中国西北地区未来潜在蒸散发集合预估及不确定性归因. (Chinese)

Potential Evapotranspiration (PET) has been one of the most important factors on terrestrial water availability. It is a high demand to predict the PET changes for the robust responsive strategies to the future climate scenarios in northwest China. However, the projected outcomes cannot fully match the decision-making on the planning, due to the uncertainties originating from different sources. Therefore, it is crucial to develop a large-scale ensemble of PET projections, considering the multiple sources of uncertainty to quantify the contribution of each uncertainty source. In this research, a monthly regression correction was carried out on the simplified PET models (temperature- and machine learning-based PET models) using historical meteorological data. A three-dimensional evaluation framework was then constructed to predict the PET changes using the meteorological data of 6 Global Climate Models (GCMs) in the sixth Phase of the Coupled Model Intercomparison Project (CMIP6), 3 future scenarios (Shared Socioeconomic Pathways, SSPs), and 6 PET models (2 combined and 4 simplified PET models). A large-scale ensemble projection was obtained, including 108 projections of annual and seasonal PET changes (△PET). The △PETs in the mid-term future and long-term future were obtained to subtract the average PET in the historical period from 2041 to 2070, and from 2071 to 2100, respectively. The different forecasts of climate scenarios (SSPs), PET models (PETMs), and GCMs were quantified to determine the multiple sources of uncertainty on the projection. Three-factor Analysis of Variance (ANOVA) was selected to quantify the contribution rate of each uncertainty source and the interactions to the total uncertainty. The result showed that: 1) The correction coefficients in the PET models after the monthly regression were represented the influence of meteorological elements (except for the temperature), indicating an improved simulation accuracy of the simplified PET models with the reduced systematic error. It infers that the regional modified and combined PET models were more reasonable than ever to evaluate the PET changes. 2) In the mid-term future (2041-2070) and the long-term future (2071-2100), the ensemble projected average values of the annual △PET were 67.8 and 95.3 mm, respectively, where the variances of projection were 17.6 and 21.4 mm, respectively. The SSP5-8.5 scenario, random forest, and ACCESS-ESM1-5 model were tended to produce the larger values in the ensemble projection, while it was smaller using SSP1-2.6 scenario, PM[CO 2 ] and MIROC6 model. In addition, there was the increased variation in the forecast outcomes caused by the uncertainties from the SSP and PETM over time. 3) The importance of various sources of uncertainty in the PET ensemble projection was ranked in the descending order of PETM, SSP, and GCM in the mid-term future. The SSP was the most important source of uncertainty with a contribution rate of 65.3% in the long-term future. Meanwhile, the contribution rates of PETM and GCM were reduced to 19.1% and 7.7%, respectively. In terms of seasonal distribution, the PETM and SSP presented a higher contribution rate to the total uncertainty in the warm seasons (summer, autumn) and cold seasons (winter, spring), respectively. Therefore, the large-scale ensemble projection with enough samples and the statistical characteristics can be widely expected to serve a more comprehensive evaluation than before, particularly for climate change. The findings can provide a potential direction to reduce the uncertainty of future PET assessments. [ABSTRACT FROM AUTHOR]

预估西北地区未来潜在蒸散发（Potential Evapotranspiration，PET）变化对该区制定气候适应性远景规划至关重 要，然而PET 预估中不可避免地存在源于气候情景、气候模式和PET 模型的不确定性。该研究以3 个气候情景（Shared Socioeconomic Pathway，SSP）、6 个性能良好的潜在蒸散发模型（Potential Evapotranspiration Model，PETM）以及第六 次国际耦合模式比较计划（Coupled Model Intercomparison Project Phase 6，CMIP6）的6 个全球气候模式（Global Climate Model，GCM）分别表征情景、模型和模式的不确定性，构建了基于多模式、多情景以及多模型的三维PET 集合预估框 架，得到108 套预估结果组成的大规模数据集合。基于集合预估结果，分析了相对于历史时期的PET 变化量的整体特征 及多源不确定性导致的预估结果差异，并基于三因素方差分析法量化了各不确定性来源及其非线性交互作用对总不确定 性的贡献率。结果表明：未来中期（2041—2070 年）和远期（2071—2100 年）年均△PET 预估结果集合均值分别为67.8 和95.3 mm。集合预估中，基于SSP1-2.6 情景（可持续发展情景）、PM[CO 2 ]模型及MIROC6 全球气候模式预估的PET 变化量较低，且情景和模型不确定性造成的结果差异均随时间推移而增大。各不确定性来源在中期PET 变化量预估中的 相对重要性由大到小依次为PETM、SSP 和GCM；而在远期，SSP 贡献率最高，达65.3%。在季节分布上，PETM 和SSP 分别在暖季（夏、秋）和冷季（冬、春）的贡献率较高。大规模PET 变化量集合预估结果及其统计特征能够为西北地区 应对气候变化的高效行动提供更科学全面的理论依据；不确定性来源相对贡献的分析结果可为进一步降低未来PET 预估 的不确定性提供研究方向。 [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)