Improving severe storms forecasts by better constraining initial conditions

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In order to make better weather forecasts, it is essential to provide the computer with the best description of the current weather situation.  Because we cannot measure all atmospheric parameters such as temperature and humidity everywhere for the whole atmosphere from the surface up, we rely on a combination of observations and physical relationships between the different atmospheric parameters to get the best picture of the current weather situation.  This technique is referred to as data assimilation.Although data assimilation is done more and more often, it is not clear that we are doing it the best that we can.  Are the best combinations of observations used?  Should we use other instruments instead?  Are we using observations over too short or too long a period?In this work, we will simulate the process of data assimilation using a computer-based approach to investigate what types of observations do the best job at describing the atmosphere as completely as possible.  We will simulate how existing and planned instruments help in this process or not.  Finally, we will use the results of this simulation to demonstrate using real observations and weather forecasting that we have determined the best combinations of instruments to perform data assimilation.