2004Journal of Geophysical Research AtmospheresOpen access

Comparison of microwave satellite humidity data and radiosonde profiles: A case study

Stefan A. Buehler, M. Kuvatov, Viju O. John, U. Leiterer, H. Dier

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Abstract

This article documents a case study comparing radiosonde humidity data to Advanced Microwave Sounding Unit (AMSU) satellite humidity data. The study had two goals: first, to develop a robust method for such a comparison, and second, to check the quality and mutual consistency of radiosonde data, radiative transfer model, and AMSU data. The radiosonde data used are Vaisala RS80 data from the station Lindenberg of the German Weather Service (DWD), which have been subject to several corrections compared to the standard data processing. The radiative transfer model is the Atmospheric Radiative Transfer Simulator (ARTS), and the AMSU data are those of the satellites NOAA 15 and 16 for the time periods 2001 and 2002. The comparison was done in radiance space, using a radiative transfer model to simulate AMSU radiances from the radiosonde data. The overall agreement is very good, with radiance biases below 1.5 K and standard deviations below 2 K. The main source of “noise” in the comparison is atmospheric inhomogeneity on the 10‐km scale. While the radiosonde correction performed at Lindenberg significantly reduces the bias between simulated and measured AMSU radiance, there still remains a slope in the radiance difference. Possible reasons for this were investigated. Most likely, the radiosondes underestimate the relative humidity under extremely dry conditions, showing 0 %RH when the true value is 2–4 %RH.

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What this paper is about

This article documents a case study comparing radiosonde humidity data to Advanced Microwave Sounding Unit (AMSU) satellite humidity data. The study had two goals: first, to develop a robust method for such a comparison, and second, to check the quality and mutual consistency of radiosonde data, radiative transfer model, and AMSU data. The radiosonde data used are Vaisala RS80 data from the station Lindenberg of the German Weather Service (DWD), which have been subject to several corrections compared to the standard data processing. The radiative transfer model is the Atmospheric Radiative Transfer Simulator (ARTS), and the AMSU data are those of the satellites NOAA 15 and 16 for the time periods 2001 and 2002. The comparison was done in radiance space, using a radiative transfer model to simulate AMSU radiances from the radiosonde data. The overall agreement is very good, with radiance biases below 1.5 K and standard deviations below 2 K. The main source of “noise” in the comparison is atmospheric inhomogeneity on the 10‐km scale. While the radiosonde correction performed at Lindenberg significantly reduces the bias between simulated and measured AMSU radiance, there still remains a slope in the radiance difference. Possible reasons for this were investigated. Most likely, the radiosondes underestimate the relative humidity under extremely dry conditions, showing 0 %RH when the true value is 2–4 %RH.

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Available abstract

This article documents a case study comparing radiosonde humidity data to Advanced Microwave Sounding Unit (AMSU) satellite humidity data. The study had two goals: first, to develop a robust method for such a comparison, and second, to check the quality and mutual consistency of radiosonde data, radiative transfer model, and AMSU data. The radiosonde data used are Vaisala RS80 data from the station Lindenberg of the German Weather Service (DWD), which have been subject to several corrections compared to the standard data processing. The radiative transfer model is the Atmospheric Radiative Transfer Simulator (ARTS), and the AMSU data are those of the satellites NOAA 15 and 16 for the time periods 2001 and 2002. The comparison was done in radiance space, using a radiative transfer model to simulate AMSU radiances from the radiosonde data. The overall agreement is very good, with radiance biases below 1.5 K and standard deviations below 2 K. The main source of “noise” in the comparison is atmospheric inhomogeneity on the 10‐km scale. While the radiosonde correction performed at Lindenberg significantly reduces the bias between simulated and measured AMSU radiance, there still remains a slope in the radiance difference. Possible reasons for this were investigated. Most likely, the radiosondes underestimate the relative humidity under extremely dry conditions, showing 0 %RH when the true value is 2–4 %RH.

Key concepts: Radiosonde, Advanced Microwave Sounding Unit, Radiance, Environmental science, Remote sensing, Meteorology, Radiative transfer, Satellite

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