Abstract
A data assimilation system combines all available information on the atmospheric state in a given time-window to produce an estimate of atmospheric conditions valid at a prescribed analysis time. Nowadays, increased computing power coupled with greater access to real-time asynoptic data is paving the way toward a new generation of high-resolution (i.e. on the order of 10 km) operational mesoscale analyses and forecasting systems. Moreover, better initial conditions are increasingly considered of the utmost importance for Numerical Weather Prediction (NWP) at the short range (0 - 12 h). This paper presents a general-purpose data assimilation system, which is coupled with the Regional Atmospheric Modelling System (RAMS) to give the analyses for: zonal and meridional wind components, temperature, relative humidity, and geopotential height. In order to show its potential, the data assimilation systems applied to produce analyses over Central Europe. For this application the background field is given by a short-range forecast (12 h) of the RAMS and analyses are produced by 2D-Var with 0.25? horizontal resolution. Results show the validity of the analyses because they are closer to the observations, consistently with the settings of the data assimilation system. To quantify the impact of improved initial conditions on the forecast, the analyses are then used as initial conditions of a short-range (6 h) forecast of the RAMS model. The results show that the RMSE is effectively reduced for the one- and two hours forecast, with some improvement for the three-hours forecast.
Highlights
Modern Numerical Weather Prediction (NWP) data assimilation systems use information from a range of sources to provide the best estimate, i.e. the analysis, at a given time
This paper presents a general-purpose data assimilation system, which is coupled with the Regional Atmospheric Modelling System (RAMS) to give the analyses for: zonal and meridional wind components, temperature, relative humidity, and geopotential height
This paper shows preliminary results of a data assimilation system, which is under development with the following two purposes: 1) to produce analyses of meteorological parameter; 2) to improve the short-term forecast of atmospheric fields
Summary
Modern NWP data assimilation systems use information from a range of sources to provide the best estimate, i.e. the analysis, at a given time. These systems combine information coming from the observations, an a-priori estimate of the atmospheric state (the background or first-guess field), detailed error statistics, and the law of physics. This paper shows preliminary results of a data assimilation system, which is under development with the following two purposes: 1) to produce analyses of meteorological parameter; 2) to improve the short-term forecast of atmospheric fields.
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