Probabilistic Forecasting of the 500 hPa Geopotential Height over the Northern Hemisphere Using TIGGE Multi-model Ensemble Forecasts

Bayesian model averaging (BMA) and ensemble model output statistics (EMOS) were used to improve the prediction skill of the 500 hPa geopotential height field over the northern hemisphere with lead times of 1–7 days based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and UK Met Office (UKMO) ensemble prediction systems. The performance of BMA and EMOS were compared with each other and with the raw ensembles and climatological forecasts from the perspective of both deterministic and probabilistic forecasting. The results show that the deterministic forecasts of the 500 hPa geopotential height distribution obtained from BMA and EMOS are more similar to the observed distribution than the raw ensembles, especially for the prediction of the western Pacific subtropical high. BMA and EMOS provide a better calibrated and sharper probability density function than the raw ensembles. They are also superior to the raw ensembles and climatological forecasts according to the Brier score and the Brier skill score. Comparisons between BMA and EMOS show that EMOS performs slightly better for lead times of 1–4 days, whereas BMA performs better for longer lead times. In general, BMA and EMOS both improve the prediction skill of the 500 hPa geopotential height field.

Identifying Weather Regimes in the Wintertime 500-hPa Geopotential Height Field for the Pacific–North American Sector Using a Limited-Contour Clustering Technique

A hierarchical clustering algorithm using Ward’s method has been applied to the 500-hPa geopotential height field in the Pacific–North American sector. In contrast to previous clustering studies that measure distance between records by using all the grid points within the domain (full-field method), the procedure outlined here, referred to as the limited-contour method, focuses on the coordinates of the 540-dam contour as the distance measure. Comparison between the regimes emerging from the two methods shows that the limited-contour method is more efficient than the full-field method with respect to grouping maps with ridges located at similar longitudes. The four regimes emerging from the limited-contour clustering analysis have been named as follows: Off-Shore Trough, Alaskan Ridge, Coastal Ridge, and Rockies Ridge. The frequencies of occurrence of the regimes have a significant relationship with the phase of the El Niño–Southern Oscillation. El Niño winters exhibit a strong preference for the Rockies Ridge pattern; La Niña winters exhibit a greater diversity of regimes. The frequencies of occurrence of extreme cold outbreaks and episodes of heavy precipitation in the Pacific Northwest show a relatively strong connection to the regime type. For other regions in the western portion of the United States, only the frequency of occurrence of cold outbreaks exhibits a significant relationship to regime type.