Wikindx Resources

Journal Article: BibTeX citation key:  AgustiPanareda2010
Agusti-Panareda, A., Beljaars, A., Ahlgrimm, M., Balsamo, G., Bock, O., Forbes, R., Ghelli, A., Guichard, F., Köhler, M., Meynadier, R. & Morcrette, J.-J. (2010) The ECMWF re-analysis for the AMMA observational campaign. IN Quarterly Journal of the Royal Meteorological Society, 136. 1457–1472.
Added by: Boichard Jean-Luc 2010-08-05 10:13:45    Last Edited by: Fanny Lefebvre 2011-01-26 10:38:33
Categories: General
Creators: Agusti-Panareda, Ahlgrimm, Balsamo, Beljaars, Bock, Forbes, Ghelli, Guichard, Köhler, Meynadier, Morcrette
Collection: Quarterly Journal of the Royal Meteorological Society

Number of views:  1018
Popularity index:  51.94%

During the 2006 African Monsoon Multidisciplinary Analysis (AMMA) field experiment, an unprecedented number of soundings were performed in West Africa. However, due to technical problems many of these soundings did not reach the Global Telecommunication System and therefore they could not be included in the operational numerical weather prediction (NWP) analyses. This issue, together with the realization that there was a significant bias in the radiosonde humidity, led to the conclusion that a re-analysis effort was necessary. This re-analysis was performed at the European Centre for Medium-Range Weather Forecasts (ECMWF) spanning the wet monsoon season of 2006 from May–September. The key features of the ECMWF AMMA re-analysis are presented, including the use of a newer model version with improved physics, all the AMMA radiosonde data available from the AMMA database and a new radiosonde humidity bias-correction scheme. Data-impact experiments show that there is a benefit from these observations, but also highlight large model physics biases over the Sahel that cause a short-lived impact of the observations on the model forecast. The AMMA re-analysis is compared with independent observations to investigate the biases in the different parts of the physics. In the framework of the AMMA project, a hybrid dataset was developed to provide a best estimate of the different terms of the water cycle. This hybrid dataset is used to evaluate the improvement achieved from the use of extra AMMA observations and of a radiosonde humidity bias-correction scheme in the water cycle of the West African monsoon. Finally, future model developments that offer promising improvements in the water cycle are discussed.
Added by: Fanny Lefebvre    Last Edited by: Fanny Lefebvre