Yuan Huihui, Ning Like, Zhou Jiewei, Shi Wen, Huang Jianbin, Luo Yong
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing, 101408, China.
Sci Data. 2024 Oct 24;11(1):1167. doi: 10.1038/s41597-024-03982-x.
Accurate climate projections are critical for various applications and impact assessments in environmental science and management. This study presents HiCPC (High-resolution CMIP6 downscaled daily Climate Projections over China), a novel dataset tailored to China's specific needs. HiCPC leverages outputs from 22 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). To address inherent biases in daily GCM simulations, an advanced Bias Correction and Spatial Disaggregation (BCSD) method is employed, using the China Meteorological Forcing Dataset (CMFD) as a reference. HiCPC offers detailed daily precipitation and temperature data across China at an enhanced spatial resolution of 0.1° × 0.1°. It covers both the historical period (1979-2014) and future projections (2015-2100) based on four CMIP6 Shared Socioeconomic Pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Upon validation, HiCPC demonstrates good performance, surpassing CMIP6 GCMs across the historical period. This reinforces its significance for essential research in climate change evaluation and its associated implications within China.
准确的气候预测对于环境科学与管理中的各种应用和影响评估至关重要。本研究介绍了HiCPC（中国高分辨率CMIP6降尺度每日气候预测），这是一个针对中国特定需求定制的新型数据集。HiCPC利用了耦合模式比较计划第六阶段（CMIP6）中22个全球气候模型（GCM）的输出。为了解决每日GCM模拟中固有的偏差，采用了先进的偏差校正和空间分解（BCSD）方法，并以中国气象强迫数据集（CMFD）作为参考。HiCPC以0.1°×0.1°的增强空间分辨率提供了中国详细的每日降水和温度数据。它涵盖了基于四个CMIP6共享社会经济路径（SSP）情景（SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5）的历史时期（1979-2014年）和未来预测（2015-2100年）。经过验证，HiCPC表现良好，在历史时期超过了CMIP6 GCM。这强化了其在中国气候变化评估及其相关影响的基础研究中的重要性。
