An Ensemble Downscaling Prediction Experiment for Medium-Range Forecast of the Daily Mean Surface Temperature Distribution over Northeastern Japan during Summer

Abstract

To assess medium-range forecasts of detailed spatial distributions of the daily mean temperature, an ensemble downscaling forecast experiment was conducted using the Japan Meteorological Agency (JMA) nonhydrostatic model (NHM) with horizontal resolutions of 25 km and 5 km. Special attention was paid to the anomalously cool summers over northeastern Japan caused by northeasterly winds called Yamase. The results are validated against the daily mean surface temperatures observed by the Automated Meteorological Data Acquisition System (AMeDAS) in the study area. Ensemble mean downscaling forecasts can successfully extract reliable signals with information about local circulations. The ensemble mean forecasts reduce the root mean square errors of the daily mean surface temperature by 15 % compared to single downscaling forecasts. The ensemble spreads also indicate the possibility of making probabilistic predictions that consider the effects of local circulations in addition to large-scale motions. The ensemble downscaling forecasts have 80 % larger spreads than the global forecasts with the JMA global spectral model at a resolution TL159L60 and approach the theoretical value. An empirical orthogonal function (EOF) analysis indicates that the predictability depends on the EOF modes. The predictable periods are 8 days for the homogeneous mode over northeastern Japan, 5 days for the Yamase mode (east-west mode), and 2 days for the north-south mode. The dynamical downscaling can properly predict the amplitudes of the EOF modes. In particular, the dynamical downscaling can predict 90 % of the Yamase mode, as compared to 20 % prediction of the global model for the same mode.