Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates
<p>A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Météo-France numerical weather forecasting model ARPEGE (Action de Recherche Petite Echell...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-03-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/22/3811/2022/acp-22-3811-2022.pdf |
| Summary: | <p>A novel method of comparison between an atmospheric model and satellite
probabilistic estimates of relative humidity (RH) in the tropical atmosphere
is presented. The method is developed to assess the Météo-France
numerical weather forecasting model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) using probability density
functions (PDFs) of RH estimated from the SAPHIR (Sondeur Atmosphérique du
Profil d'Humidité Intertropicale par Radiométrie) microwave sounder. The
satellite RH reference is derived by aggregating footprint-scale
probabilistic RH to match the spatial and temporal resolution of ARPEGE over
the April–May–June 2018 period. The probabilistic comparison is discussed
with respect to a classical deterministic comparison confronting each model
RH value to the reference average and using a set confidence interval. This
study first documents the significant spatial and temporal variability in
the reference distribution spread and shape. We demonstrate the need for a
finer assessment at the individual case level to characterize specific
situations beyond the classical bulk comparison using determinist “best”
reference estimates. The probabilistic comparison allows for a more
contrasted assessment than the deterministic one. Specifically, it reveals
cases where the ARPEGE-simulated values falling within the deterministic
confidence range actually correspond to extreme departures in the reference
distribution, highlighting the shortcomings of the too-common Gaussian
assumption of the reference, on which most current deterministic comparison
methods are based.</p> |
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| ISSN: | 1680-7316 1680-7324 |