Articles | Volume 22, issue 6
https://doi.org/10.5194/acp-22-3811-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-3811-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates
LATMOS/IPSL, Université Paris-Saclay, UVSQ, CNRS, 78280,
Guyancourt, France
Hélène Brogniez
LATMOS/IPSL, Université Paris-Saclay, UVSQ, CNRS, 78280,
Guyancourt, France
Pierre-Emmanuel Kirstetter
University of Oklahoma, Norman, Oklahoma, USA
National Severe Storms Laboratory, NOAA, Norman, Oklahoma, USA
Philippe Chambon
CNRM, Université de Toulouse, Météo France, CNRS,
Toulouse, France
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Short summary
A novel probabilistic approach is proposed to evaluate relative humidity (RH) profiles simulated by an atmospheric model with respect to satellite-based RH defined from probability distributions. It improves upon deterministic comparisons by enhancing the information content to enable a finer assessment of each model–observation discrepancy, highlighting significant departures within a deterministic confidence range. Geographical and vertical distributions of the model biases are discussed.
A novel probabilistic approach is proposed to evaluate relative humidity (RH) profiles simulated...
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