Impact of Precipitation Rate Assimilation over India and Surrounding Regions

Surya K Dutta,V S Prasad

doi:10.5539/esr.v2n1p74

Abstract

An Observation System Experiment has been described that examines the impact of precipitation rate, obtained from SSM/I onboard the DMSP satellites and those from the TRMM. Analysis scheme used is Gridpoint Statistical Interpolation (GSI) with the forecast model T254L64. Analyses are carried out globally for four times daily at six hourly intervals from 00z to 18z. Two sets of simulations were performed. Precipitation rate measured by SSM/I and TRMM are assimilated and subsequently forecasts for 168 hour are made through the NCMRWF’s GFS for the entire month of June-2009. The analyses and forecasts are also repeated for the entire period without assimilating the precipitation rate data. The results are analyzed globally giving special emphasis over India and surrounding regions. When compared with the observations, improvement of analyses and forecasts from experimental simulations were noticed. Analyses versus observation study showed improvement in terms of lower RMSE over both Tropics and Indian region. Positive impact on temperature analysis is seen over all the three levels of 850, 500 and 250hPa. For vector wind and geo-potential height analysis positive impact of assimilation is seen over 500 and 250hPa pressure levels. In forecast versus analysis comparison, the differences in the values from the two simulations are mostly insignificant. For a few cases, the experimental simulations shows significant improvement over the control runs. When compared with the observations, consistent improvement in the experimental forecast in terms of lower RMSE is found over both Tropics and Indian region. Improvement in all the three parameters (temperature, horizontal wind and geo-potential height) is observed.

Highlights

The understanding of the variability of the atmospheric moisture content, latent heat, clouds and the large scale atmospheric circulation with the variation in the change in atmospheric conditions is primarily required for understanding the response of earth’s weather and climate to atmospheric perturbations
The Global Data Assimilation and Forecast System (GDAF) used for the study are based on Global Forecast System (GFS) from National Centre for Environmental Prediction (NCEP)
Giving special emphasis to the Indian Summer Monsoon, the discussions are confined over Tropics and Indian region

Summary

Introduction

The understanding of the variability of the atmospheric moisture content, latent heat, clouds and the large scale atmospheric circulation with the variation in the change in atmospheric conditions is primarily required for understanding the response of earth’s weather and climate to atmospheric perturbations. Satellite data serves as an important source of information, especially over the oceanic regions where the other modes of observations are very scarce. Satellites on the other hand scan wide areas along their orbital track providing voluminous data which is widely used in improving the analysis for the numerical weather prediction models. Satellites serve as the source of measurements of atmospheric variables with high spatial and temporal resolution. Observations from satellite microwave soundings have proved to be the most vital information source in providing quantitative measurements of various atmospheric quantities (Stanley & Thomas, 1995; Gelaro et al, 2010). There have been limitations in the present day systems, restricting the assimilation of satellite data to clear-sky regions for infrared radiances and to non-precipitating areas for microwave radiances. In the recent years, varied studies have been made towards evaluating the potential of assimilation of satellite data over cloudy and rainy regions using 3D/4D-Var systems (Chevallier et al, 2002; Janisková et al, 2002; Moreau et al, 2004)

Methods

Results

Conclusion