Preprints
https://doi.org/10.5194/acp-2021-617
https://doi.org/10.5194/acp-2021-617

  04 Oct 2021

04 Oct 2021

Review status: this preprint is currently under review for the journal ACP.

Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

Chloé Radice1, Hélène Brogniez1, Pierre-Emmanuel Kirstetter2,3, and Philippe Chambon4 Chloé Radice et al.
  • 1Université Paris-Saclay, UVSQ, CNRS, LATMOS/IPSL, 78280, Guyancourt, France
  • 2University of Oklahoma, Norman, Oklahoma, USA
  • 3NOAA/National Severe Storms Laboratory, Norman, Oklahoma
  • 4CNRM, Université de Toulouse, Météo France, CNRS, Toulouse, France

Abstract. 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 using probability density functions (PDF) of RH estimated from the SAPHIR 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. The study first documents the significant spatial and temporal variability of the reference distribution spread and shape. It warrants the need for a finer assessment at the individual case level to characterise 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.

Chloé Radice et al.

Status: open (until 15 Nov 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Chloé Radice et al.

Chloé Radice et al.

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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 discrepancies, highlighting significant departures within a deterministic confidence range. Geographical and vertical distributions of the model biases are discussed.
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