A gridded daily observation dataset over China region and comparison with the other datasets
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摘要: 为高分辨率气候模式检验等的需要,基于2400余个中国地面气象台站的观测资料,通过插值建立了一套0.25°×0.25°经纬度分辨率的格点化数据集(CN05.1).CN05.1包括日平均和最高、最低气温,以及降水4个变量.插值通过常用的"距平逼近"方法实现,首先将计算得到的气候平均场使用薄板样条方法进行插值,随后使用"角距权重法"对距平场进行插值,然后将两者叠加,得到最终的数据集.将CN05.1与CN05、EA05和APHRO三种日气温和降水资料(四种资料的分析时段统一为1961—2005年)进行对比,分析了它们对气候平均态和极端事件描述上的不同,结果表明几者总体来说在中国东部观测台站密集的地方差别较小,而在台站稀疏的西部差别较大,相差最大的是青藏高原北部至昆仑山西段等地形起伏较大而很少或没有观测台站的地方,反映了格点化数据在这些地区的不确定性,在使用中应予以注意.Abstract: A new gridded daily dataset with the resolution of 0.25° latitude by 0.25° longitude, CN05.1, is constructed for the purpose of high resolution climate model validation over China region. The dataset is based on the interpolation from over 2400 observing stations in China, includes 4 variables: daily mean, minimum and maximum temperature, daily precipitation. The "anomaly approach" is applied in this interpolation. The climatology is first interpolated by thin-plate smoothing splines and then a gridded daily anomaly derived from angular distance weighting method is added to climatology to obtain the final dataset. Intercomparison of the dataset with other three daily datasets, CN05 for temperature, and EA05 and APHRO for precipitation is conducted. The analysis period is from 1961 to 2005. For multi-annual mean temperature variables, results show small differences over eastern China with dense observation stations, but larger differences (warmer) over western China with less stations between CN05.1 and CN05. The temperature extremes are measured by TX3D (mean of the 3 greatest maximum temperatures in a year) and TN3D (mean of the 3 lowest minimum temperatures). CN05.1 in general shows a warmer TX3D over China, while a lower TN3D in the east and greater TN3D in the west are found compared to CN05. A greater value of annual mean precipitation compared to EA05 and APHRO, especially to the latter, is found in CN05.1. For precipitation extreme of R3D (mean of the 3 largest precipitations in a year), CN05.1 presents lower value of it in western China compared to EA05.
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Key words:
- Interpolation /
- Daily data /
- Temperature /
- Precipitation /
- China
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[1] Christensen J H, Hewitson B, Busuioc A, et al. Regional climate projections. //Solomon S, Qin D, Manning M eds. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, New York: Cambridge University Press. 2007.
[2] 石英, 高学杰. 温室效应对我国东部地区气候影响的高分辨率数值试验. 大气科学, 2008, 32(5): 1006-1018. Shi Y, Gao X J. Influence of greenhouse effect on eastern China climate simulated by a high resolution regional climate model. Chinese J. Atmos. Sci. (in Chinese), 2008, 32(5): 1006-1018.
[3] Gao X J, Shi Y, Song R Y, et al. Reduction of future monsoon precipitation over China: Comparison between a high resolution RCM simulation and the driving GCM. Meteor. Atmos. Phys., 2008, 100(1-4): 73-86.
[4] Gao X J, Shi Y, Zhang D F, et al. Uncertainties in monsoon precipitation projections over China: results from two high-resolution RCM simulations. Climate Res., 2012, 52: 213-226, doi: 10.3354/cr01084.
[5] Xie P P, Chen M Y, Song Y, et al. A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeor., 2007, 8(3): 607-626.
[6] Xu Y, Gao X J, Shen Y, et al. A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci., 2009, 26(4): 763-772.
[7] Yatagai A, Arakawa O, Kamiguchi K, et al. A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. SOLA, 2009, 5: 137-140.
[8] 沈艳, 冯明农, 张洪政等. 我国逐日降水量格点化方法. 应用气象学报, 2010, 21(3): 279-286. Shen Y, Feng M N, Zhang H Z, et al. Interpolation methods of China daily precipitation data. J. Appl. Meteor. Sci. (in Chinese), 2010, 21(3): 279-286.
[9] Chen D L, Ou T H, Gong L B, et al. Spatial interpolation of daily precipitation in China: 1951-2005. Adv. Atmos. Sci., 2010, 27(6): 1221-1232.
[10] 高学杰, 石英, Giorgi F. 中国区域气候变化的一个高分辨率数值模拟. 中国科学 (D辑: 地球科学), 2010, 40(7): 911-922. Gao X J, Shi Y, Giorgi F. A high resolution simulation of climate change over China. Science China Earth Sciences, 2011, 54(3): 462-472.
[11] Yu E T, Wang H J, Sun J Q. A quick report on a dynamical downscaling simulation over china using the nested model. Atmos. Oceanic Sci. Lett., 2011, 3(6): 325-329.
[12] Ju L X, Lang X M. Hindcast experiment of extraseasonal short-term summer climate prediction over China with RegCM3_IAP9L-AGCM. Acta Meteor. Sin., 2011, 25(3): 376-385.
[13] Wang A H, Zeng X B. Sensitivities of terrestrial water cycle simulations to the variations of precipitation and air temperature in China. J. Geophys. Res., 2011, 116(D2): D02107.
[14] Feng L, Zhou T J, Wu B, et al. Projection of future precipitation change over China with a high-resolution global atmospheric model. Adv. Atmos. Sci., 2011, 28(2): 464-476.
[15] New M, Hulme M, Jones P. Representing twentieth-century space-time climate variability. Part II: Development of 1901-96 monthly grids of terrestrial surface climate. J. Climate, 2000, 13(13): 2217-2238.
[16] New M, Hulme M, Jones P. Representing twentieth-century space-time climate variability. Part 1: Development of a 1961-90 mean monthly terrestrial climatology. J. Climate, 1999, 12(3): 829-856.
[17] Hutchinson M F. Interpolating mean rainfall using thin plate smoothing splines. Int. J. Geogr. Inf. Sys., 1995, 9(4): 385-403.
[18] Hutchinson M F. ANUSPLIN Version 4.0 user guide. Centre for Resources and Environmental Studies. Canberra: Australian National University, 1999.
[19] 王军邦, 刘纪远, 邵全琴等. 基于遥感-过程耦合模型的1988—2004年青海三江源区净初级生产力模拟. 植物生态学报, 2009, 33(2): 254-269. Wang J B, Liu J Y, Shao Q Q, et al. Spatial-temporal patterns of net primary productivity for 1988—2004 based on GLOPEM-CEVSA Model in the "Three-River Headwaters" region of Qinghai province, China. Chinese Journal of Plant Ecology (in Chinese), 2009, 33(2): 254-269.
[20] 於琍, 李克让, 陶波等. 植被地理分布对气候变化的适应性研究. 地理科学进展, 2010, 29(11): 1326-1332. Yu L, Li K R, Tao B, et al. Simulating and assessing the adaptability of geographic distribution of vegetation to climate change in China. Progress in Geography (in Chinese), 2010, 29(11): 1326-1332.
[21] 赵志平, 刘纪远, 邵全琴. 近30年来中国气候湿润程度变化的空间差异及其对生态系统脆弱性的影响. 自然资源学报, 2010, 25(12): 2091-2100. Zhao Z P, Liu J Y, Shao Q Q. Spatial diversity of humidification and its impact on ecosystem venerability in China during the last 30 years. Journal of Natural Resources (in Chinese), 2010, 25(12): 2091-2100.
[22] Shepard D S. Computer mapping: The SYMAP interpolation algorithm. //Gaile G L, Willmott C J eds. Spatial Statistics and Models. Dordrecht: D. Reidel Publishing, 1984: 133-145.
[23] New M, Lister D, Hulme M, et al. A high-resolution data set of surface climate over global land areas. Climate Res., 2002, 21(1): 1-25.
[24] Gandin L S. Objective Analysis of Meteorological Fields. Israel Program for Scientific Translations, 1965.
[25] Daly C, Gibson W P, Taylor G H, et al. A knowledge-based approach to the statistical mapping of climate. Climate Res., 2002, 22(2): 99-113.
[26] Daly C, Neilson R P, Phillips D L. A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 1994, 33(2): 140-158.
[27] 韩振宇, 周天军. APHRODITE高分辨率逐日降水资料在中国大陆地区的适用性. 大气科学, 2012, 36(2): 361-373. Han Z Y, Zhou T J. Assessing the quality of APHRODITE high-resolution daily precipitation dataset over contiguous China. Chinese J. Atmos. Sci. (in Chinese), 2012, 36(2): 361-373.
[28] 沈永平, 梁红. 高山冰川区大降水带的成因探讨. 冰川冻土, 2004, 26(6): 806-809. Shen Y P, Liang H. High precipitation in Glacial Region of high mountains in High Asia: possible cause. Journal of Glaciology and Geocryology (in Chinese), 2004, 26(6): 806-809.
[29] 《中华人民共和国气候图集》编委会. 中华人民共和国气候图集. 北京: 气象出版社, 2002. Editorial Board of Climatological Atlas of the People's Republic of China. Climatological Atlas of the People's Republic of China (in Chinese). Beijing: Meteorological Press, 2002.
[30] 李生宇, 雷加强, 徐新文等. 塔克拉玛干沙漠腹地沙尘暴特征——以塔中地区为例. 自然灾害学报, 2006, 15(2): 14-19. Li S Y, Lei J Q, Xu X W, et al. Features of sandstorms in hinterland of Taklimakan Desert: a case of Tazhong area. Journal of Natural Disasters (in Chinese), 2006, 15(2): 14-19.
[31] 胡婷, 周江兴, 代刊. USCRN气候基准站网布局理论在我国的应用. 应用气象学报, 2012, 23(1): 40-46. Hu T, Zhou J X, Dai K. Application of USCRN station density strategy to China climate reference network. J. Appl. Meteor. Sci. (in Chinese), 2012, 23(1): 40-46.
[32] Li Z, Yan Z W. Application of multiple analysis of series for homogenization to Beijing daily temperature series (1960—2006). Adv. Atmos. Sci., 2010, 27(4): 777-787.
[33] 龚道溢, 王绍武. 全球气候变暖研究中的不确定性. 地学前缘, 2002, 9(2): 371-376. Gong D Y, Wang S W. Uncertainties in the global warming studies. Earth Science Frontiers (in Chinese), 2002, 9(2): 371-376.
[34] Adam J C, Lettenmaier D P. Adjustment of global gridded precipitation for systematic bias. J. Geophys. Res., 2003,108(D9):4257,doi:10.1029/2002JD002499.
[35] 叶柏生, 成鹏, 杨大庆等. 降水观测误差修正对降水变化趋势的影响. 冰川冻土, 2008, 30(5): 717-725. Ye B S, Cheng P, Yang D Q, et al. Effects of the bias-correction on changing tendency of precipitation over China. Journal of Glaciology and Geocryology (in Chinese), 2008, 30(5): 717-725.
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