• E N Rajagopal

      Articles written in Journal of Earth System Science

    • Indian Ocean surface winds from NCMRWF analysis as compared to QuikSCAT and moored buoy winds

      B N Goswami E N Rajagopal

      More Details Abstract Fulltext PDF

      The quality of the surface wind analysis at the National Centre for Medium Range Weather Forecasts (NCMRWF), New Delhi over the tropical Indian Ocean and its improvement in 2001 are examined by comparing it within situ buoy measurements and satellite derived surface winds from NASA QuikSCAT satellite (QSCT) during 1999, 2000 and 2001. The NCMRWF surface winds suffered from easterly bias of 1.0–1.5 ms-1 in the equatorial Indian Ocean (IO) and northerly bias of 2.0–3.0 ms-1 in the south equatorial IO during 1999 and 2000 compared to QSCT winds. The amplitude of daily variability was also underestimated compared to that in QSCT. In particular, the amplitude of daily variability of NCMRWF winds in the eastern equatorial IO was only about 60% of that of QSCT during 1999 and 2000. The NCMRWF surface winds during 2001 have significantly improved with the bias of the mean analyzed winds considerably reduced everywhere bringing it to within 0.5 ms-1 of QSCT winds in the equatorial IO. The amplitude and phase of daily and intraseasonal variability are very close to that in QSCT almost everywhere during 2001. It is shown that the weakness in the surface wind analysis during 1999 and 2000 and its improvement in 2001 are related to the weakness in simulation of precipitation by the forecast model in the equatorial IO and its improvement in 2001.

    • Skills of different mesoscale models over Indian region during monsoon season: Forecast errors

      Someshwar Das Raghavendra Ashrit Gopal Raman Iyengar Saji Mohandas M Das Gupta John P George E N Rajagopal Surya Kanti Dutta

      More Details Abstract Fulltext PDF

      Performance of four mesoscale models namely,the MM5,ETA,RSM and WRF,run at NCMRWF for short range weather forecasting has been examined during monsoon-2006.Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind,temperature,specific humidity,geopotential height,rainfall,systematic errors,root mean square errors and specific events like the monsoon depressions.

      It is very difficult to address the question of which model performs best over the Indian region? An honest answer is ‘none ’.Perhaps an ensemble approach would be the best.However, if we must make a final verdict,it can be stated that in general,(i)the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and,the MM5 is able to produce best All India rainfall forecasts in day-3,but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India,(ii)the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time,and (iii)the RSM is able to produce least errors in the day-1 forecasts of the tracks,while the ETA model produces least errors in the day-3 forecasts.

    • Gridded daily Indian monsoon rainfall for 14 seasons: Merged TRMM and IMD gauge analyzed values

      Ashis K Mitra I M Momin E N Rajagopal S Basu M N Rajeevan T N Krishnamurti

      More Details Abstract Fulltext PDF

      Indian monsoon is an important component of earth’s climate system. Daily rainfall data for longer period is vital to study components and processes related to Indian monsoon. Daily observed gridded rainfall data covering both land and adjoining oceanic regions are required for numerical model validation and model development for monsoon. In this study, a new gridded daily Indian rainfall dataset at 1° × 1° latitude/longitude resolution covering 14 monsoon seasons (1998–2011) are described. This merged satellite gauge rainfall dataset (NMSG) combines TRMM TMPA rainfall estimates with gauge information from IMD gridded data. Compared to TRMM and GPCP daily rainfall data, the current NMSG daily data has more information due to inclusion of local gauge analysed values. In terms of bias and skill scores this dataset is superior to other daily rainfall datasets. In a mean climatological sense and also for anomalous monsoon seasons, this merged satellite gauge data brings out more detailed features of monsoon rainfall. The difference of NMSG and GPCP looks significant. This dataset will be useful to researchers for monsoon intraseasonal studies and monsoon model development research.

    • Improvements in medium range weather forecasting system of India

      V S Prasad Saji Mohandas Surya Kanti Dutta M Das Gupta G R Iyengar E N Rajagopal Swati Basu

      More Details Abstract Fulltext PDF

      Medium range weather forecasts are being generated in real time using Global Data Assimilation Forecasting System (GDAFS) at NCMRWF since 1994. The system has been continuously upgraded in terms of data usage, assimilation and forecasting system. Recently this system was upgraded to a horizontal resolution of T574 (about 22 km) with 64 levels in vertical. The assimilation scheme of this upgraded system is based on the latest Grid Statistical Interpolation (GSI) scheme and it has the provision to use most of available meteorological and oceanographic satellite datasets besides conventional meteorological observations. The new system has an improved procedure for relocating tropical cyclone to its observed position with the correct intensity. All these modifications have resulted in improvement of skill of medium range forecasts by about 1 day.

  • Journal of Earth System Science | News

© 2017-2019 Indian Academy of Sciences, Bengaluru.