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Communication incl. Poster: BibTeX citation key:  Bocka
Bock, O. & Nuret, M. 2009. Verification of NWP model analyses and radiosonde humidity data with GPS precipitable water vapor estimates during AMMA. Work presented at Third International AMMA Conference, July 20—24, at Ouagadougou, Burkina Faso.
Added by: roussot 2009-11-23 20:24:52
 B  
Categories: Water cycle
Creators: Bock, Nuret
Publisher: African Monsoon Multidisciplinary Analyses (Ouagadougou, Burkina Faso)
Collection: Third International AMMA Conference

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Abstract
The first part of this study assesses the performance of the ECMWF-IFS operational analysis and NCEP re-analyses I and II (all at 2.5° resolution) over West Africa between 2005 and 2008. Therefore, PWV retrievals from a network of ground-based GPS receivers operated during AMMA are used. The model analyses/reanalyses 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 do not clearly reflect in PWV error over the period of study at least based on monthly mean statistics. Radiosonde humidity biases are also diagnosed compared to GPS PWV. The impact of these biases is evidenced in all three model analyses at the level of the diurnal cycle. The results point to a dry bias in the ECMWF analysis 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. The study points also to a wet bias in the Vaisala RS92 data (which represent now ~50% of all the radiosonde data on the GTS) at nighttime and suggests that one has to be careful about this in establishing a bias correction scheme.
The second part of the study focuses on the impact of the ECMWF humidity bias correction scheme and on the increase of data assimilated into the AMMA reanalysis produced by ECMWF over the SOP period (May-September 2006). PWV differences between the operational analysis and the reanalysis reach up to ± 2 kg m-2. They clearly reflect the impact of additional radiosonde data assimilated and the humidity bias correction. Overall, PWV is increased over West Africa but reduced over the Sahara. Part of the impact seems also due to changes in the model (moist convection). Differences are also observed in atmospheric circulation and consequently in moisture convergence (see also Gervois et al.). These results confirm the importance of the radiosonde humidity bias correction.
Added by: roussot