Ensemble Downscaled Climate Dataset for Alaska and Hawaii Under Historical and Future Conditions

While high-resolution future climate data are increasingly available for the contiguous United States, there has been limited focus on Alaska and Hawaii. Our study provides high temporal and spatial resolution climate data (daily precipitation and temperature on spatial grids of 10 km for Alaska and 1 km for Hawaii) based on 23 climate models from the Coupled Model Intercomparison Project Phase 6 and four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). These datasets include different statistical downscaling and bias correction techniques (seven for precipitation, six for temperature). While one method (i.e., empirical quantile mapping) generally outperforms the others, its performance can vary by climate quantity, region, or climate model, motivating our aim to provide an ensemble dataset of bias-corrected outputs. This community dataset will permit investigations into the sources of climate uncertainty and climate change uncertainty at the local scale. They may also be used for climate risk assessment across a range of societal sectors. A primary reason for their development by the authors is to drive hydrologic models and explore questions of hydrologic change in these underexplored regions. These data are described in a paper under review in the journal Scientific Data.

尽管针对美国本土的高分辨率未来气候数据日益丰富，但针对阿拉斯加与夏威夷的相关研究却相对匮乏。本研究基于耦合模式比较计划第六阶段（Coupled Model Intercomparison Project Phase 6）的23个气候模式，以及SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5四种共享社会经济路径情景，构建了高时空分辨率气候数据集：阿拉斯加地区采用10公里空间网格，夏威夷地区采用1公里空间网格，数据内容包含日降水量与气温。该数据集涵盖多种统计降尺度与偏差校正方法（其中降水校正方法7种，气温校正方法6种）。尽管经验分位数映射法（empirical quantile mapping）整体表现优于其他方法，但其性能会因气候要素、研究区域或气候模式的不同而存在差异，因此本研究旨在构建偏差校正结果的集合数据集。这款社区数据集可用于探究局地尺度下气候不确定性与气候变化不确定性的来源，同时还可用于多社会领域的气候风险评估。本数据集的研发初衷之一，是为驱动水文模型、探究这些尚未被充分研究区域的水文变化问题提供支撑。相关研究成果已投稿至《Scientific Data》期刊，目前处于审稿阶段。

搜集汇总

背景与挑战

背景概述

该数据集提供了阿拉斯加（10公里分辨率）和夏威夷（1公里分辨率）地区的高时空分辨率气候数据，涵盖1981年至2100年的历史和未来情景，基于23个气候模型和四种SSP情景。数据集包含多种降尺度和偏差校正方法，适用于气候变化不确定性分析和气候风险评估。