In these regions the accuracy of the hydrostatic approximation becomes problematic. Hence, there is an increasing need for whole atmospheric models with non-hydrostatic dynamical cores.

The Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X), developed by the High Altitude Observatory (HAO) at NCAR, extends from the Earth surface to the exobase (~600 km). However, the dynamical cores used in current WACCM-X configurations (FV, SE) are based on the hydrostatic assumption. As part of the NCAR SIMA project, we have recently developed and tested the Specified Chemistry Whole Atmosphere Community Climate Model (SC-WACCM) with the non-hydrostatic Model for Prediction Across Scales-Atmosphere (MPAS-A) dynamical core. The mean zonal wind and temperature climatology from SC-WACCM/MPAS-A is compared with the results from SC-WACCM using finite volume and spectral elements dynamical cores. Gravity wave forcing (GWF) is a key driver of the wind and temperature structure in the middle atmosphere. Hence, GWF from these simulations are also compared.

Simulating New York City’s Urban Environment using WRF Urban Physics

Roger Turnau (1,2), Jon Pleim (2), Jerry Herwehe (2), Rob Gilliam (2), Walter Robinson (1)

(1) North Carolina State University, (2) Environmental Protection Agency

A number of high resolution urban simulations were performed on the New York City metropolitan area covering the warm season of 2018 using WRF version 4.2.2. Building data drawn from NYC’s Primary Land Use Tax Lot Output (PLUTO) database was added to the input file of the urban domain so the simulations would use a more realistic urban morphology. There are few land surface model (LSM) or planetary boundary layer (PBL) schemes currently coupled with the urban physics schemes, limiting the available choices. All three PBL schemes exhibited excessive vertical periodic oscillations at the urban domain resolution of 444m with MYJ being unusable, BouLac being marginally acceptable, and YSU performing best due to its non-local nature. Attempts to use the BEP urban physics scheme uncovered a very strong accumulating nighttime cold bias making it unsuitable for simulations longer than 5-7 days. However, the BEP-BEM scheme has performed well with both the Noah and Noah MP LSMs with regards to temperature with initial analysis showing Noah MP to be warm biased in the afternoon and Noah warm biased at night, with the mean biases being below 0.5K in both cases (RMSE under 2K). Both configurations have much weaker surface winds than observed, though adding a local climate zone (LCZ) map to Noah reduces that bias by about 0.5 m/s while also increasing the vertical oscillations. Upper air nudging was used in the three outer domains to keep the simulations, which were run consecutively using restart files, close to observations.

All-sky ATMS radiance data assimilation with JEDI-MPAS

Junmei Ban (1), Zhiquan(Jake) Liu (1), Jonathan J. Guerrette (2), Byoung-Joo Jung (1), Chris Snyder (1)

(1) National Center for Atmospheric Research - MMM, (2) Tomorrow.io

The all-sky radiances from the Advanced Technology Microwave Sounder (ATMS) are assimilated into JEDI-MPAS, data assimilation system for the Model for Prediction Across Scales – Atmosphere (MPAS-A) based upon the Joint Effort for Data assimilation Integration (JEDI). In JEDI-MPAS, mixing ratios of five hydrometeors (cloud liquid water, cloud ice, rain, snow, and graupel) are included as analysis variables when assimilating all-sky ATMS radiances using the Community Radiative Transfer Model (CRTM) as radiance observation operator and the WSM6 microphysics scheme. In addition, the situation-dependent observation error model is used in all-sky radiance assimilation. The impacts of assimilating all-sky ATMS radiances are evaluated by comparing to a benchmark month-long cycling experiment that assimilates conventional observation and clear-sky radiances from AMSU-A's temperature-sounding channels and MHS's water vapor channels. Positive impacts from ATMS radiance assimilation are seen for the 6-h background forecasts and free forecasts, especially for moisture, clouds, and precipitation fields.

WRFDA 4.5 and MPAS-JEDI 2.0 Update

Zhiquan (Jake) Liu (1)

(1) National Center for Atmospheric Research - MMM

WRF version 4.5 was released on 20 April 2023, which includes its data assimilation (DA) component WRFDA. There are two main new features in WRFDA-v4.5. One is the addition of a regularized version of WSM6 microphysics scheme and its tangent linear and adjoint code, which enables WRF-4DVar to analyses all five types of hydrometeors. The other is expanding the capability of assimilating Himawari-AHI satellite radiance data from clear-sky to all-sky approach. We will announce the version 2.0 of the new generation MPAS-JEDI data assimilation system, which will be ready before the workshop. Compared to MPAS-JEDI 1.0, computational efficiency is greatly improved in MPAS-JEDI 2.0. This allowed a successful cycling 3DEnVar data assimilation experiment on a global quasi-uniform resolution mesh at 7.5 km, an intermediate step towards global convection-permitting scale data assimilation using MPAS-JEDI. For ensemble data assimilation, an initial implementation of LETKF is included in MPAS-JEDI 2.0 in addition to the EDA method available in MPAS-JEDI 1.0. Cycling experiments’ results using global and regional MPAS-JEDI will be presented with high-resolution settings.

IBM GRAF - Global High-Resolution Atmospheric Forecast System: An Operational Update and Roadmap

Brett Wilt (1), James Cipriani (1), John Wong (1), David Heeps (1)

(1) The Weather Company

Since August 2018, The Weather Company (TWC), an IBM Business, has provided operational global numerical weather prediction solutions utilizing NCAR’s Model for Prediction Across Scales (MPAS) community model. While the primary focus of early implementation was to replace legacy Global Weather Research and Forecasting Model (GWRF) applications, IBM and UCAR embraced a collaboration opportunity in developing a next-generation high performance computing global model based on IBM’s POWER9 processor and NVIDIA Tesla V100 GPU acceleration.

As a result of the IBM-UCAR collaboration, the world’s first high-resolution, convective allowing, hourly-updating global weather forecast model was introduced by IBM in 2019 – marketed as IBM Global High-Resolution Atmospheric Forecasting System (GRAF). Using a customized MPAS variable-resolution global 15/3km hexagonal mesh of 24 million cells, GRAF provided hourly updating precipitation forecasts (5-minute temporal resolution) for TWC’s short-term weather forecast platforms and applications. In addition, an extended version of GRAF provided a 4x daily 72-hour forecast on a variable 15/4km mesh, with the higher resolution 4km refinement regions across CONUS and Europe. The extended GRAF solution became a foundational asset and tool across media applications, including widespread use throughout the broadcast television weather industry. As part of the overall GRAF research and development cycle, TWC leveraged weekly feedback from a diverse user group of broadcast meteorologists, as well as a proactive engagement of social media feedback. This not only empowered clients to directly contribute to the ongoing success of GRAF, but also resulted in key precipitation and temperature forecast skill improvements.

In 2022, planning and development commenced for the next-generation GRAF initiative for continued scientific investment, including a significant HPC expansion and unification of multiple GRAF applications. With an effective 2.5x increase in compute power, a new TWC weather prediction paradigm will be possible via a high-resolution, convective allowing, hourly-updating global 72-hour forecast. Data assimilation will be an integral component for this next-generation GRAF, with a focus on transitioning from a non-cycled GSI (Gridpoint Statistical Interpolation) approach to a fully cycled, rapidly updating JEDI (Joint Effort for Data assimilation Integration) implementation. The TWC JEDI development path will include an incremental progression from 3DVar, Hybrid 3D EnVar, to Hybrid 4D EnVar, using a wide range of observation datasets such as radar, satellite, aircraft, radiosondes, conventional, and TWC proprietary sources.

The presentation will provide an overview of GRAF HPC, mesh configuration, scalability challenges, model updates, forecast skill statistics, and a GRAF roadmap summary.

Progression of Data Assimilation for IBM GRAF: Towards a JEDI-Driven System

James Cipriani (1), John Wong (1), David Heeps (1), Brett Wilt (1)

(1) The Weather Company

Data assimilation (DA) is an integral component of any numerical weather prediction system, as it determines the optimal weight between the background (B) and observation (R) error covariances, characterizing the uncertainty in the analysis. This reduces analysis error and brings the initial conditions closer to reality. IBM has been continuously developing its DA capabilities, beginning with regional WRF implementations at IBM Research and The Weather Company (TWC).

The IBM Global high-Resolution Atmospheric Forecasting (GRAF) system has extended these capabilities to the Model for Prediction Across Scales (MPAS), the underlying unstructured- mesh model for all current and future operations. To date, the Grid-point Statistical Interpolation software has been utilized to assimilate surface weather observations (operationally) and radiosondes (experimentally) in a partially cycled 3D-variational approach. The analysis increments are computed on a Gaussian grid and interpolated back to a native MPAS mesh at 15/4-km. A cloud analysis utility has also been developed, which ingests site-specific radar reflectivity and operates directly on the mesh, after the DA.

The static B matrix was derived from 180 retrospective cold-start forecasts across a continuous 3-month period, initialized at 00Z and 12Z from the 0.25-degree GFS, 2.5-km global SST analyses, and daily updated NESDIS 4-km green vegetation fraction data. The resolution and duration of each forecast was 15/3-km and 36 hours, respectively. The output at 12- and 36- hours was used as input to the NMC method, to compute the perturbations for regression on a Gaussian grid.

Moving forward, GRAF is employing more advanced DA techniques using the JCSDA’s Joint Effort for Data assimilation Integration (JEDI) software. TWC’s objective is to develop a rapidly updating, fully cycled 3D/4D-EnVar capability with JEDI, driven by an in-house MPAS ensemble (EnKF/LETKF) and higher-resolution deterministic forecast. A summary of the ongoing JEDI work will be discussed, including updates to the static B matrix, observation conversions and priorities, and recent experiments. The latest GRAF roadmap/workflow will be outlined as well.

Applications of the New York State Mesonet with High-Resolution Numerical Weather Predictions Using WRF

Lloyd Treinish (1), Anthony Praino (1), Mukul Tewari (1)

(1) IBM Thomas J. Watson Research Center

To enable proactive decision making at a highly localized scale in applications ranging from emergency management, operations of electric and water utilities, agriculture, environmental impacts on water resources to transportation among others, IBM has deployed numerical weather prediction models for over two decades. An important element of this work has been the use of high-quality local observations for both data assimilation to reduce and quantify the errors in the initial state, and to assess the fidelity of the model results. This has included data from both public and private sources. The former has typically been conventional observations available from NOAA through its Meteorological Assimilation Data Ingest System (MADIS) facility. Private data have included those from weather stations operated by customers and collaborators as well as our own efforts with micronets as part of observing systems focused on lake watersheds in New York State (NYS). However, there typically remains a significant gap at the intermediate, mesoscale in most regions to utilize for such applications. The NYS Mesonet (NYSM) deployed and operated by the State University of New York at Albany was designed specifically to address that observational gap for that state.

Therefore, we have enabled automated utilization of near-real-time conventional observations from the NYSM for our operational execution of a customized version of the community WRF-ARW weather model in NYS. This includes configurations for the New York City (NYC) metropolitan area at 667m horizontal resolution as well as upstate lake watersheds at 333m horizontal resolution. The current work in NYC updates earlier versions of our work that commenced in 2000. We are also exploring the potential for high-resolution configurations for all of NYS.

We will illustrate the value of the NYSM data for the aforementioned applications appropriate for lake watersheds and others for the large, urbanized NYC area. This will include case studies for impactful events in the regions. Given that near-real-time data from the NYSM can illustrate the localized characteristics of extreme events, we also evaluate how such data can be used to assess and improve this model.

We will present overviews of the case study events, the approach to the modelling and the results to illustrate how this scale of modelling, which leverages data from a dense, regional mesonet, can provide improved guidance prior to such extreme events.

Using WRF to Simulate Environmental Forcing Conditions for a Southwest Asia Dust Storm

Kent H. Sparrow (1), Sandra L. LeGrand (1)

(1) U.S. Army Engineer Research and Development Center (ERDC), Geospatial Research Lab, Alexandria, VA

Dust aerosols often create hazardous air quality conditions that affect human health, visibility, agriculture, and communication. Accordingly, US Army researchers, collaborating agencies, and university partners are exploring novel methods for improving simulated dust entrainment patterns in WRF-Chem. When assessing the sensitivity of dust transport models to new dust emission treatments, correctly simulating the associated environmental forcing conditions is critical. Researchers must thoroughly evaluate the atmospheric and terrain parameters that feed into the dust emission and transport modules to effectively discern forcing condition errors from dust parameterization issues in WRF-Chem simulations.

This presentation summarizes an assessment of the WRF model to simulate atmospheric forcing conditions associated with a major dust event in Southwest Asia that occurred in July-August 2018. We compared WRF simulated parameters against surface observations, radiosonde data, and ERA5 reanalysis to assess the accuracy of the WRF-simulated synoptic evolution, storm progression, vertical profile, precipitation patterns, and surface wind fields. We also compared results from various WRF configurations to determine if altering the model settings could improve the surface wind simulation performance. Results from this effort will inform ongoing work to improve the dust emission component of WRF-Chem. However, we also encourage broader use of this assessment as a reference case study for dust transport, air quality modeling, remote sensing, soil erosion, and land management research applications.

Application of a satellite-retrieved sheltering parameterization for dust event simulation with WRF-Chem

Sandra L. LeGrand (1,2), Theodore W. Letcher (1), Gregory S. Okin (2), Nicholas P. Webb (3), Alex R. Gallagher (1), Saroj Dhital (3), Taylor S. Hodgdon (1), Nancy P. Ziegler (1), and Michelle L. Michaels (1)

(1) U.S. Army Engineer Research and Development Center (ERDC), (2) University of California Los Angeles, (3) United States Department of Agriculture - ARS

Roughness features (e.g., rocks, vegetation, furrows) that shelter or attenuate wind flow over the soil surface can considerably affect the magnitude and spatial distribution of sediment transport in active aeolian environments. Existing dust and sediment transport models often rely on vegetation attributes derived from static land use datasets or remotely sensed greenness indicators to incorporate sheltering effects on simulated particle mobilization. However, these overly simplistic approaches do not represent the three-dimensional nature or spatiotemporal changes of roughness element sheltering. They also ignore the sheltering contribution of non-vegetation roughness features and photosynthetically inactive (i.e., brown) vegetation common to dryland environments.

Here, we explore the use of a novel albedo-based sheltering parameterization in a dust transport modeling application of WRF-Chem. The albedo method estimates sheltering effects on surface wind friction speeds and dust entrainment from the shadows cast by subgrid-scale roughness elements. For this study, we applied the albedo-derived drag partition to the Air Force Weather Agency (AFWA) dust emission module and conducted a sensitivity study on simulated PM10 concentrations using the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model as implemented in WRF-Chem v4.1. Our analysis focused on a convective dust event case study from 3–4 July 2014 for the southwestern United States desert region discussed by other published works. Previous studies have found that WRF-Chem simulations grossly overestimated the dust transport associated with this event. Our results show that removing the default erodibility map and adding the drag parameterization to the AFWA dust module markedly improved the overall magnitude and spatial pattern of simulated dust conditions for this event. Simulated PM10 values near the leading edge of the storm substantially decreased in magnitude (e.g., maximum PM10 values were reduced from 17,151 to 8,539 μg m^-3), bringing the simulated results into alignment with the observed PM10 measurements. Furthermore, the addition of the drag partition restricted the erroneous widespread dust emission of the original model configuration. We also show that similar model improvements can be achieved by replacing the wind friction speed parameter in the original dust emission module with globally scaled surface wind speeds, suggesting that a well-tuned constant could be used as a substitute for the albedo-based product for short-duration simulations in which surface roughness is not expected to change and for landscapes wherein roughness is constant over years to months. Though this alternative scaling method requires less processing, knowing how to best tune the model winds a priori could be a considerable challenge. Overall, our results demonstrate how dust transport simulation and forecasting with the AFWA dust module can be improved in vegetated drylands by calculating the dust emission flux with surface wind friction speed from a drag partition treatment.

Convective Transport and Wet Scavenging of Aerosols in a Modeled and Observed SEAC4RS Case study

Ajay Parottil (1), Mary Barth (1), Gustavo Cuchiara (2), Jose Jimenez (3), Pedro Campuzano-Jost (3)

(1) National Center for Atmospheric Research, (2) Colorado State University, (3) University of Colorado

The in-depth understanding on aerosol convective transport and scavenging is important in determining the aerosol vertical distribution via deep convection and to learn how it modifies the upper tropospheric chemistry and composition. Several studies already quantified the trace gas wet removal for several storms during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) campaigns. We examine the vertical transport and scavenging of aerosols for midlatitude convective storms measured on 2 September 2013 during SEAC4RS campaign using Weather Research and Forecasting with chemistry (WRF-Chem) cloud scale and regional model simulations combined with aircraft measurements. The ability of the WRF-Chem model to represent convective storm and performance of chemistry simulation is discussed. The scavenging efficiency (SE) for different aerosol species are calculated via two methods and are compared with aircraft observations. The improvement in representing aerosol convective transport and scavenging by upgrading anthropogenic emissions is also investigated. The outcome of the study will give better insights on aerosol vertical transport and scavenging representation in a convective storm case.

A conditional object-based verification of MPAS medium-range forecasts

May Wong (1), Jimy Dudhia (1), Craig Schwartz (1), and Glen Romine (2)

(1) National Center for Atmospheric Research - MMM, (2) National Center for Atmospheric Research - DO

Accurate numerical weather prediction of severe convective weather events is critical in helping forecasters provide timely forecast guidance to the public. Although prediction skills in numerical weather prediction models have improved significantly over past decades, numerical forecasting of small-scale phenomena such as convection remains a challenge. In addition to the limited intrinsic predictability of these phenomena, model errors also play a role in the limited practical predictability of these events in medium-range forecasts, including the feedback of these errors on the predicted environment that may control subsequent convection initiation, sustenance and growth. Here we utilize an object-based verification technique to diagnose the relationship between the representation errors of small-scale convection and environmental forecast errors. This technique is based on the Method for Object-based Diagnostic Evaluation (MODE), available as a part of DTC’s Model Evaluation Tools (MET). Our verification stratifies large-scale forecast errors by precipitation frequency bias categories for a spring period in CONUS. We focus on two sets of global deterministic medium-range variable-resolution (15-3 km) forecasts with lead time out to 5.5 days using two versions of MPAS (V5.1 and V7.3). Representation of convection in MPAS over CONUS as diagnosed using MODE precipitation objects and how the errors in the representation relate to the environmental forecast errors will be discussed.

What’s new with the Multiscale Infrastructure for Chemistry and Aerosols (MUSICA) Development

Mary Barth (1), Matthew Dawson (2), Louisa Emmons (2), Gabriele Pfister (2), Kyle Shores (2), Francis Vitt (2), Doug Kinnison (2), and Simone Tilmes (2)

(1) National Center for Atmospheric Research - ACOM/MMM, (2) National Center for Atmospheric Research - ACOM

Accurate numerical weather prediction of severe convective weather events is critical in helping forecasters provide timely forecast guidance to the public. Although prediction skills in numerical weather prediction models have improved significantly over past decades, numerical forecasting of small-scale phenomena such as convection remains a challenge. In addition to the limited intrinsic predictability of these phenomena, model errors also play a role in the limited practical predictability of these events in medium-range forecasts, including the feedback of these errors on the predicted environment that may control subsequent convection initiation, sustenance and growth. Here we utilize an object-based verification technique to diagnose the relationship between the representation errors of small-scale convection and environmental forecast errors. This technique is based on the Method for Object-based Diagnostic Evaluation (MODE), available as a part of DTC’s Model Evaluation Tools (MET). Our verification stratifies large-scale forecast errors by precipitation frequency bias categories for a spring period in CONUS. We focus on two sets of global deterministic medium-range variable-resolution (15-3 km) forecasts with lead time out to 5.5 days using two versions of MPAS (V5.1 and V7.3). Representation of convection in MPAS over CONUS as diagnosed using MODE precipitation objects and how the errors in the representation relate to the environmental forecast errors will be discussed.

AceCAST GPU-Accelerated WRF Model Overview

Samuel Elliott (1), Jan Ising (1), Jarno Mielikainen (1), Christian Tanasescu (1)

(1) TempoQuest Inc.

Modern GPU-based HPC systems provide significant performance benefits over their traditional CPU-based counterparts. These systems are becoming much more prevalent within the HPC industry and as such it is extremely important that the computationally expensive weather and climate codes we develop are able to take advantage of the massive performance potential that these systems provide. AceCAST is a modified version of WRF developed with this sole purpose of enabling the model to run on modern GPU-based HPC systems. Here we provide a general description of the AceCAST software and demonstrate how AceCAST’s performance can be leveraged to significantly improve WRF users’ modeling capabilities. We also touch on a number of important topics such as development strategies and model validation.

Exploring MPAS Physics Suites to Simulate Tropical Convective Systems Consistently Across Scales

Koichi Sakaguchi (1), Tamaki Suematsu (2), Zhe Feng (1), Hiroaki Miura (3), Bryce Harrop (1), L. Ruby Leung (1), Bill Skamarock (4), Michael Duda (4)

(1) Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, United States, (2) RIKEN Center for Computational Science, Japan, (3) Graduate School of Science, The University of Tokyo, Japan, (4) Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, United States

The tropical hydrological cycle affects more than 3 billions of people and drives the general circulations, being a critical component for our predictive understanding of the changing climate. However, predicting its time evolution is challenging due to a wide range of scales involved, from individual convective cells to the Madden-Julian Oscillation (MJO). As such, a global model with convection-permitting resolution is a suitable approach, although simulated convective systems are sensitive to model representations of yet unresolved turbulent mixing and cloud microphysics, among others. Our previous work showed pronounced sensitivities of simulated MJO to several tunable parameters in the Nonhydrostatic Icosahedral Atmosphere Model (NICAM) model at convection-permitting resolution.

Exploring how best we can simulate the tropical hydrological cycle with the Model for Prediction Across Scales (MPAS) model, hindcast experiments are conducted for an MJO event in December 2018 on a 9-36 km variable-resolution tropical-channel mesh. Three configurations for deep convection are tested: scale-aware Grell-Freitas (GF), New Tiedtke (NT), and no cumulus parameterization(noCu). We are also porting "MJO tuning" for the NICAM model to the corresponding microphysics parameters in MPAS's Thompson scheme. MJO diagnostics are combined with objective tracking of Mesoscale Convective Systems (MCSs) to test a hypothesis that a model that realistically simulates MCSs would also reproduce observed MJO characteristics (and other convectively coupled equatorial waves), based on the idea of MCSs being a prototype for tropical waves at larger scales.

The GF and noCu simulations show reasonable skills in producing MCSs, although the number of MCSs are underestimated. With the NT scheme, significantly fewer MCSs are simulated, most of them being tied to land masses such as the Maritime Continents. On the other hand, the NT scheme can produce an MJO-like eastward propagation of cloud systems (outgoing longwave radiation (OLR)) while such an anomaly is weaker in noCU and lacking with the GF scheme. Propagation speed of OLR anomalies and associated zonal wind fields are not well captured by any configurations, resulting in poorly simulated trajectories of the Real-time Multivariate MJO indices. Initial attempt of MJO tuning enables MPAS with GF to create east-ward propagating systems, but not originating from the Indian Ocean as observed. In fact, the tuning leads to unrealistically large MCSs in the first several days of the hindcast, leaving an unrealistic large-scale environment for subsequent convection. Further MPAS tuning and analyses are ongoing to answer the above hypothesis and gain insights on how different scales are coupled in the MPAS and NICAM models.

The Weather Research and Forecasting Model Special Interest Group (WRF-SIG) at the National Energy Research Scientific Computing Center (NERSC)

Koichi Sakaguchi (1), Steve Leak (2), Yun He (2), Xiaodong Chen (3), Zanhua Huang (4), Man-Yau Chan (5)

(1) Pacific Northwest National Laboratory/NERSC User Group Executive Committee, United States, (2) User Engagement Group, National Energy Research Scientific Computing Center, United States, (3) Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, United States, (4) Department of Computer Science, Northwestern University, United States, (5) Advanced Study Program , National Center for Atmospheric Research, United States

We have formed a user group for the Weather Research and Forecasting Model (WRF) at the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility. NERSC supports a wide range of disciplines including biosciences, material sciences, chemical sciences, high energy physics, and environmental sciences. WRF is among the most popular applications at NERSC (34th in 2018 workload analysis), suggesting that a number of NERSC users can benefit from sharing data and information related to WRF. In particular, the highly heterogeneous High Performance Computing (HPC) environment often requires system-specific solutions and best practices for using WRF, which is difficult to be covered by the generic user guide. To overcome such challenges, our WRF Special Interest Group (WRF-SIG) at NERSC has made several community-based efforts. We have quasi-regular virtual meetings to discuss technical issues and best practices using WRF on NERSC systems. We have opened a slack channel to facilitate communication among members and constructed a dedicated website for WRF SIG as a part of the official NERSC documentation (https://docs.nersc.gov/applications/wrf/). A small allocation has been awarded for WRF-SIG, allowing the members to benchmark WRF on NERSC systems, to share publicly available data and scripts on the project space, and to view support tickets submitted by other members. The group is still in its infancy but we have already seen the above-mentioned activities help solving and preventing common technical problems for users, and promote communication among the members and the NERSC User Engagement team. Our experience suggests that a similar, HPC-center-based user group can be a helpful community hub for WRF users. We plan to further encourage communication and information sharing as part of the recent efforts to build a stronger NERSC user community.

Incoming land surface data quality in high-resolution urban climate simulations and the improvement ideas in physics equations

Pater Li (1), Bingcheng Wan (2)

(1) Arup, Hong Kong SAR, 999077, China, (2) Nanjing University of Information Science and Technology, Nanjing, 211544, China

Growing computational power in recent years enabled high-resolution urban climate simulations using limited-area models to flourish. This trend empowered us to deepen our understanding of urban-scale climatology with much finer spatial-temporal details. However, these high-resolution models would also be particularly sensitive to model uncertainties, especially in urbanizing cities where natural surface texture is changed artificially into impervious surfaces with extreme rapidity. These artificial changes always lead to dramatic changes in the land surface process. While models capturing detailed meteorological processes are being refined continuously, the input data quality has been the primary source of biases in modeling results but has received inadequate attention. To address this issue, we first examine the quality of the incoming static data in two cities in China, i.e., Shenzhen and Hong Kong SAR, provided by the WRF ARW model, a widely applied state-of-the-art mesoscale numerical weather simulation model. Shenzhen was going through an unprecedented urbanization process in the past thirty years, and Hong Kong SAR is another well-urbanized city. A considerable proportion of the incoming data is outdated, highlighting the necessity of conducting incoming data quality control in the region of Shenzhen and Hong Kong SAR. Then, we proposed a sophisticated methodology to develop a high-resolution land surface dataset in this region. We conducted urban climate simulations in this region using both the developed land surface dataset and the original dataset utilizing the WRF ARW model coupled with Noah LSM/SLUCM and evaluated the performance of modeling results. The performance of modeling results using the developed high-resolution urban land surface datasets is significantly improved compared to modeling results using the original land surface dataset in this region. This result demonstrates the necessity and effectiveness of the proposed methodology. Our results provide evidence on the effects of incoming land surface data quality on the accuracy of high-resolution urban climate simulations and emphasize the importance of the incoming data quality control. To take a further step, we proposed some improvement ideas to the physics equations in Noah LSM/SLUCM model. Besides, we also found some errors shipped in the codes of Noah LSM/SLUCM model.

WRF-Chem v4.5: updates, applications, and future plans

Jordan Schnell (1)

(1) Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, NOAA/Global Systems Laboratory, Boulder, CO, USA.

The chemistry component of the Weather Research and Forecasting model (WRF-Chem) has been updated to version 4.5. This presentation will highlight recent updates to the model, applications where the WRF-Chem model is being used - both experimentally and operationally, and discuss the future of atmospheric chemistry modeling as it relates to WRF-Chem and its support.

MPAS Updates

Bill Skamarock (1), Michael Duda (1), Laura Fowler (1)

(1) National Center for Atmospheric Research - MMM

We will present an overview of the updates in the latest MPAS release.

Evaluations of three regional MPAS configurations for severe weather forecasting applications during the 2023 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment

Adam Clark, Kent Knopfmeier, Yunheng Wang, Larissa Reames, Israel Jirak, Louis Wicker, Pamela Heinselman, David Dowell, Craig Schwartz, Michael Duda, William Skamarock, and Patrick Burke

The Warn-on-Forecast initiative at the National Severe Storms Laboratory aims to extend warning lead times for severe weather hazards using an on-demand, adaptable domain and a rapidly updating high-resolution ensemble analysis and forecast system that assimilates radar, satellite, and other observations every 15 minutes. The current prototype of this model, the Warn-on-Forecast System (or WoFS), uses the Advanced Research WRF (ARW) configuration of the Weather Research and Forecasting model. However, NSSL has begun exploring alternative model cores for a next-generation version of WoFS that would accommodate both further refinements in grid-spacing (i.e., ≤ 1-km) and advancements in data assimilation. Tests with the Finite Volume Cubed Sphere model (FV3) consistently yielded spurious storms at model initialization, inability to recover from early imbalances, and unrealistic storm characteristics. Additionally, it may be overly laborious to adapt FV3 for rapid data assimilation on regional domains. Thus, in collaboration with NCAR, NSSL has begun to explore the Model for Prediction Across Scales (MPAS) for its next-generation WoFS.

The first step of this exploration is testing MPAS at “Day 1” lead times (i.e., 12-36h forecasts) to assess performance characteristics relative to the current operational baseline of the ARW-based High-Resolution Rapid Refresh (HRRR) model, as well as the Rapid Refresh Forecast System (RRFS), which is an FV3-based system tentatively scheduled to replace the HRRR in 2024. For these tests, three CONUS-domain, 3-km grid-spacing MPAS configurations were developed at NSSL: (1) MPAS HT, (2) MPAS HN, and (3) MPAS RT. In these names, the last two letters denote the initialization dataset and microphysics scheme, respectively. “HT” is HRRR/Thompson, “HN” is HRRR/NSSL, and “RT” is RRFS/Thompson. All three configurations use the MYNN boundary layer parameterization, RUC land surface model, and RRTMG short and long wave radiation. These configurations will run in real time during the 5-week (1 May – 2 June) 2023 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment, and daily model evaluation activities will assess their performance characteristics alongside the HRRR, RRFS, and other experimental systems. The results from these evaluations will be critical for informing the next steps in the development of a next-generation WoFS. This talk will present preliminary results from these evaluations and highlight notable cases of interest.

Efforts to balance the potential vorticity budget in MPAS

Manda Chasteen (1), May Wong (1)

(1) National Center for Atmospheric Research - MMM

MPAS currently contains a diagnostics package to compute Ertel’s potential vorticity (PV) and PV tendencies from various model dynamical and physical processes. These PV tendencies are computed using potential temperature tendencies from longwave and shortwave radiation, planetary boundary layer (PBL), cumulus, and microphysics parameterization schemes (i.e., diabatic PV tendencies), and momentum tendencies from PBL and cumulus schemes (i.e., frictional PV tendencies). Potential temperature and wind tendencies from explicit horizontal mixing are also included. These tendencies can be used alongside PV advection terms, which are not currently calculated in the available MPAS releases, to compute the PV budget, in which the summed tendency and advection contributions multiplied by the timestep would equal the PV change over a given timestep in the case of a balanced budget. However, the PV budget in current MPAS releases does not balance, and the residual values are often significant relative to the background PV values.

In this presentation, we discuss our efforts to balance the PV budget in MPAS. These efforts include making considerable modifications and corrections to the PV diagnostics code, including a reformulation of the computation of horizontal gradients on the native MPAS mesh, the inclusion of variables from the beginning of the timestep in the calculations of PV tendency terms, and the introduction of an inline calculation of the PV tendency term due to advection by computing the change in PV before and after the dynamics step. Additionally, we have incorporated individual microphysics process terms into the Thompson scheme such that the diabatic PV tendency from microphysics can be partitioned into contributions from the net condensation/evaporation of cloud droplets, evaporation of raindrops, net deposition/sublimation of ice particles, melting, and freezing.

Daily MPAS Convection-Allowing Forecasts at NSSL

Kent Knopfmeier (1,2), David Dowell (3), Yunheng Wang (1,2), Larissa Reames (1,2), Adam Clark (2,4), Nusrat Yussouf (1,2,4), Louis Wicker (2,4)

(1) Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma, Norman, Oklahoma, (2) NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma, (3) NOAA/OAR/Global Systems Laboratory, Boulder, Colorado, (4) School of Meteorology, the University of Oklahoma, Norman, Oklahoma

In early 2023, NSSL initiated three daily runs of the MPAS (NSSL-MPAS) to assess its suitability as the next model core for the Warn-on-Forecast System (WoFS). The NSSL-MPAS runs utilize an identical physical parameterization suite aside from cloud microphysics (MP) and differ in their initial (ICs) and lateral boundary conditions (LBCs). Two runs employ the operational 0000 UTC HRRR analysis and forecast for ICs and LBCs, with one using the Thompson MP scheme and the other using the NSSL 2-moment MP scheme. The third run employs the experimental, deterministic 0000 UTC Rapid Refresh Forecast System (RRFS) analysis and forecast for its ICs and LBCs and uses the Thompson MP scheme. This configuration was chosen to allow effective comparison between current and future operational convection-allowing models (CAMs).

The NSSL-MPAS runs are visualized on the NSSL-CAMs website (cams.nssl.noaa.gov) with a diverse set of fields ranging from the synoptic to the mesoscale. Subjective comparisons of composite reflectivity, hourly-max updraft, surface-based CAPE, 2-m temperature, and 2-m dewpoint between the runs and current operational and experimental CAMs can be viewed at cams.nssl.noaa.gov/comparisons. Examples from high-impact severe weather days during the 2023 Hazardous Weather Testbed - Spring Forecasting Experiment (HWT-SFE) period will be highlighted. Objective verification of the NSSL-MPAS runs is being completed in real time using the Model Analysis Tools Suite (MATS) developed by the Global Systems Laboratory and preliminary results from the 2023 HWT-SFE period will be presented.

Development of the CONUS NSSL Regional MPAS Forecast System/NOAA National Severe Storms Laboratory

Larissa Reames (1,2), Yunheng Wang (1,2), Adam Clark (2), Michael Duda (3), Kent Knopfmeier (1,2), Ted Mansell (2), Corey Potvin (2), Bill Skamarock (3), Lou Wicker (2), Nusrat Yussouf (1,2)

(1) Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma, Norman, Oklahoma, (2) NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma, (3) National Center for Atmospheric Research - MMM

As the first step to develop a MPAS– based Warn-on-Forecast System (WoFS), NSSL has developed a real-time regional high-resolution (3 km) MPAS forecast system over the CONUS domain. The current NSSL MPAS-based forecast system includes three configurations: the MPAS-HT-NSSL initialized from the HRRR using Thompson microphysics; the MPAS-RT-NSSL initialized from the experimental RRFS using Thompson microphysics; and the MPAS-HN-NSSL initialized from the HRRR using NSSL two-moment microphysics. In support of this effort, several additions and improvements have been made to MPAS capabilities, including support for initialization from data on regional lambert conformal grids (i.e., HRRR), inclusion of microphysics tracers on the lateral boundaries, and the addition of the RUC land surface model (LSM) and the NSSL 2/3 moment microphysics scheme. To drive and monitor the MPAS real time workflow, we have developed a set of shell and python scripts that run on various platforms including NOAA Jet, NCAR Cheyenne and a local NSSL computer. Additionally, a post-processing tool, MPASSIT, has been developed to project MPAS data onto regular grids in a format that is compatible with the Unified Post Processing system. We’ll discuss all of these capabilities, as well as share some of the problems (and their solutions) that we encountered along the way in hopes of helping community members avoid these issues themselves. We’ll also discuss any remaining issues along with plans for future development.

Adding MPAS to the Convective-Scale Model Test Suite

Louis Wicker (1)

(1) NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

Over the past several years the regional version of the Unified Forecast System (UFS) has been continuously under development by a number of institutions (NSSL, GSL, EMC) resulting in rapid advancement and improvements in its forecasting performance. During the warm season, however, the depiction of individual convective storms and their characteristics have shown some noticeable differences in spatial structure as well as excessive precipitation rates than in the current operational convective allowing models (e.g., the WRF-based HRRR model).

These issues have resulted in the development of a new set of convective storm tests for CAMS to help benchmark what the expected shapes, sizes, and intensities for a variety of convective storms and systems. While the original UFS system was tested with a single supercell case where updraft maximum and precipitation were examined, a much wider range of environments are used to provide enough statistics to robustly assess the character of individual updrafts and convective systems. Much of the testing is done using homogeneous environments that are know to generate squall lines to provide statistics from 10s to 100's of updrafts over a 6 hour period. The initial work shows that even state-of-the-art non-hydrostatic research models (e.g., NCAR’s WRF and CM1 cloud models) generate a spectrum of solutions despite using nearly identical physics and initial conditions.

This talk will extend the current analysis by adding the MPAS dynamical core to the current results. The results will be added to the statistics from running a number of squall line environments. Currently, CM1, WRF, FV3 (solo-core) have been run using 5 different CAPEs and 3 different vertical shears (all generating squall lines). The focus will be on the intensity and depth of updrafts within convection as well as precipitation statistics.

In the longer term, the results from this testing suite will be made available online for other modeling groups to use to help compare and/or tune their CAM systems.

Understanding the Drivers of Connected Extreme Precipitation Events

James M. Done (1), Ming Ge (1), Erin Towler (1), Danielle Touma (1), Daniel L. Swain (1,2,3), Jennie Bukowski (4), Manuela Brunner (5,6)

(1) National Center for Atmospheric Research, Boulder, CO, (2) Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, (3) The Nature Conservancy of California, San Francisco, CA, (4) Colorado State University, Fort Collins, CO, (5) Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland, (6) Institute for Snow and Avalanche Research SLF, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Davos, Switzerland

We explore the processes driving the clustering of extreme precipitation events on US regional and seasonal scales. We present results from a pair of 30-year historical MPAS global simulations designed to explore the dominant scales driving clustering of extreme precipitation events. One simulation uses a global variable resolution mesh that refines down from 90 km to 25 km over the US. The other uses a global 120 km uniform mesh that suppresses the explicit representation of processes on scales smaller than a few 100 km.

We first construct datasets of extreme precipitation objects in the pair of MPAS simulations and ERA5 reanalysis. We then apply a metric of clustering to each dataset. We find clustering to be ubiquitous across climate regions of the US and seasons. But the strength of the clustering varies. Clustering on the fine resolution mesh compares reasonably well with clustering in ERA5, and is far stronger than clustering on coarse resolution mesh. This suggests clustering is a multi-scale process. Current work is delving into the contributing processes.

Atmospheric River: The Cause of extreme precipitation over Eastern India in 2019

C. N Prabhu (1), A K Mishra (1), Narasimha Rao (1), Rajesh Kumar (2), Avinash Chauhan (1), Vikram Kumar (1)

(1) Bihar Mausam Seva Kendra, Department of Planning and Development, Government of Bihar, India, (2) National Centre for Atmospheric Research, Boulder, Colorado, USA

High resolution WRF model simulations were conducted for deciphering the atmospheric phenomenon and for identifying the triggering factor for an extremely heavy precipitation (rainfall > 204 .5 mm per day) event that occurred over Bihar and adjoining states in eastern India in September 2019. Events of extremely heavy rainfall in several locations in Bihar and adjoining states like Uttara Pradesh, Jharkhand Odisha etc, caused floods and inundations. Patna City, the capital of Bihar was among the worst affected.

ERA-5 data, the latest fifth-generation reanalysis global atmosphere dataset, from ECMWF, was used to drive the WRF model. ERA5 has been recognized as one of the best datasets for climate analysis due to its high spatial resolution and accuracy (Pattanaik et al., 2019). Three different model sensitivity simulations were performed. The model output was validated with rainfall data collected through the network of rain gauges spread across Bihar.

A strong correlation is observed between the model simulation results and the recorded rainfall data, with a correlation coefficient > 0.8. It was also evident that the delayed onset of Southwest Monsoon and high Indian Ocean Dipole (IOD) conditions (Kumar et al., 2020) were the triggering factors for the extremely heavy rainfall in several locations in eastern India.

A critical analysis of WRF output shows the presence of an Atmospheric River, that brought moisture from the Arabian Sea branch of the Monsoon and contributed significantly to the precipitation over the region.

Apart from the conventional usage of WRF model for weather forecasting, this study underscores the advantages of employing high-resolution hindcast WRF model simulations to investigate extreme weather events and estimate the potential impact. However, focusing on improving the accuracy of parameterization is highly essential for further improving the model accuracy.

Foreseeing the emergence of Atmospheric Rivers with enough lead-time, through WRF simulations, will greatly help in effective flood management and minimising the probable life and infrastructure losses.

Verifying and Comparing Forecasts of the HRRR, RRFS, and NSSL MPAS Models

Corey Potvin (1), Larissa Reames (1,2), Lou Wicker (1), Adam Clark (1), David Dowell (3), Michael Duda (4), Thomas Jones (1,2), Kent Knopfmeier (1,2), Ted Mansell (1), Bill Skamarock (4), Yunheng Wang (1,2), Nusrat Yussouf (1,2)

(1) NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma, (2) Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma, Norman, Oklahoma, (3) NOAA/OAR/Global Systems Laboratory, Boulder, Colorado, (4) National Center for Atmospheric Research, Boulder, Colorado

NSSL is exploring the suitability of the NCAR Model Prediction Across Scales - Atmosphere (MPAS-A; hereafter, simply “MPAS”) as the next-generation dynamical core in the NSSL Warn-on-Forecast System (WoFS). To assess strengths and weaknesses of MPAS relative to the existing WoFS dynamical core – the Advanced Research version of the Weather Research and Forecasting model (ARW) – and the UFS-based Finite-Volume Cubed-Sphere model (FV3), we are comparing forecast output among five deterministic models: the ARW-based High-Resolution Rapid Refresh (HRRR); EMC’s deterministic, CONUS-domain prototype of the FV3-based Rapid Refresh Forecast System (RRFS) that is tentatively scheduled to replace the HRRR and several other mesoscale model systems in 2024; and three regional MPAS models developed and run by NSSL. The three MPAS models differ only in their initializations and microphysics schemes: the MPAS-HT-NSSL is initialized from the HRRR and uses the Thompson scheme; the MPAS-RT-NSSL is initialized from the RRFS and uses the Thompson scheme; and the MPAS-HN-NSSL is initialized from the HRRR and uses the NSSL two-moment scheme. Comparing the MPAS-HN-NSSL and MPAS-HT-NSSL will allow us to test our hypothesis that the NSSL two-moment microphysics produces better thunderstorm forecasts in the MPAS, as it does in the ARW-based WoFS. Comparing the MPAS-RT-NSSL and RRFS, and the MPAS-HT-NSSL and HRRR, will illuminate the systematic impacts of the different dynamical cores given the similarity of the physics packages used in the models.

The project team is using a variety of methods to compare storm characteristics and forecast performance of the five models. These include probability-matched composite means to visualize systematic differences in storms and near-storm environments; vertical velocity and kinetic energy spectra to estimate model effective resolution; and object-based methods to measure storm attributes and their relationships to environmental parameters. Early results will be presented at the workshop.

A high resolution (3 km) MPAS ensemble for realtime 5-day convective forecasting

Morris Weisman (1), Craig Schwartz (1), Dave Ahijevych (1), Ryan Sobash (1)

(1) National Center for Atmospheric Research - MMM

A 5-member, variable-resolution global MPAS ensemble with ~3-km horizontal cell spacing over the CONUS was run as part of the NOAA's Hazardous Weather Testbed Spring Forecasting Experiment during May 2023 to test the capabilities of MPAS to offer probabilistic guidance for severe convective weather out to 5 days in advance. This talk will present preliminary subjective analyses from this exercise, emphasizing the capabilities of this system to represent the observed range of convective modes, and to characterize the severe weather potential over such multi-day periods.

Impact of stochastic boundary layer and microphysics perturbation under distinct weather regimes in convective-permitting resolution

I-Han Chen (1,2), Judith Berner (3), Christian Keil (1), Greg Thompson (2), Ying-Hwa (Bill) Kuo (2), George Craig (1)

(1) Meteorologisches Institut München, Ludwig-Maximilians-Universität München, Munich, Germany, NCAR/UCAR, (2) 2 University Corporation for Atmospheric Research, Boulder, CO, U.S.A., (3) National Center for Atmospheric Research, Boulder, CO, U.S.A.

Due to ever-increasing computing resources, current state-of-the art numerical weather prediction (NWP) models run at numerical resolutions of a few kilometers, which faded out the use of convective parameterization schemes that have been arguably the leading source of model-error in convection-parameterizing models. As we moved to kilometer scale, one fundamental question is "Which parameterized process dominate model uncertainties in convection-permitting models?". This study measures the impact of stochastic perturbation schemes in the planetary boundary layer (PBL) and microphysics processes. In particular, their impact for different weather types such as warm-season convection and winter storm. This study implemented the physically based stochastic perturbation (PSP) scheme, which was originally developed in the Consortium for Small-scale Modeling (COSMO) and Icosahedral Nonhydrostatic (ICON) models, into Weather Research and Forecasting (WRF) Mellor–Yamada–Nakanishi–Niino (MYNN) PBL scheme. The stochastic perturbation in Thompson aerosol-aware scheme (SPPMP) perturbs parameters including cloud droplet shape parameter, graupel and hail intercept parameters, vertical velocity for cloud condensation nuclei activation, and activation of ice nuclei concentration.

One central assumption of this study is that we aim to represent the sources of uncertainty with physically reasonable scales and amplitudes. Results from case studies indicate that boundary layer perturbations outweigh microphysics perturbation since it is able to alter precipitation timing and amplitude. Despite that, microphysics perturbation is helpful for winter storm and simulations initialized at nighttime since the scheme is more responsive to precipitation systems. Although the two schemes are designed with distinct theoretical basis, their impact are both modulated by moist processes and thus not fully orthogonal.

Project Raijin: Community Geoscience Analysis Tools for Unstructured Grids

Orhan Eroglu (1), John Clyne (1), Brian P. Medeiros (1), Colin Zarzycki (2), Cecile Hannay (1)

(1) National Center for Atmospheric Research, Boulder, Colorado - CISL, (2) Pennsylvania State University

Project Raijin has been awarded by the NSF EarthCube program in order to develop sustainable, community-owned tools for the analysis and visualization of unstructured grid model outputs arising from next generation climate and global weather models. The primary development environment for Project Raijin’s software tools is the Scientific Python Ecosystem. In particular, the Pangeo packages, Xarray, Dask, and Jupyter provide support for data ingestion and internal representation, scalability, and examples and demonstration, respectively. Two essential goals of Project Raijin are: (1) developing extensible, scalable, open source tools that are capable of operating directly (without regridding to structured grids) on unstructured grids at global storm resolving resolutions in order to support fundamental analysis and visualization methods; and (2) ensuring the long term sustainability of the project by establishing an active, vibrant community of user-contributors that share the ownership of the project and extend our work beyond the scope of this NSF award. This presentation will provide updates about what progress Project Raijin has made to support both of these goals, such as (1) creation of the brand new Python package, UXarray, to provide data analysis and visualization operators on various types of unstructured grids including MPAS, and (2) employment of an open development model to encourage community participation in all aspects of the project. We will provide our roadmap for future development and discuss how further community engagement could be possible.