Studies on the Impacts of 3D-VAR Assimilation of Satellite Observations on the Simulation of Monsoon Depressions over India - Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications - page 688

RMSE of Dew-Point Temperature Profiles

Root mean square error values for dew-point temperature are presented in Table 26.9
for the 18-22 June 2007 depression. Though the ATOVS run shows higher RMSE
of dew point temperature at the lower levels, interestingly, the upper levels show an
improved forecast of dew-point temperature especially at 200 and 300 hPa levels on
the day one of the forecast. The MODIS run shows large RMSE values of dew point
temperature for almost all the levels. The assimilation of total precipitable water
from SSM/I however does reduce the error values of dew point temperature at 950,
920, 780, 400, 300 and 200 hPa levels on 20 June 2007 12 UTC. On the second day
of the forecast, the ATOVS, MODIS and the SSM/I runs do not show significant
improvement in the forecast of the dew-point temperature while on 22 June 2007
00 UTC, the SSM/I experiment did show improved better result with lower RMSE
of dew point temperature than the other experiments.

26.4.4 Conclusions

The impact of assimilating satellite observations of temperature, humidity and total
precipitable water on the prediction of three monsoon depressions which formed
over the Bay of Bengal are investigated. Out of the three depression cases, the
first one is a land depression, the second one is a weak depression and third one
is a strong monsoon depression event over the Bay of Bengal. Four simulations are
undertaken for each of the three monsoon depression cases. The simulation without
assimilation of any observations is called the 'CTRL run', while simulation that
assimilated ATOVS, MODIS, SSM/I observations are called ATOVS run, MODIS
run, SSM/I run respectively. The results of the model simulations are compared with
one another and also with the TRMM and QuikSCAT observations as well as with
NCEP-FNL analysis. The general conclusions based on the above investigation are
as follows.
The results of the study provide direct and good evidence of the impact of
assimilation of temperature and humidity profiles and the total precipitable water
to a certain extent. From the analysis increment, it can be seen that the assimilation
of the ATOVS temperature and humidity profiles results in larger analysis increment
of 850 hPa wind speed as compared to the other assimilation experiments. The
simulated sea level pressure field of MODIS experiment is found to be relatively
in better agreement with that of the NCEP-FNL analysis in the first two cases.
Also the assimilation of the MODIS temperature and humidity profiles does produce
significant improvement in the precipitation patterns when compared to the TRMM
observation. Equitable threat score and bias score calculated to quantitatively
validate the precipitation forecast shows that the MODIS experiment yields better
results for the land depression and the weak depression events. The high-resolution
dense observations associated with MODIS data can possibly be the reason for the
better forecast produced by the MODIS experiment. The SSM/I run, however, shows