MERCURY快速模拟复合气候风险，支持多变量、高分辨率区域预测。
MERCURY: A fast and versatile multi-resolution based global emulator of compound climate hazards
- 基于多分辨率框架与逆提升算法，实现多变量联合模拟。
- 对湿球黑球温度空间相关性模拟误差仅5%，极端值捕捉准确。
- 适合气候风险评估与区域精细化分析，节省存储与计算资源。
高影响气候灾害常由复合气候条件引发，如高温高湿共同导致热应激。为在多种气候情景和大规模集合中探索未来复合灾害变化，气候代理模型可作为地球系统模型的轻量级数据驱动补充。然而，现有模型极少能同时模拟多个气候变量。本文提出多分辨率复合气候风险分析代理模型——MERCURY。MERCURY将多分辨率分析拓展至时空框架，利用数据驱动的图像压缩技术实现内存高效模拟。其包含区域模块，基于概率回归加法模型表征各变量对年均全球气温（GMT）的月度区域响应，并捕捉区域间相关性；随后通过逆提升算子，将区域月度值联合空间下放至网格单元级。我们在湿球黑球温度（WBGT）上验证了其性能，该指标由温度与相对湿度模拟得出。模拟的WBGT空间相关性与地球系统模型一致，95%与97.5%分位数误差分别约为5%与3%，平均偏差仅5%。该模型支持从区域出发高效“放大”至网格级，避免传统方法需模拟完整全球场带来的存储压力。
原文摘要 · Abstract (English)
High-impact climate damages are often driven by compounding climate conditions. For example, elevated heat stress conditions can arise from a combination of high humidity and temperature. To explore future changes in compounding hazards under a range of climate scenarios and with large ensembles, climate emulators can provide light-weight, data-driven complements to Earth System Models. Yet, only a few existing emulators can jointly emulate multiple climate variables. In this study, we present the Multi-resolution EmulatoR for CompoUnd climate Risk analYsis: MERCURY. MERCURY extends multi-resolution analysis to a spatio-temporal framework for versatile emulation of multiple variables. MERCURY leverages data-driven, image compression techniques to generate emulations in a memory-efficient manner. MERCURY consists of a regional component that represents the monthly, regional response of a given variable to yearly Global Mean Temperature (GMT) using a probabilistic regression based additive model, resolving regional cross-correlations. It then adapts a reverse lifting-scheme operator to jointly spatially disaggregate regional, monthly values to grid-cell level. We demonstrate MERCURY's capabilities on representing the humid-heat metric, Wet Bulb Globe Temperature, as derived from temperature and relative humidity emulations. The emulated WBGT spatial correlations correspond well to those of ESMs and the 95% and 97.5% quantiles of WBGT distributions are well captured, with an average of 5% deviation. MERCURY's setup allows for region-specific emulations from which one can efficiently "zoom" into the grid-cell level across multiple variables by means of the reverse lifting-scheme operator. This circumvents the traditional problem of having to emulate complete, global-fields of climate data and resulting storage requirements.
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