Impact of gridpoint statistical interpolation scheme over Indian region

Abstract

An analysis system experiment was conducted for the month of June 2008 with Gridpoint Statistical Interpolation (GSI) analysis scheme using NCMRWF’s (National Centre for Medium Range Weather Forecasting) T254L64 model. Global analyses were carried out for all days of the month and respective forecast runs are made up to 120-hr. These analyses and forecasts are inter-compared with the operational T254L64 model outputs which uses Spectral Statistical Interpolation (SSI) analysis scheme. The prime objective of this study is to assess the impact of GSI analysis scheme with special emphasis on Indian summer monsoon as compared to SSI. GSI analysis scheme do have positive impact over India and its surrounding regions. Though not for all but for some fields it is in edge over Spectral Statistical Analysis Scheme. Patterns for the forecast mean error; anomaly correlation and S1 scores with respect to the respective analyses are same for both GSI and SSI. Both have increasing S1 scores, decreasing mean errors and anomaly correlation with the advance of forecast days. The vector wind RMSE of the model forecasts with respect to the analyses is lower for GSI at 850 hPa and higher at 250 hPa. But over tropics GSI is better at both levels. The temperature field of GSI has higher correlation and lower RMSE at both 850 and 250 hPa pressure levels. There are improvements in systematic errors for 850 and 200 hPa temperature field in GSI compared to that in SSI. The depression centre in GSI analysis is closer to observation but has produced more intense depression compared to that of SSI. Rainfall forecast of SSI is better at day-1 whereas GSI is closer to the observation at day-5 forecasts valid at the same day.