设为首页
加入收藏
Threshold Values on Extreme High Temperature Events in China
-
摘要: 利用我国1951—2008年逐日最高气温资料集，进行缺测资料的恢复整理，得到较完整的1961—2008年224站逐日最高气温资料集。在此基础上，采用两种基于正态分布的传统阈值计算的方法 (方法1，方法2) 和该文提出的基于实际样本频率分布的阈值计算方法 (方法3)，对我国高温阈值的确定进行比较研究。结果表明：该文提出根据最高气温的实际样本频率分布作为实际概率分布的近似，较传统求极端气候事件阈值方法效果更好，能够比较接近日常使用极端气候事件阈值，亦有较好的稳定性。另外，根据计算结果，除西南地区、青海、东北地区大部和内蒙古外，我国大部分地区最高气温极端气候事件的阈值均超过35℃，即在我国日常人们使用的35℃高温阈值作为夏季高温极端事件标准是合理的。Abstract: The threshold values are very important to define the indices of extreme climate events. Usually, the 90 percentile threshold value is used as the threshold values of extreme high temperature events, while the specific methods of categorization and calculation lead to different threshold values. In order to find the most suitable method, the quality controlled and homogenized daily maximum temperature data in China for the period of 1951—2008 are checked, and some missing data are reconstructed. Analysis is conducted using a new data for 1961—2008 in 224 selected stations. The preliminary analysis shows that the daily data series of most stations are not fit for normal distribution as generally believed. Based on the analysis above, the comparison for the threshold values falling into the percentiles of the extreme events of maximum temperature is accomplished using three different methods (including two traditional methods of calculating threshold values based on the assumed normal distribution and a new method by which the threshold values are calculated based on the sample probability distribution).The results show that the evaluation of the threshold values on the method using the real sample frequency distribution to simulate the probability distribution (the new method) has got the best results than using the other traditional threshold values calculating methods. Based on the comparisons, the threshold values of extreme events of maximum temperature in China have been developed with the 30-year sample climate phase. The following inspection shows the threshold values can reflect the real threshold values on the maximum temperature in daily use, and they are more stable and representative. In addition, the distribution charts of the threshold values developed by the different methods are drawn, and it's found that except for in Southwest and Northeast China, Qinghai, Inner Mongolia, the threshold values of extreme high temperature events for most part of China are all above 35 ℃, which proves that it is reasonable of using the threshold 35 ℃ as the standard of high temperature disasters.
-
图 1 我国最高气温站点的地理分布
Fig. 1 The geographical distribution for maximum temperature stations in China
图 2 方法3与方法1的阈值平均值差异检验统计量t值的逐年变化
Fig. 2 Annual differences of statistical values t calculated by Method 3 and Method 1
图 3 1997年方法3与方法1计算的阈值差值的分布 (单位：℃)
Fig. 3 The geographical distribution for differences of thresholds calculated by Method 3 and Method 1(unit: ℃)
图 4 我国夏季最高气温极端气候事件的阈值分布 (单位：℃)
Fig. 4 The distribution for threshold values of climate extremes in summer (unit: ℃)
表 1 我国最高气温资料集中资料缺测日数与站数
Table 1 The number of stations and data missing days in daily maximum temperature dataset
日数范围/d 站数 比例/% 0 117 47 1~3 82 33 4~6 20 8 7~10 5 2 11~365 14 5 ＞366 12 5 
下载: 导出CSV
表 2 恢复最高气温检验的均方根误差比较 (单位：℃)
Table 2 Mean root squire error for interpolated maximum temperature data (unit: ℃)
月份 平均值 均方根误差 1 1.10 0.37 2 1.10 0.49 3 1.04 0.26 4 1.46 0.42 5 1.63 0.46 6 2.23 0.27 7 2.59 0.51 8 2.56 0.83 9 2.16 0.62 10 1.48 0.47 11 1.26 0.56 12 1.14 0.32
下载: 导出CSV
表 3 1997年夏季气温序列不同方法求取高温阈值的比较 (单位：℃)
Table 3 The threshold values by 3 methods for summer temperature in 1997 (unit: ℃)
统计量 方法1 方法2 方法3 最大值 39.3 39.3 40.5 最小值 21.1 21.0 22.1 平均值 33.3 33.3 34.7
下载: 导出CSV
表 4 我国夏季气温气候极端事件阈值的比较
Table 4 The threshold values of climate extremes by 3 methods for summer temperature
项目 方法1 方法2 方法3 最大值/℃ 39.7 39.7 41.0 最小值/℃ 20.8 20.8 22.1 平均值/℃ 34.0 33.9 35.3 大于35℃站点所占比例/% 40 38 57
下载: 导出CSV
-
[1] Karl T R, Knight R W.Secular trends of precipitation amount, frequency, and intensity in the USA. Bull Amer Meteor Soc, 1998, 79:231-241. doi: 10.1175/1520-0477(1998)079<0231:STOPAF>2.0.CO;2 [2] Stone D A, Weaver A J, Zwiers F W. Trends in Canadian precipitation intensity. Atoms Ocean, 1999, 2:321-347. doi: 10.1080/07055900.2000.9649651 [3] Yamamoto R, Sakurai Y. Long-term intensification of extremely heavy rainfall intensity in recent 100 years. World Resource Res, 1999, 11:271-281. https://www.researchgate.net/publication/283632440_Long-term_intensification_of_extremely_heavy_rainfall_intensity_in_recent_100_years [4] 任福民, 翟盘茂.1951~1990年中国极端气温变化分析.大气科学, 1998, 22(2):217-227. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXK802.009.htm [5] 翟盘茂, 潘晓华.中国北方近50年温度和降水极端事件变化.地理学报, 2003, 58(增刊):1-10. http://www.cnki.com.cn/Article/CJFDTOTAL-DLXB2003S1000.htm [6] 严中伟, 杨赤.近几十年中国极端气候变化格局.气候与环境研究, 2000, 5(3):267-272. http://www.cnki.com.cn/Article/CJFDTOTAL-QHYH200003004.htm [7] 张宁, 孙照渤, 曾刚. 1955—2005年中国极端气温的变化.南京气象学院学报, 2008, 31(1): 123-128. http://www.cnki.com.cn/Article/CJFDTOTAL-NJQX200801017.htm [8] 刘学华, 季致建, 吴洪宝, 等.中国近40年极端气温和降水的分布特征及年代际差异.热带气象学报, 2006, 22(6):618-624. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX200606015.htm [9] 杨萍, 刘伟东, 王启光, 等.近40年我国极端温度变化趋势和季节特征.应用气象学报, 2008, 21(1):29-36. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20100104&flag=1 [10] 谢庄, 苏德斌, 虞海燕, 等.北京地区热度日和冷度日的变化特征.应用气象学报, 2007, 18(2):232-236. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070239&flag=1 [11] 王鹏祥, 杨金虎.中国西北近45年来极端高温事件及其对区域性增暖的响应.中国沙漠, 2007, 27(7):649-655. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGSS200704020.htm [12] 张天宇, 程炳岩, 刘晓冉.重庆极端高温的变化特征及其对区域性增暖的响应.气象, 2008, 34(2):69-76. doi: 10.7519/j.issn.1000-0526.2008.02.010 [13] 黄丹青, 钱永甫.我国极端温度事件的定义和趋势分析.中山大学学报 (自然科学版), 2008, 47(3):112-116. http://www.cnki.com.cn/Article/CJFDTOTAL-ZSDZ200803023.htm [14] 张勇, 曹丽娟, 许吟隆, 等.未来我国极端温度事件变化情景分析.应用气象学报, 2008, 19(6):655-660. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20080603&flag=1 [15] Zhang X, Gabriele H, Francis W Z, et al. Avoiding inhomogeneity in percentile-based indices of temperature extremes. J Climate, 2005, 18: 1641-1651. doi: 10.1175/JCLI3366.1 [16] Alexander L V, Zhang X, Peterson T C, et al. Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res, 2006, 111: D05109, doi: 10.1029/2005JD006290. [17] Young K C. A three-way model for interpolating for monthly precipitation values. Mon Wea Rev, 1992, 120: 2561-2569. doi: 10.1175/1520-0493(1992)120<2561:ATWMFI>2.0.CO;2 [18] 龚道溢, 王绍武.恢复近百年北半球500hPa高度场的试验.热带气象学报, 2000, 16(2):148-154. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX200002006.htm [19] 李庆祥, 黄嘉佑, 鞠晓慧.上海地区最高气温资料的恢复试验.热带气象学报, 2008, 24(4):349-353. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX200804007.htm [20] 李庆祥, 江志红, 黄群, 等.长三角地区降水序列的均一性检验与订正试验.应用气象学报, 2008, 19(2):219-226. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20080238&flag=1 [21] Li Q, Zhang H, Chen J, et al.A mainland China homogenized historical temperature dataset of 1951—2004. Bull Amer Meteor Soc, 2009, 90, 1062-1065, doi: 10.1175/2009BAMS2736. [22] 杨金虎, 江志红, 王鹏祥, 等.西北地区东部夏季极端降水量非均匀性特征.应用气象学报, 2008, 19(1):11-115. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20080118&flag=1 [23] 李红梅, 周天军, 宇如聪.近四十年我国东部盛夏日降水特性变化分析.大气科学, 2008, 32(2): 359-370. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXK200802013.htm [24] 黄嘉佑.气象统计分析与预报方法.北京:气象出版社, 2007. [25] 李心愉.应用经济统计学.北京:北京大学出版社, 1999. -
计量
- 摘要浏览量: 6154
- HTML全文浏览量: 1026
- PDF下载量: 1990
- 被引次数: 0
