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Sultānpur Lodhi, India

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. Source

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. Source

Panwar V.,National Physical Laboratory India | Panwar V.,University of Delhi | Jain A.R.,National Physical Laboratory India | Goel A.,University of Delhi | And 3 more authors.
Atmospheric Research | Year: 2012

Spatial and temporal variation of water vapor mixing ratio (WVMR) is examined for its association with the convective activity in upper troposphere and lower stratosphere over tropical region particularly Asian monsoon region (AMR) and Indonesian-Australian West Pacific region (IAWPR) using WVMR obtained from MLS satellite with simultaneous daily mean OLR from NOAA and daily mean wind from NCEP reanalysis. An examination of WVMR at various pressure levels during high water vapor regime (moist Phase) indicates that water vapor (WV) transport, in troposphere, is rather fast up to a level of ~. 147. hPa. Seasonal variation of WVMR over tropical lower stratosphere (TLS) is noted to be closely associated with seasonal northward movement of intertropical convergence zone (ITCZ). Convection activity over AMR appears to be a prominent contributor to the moist phase of WVMR seasonal cycle in TLS. However, other tropical regions may also be contributing to the seasonal variability of WVMR. Low WV (dry) phase of the WVMR seasonal cycle in TLS observed during NH winter and early spring months may be caused by the appearance of extreme cold temperatures (≤ 191. K) close to tropopause heights over IAWPR. Mechanisms that could cause such low temperatures over IAWPR are discussed. Intraseasonal oscillations with period of 30-40. days are observed in WVMR at various pressure levels. At 100. hPa level such oscillations are noted to be closely associated with similar oscillation in OLR and temperature. These observations suggest that variations in OLR (proxy of convection activity) produce such oscillation in WVMR. Present analysis thus report signature of convection in upward transport of WV, seasonal and intraseasonal oscillation in WVMR in upper troposphere and lower stratosphere (UTLS). © 2012 Elsevier B.V. Source

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