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Satellite microwave radiometers provide measurements of precipitable water content (PWC) over the oceans, with a horizontal resolution of a few tens of kilometres. These data represent the water vapour content integrated over the atmospheric column. We assess the value of this source of information for numerical weather prediction systems. We used the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System with a four-dimensional variational method to assimilate the Special Sensor Microwave/Imager (SSM/I) PWC data over a 24-hour period. Our experiments use an incremental variational method. Comparison with observations is made using a multi-level global primitive-equation T106 spectral model with physical parametrizations. Minimization is performed using a T63 adiabatic dynamics model which includes only simplified physics (horizontal diffusion, a simple surface drag and a vertical diffusion scheme). Comparing the control and assimilation experiments with aircraft and other data shows that the use of PWC data from SSM/I improves the analysis. We also obtain a slight improvement in short-range forecasts of almost all parameters when SSM/I-PWC data are used in the assimilation.

The lack of local humidity observations over a large portion of the globe hinders any improvement of humidity forecasting in meteorological models. However, satellite microwave radiometers routinely provide fields of precipitable water content over the means, with a horizontal resolution of a few tens of kilometers. The aim of this paper is therefore to establish the feasibility of the assimilation of microwave radiometer precipitable water content in a forecast model. This preliminary study presents the assimilation method, which is based on optimal interpolation, and results of analysis and forecast runs over 12 h for one case. The Special Sensor Microwave/Imager (SSM/I) radiometer (the scanning microwave radiometer aboard the U.S. Navy Defense Meteorological Satellite Program satellite) and the Prevision a Echeance Rapprochee, Integrant des Donnees Observees et Teledetectees (PERIDOT) model (operational limited-area model of the French Meteorological Office) were used to perform this test. We ...

We provide a description and evaluation of LMDz-INCA, which couples the Laboratoire de Meteorologie Dynamique general circulation model (LMDz) and the Interaction with Chemistry and Aerosols (INCA) model. In this first version of the model a CH 4 ANO x ACOAO 3 chemical scheme representative of the background chemistry of the troposphere is considered. We derive rapid interhemispheric exchange times of 1.13-1.38 years and 0.70-0.82 years, based on surface and pressure-weighted mixing ratios of inert tracers, respectively. The general patterns of the nitrogen deposition are correctly reproduced by the model. However, scavenging processes remain a major source of uncertainty in current models, with convective precipitation playing a key role in the global distribution of soluble species. The global and annual mean methane (7.9 years) and methylchloroform (4.6 years) chemical lifetimes suggest that OH is too high by about 19-25% in the model. This disagreement with previous estimates is attributed to the missing nonmethane hydrocarbons in this version of the model. The model simulates quite satisfactorily the distribution and seasonal cycle of CO at most stations. At several tropical sites and in the Northern Hemisphere during summer, the OH overestimate leads, however, to a too intense CO chemical destruction. LMDz-INCA reproduces fairly well the distribution of ozone throughout most of the troposphere. A main disagreement appears in the Northern Hemisphere upper troposphere during summer, due to a too high tropopause in the GCM. When the GCM winds are relaxed toward assimilated meteorology, a much higher variability is obtained for ozone in the upper troposphere, reflecting more frequent stratospheric intrusions. The stratospheric influx of ozone increases from 523 Tg/yr in the base case simulation to 783 Tg/yr in the nudged version.