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Journal Article: BibTeX citation key:  Bock2009
Bock, O. & Nuret, M. (2009) Verification of NWP model analyses and radiosonde humidity data with GPS precipitable water vapor estimates during AMMA. IN American Meteorological Society, 24. 1085–1101.
Added by: Devic 2009-06-05 10:09:47    Last Edited by: Fanny Lefebvre 2010-11-24 15:09:54
 B  
Categories: General
Creators: Bock, Nuret
Collection: American Meteorological Society
Bibliographies: cnrm, Prior150410

Peer reviewed
Number of views:  760
Popularity index:  39.83%
Maturity index:  accepted

 
Abstract
This paper assesses the performance of ECMWF-IFS operational analysis and NCEP re-analyses I and II over West Africa, using PWV retrievals from a network of ground-based GPS receivers operated during AMMA. The model analyses show reasonable agreement with GPS PWV from 5-daily to monthly means. Errors increase at shorter time-scales, indicating that these global NWP models have difficulty in handling the diurnal cycle and moist processes at synoptic-scale. The ECMWF-IFS analysis shows better agreement with GPS PWV than NCEP re-analyses (the RMS error is smaller by a factor of two). The model changes in ECMWF-IFS did not clearly reflect in PWV error over the period of study (2005 to 2008). Radiosonde humidity biases are diagnosed compared to GPS PWV. The impact of these biases could be evidenced in all three model analyses at the level of the diurnal cycle. The results point to a dry bias in the ECMWF analysis in 2006 when Vaisala RS80-A soundings were assimilated, and a diurnally varying bias when Vaisala RS92 or MODEM M2K2 soundings were assimilated: dry during day and wet during night. The overall bias is offset to wetter values in NCEP re-analysis II, but the diurnal variation of the bias is observed too. Radiosonde bias correction is necessary to reduce NWP model analysis humidity biases and improve precipitation forecast skill. The study points to a wet bias in the Vaisala RS92 data at nighttime and suggests that one has to be careful about this in establishing a bias correction scheme.
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Last Edited by: Fanny Lefebvre