The ECMWF re‐analysis for the AMMA observational campaign
The ECMWF re‐analysis for the AMMA observational campaign
复制标题
ECMWF 对 AMMA 观测活动的重新分析
DOI：
10.1002/qj.662
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发表时间：
2010
影响因子：
8.9
通讯作者：
J. Morcrette
中科院分区：
文献类型：
--
作者：
A. Agustí;A. Beljaars;M. Ahlgrimm;G. Balsamo;O. Bock;R. Forbes;A. Ghelli;F. Guichard;M. Köhler;R. Meynadier;J. Morcrette
在2006年非洲季风多学科分析（AMMA）野外试验期间，在西非进行了空前数量的探测。然而，由于技术问题，许多这些探测没有到达全球电信系统，因此它们不能包括在业务数值天气预报（NWP）分析中。这个问题，再加上认识到无线电探空仪湿度存在显著偏差，得出了重新分析工作是必要的结论。这项重新分析是在欧洲中期天气预报中心（ECMWF）进行的，时间跨度为2006年5月至9月的潮湿季风季节。介绍了ECMWF AMMA再分析的主要特点，包括使用具有改进物理特性的新模型版本，所有AMMA无线电探空仪数据可从AMMA数据库中获得，以及新的无线电探空仪湿度偏差校正方案。数据影响实验表明，这些观测结果是有益的，但也强调了萨赫勒地区的大模型物理偏差，这些偏差会导致观测结果对模型预测产生短期影响。AMMA再分析与独立观测结果进行比较，以调查物理不同部分的偏差。在AMMA项目的框架内，开发了一个混合数据集，以提供对水循环不同术语的最佳估计。该混合数据集用于评估利用额外的AMMA观测和无线电探空湿度偏差校正方案在西非季风水循环中所取得的改进。最后，讨论了未来模型的发展，为水循环提供了有希望的改进。版权所有©2010英国皇家气象学会
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. Copyright © 2010 Royal Meteorological Society