論文ID: 2022-024
We investigated the sub-seasonal predictability of heavy snowfall events in Iwamizawa, Hokkaido, using the Japan Meteorological Agency's 1-month ensemble predictions. First, the self-organizing map (SOM) technique was applied to the Japanese 55-year Reanalysis sea-level pressure anomalies to identify weather patterns resulting in heavy snowfall. It revealed that heavy snowfall developed in SOM nodes (weather patterns) with low-pressure centers to the east/northeast of Hokkaido and Siberian high to the west, resulting in westerly to northwesterly monsoon winds traversing the Sea of Japan towards western Hokkaido. Next, ensemble forecasts were projected onto the SOM map to determine the predictability of weather patterns up to a month in advance. For winter 2019, there was relatively low probability of projecting a high number of ensembles in SOM nodes to those observed in the reanalysis. In contrast, much higher probability was seen in 2020 to ∼10 forecast days. When considering multiple SOM nodes that contribute to heavy snowfall in the forecast, both winters saw more ensemble members predicting heavy snowfall to ∼10 forecast days. We also saw a higher probability of heavy snowfall beyond 10-days in 2020. These results highlight the potential benefit of incorporating multiple weather patterns to forecast heavy snowfall.