All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 0 0 0
PDF Downloads 0 0 0

Impact of Scene Dependence on AVHRR Albedo Models

View More View Less
  • 1 Research and Data Systems Corporation, Greenbelt, Maryland
  • | 2 Satellite Research Laboratory, Washington, D.C.
Full access

Abstract

Narrowband observations from NOAA's Advanced Very High Resolution Radiometer (AVHRR) are used operationally by NOAA to estimate the earth's broadband planetary albedo. Since May of 1988; these broadband albedo estimates have been derived using the two-channel (visible and near-infrared), scene-independent regression model of Wydick et al. The occurrence of relatively large regional bias errors using this model has led to a study of scene-dependent models that substantially reduce these errors. Three classes of scene stratification are considered: 1) by surface geography type alone (SFC); and 2) and 3) by surface geography type in combination with cloud amount category (SCN) and normalized difference albedo index (NDAI) using AVHRR channels 1 and 2. These and the Wydick model are applied to independent AVHRR global data of 2 July 1985 (hereafter July) and 9 January 1986 (hereafter January). Using ERBE (Earth Radiation Budget Experiment) data as a reference, errors in reflected flux are computed for each day.

The total AVHRR-ERBE shortwave flux difference is separated into two terms. One is due to inaccuracy in the calibration of the AVHRR reflectances (calibration error). The second is the error due to all other sources of the AVHRR-ERBE flux difference. It is referred to as the measurement error. Spatial sampling differences (sampling error) and limitations in the mathematical form and specification of the AVHRR regression model equations (model error) are probably the two primary components of the measurement error.

When calibration error vanishes (due to the implementation of calibration corrections) and sampling differences are small (i.e., for global and zonal averaging), only the model error remains. The Wydick model yields high positive global bias errors of 22 and 37 W m−2 for July and January, respectively. In contrast, errors of ±5 W m−2 are obtained with the scene-dependent models (i.e., SCN). When no calibration adjustments to the AVHRR data are performed, as in operational processing, the Wydick model produces bias errors of −6.8 and 1.5 W m−2 for July and January, respectively. These low bias errors may be misleading though as they result from the near cancellation of large model and calibration error components. The cancellation is not effective at all latitudes, so the Wydick model tends to generate large north-south error gradients. These latitudinal errors are largely removed by all of the scene-dependent models.

Abstract

Narrowband observations from NOAA's Advanced Very High Resolution Radiometer (AVHRR) are used operationally by NOAA to estimate the earth's broadband planetary albedo. Since May of 1988; these broadband albedo estimates have been derived using the two-channel (visible and near-infrared), scene-independent regression model of Wydick et al. The occurrence of relatively large regional bias errors using this model has led to a study of scene-dependent models that substantially reduce these errors. Three classes of scene stratification are considered: 1) by surface geography type alone (SFC); and 2) and 3) by surface geography type in combination with cloud amount category (SCN) and normalized difference albedo index (NDAI) using AVHRR channels 1 and 2. These and the Wydick model are applied to independent AVHRR global data of 2 July 1985 (hereafter July) and 9 January 1986 (hereafter January). Using ERBE (Earth Radiation Budget Experiment) data as a reference, errors in reflected flux are computed for each day.

The total AVHRR-ERBE shortwave flux difference is separated into two terms. One is due to inaccuracy in the calibration of the AVHRR reflectances (calibration error). The second is the error due to all other sources of the AVHRR-ERBE flux difference. It is referred to as the measurement error. Spatial sampling differences (sampling error) and limitations in the mathematical form and specification of the AVHRR regression model equations (model error) are probably the two primary components of the measurement error.

When calibration error vanishes (due to the implementation of calibration corrections) and sampling differences are small (i.e., for global and zonal averaging), only the model error remains. The Wydick model yields high positive global bias errors of 22 and 37 W m−2 for July and January, respectively. In contrast, errors of ±5 W m−2 are obtained with the scene-dependent models (i.e., SCN). When no calibration adjustments to the AVHRR data are performed, as in operational processing, the Wydick model produces bias errors of −6.8 and 1.5 W m−2 for July and January, respectively. These low bias errors may be misleading though as they result from the near cancellation of large model and calibration error components. The cancellation is not effective at all latitudes, so the Wydick model tends to generate large north-south error gradients. These latitudinal errors are largely removed by all of the scene-dependent models.

Save