Present study describes a methodology to establish an empirical expression to estimate the upper tropospheric humidity
(UTH) from brightness temperature observations in water vapour channel of Very High Resolution Radiometer (VHRR)
onboard Indian geostationary satellites INSAT-3A and Kalpana. Radiative transfer simulations for VHRR water vapour
channel were made using SBDART model for tropical atmosphere with different upper tropospheric relative humidity
values and varying zenith angles. INSAT-3A and Kalpana VHRR sensor response functions (SRF) for water vapour
channel were used to simulate the convolved radiances. Estimated UTH values have been compared with corresponding
Meteosat-5 observations. Comparison of retrieved UTH is also made with radiosonde observations of relative humidity
weighted by water vapour channel weighting function.
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 (2)
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions II
19 November 2008 | Noumea, New Caledonia
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.