A framework for modeling uncertainty in regional climate change
作者： Erwan Monier , Xiang Gao , Jeffery R. Scott , Andrei P. Sokolov , C. Adam Schlosser
DOI: 10.1007/S10584-014-1112-5
关键词: Environmental science 、 Climate model 、 Mean radiant temperature 、 Precipitation 、 Climatology 、 Meteorology 、 Range (statistics) 、 Climate change 、 Transient climate simulation 、 Climate sensitivity 、 Atmospheric model
摘要: In this study, we present a new modeling framework and large ensemble of climate projections to investigate the uncertainty in regional change over United States (US) associated with four dimensions uncertainty. The sources considered are emissions projections, global system parameters, natural variability model structural revolves around Massachusetts Institute Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment Earth Intermediate Complexity (EMIC) (with two-dimensional zonal-mean atmosphere). Regional US is obtained through two-pronged approach. First, use IGSM-CAM framework, which links IGSM National Center for Atmospheric Research (NCAR) Community Atmosphere (CAM). Second, pattern-scaling method that extends zonal mean based on patterns from various models. Results show range annual temperature changes mainly driven by policy choices sensitivity considered. Meanwhile, contribute more equally end-of-century precipitation changes, dominating until 2050. For set scenarios used choice largest driver uncertainty, defined as warming precipitation, future US.
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