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Dry Bias and Variability in Vaisala RS80-H Radiosondes: The ARM Experience

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  • 1 Pacific Northwest National Laboratory, Richland, Washington, and University of Wisconsin—Madison, Madison, Wisconsin
  • | 2 Argonne National Laboratory, Argonne, Illinois
  • | 3 Atmospheric and Environmental Research, Inc., Cambridge, Massachusetts
  • | 4 Argonne National Laboratory, Argonne, Illinois
  • | 5 University of Wisconsin—Madison, Madison, Wisconsin
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Abstract

Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM's science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the corrected radiosonde. However, because the physically based correction scheme does not address the apparently random calibration variations observed, it does not reduce the variability either between radiosonde calibration batches or within individual calibration batches.

Corresponding author address: David D. Turner, CIMSS, University of Wisconsin—Madison, 1225 W. Dayton St., Madison, WI 53706. Email: dturner@ssec.wisc.edu

Abstract

Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM's science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the corrected radiosonde. However, because the physically based correction scheme does not address the apparently random calibration variations observed, it does not reduce the variability either between radiosonde calibration batches or within individual calibration batches.

Corresponding author address: David D. Turner, CIMSS, University of Wisconsin—Madison, 1225 W. Dayton St., Madison, WI 53706. Email: dturner@ssec.wisc.edu

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