Total energy norm in NWP closure parameter optimization

P. Ollinaho, H. Järvinen, P. Bauer, M. Laine, P. Bechtold, J. Susiluoto, H. Haario
2013 Geoscientific Model Development Discussions  
We explore the use of total energy norm in improving numerical weather prediction (NWP) model forecast skill. The Ensemble Prediction and Parameter Estimation System (EPPES) is utilized to estimate ECHAM5 atmospheric GCM closure parameters related to clouds and precipitation. The target criterion in the optimization is the total 5 energy norm of three-day forecast error with respect to the ECMWF operational analyses. The results are summarized as follows: (i) forecast error growth in terms of
more » ... rowth in terms of energy norm is slower in the optimized than in the default model up to day ten forecasts (and beyond), (ii) headline forecast skill scores are improved in the training sample as well as in independent samples, (iii) the decrease of the forecast error energy norm at day 15 20 the aim is also to increase predictive skill. Tuning procedures in modeling are predominantly manual and there are no generally applicable or accepted algorithmic tools in everyday use. One reason is that in multi-scale and multi-phase systems the model response to closure parameter variations is very non-linear and general non-stationary inverse problem tools can fail. Therefore results may be promising in idealized cases 25 but this does not seem to carry-on to more demanding real-world estimation cases. 6718 GMDD This difficulty is nicely illustrated in Schirber et al. (2013) where the inverse problem realism is gradually increased from synthetic to fully realistic estimation in case of an atmospheric general circulation model. The parameter-augmented state filter works well in an idealized setup but is less succesful in realistic estimation cases. The aim of this paper is by no means to declare that a final solution has been found to 5 20 terms of total energy norm. As the energy norm is computed as an integral over the entire model atmosphere, it is not selective to any particular model variable, level, or geographical region. It is thus a potentially powerful target. Experiment configuration The ECHAM5 .4 atmospheric general circulation model (Roeckner et al., 2003) is used 25 here with a coarse horizontal resolution of T42 and 31 vertical layers, the model top being at 10 hPa. Abstract 20 The ECMWF operational analyses are used in computation of Eq. (2). The target criterion, or cost function, for the EPPES estimation is then the forecast error from analysis, the norm being the total energy norm. 6721 GMDD Abstract GMDD
doi:10.5194/gmdd-6-6717-2013 fatcat:5iwzfc3eajao7djks6rnqtiqem