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加拿大经偏差校正的高分辨率温度和降水预测。

Bias-corrected high-resolution temperature and precipitation projections for Canada.

作者信息

Abdelmoaty Hebatallah M, Rajulapati Chandra Rupa, Nerantzaki Sofia D, Papalexiou Simon Michael

机构信息

Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada.

Irrigation and Hydraulics Department, Faculty of Engineering, Cairo University, Giza, Egypt.

出版信息

Sci Data. 2025 Feb 1;12(1):191. doi: 10.1038/s41597-025-04396-z.

Abstract

High-resolution precipitation and temperature projections are indispensable for informed decision-making, risk assessment, and planning. Here, we have developed an extensive database (SPQM-CMIP6-CAN) of high-resolution (0.1°) precipitation and temperature projections extending till 2100 at a daily scale for Canada. We employed a novel Semi-Parametric Quantile Mapping (SPQM) methodology to bias-correct the Coupled Model Intercomparison Project, Phase-6 (CMIP6) projections for four Shared Socio-economic Pathways. SPQM is simple, yet robust, in reproducing the observed marginal properties, trends, and variability according to future scenarios, while maintaining a smooth transition from observations to projected simulations. The SPQM-CMIP6-CAN database encompasses 693 simulations derived from 34 diverse climate models for precipitation. Similarly, for temperature projections, our database comprises 581 simulations from 27 climate models. These projections are valuable for hydrological, environmental, and ecological studies, offering a comprehensive resource for analyses within these domains. Furthermore, these projections serve as a vital tool for the quantification of uncertainties arising from climate models, their variant configurations, and future scenarios.

摘要

高分辨率降水和温度预测对于明智的决策、风险评估和规划而言不可或缺。在此,我们开发了一个广泛的数据库(SPQM-CMIP6-CAN),其中包含加拿大直至2100年的高分辨率(0.1°)每日尺度降水和温度预测。我们采用了一种新颖的半参数分位数映射(SPQM)方法,对四个共享社会经济路径的耦合模型比较计划第六阶段(CMIP6)预测进行偏差校正。SPQM简单却稳健,能够根据未来情景再现观测到的边际特征、趋势和变异性,同时保持从观测到预测模拟的平稳过渡。SPQM-CMIP6-CAN数据库包含来自34个不同气候模型的693个降水模拟。同样,对于温度预测,我们的数据库包含来自27个气候模型的581个模拟。这些预测对于水文、环境和生态研究具有重要价值,为这些领域的分析提供了全面的资源。此外,这些预测是量化气候模型、其不同配置以及未来情景所产生不确定性的重要工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88df/11787352/8ea2f203d420/41597_2025_4396_Fig1_HTML.jpg

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