Search NASA⌕ Search

SEARCH · Search NASA

Results for “WRF model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Coarse, Intermediate and High Resolution Numerical Simulations of the Transition of a Tropical Wave Critical Layer to a Tropical Storm

Recent work has hypothesized that tropical cyclones in the deep Atlantic and eastern Pacific basins develop from within the cyclonic Kelvin cat's eye of a tropical easterly wave critical layer located equatorward of the easterly jet axis. The cyclonic critical layer is thought to be important to tropical cyclogenesis because its cat's eye provides (i) a region of cyclonic vorticity and weak deformation by the resolved flow, (ii) containment of moisture entrained by the developing flow and/or lofted by deep convection therein, (iii) confinement of mesoscale vortex aggregation, (iv) a predominantly convective type of heating profile, and (v) maintenance or enhancement of the parent wave until the developing proto-vortex becomes a self-sustaining entity and emerges from the wave as a tropical depression. This genesis sequence and the overarching framework for describing how such hybrid wave-vortex structures become tropical depressions/storms is likened to the development of a marsupial infant in its mother's pouch, and for this reason has been dubbed the "marsupial paradigm". Here we conduct the first multi-scale test of the marsupial paradigm in an idealized setting by revisiting the Kurihara and Tuleya problem examining the transformation of an easterly wave-like disturbance into a tropical storm vortex using the WRF model. An analysis of the evolving winds, equivalent potential temperature, and relative vertical vorticity is presented from coarse (28 km), intermediate (9 km) and high resolution (3.1 km) simulations. The results are found to support key elements of the marsupial paradigm by demonstrating the existence of rotationally dominant region with minimal strain/shear deformation near the center of the critical layer pouch that contains strong cyclonic vorticity and high saturation fraction. This localized region within the pouch serves as the "attractor" for an upscale "bottom up" development process while the wave pouch and proto-vortex move together.

Montgomery, M. T.↗
NASA NTRS2012

EnKF OSSE Experiments Assessing the Impact of HIRAD Wind Speed and HIWRAP Radial Velocity Data on Analysis of Hurricane Karl (2010)

Previous studies (e.g., Zhang et al. 2009, Weng et al. 2011) have shown that radial velocity data from airborne and ground-based radars can be assimilated into ensemble Kalman filter (EnKF) systems to produce accurate analyses of tropical cyclone vortices, which can reduce forecast intensity error. Recently, wind speed data from SFMR technology has also been assimilated into the same types of systems and has been shown to improve the forecast intensity of mature tropical cyclones. Two instruments that measure these properties were present during the NASA Genesis and Rapid Intensification Processes (GRIP) field experiment in 2010 which sampled Hurricane Karl, and will next be co-located on the same aircraft for the subsequent NASA HS3 experiment. The High Altitude Wind and Rain Profiling Radar (HIWRAP) is a conically scanning Doppler radar mounted upon NASAs Global Hawk unmanned aerial vehicle, and the usefulness of its radial velocity data for assimilation has not been previously examined. Since the radar scans from above with a fairly large fixed elevation angle, it observes a large component of the vertical wind, which could degrade EnKF analyses compared to analyses with data taken from lesser elevation angles. The NASA Hurricane Imaging Radiometer (HIRAD) is a passive microwave radiometer similar to SFMR, and measures emissivity and retrieves hurricane surface wind speeds and rain rates over a much wider swath. Thus, this study examines the impact of assimilating simulated HIWRAP radial velocity data into an EnKF system, simulated HIRAD wind speed, and HIWRAP+HIRAD with the Weather Research and Forecasting (WRF) model and compares the results to no data assimilation and also to the Truth from which the data was simulated for both instruments.

Albers, Cerese↗
NASA NTRS2012

Direct Radiative Effect of Mineral Dust on the Development of African Easterly Wave in Late Summer, 2003-2007

Episodic events of both Saharan dust outbreaks and African Easterly Waves (AEWs) are observed to move westward over the eastern tropical Atlantic Ocean. The relationship between the warm, dry, and dusty Saharan Air Layer (SAL) on the nearby storms has been the subject of considerable debate. In this study, the Weather Research and Forecasting (WRF) model is used to investigate the radiative effect of dust on the development of AEWs during August and September, the months of maximum tropical cyclone activity, in years 2003-2007. The simulations show that dust radiative forcing enhances the convective instability of the environment. As a result, most AEWs intensify in the presence of a dust layer. The Lorenz energy cycle analysis reveals that the dust radiative forcing enhances the condensational heating, which elevates the zonal and eddy available potential energy. In turn, available potential energy is effectively converted to eddy kinetic energy, in which local convective overturning plays the primary role. The magnitude of the intensification effect depends on the initial environmental conditions, including moisture, baroclinity, and the depth of the boundary layer. We conclude that dust radiative forcing, albeit small, serves as a catalyst to promote local convection that facilitates AEW development.

Ma, Po-Lun↗
NASA NTRS2013

Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

Zavodsky, Bradley T.↗
NASA NTRS2007

Applied Meteorology Unit (AMU)

This report summarizes the Applied Meteorology Unit (AMU) activities for the second quarter of Fiscal Year 2007 (January - March 2007). Tasks reported on are: Obiective Lightning Probability Tool, Peak Wind Tool for General Forecasting, Situational Lightning Climatologies for Central Florida, Anvil Threat Corridor Forecast Tool in AWIPS, Volume Averaqed Heiqht lnteq rated Radar Reflectivity (VAHIRR), Tower Data Skew-t Tool, and Weather Research and Forecastini (WRF) Model Sensitivity Study

Bauman, William↗
NASA NTRS2013

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

microwave observations↗
NASA NTRS2016

Isentropic Analysis of a Simulated Hurricane

Hurricanes, like many other atmospheric flows, are associated with turbulent motions over a wide range of scales. Here the authors adapt a new technique based on the isentropic analysis of convective motions to study the thermodynamic structure of the overturning circulation in hurricane simulations. This approach separates the vertical mass transport in terms of the equivalent potential temperature of air parcels. In doing so, one separates the rising air parcels at high entropy from the subsiding air at low entropy. This technique filters out oscillatory motions associated with gravity waves and separates convective overturning from the secondary circulation. This approach is applied here to study the flow of an idealized hurricane simulation with the Weather Research and Forecasting (WRF) Model. The isentropic circulation for a hurricane exhibits similar characteristics to that of moist convection, with a maximum mass transport near the surface associated with a shallow convection and entrainment. There are also important differences. For instance, ascent in the eyewall can be readily identified in the isentropic analysis as an upward mass flux of air with unusually high equivalent potential temperature. The isentropic circulation is further compared here to the Eulerian secondary circulation of the simulated hurricane to show that the mass transport in the isentropic circulation is much larger than the one in secondary circulation. This difference can be directly attributed to the mass transport by convection in the outer rainband and confirms that, even for a strongly organized flow like a hurricane, most of the atmospheric overturning is tied to the smaller scales.

convection↗
NASA NTRS2017

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June-August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.

Iguchi, Takamichi↗
NASA NTRS2018

Microphysics and Radiation Effect of Dust on Saharan Air Layer: An HS3 Case Study

A Saharan air layer (SAL) event associated with a nondeveloping African easterly wave (AEW) over the main development region of the eastern Atlantic was sampled by the NASA Global Hawk aircraft on 24-25 August 2013 during the NASA Hurricane and Severe Storm Sentinel (HS3) campaign and was simulated with the NASA Unified Weather Research and Forecasting (NU-WRF) Model. Airborne, ground-based, and spaceborne measurements were used to evaluate the model performance. The microphysical and radiative effects of dust and other aerosols on the SAL structure and environment were investigated with the factor-separation method. The results indicate that relative to a simulation without dust-radiative and microphysical impacts, Saharan dust and other aerosols heated the SAL air mainly through shortwave heating by the direct aerosol-radiation (AR) effect, resulting in a warmer (up to 0.6 K) and drier (up to 5% RH reduction) SAL and maintaining the strong temperature inversion at the base of the SAL in the presence of predominant longwave cooling. Radiative heating of the dust accentuated a vertical circulation within the dust layer, in which air rose (sank) in the northern (southern) portions of the dust layer. Furthermore, above and to the south of the dust layer, both the microphysical and radiative impacts of dust tended to counter the vertical motions associated with the Hadley circulation, causing a small weakening and southward shift of convection in the intertropical convergence zone (ITCZ) and reduced anvil cloud to the north. Changes in moisture and cloud/precipitation hydrometeors were largely driven by the dust induced changes in vertical motion. Dust strengthened the African easterly jet by up to ~1ms(exp -1) at the southern edge of the jet, primarily through the AR effect, and produced modest increases in vertical wind shear within and in the vicinity of the dust layer. These modulations of the SAL and AEW environment clearly contributed to the nondevelopment of this AEW.

Tao, Zhining↗
NASA NTRS2019

Monitoring Extreme Weather in the Hindu Kush Himalaya Region

Why is monitoring extreme weather events important? The HKH (Hindu Kush Himalaya region experiences many extreme weather events, such as thunderstorms, especially during monsoon season. These events can cause economic hardship and loss of life. Monitoring Extreme Weather in the HKH Region is a service in development through SERVIR-Hindu Kush Himalaya that aims to develop a customized numerical weather prediction toolkit to assess these high impact events in this relatively data-sparse region. The High Impact Weather Assessment Toolkit (HIWAT) consists of an ensemble Weather Research and Forecasting (WRF)model, threat assessments based on the Global Precipitation Measurement (GPM) missions, and impact assessments based on Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. In spring 2019, we began validation of forecasted precipitation using station data in Bangladesh and Climate Hazards Group InfraRed with Station data (CHIRPS).

Remote Sensing↗
NASA NTRS2018

Estimating CO2 Emissions Using Real and Simulated Total Column Observations

Total column measurements of CO2 (XCO2) have been proposed as a possible way to estimate emissions from large urban regions. Using calculations from the Weather Research and Forecasting (WRF) model with a 1km emissions field, we investigate the viability of both real and proposed observing systems consisting of surface and/or column measurements for constraining emission sources of various types and sizes in the San Francisco Bay Area. We find that column observations are best suited for assessing enhancements downwind of very large emissions sources. For smaller sources (such as highways), in situ surface monitors are required to provide sufficient sensitivity. We explore methods for estimating emissions from the real and simulated observations.

Raheja, Garima↗
NASA NTRS2021

Assimilation of Lidar Planetary Boundary Layer Height Observations

Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22 hourly forecasts from the NASA Unified - Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection Convection at Night (PECAN) campaign on July 11, 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with 6 independent radiosonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had a small impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the Doppler lidar PBLH observations were found to improve the temperature and V velocity profiles relative to independent radiosonde profiles. Water vapor was overcorrected, leading to increased differences with independent data. Errors in the U velocity were made slightly larger. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

Andrew Tangborn↗
NASA NTRS2022

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗
NASA NTRSDate not supplied

NASA Earth Exchange – Current overview of climate and wildfire-oriented works

NASA Earth Exchange (NEX) combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing petabyte-scale datasets covering large regions, continents, or the globe. As an accessible platform, NEX can accelerate fundamental research, develop new applications, and reduce overall project costs by providing the research community with data, software, and high-end computing power. Two research thrusts for the NEX community are developing and distributing the NEX-GDDP-CMIP6 downscaled climate dataset and the community-driven wildfire research. NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The wildfire research thrust leverages geostationary and low earth orbit remote sensing platforms and advanced modeling (WRF). We present a high-level overview of the NEX community, discuss relevant datasets and show several visualization techniques of data used in the wildfire research activity.

NEX↗
NASA NTRS2021

Spring Dust in Western North America and its Interannual Variability – Understanding the Role of Local and Transported Dust

Mineral dust over western North America is an important aerosol type contributing up to one half of surface aerosol concentrations in spring. In the present study, we use data from in-situ and remote-sensing observations and the NASA Unified WRF (NU-WRF) model to investigate the sources and interannual variations of the springtime fine-mode dust over western North America. The horizontal distribution, seasonality, and interannual variability of the springtime dust over the region are characterized with observations of fine dust concentrations at the Interagency Monitoring of Protected Visual Environments (IMPROVE) sites and dust optical depth (DOD) from the Aerosol Robotic Network (AERONET) measurements. We have conducted detailed modeling and analysis for April in selected years of 2005, 2008, and 2009, to understand the causes of interannual variabilities of the springtime dust with model experiments that separate the dust generated from local deserts with that transported across the Pacific Ocean. The results suggest that although several permanent deserts and semi-arid regions in the western North America are the major source of surface fine dust concentrations in the immediate vicinity, long-range transpacific transported dust is a dominant dust source in springtime, especially over the coastal regions and areas remote from the local deserts. Interannual variability of fine dust over western North America is explained with both local dust emission and long-range transported dust.

North America spring dust↗
NASA NTRS2006

An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NM'S Environmental Modeling System

The Weather Research and Forecasting (WRF) model is the next generation community mesoscale model designed to enhance collaboration between the research and operational sectors. The NM'S as a whole has begun a transition toward WRF as the mesoscale model of choice to use as a tool in making local forecasts. Currently, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) are running the Advanced Regional Prediction System (AIRPS) Data Analysis System (ADAS) every 15 minutes over the Florida peninsula to produce high-resolution diagnostics supporting their daily operations. In addition, the NWS MLB and SMG have used ADAS to provide initial conditions for short-range forecasts from the ARPS numerical weather prediction (NWP) model. Both NM'S MLB and SMG have derived great benefit from the maturity of ADAS, and would like to use ADAS for providing initial conditions to WRF. In order to assist in this WRF transition effort, the Applied Meteorology Unit (AMU) was tasked to configure and implement an operational version of WRF that uses output from ADAS for the model initial conditions. Both agencies asked the AMU to develop a framework that allows the ADAS initial conditions to be incorporated into the WRF Environmental Modeling System (EMS) software. Developed by the NM'S Science Operations Officer (S00) Science and Training Resource Center (STRC), the EMS is a complete, full physics, NWP package that incorporates dynamical cores from both the National Center for Atmospheric Research's Advanced Research WRF (ARW) and the National Centers for Environmental Prediction's Non-Hydrostatic Mesoscale Model (NMM) into a single end-to-end forecasting system. The EMS performs nearly all pre- and postprocessing and can be run automatically to obtain external grid data for WRF boundary conditions, run the model, and convert the data into a format that can be readily viewed within the Advanced Weather Interactive Processing System. The EMS has also incorporated the WRF Standard Initialization (SI) graphical user interface (GUT), which allows the user to set up the domain, dynamical core, resolution, etc., with ease. In addition to the SI GUT, the EMS contains a number of configuration files with extensive documentation to help the user select the appropriate input parameters for model physics schemes, integration timesteps, etc. Therefore, because of its streamlined capability, it is quite advantageous to configure ADAS to provide initial condition data to the EMS software. One of the biggest potential benefits of configuring ADAS for ingest into the EMS is that the analyses could be used to initialize either the ARW or NMM. Currently, the ARPS/ADAS software has a conversion routine only for the ARW dynamical core. However, since the NIvIM runs about 2.5 times faster than the ARW, it is quite advantageous to be able to run an ADAS/NMM configuration operationally due to the increased efficiency.

Case, Jonathan↗
NASA NTRS2007

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision at the Shuttle Landing Facility. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAFs), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. Both the SMG and the MLB are currently implementing the Weather Research and Forecasting Environmental Modeling System (WRF EMS) software into their operations. The WRF EMS software allows users to employ both dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model- the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

Watson, Leela R.↗
NASA NTRS2021

Cold Season Performance of the NU-WRF Regional Climate Model in the Great Lakes Region

As Earth’s largest collection of freshwater, the Laurentian Great Lakes have enormous ecological and socio-economic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake-atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014-2015 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.

Michael Notaro↗