Mesoscale modeling investigation using PENNSTATE/NCAR MM5 model and remote sensing technology for weather simulation and prediction

The objective of present study is to adapt the MM5 climate and weather prediction model for possible use in areas where solar cookers and solar Stirling engines will be used under the NASA/HBCU Renewable Energy and Technology Utilization project. Equipments that use solar energy for cooking and heating are valuable in areas that predominantly include third world countries where other resources are limited. In such conditions solar energy cannot be wasted; hence to make use of it at the right time effectively, accurate prediction of sunshine is absolutely necessary. The MM5 modeling system is used as a research tool for diagnostics and prediction of mesoscale weather patterns and circulations. Two regions were chosen as case study-Washington D.C. and Louisiana. NCEP/NCAR global analysis data is used to construct the initial and boundary conditions. Later the simulation uses the remote sensing data including satellite and radar for model initialization and run. The model is run for a 48 hour time period on 14-15 June, 2002 over Washington D.C. and 2-3 October, 2002 over the Louisiana costal region. Cloud cover, precipitation and sunshine are the major parameters of model simulation and forecast. Better prediction of sunshine help solar energy equipments be better utilized.