Historical trends in climate indices relevant to surface air temperature and precipitation in Japan for recent 120 years

Abstract

AbstractGeographical distributions of trends in climate indices with statistical significance in Japan are investigated at each of the 51 observation stations for the recent 120 years. We employed a comprehensive set of the 70 climate indices on an annual timescale to detect climate changes and to facilitate climate information for a variety of sectors, which are developed by expert team on sector‐specific indices in the World Meteorological Organization. The rising trends have regional differences such as the annual mean of daily maximum and minimum surface air temperatures in the Kanto‐Koushin region. The statistically significant increasing trends in three daily heavy precipitation‐relevant climate indices, R95p, R99p, and RX1day, are seen in Hokuriku, Shikoku, the western part of Northern and Southern Kyusyu regions, and isolated stations in the other regions. Rotational empirical orthogonal function analysis of R99p revealed different features of statistically significant modes suggesting the trends are attributed to changes in different atmospheric phenomena as well as those of warm spell duration index. The number of the stations with statistically significant trends varies with an index. Indies relevant to daily minimum surface air temperatures have statistically significant trends at most of the 51 stations. Consecutive dry days are the most sensitive to climate changes for the 120 years among the indices relevant to precipitation in this analysis. The indices relevant to heavy precipitation are not always been most sensitive to climate change detections in Japan. The geographical distributions of the percentage of the number of indices with statistically significant changes to the total number of the stations provide information about stations sensitive to climate changes. The highest sensitivity is seen at Kumamoto. These results directly provide detection of climate changes and show the potentials of which index is sensitive to ongoing climate changes from the viewpoint of geographical distributions.