Toward Elimination of the Warm Bias in Historic Radiosonde Temperature Records—Some New Results from a Comprehensive Intercomparison of Upper-Air Data

By L. Haimberger, Christina Tavolato, S. Sperka. 2008

151 citations recorded by the source corpus.

Abstract The apparent cooling trend in observed global mean temperature series from radiosonde records relative to Microwave Sounding Unit (MSU) radiances has been a long-standing problem in upper-air climatology. It is very likely caused by a warm bias of radiosonde temperatures in the 1980s, which has been reduced over time with better instrumentation and correction software. The warm bias in the MSU-equivalent lower stratospheric (LS) layer is estimated as 0.6 ± 0.3 K in the global mean and as 1.0 ± 0.3 K in the tropical (20°S–20°N) mean. These estimates are based on comparisons of unadjusted radiosonde data, not only with MSU data but also with background forecast (BG) temperature time series from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and with two new homogenized radiosonde datasets. One of the radiosonde datasets [Radiosonde Observation Correction using Reanalyses (RAOBCORE) version 1.4] employs the BG as reference for homogenization, which is not s...

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/b75a2711145b5f8130477a902f1201b44ff2433c

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Citations in the corpus

A New Approach to Homogenize Daily Radiosonde Humidity Data (2011, methodology): “15c), as is usually the case for the homogenization of radiosonde temperature (Haimberger et al. 2008).”
Homogenization of the Global Radiosonde Temperature Dataset through Combined Comparison with Reanalysis Background Series and Neighboring Stations (2012, methodology): “The present paper is motivated by the fact that Haimberger et al. (2008) provided only rudimentary documentation of RICH, by the availability of verymuch enhanced background forecasts due to the advent of ERA-Interim (Dee andUppala 2009; Dee et al. 2011a,b), and by substantial extensions and…”
An update of observed stratospheric temperature trends (2009, unknown): “Haimberger [2007] and Haimberger et al. [2008] discuss homogenization of radiosonde data using differences between original observations and background forecasts of an atmospheric climate data assimilation (reanalysis) system.”
Reanalyses Suitable for Characterizing Long-Term Trends (2010, background): “There is a substantial heritage of efforts to investigate the homogeneity of much of the data that are ingested and form climate data records from there (e.g., Durre et al. 2006; Thorne et al. 2005b; Free et al. 2005; Sherwood et al. 2008; Haimberger et al. 2008; Rayner et al. 2003; Mears and Wentz ”
The ERA5 global reanalysis (2020, methodology): “Regarding bias corrections for radiosonde temperature, an update of the method of a pre-calculated RAOBCORE (Haimberger et al., 2008) homogenization as in ERA-Interim is used, where estimates are now also based on comparison between neighbouring stations, rather than from departure statistics alone…”