21st Century Hydrologic Projections for Alaska and Hawaii

High resolution ensembles of hydroclimate projections are useful for climate and water resources adaptation planning and many of these datasets exist over United States focused domains specifically the Contiguous United States (CONUS). However, very few century-long, high-resolution hydroclimate projections exist over Alaska and Hawaii and no statewide projections including hydrology exist. This motivated us to develop a dataset consisting of multiple statistically downscaled climate model projections and corresponding off-line hydrologic model simulations to obtain hydrologic simulations from 1950 to 2099 over the two domains, which fills a critical gap in hydroclimate projection capabilities for these two under-served regions. We take an approach similar to previous CONUS hydrologic assessments where we: 1) select climate model outputs based on CMIP5 Representative Concentration Pathway 4.5 and 8.5; 2) perform statistical downscaling to generate high-resolution climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaii); and 3) perform off-line hydrologic model simulations, using the Variable Infiltration Capacity (VIC) model. A notable difference in the hydrologic model configuration from CONUS to this case, is the use of full water-energy balance computation with a simple glacier model for Alaska. Overall, the simulations in Hawaii show large uncertainty in total runoff driven by large variability in precipitation among the GCMs used for this study. Robust warming and increases in precipitation produce runoff increases for most of Alaska. However, runoff is likely to decrease in current glacierized areas in southeast Alaska.

高分辨率水文气候集合预估成果对气候与水资源适应规划具有重要应用价值，目前美国境内已有多款此类数据集，其中尤以美国本土48州（Contiguous United States, CONUS）相关成果最为丰富。然而，针对阿拉斯加与夏威夷的百年尺度高分辨率水文气候预估成果却极为匮乏，且目前尚无覆盖全州且包含水文模块的相关预估数据集。为此，本研究开发了一款数据集，包含多套经统计降尺度处理的气候模式预估结果，以及与之匹配的离线水文模式模拟成果，可生成1950年至2099年期间阿拉斯加与夏威夷全域的水文模拟数据，填补了这两个欠充分研究区域在水文气候预估能力上的关键空白。本研究采用与此前美国本土48州水文评估类似的技术路线，具体步骤如下：1）基于耦合模式比较计划第五阶段（CMIP5）的典型浓度路径（Representative Concentration Pathway, RCP）4.5与8.5情景筛选气候模式输出结果；2）开展统计降尺度处理，生成适配水文模式的高分辨率气候输入数据（阿拉斯加区域网格分辨率为12千米，夏威夷区域为1千米）；3）采用可变下渗容量（Variable Infiltration Capacity, VIC）模型开展离线水文模式模拟。与美国本土48州的水文模式配置相比，本数据集存在一项显著差异：针对阿拉斯加区域，我们采用了包含完整水-能量平衡计算的方案，并耦合了简化冰川模型。总体而言，由于本研究所用的全球大气环流模式（General Circulation Model, GCM）在降水模拟上存在较大差异，夏威夷区域的总径流模拟结果呈现出显著不确定性。阿拉斯加大部分区域将经历显著增温与降水增加，进而导致径流上升；但阿拉斯加东南部现有冰川覆盖区域的径流则可能出现下降。