著者
NAKAMURA Shingo KUSAKA Hiroyuki SATO Ryogo SATO Takuto
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2022-030, (Released:2022-04-08)
被引用文献数
4

This study assesses heatstroke risk in the near future (2031-2050) under RCP8.5 scenario. The developed model is based on a generalized linear model with the number of ambulance transport due to heatstroke (hereafter the patients with heatstroke) as the explained variable and the daily maximum temperature or Wet-Bulb Globe Temperature (WBGT) as the explanatory variable. With the model based on the daily maximum temperature, we performed the projection of the patients with heatstroke in case of considering only climate change (Case 1), climate change and population dynamics (Case 2), and climate change, population dynamics, and long-term heat acclimatization (Case 3). In Case 2, the number of patients with heatstroke in the near future will be 2.3 times higher than that in the baseline period (1981-2000) on average nationwide. The number of future patients with heatstroke in Case 2 is about 10 % larger than that in Case 1 on average nationwide despite of population decline. This is due to the increase in the number of elderly people from the baseline period to the near future. However, there were 21 prefectures where the number of patients in Case 2 is smaller compared to Case 1. Comparing the results from Cases 1 and 3 reveals that the number of patients with heatstroke could be reduced by about 60 % nationwide by acquiring heat tolerance and changing lifestyles. Notably, given the lifestyle changes represented by the widespread use of air conditioners, the number of patients with heatstroke in the near future was lower than that of the baseline period in some areas. In other words, lifestyle changes can be an important adaptation to the risk of heatstroke emergency. All of the above results were also confirmed in the prediction model with WBGT as the explanatory variable.
著者
SATO Takuto KUSAKA Hiroyuki
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2021-047, (Released:2021-04-14)
被引用文献数
1

In this study, we compare the accuracy of five representative similarity metrics in extracting sea level pressure (SLP) patterns for accurate weather chart classification: correlation coefficient, Euclidean distance (EUC), S1-score (S1), structural similarity (SSIM), and average hash. We use a large amount of teacher data to statistically evaluate the accuracy of each metric. The evaluation results reveal that S1 and SSIM have the highest accuracy in terms of both average and maximum scores. Their accuracy does not change even when non-ideal data are used as the teacher data. In addition, S1 and SSIM can reproduce the subjective resemblance between two maps better than EUC. However, EUC reproduces the central position of the signal in a sample case. This study can serve as a reference for identifying the most useful similarity metric for the classification of SLP patterns, especially when using non-ideal teacher data.