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NASA NTRS2014

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

Zavordsky, Bradley↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Zavodsky, Bradley↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Execute Cycled WRF/GSI Forecasts

Automating the coupling of data assimilation (DA) and modeling systems is a unique challenge in the numerical weather prediction (NWP) research community. In recent years, the Development Testbed Center (DTC) has released well-documented tools such as the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolation (GSI) DA system that can be easily downloaded, installed, and run by researchers on their local systems. However, developing a coupled system in which the various preprocessing, DA, model, and postprocessing capabilities are all integrated can be labor-intensive if one has little experience with any of these individual systems. Additionally, operational modeling entities generally have specific coupling methodologies that can take time to understand and develop code to implement properly. To better enable collaborating researchers to perform modeling and DA experiments with GSI, the Short-term Prediction Research and Transition (SPoRT) Center has developed a set of Perl scripts that couple GSI and WRF in a cycling methodology consistent with the use of real-time, regional observation data from the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC). Because Perl is open source, the code can be easily downloaded and executed regardless of the user's native shell environment. This paper will provide a description of this open-source code and descriptions of a number of the use cases that have been performed by SPoRT collaborators using the scripts on different computing systems.

Zavodsky, Bradley↗

NASA NTRS2018

Interactions Between Asian Air Pollution and Monsoon System: South Asia (ROSES-2014 ACMAP)

Asia's rapid economic growth over the past several decades has brought a remarkable increase in air pollution levels in that region. High concentrations of aerosols (also known as particulate matter or PM) from pollution sources pose major health hazards to half of the world population in Asia including South Asia. How do pollution and dust aerosols regulate the monsoon circulation and rainfall via scattering and absorbing solar radiation, changing the atmospheric heating rates, and modifying the cloud properties? We conducted a series of regional model experiments with NASA-Unified Weather Research and Forecast (NUWRF) regional model with coupled aerosol-chemistry-radiation-microphysics processes over South Asia for winter, pre-monsoon, and monsoon seasons to address this question. This study investigates the worsening air quality problem in South Asia by focusing on the interactions between pollution and South Asian monsoon, not merely focusing on the increase of pollutant emissions.

regional model experiments with NASA-Unified Weath↗

NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Case. Jonathan↗

NASA NTRS2010

Implications of Wind-Assisted Aerial Navigation for Titan Mission Planning and Science Exploration

The recent Titan Saturn System Mission (TSSM) proposal incorporates a montgolfiere (hot air balloon) as part of its architecture. Standard montgolfiere balloons generate lift through heating of the atmospheric gases inside the envelope, and use a vent valve for altitude control. A Titan aerobot (robotic aerial vehicle) would have to use radioisotope thermoelectric generators (RTGs) for electric power, and the excess heat generated can be used to provide thermal lift for a montgolfiere. A hybrid montgolfiere design could have propellers mounted on the gondola to generate horizontal thrust; in spite of the unfavorable aerodynamic drag caused by the shape of the balloon, a limited amount of lateral controllability could be achieved. In planning an aerial mission at Titan, it is extremely important to assess how the moon-wide wind field can be used to extend the navigation capabilities of an aerobot and thereby enhance the scientific return of the mission. In this paper we explore what guidance, navigation and control capabilities can be achieved by a vehicle that uses the Titan wind field. The control planning approach is based on passive wind field riding. The aerobot would use vertical control to select wind layers that would lead it towards a predefined science target, adding horizontal propulsion if available. The work presented in this paper is based on aerodynamic models that characterize balloon performance at Titan, and on TitanWRF (Weather Research and Forecasting), a model that incorporates heat convection, circulation, radiation, Titan haze properties, Saturn's tidal forcing, and other planetary phenomena. Our results show that a simple unpropelled montgolfiere without horizontal actuation will be able to reach a broad array of science targets within the constraints of the wind field. The study also indicates that even a small amount of horizontal thrust allows the balloon to reach any area of interest on Titan, and to do so in a fraction of the time needed by the unpropelled balloon. The results show that using the Titan wind field allows an aerobot to significantly extend its scientific reach, and that a montgolfiere (unpropelled or propelled) is a highly desirable architecture that can very significantly enhance the scientific return of a future Titan mission.

aerobot↗

NASA NTRS2011

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Case, Jonathan L.↗

NASA NTRS2018

Comparisons of Bin and Bulk Microphysics Schemes in Simulations of Topographic Winter Precipitation with Radar and Radiometer Measurements

The Hebrew University Cloud Model (HUCM) bin scheme and the Thompson bulk scheme in the Weather Research and Forecasting (WRF) model are compared to assess biases often found in simulated brightness temperature and radar reflectivity. Compared to our preceding study that evaluated several bulk schemes in the WRF model, the current study obtains a reduction of the bias from excessive microwave scattering by precipitation ice for both HUCM bin and the Thompson bulk microphysics schemes for a topographic winter precipitation event associated with an atmospheric river. The Thompson particle size distributions (PSDs) and snow particle density assumption are implemented into the Goddard Satellite Data Simulator Unit (G‐SDSU) and have produced improvements. Despite the greater sophistication of the bin scheme in representing cloud and precipitation processes, the simulation with the Thompson bulk scheme is generally in better agreement with observations for this winter event. The explicitly resolved hydrometeor PSDs in HUCM enable analysis of mass spectra variations in response to changes in microphysics assumptions. Two HUCM sensitivity runs tested the enhancement of snow particle breakup and the influence of ice nuclei (IN) concentration. Higher IN concentration resulted in increased snow mass and broadened the spectrum toward small‐size particles. Modified snow mass spectra and resultant changes in graupel contributed to modifications in scattering and reflectivity simulations. The article demonstrates the bin scheme's capability to provide a new means to improve our understanding of uncertainties in mesoscale weather models and radiative transfer models.

microwave remote sensing↗

NASA NTRS2010

Evaluation of Enhanced High Resolution MODIS/AMSR-E SSTs and the Impact on Regional Weather Forecast

Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs, the discernable impacts on the WRF model were still somewhat limited. This paper explores several factors that may have contributed to this result. First, the original methodology to initialize the model used the most recent SST composite available in a hypothetical real ]time configuration, often matching the forecast initial time with an SST field that was 5-8 hours offset. To minimize the differences that result from the diurnal variations in SST, the previous day fs SST composite is incorporated at a time closest to the model initialization hour (e.g. 1600 UTC composite at 1500 UTC model initialization). Second, the diurnal change seen in the MODIS SST composites was not represented by the WRF model in previous simulations, since the SSTs were held constant throughout the model integration. To address this issue, we explore the use of a water skin-temperature diurnal cycle prediction capability within v3.1 of the WRF model to better represent fluctuations in marine surface forcing. Finally, the verification of the WRF model is limited to very few over-water sites, many of which are located near the coastlines. In order to measure the open ocean improvements from the AMSR-E, we could use an independent 2-dimensional, satellite-derived data set to validate the forecast model by applying an object-based verification method. Such a validation technique could aid in better understanding the benefits of the mesoscale SST spatial structure to regional models applications.

Schiferl, Luke D.↗

NASA NTRS2010

Extracting Space Weather Information from Research Models: Opportunities and Challenges

In addition to supporting space research in the international community, the Community Coordinated Modeling Center (CCMC) has as its second objective to apply the power of modern research models toward space weather specification and forecasting. Motivated by the objectives to test models and to ease the transition of research models to space weather forecasting organizations, the CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products for space weather forecasting support. Over time, these activities have produced tailored products for partners, as well as tools, which address the space weather needs of NASA's robotic mission community. All tools are accessible via a configurable, flexible interface. During this process, CCMC has accumulated substantial experience in understanding model performance, as well as in the design and execution of realtime systems. This presentation will focus on lessons learned and it will suggest low hanging fruit for transition to operations at partner agencies.

Hesse, Michael↗

NASA NTRS2011

Demonstrating the Operational Value of Atmospheric Infrared Sounder (AIRS) Retrieved Profiles in the Pre-Convective Environment

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One operational forecast challenge is forecasting convective weather in data-void regions such as large bodies of water (e.g. Gulf of Mexico). To address this forecast challenge, SPoRT produces a twice-daily three-dimensional analysis that blends a model first-guess from the Advanced Research Weather Research and Forecasting (WRF-ARW) model with retrieved profiles from the Atmospheric Infrared Sounder (AIRS) -- a hyperspectral sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. AIRS profiles are unique in that they give a three dimensional view of the atmosphere that is not available through the current rawinsonde network. AIRS has two overpass swaths across North America each day, one valid in the 0700-0900 UTC timeframe and the other in the 1900-2100 UTC timeframe. This is helpful because the rawinsonde network only has data from 0000 UTC and 1200 UTC at specific land-based locations. Comparing the AIRS analysis product with control analyses that include no AIRS data demonstrates the value of the retrieved profiles to situational awareness for the pre-convective (and convective) environment. In an attempt to verify that the AIRS analysis was a good representation of the vertical structure of the atmosphere, both the AIRS and control analyses are compared to a Rapid Update Cycle (RUC) analysis used by operational forecasters. Using guidance from operational forecasters, convective available potential energy (CAPE) was determined to be a vital variable in making convective forecasts and is used herein to demonstrate the utility of the AIRS profiles in changing the vertical thermodynamic structure of the atmosphere in the pre-convective and convective environment. CAPE is an important metric because of it is a quantitative measure of atmospheric stability, which is necessary information when forecasting for convective weather. Case studies from the summer of 2010 were examined, and most impact from the AIRS retrieved profiles occurred over the data-void Gulf of Mexico with fields of convective potential closer to the RUC than the CNTL. Mixed results were found when AIRS retrieved profiles were used over land, so more cases need to be examined to determine whether AIRS would be an effective tool over land. Additional analyses of problematic convective forecasts over the Gulf Coast will be needed to determine the operational impact of AIRS. SPoRT eventually plans to transition the AIRS product to select Weather Forecast Office (WFO) partners, pending the outcome of these additional analyses.

Kozlowski, Danielle M.↗

NASA NTRS2009

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.

Case, Jonathan L.↗

NASA NTRS2007

An Improved Bulk Microphysical Scheme for Studying Precipitation Processes: Comparisons with Other Schemes

Cloud microphysical processes play an important role in non-hydrostatic high-resolution simulations. Over the past decade both research and operational numerical weather prediction models have started using more complex cloud microphysical schemes that were originally developed for high-resolution cloud-resolving models. An improved bulk microphysical parameterization (adopted from the Goddard microphysics schemes) has recently implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options --- 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). In addition, this bulk microphysical parameterization is compared with WIRF's three other bulk microphysical schemes.

Tao, W. K.↗

NASA NTRS2013

Influences of Regional Climate Change on Air Quality Across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture regional-scale changes in temperatures and precipitation. We use a regional climate model (RCM) to dynamically downscale the GCM's large-scale signal to investigate the changes in regional and local extremes of temperature and precipitation that may result from a changing climate. In this paper, we show preliminary results from downscaling the NASA/GISS ModelE IPCC AR5 Representative Concentration Pathway (RCP) 6.0 scenario. We use the Weather Research and Forecasting (WRF) model as the RCM to downscale decadal time slices (1995-2005 and 2025-2035) and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0. The regional climate change scenario is further processed using the Community Multiscale Air Quality modeling system to explore influences of regional climate change on air quality.

Air quality control↗

NASA NTRS2007

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF: Comparisons with Other Schemes - Part 1

Advances in computing power allow atmospheric prediction models to be mn at progressively finer scales of resolution, using increasingly more sophisticated physical parameterizations and numerical methods. The representation of cloud microphysical processes is a key component of these models, over the past decade both research and operational numerical weather prediction models have started using more complex microphysical schemes that were originally developed for high-resolution cloud-resolving models (CRMs). A recent report to the United States Weather Research Program (USWRP) Science Steering Committee specifically calls for the replacement of implicit cumulus parameterization schemes with explicit bulk schemes in numerical weather prediction (NWP) as part of a community effort to improve quantitative precipitation forecasts (QPF). An improved Goddard bulk microphysical parameterization is implemented into a state-of the-art of next generation of Weather Research and Forecasting (WRF) model. High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atllan"ic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The 31CE scheme with a cloud ice-snow-hail configuration led to a better agreement with observation in terms of simulated narrow convective line and rainfall intensity. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 m/s). For an Atlantic hurricane case, varying the microphysical schemes had no significant impact on the track forecast but did affect the intensity (important for air-sea interaction)

Tao, W.-K.↗

NASA NTRS2014

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗

NASA NTRS2011

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

The degree of coupling between the land surface and PBL in NWP models remains largely undiagnosed due to the complex interactions and feedbacks present across a range of scales. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with observations during the summers of 2006/7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which enables a suite of PBL and land surface model (LSM) options along provides a flexible and high-resolution representation and initialization of land surface physics and states. This coupling is one component of a larger project to develop a NASA-Unified WRF (NU-WRF) system. A range of diagnostics exploring the feedbacks between soil moisture and precipitation are examined for the dry/wet extremes, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture.

Santanello, Joseph A., Jr.↗

NASA NTRS2012

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

Santanello, Joseph A., Jr.↗