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高分辨率气候模型改进了对恒河-布拉马普特拉河-梅格纳河流域季风降雨变化的模拟。

High-resolution climate models improve simulation of monsoon rainfall changes in the Ganga-Brahmaputra-Meghna basin.

作者信息

Ali Haider, Fowler Hayley J, Turner Andrew G

机构信息

School of Engineering, Newcastle University, Newcastle Upon Tyne, UK.

Tyndall Centre for Climate Change Research, Newcastle University, Newcastle Upon Tyne, UK.

出版信息

Clim Dyn. 2025;63(6):246. doi: 10.1007/s00382-025-07716-6. Epub 2025 Jun 6.

Abstract

UNLABELLED

This study investigates the impact of model resolution on simulating South Asian monsoon rainfall, focusing on the Ganges-Brahmaputra-Meghna (GBM) basin. By comparing high- and low-resolution versions of four CMIP6 HighResMIP model families against reference datasets (MSWEP and ERA5), we emphasize the advantages of high-resolution models in accurately simulating key monsoon characteristics, including annual rainfall, timing, intensity, and duration. Our results show that the high-resolution models align more closely with observed data, outperforming their low-resolution counterparts. Between 1979 and 2014, the high-resolution model ensemble (HR-models) captures key shifts in monsoon timing, such as delayed onset and withdrawal, leading to a slight increase in monsoon duration. In contrast, the low-resolution ensemble (LR-models) showed more pronounced delays in onset. The observational datasets, MSWEP and ERA5, indicate earlier (7 ± 3 days) and later (3 ± 1.2 days) onsets, respectively, with both showing delays in withdrawal, indicating extended monsoon duration. Notably, the increase in monsoon duration is more pronounced in MSWEP observations than in the model simulations, particularly for LR-models. Regarding rainfall trends, the HR-models more accurately reflect observed changes in both total rainfall and extreme rainfall from 1979-2014 compared to LR-models. Future projections (2015-2050) indicate further delays in monsoon onset, with HR-models projecting larger increases in total rainfall and extreme events (up to 4.5%/decade for the 95th percentile of rainfall) compared to LR-models, which show smaller increases and higher variability in total and extreme rainfall. These findings highlight the critical role of model resolution in improving the accuracy of monsoon simulations, with HR models offering more reliable simulations of historical monsoon behaviour and therefore likely more robust projections of future monsoon behavior. These are essential for informed water management and agricultural decision-making over the complex topography of the GBM basin.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00382-025-07716-6.

摘要

未标注

本研究调查了模式分辨率对模拟南亚季风降雨的影响,重点关注恒河-布拉马普特拉河-梅格纳河(GBM)流域。通过将四个CMIP6高分辨率模式家族的高分辨率和低分辨率版本与参考数据集(MSWEP和ERA5)进行比较,我们强调了高分辨率模式在准确模拟关键季风特征(包括年降雨量、时间、强度和持续时间)方面的优势。我们的结果表明,高分辨率模式与观测数据的一致性更高,优于其低分辨率对应模式。在1979年至2014年期间,高分辨率模式集合(HR模式)捕捉到了季风时间的关键变化,如 onset延迟和撤退延迟,导致季风持续时间略有增加。相比之下,低分辨率集合(LR模式)在onset上表现出更明显的延迟。观测数据集MSWEP和ERA5分别显示onset更早(7±3天)和更晚(3±1.2天),两者都显示撤退延迟,表明季风持续时间延长。值得注意的是,季风持续时间的增加在MSWEP观测中比在模式模拟中更为明显,特别是对于LR模式。关于降雨趋势,与LR模式相比,HR模式更准确地反映了1979 - 2014年期间总降雨量和极端降雨量的观测变化。未来预测(2015 - 2050年)表明季风onset将进一步延迟,与LR模式相比,HR模式预测总降雨量和极端事件的增加幅度更大(降雨量第95百分位数高达4.5%/十年),而LR模式在总降雨量和极端降雨量方面的增加幅度较小且变率更高。这些发现突出了模式分辨率在提高季风模拟准确性方面的关键作用,HR模式对历史季风行为提供了更可靠的模拟,因此可能对未来季风行为做出更稳健的预测。这些对于在GBM流域复杂地形上进行明智的水资源管理和农业决策至关重要。

补充信息

在线版本包含可在10.1007/s00382-025-07716-6获取的补充材料。 (注:原文中onset未明确中文释义,根据语境推测可能是季风开始之类的意思,这里保留英文未翻译)

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fa7/12144052/b1daf7844606/382_2025_7716_Fig1_HTML.jpg

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