In the pursuit of providing tropical cyclone (TC) forecasts beyond the conventional timescales covered by weather forecasting in the Philippines, this study has examined the multi-week (i.e., from Week-1 to Week-4) TC forecast skill in the country. TC forecasts derived from three ensemble models, namely: NCEP Climate Forecast System version 2 (CFSv2), European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF), and NCEP Global Ensemble Forecast System version 12 (GEFSv12) from 06 October 2020 to 31 October 2021 were verified. Results revealed that the ECMWF model is consistently the most skillful in multi-week TC prediction over the domain bounded by 110°–155°E and 0°–27°N in the western North Pacific. The ECMWF obtained hit rates ranging from 0.25 to 0.31, low false alarm rates of 0–0.33, and the highest equitable threat scores among the models. In contrast to this, the GEFSv12 and CFSv2 models had varying skills, with the former performing better in the first two weeks and the latter in longer lead times. It is further revealed that the three models generally underestimate the observed number of storms, storm days, and accumulated cyclone energy. Moreover, the study shows that the forecast TC tracks have a significant (p<0.05) positional bias toward the right of observed tracks beyond Week-1, and that they tend to propagate slower than observations especially in Week-1 and Week-2. These findings contribute to better understanding the strengths and limitations of these ensemble models useful for eventual provision of multi-week TC forecasts in the Philippines.
