Operational Implementation of the 1D+3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model
| Autor: | Jean-François Mahfouf, Eric Wattrelot, Olivier Caumont |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
021110 strategic
defence & security studies Atmospheric Science 010504 meteorology & atmospheric sciences Meteorology Computer science Bayesian probability 0211 other engineering and technologies Mesoscale meteorology Context (language use) 02 engineering and technology 01 natural sciences Data assimilation 13. Climate action Consistency (statistics) Preprocessor Relative humidity Variational analysis 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Monthly Weather Review. 142:1852-1873 |
| ISSN: | 1520-0493 0027-0644 |
| DOI: | 10.1175/mwr-d-13-00230.1 |
| Popis: | This paper presents results from radar reflectivity data assimilation experiments with the nonhydrostatic limited-area model Application of Research to Operations at Mesoscale (AROME) in an operational context. A one-dimensional (1D) Bayesian retrieval of relative humidity profiles followed by a three-dimensional variational data assimilation (3D-Var) technique is adopted. Several preprocessing procedures of raw reflectivity data are presented and the use of the nonrainy signal in the assimilation is widely discussed and illustrated. This two-step methodology allows the authors to build up a screening procedure that takes into account the evaluation of the results from the 1D Bayesian retrieval. In particular, the 1D retrieval is checked by comparing a pseudoanalyzed reflectivity to the observed reflectivity. Additionally, a physical consistency between the reflectivity innovations and the 1D relative humidity increments is imposed before assimilating relative humidity pseudo-observations with other observations. This allows the authors to counteract the difficulty of the current 3D-Var system to correct strong differences between model and observed clouds from the crude specification of background-error covariances. Assimilation experiments of radar reflectivity data in a preoperational configuration are first performed over a 1-month period. Positive impacts on short-term precipitation forecast scores are systematically found. The evaluation shows improvements on the analysis and also on objective conventional forecast scores, in particular for the model wind field up to 12 h. A case study for a specific precipitating system demonstrates the capacity of the method for improving significantly short-term forecasts of organized convection. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|