Global 4DVAR Assimilation and Forecast Experiments Using AMSU Observations over Land. Part II: Impacts of Assimilating Surface-Sensitive Channels on the African Monsoon during AMMA

Florence Rabier,Jean-Luc Redelsperger,Jean-Philippe Lafore,Fatima Karbou,Olivier Bock

doi:10.1175/2009waf2222244.1

Abstract

Abstract Observations from Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) have been more intensively used over sea than over land because of large uncertainties about the land surface emissivity and the skin temperature. Several methods based on a direct estimation of the land emissivity from satellite observations have been found to be very useful for improving the assimilation of sounding channels over land. Feasibility studies have been conducted within the Météo-France global assimilation system in order to examine the possibility of assimilating low-level atmospheric observations receiving a contribution from the land surface. The present study reports on three 2-month assimilation and forecast experiments, which include the assimilation of surface-sensitive observations from AMSU-A and -B together with a control experiment, which represents the operational model. The assimilation experiments have been compared with the control, and important changes in the analyzed atmospheric fields and in the precipitation forecasts over parts of the tropics, and especially over West Africa, have been noticed. The experiments seem to emphasize the atmospheric moistening in India, South America, and in West Africa, together with atmospheric drying over Saudi Arabia and northeast Africa. The drying or moistening of the atmosphere has been successfully evaluated using independent measurements from the GPS African Monsoon Multidisciplinary Analysis (AMMA) network. Precipitation and OLR forecasts have also been examined and compared with independent measurements. Physically, the changes result in a better-organized African monsoon with a stronger ITCZ in terms of ascent, vorticity, and precipitation, but there is no northward shift of the monsoon system. Low-level humidity observations have been found to have important impacts on the analysis and to produce positive impacts on forecast scores over the tropics.

Highlights

The West African monsoon (WAM) is still far from being well represented in numerical weather prediction (NWP) models
The assimilation of such observations was made possible after alternative methods for estimating the land surface emissivity and the skin temperature were developed in the Meteo-France data assimilation system
The impacts of assimilating surface-sensitive observations from AMSU-A and -B over land have been studied with respect to a control experiment, which was representative of the operational model

Summary

Introduction

The West African monsoon (WAM) is still far from being well represented in numerical weather prediction (NWP) models. Observations from satellite sensors such as the Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B), which have considerable information content, gave a valuable description of the temperature and humidity at different levels in the atmosphere The use of these measurements in NWP has led to substantial progress being made, but more effort is needed to assimilate many more observations in a wide range of atmospheric situations (clear, cloudy) and with a variety of surface conditions (ocean, land, snow, etc.). It has been found that the use of an improved description of the land surface emissivity and/or skin temperature allows the assimilation system to take advantage of the information content of the AMSU temperature and humidity sounding channels over land (Karbou et al 2010, hereafter Part I) These results are very encouraging and suggest that it is possible to explore various strategies for assimilating surface-affected microwave observations. In addition to the four 2-month experiments comprehensively described in Part I, three 2-month assimilation experiments were run for summer

Objectives

Methods

Findings

Conclusion