A Comparative Study of Weather Forecasting Simulation Models through Sensors for Accurate Monsoon Predictions in the Indian Ocean

When Monsoon depressions form over the seas, the Moderate Resolution Imaging Spectroradiometer (MODIS) provides humidity and high-horizontal resolution temperature details about the depressions. These high-resolution satellite data related to temperature and humidity can improve the poor predicting rate of depressions [1]. Using three-dimensional variational data assimilation (3DVAR) and with the help of humidity profiles along with MODIS temperature. We can achieve an advanced prospect of detection and a larger value of (ETS) equitable threat score observed over 48 hours collected precipitation with respect to the control run. The 3DVAR assimilation of Doppler Weather Radar wind data associated with Indian Meteorological Department (IMD) surface data and upper air data helped in the improvements in the simulation of strong gradients associated with horizontal wind speed ,higher warm core temperature , high vertical velocity & better precipitation and spatial distribution.[2]. The effect of Spectral sensor microwave imager (SSM/I), humidity profiles, use of Advanced TIROS Vertical Sounder (ATOVS) temperature and total precipitable water (TPW) helped in improving the ‘‘forecast impact’’ parameters of ‘‘bias score’’ and ‘‘equitable threat score’’ with respect to the assimilation of satellite observation[3] . In this paper we have discussed a comparative study of different proposed techniques to analyze its effects in improving the low prediction rates of depressions.