State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, Shaanxi, China.
College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Sci Total Environ. 2019 Jun 1;667:271-286. doi: 10.1016/j.scitotenv.2019.02.188. Epub 2019 Feb 13.
General circulation models (GCMs) are useful tools for investigating mechanisms of climate change and projecting future climate change scenarios, but have large uncertainties and biases. Accurate models are of significant importance for agriculture, water resources management, hydrological simulation, and species distribution. In this study, we examined the precipitation and temperature reproducibility of 34 GCMs during the period from 1961 to 1999 over arid and semiarid regions of China. The study area was divided into eight sub-regions; each represented a specific topography. The evaluation was conducted for the whole study area and the sub-regions. Spatial and temporal indices and weighting methodology were used to comprehensively illustrate the models' reproducibility. The results showed that the simulation ability during winter outperformed than that during summer (the weight was 0.192 higher for precipitation and 0.044 higher for temperature during winter than that during summer over the whole study area). Precipitation was more accurately simulated during spring than during autumn as opposed to temperature (the weight was 0.124 higher during spring than during autumn for precipitation and 0.1 higher during autumn than during spring for temperature for the whole region). For precipitation, the simulation ability in the basins was the best, followed by plateaus and mountains; the weights were 0.462, 0.308, and 0.231, respectively. For temperature, the mountains and plateaus had the best and poorest reproducibility, at weights of 0.446 and 0.198, respectively. The top models for precipitation and temperature at different spatial scales (whole study area, three topography types, eight sub-regions) were recommended. The results served as a reference for model selection in future studies regarding impacts of climate change on eco-hydrology.
通用环流模型(GCMs)是研究气候变化机制和预测未来气候变化情景的有用工具,但存在较大的不确定性和偏差。准确的模型对于农业、水资源管理、水文模拟和物种分布都具有重要意义。本研究考察了 34 个 GCM 在 1961 年至 1999 年期间对中国干旱半干旱地区降水和温度的再现能力。研究区分为 8 个子区域;每个区域代表一种特定的地形。对整个研究区和子区域进行了评估。使用时空指数和加权方法全面说明模型的再现能力。结果表明,冬季的模拟能力优于夏季(整个研究区冬季降水的权重比夏季高 0.192,温度高 0.044)。春季降水的模拟能力优于秋季,而温度则相反(整个区域春季降水的权重比秋季高 0.124,温度高 0.1)。对于降水,流域的模拟能力最好,其次是高原和平原;权重分别为 0.462、0.308 和 0.231。对于温度,山区和平原的再现能力最好和最差,权重分别为 0.446 和 0.198。推荐了不同空间尺度(整个研究区、三种地形类型、八个子区域)降水和温度的最佳模型。研究结果为未来气候变化对生态水文学影响的研究中模型选择提供了参考。