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Abstract
Abstract. We use 30 years of intercalibrated HIRS (High-Resolution Infrared Radiation Sounder) data to produce a 30-year data set of upper tropospheric humidity with respect to ice (UTHi). Since the required brightness temperatures (channels 12 and 6, T12 and T6) are intercalibrated to different versions of the HIRS sensors (HIRS/2 and HIRS/4) it is necessary to convert the channel 6 brightness temperatures which are intercalibrated to HIRS/4 into equivalent brightness temperatures intercalibrated to HIRS/2, which is achieved using a linear regression. Using the new regression coefficients we produce daily files of UTHi, T12 and T6, for each NOAA satellite and METOP-A (Meteorological Operational Satellite Programme), which carry the HIRS instrument. From this we calculate daily and monthly means in 2.5° × 2.5° resolution for the northern midlatitude zone 30–60° N. As a first application we calculate decadal means of UTHi and the brightness temperatures for the two decades 1980–1989 and 2000–2009. We find that the humidity mainly increased from the 1980s to the 2000s and that this increase is highly statistically significant in large regions of the considered midlatitude belt. The main reason for this result and its statistical significance is the corresponding increase of the T12 variance. Changes of the mean brightness temperatures are less significant.
Highlights
The detection of climate change is often hampered by the small signal-to-noise ratio in time series of climate data
Comparisons of the brightness temperatures from NOAA-14 with NOAA-15 and from NOAA-17 with METOP-A showed that channel values of T6 are very similar across the different instrument versions, such that a very simple solution to our problem would be to ignore these differences and assume that T6/2 = T6/4
We have used 30 years of intercalibrated data of HIRS brightness temperatures to derive a corresponding data set of upper tropospheric humidity
Summary
The detection of climate change is often hampered by the small signal-to-noise ratio in time series of climate data. Comparisons of the brightness temperatures from NOAA-14 with NOAA-15 (transition from HIRS/2 to HIRS/3) and from NOAA-17 with METOP-A (transition from HIRS/3 to HIRS/4) showed that channel values of T6 are very similar across the different instrument versions, such that a very simple solution to our problem would be to ignore these differences and assume that T6/2 = T6/4 (the hat over T signifies an estimate) This would induce rms (root mean square) errors of the order 0.05 % (about 0.125 K). In the following we develop the regression of T6/2 on T6/4 and introduce simple quality checks Using this method we have produced a new UTHi data set that shares the file structure with the data set of intercalibrated brightness temperatures (sorted with respect to satellite, year and date). The first applications of this new data set are presented in Sect. 3 before a summary and an outlook to further plans is given in the final Sect. 4
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