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Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Kakar, Ramesh↗

TPSAS-NF1676L-28151-DND

The proposed suborbital mission is to collect and analyze observations to help improve our ability to model and forecast these crucial monsoonal transports and their downstream effects. The objectives are 1) to observe and relate convective-scale to meso-scale changes in the three-dimensional circulation with the efficiency of the resulting convective transports (of air mass and heat) and the build-up of the large-scale anomalies, as they are modulated by the three-dimensional structure of the aerosol loading; and 2) to observe how fluctuations in the monsoon large-scale upper-level outflow affect downstream convection, especially within AEWs. The observations will be tailor-made to help understand the controls of the northward march of the monsoon isochrones, the initiation and magnitude of heat towers over the subcontinent during the monsoon, and how the mostly zonal land-sea differential heating interacts with the meridional progress of the Intertropical Convergence Zone (ITCZ) to constrain the intensities of the northern and western outflows. Unique contributions will be made by two airborne instruments, operated in concert: NASA-LARC's Doppler Aerosol Wind Lidar (DAWN) coherent-detection wind lidar which uses a pulsed laser with a wavelength of about two microns to measure vertical profiles of the three dimensional components of the wind field, and JPL's Airborne Second Generation Precipitation Radar (APR-2) precipitation radar which measures the three-dimensional structure of rain within a swath that is about10km wide (depending on the altitude of the plane) and extends from flight level down to the surface.

Upendra N Singh↗

Enhanced Monitoring and Forecasting of South Asian Air Quality Episodes with Multi-Sensor Satellite Products and Dispersion Modeling

Air pollution and particulates represent a serious environmental, public health, and overarching societal concern in the Hindu Kush Himalaya (HKH) region of south-central Asia, especially during the boreal winter and spring months. Frequent contributors to poor air quality of the region include dust and particulate matter transport from the Middle East region and western India, persistent nocturnal fog and smog during the stable dry monsoon months, and biomass burning during the pre-monsoon months of boreal spring. Nocturnal and multi-day persistent stable fog and smog events can occur during the stable conditions of the dry monsoon months that lead to hazardous visibility reductions (e.g., at major airports such as Delhi, India)and poor air quality, particularly in urban corridors.Our project goal is therefore to design and implement a robust air quality and chemistry observation and modeling system using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. This system effectively assimilates aerosol and trace gas retrievals from geostationary and polar-orbiting satellites to advance the monitoring and prediction capabilities of air quality and visibility reductions throughout the HKH region. For this presentation, we highlight several[multi-spectral] geostationary satellite products and dispersion modeling capabilities being developed and implemented for improved situational awareness and forecasting of air quality episodes.Launched in December 2018, the Advanced Meteorological Imager (AMI) aboard the Geostationary-Korean Multi-Purpose Satellite-2A (GEO-KOMPSAT-2A, or GK2A) provides 16 channels of multi-spectral information similar to the U.S. GOES-16/17 satellites. Proven community recipes for generating multi-spectral Red-Green-Blue (RGB) composite products to detect specific meteorological phenomena are applied to the AMI data for the HKH region. We implemented four such RGB products consisting of truecolor with Rayleigh correction to aid in smoke detection; dust RGB for monitoring larger particulate matter; nighttime microphysics for fog/smog detection;and natural color fire RGB and the shortwave 3.8 micron channel for fire hot-spot detection.We additionally configured HYSPLIT for dust/sand dispersion and concentration forecasts over HKH. The HYSPLIT dispersion simulations are initially being conducted with two different methodologies: (1) dust/sand lofting based on initializing plume releases from visual inspection of the dust RGB imagery; and (2) dust/sand release and dispersion using the internal HYSPLIT algorithm that determines lofting from input wind speeds and prescribed land use. The goal is to develop a near real-time HYSPLIT modeling solution for routinely simulating the transport and dispersion of dust plumes across the HKH region. This presentation illustrates these products and capabilities for various use cases from the 2019 to 2021 period, highlighting a particularly unhealthy episode during late March 2021 across Nepal.

Remote Sensing↗

Combining New Satellite Tools and Models to Examine Role of Mesoscale Interactions in Formation and Intensification of Tropical Cyclones

The objective of this research is to start filling the mesoscale gap to improve understanding and probability forecasts of formation and intensity variations of tropical cyclones. Sampling by aircraft equipped to measure mesoscale processes is expensive, thus confined in place and time. Hence we turn to satellite products. This paper reports preliminary results of a tropical cyclone genesis and early intensification study. We explore the role of mesoscale processes using a combination of products from TRMM, QuikSCAT, AMSU, also SSM/I, geosynchronous and model output. Major emphasis is on the role of merging mesoscale vortices. These initially form in midlevel stratiform cloud. When they form in regions of lowered Rossby radius of deformation (strong background vorticity) the mesoscale vortices can last long enough to interact and merge, with the weaker vortex losing vorticity to the stronger, which can then extend down to the surface. In an earlier cyclongenesis case (Oliver 1993) off Australia, intense deep convection occurred when the stronger vortex reached the surface; this vortex became the storm center while the weaker vortex was sheared out as the major rainband. In our study of Atlantic tropical cyclones originating from African waves, we use QuikSCAT to examine surface winds in the African monsoon trough and in the vortices which move westward off the coast, which may or may not undergo genesis (defined by NHC as reaching TD, or tropical depression, with a west wind to the south of the surface low). We use AMSU mainly to examine development of warm cores. TRMM passive microwave TMI is used with SSM/I to look at the rain structure, which often indicates eye formation, and to look at the ice scattering signatures of deep convection. The TRMM precipitation radar, PR, when available, gives precipitation cross sections. So far we have detailed studies of two African-origin cyclones, one which became severe hurricane Floyd 1999, and the other reached TD2 in June 2000 and then died out. The atmosphere off West African is dry and stable. It becomes less so between June and September, as the SST and convection heat up. QuikSCAT shows the African monsoon trough and shear zone extend westward over the ocean to nearly 30 degrees West. The evidence is strong that the two cyclones had in common multiple midlevel mergers, which extended to the surface keeping the surface vortex strong. These continued until both systems were designated TD's by NHC. In the June 2000 case, the main reason for failure was the lower SST and dry, stable atmosphere. This is shown by the comparison of the equivalent potential temperature maps and profiles with those from pre-Floyd. In the vortex which became Floyd, QuikSCAT shows continuous importation of high theta e (warm, moist) air from the south. From September 2-8, this air flowed around the vortex center, building up a high theta-e pool to the north. Then late on September 9, a 100-km wide jet of high theta-e air penetrated the vortex core, a major convective burst' was observed, and an intensifying, more elevated warm core was seen on AMSU. Rapid pressure fall and wind intensification were underway by 0000 UTC on September 10. Floyd became a Hurricane at 1200 UTC on Sept 10, 1999, with successive convective bursts running the hurricane thermodynamic engine by intensifying the warm core. TD2 was a strong African vortex, sustained by moderate convection (up to about 12.5 km) offshore of Africa. It peaked on June 23, showing an apparent "eye" on passive microwave composites. However, it could not assemble the ingredients for a convective burst. Thus it failed to get the thermodynamic hurricane engine going before it moved too far west of the region of lowered Rossby radius. By June 26, cloud systems were dying out. On June 25, a surface vortex was no longer seen on QuikSCAT, although one continued above the surface on model profiles until June 27. One of our main findings so far is showing the role of the mesoscale vortex interactions in sustaining some African vortices far out in to the mid Atlantic, where under adequate thermal/moisture conditions the hurricane heat engine can sometimes be started. We are working on similar studies of Cindy and Irene 1999. Cindy illustrates a case of wind shear working against an early-stage hurricane heat engine, while Irene formed from a Caribbean wave. An enormous value of combinations of satellite tools is that tropical cyclones can be studied in all parts of the global oceans where they occur. Detailed studies like ours are labor intensive but many statistical studies can be based on physical postulates developed. There are other new tools such as MODIS on TERRA of the Earth Observing System (EOS) which can be used to study the microphysics of tropical cyclones world wide, in particular to investigate the presence of mixed phase and the impact of atmospheric aerosols on the hydrometeor structure and rainfall from tropical cyclones.

Simpson, Joanne↗

Improved Ionospheric Electrodynamic Models and Application to Calculating Joule Heating Rates

Improved techniques have been developed for empirical modeling of the high-latitude electric potentials and magnetic field aligned currents (FAC) as a function of the solar wind parameters. The FAC model is constructed using scalar magnetic Euler potentials, and functions as a twin to the electric potential model. The improved models have more accurate field values as well as more accurate boundary locations. Non-linear saturation effects in the solar wind-magnetosphere coupling are also better reproduced. The models are constructed using a hybrid technique, which has spherical harmonic functions only within a small area at the pole. At lower latitudes the potentials are constructed from multiple Fourier series functions of longitude, at discrete latitudinal steps. It is shown that the two models can be used together in order to calculate the total Poynting flux and Joule heating in the ionosphere. An additional model of the ionospheric conductivity is not required in order to obtain the ionospheric currents and Joule heating, as the conductivity variations as a function of the solar inclination are implicitly contained within the FAC model's data. The models outputs are shown for various input conditions, as well as compared with satellite measurements. The calculations of the total Joule heating are compared with results obtained by the inversion of ground-based magnetometer measurements. Like their predecessors, these empirical models should continue to be a useful research and forecast tools.

Weimer, D. R.↗

Effects of Spatial Resolution on the Simulated Dust Aerosol Lifecycle: Implications for Dust Event Magnitude and Timing in the NASA GEOS-5 AGCM

The NASA GEOS-5 atmospheric transport model simulates global aerosol distributions with an online aerosol module. GEOS-5 may be run at various horizontal spatial resolutions depending on the research application. For example, long integration climate simulations are typically run at 2 deg or 1 deg grid spacing, whereas aerosol reanalysis and forecasting applications may be performed at O.5 deg or 0.25 deg resolutions. In this study, we assess the implications of varying spatial resolution on the simulated aerosol fields, with a particular focus on dust. Dust emissions in GEOS-5 are calculated with one of two parameterizations, one based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GO CART) model and another based on the Dust Entrainment and Deposition (DEAD) model. Emission fluxes are parameterized in terms of the surface wind speed, either the 10-m (GO CART) or friction (DEAD) wind speed. We consider how surface wind speeds and thus the dust emission rates are a function of the model spatial resolution. We find that spatial resolution has a significant effect on the magnitude of dust emissions, as higher resolution versions of the model have typically higher surface wind speeds. Utilizing space-borne observations from MISR, MODIS, and CALIOP, we find that simulated Aerosol Optical Thickness (AOT) distributions respond differently to spatial resolution over the African and Asian source regions, highlighting the need to regional dust emission tuning. When compared to ground-based observations from AERONET, we found improved timing of dust events with as spatial resolution was increased. In an attempt to improve the representation of the dust aerosol lifecycle at coarse resolutions, we found that incorporating the effects of sub-grid wind variability in a course resolution simulation led to improved agreement with observed AOT magnitudes, but did not impact the timing of simulated dust events.

Nowottnick, E.↗

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the realtime airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft using the operational airborne Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (~ 3 x the aircraft altitude). The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a detailed numerical model, and those results are used to construct H*Wind analyses. The H*Wind analysis, a product of the Hurricane Research Division of NOAA s Atlantic Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa.gov/hrd/data_sub/wind.html. Evaluations will be presented on the impact of the HIRAD instrument on H*Wind analyses, both in terms of adding it to the full suite of current measurements, as well as using it to replace instrument(s) that may not be functioning at the future time the HIRAD instrument is deployed. Plans to demonstrate the potential for HIRAD to improve numerical weather prediction of hurricanes will also be presented.

Miller, Timothy↗

Seafloor Control on Sea Ice

The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

Nghiem, S. V.↗

Anomalous Heat Budgets in the Interior Pacific Ocean on Seasonal- to -Timescales and Gyre Spacescales

This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage over the Pacific Ocean from 20 degrees S to 60 degrees N through the synthesis of World Ocean Circulation Experiment (WOCE) products over 7 years from 1993-1999. We utilize WOCE reanalysis products from the following sources: diabatic heat storage (DHS) from the Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from the Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). We interpolate these products onto a common grid, allowing the seasonal cycle of DHS to be modeled for comparison with that observed. Everywhere latent heat flux residuals dominate sensible heat flux residuals and shortwave heat flux residuals dominate longwave heat flux residuals, both comparable in magnitude to the residual horizontal heat advection. We find the root-mean-square (RMS) of the differences between observed and model residual DHS tendencies to be less than 15 W per square meters everywhere except in the Kuroshio extension. Comparable COADS and NCEP products perform better than ECMWF products in the extra-tropics, while the NCEP product performs best in the tropics. Radiative and turbulent air-sea heat flux residuals computed from ship-born measurements perform better than those computed from satellite cloud and wind measurements. Since the RMS differences derive largely from biases in measured wind speed and cloud fraction, least-squares minimization is used to correct the residual Ekman heat advection and air-sea heat flux. Minimization reduces RMS differences less than 5 W per square meters except in the Kuroshio extension, suggesting how winds, clouds, and exchange coefficients in the NCEP, ECMWF, and ESR products can be improved.

White, Warren↗

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

weather research and forecasting ===== The NASA Short‐term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2‐km northwestern‐hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra‐tropical cyclones with intense non‐convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified‐WRF (NU‐WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real‐time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU‐WRF, EMS, LIS, and GSI.

Case, Jonathan L.↗

Regional-Scale Modeling at NASA Goddard Space Flight Center

Over the past decade, the Goddard Mesoscale Modeling and Dynamics Group has used a popular regional scale model, MM5, to study precipitation processes. Our group is making contributions to the MM5 by incorporating the following physical and numerical packages: improved Goddard cloud processes, a land processes model (Parameterization for Land-Atmosphere-Cloud Exchange - PLACE), efficient but sophisticated radiative processes, conservation of hydrometeor mass (water budget), four-dimensional data assimilation for rainfall, and better computational methods for trace gas transport. At NASA Goddard, the MM5 has been used to study: (1) the impact of initial conditions, assimilation of satellite-derived rainfall, and cumulus parameterizations on rapidly intensifying oceanic cyclones, hurricanes and typhoons, (2) the dynamic and thermodynamic processes associated with the development of narrow cold frontal rainbands, (3) regional climate and water cycles, (4) the impact of vertical transport by clouds and lightning on trace gas distributiodproduction associated with South and North American mesoscale convective systems, (5) the development of a westerly wind burst (WWB) that occurred during the TOGA COARE and the diurnal variation of precipitation in the tropics, (6) a Florida sea breeze convective event and a Mid-US flood event using a sophisticated land surface model, (7) the influence of soil heterogeneity on land surface energy balance in the southwest GCIP region, (8) explicit simulations (with 1.33 to 4 km horizontal resolution) of hurricanes Bob (1991) and Bonnie (1998), (9) a heavy precipitation event over Taiwan, and (10) to make real time forecasts for a major NASA field program. In this paper, the modifications and simulated cases will be described and discussed.

Tao, W.-K.↗

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters : Synthetic Sensor Radiance Formulation - Pt. 1

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Simulations↗

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters: Equivalent Sensor Radiance Formulation - Part 1

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Simulations↗

The LATEST Project: Operational Assessment of Total Lightning Data in the U.S.

A government, university, and industry alliance has joined forces to transition total lightning observations from ground-based research networks and NASA satellites (LIS/TRMM) to improve the short range prediction of severe weather. This interest builds on the desire of the U.S Weather Research Program to foster a national Nowcasting Test Bed, with this specific transition activity initiated through the NASA short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL. A kick-off national workshop sponsored by the SPoRT Center was held in Huntsville April 1-2 to identify the common goals and objectives of the research and operational community, and to assign roles and responsibilities within the alliance. The workshop agenda, presentations, and summary are available at the SPoRT Center Web site ( h h under the "Meetings" tab. The next national workshop is planned for 2005 in Dallas, TX. The NASA North Alabama regional Lightning Mapping Array &MA) has been operational in the Huntsville area for 3 years, and has continuously sampled a variety of severe weather systems during that period. A gridded version of the LMA total lightning data is currently being supplied to National Weather Service offices in Huntsville, Nashville and Birmingham through the NWS AWES decision support system, for the purposes of assessing the utility of the data in the nowcasting of severe weather such as tornadoes, damaging straight line winds, flash flooding and other weather hazards (lightning induced forest fires, microbursts). While the raw LMA data have been useful to NWS forecasters, even greater utility would be realized if higher-order data products could be supplied through AWIPS along with the gridded data over a larger domain. In 2003-2004 additional LMA systems have been deployed across the southern US. from Florida to New Mexico, providing an opportunity for more than 20 NWS forecast offices to evaluate the incremental value of total lightning data in the warning decision making process.

Goodman, Steven↗

Analyses and forecasts with LAWS winds

Horizontal fluxes of atmospheric water vapor are studied for summer months during 1989 and 1992 over North and South America based on analyses from European Center for Medium Range Weather Forecasts, US National Meteorological Center, and United Kingdom Meteorological Office. The calculations are performed over 20 deg by 20 deg box-shaped midlatitude domains located to the east of the Rocky Mountains in North America, and to the east of the Andes Mountains in South America. The fluxes are determined from operational center gridded analyses of wind and moisture. Differences in the monthly mean moisture flux divergence determined from these analyses are as large as 7 cm/month precipitable water equivalent over South America, and 3 cm/month over North America. Gridded analyses at higher spatial and temporal resolution exhibit better agreement in the moisture budget study. However, significant discrepancies of the moisture flux divergence computed from different gridded analyses still exist. The conclusion is more pessimistic than Rasmusson's estimate based on station data. Further analysis reveals that the most significant sources of error result from model surface elevation fields, gaps in the data archive, and uncertainties in the wind and specific humidity analyses. Uncertainties in the wind analyses are the most important problem. The low-level jets, in particular, are substantially different in the different data archives. Part of the reason for this may be due to the way the different analysis models parameterized physical processes affecting low-level jets. The results support the inference that the noise/signal ratio of the moisture budget may be improved more rapidly by providing better wind observations and analyses than by providing better moisture data.

Wang, Muyin↗

Impact of Lake Okeechobee Sea Surface Temperatures on Numerical Predictions of Summertime Convective Systems over South Florida

The NASA Short-term Prediction Research and Transition (SPoRT) Center, the Florida Institute of Technology, and the NOAA/NWS Weather Forecast Office at Miami, FL (MFL) are collaborating on a project to investigate the impact of using high-resolution, 2-km Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composites within the Weather Research and Forecasting (WRF) prediction system. The NWS MFL is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run daily initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution. The project objective is to determine whether more accurate specification of the lower-boundary forcing over water using the MODIS SST composites within the 4-km WRF runs will result in improved sea fluxes and hence, more accurate e\~olutiono f coastal mesoscale circulations and the associated sensible weather elements. SPoRT conducted parallel WRF EMS runs from February to August 2007 identical to the operational runs at NWS MFL except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. During the course of this evaluation, an intriguing case was examined from 6 May 2007, in which lake breezes and convection around Lake Okeechobee evolved quite differently when using the high-resolution SPoRT MODIS SST composites versus the lower-resolution RTG SSTs. This paper will analyze the differences in the 6 May simulations, as well as examine other cases from the summer 2007 in which the WRF-simulated Lake Okeechobee breezes evolved differently due to the SST initialization. The effects on wind fields and precipitation systems will be emphasized, including validation against surface mesonet observations and Stage IV precipitation grids.

Case, Jonathan L.↗

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

In order to support research on optimal data assimilation methods for the Cyclone Global Navigation Satellite System (CYGNSS), launching in 2016, work has been ongoing to produce a high‐resolution merged wind dataset for the Dynamics of the Madden Julian Oscillation (DYNAMO) field campaign, which took place during late 2011/early 2012. The winds are produced by assimilating DYNAMO observations into the Weather Research and Forecasting (WRF) three‐dimensional variational (3DVAR) system. Data sources from the DYNAMO campaign include the upper‐air sounding network, radial velocities from the radar network, vector winds from the Advanced Scatterometer (ASCAT) and Oceansat‐2 Scatterometer (OSCAT) satellite instruments, the NOAA High Resolution Doppler Lidar (HRDL), and several others. In order the prep them for 3DVAR, significant additional quality control work is being done for the currently available TOGA and SMART‐R radar datasets, including automatically dealiasing radial velocities and correcting for intermittent TOGA antenna azimuth angle errors. The assimilated winds are being made available as model output fields from WRF on two separate grids with different horizontal resolutions ‐ a 3‐km grid focusing on the main DYNAMO quadrilateral (i.e., Gan Island, the R/V Revelle, the R/V Mirai, and Diego Garcia), and a 1‐km grid focusing on the Revelle. The wind dataset is focused on three separate approximately 2‐week periods during the Madden Julian Oscillation (MJO) onsets that occurred in October, November, and December 2011. Work is ongoing to convert the 10‐m surface winds from these model fields to simulated CYGNSS observations using the CYGNSS End‐To‐End Simulator (E2ES), and these simulated satellite observations are being compared to radar observations of DYNAMO precipitation systems to document the anticipated ability of CYGNSS to provide information on the relationships between surface winds and oceanic precipitation at the mesoscale level. This research will improve our understanding of the future utility of CYGNSS for documenting key MJO processes.

Lang, Timothy J.↗