Estimating gravity wave parameters with a genetic algorithm for realistic gravity wave drag profiles

There is a current need to constrain the parameters of gravity wave drag schemes of climate models using observational information instead of tuning them arbitrarily. In this work, a technique is developed using inverse modelling to estimate parameters from gravity wave schemes. We define a cost function that measures the differences between the zonal and meridional components of the observed gravity wave drag field and the gravity wave drag calculated with a scheme. Because most gravity wave drag schemes assume instantaneous vertical propagation of gravity waves in a column, observations in a single column can be used to obtain information about input parameters to a gravity wave drag scheme so that a one-dimensional inverse problem is formulated. The minimization is performed using a mixed method based on a genetic algorithm and conjugate gradients. In this work we estimate the parameters for gravity wave drag analised fields, ie the output of the ASDE assimilation system developed by Pulido and Thuburn. The ability of the gravity wave drag scheme to fit the gravity wave drag vertical profiles is discussed.