ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan
TLDR
A dataset of local-scale daily climate change scenarios for Japan using the stochastic weather generators LARS-WG and, in part, WXGEN offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.Abstract:
We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981–2000 is assessed using several statistical tests and quantile–quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081–2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.read more
Citations
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Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections
TL;DR: In this article, the integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator is described.
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Genotypic differences in soybean yield responses to increasing temperature in a cool climate are related to maturity group
Etsushi Kumagai,Ryoji Sameshima +1 more
TL;DR: The yield of the late-maturing cultivars sown during the conventional season in the cool regions of Japan will increase during the 21st century, and the differential response in post-flowering development in different maturity groups is probably related to the differences in the day length requirements of these cultivars.
Journal ArticleDOI
A meteorological forcing data set for global crop modeling: Development, evaluation, and intercomparison
TL;DR: The Global Risk Assessment toward Stable Production of Food (GRASP) project uses global crop models to evaluate the impacts on global food security by changes in climate extremes, water resources, and land use as mentioned in this paper.
Journal ArticleDOI
Future change of daily precipitation indices in Japan: A stochastic weather generator‐based bootstrap approach to provide probabilistic climate information
Toshichika Iizumi,Izuru Takayabu,Koji Dairaku,Hiroyuki Kusaka,Motoki Nishimori,Gen Sakurai,Noriko N. Ishizaki,Sachiho A. Adachi,Mikhail A. Semenov +8 more
TL;DR: In this article, a stochastic weather generator (WG)-based bootstrap approach is proposed to provide the probabilistic climate change information on mean precipitation as well as extremes, which applies a WG (i.e., LARS-WG) to daily precipitation under the present-day and future climate conditions derived from dynamical and statistical downscaling models.
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