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Evaluating CEOP model performance in semi-arid region of China

机译:评估中国半干旱地区CEOP模型的绩效

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This study systematically evaluates simulations of near-surface temperature and precipitation using the station observations collected in the semi-arid region of China during the Coordinated Enhanced Observing Period (CEOP) from October 2002 to December 2004 (EOP3 and EOP4). The outputs being evaluated are from eight general circulation models (GCMs) archived by the Coordinated Energy and Water Cycle Observations Project (CEOP), as well as a multi-model ensemble based on these eight models. We find that the multi-model ensemble has a better performance than most of the individual models. Our results show that all individual models and the Model Analysis Comparison (MAC) ensemble mean perform much better when simulating regionally averaged temperature than precipitation. For most models, a systematically low bias is identified in the regionally averaged simulated temperatures, while a high bias exists in the simulated precipitation except in summer. For the simulated temperatures, the lowest and largest rRMSE are found in JMA and BMRC, respectively. Furthermore, temperature is always overestimated when it is between ???18 and ???10?°C, while the temperature is underestimated when it is greater than 6?°C; the best performance lies between ???10 and 2?°C for all the models except BMRC. For the simulated precipitation, excessive rainfall is reproduced at all intervals except in ECPC-SFM, and the largest deviation is identified at the interval of 2–5?mm with a bias of 18.3%. With respect to sub-regions, the simulated temperatures are better in eastern China, but the simulated precipitation is better in the transition zone from the semi-arid region to the arid region. However, the simulation bias increases west of 100°E, which may be associated with the complex and steep topography there. We want to stress that the MAC ensemble mean is superior to any individual models.
机译:这项研究使用协调增强观测期(CEOP)从2002年10月至2004年12月(EOP3和EOP4)在中国半干旱地区收集的台站观测资料,系统地评估了近地表温度和降水的模拟。正在评估的输出来自协调能源和水循环观测项目(CEOP)存档的八个通用循环模型(GCM),以及基于这八个模型的多模型集合。我们发现,多模型集合比大多数单个模型具有更好的性能。我们的结果表明,在模拟区域平均温度时,所有单个模型和模型分析比较(MAC)集合均值的表现要好于降水。对于大多数模型,在区域平均模拟温度中识别出系统地较低的偏差,而除夏季外,模拟降水中存在较高的偏差。对于模拟温度,分别在JMA和BMRC中找到最低和最大rRMSE。此外,当温度在18和10℃之间时,温度总是被高估,而当温度大于6℃时,温度被低估了。对于除BMRC以外的所有型号,最佳性能均在10°C至2°C之间。对于模拟降水,除ECPC-SFM外,所有间隔都会产生过多的降水,并且在2–5?mm的间隔内发现最大偏差,偏差为18.3%。就次区域而言,中国东部的模拟温度较好,但从半干旱地区到干旱地区的过渡带模拟降水较好。但是,模拟偏差在100°E以西增加,这可能与那里复杂而陡峭的地形有关。我们要强调的是,MAC集成均值优于任何单个模型。

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