兰州大学机构库 >大气科学学院
中国大气再分析资料降水产品在天气和气候中的适用性研究
Alternative TitleResearch on the Applicability of precipitation Reanalysis Data in CRA-interim of Climate and Weather Characters in China
叶梦姝
Thesis Advisor王式功 ; 许小峰
2018-12-01
Degree Grantor兰州大学
Place of Conferral兰州
Degree Name硕士
Degree Discipline气象学
Keyword再分析资料 降水 适用性 误差分析 定量降水评估
Abstract大气再分析资料是大气科学各领域进行科学研究重要的资料基础。大气再分析资料中降水产品,与常规地面站观测资料以及卫星、雷达等融合产品相比,具有空间覆盖全面、时间尺度长、有动力和物理意义等特点,在气候检测和季节预报、气候变率和变化研究、区域气候研究、全球水分循环研究以及平流层研究等领域,发挥着不可替代的作用。因此有必要对不同区域范围、时间尺度、降水量级再分析降水资料的适用性进行较为系统的评估。本研究利用2007-2016年中国气象局全国综合气象信息共享平台(CIMISS)中的“中国地面气象站逐小时观测资料”与中国大气再分析资料(CRA-Interim)、ERA5和JRA-55三种全球大气再分析资料中的逐3小时降水资料进行了对比分析,探讨了再分析数据集对表征中国区域降水的空间分布特征、不同季节降水特征、降水的月-年变化特征、日变化特征的模拟情况,并对比了不同区域、季节和降水量级的定量降水预报评估指标,以2012年北京“721”特大暴雨过程和2014年“华西秋雨”事件为例,分析中国大气再分析资料CRA-Interim对夏季极端降水和持续性锋面降水的模拟误差特征,得到如下初步结论:(1)从误差的整体情况来看,CRA降水资料和其它两套再分析资料的误差水平整体相当,其中,ERA5和JRA-55整体呈现正偏差,CRA整体呈现负偏差,CRA的误差水平大于其它两套再分析资料,ERA5和JRA-55整体误差水平基本一致,JRA-55略小于ERA5。(2)从误差的空间分布来看,再分析资料在平原地区的适用性要优于山区,在平原地区的空报率和漏报率显著低于复杂地形区域;并且在一些观测站点分布较为稀疏的山区,再分析资料有可能反映了一些观测无法反映的细节。再分析资料在较干旱地区优于降水偏多的地区,但也需要考虑降水资料不连续的特征会导致其降水高值区也即是降水方差的高值区, CRA-Interim评分受到地形的影响更大。(3)从误差的季节分布来看,再分析资料对雨带季节移动的模拟在时间上略有提前,对春季降水的模拟以正偏差为主;CRA-Interim对于华南前汛期降水的模拟偏弱,对于长江中下游地区梅雨的模拟较好,对于华西秋雨的模拟偏弱。(4)从误差的日变化情况来看,再分析资料所反映的日降水优于夜间降水;CRA-Interim对我国大部分地区白天降水量的模拟更好,JRA-55对我国西南地区夜雨的特征模拟的更好。(5)从不同量级降水的误差情况来看,三套再分析资料对于弱降水模拟的定量指标得分较为一致,能够较好地反映气候态降水的季节分布特征;但是对强降水的误差波动性较大,反映出再分析资料对于天气尺度降水的模拟误差较大;CRA-Interim在强降水中表现相对优于弱降水,在中雨量级的误差与其它两套再分析资料相比相对较大。(6)从误差的天气学分析结果来看,以2012年北京“7.21”强降水为例,再分析资料对夏季极端降水事件的模拟误差较大,尤其是对于中尺度降水的模拟能力较为有限,降水量级偏小,降水落区偏东,雨区移动偏快;以2014年“华西秋雨”事件为例,再分析资料基本能够再现持续性锋面降水的落区范围和阶段性特征,但整体降水量级偏小,对中等强度降水的模拟能力明显好于强降水,部分地区降水发生时间存在一定滞后。总之,本研究对资料研发方更准确地改进和完善其研发成果、对使用方更准确地把握所用资料,更好地实现对其趋利避害、扬长避短之功效,都具有一定的参考价值。
Other AbstractAtmospheric reanalysis data is a powerful tool for research in atmospheric science. The precipitation products of atmospheric reanalysis data, compared with ground precipitation observation and other data assimilation products which is comprised of satellite and radar observation, is characterized by comprehensive spatial coverage, long time scale, dynamic and physical significance. Thus, it is widely-used and playing an irreplaceable role in climate detection and seasonal forecasting, climate variability and Change research, regional climate research, global water cycle research, and stratospheric research. Therefore, it is necessary to conduct a systematic evaluation of the applicability of reanalysis of precipitation data at different regional scales, time scales, and precipitation levels.This study uses the "China Ground Meteorological Station hourly observation data" in the China Meteorological Administration National Integrated Meteorological Information Sharing Platform (CIMISS) and three Atmospheric Reanalysis Datasets including CRA-Interim, ERA5 and JRA-55 from 2007 to 2016. The 3-hourly precipitation data in global atmospheric reanalysis data were compared and analyzed on spatial distribution characteristics, seasonal distribution, variation characteristics and daily variation characteristics of precipitation. And also, precipitation prediction indicators for seasons, different precipitation quantitative different regions were analyzed and compared. At last, taking the heavy storm happened on 21st July 2012 (“7.21”) in Beijing and Autumn rain of West China in 2014 as examples, analyzed the simulated error characteristics of CRA-Interim on summer meso-scale extreme precipitation and frontal precipitation events. Preliminary conclusions of all above are as follows: (1) Overall, the magnitude of the error of CRA precipitation data and the other two sets of reanalysis data are simlar. Among them, ERA5 and JRA-55 show positive deviation overall, CRA shows negative deviation overall, and CRA error level is greater than The other two sets of reanalysis data, the overall error level of ERA5 and JRA-55 is basically the same, JRA-55 is slightly smaller than ERA5.(2) On the atmospheric reanalysis data error of precipitation spatial distribution, it is found that the applicability of reanalysis data in plain areas is better than that in mountainous areas. The Free Arm Rate (FAR) and Missing Rate (PO) in plain areas is significantly lower than that in complex terrain areas; In sparse mountainous areas, reanalysis of data may reflect details that some observations cannot reflect. The reanalysis data is superior to the precipitation in the arid regions, but it is also necessary to consider the discontinuous characteristics of the precipitation data, which will lead to the high precipitation area, which is the high value area of ​​the precipitation variance. The CRA-Interim score is likely to affected by the topography.(3) On the atmospheric reanalysis data error of precipitation seasonal distribution, it is found that the simulation analysis of the seasonal movement of the rainband is slightly advanced in time, and the simulation of the spring precipitation is dominated by positive deviation; CRA-Interim gives a better simulation of Meiyu in the middle and lower reaches of the Yangtze River while has a negative deviation for the pre-flood precipitation in the southern China and autumn rain in West China.(4) On the error of precipitation daily variation, the day-time precipitation reflected by the reanalysis data is closer to observation value than the night precipitation; CRA-Interim performs better in daytime precipitation in most parts of China, and JRA-55 performs better in the night rain in southwest China.(5) On the error of different magnitude precipitation, the three sets of reanalysis data have consistent scores for the quantitative indicators of weak precipitation simulation, which can better reflect the seasonal distribution characteristics of climatic precipitation; however, the error fluctuation of strong precipitation It is relatively large, reflecting that the reanalysis data has a large simulation error for weather scale precipitation; CRA-Interim performs better in heavy precipitation than in weak precipitation, and its error in moderate rainfall is relatively higher than the other two sets of reanalysis data.(6)From the results of error synoptic analysis, taking the "7.21" heavy rainfall in Beijing in 2012 as an example, the simulation error of the reanalysis data for summer extreme precipitation events is relatively large, especially for the mesoscale precipitation, the simulation ability is limited, the precipitation level is smaller than observation, the precipitation area is eastward, and the precipitation area moves faster. Taking the autumn rain event in West China in 2014 as an example, the reanalysis data can basically reproduce the falling area and periodic characteristics of persistent frontal precipitation, but the overall precipitation level is small, and the moderate intensity precipitation simulation ability is obviously better than the heavy precipitation, and the occurrence time of precipitation in some areas has a certain lag.
Pages96
URL查看原文
Language中文
Document Type学位论文
Identifierhttp://ir.lzu.edu.cn/handle/262010/338264
Collection大气科学学院
Affiliation大气科学学院
First Author AffilicationCollege of Atmospheric Sciences
Recommended Citation
GB/T 7714
叶梦姝. 中国大气再分析资料降水产品在天气和气候中的适用性研究[D]. 兰州. 兰州大学,2018.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Altmetrics Score
Google Scholar
Similar articles in Google Scholar
[叶梦姝]'s Articles
Baidu academic
Similar articles in Baidu academic
[叶梦姝]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[叶梦姝]'s Articles
Terms of Use
No data!
Social Bookmark/Share
No comment.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.