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  • Bruce, R. E., L. D. Duncan, and J. H. Pierluissi, 1977: Experimental study of the relationships between radiosonde temperatures and satellite-derived temperatures. Mon. Wea. Rev.,105, 493–496.

  • Ellrod, G., 1989: Environmental conditions associated with the Dallas microburst storm determined from satellite soundings. Wea. Forecasting,4, 469–484.

  • ——, cited 1998: Experimental GOES microburst products. [Available online at http://orbit-net.nesdis.noaa.gov/ora/fpdt1/mb.html.].

  • Fleming, H. E., N. C. Grody, and E. J. Katz, 1991: The forward problem and corrections for the SSM/T satellite microwave temperature sounder. IEEE Trans. Geosci. Remote Sens.,29, 571–583.

  • Franklin, J. L., C. S. Velden, C. M. Hayden, and J. Kaplan, 1989: A comparison of VAS and ODW data around a subtropical cold low. Preprints, Fourth Conf. on Satellite Meteorology and Oceanography, San Diego, CA, Amer. Meteor. Soc., 141–144.

  • Fuelberg, H. E., and S. R. Olson, 1991: An assessment of VAS-derived retrievals and parameters used in thunderstorm forecasting. Mon. Wea. Rev.,119, 795–814.

  • ——, P. A. Rao, and D. W. Hillger, 1995: Clustering of satellite sounding radiances to investigate intense low-level humidity gradients. J. Appl. Meteor.,34, 1525–1535.

  • Garand, L., 1993: A pattern recognition technique for retrieving humidity profiles from METEOSAT or GOES imagery. J. Appl. Meteor.,32, 1592–1607.

  • Gray, D. G., C. M. Hayden, and W. P. Menzel, 1996: Review of quantitative satellite products derived from GOES-8/9 imager and sounder instrument data. Preprints, Eighth Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., 159–163.

  • Hayden, C. M., 1988: GOES–VAS simultaneous temperature–moisture retrieval algorithm. J. Appl. Meteor.,27, 705–733.

  • ——, G. S. Wade, and T. J. Schmit, 1996: Derived product imagery from GOES-8. J. Appl. Meteor.,35, 153–162.

  • Hillger, D. W., and J. F. W. Purdom, 1990: Clustering of satellite sounding radiances to enhance mesoscale meteorological retrievals. J. Appl. Meteor.,29, 1344–1351.

  • Knabb, R. D., and H. E. Fuelberg, 1997: A comparison of the first-guess dependence of precipitable water estimates from three techniques using GOES data. J. Appl. Meteor.,36, 417–427.

  • Lee, T. H., D. Chesters, and A. Mostek, 1983: The impact of conventional surface data upon VAS regression retrievals in the lower troposphere. J. Climate Appl. Meteor.,22, 1853–1874.

  • Menzel, W. P., and J. F. W. Purdom, 1994: Introducing GOES-I: The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc.,75, 757–781.

  • ——, W. L. Smith, and L. D. Herman, 1981: Visible infrared spin-scan radiometer atmospheric sounder radiometric calibration: An inflight evaluation from intercomparisons with HIRS and radiosonde measurements. Appl. Opt.,20, 3641–3644.

  • Pratt, R. W., 1985: Review of radiosonde humidity and temperature errors. J. Atmos. Oceanic Technol.,2, 404–407.

  • Rao, P. A., and H. E. Fuelberg, 1997: Diagnosing convective instability from GOES-8 radiances. J. Appl. Meteor.,36, 350–364.

  • Schmit, T. J., 1996: Sounder bias correction of the east–west radiance gradient. Preprints, GOES-8 and Beyond, Denver, CO, SPIE, 630–637.

  • Schwartz, B., and C. A. Doswell III, 1991: North American rawinsonde observations: Problems, concerns, and a call to action. Bull. Amer. Meteor. Soc.,72, 1885–1896.

  • ——, and S. G. Benjamin, 1995: A comparison of temperature and wind measurements from ACARS-equipped aircraft and rawinsondes. Wea. Forecasting,10, 528–544.

  • Smith, W. L., H. M. Woolf, and A. J. Schreiner, 1985: Simultaneous retrieval of surface atmospheric parameters: A physical and analytically direct approach. Advances in Remote Sensing, A. Deepak, H. E. Fleming, and M. T. Chahine, Eds., A. Deepak Publishing, 221–232.

  • Susskind, J., J. Rosenfield, D. Reuter, and M. T. Chahine, 1984: Remote sensing of weather and climate parameters from HIRS2/MSU on TIROS-N. J. Geophys. Res.,89, 4677–4697.

  • Uddstrom, M. J., and L. M. McMillin, 1994: System noise in the NESDIS TOVS forward model. Part I: Specification. J. Appl. Meteor.,33, 919–938.

  • Velden, C. S., W. L. Smith, and M. Mayfield, 1984: Application of VAS and TOVS to tropical cyclones. Bull. Amer. Meteor. Soc.,65, 1059–1067.

  • Weinreb, M. P., J. X. Johnson, J. C. Bremer, E. C. Wack, and O. Chen, 1996: Algorithm to compensate for variation of reflectance of GOES-8 and -9 scan mirrors with scan angle. Preprints, Eighth Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., 110–114.

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Article Type:
Research Article

An Evaluation of GOES-8 Retrievals

P. Anil RaoDepartment of Meteorology, The Florida State University, Tallahassee, Florida

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Henry E. FuelbergDepartment of Meteorology, The Florida State University, Tallahassee, Florida

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Print Publication:
01 Dec 1998
DOI:
https://doi.org/10.1175/1520-0450(1998)037<1577:AEOGR>2.0.CO;2
Page(s):
1577–1587
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Abstract

The Geostationary Operational Environmental Satellite (GOES-8) temperature–moisture retrievals were compared with collocated National Weather Service radiosonde observations (RAOBs) to assess retrieval performance. Retrieved values of temperature and dewpoint were evaluated at individual levels. Precipitable water and thickness also were evaluated, and the GOES-8 retrievals were compared with the first-guess data used in the algorithm. The dataset consisted of 1113 RAOB–retrieval pairs (collocated to within 50 km) over the United States at 1200 UTC during August–November 1995.

GOES-8 temperature retrievals were found to agree better with their RAOB-derived counterparts than did the dewpoints. However, both temperatures and dewpoints were found to be highly dependent on their first-guess data from the Nested Grid Model. Retrievals generally were closer to the RAOBs than was the first guess. However, this was never guaranteed, even for large first-guess discrepancies. In fact, some retrievals did not agree as well with the RAOBs as did the first guess.

GOES-8 and RAOB-derived precipitable water (PW) and thickness showed closer agreement than the level-specific data. Both integrated parameters were dependent on their first guess. However, GOES-8 and RAOB PW agreed more often in layers above the surface where the guess was less accurate.

Comparison with a previous evaluation of retrievals from the Visible and Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) indicated that GOES-8 retrievals agreed better with RAOBs than did the VAS versions. This improvement is likely due to GOES-8’s increased number of channels and better signal-to-noise values, along with the assumed increase in quality of the first-guess data being used.

Corresponding author address: P. Anil Rao, Department of Meteorology, The Florida State University, Tallahassee, FL 32306-4520.

rao@met.fsu.edu

Abstract

The Geostationary Operational Environmental Satellite (GOES-8) temperature–moisture retrievals were compared with collocated National Weather Service radiosonde observations (RAOBs) to assess retrieval performance. Retrieved values of temperature and dewpoint were evaluated at individual levels. Precipitable water and thickness also were evaluated, and the GOES-8 retrievals were compared with the first-guess data used in the algorithm. The dataset consisted of 1113 RAOB–retrieval pairs (collocated to within 50 km) over the United States at 1200 UTC during August–November 1995.

GOES-8 temperature retrievals were found to agree better with their RAOB-derived counterparts than did the dewpoints. However, both temperatures and dewpoints were found to be highly dependent on their first-guess data from the Nested Grid Model. Retrievals generally were closer to the RAOBs than was the first guess. However, this was never guaranteed, even for large first-guess discrepancies. In fact, some retrievals did not agree as well with the RAOBs as did the first guess.

GOES-8 and RAOB-derived precipitable water (PW) and thickness showed closer agreement than the level-specific data. Both integrated parameters were dependent on their first guess. However, GOES-8 and RAOB PW agreed more often in layers above the surface where the guess was less accurate.

Comparison with a previous evaluation of retrievals from the Visible and Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) indicated that GOES-8 retrievals agreed better with RAOBs than did the VAS versions. This improvement is likely due to GOES-8’s increased number of channels and better signal-to-noise values, along with the assumed increase in quality of the first-guess data being used.

Corresponding author address: P. Anil Rao, Department of Meteorology, The Florida State University, Tallahassee, FL 32306-4520.

rao@met.fsu.edu

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