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The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and
the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm
of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall
of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating
the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different
cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale
circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in
the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization
schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency
bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for
the low precipitation threshold. 相似文献
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Sukanta Kumar Das Sanjib Kumar Deb C. M. Kishtawal P. K. Pal 《Theoretical and Applied Climatology》2012,109(1-2):81-94
Seasonal prediction of Indian Summer Monsoon (ISM) has been attempted for the current year 2011 using Community Atmosphere Model (CAM) developed at the National Centre for Atmospheric Research (NCAR). First, 30?years of model climatology starting from 1981 to 2010 has been generated to capture the variability of ISM over the Indian region using 30 seasonal simulations. The simulated model climatology has been validated with different sets of observed climatology, and it was observed that the simulated climatological rainfall is affected by model bias. Subsequently, a bias correction procedure using the Tropical Rainfall Measuring Mission (TRMM) 3B43 rainfall has been proposed. The bias-corrected rainfall climatology shows both spatial and temporal variability of ISM satisfactorily. Further, four sets of 10-member ensemble simulations of ISM 2009 and 2010 have been performed in hindcast mode using observed sea surface temperature (SST) and persistence of April SST anomaly, and it has been found that the bias-corrected model rainfall captures the seasonal variability of ISM reasonably well with some discrepancies in these two contrasting monsoon years. With this positive background, the seasonal prediction of ISM 2011 has been carried out in forecast mode with the assumption of persistence of May SST anomaly from June through September 2011. The model assessment shows an 11% deficiency in All-India Rainfall (AIR) of ISM 2011. In particular, the monthly accumulated rains are predicted to be 101% (17.6?cm), 86% (24.3?cm), 83% (21.0?cm) and 95% (15.5?cm) of normal AIR for the months of June, July, August and September, respectively. 相似文献
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P. K. Pal W. J. Prakash P. K. Thapliyal C. M. Kishtawal 《Meteorology and Atmospheric Physics》1999,71(3-4):157-168
Summary ?A methodology has been developed to assimilate satellite-measured rainfall during the initial phase of model integration
for extended range monsoon prediction. The vertical profiles of latent heating corresponding to different rain rates have
been derived from the model statistics. These heating rates have been assimilated through nudging in the thermodynamics equation
of the model. This procedure of assimilating observed heating has corrected the simulation of heating location in the model
and consequently removed the anomalous sinking motion over Indian landmass. With the correction of vertical circulation, both
mean July rainfall over India and the distribution have improved. Interannual variability has been brought out for the years
1987 and 1988. In view of the availability of rainfall profile from Tropical Rain Measuring Mission (TRMM) there is a scope
of adopting this method of assimilating observed rainfall, for extended range monsoon prediction.
Received February 12, 1999/Revised May 4, 1999 相似文献
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The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity
of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We
have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets
of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold’s
SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold’s
and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial
resolution showed sharper gradient when compared to the Reynold’s SST. The use of TMI SST improved the WRF cyclone intensity
prediction when compared to that using Reynold’s SST for both the cases studied. The improvements in intensity were mainly
due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold’s SST improved
cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling
study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification
and movement of tropical cyclones over the Indian Ocean. 相似文献
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Prashant?KumarEmail author Sanjib?K.?Deb C.?M.?Kishtawal P.?K.?Pal 《Theoretical and Applied Climatology》2017,128(3-4):575-586
The Weather Research and Forecasting (WRF) model and its three-dimensional variational data assimilation system are used in this study to assimilate the INSAT-3D, a recently launched Indian geostationary meteorological satellite derived from atmospheric motion vectors (AMVs) over the South Asian region during peak Indian summer monsoon month (i.e., July 2014). A total of four experiments were performed daily with and without assimilation of INSAT-3D-derived AMVs and the other AMVs available through Global Telecommunication System (GTS) for the entire month of July 2014. Before assimilating these newly derived INSAT-3D AMVs in the numerical model, a preliminary evaluation of these AMVs is performed with National Centers for Environmental Prediction (NCEP) final model analyses. The preliminary validation results show that root-mean-square vector difference (RMSVD) for INSAT-3D AMVs is ～3.95, 6.66, and 5.65 ms?1 at low, mid, and high levels, respectively, and slightly more RMSVDs are noticed in GTS AMVs (～4.0, 8.01, and 6.43 ms?1 at low, mid, and high levels, respectively). The assimilation of AMVs has improved the WRF model of produced wind speed, temperature, and moisture analyses as well as subsequent model forecasts over the Indian Ocean, Arabian Sea, Australia, and South Africa. Slightly more improvements are noticed in the experiment where only the INSAT-3D AMVs are assimilated compared to the experiment where only GTS AMVs are assimilated. The results also show improvement in rainfall predictions over the Indian region after AMV assimilation. Overall, the assimilation of INSAT-3D AMVs improved the WRF model short-range predictions over the South Asian region as compared to control experiments. 相似文献