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- Author or Editor: Rachel Pinker x
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Abstract
The first stage in a program of research to develop a regional model capable of describing the hydrology of semiarid areas of northwest Mexico and southwest United States, using remotely sensed data, is described in this paper. Finescale information on cloud cover is required to provide the radiation forcing for making simple, near-real-time estimates of daytime evaporation in hydrologic models, and frequent satellite observations have the potential to document cloud variability at high spatial and temporal resolutions. In this study, the operational framework for obtaining information on cloud cover was developed and applied, using hourly sampled, 1-km resolution GOES-7 data as received in real time in Obregon, Mexico. These satellite data were collected and analyzed from 1 July 1993 to 31 July 1994 for an approximately 106 km2 rectangular area in northwest Mexico. An efficient method was devised to provide clear-sky radiance images for the study area, at 4 km × 4 km resolution, and updated at monthly intervals, by applying thresholds indexed to the locally appropriate clear-sky radiance, thereby allowing for spatial and temporal changes in surface conditions. Manual image inspection and comparison with ground-based measurements of cloud cover and surface solar radiation provided reassurance that the high-resolution cloud-screening algorithm gave satisfactory results.
This algorithm was applied to investigate the effects of temporal sampling frequency on estimates of daytime-average cloud cover and to document aspects of the cloud characteristics for the study area. The high-resolution algorithm proved to be efficient and reliable and bodes well for its future use in providing high-resolution estimates of surface solar radiation for use in a hydrologic model. Monthly clear-sky composite images were consistently generated, showing little evidence of contamination by persistent clouds, and tracked the seasonal evolution in surface radiance. Comparison with ground-based measurements gave confidence in the credibility of the satellite estimates and revealed weaknesses in the Campbell–Stokes solarimeter. The seasonal evolution of spatial patterns of cloud and its diurnal cycle were investigated. The average cloudiness for the study area is 0.25, with a substantial annual variation from 0.19 in April to 0.40 in December. Persistent cloudy conditions throughout the year were detected over the Pacific Ocean west of Baja California. The derived high-resolution cloud estimates, when compared with similar estimates from the International Satellite Cloud Climatology Project (ISCCP D1), were about half those obtained with the low-resolution data, indicating that, in this complex study area where land and water boundaries are in close proximity, low-resolution satellite observations of clouds may not be able to depict the true cloud cover.
Abstract
The first stage in a program of research to develop a regional model capable of describing the hydrology of semiarid areas of northwest Mexico and southwest United States, using remotely sensed data, is described in this paper. Finescale information on cloud cover is required to provide the radiation forcing for making simple, near-real-time estimates of daytime evaporation in hydrologic models, and frequent satellite observations have the potential to document cloud variability at high spatial and temporal resolutions. In this study, the operational framework for obtaining information on cloud cover was developed and applied, using hourly sampled, 1-km resolution GOES-7 data as received in real time in Obregon, Mexico. These satellite data were collected and analyzed from 1 July 1993 to 31 July 1994 for an approximately 106 km2 rectangular area in northwest Mexico. An efficient method was devised to provide clear-sky radiance images for the study area, at 4 km × 4 km resolution, and updated at monthly intervals, by applying thresholds indexed to the locally appropriate clear-sky radiance, thereby allowing for spatial and temporal changes in surface conditions. Manual image inspection and comparison with ground-based measurements of cloud cover and surface solar radiation provided reassurance that the high-resolution cloud-screening algorithm gave satisfactory results.
This algorithm was applied to investigate the effects of temporal sampling frequency on estimates of daytime-average cloud cover and to document aspects of the cloud characteristics for the study area. The high-resolution algorithm proved to be efficient and reliable and bodes well for its future use in providing high-resolution estimates of surface solar radiation for use in a hydrologic model. Monthly clear-sky composite images were consistently generated, showing little evidence of contamination by persistent clouds, and tracked the seasonal evolution in surface radiance. Comparison with ground-based measurements gave confidence in the credibility of the satellite estimates and revealed weaknesses in the Campbell–Stokes solarimeter. The seasonal evolution of spatial patterns of cloud and its diurnal cycle were investigated. The average cloudiness for the study area is 0.25, with a substantial annual variation from 0.19 in April to 0.40 in December. Persistent cloudy conditions throughout the year were detected over the Pacific Ocean west of Baja California. The derived high-resolution cloud estimates, when compared with similar estimates from the International Satellite Cloud Climatology Project (ISCCP D1), were about half those obtained with the low-resolution data, indicating that, in this complex study area where land and water boundaries are in close proximity, low-resolution satellite observations of clouds may not be able to depict the true cloud cover.
Abstract
Parameters derived from satellite observations depend on the quality of the calibration method applied to the raw satellite radiance measurements. This study investigates the sensitivity of absolute reflectance, derived cloud cover, and estimated surface shortwave (SW) downward fluxes to two different calibration methods for the visible sensor aboard the eighth Geostationary Operational Environmental Satellite (GOES-8). The first method was developed at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS), and the second at the NASA Langley Research Center. Differences in visible reflectance ranged from −0.5% to 3%. The average difference in monthly mean cloud amount was ∼3%, and the average difference in monthly mean shortwave downward flux was 5 W m−2. Differences in bias and rms of the SW fluxes when evaluated against ground station measurements were less than 3 W m−2. Neither calibration method was shown to consistently outperform the other. This evaluation yields an estimate of the errors in fluxes that can be attributed to calibration.
Abstract
Parameters derived from satellite observations depend on the quality of the calibration method applied to the raw satellite radiance measurements. This study investigates the sensitivity of absolute reflectance, derived cloud cover, and estimated surface shortwave (SW) downward fluxes to two different calibration methods for the visible sensor aboard the eighth Geostationary Operational Environmental Satellite (GOES-8). The first method was developed at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS), and the second at the NASA Langley Research Center. Differences in visible reflectance ranged from −0.5% to 3%. The average difference in monthly mean cloud amount was ∼3%, and the average difference in monthly mean shortwave downward flux was 5 W m−2. Differences in bias and rms of the SW fluxes when evaluated against ground station measurements were less than 3 W m−2. Neither calibration method was shown to consistently outperform the other. This evaluation yields an estimate of the errors in fluxes that can be attributed to calibration.
Land Surface Temperature from GOES-East and GOES-WestABSTRACT
Land surface temperature (LST) is an important climate parameter that controls the surface energy budget. For climate applications, information is needed at the global scale with representation of the diurnal cycle. To achieve global coverage there is a need to merge about five independent geostationary (GEO) satellites that have different observing capabilities. An issue of practical importance is the merging of independent satellite observations in areas of overlap. An optimal approach in such areas could eliminate the need for redundant computations by differently viewing satellites. We use a previously developed approach to derive information on LST from GOES-East (GOES-E), modify it for application to GOES-West (GOES-W) and implement it simultaneously across areas of overlap at 5-km spatial resolution. We evaluate the GOES-based LST against in situ observations and an independent MODIS product for the period of 2004–09. The methodology proposed minimizes differences between satellites in areas of overlap. The mean and median values of the differences in monthly mean LST retrieved from GOES-E and GOES-W at 0600 UTC for July are 0.01 and 0.11 K, respectively. Similarly, at 1800 UTC the respective mean and median value of the differences were 0.15 and 1.33 K. These findings can provide guidelines for potential users to decide whether the reported accuracy based on one satellite alone, meets their needs in area of overlap. Since the 6 yr record of LST was produced at hourly time scale, the data are well suited to address scientific issues that require the representation of LST diurnal cycle or the diurnal temperature range (DTR).
ABSTRACT
Land surface temperature (LST) is an important climate parameter that controls the surface energy budget. For climate applications, information is needed at the global scale with representation of the diurnal cycle. To achieve global coverage there is a need to merge about five independent geostationary (GEO) satellites that have different observing capabilities. An issue of practical importance is the merging of independent satellite observations in areas of overlap. An optimal approach in such areas could eliminate the need for redundant computations by differently viewing satellites. We use a previously developed approach to derive information on LST from GOES-East (GOES-E), modify it for application to GOES-West (GOES-W) and implement it simultaneously across areas of overlap at 5-km spatial resolution. We evaluate the GOES-based LST against in situ observations and an independent MODIS product for the period of 2004–09. The methodology proposed minimizes differences between satellites in areas of overlap. The mean and median values of the differences in monthly mean LST retrieved from GOES-E and GOES-W at 0600 UTC for July are 0.01 and 0.11 K, respectively. Similarly, at 1800 UTC the respective mean and median value of the differences were 0.15 and 1.33 K. These findings can provide guidelines for potential users to decide whether the reported accuracy based on one satellite alone, meets their needs in area of overlap. Since the 6 yr record of LST was produced at hourly time scale, the data are well suited to address scientific issues that require the representation of LST diurnal cycle or the diurnal temperature range (DTR).
