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Probabilistic projections of climate change over China under the SRES A1B scenario using 28 AOGCMs.

机译:SRES A1B情景下使用28个AOGCM对中国气候变化的概率预测。

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Probabilistic projection of climate change consists of formulating the climate change information in a probabilistic manner at either global or regional scale. This can produce useful results for studies of the impact of climate change impact and change mitigation. In the present study, a simple yet effective approach is proposed with the purpose of producing probabilistic results of climate change over China for the middle and end of the twenty-first century under the Special Report on Emissions Scenarios A1B (SRES A1B) emission scenario. Data from 28 coupled atmosphere-ocean general circulation models (AOGCMs) are used. The methodology consists of ranking the 28 models, based on their ability to simulate climate over China in terms of two model evaluation metrics. Different weights were then given to the models according to their performances in present-day climate. Results of the evaluation for the current climate show that five models that have relatively higher resolutions - namely, the Istituto Nazionale di Geofisica e Vulcanologia ECHAM4 (INGV ECHAM4), the third climate configuration of the Met Office Unified Model (UKMO HadCM3), the CSIRO Mark version 3.5 (Mk3.5), the NCAR Community Climate System Model, version 3 (CCSM3), and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2 (hires)] - perform better than others over China. Their corresponding weights (normalized to 1) are 0.289, 0.096, 0.058, 0.048, and 0.044, respectively. Under the A1B scenario, surface air temperature is projected to increase significantly for both the middle and end of the twenty-first century, with larger magnitude over the north and in winter. There are also significant increases in rainfall in the twenty-first century under the A1B scenario, especially for the period 2070-99. As far as the interannual variability is concerned, the most striking feature is that there are high probabilities for the future intensification of interannual variability of precipitation over most of China in both winter and summer. For instance, over the Yangtze-Huai River basin (28 degrees -35 degrees N, 105 degrees -120 degrees E), there is a 60% probability of increased interannual standard deviation of precipitation by 20% in summer, which is much higher than that of the mean precipitation. In general there are small differences between weighted and unweighted projections, but the uncertainties in the projected changes are reduced to some extent after weighting.
机译:气候变化的概率预测包括以概率的方式在全球或区域范围内制定气候变化信息。这可以为研究气候变化影响和减缓变化的影响提供有用的结果。在本研究中,提出了一种简单而有效的方法,目的是在《排放情景特别报告》 A1B(SRES A1B)排放情景下,得出中国在二十一世纪中叶末期气候变化的概率结果。使用了来自28个大气海洋耦合总循环模型(AOGCM)的数据。该方法包括根据两个模型评估指标对28个模型进行模拟的能力,对它们进行排名。然后根据模型在当前气候下的性能为模型赋予不同的权重。对当前气候的评估结果表明,有五个具有相对较高分辨率的模型-地理地理国家信息模型ECHAM4(INGV ECHAM4),气象局统一模型(UKMO HadCM3)的第三种气候配置,CSIRO Mark版本3.5(Mk3.5),NCAR社区气候系统模型版本3(CCSM3)和气候问题跨学科研究模型3.2,高分辨率版本[MIROC3.2(雇员)]-在中国。它们的相应权重(标准化为1)分别为0.289、0.096、0.058、0.048和0.044。在A1B情景下,预计在21世纪中叶和冬季末,地表空气温度将显着升高,而在北部和冬季,地表气温将升高。在A1B情景下,尤其是在2070-99年期间,二十一世纪的降雨量也显着增加。就年际变化而言,最显着的特征是冬季和夏季中国大部分地区未来降水年际变化加剧的可能性很高。例如,在长江淮流域(北纬28度-35度,东经105度-120度)上,夏季降水的年际标准偏差增加60%的可能性为20%,这远高于平均降水量一般而言,加权和未加权预测之间的差异很小,但加权后预测变化的不确定性在一定程度上降低了。

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