Panda J.,Satellite Meteorology Division |
Panda J.,Nanyang Technological University |
Giri R.K.,Satellite Meteorology Division
Natural Hazards | Year: 2012
While qualitative information from meteorological satellites has long been recognized as critical for monitoring weather events such as tropical cyclone activity, quantitative data are required to improve the numerical prediction of these events. In this paper, the sea surface winds from QuikSCAT, cloud motion vectors and water vapor winds from KALPANA-1 are assimilated using three-dimensional variational assimilation technique within Weather Research Forecasting (WRF) modeling system. Further, the sensitivity experiments are also carried out using the available cumulus convective parameterizations in WRF modeling system. The model performance is evaluated using available observations, and both qualitative and quantitative analyses are carried out while analyzing the surface and upper-air characteristics over Mumbai (previously Bombay) and Goa during the occurrence of the tropical cyclone PHYAN at the west coast of Indian subcontinent. The model-predicted surface and upper-air characteristics show improvements in most of the situations with the use of the satellite-derived winds from QuikSCAT and KALPANA-1. Some of the model results are also found to be better in sensitivity experiments using cumulus convection schemes as compared to the CONTROL simulation. © 2012 Springer Science+Business Media B.V.
Mitra A.K.,Satellite Meteorology Division |
Kundu P.K.,Jadavpur University |
Giri R.K.,Satellite Meteorology Division
Meteorology and Atmospheric Physics | Year: 2013
The coverage of satellite derived winds over the Indian region including Indian Ocean has improved by the operation of India's first dedicated satellite for meteorology, KALPANA-1 since 12 September 2002. Atmospheric motion vectors (AMVs) are being derived at the India Meteorological Department (IMD), New Delhi on a routine operational basis. The AMV is recognized as an important source of information for numerical weather prediction (NWP) and is particularly suited for tracking the low and middle level clouds mainly because of the good contrast in albedo between target and background, whereas the upper level moisture pattern can be better tracked by water vapor winds (WVW) using water vapor (WV) channel (5. 7-7. 1 μm). The WVWs proved to be a very useful wind product for predicting the future track position of cyclones, well marked low pressure areas or heavy rainfall warnings in advance and so, often these types of weather systems are steered by the upper level winds. In the present study, the quantitative as well as qualitative analyses of KALPANA-1 WVW have been carried out. The primary change introduced is making use of first guess (FG) forecast fields obtained from National Center for Environmental Prediction (NCEP) and Global Forecast System (GFS), at a resolution of 1° × 1° with T-382/L64 instead of forecasts of operational limited area model (LAM) of IMD. The overall results showed a consistent improvement after using improved FG wind fields from NCEP instead of LAM with a significantly increasing number of good qualities of KALPANA-1 derived WVWs. The quantitative error analysis has also been carried out for the validation of WVWs using collocated radiosonde observations for the period from May 2008 to December 2009 and the available mid-upper level winds derived from METEOSAT-7 data for the period from October to December 2008. The analysis shows that after modification, the RMSE and bias of KALPANA-1 WVWs have reduced considerably. Further, to assess the impact of these winds, a high resolution mesoscale model WRF 3DVAR system is used in the present study for the analysis of tropical cyclone 'Sidr'. The results show that the wind assimilation experiments (analysis at 200 hPa) using upper level KALPANA-1 WVW have great potential for improving the NWP analysis. The impact of additional wind data in the model is found to be positive and beneficial. © 2013 Springer-Verlag Wien.