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Past MMM Events

Speaker: Marcus van Lier-Walqui
NASA/GISS & CCSR, Columbia University 

Weather and climate models have well-known biases in their representation of physical processes. A prime offender is cloud microphysics, owing to the complexity of hydrometeor interactions as well as the approximations that underpin bulk parameterizations. To some extent, models can be improved by finding optimal values for tunable model parameters, and estimating the uncertainty in these parameters — “parametric” uncertainty. Radar observations, including polarimetric radars and radar Doppler spectra, have shown much promise in providing information related to microphysical processes and can thus be leveraged via, e.g., Bayesian estimation, to probabilistically constrain model parameters. A deeper problem is that structural assumptions are typically hard-coded into parameterization schemes, and thus cannot be systematically improved in the same manner, nor can uncertainty associated with these choices be quantified. This fundamental shortcoming of traditional parameterizations motivates the use of multi-physics ensembles in probabilistic weather forecasts — these are, in essence, attempts at spanning both parametric and structural uncertainties in physical parameterizations, but they typically cannot span these uncertainties smoothly or probabilistically. I will present work on a new microphysics scheme, the Bayesian Observationally-constrained Statistical-physical Scheme, or BOSS,  and describe how it was developed specifically to facilitate characterization of parametric and structural uncertainties in a Bayesian framework. An additional benefit of BOSS is that it is “smooth” and therefore amenable to adjoint methods. I will also present work on applications of Bayesian parameter estimation to ice microphysics, cloud property retrievals, and climate model tuning.

Refreshments: 3:15 PM

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, April 5, 2018 - 3:30pm to 4:30pm

Speaker: Andrew HeymsfieldNCAR/MMM  

In this seminar, I will describe the general properties of graupel (rimed particles < 0.5 cm) and hail, based on observations. I will then report on my work that uses novel approaches to estimate the fall characteristics of hail. Three-dimensional volume scans of hailstones of sizes from 2 to 7 cm were printed in 3D models (I’ll show some in my seminar) using ABS plastic, and their terminal velocities were measured in the Mainz vertical wind tunnel. To simulate graupel, some of the hailstone models were printed with dimensions of 0.2-0.5 cm, and their terminal velocities measured. From these experiments, together with earlier observations, I’ve parameterized the properties of graupel and hail for a wide range of particle sizes and heights (pressures) in the atmosphere. The wind tunnel observations, together with the combined total of more than 2800 hailstones for which the mass and cross-sectional area were measured, has been used to develop size-dependent relationships for the terminal velocity, mass flux, and kinetic energy of realistic hailstones.

Also in my seminar, I’ll fill you in on work that I’ve unraveled (going back to data from the mid 1930’s), to try and understand why the insurance and building industries use “outdated” data to estimate and repair hail damage.

Refreshments: 3:15 PM

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, March 30, 2018 - 3:30am to 4:30am

Speaker: Andrew Heymsfield
NCAR/MMM  

In this seminar, I will describe the general properties of graupel (rimed particles < 0.5 cm) and hail, based on observations. I will then report on my work that uses novel approaches to estimate the fall characteristics of hail. Three-dimensional volume scans of hailstones of sizes from 2 to 7 cm were printed in 3D models (I’ll show some in my seminar) using ABS plastic, and their terminal velocities were measured in the Mainz vertical wind tunnel. To simulate graupel, some of the hailstone models were printed with dimensions of 0.2-0.5 cm, and their terminal velocities measured. From these experiments, together with earlier observations, I’ve parameterized the properties of graupel and hail for a wide range of particle sizes and heights (pressures) in the atmosphere. The wind tunnel observations, together with the combined total of more than 2800 hailstones for which the mass and cross-sectional area were measured, has been used to develop size-dependent relationships for the terminal velocity, mass flux, and kinetic energy of realistic hailstones.

Also in my seminar, I’ll fill you in on work that I’ve unraveled (going back to data from the mid 1930’s), to try and understand why the insurance and building industries use “outdated” data to estimate and repair hail damage.

Refreshments: 3:15 PM

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, March 29, 2018 - 3:30pm to 4:30pm

Charles KnightNCAR/MMM  

“The box” represents classical nucleation theory, CNT, a conceptually simple and at first appealing mechanism in which the interfacial energy between an initial, unstable phase (liquid water, here) and a stable one (ice) constitutes an energy barrier against the stable one’s first appearance.  Ice nucleation obviously involves crystal growth, but the theory of CNT in general has been based upon thermodynamics and chemical reaction theory, independent of crystal structure.  Outside the box here is treating crystal growth and nucleation in terms of growth of the known hydrogen-bond network of ice: the ice crystal structure and its tetrahedral bonding.  The initial context here was trying to explain the observed correlations between ice crystal growth in liquid water and the ice crystal structure, part of which appeared to involve two-dimensional nucleation of new molecular layers at an interface between ice and liquid water.  This explanation turned out not to work well whereas a simple model of growth of the bonding network does seem to provide conceptual understanding.  A bonding-network approach to homogeneous nucleation is unwieldy but interesting, and from that point of view, CNT (for nucleating ice) seems dubious.  The actual mechanism may be dominated by structural effects, not interfacial energy.

Refreshments: 3:15 PM

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, March 23, 2018 - 3:30am to 4:30am

Charles Knight
NCAR/MMM  

“The box” represents classical nucleation theory, CNT, a conceptually simple and at first appealing mechanism in which the interfacial energy between an initial, unstable phase (liquid water, here) and a stable one (ice) constitutes an energy barrier against the stable one’s first appearance.  Ice nucleation obviously involves crystal growth, but the theory of CNT in general has been based upon thermodynamics and chemical reaction theory, independent of crystal structure.  Outside the box here is treating crystal growth and nucleation in terms of growth of the known hydrogen-bond network of ice: the ice crystal structure and its tetrahedral bonding.  The initial context here was trying to explain the observed correlations between ice crystal growth in liquid water and the ice crystal structure, part of which appeared to involve two-dimensional nucleation of new molecular layers at an interface between ice and liquid water.  This explanation turned out not to work well whereas a simple model of growth of the bonding network does seem to provide conceptual understanding.  A bonding-network approach to homogeneous nucleation is unwieldy but interesting, and from that point of view, CNT (for nucleating ice) seems dubious.  The actual mechanism may be dominated by structural effects, not interfacial energy.

Refreshments: 3:15 PM

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, March 22, 2018 - 3:30pm to 4:30pm

Xiang-Yu LiDepartment of MeteorologyStockholm University, Sweden

We investigate the effect of turbulence on the collisional growth of μm-sized droplets by high-resolution numerical simulations with well resolved Kolmogorov scales, assuming a collision and coalescence efficiency of unity. The droplet dynamics and collisions are approximated using a superparticle approach. We show that the time evolution of the shape of the droplet-size distribution due to turbulence-induced collision depends strongly on the turbulent energy-dissipation rate, but only weakly on the Reynolds number. The size distribution exhibits power law behavior with a slope of −3.7 in the size range of about 10 ∼40 μm, which is close to the power law size distribution found for interstellar dust grains. When gravity is invoked, the strong dependency becomes weakened. Turbulence is found to dominate the time evolution of an initially monodisperse droplet distribution at early times. At later times, however, gravity takes over and dominates the collisional growth. With combined turbulence and gravity, the time scale to reach drizzle sized droplets is about 900 s, which is close to the time scale of rapid warm rain formation. The collision rate grows exponentially, which is consistent with the theoretical prediction of the continuous collisional growth even when the turbulence-generated collision is invoked.

Refreshments: 3:15 PM

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, March 9, 2018 - 5:30am to 6:30am

Xiang-Yu Li
Department of Meteorology
Stockholm University, Sweden

We investigate the effect of turbulence on the collisional growth of μm-sized droplets by high-resolution numerical simulations with well resolved Kolmogorov scales, assuming a collision and coalescence efficiency of unity. The droplet dynamics and collisions are approximated using a superparticle approach. We show that the time evolution of the shape of the droplet-size distribution due to turbulence-induced collision depends strongly on the turbulent energy-dissipation rate, but only weakly on the Reynolds number. The size distribution exhibits power law behavior with a slope of −3.7 in the size range of about 10 ∼40 μm, which is close to the power law size distribution found for interstellar dust grains. When gravity is invoked, the strong dependency becomes weakened. Turbulence is found to dominate the time evolution of an initially monodisperse droplet distribution at early times. At later times, however, gravity takes over and dominates the collisional growth. With combined turbulence and gravity, the time scale to reach drizzle sized droplets is about 900 s, which is close to the time scale of rapid warm rain formation. The collision rate grows exponentially, which is consistent with the theoretical prediction of the continuous collisional growth even when the turbulence-generated collision is invoked.

Refreshments: 3:15 PM

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, March 8, 2018 - 3:30pm to 4:30pm

Andy Wood Martyn Clark NCAR/RAL/HAP 

Ensemble hydrologic (streamflow) prediction provides critical inputs for water, energy and hazard management, particularly in the face of extremes such as floods and droughts.  Following steady advances in operational ensemble numerical weather prediction since the 1990s, US and international operational prediction groups have invested heavily in developing datasets, methods, and models to enable a seamless suite of probabilistic hydrologic predictions spanning timescales from hours to seasons.  Ensemble hydrologic forecasting systems are now operational in a number of countries (including the US), and are enhanced by an increasingly crowded field of operational continental and global ensemble hydrologic prediction services.  In this presentation, we provide background describing the evolution of ensemble hydrologic prediction systems, and highlight the role of the HEPEX (Hydrologic Ensemble Prediction Experiment; www.hepex.org) initiative since 2004 in defining and promoting an integrative, scientific view of the elements of a hydrologic ensemble prediction approach.  These include methods for the probabilistic downscaling and calibration of meteorological forecast ensembles, hydrologic model parameter estimation and uncertainty quantification, hydrologic model data assimilation, model output post-processing, and ensemble forecast verification and communication for use in risk-based decision-making.  We summarize the current state of practice in applying these methods to achieve reliable ensemble streamflow forecasts (locally and globally), and discuss long-standing and new challenges identified by the ensemble hydrologic prediction community.

Refreshments:  3:15 PM  

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, March 2, 2018 - 5:30am to 6:30am

Andy Wood
Martyn Clark
NCAR/RAL/HAP 

Ensemble hydrologic (streamflow) prediction provides critical inputs for water, energy and hazard management, particularly in the face of extremes such as floods and droughts.  Following steady advances in operational ensemble numerical weather prediction since the 1990s, US and international operational prediction groups have invested heavily in developing datasets, methods, and models to enable a seamless suite of probabilistic hydrologic predictions spanning timescales from hours to seasons.  Ensemble hydrologic forecasting systems are now operational in a number of countries (including the US), and are enhanced by an increasingly crowded field of operational continental and global ensemble hydrologic prediction services.  In this presentation, we provide background describing the evolution of ensemble hydrologic prediction systems, and highlight the role of the HEPEX (Hydrologic Ensemble Prediction Experiment; www.hepex.org) initiative since 2004 in defining and promoting an integrative, scientific view of the elements of a hydrologic ensemble prediction approach.  These include methods for the probabilistic downscaling and calibration of meteorological forecast ensembles, hydrologic model parameter estimation and uncertainty quantification, hydrologic model data assimilation, model output post-processing, and ensemble forecast verification and communication for use in risk-based decision-making.  We summarize the current state of practice in applying these methods to achieve reliable ensemble streamflow forecasts (locally and globally), and discuss long-standing and new challenges identified by the ensemble hydrologic prediction community.

Refreshments:  3:15 PM  

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, March 1, 2018 - 3:30pm to 4:30pm

Hugh Morrison MMM/NCAR

The representation of cloud and precipitation microphysics is a critical element in atmospheric models of all scales. It affects the thermodynamics and dynamics from latent heating/cooling and condensate drag, strongly influences cloudy radiative transfer, and is a key component of the hydrological cycle through the generation and fallout of precipitation. An overview of the historical development of microphysics schemes in cloud and mesoscale models will be presented first. Advances over the last decade will be covered in more detail, particularly the recent development of a scheme called Predicted Particle Properties (P3) that predicts and smoothly evolves ice particle properties such as density and fall speed. This approach is a significant departure from traditional microphysics schemes that separate ice into categories with fixed properties corresponding to particular ice types (small ice, snow, graupel, hail, etc.). Simulations using P3 implemented in the Weather Research and Forecasting (WRF) model will be presented and contrasted with those using traditional schemes. Additional developments related to P3, including an improved numerical treatment of cloud and precipitation transport, will also be presented. Finally, more “outside of the box” ideas for parameterizing microphysics will be highlighted, including a Bayesian statistical-physical parameterization framework that facilitates observational constraint of process rates and a rigorous characterization of uncertainty. The talk with conclude with a broader outlook and commentary on future microphysics scheme developments over the next 5-10 years and beyond.

Refreshments: 3:15 PM

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, February 16, 2018 - 5:30am to 6:30am

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