| 分位数映射法在RegCM4中国气温模拟订正中的应用 |
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| 引用本文： | 韩振宇,童尧,高学杰,徐影.分位数映射法在RegCM4中国气温模拟订正中的应用[J].气候变化研究进展,2018,14(4):331-340. |
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| 作者姓名： | 韩振宇 童尧 高学杰 徐影 |
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| 作者单位： | 1.中国气象局国家气候中心,北京 1000812 盖州市气象局,盖州 1152003 中国科学院大气物理研究所气候变化研究中心,北京 1000294 中国科学院大学,北京 100049 |
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| 基金项目： | 国家重点研发计划(2016YFC0402405);国家重点研发计划(2018YFA0606301);自然科学基金项目(41405101) |
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| 摘 要： | 将一种分位数映射法RQUANT,应用到一个区域气候模式（RegCM4）所模拟中国气温的误差订正中。从气候平均态、年际变率、极端气候及农业气候等多方面,评估了该方法对日平均气温、日最高气温和日最低气温模拟的订正效果。结果表明,该订正方法对模式模拟的日平均、日最高和最低气温气候平均态的订正效果都非常明显,中国大部分地区的订正结果与观测的偏差在±0.5℃之间。在降低极端气温指数和农业气候相关指数的模拟误差方面也有显著的效果,但对气温年际变率的订正效果有限。结合以往对降水订正的评估分析,该方法对模式模拟结果有较好的订正效果,可以应用于区域气候模式的气候变化模拟预估中,为气候变化及相关影响评估研究提供更适用和可靠的数据。
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| 关 键 词： | 分位数映射 误差订正 区域气候模式 气温 |
| 收稿时间： | 2017-08-02 |
| 修稿时间： | 2017-09-18 |
Correction based on quantile mapping for temperature simulated by the RegCM4 |
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| Zhen-Yu HAN,Yao TONG,Xue-Jie GAO,Ying XU.Correction based on quantile mapping for temperature simulated by the RegCM4[J].Advances in Climate Change,2018,14(4):331-340. |
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| Authors: | Zhen-Yu HAN Yao TONG Xue-Jie GAO Ying XU |
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| Institution: | 1.National Climate Center, China Meteorological Administration, Beijing 100081, China2 Gaizhou Meteorological Service, Gaizhou 115200, China3 Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China4 University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | A quantile mapping method called RQUANT was applied to the bias correction on the temperature (including daily mean temperature, daily maximum temperature, and daily minimum temperature) simulation of a regional climate model (RegCM4). Assessment on the correction effect was carried out, focusing on the simulation of climatological mean, interannual variation, extreme temperature, and agro-climatic conditions. Results show that this correction method is capable of improving the simulation of mean state of temperature. The biases of the correction results on mean temperature are within ±0.5℃. It can also significantly improve the simulation of both extreme temperature and agro-climatic conditions. However, it has little correction effect on interannual variation. Considering the good performance of this method on correcting precipitation simulation in previous study, it implies that the RQUANT method can be used on climate change projection simulations, and these bias corrected simulations would be more useful and reliable for climate change and climate change impact studies. |
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| Keywords: | Quantile mapping Bias correction Regional climate model Temperature |
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