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首页> 外文期刊>Physical Geography >Downscaling climate-model output in mountainous terrain using local topographic lapse rates for hydrologic modeling of climate-change impacts
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Downscaling climate-model output in mountainous terrain using local topographic lapse rates for hydrologic modeling of climate-change impacts

机译:利用本地地形流逝速率的山地地形缩小气候模型输出,用于气候变化影响的水文建模

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摘要

One of the challenges in using general circulation model (GCM) output is the need to downscale beyond the model's coarse spatial grid for use in hydrologic modeling of climate-change impacts. In mountainous terrain, using elevation as a primary control on temperature and precipitation at the local scale provides the potential for topographic variables to be used to adjust climate-model output. Here, local topographic lapse rates (LTLR) were estimated from gridded climate data for the Pacific Northwest of the United States and used to downscale GCM output. Skill scores were calculated for the LTLR-downscaled climate-model output relative to an existing set of model output downscaled using the established statistical downscaling technique of localized constructed analogs (LOCA). The results indicate that the LTLR method performs well in the mountainous study region relative to the LOCA method. LTLR downscaling offers a promising method for downscaling climate-model output in regions in which elevation strongly controls climate, particularly for studying impacts of future climate change on water resources.
机译:使用一般循环模型(GCM)输出的挑战之一是需要在模型的粗糙空间网格之外脱节,以用于气候变化影响的水文建模。在山区地形中,使用升降作为对局部温度和沉淀的主要控制,提供了用于调整气候模型输出的地形变量的潜力。在这里,本地地形失效率(LTLR)估计了美国太平洋西北地区的网格气候数据,并习惯了低档GCM产量。对于使用局部构造类似物(Loca)的建立的统计缩小技术(LOCA)的统计缩小技术,为LTLR-Downscalded气候模型输出计算了LTLR-Downscaled气候模型输出。结果表明,LTLR方法在山区研究区域相对于基因座方法中的表现良好。 LTLR Downscaling提供了一种有希望的方法,用于在海拔强烈控制气候的地区缩小气候模型输出的有希望的方法,特别是为了研究未来气候变化对水资源的影响。

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