LS3MIP 模型中的中国陆表水文评估与不确定性分析

IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS
Xin Ma, Aihui Wang
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引用次数: 0

摘要

陆地表面、积雪和土壤水分模式相互比较项目(LS3MIP)提供了来自当前地球系统模式(ESM)陆地模块的宝贵陆地表面水文产品。陆地模式互比项目(LMIP)中的四个气象强迫数据集(GSWP、WFDEI、CRU-NCEP 和 Princeton)驱动的六个 ESM 的历史水文变量与中国大陆的各种高质量参考数据集进行了广泛的评估。与参考数据集相比,大多数水文变量的多模型集合均值(MMEs)被低估,而其年变化趋势表现出较高的空间一致性,符号一致性超过 56%-85% 的陆地面积。在对模拟结果和参考文献之间的四个统计指标(偏差、相关系数、归一化标准偏差和无偏均方根偏差)进行计算和排序后,发现 CLM5 的性能最好,而 GSWP3 的质量最高。此外,还利用方差分析法(ANOVA)追溯了 1900-2012 年(1948-2012 年径流)中国上空水文变量模拟不确定性的来源(模式、大气强迫数据集及其相互作用)。结果表明,总的不确定性及其构成随时间而变化,近几十年来不确定性显著降低,这反映了强迫数据质量的提高。在 20 世纪早期,由于采用了较少的观测数据集来约束气候变量,因此存在较大的强迫不确定性。对于所有建模水文变量来说,模式的不确定性起着主导作用,这表明 LMIP 产品的质量在很大程度上取决于陆地表面模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluation and Uncertainty Analysis of the Land Surface Hydrology in LS3MIP Models Over China

Evaluation and Uncertainty Analysis of the Land Surface Hydrology in LS3MIP Models Over China

The Land Surface, Snow and Soil moisture Model Intercomparison Project (LS3MIP) offers valuable land surface hydrology products from the land modules of current Earth system models (ESMs). Historical hydrological variables from six ESMs driven by four meteorological forcing data sets (GSWP, WFDEI, CRU-NCEP, and Princeton) in Land Model Intercomparison Project (LMIP) have been extensively evaluated with various high-quality reference data sets over Chinese mainland. Compared with the reference data sets, the multi-model ensemble means (MMEs) of most hydrological variables are underestimated, while their annual trends show high spatial consistency, with sign consistency over 56%–85% of land area. After computing and ranking four statistical metrics (bias, correlation coefficient, normalized standard deviation, and unbiased root-mean-square biases) between simulations and references, it is found that the CLM5 has the best performance, while the GSWP3 exhibits the highest quality. Furthermore, the analysis of variance method (ANOVA) is then used to trace sources (model, atmospheric forcing data sets and their interactions) of the uncertainty of those modeling hydrological variables for 1900–2012 (1948–2012 for runoff) over China. The results indicate that the total uncertainty and its composition vary with time and decrease significantly in recent decades, reflecting the enhanced forcing data quality. Larger forcing uncertainty existed during the early twentieth century because less available observation data sets have been adopted to constrain climate variables. For all modeling hydrological variables, the model uncertainty plays the dominant role, suggesting that the quality of LMIP products largely relies on Land surface models.

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来源期刊
Earth and Space Science
Earth and Space Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
5.50
自引率
3.20%
发文量
285
审稿时长
19 weeks
期刊介绍: Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.
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