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Homogenization of Radiosonde Temperature Time Series Using Innovation Statistics

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  • 1 Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
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Abstract

Radiosonde temperature records contain valuable information for climate change research from the 1940s onward. Since they are affected by numerous artificial shifts, time series homogenization efforts are required. This paper introduces a new technique that uses time series of temperature differences between the original radiosonde observations (obs) and background forecasts (bg) of an atmospheric climate data assimilation system for homogenization.

These obs − bg differences, the “innovations,” are a by-product of the data assimilation process. They have been saved during the 40-yr ECMWF Re-Analysis (ERA-40) and are now available for each assimilated radiosonde record back to 1958. It is demonstrated that inhomogeneities in the obs time series due to changes in instrumentation can be automatically detected and adjusted using daily time series of innovations at 0000 and 1200 UTC.

The innovations not only reveal problems of the radiosonde records but also of the data assimilation system. Although ERA-40 used a frozen data assimilation system, the time series of the bg contains some breaks as well, mainly due to changes in the satellite observing system. It has been necessary to adjust the global mean bg temperatures before the radiosonde homogenization.

After this step, homogeneity adjustments, which can be added to existing raw radiosonde observations, have been calculated for 1184 radiosonde records. The spatiotemporal consistency of the global radiosonde dataset is improved by these adjustments and spuriously large day–night differences are removed. After homogenization the climatologies of the time series from certain radiosonde types have been adjusted. This step reduces temporally constant biases, which are detrimental for reanalysis purposes. Therefore the adjustments applied should yield an improved radiosonde dataset that is suitable for climate analysis and particularly useful as input for future climate data assimilation efforts. The focus of this paper relies on the lower stratosphere and on the internal consistency of the homogenized radiosonde dataset. Implications for global mean upper-air temperature trends are touched upon only briefly.

Corresponding author address: Dr. Leopold Haimberger, Department of Meteorology and Geophysics, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria. Email: leopold.haimberger@univie.ac.at

Abstract

Radiosonde temperature records contain valuable information for climate change research from the 1940s onward. Since they are affected by numerous artificial shifts, time series homogenization efforts are required. This paper introduces a new technique that uses time series of temperature differences between the original radiosonde observations (obs) and background forecasts (bg) of an atmospheric climate data assimilation system for homogenization.

These obs − bg differences, the “innovations,” are a by-product of the data assimilation process. They have been saved during the 40-yr ECMWF Re-Analysis (ERA-40) and are now available for each assimilated radiosonde record back to 1958. It is demonstrated that inhomogeneities in the obs time series due to changes in instrumentation can be automatically detected and adjusted using daily time series of innovations at 0000 and 1200 UTC.

The innovations not only reveal problems of the radiosonde records but also of the data assimilation system. Although ERA-40 used a frozen data assimilation system, the time series of the bg contains some breaks as well, mainly due to changes in the satellite observing system. It has been necessary to adjust the global mean bg temperatures before the radiosonde homogenization.

After this step, homogeneity adjustments, which can be added to existing raw radiosonde observations, have been calculated for 1184 radiosonde records. The spatiotemporal consistency of the global radiosonde dataset is improved by these adjustments and spuriously large day–night differences are removed. After homogenization the climatologies of the time series from certain radiosonde types have been adjusted. This step reduces temporally constant biases, which are detrimental for reanalysis purposes. Therefore the adjustments applied should yield an improved radiosonde dataset that is suitable for climate analysis and particularly useful as input for future climate data assimilation efforts. The focus of this paper relies on the lower stratosphere and on the internal consistency of the homogenized radiosonde dataset. Implications for global mean upper-air temperature trends are touched upon only briefly.

Corresponding author address: Dr. Leopold Haimberger, Department of Meteorology and Geophysics, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria. Email: leopold.haimberger@univie.ac.at

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