Short and Associates Inc.

Chevy Chase, MD, United States

Short and Associates Inc.

Chevy Chase, MD, United States
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Gallo K.,The Center for Satellite Applications and Research | Hale R.,Cooperative Institute for Research in the Atmosphere | Tarpley D.,Short and Associates Inc. | Yu Y.,The Center for Satellite Applications and Research
Journal of Applied Meteorology and Climatology | Year: 2011

Clear and cloudy daytime comparisons of land surface temperature (LST) and air temperature (Tair) were made for 14 stations included in the U.S. Climate Reference Network (USCRN) of stations from observations made from 2003 through 2008. Generally, LST was greater than Tair for both the clear and cloudy conditions; however, the differences between LST and Tair were significantly less for the cloudy-sky conditions. In addition, the relationships between LST and Tair displayed less variability under the cloudy-sky conditions than under clear-sky conditions. Wind speed, time of the observation of Tair and LST, season, the occurrence of precipitation at the time of observation, and normalized difference vegetation index values were all considered in the evaluation of the relationship between Tair and LST. Mean differences between LST and Tair of less than 2°C were observed under cloudy conditions for the stations, as compared with a minimum difference of greater than 2°C (and as great as 7+°C) for the clear-sky conditions. Under cloudy conditions, Tair alone explained over 94%-and as great as 98%-of the variance observed in LST for the stations included in this analysis, as compared with a range of 81%-93% for clear-sky conditions. Because of the relatively homogeneous land surface characteristics encouraged in the immediate vicinity of USCRN stations, and potential regional differences in surface features that might influence the observed relationships, additional analyses of the relationships between LST and Tair for additional regions and land surface conditions are recommended. © 2011 American Meteorological Society.

Goodman S.J.,NASA | Gurka J.,NASA | De Maria M.,The Center for Satellite Applications and Research | Schmit T.J.,The Center for Satellite Applications and Research | And 9 more authors.
Bulletin of the American Meteorological Society | Year: 2012

The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground (PG) is an initiative to accelerate user readiness for the next generation of US geostationary environmental satellites. The GOES-R PG program enables the transition from research to operations with the principal emphasis on National Oceanic and Atmospheric Administration's (NOAA) operational forecast office environment. The GOES-R PG principal collaboration for severe convective weather occurs within NOAA's HWT and Storm Prediction Center (SPC) in Norman, Oklahoma. The Satellite-Based Convection Analysis and Tracking (SATCAST) is a proxy for the AWG version of the GOES-R CI algorithm. Simulated GOES-R ABI imagery and band differences generated from the NSSL WRF 0000 UTC 4-km model run are provided by CIMSS and CIRA for display within the HWT National Advanced Weather Information Processing System (NAWIPS).

Hale R.C.,Colorado State University | Gallo K.P.,The Center for Satellite Applications and Research | Tarpley D.,Short and Associates Inc. | Yu Y.,The Center for Satellite Applications and Research
Remote Sensing Letters | Year: 2011

Calibration and validation (cal/val) of data derived from satellite-based instruments is critical to providing accurate global measurements of environmental variables at useful spatial and temporal resolutions. In this letter, statistical models based on linear regressions employing various predictor variables were utilized to elucidate appropriate methods of characterizing variability near ground sites that might be used for calibration and validation. Regressions based on more complex statistics performed no better than those based on easily derived statistics, and the regression relations provided valuable information for assessing the potential quality of satellite-based measures of land surface temperature. © 2011 Taylor & Francis.

Vinnikov K.Y.,University of Maryland University College | Yu Y.,National Oceanic and Atmospheric Administration | Goldberg M.D.,National Oceanic and Atmospheric Administration | Chen M.,National Oceanic and Atmospheric Administration | Tarpley D.,Short and Associates Inc.
Journal of Geophysical Research: Atmospheres | Year: 2011

Scales of temporal and spatial variability of clear-sky land surface temperature (LST) in middle latitudes are empirically evaluated using data from satellite and land surface observations. We consider separately the time-dependent expected value, its spatial variations, weather-related temporal and spatial anomalies, and errors of LST observation. Seasonal and diurnal cycles in the time-dependent expected value of LST are found to be the main components of temporal variations of clear-sky LST. The scale of spatial variability in the expected value of LST is found to be much smaller than the scale of spatial variability of the weather-related signal. The scale of temporal autocorrelation of weather-related LST variations is found to be in a good agreement with our earlier preliminary estimate and equal to 3 d, which corresponds to the time scale of weather system variations. This weather-related signal in clear-sky LST is statistically the same as in surface air temperature (SAT) observations at regular meteorological stations. The scale of spatial autocorrelation of weather-related LST variations exceeds 1000 km, which is the spatial scale of synoptic weather systems. These estimates provide us with a basis for better understanding and interpretation of LST observations from past, current, and future geostationary satellites and polar orbiters. Copyright 2011 by the American Geophysical Union.

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