Editorial Type:
Article
Article Type:
Research Article

Retrieval of Geophysical Parameters from GOES: Evaluation of a Split-Window Technique

Ronnie J. Suggs Global Hydrology and Climate Center, NASA/Marshall Space Flight Center, Huntsville, Alabama

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Gary J. Jedlovec Global Hydrology and Climate Center, NASA/Marshall Space Flight Center, Huntsville, Alabama

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Anthony R. Guillory Global Hydrology and Climate Center, NASA/Marshall Space Flight Center, Huntsville, Alabama

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Print Publication:
01 Oct 1998
DOI:
https://doi.org/10.1175/1520-0450(1998)037<1205:ROGPFG>2.0.CO;2
Page(s):
1205–1227
Restricted access

Abstract

The performance of a physical split-window retrieval algorithm used to retrieve skin temperature (ST) and precipitable water (PW) from Geostationary Operational Environmental Satellites’ (GOES) infrared measurements is evaluated. The evaluation assesses the potential of using GOES measurements to provide accurate retrieval products for climate research studies. Several algorithm performance issues are addressed, including the time of retrieval (diurnal effects), sensitivity to the first-guess field, and an evaluation of performance differences associated with the split-window channel characteristics of the GOES-7 VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS) and the GOES-8 imager and sounder. The investigation used a mesoscale model, initialized by radiosonde data, to generate a simulated atmosphere representative of a case study characterized by summertime conditions over the east-central United States. Synthetic GOES channel radiances were developed from the surrogate atmosphere using GOES channel response functions and an appropriate radiative transfer code. The model fields also provided the necessary ground truth and first-guess field for the retrieval algorithm. Retrievals of ST and PW were made from the simulated channel radiances associated with the VAS and GOES-8 imager and sounder split-window channels. Retrieval methodologies were applied to address issues of importance in climate research studies, such as long-term trends and diurnal variability of ST and PW. The performance was measured by comparing the retrieved values with the model values at each of the retrieval locations.

The algorithm performance for both ST and PW was found to be sensitive to the quality of the first-guess field and to the channel characteristics of the GOES sensors. An estimate of the lower bound on ST and PW retrieval errors was determined. The ST retrievals in all cases showed a significant improvement over the first-guess values. The GOES-8 imager ST retrieval errors, which were about half of the VAS values, ranged from about 0.2 to 0.6 K, exhibiting little diurnal effect. The PW retrieval errors ranged from about 2.0 to 7.0 mm with a modest sensitivity to the different sensor channels. However, a significant diurnal trend in the PW retrieval errors that correlated with the presence of surface- and low-level temperature inversions was observed. The algorithm performance results provide insight into the application of GOES split-window retrieval methodologies for climate variability studies and may have implications for operational applications of similar retrieval techniques.

Corresponding author address: Ronnie J. Suggs, NASA/Global Hydrology and Climate Center, 977 Explorer Boulevard, Huntsville, AL 35806.

Abstract

The performance of a physical split-window retrieval algorithm used to retrieve skin temperature (ST) and precipitable water (PW) from Geostationary Operational Environmental Satellites’ (GOES) infrared measurements is evaluated. The evaluation assesses the potential of using GOES measurements to provide accurate retrieval products for climate research studies. Several algorithm performance issues are addressed, including the time of retrieval (diurnal effects), sensitivity to the first-guess field, and an evaluation of performance differences associated with the split-window channel characteristics of the GOES-7 VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS) and the GOES-8 imager and sounder. The investigation used a mesoscale model, initialized by radiosonde data, to generate a simulated atmosphere representative of a case study characterized by summertime conditions over the east-central United States. Synthetic GOES channel radiances were developed from the surrogate atmosphere using GOES channel response functions and an appropriate radiative transfer code. The model fields also provided the necessary ground truth and first-guess field for the retrieval algorithm. Retrievals of ST and PW were made from the simulated channel radiances associated with the VAS and GOES-8 imager and sounder split-window channels. Retrieval methodologies were applied to address issues of importance in climate research studies, such as long-term trends and diurnal variability of ST and PW. The performance was measured by comparing the retrieved values with the model values at each of the retrieval locations.

The algorithm performance for both ST and PW was found to be sensitive to the quality of the first-guess field and to the channel characteristics of the GOES sensors. An estimate of the lower bound on ST and PW retrieval errors was determined. The ST retrievals in all cases showed a significant improvement over the first-guess values. The GOES-8 imager ST retrieval errors, which were about half of the VAS values, ranged from about 0.2 to 0.6 K, exhibiting little diurnal effect. The PW retrieval errors ranged from about 2.0 to 7.0 mm with a modest sensitivity to the different sensor channels. However, a significant diurnal trend in the PW retrieval errors that correlated with the presence of surface- and low-level temperature inversions was observed. The algorithm performance results provide insight into the application of GOES split-window retrieval methodologies for climate variability studies and may have implications for operational applications of similar retrieval techniques.

Corresponding author address: Ronnie J. Suggs, NASA/Global Hydrology and Climate Center, 977 Explorer Boulevard, Huntsville, AL 35806.

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