Statistical Analysis of Present and Future River Water Temperature in Cold Regions Using Downscaled GCMs Data

Abstract

河川水温の上昇は、水質や生態系に重大な影響を及ぼすことが懸念される。本研究は、寒冷地域における河川水温の長期間(現在と将来)変動の解析を目的とする。まず、札幌における長期間(1961年-2001年)の季節変動と年変動を解析する。その後、将来の水温を予測するため、統計的ダウンスケーリング法を用い、北海道における将来の日単位気温をダウンスケーリングする。また、札幌における観測された日単位の気温と水温の関係を解析し、米国大気海洋庁の NCEP 再解析データ(1961-2000)と英国ハドレーセンター(Hadley Centre)のHadCM3(Hadley Climate Model)のGCMデータ(1961-2099)を用い、札幌における将来の河川水温を予測する。

Stream water temperature has a direct impact on the water quality and ecosystem through its influences on many chemical processes. The main objectives of this study is to investigate the long term monthly and yearly variation of stream water temperatures in cold regions for both historical and future periods. Firstly, the long-term trends (1961-2001) in the monthly and yearly time series of water temperature at Sapporo were identified. Then, to predict the future water temperatures, the approach of downscaling the outputs of a global climate model (GCM) to a local scale was investigated by employing the Statistical Downscaling Model to downscale air temperature (T) in both the present and future climate scenarios. The above downscaling approach was applied to the Sapporo meteorological station in Japan by simulating the local scale daily temperature based on large scale atmospheric variables including National Center for Environmental Prediction (NCEP) reanalysis datasets (1961-2000) and a general circulation model (HadCM3) outputs (1961-2099).