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Information about several papers discussed at the International Conference on Mesoscale Processes in Atmosphere, Ocean and Environmental Systems, held at the Centre for Atmospheric Sciences of the Indian Institute of Technology (IIT), Delhi, India is presented. Topics included high resolution mesoscale models, special computation techniques, land-ocean-atmosphere processes and satellite observations. The participants included professors, T. Krishnamurti, R. Narsimha, and J.C.R. Hunt.

In this paper, an attempt has been made to evaluate cloudiness/haziness and atmospheric transmittance factors for the composite climate of New Delhi, India by considering the hourly data of global and diffuse radiation obtained for (i) the city region, experimentally observed and (ii) the flat land region obtained from the Department of Indian Meteorology, Pune. Cloudiness/haziness factor for the two models have been determined using simple regression analysis for clear sky condition for New Delhi. The comparison between the cloudiness/haziness and atmospheric transmittance factors for the composite climate of New Delhi for both the models and regions have been made. It has been observed that the cloudiness/haziness and atmospheric transmittance factors obtained by both models gave fair agreement within an accuracy of 0.57%. It has also been observed that there is a significant effect of region on beam and diffuse radiation due to cloudiness/haziness factors as expected. Further the data of solar radiation obtained from the Department of Indian Meteorology, Pune, have been used to evaluate the monthly performance of photovoltaic thermal (PV/T) air collector. It has been found that an overall thermal efficiency and exergy efficiency of PV/T air collector were about 50 and 14%, respectively. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

India Meteorological Department (IMD) has been using a Limited Area Model (LAM) on operational basis for the forecast up to 48 hours with the first guess fields for objective analysis and lateral boundary conditions from the global spectral model (T-80) run of the National Center for Medium Range Weather Forecasting (NCMRWF), New Delhi. In this paper the model code has been modified and made more flexible, delinking it from the NCMRWF (T-80). This has allowed the use of initial and boundary conditions directly from the NCEP Global Forecast System (GFS) products available at the resolution of 1° × 1° lat./long. The main interest in this study is to improve the analysis and forecast in the short range time scale (up to 72 hours) by improving the model (LAM) resolution and using better Initial and boundary conditions from the NCEP GFS instead of the NCMRWF T-80 model. Simulation experiments are performed on wide variety of synoptic situations which occur very often over the Indian sub-continent. The performance evaluation in terms of qualitative comparison between the model simulated outputs against actual observations and the outputs of the operational model indicates that the modified version of the model is capable to provide a improved numerical guidance on the occurrence of heavy rainfall in the 48-72 hours forecast scale. [ABSTRACT FROM AUTHOR]

A comparative study was performed to evaluate the performance of the UK Met Office’s Global Seasonal (GloSea) prediction General Circulation Model (GCM) for the forecast of maximum surface air temperature (Tmax) over the Indian region using the model generated hindcast of 15-members ensemble for 16 years (1987–2002). Each hindcast starts from 1st January and extends for a period of six months in each year. The model hindcast Tmax is compared with Tmax obtained from verification analysis during the hot weather season on monthly and seasonal scales from March to June. The monthly and seasonal model hindcast climatology of Tmax from 240 members during March to June and the corresponding observed climatology show highly significant (above 99.9% level) correlation coefficients (CC) although the hindcast Tmax is over-estimated (warm bias) over most parts of the Indian region. At the station level over New Delhi, although the forecast error (forecast-observed) at the monthly scale gradually increases from March to June, the forecast error at the seasonal scale during March to May (MAM) is found to be just 1.67 °C. The GloSea model also simulates well Tmax anomalies on monthly and seasonal scales during March to June with the lower Root Mean Square Error (RMSE) of bias corrected forecast (less than 1.2 °C), which is much less than the corresponding RMSE of climatology (reference) forecast. The anomaly CCs (ACCs) over the station in New Delhi are also highly significant (above 95% level) on monthly to seasonal time scales from March to June, except for April. The skill of the GloSea model for the seasonal forecast of Tmax as measured from the ACC map and the bias corrected RMSE map is reasonably good during MAM and April to June (AMJ) with higher ACC (significant at 95% level) and lower RMSE (less than 1.5 °C) found over many parts of the Indian regions. [ABSTRACT FROM AUTHOR]