Gary J. Jedlovec

Radiance and Jacobian Intercomparison of Radiative Transfer Models Applied to HIRS and AMSU Channels

The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: 7 HIRS (High-resolution Infrared Sounder) and 4 AMSU (advanced microwave sounding unit) channels. Interest in this topic was evident by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However, significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle or more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences.

Spatial and Temporal Varying Thresholds for Cloud Detection in GOES Imagery

A new cloud detection technique has been developed and applied to GOES-12 Imager data. The bispectral composite threshold (BCT) technique uses only the 11- and 3.9- channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single-pixel resolution. An innovative aspect of this algorithm is the use of 20-day composites of the 11- and the 11-3.9- channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection technique has been validated against a ldquotruthrdquo data set generated by the manual determination of the sky conditions from available satellite imagery for four seasons during 2003-2004. The day-and-night algorithm has been shown to determine the correct sky conditions 87.6% of the time (on average) over the eastern two-thirds of the U.S. and surroundings oceans. The incorrectly determined conditions arose from missing clouds 8.9% of the time or from overdetermining clouds 3.5% of the time. Nearly 82% of the misses came in the presence of low clouds. Only small variations in algorithm performance occurred between day-night, land-ocean, and between seasons. The algorithm performed best in the warmer seasons (90.9% correct during the summer versus 81.8% correct in the winter season) and during the day, when the solar illumination provides enhanced surface atmospheric cloud contrast in the infrared channels, and least well during the winter season. The algorithm was found to slightly underdetermine clouds at night and during times of low sun angle and tends to be cloud conservative during the day, particularly in the summertime.

A MODIS Sea Surface Temperature Composite for Regional Applications

Sea surface temperature (SST) is an important input for regional and global weather modeling, but timely high- resolution SST data from either in situ or satellite sources are limited. A regional near-real-time aqua moderate resolution imaging spectroradiometer (MODIS) 1-km-resolution SST composite has been developed by the NASA Short-term Prediction and Research Transition (SPoRT) program to provide continuous high-resolution SST fields twice daily for regional weather applications. The SPoRT Aqua MODIS SST composite is inter- compared to both half-degree-resolution real-time global (RTG) SST analysis and a 6-km-resolution geostationary operational environmental satellite 12 (GOES) Imager SST analysis and validated against buoy data for the month of May 2004. The SPoRT MODIS composite provides more accurate and detailed spatial information than the RTG-SST or GOES products during this period. Compared to limited buoy data, the daytime MODIS composites for May 2004 were found to have an average cool bias of -0.09degC, and the nighttime composites an average cool bias of -0.29degC, with both day and night composites having correlation values of approximately 0.90. A comparison of the MODIS SST composite to the more recent and higher resolution 12th-degree RTG-SST analysis and the 20th-degree resolution operational sea surface temperature and sea ice analysis indicated that the SPoRT MODIS composite provides additional spatial and diurnal cycle information on a regional scale.

An intercomparison of radiation codes for retrieving upper-tropospheric humidity in the 6.3-μm band: A report from the first GVaP workshop

Abstract An intercomparison of radiation codes used in retrieving upper–tropospheric humidity (UTH) from observations in the n2 (6.3 mm) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the Global Energy and Water Cycle Experiment Water Vapor Project to assess our ability to monitor the distribution and variations of upper–tropospheric moisture from spaceborne sensors. A total of 23 different codes, ranging from detailed line–by–line (LBL) models, to coarser–resolution narrowband (NB) models, to highly parameterized single–band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature(Tb). The majority of NB and SB models ag...

THE GOES-R PROVING GROUND Accelerating User Readiness for the Next-Generation Geostationary Environmental Satellite System

The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground engages the National Weather Service (NWS) forecast, watch, and warning community and other agency users in preoperational demonstrations of the new and advanced capabilities to be available from GOES-R compared to the current GOES constellation. GOES-R will provide significant advances in observing capabilities but will also offer a significant challenge to ensure that users are ready to exploit the new 16-channel imager that will provide 3 times more spectral information, 4 times the spatial coverage, and 5 times the temporal resolution compared to the current imager. In addition, a geostationary lightning mapper will provide continuous and near-uniform real-time surveillance of total lightning activity throughout the Americas and adjacent oceans encompassing much of the Western Hemisphere. To ensure user readiness, forecasters and other users must have access to prototype advanced products within their operational en...

NPOESS: Next-Generation Operational Global Earth Observations

Abstract The United States is merging its two polar-orbiting operational environmental satellite programs operated by the Department of Commerce and the Department of Defense into a single system, which is called the National Polar-orbiting Operational Environmental Satellite System (NPOESS). During the next decade, NPOESS will provide global operational data to meet many of the needs of weather forecasters, climate researchers, and global decision makers for remotely sensed Earth science data and global environmental monitoring. The NPOESS Preparatory Project (NPP) will be launched in 2011 as a precursor to NPOESS to reduce final development risks for NPOESS and to provide continuity of global imaging and atmospheric sounding data from the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) missions. Beginning in 2014, NPOESS spacecraft will be launched into an afternoon orbit and in 2016 into an early-morning orbit to provide significantly improved operational capabilities ...

The Emergence of Weather-Related Test Beds Linking Research and Forecasting Operations

Test beds have emerged as a critical mechanism linking weather research with forecasting operations. The U.S. Weather Research Program (USWRP) was formed in the 1990s to help identify key gaps in research related to major weather prediction problems and the role of observations and numerical models. This planning effort ultimately revealed the need for greater capacity and new approaches to improve the connectivity between the research and forecasting enterprise. Out of this developed the seeds for what is now termed “test beds.” While many individual projects, and even more broadly the NOAA/National Weather Service (NWS) Modernization, were successful in advancing weather prediction services, it was recognized that specific forecast problems warranted a more focused and elevated level of effort. The USWRP helped develop these concepts with science teams and provided seed funding for several of the test beds described. Based on the varying NOAA mission requirements for forecasting, differences in the orga...

Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State

AbstractIt is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high-resolution models. This paper presents model verification results of a case study period from June to August 2008 over the southeastern United States using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the National Aeronautics and Space Administration’s (NASA) Land Information System (LIS) and sea surface temperatures (SSTs) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction’s (NCEP) 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a...

Detection of Storm Damage Tracks with EOS Data

Abstract The damage surveys conducted by the NWS in the aftermath of a reported tornadic event are used to document the location of the tornado ground damage track (pathlength and width) and an estimation of the tornado intensity. This study explores the possibility of using near-real-time medium and high spatial resolution satellite imagery from the NASA Earth Observing System satellites to provide additional information for the surveys. Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data were used to study the damage tracks from three tornadic storms: the La Plata, Maryland, storm of 28 April 2002 and the Ellsinore and Marquand, Missouri, storms of 24 April 2002. These storms varied in intensity and occurred over regions with significantly different land cover. It was found that, depending on the nature of the land cover, tornado damage tracks from intense storms (F1 or greater) and hail storms may be evident in ASTER, La...

A Real-Time MODIS Vegetation Product for Land Surface and Numerical Weather Prediction Models

A technique is presented to produce real-time, daily vegetation composites at 0.01 ° resolution ( ~ 1 km) over the Conterminous United States (CONUS) for use in the NASA Land Information System (LIS) and weather prediction models. Green vegetation fraction (GVF) is derived from direct-broadcast swaths of normalized difference vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the NASA Earth Observing System satellites. The real-time data and increased resolution compared to the 0.144 ° ( ~ 16 km) resolution monthly GVF climatology in community models result in an improved representation of vegetation in high-resolution models, especially in complex terrain. The MODIS GVF fields show seasonal variations that are similar to the community model climatology, and respond realistically to temperature and precipitation anomalies. The wet spring and summer 2010 over the U.S. Plains led to higher regional GVF than in the climatology. The GVF substantially decreased over the U.S. Southern Plains from 2010 to 2011, consistent with the transition to extreme drought in summer 2011. LIS simulations depict substantial sensitivity to the MODIS GVF, with regional changes in heat fluxes around 100 Wm-2 over the northern U.S. in June 2010. CONUS LIS simulations during the 2010 warm season indicate that the larger MODIS GVF in the western U.S. led to higher latent heat fluxes and initially lower sensible heat fluxes, with a net drying effect on the soil. With time, the drier soil eventually lead to higher mean sensible heat fluxes such that the total surface energy output increased by late summer 2010 over the western U.S. A sensitivity simulation of a severe weather event using real-time MODIS GVF data results in systematic changes to low-level temperature, moisture, and instability fields, and improves the evolution of simulated precipitation.