Events (Upcoming & Past)

Past MMM Events

Xiaolei ZouEarth System Science Interdisciplinary Center (ESSIC)University of Maryland

Abstract: The Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar orbiter Partnership (S-NPP) satellite combines Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) onboard NOAA and Meteorological Operational Satellite Program of Europe (MetOP) satellites to simultaneously provide collocated radiance measurements of the atmospheric temperature and moisture profiles under almost all weather conditions except for heavy precipitation. The two lowest frequency ATMS window channels 1-2 (23.8GHz and 31.4 GHz) are the same as AMSU-A channels 1-2 and the other two high-frequency ATMS window channels 17-18 (88.2GHz and 165.5GHz) are similar to MHS window channels 1-2. These four ATMS window channels can be used together for identifying both liquid and ice cloudy radiances. This important feature of ATMS proved to be important for improving the forecast skill of severe weathers populated with clouds (e.g., hurricanes) through satellite microwave radiance assimilation (Zou et al., 2013). Assimilation of microwave radiance data in numerical weather prediction (NWP) models has traditionally been carried out with AMSU-A and MHS data in two separate data streams since the launch of NOAA-15 in 1998. Inspired by the ATMS data assimilation success, a new approach was proposed to combine AMSU-A and MHS radiances into one data stream for their assimilation. It was shown that the spatial collocation between AMSU-A and MHS field of views (FOVs) allows for an improved quality control of MHS data, especially over the conditions where the liquid-phase clouds are dominate. It was found that the quantitative precipitation forecast (QPF) skill associated with landfall hurricanes was significantly improved by the one data stream approach, resulting from a closer fit of analyses to AMSU-A and MHS observations is obtained, especially for AMSU-A surface-sensitive channels (Zou et al., 2017). A shortcoming was also found for S-NPP ATMS whose radiance observations displayed a clear across-track striping noise, which was not found in AMSU-A radiances. Three algorithms were subsequently developed for mitigating the ATMS striping noise for the upper-level sounding channels (Qin et al., 2013), for an operational implementation (Ma and Zou, 2015) and for surface sensitive channels (Zou et al., 2017). Impacts of striping noise mitigation on observation error variances were also quantified for assimilation of destriped ATMS radiance observations.

Refreshments:  10:45 AM

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Wednesday, August 23, 2017 - 11:00pm to Thursday, August 24, 2017 - 12:00am

Xiaolei Zou
Earth System Science Interdisciplinary Center (ESSIC)
University of Maryland

Abstract: The Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar orbiter Partnership (S-NPP) satellite combines Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) onboard NOAA and Meteorological Operational Satellite Program of Europe (MetOP) satellites to simultaneously provide collocated radiance measurements of the atmospheric temperature and moisture profiles under almost all weather conditions except for heavy precipitation. The two lowest frequency ATMS window channels 1-2 (23.8GHz and 31.4 GHz) are the same as AMSU-A channels 1-2 and the other two high-frequency ATMS window channels 17-18 (88.2GHz and 165.5GHz) are similar to MHS window channels 1-2. These four ATMS window channels can be used together for identifying both liquid and ice cloudy radiances. This important feature of ATMS proved to be important for improving the forecast skill of severe weathers populated with clouds (e.g., hurricanes) through satellite microwave radiance assimilation (Zou et al., 2013). Assimilation of microwave radiance data in numerical weather prediction (NWP) models has traditionally been carried out with AMSU-A and MHS data in two separate data streams since the launch of NOAA-15 in 1998. Inspired by the ATMS data assimilation success, a new approach was proposed to combine AMSU-A and MHS radiances into one data stream for their assimilation. It was shown that the spatial collocation between AMSU-A and MHS field of views (FOVs) allows for an improved quality control of MHS data, especially over the conditions where the liquid-phase clouds are dominate. It was found that the quantitative precipitation forecast (QPF) skill associated with landfall hurricanes was significantly improved by the one data stream approach, resulting from a closer fit of analyses to AMSU-A and MHS observations is obtained, especially for AMSU-A surface-sensitive channels (Zou et al., 2017). A shortcoming was also found for S-NPP ATMS whose radiance observations displayed a clear across-track striping noise, which was not found in AMSU-A radiances. Three algorithms were subsequently developed for mitigating the ATMS striping noise for the upper-level sounding channels (Qin et al., 2013), for an operational implementation (Ma and Zou, 2015) and for surface sensitive channels (Zou et al., 2017). Impacts of striping noise mitigation on observation error variances were also quantified for assimilation of destriped ATMS radiance observations.

Refreshments:  10:45 AM

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: 
Wednesday, August 23, 2017 - 11:00am to 12:00pm

Sisi ChenDepartment of Atmospheric and Oceanic Sciences, McGill UniversityMontreal, Quebec, Canada

Shallow convective clouds are ubiquitous, and warm rain largely contributes to the total annual rainfall, particularly in the tropics. Therefore, understanding the microphysical processes inside these cloud systems becomes important. Classical parcel models often produce narrow droplet size distributions (DSDs) which disagree with observations in cumulus clouds. Since the last century, turbulence have been postulated to explain the effective DSD broadening in early cloud stage.

This work studies the very fundamental process involving droplet condensational and collisional growth to explore the fast warm-rain initiation using the direct numerical simulation (DNS). DNS model can accurately resolve small-scale turbulence and simulates the turbulence impacts on droplets that are tracked in the Lagrangian framework, which is infeasible in other models.

This is the first modeling study that incorporates both droplet condensational process and collisional process into the DNS model and investigates the full droplet growth history in the turbulent environment. 

Model results show that condensational growth by itself produces narrow DSD under small-scale turbulence, which is similar to the parcel model results. Results from the simulations that consider pure collision-coalescence process show that small-scale turbulence significantly increases the collision rate between small droplets and thus accelerates the formation of large droplets. In particular, the enhancement is the strongest between similar-sized droplets, which indicates that turbulence effectively broadens the narrow DSD formed by condensational growth. On the other hand, condensational growth considerably brings tiny droplets to 5-10 microns, dynamically shifting the collision rates of those droplets in turbulence. To study how collisional process and condensational process interact under the effect of turbulence, simulation results that consider both condensational and collisional processes will be compared to pure collision-coalescence case. It is shown that the inclusion of condensation significantly changes the behavior of droplet collisions in the turbulence and thus has strong feedback on the DSD broadening. Detailed results and comparison will be presented in the talk.

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, August 18, 2017 - 3:30am to 4:30am

Sisi Chen
Department of Atmospheric and Oceanic Sciences, McGill University
Montreal, Quebec, Canada

Shallow convective clouds are ubiquitous, and warm rain largely contributes to the total annual rainfall, particularly in the tropics. Therefore, understanding the microphysical processes inside these cloud systems becomes important. Classical parcel models often produce narrow droplet size distributions (DSDs) which disagree with observations in cumulus clouds. Since the last century, turbulence have been postulated to explain the effective DSD broadening in early cloud stage.

This work studies the very fundamental process involving droplet condensational and collisional growth to explore the fast warm-rain initiation using the direct numerical simulation (DNS). DNS model can accurately resolve small-scale turbulence and simulates the turbulence impacts on droplets that are tracked in the Lagrangian framework, which is infeasible in other models.

This is the first modeling study that incorporates both droplet condensational process and collisional process into the DNS model and investigates the full droplet growth history in the turbulent environment. 

Model results show that condensational growth by itself produces narrow DSD under small-scale turbulence, which is similar to the parcel model results. Results from the simulations that consider pure collision-coalescence process show that small-scale turbulence significantly increases the collision rate between small droplets and thus accelerates the formation of large droplets. In particular, the enhancement is the strongest between similar-sized droplets, which indicates that turbulence effectively broadens the narrow DSD formed by condensational growth. On the other hand, condensational growth considerably brings tiny droplets to 5-10 microns, dynamically shifting the collision rates of those droplets in turbulence. To study how collisional process and condensational process interact under the effect of turbulence, simulation results that consider both condensational and collisional processes will be compared to pure collision-coalescence case. It is shown that the inclusion of condensation significantly changes the behavior of droplet collisions in the turbulence and thus has strong feedback on the DSD broadening. Detailed results and comparison will be presented in the talk.

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, August 17, 2017 - 3:30pm to 4:30pm

Dale Barker UK Met Office

The Met Office global and regional NWP applications are centered around the use of the Unified Model (UM) to provide short-range forecasts out to 5-7 days of global and local significant weather. This talk will describe some of the major upgrades implemented or planned during the timeframe of the new Cray XC40 supercomputer (2015 - 2020) beginning with a brief description of the basic NWP configurations and a summary or recent major upgrades e.g. variational bias correction, additional satellite data, etc.

In July 2017, the resolution of the global NWP system at the Met Office was increased to ~10km, with an associated increase to 20km for the global (MOGREPS-G) ensemble. A more significant change is the introduction of hourly-cycling four dimensional variational (4DVar) data assimilation for the km-scale UK model. The relative contributions to forecast skill improvements of hourly-cycling, the use of the 4DVar technique, and improved driving global model will be assessed in this talk.

Looking forward, additional major upgrades are planned in the next 1-2 years including weakly coupled ocean-atmosphere data assimilation, extension of the km-scale MOGREPS-UK ensemble to T+5 days (plus resolution increase from 2.2km to 1.5km), replacement of the current ETKF ensemble system with an ‘Ensemble of 4D Ensemble Vars’. Details of these promising scientific developments will be provided. Finally, a brief summary of plans for the post-UM ‘Exascale Era’ beginning in ~2023 will be outlined.

Note special date and time. 

Refreshments: 10:45 AM 

Building:
Room Number: 
1022
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Tuesday, August 8, 2017 - 11:00pm to Wednesday, August 9, 2017 - 12:00am

Dale Barker
UK Met Office

The Met Office global and regional NWP applications are centered around the use of the Unified Model (UM) to provide short-range forecasts out to 5-7 days of global and local significant weather. This talk will describe some of the major upgrades implemented or planned during the timeframe of the new Cray XC40 supercomputer (2015 - 2020) beginning with a brief description of the basic NWP configurations and a summary or recent major upgrades e.g. variational bias correction, additional satellite data, etc.

In July 2017, the resolution of the global NWP system at the Met Office was increased to ~10km, with an associated increase to 20km for the global (MOGREPS-G) ensemble. A more significant change is the introduction of hourly-cycling four dimensional variational (4DVar) data assimilation for the km-scale UK model. The relative contributions to forecast skill improvements of hourly-cycling, the use of the 4DVar technique, and improved driving global model will be assessed in this talk.

Looking forward, additional major upgrades are planned in the next 1-2 years including weakly coupled ocean-atmosphere data assimilation, extension of the km-scale MOGREPS-UK ensemble to T+5 days (plus resolution increase from 2.2km to 1.5km), replacement of the current ETKF ensemble system with an ‘Ensemble of 4D Ensemble Vars’. Details of these promising scientific developments will be provided. Finally, a brief summary of plans for the post-UM ‘Exascale Era’ beginning in ~2023 will be outlined.

Note special date and time. 

Refreshments: 10:45 AM 

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: 
Tuesday, August 8, 2017 - 11:00am to 12:00pm

Nedjelika ŽagarUniversity of LjubljanaLjubljana, Slovenia

Many studies of the forecast error growth focused on the extra-tropical quasi-geostrophic dynamics and often considered the error-free large-scale initial state.  In contrast, the operational global numerical weather prediction and ensemble prediction systems are characterized by uncertainties in the initial state at all scales, especially in the tropics.  In this seminar the evidence will be discussed about the dominant role of the large-scale error growth early in the forecasts in comparison with the errors cascades from the smaller scales.   A new parametric model for the representation of the error growth will be derived.  In contrast to the commonly used models, the new model does not involve computation of the time derivatives of the empirical data. The asymptotic error is not a fitting parameter, but it is computed from the model constants. 

Simulated forecast errors by the operational ensemble prediction system of the European Centre for Medium-Range Weather Forecasts are decomposed into scales and the new model is applied independently to every zonal wavenumber.  A combination of hyperbolic tangent functions in the parametrization of the error growth proves robust to reliably model complex growth dynamics across many scales.  The range of useful prediction skill, estimated as a scale where forecast errors exceeds 60% of their asymptotic values is around 7 days on large scales and 2-3 days at 1000 km scale.  The new model is easily transformed to the widely used model of Dalcher and Kalnay (1987) to discuss the scale-dependent growth as a sum of two terms, the so-called a and b terms.  Their comparison shows that at planetary scales their contributions to the growth in the first 2 days are similar whereas at small scales the b term describes most of a rapid exponential growth of errors towards saturation. 

Refreshments: 3:15pm

Building:
Room Number: 
1022
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, August 11, 2017 - 3:30am to 4:30am

Nedjelika Žagar
University of Ljubljana
Ljubljana, Slovenia

Many studies of the forecast error growth focused on the extra-tropical quasi-geostrophic dynamics and often considered the error-free large-scale initial state.  In contrast, the operational global numerical weather prediction and ensemble prediction systems are characterized by uncertainties in the initial state at all scales, especially in the tropics.  In this seminar the evidence will be discussed about the dominant role of the large-scale error growth early in the forecasts in comparison with the errors cascades from the smaller scales.   A new parametric model for the representation of the error growth will be derived.  In contrast to the commonly used models, the new model does not involve computation of the time derivatives of the empirical data. The asymptotic error is not a fitting parameter, but it is computed from the model constants. 

Simulated forecast errors by the operational ensemble prediction system of the European Centre for Medium-Range Weather Forecasts are decomposed into scales and the new model is applied independently to every zonal wavenumber.  A combination of hyperbolic tangent functions in the parametrization of the error growth proves robust to reliably model complex growth dynamics across many scales.  The range of useful prediction skill, estimated as a scale where forecast errors exceeds 60% of their asymptotic values is around 7 days on large scales and 2-3 days at 1000 km scale.  The new model is easily transformed to the widely used model of Dalcher and Kalnay (1987) to discuss the scale-dependent growth as a sum of two terms, the so-called a and b terms.  Their comparison shows that at planetary scales their contributions to the growth in the first 2 days are similar whereas at small scales the b term describes most of a rapid exponential growth of errors towards saturation. 

Refreshments: 3:15pm


First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1022
Host lab/program/group:
Calendar Timing: 
Thursday, August 10, 2017 - 3:30pm to 4:30pm

James Done NCAR/MMM

As populations increase in hazard-prone regions, the human, cultural and economic costs rise, and will continue to rise in the future. The likely scenario of the weather and climate hazards themselves changing in the future will compound the problem. A transformation of how weather and climate risk is assessed and integrated with risk management practice is needed for society to confront this new era of weather and climate risk. Bringing physics to bear on risk assessment has the potential to transform our understanding of weather and climate risk. Furthermore, physically based risk assessments that are informed by risk management practice are a potentially powerful component of climate resilience. Three recent examples will be presented to illustrate the flow between physically based weather and climate risk assessments and community action.

The first example is the development of a terrain-aware tropical cyclone wind probability assessment at the global scale. In collaboration with a reinsurance broker, an approach to modeling tropical cyclone wind footprints is developed by fitting a parametric wind field model to historical and synthetic cyclone track data, and bringing the winds down to the surface using a 3-dimensional numerical boundary model, accounting for terrain and surface roughness effects. The new wind probability assessments are being used to understand inland wind risk in regions of complex topography, and assess public and private risk management strategies in regions of sparse historical data. The second example explores how the relationship between residential losses and hurricane winds is modified through building codes. Adherence to the Florida building code drives down losses by up to 70%, and the code is cost-effective with a return on investment after 12 years under current climate. The final example explores the role of decadal climate predictions in water resource and flood risk management. The multi-disciplinary UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales) project combines statistical and physical assessments of climate prediction skill with data from interviews with managers to identify intersections at the decadal scale in support of effective management.

Refreshments:  3:15pm

Building:
Room Number: 
1001 (Note Location)
Type of event:
Will this event be webcast to the public by NCAR|UCAR?: 
Calendar Timing: 
Friday, August 4, 2017 - 3:30am to 4:30am

James Done 
NCAR/MMM

As populations increase in hazard-prone regions, the human, cultural and economic costs rise, and will continue to rise in the future. The likely scenario of the weather and climate hazards themselves changing in the future will compound the problem. A transformation of how weather and climate risk is assessed and integrated with risk management practice is needed for society to confront this new era of weather and climate risk. Bringing physics to bear on risk assessment has the potential to transform our understanding of weather and climate risk. Furthermore, physically based risk assessments that are informed by risk management practice are a potentially powerful component of climate resilience. Three recent examples will be presented to illustrate the flow between physically based weather and climate risk assessments and community action.

The first example is the development of a terrain-aware tropical cyclone wind probability assessment at the global scale. In collaboration with a reinsurance broker, an approach to modeling tropical cyclone wind footprints is developed by fitting a parametric wind field model to historical and synthetic cyclone track data, and bringing the winds down to the surface using a 3-dimensional numerical boundary model, accounting for terrain and surface roughness effects. The new wind probability assessments are being used to understand inland wind risk in regions of complex topography, and assess public and private risk management strategies in regions of sparse historical data. The second example explores how the relationship between residential losses and hurricane winds is modified through building codes. Adherence to the Florida building code drives down losses by up to 70%, and the code is cost-effective with a return on investment after 12 years under current climate. The final example explores the role of decadal climate predictions in water resource and flood risk management. The multi-disciplinary UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales) project combines statistical and physical assessments of climate prediction skill with data from interviews with managers to identify intersections at the decadal scale in support of effective management.

Refreshments:  3:15pm

First Name: 
Bobbie
Last Name: 
Weaver
Phone Extension (4 digits): 
8946
Email: 
weaver@ucar.edu
Building:
Room Number: 
1001 (Note Location)
Host lab/program/group:
Type of event:
Calendar Timing: 
Thursday, August 3, 2017 - 3:30pm to 4:30pm

Pages