气候模式同站点插值外推气象数据的比较

doi:10.11821/dlyj201504003

摘要/Abstract

摘要：

在气象站稀疏的中亚荒漠地区采用基于大气物理机制的区域气候模式,可获得高分辨率格点气象资料进行气候变化研究。针对中亚地区1958-2001年的气候变化,采用RegCM区域气候模式对ERA40和NCEP/NCAR两套气象再分析数据进行动力降尺度至40 km,并将结果同三套基于气象站点插值外推的格点数据（CRU、WM和APHRO）进行比较。所有数据一致表明,1960年代以来新疆地区的气温显著增加,南疆地区降水增加、天山山区降水减少。除APHRO外,数据都表明北疆地区降水呈增加趋势。RegCM模拟的气温和降水数据与站点外推数据空间分布格局基本一致;但RegCM数据年平均气温低于站点外推数据,RegCM数据在新疆山区的年降水量是站点外推数据年降水量的1.3倍。由于研究区内73%的气象站点分布在中山带以下的干热气候区,站点外推数据可能低估山区降水并高估该区域气温。与站点插值外推的格点数据相比,区域气候模式具有能细致描述区域内中小尺度的地形/下垫面特征、更精确反映气象要素空间变异格局的能力。但因为缺乏足够的地面观测以及高精度遥感反演气象数据,当前尚无法全面评估区域气候模式在中亚地区尤其是山区的模拟精度。

关键词: 区域气候模式, 站点插值外推, 气候变化, 中亚

Abstract:

Regional Climate Model (RegCM) simulations, which is based on the fundamental physical and metrological mechanisms, could produce high-resolution climate dataset, without being limited by the availability of meteorological stations in Central Asia. In order to analyze the climate change in Xinjiang from 1958 to 2001, this study used the RegCM model to downscale the ERA40 and NCEP/NCAR reanalysis datasets to a 40-km resolution, and compared the simulation results with three widely used extrapolation datasets (CRU, WM and APHRO). All datasets indicated increased temperature in Xinjiang, increased precipitation in southern Xinjiang, and decreased precipitation in the Tianshan mountainous areas. All datasets except for the APHRO interpolated data indicated increased precipitation in northern Xinjiang. Our analysis showed similar spatial patterns in temperature and precipitation between the RegCM simulated and the extrapolation datasets. However, the simulated regional mean temperature was -3℃ lower than that of the extrapolated datasets. The simulated precipitation in the Tianshan mountainous areas was about twice the value of the extrapolated datasets. Because 73% of the meteorological stations in the study located at the low-mountain areas or the desert plains were in relatively hot and dry climate regimes, extrapolation datasets based on observations at these stations tended to overestimate temperature and underestimate precipitation. Compared with the extropolation method, regional climate modelling considers the detailed topography/landsurface characteristics in the study region at meso-/micro-scales, and is capable to reflect the spatial variation of major climatological elements with higher precision. However, due to limited sparse field observations and a lack of high-resolution remote-sensing-based climate datasets, we are currently unable to fully evaluate the accuracy of the model simulated climate datasets in central Asia, especially in the mountainous areas.

Key words: regional climate model, climate extrapolation, climate change, Central Asia

殷刚, 陈曦, 塔西甫拉提∙特依拜, 邵华, 白磊, 胡增运, 张弛, 徐婷. 气候模式同站点插值外推气象数据的比较[J]. 地理研究, 2015, 34(4): 631-643.

Gang YIN, Xi CHEN, Tashpolat TIYIP, Hua SHAO, Lei BAI, Zengyun HU, Chi ZHANG, Ting XU. A comparison study between site-extrapolation-based and regional climate model-simulated climate datasets[J]. GEOGRAPHICAL RESEARCH, 2015, 34(4): 631-643.

图/表 11

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表3

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图4

表4

表5

图5

表6

山区和低山平原气象站的气温和降水比较"

组号	配对气象站	编号	经度(°)	纬度(°)	海拔(m)	垂直划分	温度(℃)	降水(mm)	M降水 $∶$ L降水
1	昭苏	51437	81.08	43.09	1721	M	3.5	511.3	1.8
1	伊宁	51431	81.20	43.57	1266	L	9.2	278.6	1.8
2	巴音布鲁克	51542	84.09	43.02	2517	M	4.3	277.2	1.3
2	巴伦台	51467	84.40	44.26	886	L	6.9	206.9	1.3
3	乌鲁木齐	51463	87.37	43.47	1781	M	7.4	265.8	1.9
3	昌吉	51365	87.32	44.12	493	L	6.5	142.8	1.9
4	托里	51241	83.36	45.56	1993	M	5.5	245.5	2.2
4	克拉玛依	51243	84.51	45.36	654	L	8.7	111.0	2.2
5	巴里坤	52101	93.00	43.36	2440	M	2.9	219.8	5.7
5	哈密	52203	93.31	42.49	562	L	10.1	38.7	5.7
6	阿合奇	51711	78.27	40.56	2113	M	6.8	219.0	2.2
6	柯坪	51720	79.03	40.30	1279	L	11.7	98.2	2.2

表6

参考文献 32

[1]	万瑜, 曹兴, 崔玉玲. 中天山北坡山区近30a气候变化特征. 干旱气象, 2012, 30(4): 575-582.
	[Wan Yu, Cao Xin, Cui Yulin.Analysis of climate change tengency in north piedmont of middle Tianshan Mountain over recent 30 years. Journal of Arid Meteorology, 2012, 30(4): 575-582.]
[2]	沈永平. 中亚天山是全球气候变化和水循环变化的热点地区. 冰川冻土, 2009, 31(4): 780-780.
	[Shen Yongping.Central Asia Tianshan is the hot spot of global climate change and water cycle change. Journal of Glaciology and Geocryology, 2009, 31(4): 780-780.]
[3]	陈发虎, 黄伟, 靳立亚. 全球变暖背景下中亚干旱区降水变化特征及其空间差异. 中国科学, 2011, 41(11): 1647-1657.
	[Chen Fahu, Huang Wei, Jin Liya, et al.Spatiotemporal precipitation variations in the arid Central Asia in the context of global warming. Science China, 2011, 41(11): 1647-1657.]
[4]	Zwiers F W, Alexander L V, Hegerl G C.Climate extremes: Challenges in estimating and understanding recent changes in the frequency and intensity of extreme climate and weather events. In: Ghassem R A, James W H. Climate Science for Serving Society. Berlin: Springer Netherlands, 2013: 339-389.
[5]	Mitchell T D, Jones P D.An improved method of constructing a database of monthly climate observations and associated high-resolution grids. International Journal of Climatology, 2005, 25(6): 693-712.
[6]	Willmott C J, Robeson S M.Climatologically aided interpolation (CAI) of terrestrial air temperature. International Journal of Climatology, 1995, 15(2): 221-229.
[7]	Yatagai A, Arakawa O, Kamiguchi K.APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bulletin of the American Meteorological Society, 2012, 93(9): 1401-1415.
[8]	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 Zhenyu, Zhou Tianjun.Assessing the quality of APHRODITE high-resolution daily precipitation dataset over contiguous China. Atmospheric Sciences, 2012, 36(2): 361-373.]
[9]	Lanhai L, Lei B, Yanan Y, et al.Patterns of climate change in Xinjiang projected by IPCC SRES. Journal of Resources and Ecology, 2013, 4(1): 27-35.
[10]	Lioubimtseva E, Cole R.Uncertainties of climate change in arid environments of Central Asia. Reviews in Fisheries Science, 2006, 14(1-2): 29-49.
[11]	Xu Ying, Gao Xuejie, Shen Yan.A daily temperature dataset over China and its application in validating a RCM simulation. Advances in Atmospheric Sciences, 2009, 26(4): 763-772.
[12]	周建玮, 王咏青. 区域气候模式RegCM3应用研究综述. 气象科学, 2008, 27(6): 702-708.
	[Zhou Jianwei, Wang Yongqing.The advance in application and research of regional climate model RegCM3. Scientia Meteorologica Sinica, 2008, 27(6): 702-708.]
[13]	高学杰, 石英, 张冬峰. RegCM3 对21世纪中国区域气候变化的高分辨率模拟. 科学通报, 2012, 57(5): 374-381.
	[Gao Xuejie, Shi Yin, Zhang Dongfeng.Climate change in China in the 21st century as simulated by a high resolution regional climate model. Chinese Science Bulletin, 2012, 57(5): 374-381.]
[14]	Uppala S M, Kallberg P W, Simmons A J, et al.The ERA40 reanalysis. Quarterly Journal of the Royal Meteorological Society, 2005, 131(612): 2961-3012.
[15]	Bromwich D H, Fogt R L.Strong trends in the skill of the ERA40 and NCEP-NCAR reanalyses in the high and midlatitudes of the Southern Hemisphere, 1958-2001. Journal of Climate, 2004, 17(23): 4603-4619.
[16]	Kalnay E, Kanamitsu M, Kistler R, et al.The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 1996, 77(3): 437-471.
[17]	Willmott C J, Matsuura K.On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. International Journal of Geographical Information Science, 2006, 20(1): 89-102.
[18]	Yue S, Pilon P, Cavadias G.Power of the mann-kendall and spearman's rho tests for detecting monotonic trends in hydrological series. Journal of Hydrology, 2002, 259(1): 254-271.
[19]	杨莲梅. 新疆极端降水的气候变化. 地理学报, 2003, 58(4): 577-583.
	[Yang Lianmei.Climate change of extreme precipitation in Xinjiang. Acta Geographica Sinica, 2003, 58(4): 577-583.]
[20]	姜逢清, 胡汝骥, 杨跃辉. 新疆洪灾时间序列突变及其气候原因分析. 冰川冻土, 2004, 26(6): 674-681.
	[Jiang Fengqing, Hu Ruji, Yang Yuehui.Abrupt change in the time sequences of flood disasters in Xinjiang and its possible climate reasons. Journal of Glaciology and Geocryology, 2004, 26(6): 674-681.]
[21]	陈曦, 夏军, 钱静. 三工河流域分布式水文模型研究. 干旱区地理, 2003, 26(4): 305-308.
	[Chen Xi, Xia Jun, Qian Jing.Study on distributed hydrological model in Sangong River Basin. Arid Land Geography, 2003, 26(4): 305-308.]
[22]	IPCC. Climate change 2007: The physical science basis. In: Solomon S, Qin D, Manning M, et al. Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York: Cambridge University Press, 2007: 608-629.
[23]	Schiemann R, Luthi D, Vidale P L, et al.The precipitation climate of Central Asia: Intercomparison of observational and numerical data sources in a remote semiarid region. International Journal of Climatology, 2008, 28(3): 295-314.
[24]	Small E E, Giorgi F, Sloan L C.Regional climate model simulation of precipitation in central Asia: Mean and interannual variability. Journal of Geophysical Research: Atmospheres (1984-2012), 1999, 104(D6): 6563-6582.
[25]	姜燕敏, 吴昊旻. 20个CMIP5模式对中亚地区年平均气温模拟能力评估. 气候变化研究进展, 2013, 9(2): 110-116.
	[Jiang Yanmin, Wu Haomin.Simulation capabilities of 20 CMIP5 models for annual mean air temperatures in Central Asia. Advances in Climate Change Research, 2013, 9(2): 110-116.]
[26]	Adam J C, Lettenmaier D P.Adjustment of global gridded precipitation for systematic bias. Journal of Geophysical Research: Atmospheres (1984-2012), 2003, 108(D9): 4257-4272.
[27]	Elguindi N, Giorgi F.Simulating multi-decadal variability of Caspian Sea level changes using regional climate model outputs. Climate Dynamics, 2006, 26(2-3): 167-181.
[28]	Liu Z, Ostrenga D, Teng W.Tropical rainfall measuring mission (TRMM) precipitation data and services for research and applications. Bulletin of the American Meteorological Society, 2012, 93(9): 1317-1325.
[29]	祝合勇, 杨太保, 田洪阵. 1973-2010年阿尔金山冰川变化. 地理研究, 2013, 32(8): 1430-1438.
	[Zhu Heyong, Yang Taibao, Tian Hongzhen.Glacier variation in the Altun Mountains from 1973 to 2010. Geographical Research, 2013, 32(8): 1430-1438.]
[30]	Barry R G.Mountain Weather and Climate. New York: Cambridge University Press, 2013.
[31]	陈曦. 中国干旱区自然地理. 北京: 科学出版社, 2010.
	[Chen Xi.Physical Geography of Arid Land in China. Beijing: Science Press, 2010.]
[32]	姚晓军, 张晓, 孙美平. 1960-2010年中国西北地区水分盈亏量时空特征. 地理研究, 2013, 32(4): 607-616.
	[Yao Xiaojun, Zhang Xiao, Sun Meiping.Spatial-temporal characteristics of water deficit in Northwest China from 1960 to 2010. Geographical Research, 2013, 32(4): 607-616.]

数据集名称	变量	时间覆盖	时间分辨率	区域	空间分辨率
NCEP	气温、降水	1979-2011	日	全球	2.5°
ERA40	气温、降水	1957-2002	日	全球	2.5°
NCEP-RegCM	气温、降水	1948-2010	日	中亚	40 km
ERA40-RegCM	气温、降水	1979-2010	日	中亚	40 km
CRU	气温、降水	1901-2009	月	全球	0.5°
WM	气温、降水	1900-2008	月	全球	0.5°
APHRO	降水	1951-2007	日	全球	0.25°

子研究区	驱动数据源	模拟数据与站点外推数据的相关系数
子研究区	驱动数据源	CRU	WM
北疆准格尔	ERA40	0.73	0.72
北疆准格尔	NCEP/NCAR	0.77	0.77
南疆塔里木	ERA40	0.58	0.69
南疆塔里木	NCEP/NCAR	0.61	0.69
天山山区	ERA40	0.66	0.72
天山山区	NCEP/NCAR	0.70	0.75

子研究区	驱动数据源	模拟数据与站点外推数据的相关系数			模拟数据与站点外推数据的年降水量(mm)
子研究区	驱动数据源	CRU	WM	APHRO	RegCM	CRU	WM	APHRO
北疆准格尔	ERA40	0.55	0.52	0.51	192	150	173	149
北疆准格尔	NCEP	0.61	0.64	0.63	178	150	173	149
南疆塔里木	ERA40	0.61	0.60	0.59	90	90	83	61
南疆塔里木	NCEP	0.49	0.55	0.61	71	90	83	61
天山山区	ERA40	0.62	0.59	0.65	400	282	291	300
天山山区	NCEP	0.71	0.65	0.69	356	282	291	300

研究区	数据集	多年平均气温	K(℃/10a)	突变年份	突变前平均气温(℃)	突变后平均气温(℃)	突变后/突变前
北疆准格尔	NCEP-RegCM	2.95	0.28^*	1977	2.37	3.39	1.43
北疆准格尔	ERA40-RegCM	3.26	0.08
	CRU	5.75	0.43^*	1987	5.39	6.51	1.21
	WM	4.56	0.30^*	1977	4.15	4.88	1.18
南疆塔里木	NCEP-RegCM	6.51	0.13
南疆塔里木	ERA40-RegCM	6.68	-0.02
	CRU	10.26	0.22^*	1994	10.12	10.89	1.08
	WM	10.01	0.12^*	1996	9.94	10.60	1.07
天山山区	NCEP-RegCM	0.58	0.12
	ERA40-RegCM	0.91	-0.01
	CRU	4.34	0.30^*	1989	4.13	4.88	1.18
	WM	3.33	0.23^*	1989	3.12	3.77	1.21

研究区域	数据集	多年平均降水(mm)	K(mm/a)	突变年份	突变前平均降水(mm)	突变后平均降水(mm)	突变后/突变前
北疆准格尔	NCEP-RegCM	177.51	0.21
北疆准格尔	ERA40-RegCM	191.72	0.27
	CRU	149.61	0.63
	WM	173.37	1.24^*	1989	162.03	200.41	1.24
	APHRO	148.40	-0.23
南疆塔里木	NCEP-RegCM	71.36	0.08
南疆塔里木	ERA40-RegCM	90.07	0.49^*	1973	82.42	94.02	1.14
	CRU	83.80	0.11
	WM	60.66	0.78^*	1988	53.75	75.48	1.40
	APHRO	62.76	0.46^*
天山山区	NCEP-RegCM	355.69	-0.86
天山山区	ERA40-RegCM	399.88	0.30
	CRU	281.54	-0.31
	WM	291.10	-0.11
	APHRO	300.39	-0.33