Open AccessA simple method to relate microwave radiances to upper tropospheric humidity
Author(s) -
Buehler S. A.,
John V. O.
Publication year - 2005
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2004jd005111
Subject(s) - radiosonde , troposphere , standard deviation , relative humidity , noise (video) , environmental science , radiometer , microwave radiometer , atmospheric sciences , meteorology , remote sensing , mathematics , geology , statistics , physics , artificial intelligence , computer science , image (mathematics)
A brightness temperature (BT) transformation method can be applied to microwave data to retrieve Jacobian weighted upper tropospheric relative humidity (UTH) in a broad layer centered roughly between 6 and 8 km altitude. The UTH bias is below 4% RH, and the relative UTH bias below 20%. The UTH standard deviation is between 2 and 6.5% RH in absolute numbers, or between 10 and 27% in relative numbers. The standard deviation is dominated by the regression noise, resulting from vertical structure not accounted for by the simple transformation relation. The UTH standard deviation due to radiometric noise alone has a relative standard deviation of approximately 7% for a radiometric noise level of 1 K. The retrieval performance was shown to be of almost constant quality for all viewing angles and latitudes, except for problems at high latitudes due to surface effects. A validation of AMSU UTH against radiosonde UTH shows reasonable agreement if known systematic differences between AMSU and radiosonde are taken into account. When the method is applied to supersaturation studies, regression noise and radiometric noise could lead to an apparent supersaturation even if there were no supersaturation. For a radiometer noise level of 1 K the drop‐off slope of the apparent supersaturation is 0.17% RH −1 , for a noise level of 2 K the slope is 0.12% RH −1 . The main conclusion from this study is that the BT transformation method is very well suited for microwave data. Its particular strength is in climatological applications where the simplicity and the a priori independence are key advantages.