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- Author or Editor: J. D. Tarpley x
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Abstract
A 6-year(1980–85)set of GOES data for seven sites in Kansas has been analyzed to determine the climatological characteristics of surface heating. The dataset as described, and procedures for automatically screening out cloudy observations are outlined. Morning surface heating between 0900 and 1200 LST is found to have distinctive seasonal and geographical variations that are related to climatological conditions at the surface. Conventional weather observations at Dodge City, Kansas, that were coincident with the satellite observations are used to relate the satellite-observed surface heating with meteorological conditions and soil moisture. Statistically significant relations between morning surface heating and soil moisture are observed, with higher heating rates occurring under dry conditions. Average surface heating is lower on days with higher than average wind speeds.
Abstract
A 6-year(1980–85)set of GOES data for seven sites in Kansas has been analyzed to determine the climatological characteristics of surface heating. The dataset as described, and procedures for automatically screening out cloudy observations are outlined. Morning surface heating between 0900 and 1200 LST is found to have distinctive seasonal and geographical variations that are related to climatological conditions at the surface. Conventional weather observations at Dodge City, Kansas, that were coincident with the satellite observations are used to relate the satellite-observed surface heating with meteorological conditions and soil moisture. Statistically significant relations between morning surface heating and soil moisture are observed, with higher heating rates occurring under dry conditions. Average surface heating is lower on days with higher than average wind speeds.
Abstract
Solar radiant energy incident at the earth's surface is a quantity of increasing importance in agricultural monitoring and solar power development. An experiment was undertaken in the summer of 1977 to determine if incoming visible radiation at the surface could be estimated from geostationary meteorological satellite data. The experiment entailed the collection of coincident satellite, conventional meteorological and pyranometer data over the Great Plains of the United States. Regression techniques were used to estimate hourly insolation from the satellite data. Hourly estimates were summed to give daily total insolation. The standard error of the satellite-derived daily insolation when compared against pyranometers was 10% of the mean, an accuracy more than sufficient for most agricultural uses. Problems of producing insolation operationally from both geostationary and polar-orbiting satellites are discussed.
Abstract
Solar radiant energy incident at the earth's surface is a quantity of increasing importance in agricultural monitoring and solar power development. An experiment was undertaken in the summer of 1977 to determine if incoming visible radiation at the surface could be estimated from geostationary meteorological satellite data. The experiment entailed the collection of coincident satellite, conventional meteorological and pyranometer data over the Great Plains of the United States. Regression techniques were used to estimate hourly insolation from the satellite data. Hourly estimates were summed to give daily total insolation. The standard error of the satellite-derived daily insolation when compared against pyranometers was 10% of the mean, an accuracy more than sufficient for most agricultural uses. Problems of producing insolation operationally from both geostationary and polar-orbiting satellites are discussed.
Abstract
Monthly mean satellite measurements of surface heating rate, surface temperature, and normalized difference vegetation index were collected for seven locations in Kansas. These were combined with monthly average surface observations and used in a surface energy balance model to estimate monthly mean evapotranspiration at each site. The modeled evapotranspiration and surface energy fluxes are reasonable. The nature of the surface energy balance model is such that it can be solved with satellite measurements and numerical weather forecast model output alone. This suggests that large-scale evapotranspiration climatologies can be made without in situ observations.
Abstract
Monthly mean satellite measurements of surface heating rate, surface temperature, and normalized difference vegetation index were collected for seven locations in Kansas. These were combined with monthly average surface observations and used in a surface energy balance model to estimate monthly mean evapotranspiration at each site. The modeled evapotranspiration and surface energy fluxes are reasonable. The nature of the surface energy balance model is such that it can be solved with satellite measurements and numerical weather forecast model output alone. This suggests that large-scale evapotranspiration climatologies can be made without in situ observations.
Abstract
In an earlier study, Pinker et al. have shown that the daily average net radiation at the top of the atmosphere is highly correlated with the daily average net radiation at the surface. A regression formalism was derived and tested on independent datasets; it proved to yield estimates of net radiation to accuracies required for climate studies. The objective of the present paper has been to simplify the regression approach for deriving surface net radiation from satellite observations. It was found that the scene brightness alone, as sensed by the GOES satellite, can serve as a predictor of the net radiation at the surface.
Abstract
In an earlier study, Pinker et al. have shown that the daily average net radiation at the top of the atmosphere is highly correlated with the daily average net radiation at the surface. A regression formalism was derived and tested on independent datasets; it proved to yield estimates of net radiation to accuracies required for climate studies. The objective of the present paper has been to simplify the regression approach for deriving surface net radiation from satellite observations. It was found that the scene brightness alone, as sensed by the GOES satellite, can serve as a predictor of the net radiation at the surface.
Abstract
As a first step in the development of a technique for estimating daily maximum and minimum shelter temperatures for agricultural monitoring, this study made use of operational satellite sounder data to estimate shelter temperature. Linear regression methods were used with a ground-truth data set of surface observations matched against data from operationally derived soundings. Regression estimates based solely on temperature predictors from the satellite soundings yielded residual standard deviations of 1.6–2.6 K for the NOAA-6 and NOAA-7 clear and partly cloudy retrievals. Regressions for cloudy conditions based only on the microwave retrievals had errors ranging from 2.9–4.0 K. Shelter temperatures estimated by regression have errors somewhat smaller than those reported for the lower levels of the atmospheric soundings. This suggests that satellite temperature soundings near the surface are more accurate than previous studies indicate.
Abstract
As a first step in the development of a technique for estimating daily maximum and minimum shelter temperatures for agricultural monitoring, this study made use of operational satellite sounder data to estimate shelter temperature. Linear regression methods were used with a ground-truth data set of surface observations matched against data from operationally derived soundings. Regression estimates based solely on temperature predictors from the satellite soundings yielded residual standard deviations of 1.6–2.6 K for the NOAA-6 and NOAA-7 clear and partly cloudy retrievals. Regressions for cloudy conditions based only on the microwave retrievals had errors ranging from 2.9–4.0 K. Shelter temperatures estimated by regression have errors somewhat smaller than those reported for the lower levels of the atmospheric soundings. This suggests that satellite temperature soundings near the surface are more accurate than previous studies indicate.
Abstract
In this study, an attempt has been made to derive the daily net radiation at the top of the atmosphere using the Geostationary Operational Environmental Satellite (GOES) visible (0.55–0.75 μm) and IR window (10.5–12.5 μm) observations and to correlate it with the net radiation at the surface. The NOAA/NESDIS agency arranged for the collection of GOES-E satellite data for a two year period (1981–82) at selected sites in Canada, where surface net radiation is observed routinely. The derived daily average net radiation at the top of the atmosphere was found to be highly correlated to the daily average net radiation at the surface. Preliminary tests of a statistical approach to estimate the surface daily average net radiation from satellite observations of planetary daily average net radiation yielded encouraging results. It was also demonstrated that when the averaging period for the net radiation was increased from one to ten days, the standard error of estimate was reduced from 20 to 7 W m−2.
Abstract
In this study, an attempt has been made to derive the daily net radiation at the top of the atmosphere using the Geostationary Operational Environmental Satellite (GOES) visible (0.55–0.75 μm) and IR window (10.5–12.5 μm) observations and to correlate it with the net radiation at the surface. The NOAA/NESDIS agency arranged for the collection of GOES-E satellite data for a two year period (1981–82) at selected sites in Canada, where surface net radiation is observed routinely. The derived daily average net radiation at the top of the atmosphere was found to be highly correlated to the daily average net radiation at the surface. Preliminary tests of a statistical approach to estimate the surface daily average net radiation from satellite observations of planetary daily average net radiation yielded encouraging results. It was also demonstrated that when the averaging period for the net radiation was increased from one to ten days, the standard error of estimate was reduced from 20 to 7 W m−2.
Abstract
Northern and Southern Hemisphere polar stereographic maps of “vegetation index” are now being produced by the National Oceanic and Atmospheric Administration. The maps are derived from visible and near-infrared data from NOAA's operational polar orbiting satellites. The data are composited over a weekly period to minimize cloud and scan angle effects. The mapped images are being made available to the public in both image and tape format, on a regular schedule.
Abstract
Northern and Southern Hemisphere polar stereographic maps of “vegetation index” are now being produced by the National Oceanic and Atmospheric Administration. The maps are derived from visible and near-infrared data from NOAA's operational polar orbiting satellites. The data are composited over a weekly period to minimize cloud and scan angle effects. The mapped images are being made available to the public in both image and tape format, on a regular schedule.
Abstract
A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.
Abstract
A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.
