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Open AccessJournal ArticleDOI

A simple method to relate microwave radiances to upper tropospheric humidity

TLDR
In this paper, the brightness temperature transformation was 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.
Abstract
[1] 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.

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Citations
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COSP: Satellite simulation software for model assessment

TL;DR: COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables that permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models.
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The growing impact of satellite observations sensitive to humidity, cloud and precipitation

TL;DR: In this paper, the authors reviewed the impact of and the science behind satellite microwave radiances sensitive to humidity, cloud and precipitation, as measured by adjoint-based forecast sensitivity diagnostics.
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Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies

TL;DR: In this paper, the authors used global forecast departures from an numerical weather prediction (NWP) system (e.g. observation minus forecast differences) to indicate the quality of agreement between model and observations.
Journal ArticleDOI

An upper tropospheric humidity data set from operational satellite microwave data

TL;DR: In this paper, a new data set of Upper Tropospheric Humidity (UTH) data from the Advanced Microwave Sounding Unit B (AMSU-B) instruments onboard the NOAA 15, 16, and 17 satellites was used to derive a new UTH data set.
References
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