Review of the U.S. Climate Change Science Program's Synthesis and Assessment Product 3.2, "Climate Projections Based on Emission Scenarios for Long-lived and Short-lived Radiatively Active Gases and Aerosols"

2007 ◽  
Author(s):  
Toshichika Iizumi ◽  
Mikhail A. Semenov ◽  
Motoki Nishimori ◽  
Yasushi Ishigooka ◽  
Tsuneo Kuwagata

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.


2010 ◽  
Vol 7 (5) ◽  
pp. 6823-6850 ◽  
Author(s):  
H. Xu ◽  
R. G. Taylor ◽  
Y. Xu

Abstract. Quantitative evaluations of the impacts of climate change on water resources are primarily constrained by uncertainty in climate projections from GCMs. In this study we assess uncertainty in the impacts of climate change on river discharge in two catchments of the River Yangtze and Yellow Basins that feature contrasting climate regimes (humid and semi-arid). Specifically we quantify uncertainty associated with GCM structure from a subset of CMIP3 AR4 GCMs (HadCM3, HadGEM1, CCSM3.0, IPSL, ECHAM5, CSIRO, CGCM3.1), SRES emissions scenarios (A1B, A2, B1, B2) and prescribed increases in global mean air temperature (1 °C to 6 °C). Climate projections, applied to semi-distributed hydrological models (SWAT 2005) in both catchments, indicate trends toward warmer and wetter conditions. For prescribed warming scenarios of 1 °C to 6 °C, linear increases in mean annual river discharge, relative to baseline (1961–1990), for the River Xiangxi and River Huangfuchuan are +9% and 11% per +1 °C, respectively. Intra-annual changes include increases in flood (Q05) discharges for both rivers as well as a shift in the timing of flood discharges from summer to autumn and a rise (24 to 93%) in dry season (Q95) discharge for the River Xiangxi. Differences in projections of mean annual river discharge between SRES emission scenarios using HadCM3 are comparatively minor for the River Xiangxi (13% to 17% rise from baseline) but substantial (73% to 121%) for the River Huangfuchuan. With one minor exception of a slight (−2%) decrease in river discharge projected using HadGEM1 for the River Xiangxi, mean annual river discharge is projected to increase in both catchments under both the SRES A1B emission scenario and 2° rise in global mean air temperature using all AR4 GCMs on the CMIP3 subset. For the River Xiangxi, there is great uncertainty associated with GCM structure in the magnitude of the rise in flood (Q05) discharges (−1% to 41% under SRES A1B and −3% to 41% under 2° global warming) and dry season (Q95) discharges (2% to 55% under SRES A1B and 2% to 39% under 2° global warming). For the River Huangfuchuan, all GCMs project a rise in the Q05 flow but there is substantial uncertainty in the magnitude of this rise (7% to 70% under SRES A1B and 2% to 57% under 2° global warming). Greatest differences in the projected hydrologic changes are associated with GCMs in both catchments than emission scenarios and climate sensitivity. Critically, estimated uncertainty in projections of mean annual flows is less than that calculated for extreme (Q05, Q95) flows. This research suggest that the common approach of reporting of climate change impacts on river in terms of mean annual flows may mask the magnitude of uncertainty in flows of most importance to water managers.


2018 ◽  
Vol 66 (6) ◽  
pp. 1509-1523 ◽  
Author(s):  
Zbigniew W. Kundzewicz ◽  
Mikołaj Piniewski ◽  
Abdelkader Mezghani ◽  
Tomasz Okruszko ◽  
Iwona Pińskwar ◽  
...  

Abstract The present paper offers a brief assessment of climate change and associated impact in Poland, based on selected results of the Polish–Norwegian CHASE-PL project. Impacts are examined in selected sectors, such as water resources, natural hazard risk reduction, environment, agriculture and health. Results of change detection in long time series of observed climate and climate impact variables in Poland are presented. Also, projections of climate variability and change are provided for time horizons of 2021–2050 and 2071–2100 for two emission scenarios, RCP4.5 and RCP8.5 in comparison with control period, 1971–2000. Based on climate projections, examination of future impacts on sectors is also carried out. Selected uncertainty issues relevant to observations, understanding and projections are tackled as well.


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