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Implementation of a high-resolution atmosphere-ocean coupled model with an ensemble Kalman filter

For the application of an ensemble Kalman filtering (EnKF) to limited-area models for regional numerical weather prediction, treating uncertainties of boundary conditions has been one of the major issues. Although there are some previous studies focusing on effectiveness of lateral boundary uncertainties, few studies investigated in detail the impact of perturbing the lower boundary conditions with an EnKF. In this study, a high-resolution atmosphere-ocean coupled model is implemented with the EnKF, so that the sensitivity of SST perturbations on an EnKF data assimilation cycles is evaluated.

A five-year research project of high performance regional numerical weather prediction has been started since 2011 as one of the five research fields of the Strategic Programs for Innovative Research (SPIRE). The ultimate goal of the project is to demonstrate feasibility of precise prediction of sever whether phenomena using high performance computing resources such as the K-computer. The following three subjects have been conducted; 1) Development of cloud resolving four dimensional data assimilation systems, 2) Development and validation of a cloud resolving ensemble analysis and prediction system, 3) Basic research using very high resolution atmospheric models. <br>In this session, we will present the scientific achievement in the project, and discuss about study of the mesoscale meteorology on current and future high performance computing infrastructures.  

Japan Geoscience Union

Japan Geoscience Union Meeting 2015

Japan Geoscience Union Meeting 2015

[AAS02-07]Implementation of a high-resolution atmosphere-ocean coupled model with an ensemble Kalman filter