The south-west monsoon seasonal variations of the rainfall and water vapor over the Indian subcontinent and oceans are studied using microwave (MW) and near-Infrared (NIR) satellite measurements on monthly scales. The total precipitable water (TPW) derived from multi channel imaging data acquired with the Moderate Resolution Imaging Spectrometer (MODIS) on the Terra Spacecraft and rainfall data from merged infrared estimates calibrated against Tropical Rainfall Measuring Mission (TRMM) microwave data respectively are used. Since TPW is an important link connecting the various components of the hydrological cycle, its variability with rainfall on monthly scales have been used to meet this objective in the present study during the three successive contrasting good (normal), bad (drought) and good (normal) south-west monsoon years of 2001 to 2003 respectively.
The skill of short-range forecasts produced using the PSU-NCAR Mesoscale Model (MM5) during the July 1998 episode
of Indian summer monsoon is evaluated statistically. The spatial and temporal variations in the forecast error is analysed
by computing bias and root mean square error (rmse) in the model predicted wind, temperature, and relative humidity.
The model forecasted rainfall is evaluated against observation by computing statistical skill scores. It is observed that
model simulated upper-tropospheric anticyclone from both 24- and 48-h forecast is slightly east of its observed position.
The strength of tropical easterly jet (TEJ) is underestimated in model forecast. It is seen that the rmse in forecasted wind
at 850 hPa is higher in case of Peninsular India (PI) as compared to other regions studied. Over Indian subcontinent the
model forecast under predicts moisture at 850 hPa, which is consistent with the previous studies. The rainfall distribution
from both 24- and 48-h predictions shows an underestimation of monthly rainfall over Indian land mass. The rain
shadow region observed in the eastern coast of southern Peninsular India is reproduced in model forecast. It is evident
from the threat scores obtained that MM5 shows moderate skill in predicting rainfall and model skill does not vary
significantly with rainfall threshold.
Conference Committee Involvement (1)
Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges