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Evaluation of GCMs historical simulations of monthly and seasonal climatology over Bolivia

机译:GCM对玻利维亚月度和季节气候的历史模拟的评估

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摘要

Bolivia is a low-latitude, developing country at grave risk to the deleterious effects of human-induced climate changes. Due to the complexity of the topography in Bolivia, it is difficult to capture future impacts of the climate change on the regional scale with the coarse resolution of current GCMs. A robust strategy has been developed to dynamically downscale the GCM outputs to a more appropriate temporal and spatial resolution for impact studies. Prior to downscaling, however, evaluation of the GCMs used to provide large-scale forcing is a necessary step to ensure physically meaningful results from regional climate models. This study represents the first part of a broader project on evaluating climate change impacts over Bolivia. We examined precipitation, temperature, wind patterns and moisture transport to evaluate the performance of eight CMIP5 GCMs in simulating the continental and regional climate patterns. Phenomena including the seasonal and monthly positions of the intertropical convergence zone, South Atlantic convergence zone, Bolivian high, Chaco low and South American low-level jet, were analyzed. Our results confirm that, in general, all the GCMs do reasonably well in simulating the basic patterns of the variables with some discrepancies in magnitude across models, especially in the regional scale. Some models outperform the others for the variables and the region of our interest. Finally, the results of this research will help improve quantifying the uncertainty range of further regional downscaling outputs.
机译:玻利维亚是一个低纬度的发展中国家,面临着人类造成的气候变化的有害影响的严重风险。由于玻利维亚地形的复杂性,很难用当前GCM的粗略分辨率来捕捉气候变化对区域规模的未来影响。已经开发出了一种强大的策略,可以动态地将GCM输出缩减为更合适的时间和空间分辨率,以进行影响研究。但是,在缩减规模之前,对用于提供大规模强迫的GCM进行评估是确保区域气候模型在物理上有意义的结果的必要步骤。这项研究是评估气候变化对玻利维亚影响的更广泛项目的第一部分。我们检查了降水,温度,风模式和水分传输,以评估八种CMIP5 GCM在模拟大陆和区域气候模式中的性能。分析了包括热带辐合带,南大西洋辐合带,玻利维亚高,查科低和南美低空急流的季节和月度位置的现象。我们的结果证实,总体而言,所有GCM在模拟变量的基本模式方面表现都相当不错,模型之间在幅度上存在一些差异,尤其是在区域范围内。在变量和我们感兴趣的区域方面,某些模型优于其他模型。最后,这项研究的结果将有助于改善量化进一步区域缩减规模产出的不确定性范围。

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  • 来源
    《Climate dynamics》 |2018年第2期|733-754|共22页
  • 作者单位

    Univ Nebraska Lincoln, Dept Earth & Atmospher Sci, Lincoln, NE 68588 USA;

    Univ Nebraska Lincoln, Dept Earth & Atmospher Sci, Lincoln, NE 68588 USA;

    Univ Nebraska Lincoln, Dept Earth & Atmospher Sci, Lincoln, NE 68588 USA;

    Iowa State Univ, Dept Geol & Atmospher Sci, Ames, IA USA;

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