Events (Upcoming & Past)

Upcoming MMM Seminars

Date Time Seminar TItle Presenter(s) Affiliation(s) Location
Aug 26, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Sep 2, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Sep 9, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Sep 16, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Sep 30, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Oct 7, 2021 (Thu) 3:30pm No seminar scheduled. Date is available. No seminar scheduled. Date is available. No seminar scheduled. Date is available.
Jun 16, 2022 (Thu) 3:30pm TBD (*MMM Distinguished Lecturer) *Dr. David Henderson James Cook University, Australia virtual

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Past MMM Events

MMM Seminar - Thursday, February 13, 2020 - 3:30pm

Speaker: Chris Riedel

Affiliation: University of Oklahoma

     In recent decades, the duration of skillful forecasts in global models has steadily increased in the mid-latitudes. Much of this improvement can be attributed to the development of higher resolution models, advances in data assimilation techniques, and – perhaps more importantly – growing understanding of physical processes associated with various atmospheric phenomena.  However, forecasts in polar regions are not experiencing an equivalent increase in skillful forecast duration even with these improvements.  The poles pose a unique modeling challenge that may perhaps be due to a relative dearth in the coverage of conventional observations, which places more weight on satellite remote sensing observations with higher uncertainty for forecast analyses and scientific studies. Additionally, atmospheric features are inherently smaller in the polar regions due to the Earth’s rotation, implying that higher resolution, more computationally expensive NWP model grids are needed to resolve features of equal geographic size in the midlatitudes.  Thus, understanding of key polar processes associated with polar weather features is only in its infancy and potentially not well-accounted for in current models. Recent studies highlight the influence polar regions can have on forecast skill in the mid-latitudes, which suggests improved understanding of key polar processes could help extend the current forecast barrier.

     In this study, we focus on a predominantly Arctic feature called a tropopause polar vortex (TPV), which are features that can persist for many days to months.   The location of TPVs on the tropopause and the known impacts that water vapor has on their growth and evolution leads to poor observational sampling and high forecast uncertainties associated with them. An overview and evaluation of a new research tool called Model for Prediction Across Scales (MPAS) with ensemble Kalman Filter data assimilation from the Data Assimilation Research Testbed (DART), or MPAS-DART configured for Arctic studies will be discussed.

     The ability of MPAS-DART to represent key characteristics of TPVs is investigated along with potential biases that might degrade TPVs in the cycling system. Using observations and analysis increments, initial evaluation of MPAS-DART suggests the existence of systematic model biases in the Arctic. We apply the mean initial tendency and analysis increment method to further quantify these systematic biases. This method provides a way to identify potential model errors associated with either model dynamics or physical parameterizations. A moisture bias is identified in the upper-troposphere lower-stratosphere region, which leads to increased cooling near the tropopause. Special dropsonde observations from the North Atlantic Waveguide and Downstream Impact Experiment are used in order to evaluate the impact of this identified systematic bias and help elucidate TPV forecast sensitivity to initial states.

Refreshments: 3:15 PM

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Monday, February 3, 2020 to Thursday, February 13, 2020
Calendar Timing: 
Thursday, February 13, 2020 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

MMM Seminar - Thursday, February 6, 2020 - 3:30pm

Speaker: Ian Bolliger

Affiliation: UC Berkeley

Hurricanes are one of the costliest natural disasters, imparting over $50 billion in losses per year in the U.S. alone. Because each event can cause significant immediate damage, as well as long-lasting negative impact, the resilience of coastal regions depends crucially on quantifying the present and future risk of hurricane-driven economic losses. In this study, we construct and apply an open-source, physical-econometric catastrophe model that directly simulates high-resolution storm surge and wind from >100,000 real and synthetic storm events, accounting for probabilistic local sea level rise. We merge this hazard model with a property sale price dataset for all U.S. properties and insurance claims data from historical storms to empirically derive a damage function for both of these hazards. We then project damages from 1980-2100 using seven climate models, two emissions scenarios, and 100 stochastic realizations of each hurricane season. We use the distribution of realized losses to quantify how hurricane risk has changed across the Atlantic and Gulf coastlines over the past 35 years and how it may change over the next century. Preliminary results suggest that the U.S. economic risk from hurricanes may have grown by as much as 100% relative to a 1980s baseline and may further grow another 300% by the end of the century, under RCP 8.5. These results have informed reports and regulation from Blackrock Investment Institute, the First Street Foundation, the American Flood Coalition, and the Bank of England, each of which seek to better account for changing hurricane patterns in assessing risk to their assets and/or population.

Refreshments: 3:15 PM

 

 

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Tuesday, January 28, 2020 to Thursday, February 6, 2020
Calendar Timing: 
Thursday, February 6, 2020 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

*MMM Seminar - Thursday, January 30, 2020 - 3:30pm

*Please note special location - FL2-1001/Small Auditorium

Speaker: Xiaoxu Tian

Affiliation: University of Maryland

A four-dimensional variational (4D-Var) vortex initialization (VI) system is developed for a nonhydrostatic axisymmetric numerical model with convection accounted for (the RE87 model). Derivations of the tangent linear and adjoint models of the RE87 model and the correctness checks are presented. As an initial evaluation of the 4D-Var VI system, a cost function that measures the model fit to satellite microwave retrievals of tropical cyclone (TC) warm-core temperatures and total precipitable water (TPW) from the following four polar-orbiting satellites within a slightly longer than 1-h assimilation window is minimized using the limited-memory quasi-Newton minimization algorithm: the Suomi National Polar-orbiting Partnership, NOAA-20, Fengyun-3D, and Global Change Observation Mission  – Water Satellite 1. An azimuthal spectral analysis in cylindrical coordinates centered on the TC centers shows that the warm core and TPW fields within TCs are dominated by the axisymmetric component. The 4D-Var VI results assimilating the axisymmetric component of the above satellite retrievals produced a significant reduction in the cost function and the norm of the gradient as the minimization process is completed. The gradient of the cost function is accurately computed by a single integration of the RE87 adjoint model. In the cases of Hurricane Florence and Typhoon Mangkhut, improved forecast of intensifications and more realistic vertical structures of all model state variables (e.g., temperature, water vapor mixing ratio, liquid water content mixing ratio, tangential and radial wind components, and vertical velocity) are obtained when compared with a parallel run initialized simply by the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis.

Refreshments: 3:15 PM

Building:
Room Number: 
*FL2-1001 Small Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Tuesday, January 14, 2020 to Thursday, January 30, 2020
Calendar Timing: 
Thursday, January 30, 2020 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

MMM Seminar - Thursday, January 23, 2020 - 3:30pm

Speaker: Forrest J. Masters

Affiliation: University of Florida

The presentation will offer a forward-looking perspective that the civil (wind) engineering and atmospheric science fields are poised to reverse this trend by leveraging recent advancements in automation, data fusion and machine learning, heterogenous computing, multi-modal sensing, and other technologies reinventing modalities for scientific research and technology transfer. To build that case, we will begin by exploring the evolution of field reconnaissance efforts in landfalling Atlantic tropical cyclones to characterize the intensity and structure of damaging winds and how it is has influenced complementary research in atmospheric boundary layer wind tunnels (BLWTs). Key highlights will include activities and findings originating from the Florida Coastal Monitoring Program (which has led field experiments in 34 storms, including Harvey, Michael, and Dorian) and the Digital Hurricane Consortium, which represents the broader community of landfall experimentalists that deploy anemometry, mobile doppler radars, and storm surge/wave sensors.

The presentation will then explore cyber physical wind engineering experiments conducted in the NSF Natural Hazards Engineering Research Infrastructure (NHERI) BLWT using its computer-controlled terrain generator (the “Terraformer”) and other exciting new technologies that are reinventing the conventional design-build-test paradigm. Examples will include mechatronic building modeling to optimize the design of wind sensitive structures and the development of a new 300+ fan system to simulate non-stationary and non-neutral flows for the study of bluff-body aerodynamics in unsteady winds, flows over geomorphically complex terrain, and internal boundary layer formations. All systems are available for use by NCAR. Information will be given about how to access these resources as well as the lab/field data.

The presentation will conclude with remarks about how these research activities interrelate with the rapid transformation now taking place at engineering campuses worldwide, which is being driven by the so-called 4th Industrial Revolution (i.e., the integration of artificial intelligence, robotics, and the internet of things into industry and mainstream life), reduced barriers to adopt technology, and the emergence of student bodies that are increasingly more prepared for living and working in a “digital” world than previous generations. The perceived ripple effect on atmospheric science will then be discussed from an engineering perspective, with the goal of identifying opportunities in a future where data streams are sufficiently rich and forecasting tools are sufficiently skilled that the role of the “human in the loop” is far diminished by today’s standards.

Refreshments: 3:15 PM

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Wednesday, January 8, 2020 to Thursday, January 23, 2020
Calendar Timing: 
Thursday, January 23, 2020 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

MMM Seminar - Thursday, January 9, 2020 - 3:30pm

Speaker: Naoki Ikegaya

Affiliation: Kyushu University, Japan

The momentum and scalar forcings via urban surfaces are one of the important factors to determine velocity and concentration fields within urban boundary layers. Surface fluxes are commonly modelled by the bulk transfer methods in which the drag force and scalar flux from the surface are parameterized by the bulk transfer coefficients and the differences in the quantity across the interface. However, the geometric and scale dependency of the bulk scalar transfer coefficients not well known. In this presentation, we discuss how we can consider the geometric and scale dependency of the bulk scalar transfer coefficients. To understand the geometric dependency, we performed a series of wind-tunnel experiments under neutral conditions and create a comprehensive database of the bulk scalar transfer coefficients using regular block arrays representing an urban environment. The various configurations of the block arrays allow us to determine influential factors for the bulk scalar transfer coefficients. In addition, we consider how we can apply the results from a laboratory work to an urban boundary layer a realistic scale by referring previous literatures dealing with the scale dependency of the bulk scalar transfer coefficient.

Refreshments: 3:15 PM

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Monday, December 23, 2019 to Thursday, January 9, 2020
Calendar Timing: 
Thursday, January 9, 2020 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

*MMM Seminar - Wednesday, January 8, 2020 - 3:30pm

*Please note special day - Wednesday

Speaker: Zhiquan (Jake) Liu

Affiliation: National Center for Atmospheric Research (NCAR)

Different from numerical weather prediction that is mainly an initial condition problem, the accuracy of air quality forecast relies on not only the initial state of a chemical model, but also the surface emissions of chemical constituents. The latter is to a large extent related to the human activities such as those from industrial, residential, and agricultural sectors and is subject to large uncertainties. In this talk, I will demonstrate both the usefulness and the limitations of data assimilation for chemical initial condition analysis and source emission estimation when using different data assimilation techniques and various combinations of different observations from satellite (e.g., aerosol optical depth) and ground observing networks (e.g., surface particulate matters and chemical gases). While it is demonstrated that data assimilation is overall very useful for improving the accuracy of chemical weather prediction, its limitations will also be shown, e.g., short-lasting impact and the lack of sufficient observations of chemical speciation to constrain the large number of model prognostic variables and emission parameters. A recent study on using data assimilation as a tool to separate the effects of weather condition change and emission control in recent trend of winter time air quality in China will also be presented before closing with future perspectives.

Refreshments: 3:15 PM

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Friday, December 20, 2019 to Wednesday, January 8, 2020
Calendar Timing: 
Wednesday, January 8, 2020 - 3:30pm to 4:30pm
Nancy
Kerner
8946

*Special RAL/MMM Joint Seminar - Thursday, December 5, 2019 - 3:00pm

*Please note special time - 3:00pm

Speaker: Dr. David L. Darmofal

Affiliation: Department of Aeronautics & Astronautics, Massachusetts Institute of Technology

For phenomenon that exhibit a wide range of scales, adaptive methods can enable efficient yet accurate discretizations.  In this talk, we consider the use of space-time adaptive methods to solve time-dependent, multi-scale phenomenon in which the space-time domain is discretized using simplices (i.e. pentatopes for 3D+time) that are not required to have face aligned with the temporal direction.  The adaptive method utilizes an goal-oriented approach in which an adjoint solution and dual-weighted residual is employed to estimate the local contribution to the discretization error of a desired output.  The dependence of the error estimate on the mesh is then synthesized into a model using the Metric Optimization through Error Sampling and Synthesis (MOESS) algorithm, and the resulting error model is then optimized to produce adapted meshes with minimal error at a fixed computational cost. We demonstrate this approach for higher-order finite element discretizations applied to convection-dominated flows and porous media.  Also, similar to parallel-in-time strategies, we show that parallel solution of space-time adapted meshes are more scalable than time-marching approaches.  We conclude with a discussion of remaining challenges and opportunities for space-time adaptive methods.

Refreshments: 2:45pm

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Tuesday, December 3, 2019 to Thursday, December 5, 2019
Calendar Timing: 
Thursday, December 5, 2019 - 3:00pm to 4:00pm
Nancy Sue
Kerner
8946

*MMM Seminar - Distinguished Speaker Series  - Tuesday, 3 December 2019 - 3:30pm *Please note special day - TUESDAY

Speaker: Chun-Chieh Wu

Affiliation: Department of Atmospheric Sciences, National Taiwan University

     This study examines the roles of surface heat fluxes, particularly in relation to the wind-induced surface heat exchange (WISHE) mechanism, in the (i) secondary eyewall formation (SEF) and (ii) rapid intensification (RI) of tropical cyclones.

     (i) To examine the sensitivity of SEF to the WISHE mechanism, the surface wind used for the calculation of surface heat fluxes is capped at several designated values and at different radial intervals.  When the heat fluxes are moderately suppressed around and outside the SEF region observed in the control experiment, sensitivity experiments show that the formation of the outer eyewall is delayed, and the intensity of both eyewalls is weaker.  When the heat fluxes are strongly suppressed in the same region, SEF does not occur.  In contrast, suppressing the surface heat fluxes in the storm’s inner-core region has limited effect on the evolution of the outer eyewall.  This study provides important physical insight into SEF, indicating that the WISHE mechanism plays a crucial role in SEF.

     (ii) Sensitivity experiments with capped surface fluxes and reduced WISHE exhibit delayed RI and weaker peak intensity, while WISHE could affect the evolutions of TC both before and after the onset of RI.  Before RI, more WISHE leads to faster increase of  in the lower levels, resulting in the eruption and the axisymmetrization of the convection (especially in the lower levels).  In addition, TCs in experiments with more WISHE reach a certain strength earlier, before the onset of RI.  During the RI period, more surface heat fluxes cause more efficient intensification in a TC, leading to a stronger peak intensity, more significant and deeper warm core in TC center, and the axisymmetrization of convection in the higher levels.  In both stages, different levels of WISHE alter the thermodynamic environment and convective-scale processes.  With WISHE, a consequent development in the convective activity is identified, resulting in a stronger secondary circulation and increased diabatic heating.  Within the inner-core region, deeper inflow increases the transport of angular momentum from the outer radii, leading to faster spin-up of the tangential circulation.  In all, the important role of the WISHE feedback in RI, both during the pre-RI stage and during the RI period, is highlighted.

Refreshments: 3:15 PM

   

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Monday, December 2, 2019 to Tuesday, December 3, 2019
Calendar Timing: 
Tuesday, December 3, 2019 - 3:30pm to 4:30pm
Nancy
Kerner
8946

*Special RAL/MMM Joint Seminar - Wednesday, November 20, 2019 - 3:30pm

*Please note special day - Wednesday

Speaker: Prasanth Prabhakaran

Affiliation: Michigan Technological University

The formation of ice in mixed-phase clouds greatly impacts Earth’s hydrologic cycle. The intensity, distribution, and frequency of precipitation as well as radiative properties of clouds in the mid-latitudes are strongly influenced by the number concentration of ice particles. A long-standing riddle in cold clouds is the frequent observation of measured ice particle concentrations several orders of magnitude higher than measured ice-nucleating particle concentrations. Here, we report laboratory observations of copious cloud droplets and ice crystals formed in the wake of a warm, falling water drop. Aerosols were activated in the transient regions of very high supersaturation due to evaporative mixing in the wake. We extend these results to typical mixed-phase atmospheric conditions, and our calculations show that the induced evaporative supersaturation may significantly enhance the activated ice nuclei concentration in the particle’s wake. 

Refreshments: 3:15 PM

 

Building:
Room Number: 
FL2-1022 - Large Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Monday, November 11, 2019 to Wednesday, November 20, 2019
Calendar Timing: 
Wednesday, November 20, 2019 - 3:30pm to 4:30pm
Nancy
Kerner
8946

*Special MMM/GTP Joint Seminar - Thursday, November 14, 2019 - 3:30pm

*Please note special location - FL2/1001 Small Auditorium

Speaker: Shaun Lovejoy

Affiliation: McGill University, MontréalQuébec

     A hundred years ago, Lewis Fry Richardson made the first numerical weather forecast, founding the field of numerical weather prediction (NWP).  Based on deterministic continuum mechanics, today it is not only ubiquitous in daily weather forecasts, but has been extended to seasonal predictions through to multidecadal climate projections. 

    But Richardson also pioneered the development of high level turbulent laws.  In 1926 he proposed the “Richardson 4/3 law” of turbulent diffusion, a law that wasn’t vindicated until 2013.   Whereas NWP attempts to account for every whirl, cloud, eddy, structure, the 4/3 law exploits the idea of scaling to statistically account for the collective outcome of billions upon billions of structures jointly acting from millimetres up to the size of the planet. 

    The idea that high-level statistical laws could explain the actions of myriads of vortices, cells and structures was shared by successive generations of turbulence scientists.  Unfortunately, they faced monumental mathematical difficulties largely connected to turbulent intermittency: the fact that most of the activity (e.g. energy flux) is inside tiny, violently active regions, themselves buried in a hierarchy of structures within structures.  The application of turbulence theory to the atmosphere, encounters an additional obstacle: stratification that depends on scale. 

    The 1980’s marked a turning point when Richardson’s deterministic and statistical strands parted company, the unity of the atmospheric sciences was broken.  On the one hand, computers revolutionized NWP, on the other hand, the nonlinear revolution promised to tame chaos itself, including turbulent chaos with its fractal structures within structures. 

    In this talk, I summarize four decades of work attempting to understand atmospheric variability that occurs over an astonishing range of scales: from millimetres to the size of the planet, from milliseconds to billions of years.   The variability is so large that standard ways of dealing with it are utterly inadequate: in 2015, it was found that classical approaches had underestimated the variability by the astronomical factor of a quadrillion.  The new understanding allows us to finally reunite Richardson’s strands. 

    For example, I show that the deterministic weather models respect the stochastic scaling laws very well.  I explain “macroweather” and how it sits in between the weather and climate, finally settling the question: “What is Climate”?  I answer the question “how big is a cloud?” and show that Mars is our statistical twin and why this shouldn’t surprise us.  I explain how the multifractal butterfly effect gives rise to events that are so extreme that they have been called “black swans”. 

    By using data from the real world – not model – climate, and with the help of the Fractional Energy Balance Equation (FEBE), I explain how the emergent scaling laws can make accurate monthly to decadal (macroweather) forecasts by exploiting an unsuspected but huge memory in the atmosphere-ocean system itself.  I show how the FEBE can help to significantly reduce the large uncertainties in our current climate projections to 2050 and 2100.

Refreshments: 3:15 PM

 

 

Building:
Room Number: 
*FL2-1001 Small Auditorium
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Announcement Timing: 
Friday, November 8, 2019 to Thursday, November 14, 2019
Calendar Timing: 
Thursday, November 14, 2019 - 3:30pm to 4:30pm
Nancy Sue
Kerner
8946

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