The study of climate changes in India and search for robust evidences are issues of concern specially when it is known that poor people are very vulnerable to climate changes. Due to the vast size of India and its complex geography, climate in this part of the globe has large spatial and temporal variations. Important weather events affecting India are floods and droughts, monsoon depressions and cyclones, heat waves, cold waves, prolonged fog and snowfall. Results of this comprehensive study based on observed data and model reanalyzed fields indicate that in the last century, the atmospheric surface temperature in India has enhanced by about 1 and 1.1°C during winter and post-monsoon months respectively. Also decrease in the minimum temperature during summer monsoon and its increase during post-monsoon months have created a large difference of about 0.8°C in the seasonal temperature anomalies which may bring about seasonal asymmetry and hence changes in atmospheric circulation. Opposite phases of increase and decrease in the minimum temperatures in the southern and northern regions of India respectively have been noticed in the interannual variability. In north India, the minimum temperature shows sharp decrease of its magnitude between 1955 and 1972 and then sharp increase till date. But in south India, the minimum temperature has a steady increase. The sea surface temperatures (SST) of Arabian Sea and Bay of Bengal also show increasing trend. Observations indicate occurrence of more extreme temperature events in the east coast of India in the recent past. During summer monsoon months, there is a decreasing (increasing) trend in the frequency of depressions (low pressure areas). In the last century the frequency of occurrence of cyclonic storms shows increasing trend in the month of November. In addition there is increase in the number of severe cyclonic storms crossing Indian Coast. Analysis of rainfall Climatic Change (2007) 85: amount during different seasons indicate decreasing tendency in the summer monsoon rainfall over Indian landmass and increasing trend in the rainfall during pre-monsoon and post-monsoon months.
The first observational experiment under the Indian Climate Research Programme, called the Bay of Bengal Monsoon Experiment (BOBMEX), was carried out during July-August 1999. BOBMEX was aimed at measurements of important variables of the atmosphere, ocean, and their interface to gain deeper insight into some of the processes that govern the variability of organized convection over the bay. Simultaneous time series observations were carried out in the northern and southern Bay of Bengal from ships and moored buoys. About 80 scientists from 15 different institutions in India collaborated during BOBMEX to make observations in most-hostile conditions of the raging monsoon. In this paper, the objectives and the design of BOBMEX are described and some initial results presented. During the BOBMEX field phase there were several active spells of convection over the bay, separated by weak spells. Observation with high-resolution radiosondes, launched for the first time over the northern bay, showed that the magnitudes of the convective available potential energy (CAPE) and the convective inhibition energy were comparable to those for the atmosphere over the west Pacific warm pool. CAPE decreased by 2-3 kJ kg-1 following con-vection, and recovered in a time period of 1-2 days. The surface wind speed was generally higher than 8 ms-1. The thermohaline structure as well as its time evolution during the BOBMEX field phase were found to be different in the northern bay than in the southern bay. Over both the regions, the SST decreased during rain events and increased in cloud-free conditions. Over the season as a whole, the upper-layer salinity decreased for the north bay and increased for the south bay. The variation in SST during 1999 was found to be of smaller amplitude than in 1998. Further analysis of the surface fluxes and currents is expected to give insight into the nature of coupling.
An empirical model for predicting the maximum surface wind speed associated with a tropical cyclone after crossing the east coast of India is described. The model parameters are determined from the database of 19 recent cyclones. The model is based upon the assumption that tropical cyclone winds decay exponentially after landfall. A method for correcting the forecast during subsequent observation hours is also presented. Results show that without the correction factor the absolute mean error ranges from 6.1 to 4.9 kt (1 kt ϭ 0.5144 m s Ϫ1 ) and the root-mean-square error ranges from 7.9 to 5.6 kt, with both decreasing over time. With the incorporation of the correction procedure, a significant improvement in the forecast skill is noticed for the case in which it is tested using the dependent sample. The model is expected to be very useful to operational forecasters.
[1] We examine a deep precipitating system that formed over the west coast of India during 26-28 June 2002 producing heavy rainfall of 2-61 cm day À1 . The system developed into a well-marked low pressure area due to interaction between an eastward moving westerly trough and a westward moving monsoon low. We used the PSU/NCAR Mesoscale Model (MM5) to make 10-day interactively nested simulations at 90, 30, and 10 km grid-resolutions. We used observations from a special data set collected during an Arabian Sea Monsoon Experiment (ARMEX) conducted June-August, 2002. Nudging the observations produced a balanced atmosphere which, in turn, matched the location of vortex with cloud clusters observed from satellite. The simulated rainfall corresponded well with observations. We then use the simulated fields as forcing and boundary conditions for MM5 run in cloud-system resolving mode at 2 km grid-resolution to detail cloud-clusters embedded within the monsoon disturbance. We examined the sensitivity to different physical parameterizations and also the effect of continuous nudging four dimensional data assimilation (FDDA) on the rainfall forecasts. While the simulation of the convective event improved with certain combinations of physical parameterizations, the rainfall was not forecasted at the correct location, no matter which parameterization was used, unless continuous FDDA was performed in all domains throughout the integrations. Finally, cloud-cluster properties of the cloud-system resolving simulations were compared with observations.
Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.
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