基于ArcGIS的陕西省天气气候极值及其重现期值的时空分布特征研究
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摘要
气象灾害是自然灾害中最为频繁而又严重的灾害,随着全球气候变暖趋势的加剧,影响我国最为严重的特大干旱、暴雨洪涝等极端天气气候事件发生的频率越来越高,破坏程度越来越强,影响范围越来越大,多年一遇,甚至百年一遇,超百年一遇的极端天气气候事件不断发生,严重威胁到人民的正常生活和社会的安全生产。随着气候变化和人们对于极端气候事件的重视及气候可行性论证工作的开展,对于极端气候事件暨气候极值如极端最高气温,极端最低气温,日最大降水量,年降水量等的时空分布特征及影响的研究就显得较为迫切。
本文以ArcGIS为主要工具,结合DEM和数理统计方法,对陕西省气象台站观测的历史极端气温和降水资料的空间插值方法进行了探讨和甄别,并通过科学方法进行了验证,进而分析了陕西省极端气温和降水的时空分布特征;通过Visual Basic编程,对气温、降水等不同气象要素重现期的计算方法进行了筛选,对陕西省极端气温和降水分别采用科学的方法给出了不同重现期的空间分布,并给出了相应的定量分析结果。结论如下:
1.陕西省极端最高气温多出现在6月和7月,极端最低气温多出现在12月和1月,地区差异很大。极端最高气温年际变化特征明显,1951年至1982年各个地区年极端最高气温呈持平或降低趋势。1983年以后,年极端最高气温呈现出明显的上升趋势。极端最低气温年际变化特征明显,1951年至2007年各个地区年极端最高气温呈现逐步升高的趋势。
2.陕西省日最大降水量多出现在6、7、8月,各月差异非常大,且日最大降水量并没有显著的北少南多特征。年降水量有显著的北少南多特征,年际变化特征明显,以榆林,延安,西安,安康,汉中为代表站点,1951年至2007年各个地区除安康略有上升外,其余四站年降水量均呈现减少趋势。
3.在考虑海拔高度影响下,无论极端最高气温还是极端最低气温,用普通克里金插值的方法效果最好。极端气温重现期的计算采用Weibull分布的S~2_f、R_f及K_f最小,效果最好。
极端降水插值方法的选取中,径向基函数法效果最好,极端降水量重现期的计算应用矩法参数估计的极值Ⅰ型分布的S~2_f、R_f及K_f最小,效果最为理想。
4.陕西省重现期极端最高和极端最低气温的地域差异明显,十五年一遇极端最高气温多集中于34～42℃,占总面积的88.92%。三十年一遇极端最高气温多集中于34～42℃,占总面积的87.11%。五十年一遇极端最高气温多集中于36～42℃,占总面积的76.76%。百十年一遇极端最高气温多集中于36～44℃,占总面积的88.83%。
十五年一遇极端最低气温多集中于-11～-29℃,占总面积的72.98%。三十年一遇极端最低气温多集中于-11～-29℃,占总面积的74.30%。五十年一遇极端最低气温多集中于-11～-32℃,占总面积的87.63%。百年一遇极端最低气温多集中于-14～-32℃,占总面积的72.80%。
5.陕西省大部分地区十五年一遇日最大降水量介于75.0～200.0mm。三十年一遇日最大降水量介于75.0～225.0mm。五十年一遇日最大降水量介于100.0～250.0mm。百年一遇日最大降水量介于100.0～300.0mm。其中,汉中的镇巴和安康的紫阳及宁陕小部分地区为重现期日最大降水量大值区。
陕西省全境绝大部分地区三十年一遇以上的日最大降水量都达到了大暴雨的标准。部分地区百年一遇日最大降水量达到了特大暴雨的标准。
陕西省大部分地区十五年一遇年最大降水量介于400.0～1900.0mm。三十年一遇年最大降水量介于500.0～2100.0mm。五十年一遇年最大降水量介于500.0～2200.0mm。百年一遇年最大降水量介于600.0～2400.0mm。陕西省多年一遇年最大降水量空间分布总体呈现明显的阶梯状分布特征,由南至北年最大降水量逐级递减,有几个大值区,大值区多出现在汉中的镇巴和宁强等。
本文在以下几个方面具有一定的创新性:
1.以反映天气气候最基本的气温和降水为研究对象,给出了陕西省极端天气气候要素的时空分布特征,在为社会各行业提供一定参考的同时,也可以为防灾减灾提供相应的数据支撑和科学依据。相似的文献至今鲜见,具有一定的创新性。
2.通过编程,利用ArcGIS软件,结合DEM以及对不同气象要素重现期计算方法及空间插值方法的选择,对气象要素极值的时空分布特征及其重现期值的空间分布特征进行了探讨,并且给出了定量的结论,为今后进行类似的科学研究提供了可参考的解决思路,具有一定的创新性。
Weather disasters are the most frequent and severe disasters among the natural disasters,with the trend of global warming intensifies,the frequency of extreme weather and climate events such as drought,flood which impact China are higher,the damage cause by it are stronger,the range of influence cause by it are larger.The extreme weather and climate events which once in several yeares,once in 100 yeares or once in more than 100 yeares are continue to occur,even become a serious threat to people's normal life and social safety.With the climate change、people pay more attention to the extreme climate events and the development of feasibility study of climate,the study of spatial and temporal distribution and its impact of extreme climate events such as extreme maximum temperature,extreme minimum temperature,daily maximum precipitation,annual precipitation has become more urgent.
This thesis take ArcGIS as the main tool,combined with DEM and mathematical statistical methods,probe and distinguish the spatial interpolation methods of history extreme temperature and precipitation data which observed by meteorological stations of Shaanxi Province,the conclution has been verified through scientific methods,after this,the characteristics of the spatial and temporal distribution of extreme temperature and precipitation of Shaanxi Province has been analyzed.Through the Visual Basic programming,the methods of calculation the different return periods of precipitation and other meteorological factors has been selected,the spatial distribution of extreme temperature and precipitation of Shaanxi Province has been given by adopt scientific method,the corresponding quantitative analysis results has been given too.Conclusions were as follows:
1.The extreme maximum temperature of Shaanxi Province appears in June and July mostly, which appears in December and January mostly,there has significant regional differences.The characteristics of inter-annual extreme temperature are obvious from 1951 to 1982.After 1983,the annual extreme maximum temperatures show a clear upward trend.The inter-annual variation of extreme minimum temperature is obvious;from 1951 to 2007 the extreme maximum temperature in various regions has upward trend.
2.The daily maximum precipitation of Shaanxi Province appears in June、July and August mostly,the difference between each month is very large,and it has no significant characteristics of less in North and more in South.Annual precipitation has the significantly characteristics of less in North and more in South,and inter-annual characteristics is obvious.Take Yulin,Yan'an, Xi'an,Ankang,Hanzhong as the representative site,the annual precipitation of Ankang is increased slightly from 1951 to 2007,and the remaining four years showed a decreasing trend.
3.In considering the influence of altitude,whenever extreme maximum temperatures or extreme minimum temperature,the effect of interpolation by using ordinary Kriging method is best. The S_f~2,R_f and K_f of Return periods of extreme temperatures calculated using Weibull distribution is smallest and the effect is best.
In the selection of interpolation methods of extreme precipitation,the method of radial basis function is best.The S_f~2,R_f and K_f of Return periods of extreme precipitation calculated using the methord of extreme value type I distribution which estimated by moment parameters is smallest and the effect is best.
4.The regional differences of return period of extreme maximum and extreme minimum temperature of Shaanxi Province is obvious,Once in 15 years is mostly during 34～42℃,88.92% of total area.Once in 30 years is mostly during 34～42℃,87.11%of total area.Once in 50 years is mostly during 36～42℃,76.76%of total area.Once in 100 years is mostly during 36～44℃, 88.83%of total area.
The extreme minimum temperatures of once in 15 years is mostly during -11～-29℃,72.98% of total area.Once in 30 years is mostly during -11～-29℃,74.30%of total area.Once in 50 years is mostly during -11～-32℃,87.63%of total area.Once in 100 years is mostly during -14～-32℃, 72.80%of total area.
5.The daily maximum precipitation of once in 15 years in most areas of Shaanxi Province are between 75.0～200.0mm.Once in 30 years in most areas of Shaanxi Province are between 75.0～225.0mm.Once in 50 years in most areas of Shaanxi Province are between 10.0～250.0mm.Once in 100 years in most areas of Shaanxi Province are between 100.0～300.0mm.Among them, Zhenba of Hanzhong and Ziyang of Ankang and other small area in Ningshan are the largest value areas of daily maximum precipitation of return period.
The daily maximum precipitation of once in 30 years or above in most areas of Shaanxi Province has reached the heavy rain standard.Once in 100 years in some areas has reached the ultra-heavy rain standard.
The annual maximum precipitation of once in 15 years in most areas of Shaanxi Province are between 40.0～1900.0mm.Once in 30 years are between 500.0～2200.0mm.Once in 50 years are between 500.0～2100.0mm.Once in 100 years are between 600.0～2400.0mm.The spatial distribution of annual maximum precipitation of once in several years of Shaanxi Province shows a clear ladder-like characteristic,the annual maximum precipitation are decreased from south to north,there are several large values district which appears in the Zhenba and Ningqiang of Hanzhong.
In this thesis,there has some innovation in following aspects:
1.The study of temperature and precipitation which is the basic reflection of weather and climate has been developed,the temporal and spatial distribution extreme weather and climate elements in Shaanxi Province has been given,it can provide a reference for various sectors of society,and provide corresponding data support and scientific basis for disaster prevention.There has little similar literature so far,so it has a certain degree of innovation.
2.Through programming,the use of ArcGIS software,combined with DEM and the selection of calculation methods and interpolation methods for meteorological factors of different return periods,this thesis analysis the spatial and temporal distribution characteristics of meteorological elements and its return period value,the quantitative conclusions are given.All above gives the solution ideas about similar analysis on the future,there has some innovation.
本文以ArcGIS为主要工具,结合DEM和数理统计方法,对陕西省气象台站观测的历史极端气温和降水资料的空间插值方法进行了探讨和甄别,并通过科学方法进行了验证,进而分析了陕西省极端气温和降水的时空分布特征;通过Visual Basic编程,对气温、降水等不同气象要素重现期的计算方法进行了筛选,对陕西省极端气温和降水分别采用科学的方法给出了不同重现期的空间分布,并给出了相应的定量分析结果。结论如下:
1.陕西省极端最高气温多出现在6月和7月,极端最低气温多出现在12月和1月,地区差异很大。极端最高气温年际变化特征明显,1951年至1982年各个地区年极端最高气温呈持平或降低趋势。1983年以后,年极端最高气温呈现出明显的上升趋势。极端最低气温年际变化特征明显,1951年至2007年各个地区年极端最高气温呈现逐步升高的趋势。
2.陕西省日最大降水量多出现在6、7、8月,各月差异非常大,且日最大降水量并没有显著的北少南多特征。年降水量有显著的北少南多特征,年际变化特征明显,以榆林,延安,西安,安康,汉中为代表站点,1951年至2007年各个地区除安康略有上升外,其余四站年降水量均呈现减少趋势。
3.在考虑海拔高度影响下,无论极端最高气温还是极端最低气温,用普通克里金插值的方法效果最好。极端气温重现期的计算采用Weibull分布的S~2_f、R_f及K_f最小,效果最好。
极端降水插值方法的选取中,径向基函数法效果最好,极端降水量重现期的计算应用矩法参数估计的极值Ⅰ型分布的S~2_f、R_f及K_f最小,效果最为理想。
4.陕西省重现期极端最高和极端最低气温的地域差异明显,十五年一遇极端最高气温多集中于34～42℃,占总面积的88.92%。三十年一遇极端最高气温多集中于34～42℃,占总面积的87.11%。五十年一遇极端最高气温多集中于36～42℃,占总面积的76.76%。百十年一遇极端最高气温多集中于36～44℃,占总面积的88.83%。
十五年一遇极端最低气温多集中于-11～-29℃,占总面积的72.98%。三十年一遇极端最低气温多集中于-11～-29℃,占总面积的74.30%。五十年一遇极端最低气温多集中于-11～-32℃,占总面积的87.63%。百年一遇极端最低气温多集中于-14～-32℃,占总面积的72.80%。
5.陕西省大部分地区十五年一遇日最大降水量介于75.0～200.0mm。三十年一遇日最大降水量介于75.0～225.0mm。五十年一遇日最大降水量介于100.0～250.0mm。百年一遇日最大降水量介于100.0～300.0mm。其中,汉中的镇巴和安康的紫阳及宁陕小部分地区为重现期日最大降水量大值区。
陕西省全境绝大部分地区三十年一遇以上的日最大降水量都达到了大暴雨的标准。部分地区百年一遇日最大降水量达到了特大暴雨的标准。
陕西省大部分地区十五年一遇年最大降水量介于400.0～1900.0mm。三十年一遇年最大降水量介于500.0～2100.0mm。五十年一遇年最大降水量介于500.0～2200.0mm。百年一遇年最大降水量介于600.0～2400.0mm。陕西省多年一遇年最大降水量空间分布总体呈现明显的阶梯状分布特征,由南至北年最大降水量逐级递减,有几个大值区,大值区多出现在汉中的镇巴和宁强等。
本文在以下几个方面具有一定的创新性:
1.以反映天气气候最基本的气温和降水为研究对象,给出了陕西省极端天气气候要素的时空分布特征,在为社会各行业提供一定参考的同时,也可以为防灾减灾提供相应的数据支撑和科学依据。相似的文献至今鲜见,具有一定的创新性。
2.通过编程,利用ArcGIS软件,结合DEM以及对不同气象要素重现期计算方法及空间插值方法的选择,对气象要素极值的时空分布特征及其重现期值的空间分布特征进行了探讨,并且给出了定量的结论,为今后进行类似的科学研究提供了可参考的解决思路,具有一定的创新性。
Weather disasters are the most frequent and severe disasters among the natural disasters,with the trend of global warming intensifies,the frequency of extreme weather and climate events such as drought,flood which impact China are higher,the damage cause by it are stronger,the range of influence cause by it are larger.The extreme weather and climate events which once in several yeares,once in 100 yeares or once in more than 100 yeares are continue to occur,even become a serious threat to people's normal life and social safety.With the climate change、people pay more attention to the extreme climate events and the development of feasibility study of climate,the study of spatial and temporal distribution and its impact of extreme climate events such as extreme maximum temperature,extreme minimum temperature,daily maximum precipitation,annual precipitation has become more urgent.
This thesis take ArcGIS as the main tool,combined with DEM and mathematical statistical methods,probe and distinguish the spatial interpolation methods of history extreme temperature and precipitation data which observed by meteorological stations of Shaanxi Province,the conclution has been verified through scientific methods,after this,the characteristics of the spatial and temporal distribution of extreme temperature and precipitation of Shaanxi Province has been analyzed.Through the Visual Basic programming,the methods of calculation the different return periods of precipitation and other meteorological factors has been selected,the spatial distribution of extreme temperature and precipitation of Shaanxi Province has been given by adopt scientific method,the corresponding quantitative analysis results has been given too.Conclusions were as follows:
1.The extreme maximum temperature of Shaanxi Province appears in June and July mostly, which appears in December and January mostly,there has significant regional differences.The characteristics of inter-annual extreme temperature are obvious from 1951 to 1982.After 1983,the annual extreme maximum temperatures show a clear upward trend.The inter-annual variation of extreme minimum temperature is obvious;from 1951 to 2007 the extreme maximum temperature in various regions has upward trend.
2.The daily maximum precipitation of Shaanxi Province appears in June、July and August mostly,the difference between each month is very large,and it has no significant characteristics of less in North and more in South.Annual precipitation has the significantly characteristics of less in North and more in South,and inter-annual characteristics is obvious.Take Yulin,Yan'an, Xi'an,Ankang,Hanzhong as the representative site,the annual precipitation of Ankang is increased slightly from 1951 to 2007,and the remaining four years showed a decreasing trend.
3.In considering the influence of altitude,whenever extreme maximum temperatures or extreme minimum temperature,the effect of interpolation by using ordinary Kriging method is best. The S_f~2,R_f and K_f of Return periods of extreme temperatures calculated using Weibull distribution is smallest and the effect is best.
In the selection of interpolation methods of extreme precipitation,the method of radial basis function is best.The S_f~2,R_f and K_f of Return periods of extreme precipitation calculated using the methord of extreme value type I distribution which estimated by moment parameters is smallest and the effect is best.
4.The regional differences of return period of extreme maximum and extreme minimum temperature of Shaanxi Province is obvious,Once in 15 years is mostly during 34～42℃,88.92% of total area.Once in 30 years is mostly during 34～42℃,87.11%of total area.Once in 50 years is mostly during 36～42℃,76.76%of total area.Once in 100 years is mostly during 36～44℃, 88.83%of total area.
The extreme minimum temperatures of once in 15 years is mostly during -11～-29℃,72.98% of total area.Once in 30 years is mostly during -11～-29℃,74.30%of total area.Once in 50 years is mostly during -11～-32℃,87.63%of total area.Once in 100 years is mostly during -14～-32℃, 72.80%of total area.
5.The daily maximum precipitation of once in 15 years in most areas of Shaanxi Province are between 75.0～200.0mm.Once in 30 years in most areas of Shaanxi Province are between 75.0～225.0mm.Once in 50 years in most areas of Shaanxi Province are between 10.0～250.0mm.Once in 100 years in most areas of Shaanxi Province are between 100.0～300.0mm.Among them, Zhenba of Hanzhong and Ziyang of Ankang and other small area in Ningshan are the largest value areas of daily maximum precipitation of return period.
The daily maximum precipitation of once in 30 years or above in most areas of Shaanxi Province has reached the heavy rain standard.Once in 100 years in some areas has reached the ultra-heavy rain standard.
The annual maximum precipitation of once in 15 years in most areas of Shaanxi Province are between 40.0～1900.0mm.Once in 30 years are between 500.0～2200.0mm.Once in 50 years are between 500.0～2100.0mm.Once in 100 years are between 600.0～2400.0mm.The spatial distribution of annual maximum precipitation of once in several years of Shaanxi Province shows a clear ladder-like characteristic,the annual maximum precipitation are decreased from south to north,there are several large values district which appears in the Zhenba and Ningqiang of Hanzhong.
In this thesis,there has some innovation in following aspects:
1.The study of temperature and precipitation which is the basic reflection of weather and climate has been developed,the temporal and spatial distribution extreme weather and climate elements in Shaanxi Province has been given,it can provide a reference for various sectors of society,and provide corresponding data support and scientific basis for disaster prevention.There has little similar literature so far,so it has a certain degree of innovation.
2.Through programming,the use of ArcGIS software,combined with DEM and the selection of calculation methods and interpolation methods for meteorological factors of different return periods,this thesis analysis the spatial and temporal distribution characteristics of meteorological elements and its return period value,the quantitative conclusions are given.All above gives the solution ideas about similar analysis on the future,there has some innovation.
引文
[1]郭进修,毕宝贵,李泽春.我国气象灾害分类和科学防灾减灾[M].气象出版社.2004.
[2]李世奎.中国农业灾害风险评价与对策[M]气象出版社.1999.
[3]http://www.xinhuanet.com/chinanews/2007-11/28/content_11787783.htm.
[4]Rajendra K.Pachauri.气候变化2007综合报告[M].2007.
[5]雷治平,刘引鸽,李录堂.陕西农业干旱灾害分析评估[J].陕西气象,2006,01(1):12-14.
[6]陈洪滨,范学花,董文杰.2005年极端天气与气候事件及其他相关事件的概要回顾.气候与环境研究,2006,11(2):236-244
[7]么枕生,丁裕国.气候统计[M].北京:气象出版社,1990,45-51.
[8]刘小宁.我国暴雨极端事件的气候变化特征[J].灾害学,1999,14(1):54-59
[9]Changnon S A,Roger A,Pielk Jr.,et al.Human factors explain the increased losses from weather and climate extremes[J].Bull.Of the Amer.Mete.Soci.2000,81(3):437-442.
[10]Houghton J T,Ding Y,Griggs J,et al.Climate Change2001:The Scientific Basis,Observed Climate Variability and Chang.Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change[M].Cambridge,UK:Cambridge University Press,2001:1-881.
[11]Easterling D R,Evans J L,YaGroisman P,etal.Observed variability and trends in extreme climate events:a brief review[J].Bull.oftheAmeri.Mete.Soci.2000,81(3):417-425.
[12]Karl T R,Kukla G,Razuvayev V N,et.al.Global Warming:Evidence for asymmetric diurnal temperature change[J].Geography.Res.Lett.1991,18:2253-2256
[13]Horton B.Geo graphical distribution of change at maximum and minimum temperatures,Atmos.Res,1995,37,101-117.
[14]Karl T R,Jones P D,Knight R W,et al.A new perspective on recent global warming:asymmetric trends of daily maximum and minimum temperature[J].Bull.Amer.Meteor.Soc.1993,74(6):1007-1023.
[15]Cooter E J,LeDuk S K.Recent frost data trends in the northern United States[J].Int.J.Climatology,1993,15:65-75.
[16]ZhaiPM,PanXH.Trends in temperature extremes during1951-1999 in china [J].Geophysical Research Letters,2003,30(17):1913-1916.
[17]Gruza G,Rankova E,Razuvaev V.Indicators of climate change for the Russian Federation[J].Clim.Change,1999,42:219-242
[18]Frith P,Alexander L V,Della-Marta P,et al.Observed coherent changes in climate extremes during the second half of the 20th century[J].Clim.Res.,2002,19:193-212.
[19]Manton M J,Della-Marta P M,Haylock M R,etal.Trend in extreme daily rainfall and temperature in southeast Asia and the South Pacific:1961-1998[J].Int.J.Climatol.,2001,21:269-284.
[20]Mearns and Katz R.W.Extreme high-temperature events in their probalities changes in mean temperature.Climate and Appl.Meteo,1984,23(2):1601-1613.
[21]Katz,R.W,B.G.Browns,Extreme events in a changing climate:Variability is more impotant than averages,Climatic Change,21,289-302,1992.
[22]Zhai Panmao,Pan Xiaohua.Change in extreme temperature and precipitation over Northern China during the second half of the20th century[J].Acta Geographica Sinica,2003,58(supp.1):1-10.
[翟盘茂,潘晓华.中国北方近50年温度和降水极端事件变化[J].地理学报,2003,58(增刊):1-10.
[23]Zhai Panmao,Ren Fumin.On changes ofChina'smaxmum andminimum temperatures in the recent 40 years[J].ActaMeteoro-logica Sinica,1997,55(4):418-429.
[翟盘茂,任福民.中国近四十年最高最低温度变化[J].气象学报,1997,55(4):418-429.
[24]Ren Fumin,Zhai Panmao.Study on changes ofChina's extremetemperature during 1951-1990[J].Scientia Atmospheric Sinica,1998,22(2):217-226.
[任福民,翟盘茂.1951-1990年中国极端温度变化分析[J].大气科学,1998,22(2):217-226.
[25]Zhai Panmao,ZouXuka.i Change in temperature and precipitati-on and their impacts on drought in China during 1951-2003[J].Advances in Climate ChangeResearch,2005,1(1):16-18.
[翟盘茂,邹旭恺.1951-2003年中国气温和降水变化及其对干旱的影响[J].气候变化研究进展,2005,1(1):16-18.
[21]Pan Xiaohua,Zhai Panmao.Analysis of surface air temperature extremum[J].Meteorological Monthly,2002,28(10):28-31.
[潘晓华,翟盘茂.气候 极端值的选取与分析[J].气象,2002,28(10):28-31.
[26]Tang Hongyu,ZhaiPanmao,Wang Zhenyu.On change in mean maximum temperature,minimum temperature and diurnal range in China during 1951-2002[J].Climatic and EnvironmentalRe-search,2005,10(4):728-735.
[唐红玉,翟盘茂,王振宇.1951-2002年中国平均最高、最低气温及日较差变化[J].气候与环境研究,2005,10(4):728-735.
[27]Wang Yawe,i Zhai Panmao,Tian Hua.Extreme high temperatures in Southern China in 2003 under the background of climate change[J].Meteorological Monthly,2006,32(10):27-33.
[王亚伟,翟盘茂,田华.近40年南方高温变化特征与2003年的高温事件[J].气象,2006,32(10):27-33.
[28]Ma Zhuguo.Variation of frostdays and its relationship to regional warming in Northern China[J].Acta Geographica Sinic,2003,58(supp.l):31-37.
马柱国.中国北方地区霜冻日的变化与区域增暖相互关系[J].地理学报,2003,58(增刊):31-37.
[29]Ma Zhuguo,Hua Lijuan,Ren Xiaobo.The extreme dry/wet events in Northern China during recent 100 years[J].Acta Geographical Sinic,2003,58(supp.l):69-74.
[马柱国,华丽娟,任小波.中国近代北方极端干湿事件的演变规律[J].地理学报,2003,58(增刊):69-74.
[30]Hua Lijuan,Ma Zhuguo,Zeng Zhaome.i The comparative analysis of the changes of extreme temperature and extreme diurnal temperature range of large cities and small towns in Eastern China[J].Scientia Atmospheric Sinica,2006,30(1):80-92.
[华丽娟,马柱国,曾昭美.中国东部地区大城市和小城镇极端温度及日较差变化对比分析[J].大气科学,2006,30(1):80-92.
[31]Yan Zhongwe,i YangCh.i Geographic patterns of extreme climate changes in China during 1951-1997[J].Climatic and Environmental Research,2000,5(3):265-270.
[严中伟,杨赤.近几十年中国极端气候变化格局[J].气候与环境研究,2000,5(3):265-270.
[32]Yan ZW,Yang C,Jones P.Influence of inhomogeneity on the estimation of mean and extreme temperature trends in Beijing and Shanghai[J].Advances in Atmospheric Sciences,2001,18(3):309-322.
[33]邓自旺,定裕国,陈业国.全球气候变化对长江三角洲极端高温事件概率的影响[J].南京气象学院学报,2000,23(1):42-47.
[34]HuRu ji,FanZili,WangYajun.Assessment about the impact of climate change on environment in Xin jiang since recent 50 years[J].AridLandGeo graphy,2001,24(2):97-103.
(胡汝骥,樊自立,王亚俊.近50a新疆气候变化对环境影响评估[J].干旱区地理,2001,24(2):97-103.
[35]施能,陈家其,屠其璞.中国近100年来4个年代际的气候变化特征[J].气象学报,1995,53(4):431-439.
[36]丁裕国,刘吉峰,张耀存.基于概率加权估计的中国极端气温时空分布模拟试验[J].大气科学,2004,28(5):770-782.
[37]苏志,李艳兰,涂方旭,等.广西冬季极端最低气温的概率分布模型选择及其极值和重现期计算[J].广西科学,2002,9(1):73-77.
[38]陈建昌,郭化文,魏牲生,等.用Jenkinson法推算山东年最大日雨量重现期值的初探[J].应用气象学报,1995(4):486-488.
[39]杨水泉.用极值分布计算黔南最大一日降水量的重现期[J].贵州气象,1997(6).
[40]程乾,张惠生,黄显金,等.吐鲁番一日最大降水量年极值频率分布[J].新疆气象,1998(1).
[41]郭兆夏,符昱,王军,等.陕西苹果主产区日最低(最高)气温的空间插值[J].陕西气象,2008(5):24-26.
[42]党安荣,贾海峰,易善桢.等著.ArcGIS 9 Desktop地理信息系统应用指南[M].北京:清华大学出版社,2007.
[43]Visual Basic程序设计教程,罗朝盛,人民邮电出版社,2005.
[44]唐启义,冯明光.实用统计分析及其DPS数据处理系统.北京:科学出版社,2002.1-647.
[45]林少宫.基础概率与数理统计.第2版.北京:人民教育出版社,1978.262-271.
[46]屠其璞,丁裕国.气象应用概率统计学[M].北京:气象出版社,1984.196-206.
[47]谭冠日,严济远,朱瑞兆,应用气候.上海:上海科学技术出版社,1985.54-70.
[48]张学文,马力.熵气象学[M].北京:气象出版社,1992.154-190.
[49]马开玉,张耀存.陈星.现代应用统计学[M].北京:气象出版社,2004.177-200.
[50]朱求安,张万昌,余钧辉.基于GIS的空间插值方法研究[J].江西师范大学学报:自然科学版,2004,28(2):184.
[51]冯锦明,赵天保,张英娟.基于台站降水资料对不同空间内插方法的比较[J].气候与环境研究,2004,9(2):261-277.
[52]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值[J].地理学报,2002,57(1):47-56.
[53]杨晓霞,沈桐立,徐文金,等.最优插值客观分析方法[J].南京气象学院学报,1991,14(4):566-574.
[54]周锁铨,缪启龙,吴战平.山区平均气温细网格插值方法的比较[J].南京气象学院学报,1994,17(4):488-492.
[55]潘晓滨,魏绍远,马华平,等.逐次最优插值方案及其试验[J].气象科学,1996,16(1):30-39.
[56]李培军,张维峰,郭洪涛,等.气象资料三维化技术中的插值问题[J].气象科学,2005,25(6):617-623.
[57]李兆芹,益平,姚克敏.NCEP/NCAR再分析温度资料在农业气象中的应用可行性[J].南京气象学院学报,2004,27(6):420-427.
[58]Oliver M A,W ebster R.Kriging:a method of interpolation forgeographical information system[J].Int J Geographical Information Systems,1990,4(3):313-332.
[59]KarnieliA D.App lication of kriging technique to areal p recip itation mapp ing in A rizona[J].GeoJournal,1990,22(4):391-398.
[60]M ardiklsM G,Kalivas D P,Kollias V J.Comparison of interpolation methods for the p rediction of reference evapotransp irationan app lication in greece[J].W ater Resources M anagement,2005,19(33):251-278.
[61]Pardo-Iguzquiza E,D ow d P A.The second order stationary universal kriging model revisited[J].Mathematical Geology,199830(4):347-378.
[62]常文渊,戴新刚.地质统计学在气象要素场插值的实例研究[J].地球物理学报,2004,47(6):40-47.
[63]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值中的应用[J].地理研究,2001,20(4):446-452.
[64]潘永地,徐为根.沿海丘陵地区面雨量估算插值方法试验比较[J].气象科学,2005,25(2):124-132.
[65]李丽娟,王娟,李海滨.无定河流域降雨量空间变异性研究[J].地理研究,2002,21(4):434-440.
[66]冯仲科.空间数据的最佳内插法(Kriging法)及其在GIS中应用的构想[J].测绘科学,1995(3):22-26.
[67]刘峰.应用Kriging算法实现气象资料空间内插[J].气象科技,2004,32(2):110-115.
[68]尤卫红,夏欣健,赵宁坤.云南逐月雨量和气温的格点数据资料场建立[J].云南地理环境研究,2004,16(1):14-18.
[69]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值[J].地理学报,2002,57(1):47-56.
[70]庄立伟,王石立.东北地区逐日气象要素的空间插值方法应用研究[J].应用气象学报,2003,14(5):605-615.
[71]魏凤英,曹鸿兴.我国月降水和气温网格点资料的处理和分析[J].气象,1994,20(10):26-30.
[72]Dirks K N,Hay J E,Stow C D,et al.High-resolution studies of rainfall on Norfolk Sland.Part Ⅱ:Interpolation of rainfall data.JHydrol,1998,208:187-193.
[73]尚宗波,高凉,杨奠安.利用中国气候信息系统研究年降水量空间分布规律.生态学报,2001,21(5):689-694.
[74]薛根元,周锁铨,余越辉,等.复杂地形条件下气候变量空间分析方案研究.科技导报,2004,22(8):42-46.
[75]傅抱璞.地形和海拔高度对降水的影响.地理学报,1992,47:302-314.
[76]张连强,赵有中,欧阳宗继,等.运用地理因子推算山区局地降水量的研究.中国农业气象,1996,17(2):6-10.
[77]蒋忠信.山地降水垂直分布模式讨论.地理研究,1989,7(1):73-77.
[78]梁天刚,王兮之,戴若兰.多年平均降水资源空间变化模拟方法的研究.西北植物学报,2002,20(5):856-86.
[79]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值.地理学报,2002,(1):47-56.
[80]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值中的应用.地理研究,2001,(9):446-452.
[81]黄杏元,马劲松,汤勤.地理信息系统概论[M].北京:高等教育出版社,2001
[82]封志明,杨艳昭,丁晓强.气象要素空间插枝方法优化.地理研究,2004,23(3):357-364.
[83]杨昌军,陈渭民,罗玲,等.高斯权重法在温度场插值中的应用研究[J].南京气象学院学报1994,20(10):26-30
[84]傅抱璞,虞静明,卢其尧.山地气候资源与开发利用[M].南京:南京大学出版社,1996.203-232.
[85]朱会义,贾绍凤.降水信息空间插值的不确定性分析[J].地理科学进展,2004,23(2):34-42.
[86]杨昕,汤国安,王春,等.基于DEM的山区气温地形修正模型-以陕西省耀县为例[J].地理科学,2007,08(27):525-530.
[87]田武文,黄祖英,胡春娟.2006.西安市气候变暖与城市效应问题研究[J].应用气象学报,17(4):438-443.
[2]李世奎.中国农业灾害风险评价与对策[M]气象出版社.1999.
[3]http://www.xinhuanet.com/chinanews/2007-11/28/content_11787783.htm.
[4]Rajendra K.Pachauri.气候变化2007综合报告[M].2007.
[5]雷治平,刘引鸽,李录堂.陕西农业干旱灾害分析评估[J].陕西气象,2006,01(1):12-14.
[6]陈洪滨,范学花,董文杰.2005年极端天气与气候事件及其他相关事件的概要回顾.气候与环境研究,2006,11(2):236-244
[7]么枕生,丁裕国.气候统计[M].北京:气象出版社,1990,45-51.
[8]刘小宁.我国暴雨极端事件的气候变化特征[J].灾害学,1999,14(1):54-59
[9]Changnon S A,Roger A,Pielk Jr.,et al.Human factors explain the increased losses from weather and climate extremes[J].Bull.Of the Amer.Mete.Soci.2000,81(3):437-442.
[10]Houghton J T,Ding Y,Griggs J,et al.Climate Change2001:The Scientific Basis,Observed Climate Variability and Chang.Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change[M].Cambridge,UK:Cambridge University Press,2001:1-881.
[11]Easterling D R,Evans J L,YaGroisman P,etal.Observed variability and trends in extreme climate events:a brief review[J].Bull.oftheAmeri.Mete.Soci.2000,81(3):417-425.
[12]Karl T R,Kukla G,Razuvayev V N,et.al.Global Warming:Evidence for asymmetric diurnal temperature change[J].Geography.Res.Lett.1991,18:2253-2256
[13]Horton B.Geo graphical distribution of change at maximum and minimum temperatures,Atmos.Res,1995,37,101-117.
[14]Karl T R,Jones P D,Knight R W,et al.A new perspective on recent global warming:asymmetric trends of daily maximum and minimum temperature[J].Bull.Amer.Meteor.Soc.1993,74(6):1007-1023.
[15]Cooter E J,LeDuk S K.Recent frost data trends in the northern United States[J].Int.J.Climatology,1993,15:65-75.
[16]ZhaiPM,PanXH.Trends in temperature extremes during1951-1999 in china [J].Geophysical Research Letters,2003,30(17):1913-1916.
[17]Gruza G,Rankova E,Razuvaev V.Indicators of climate change for the Russian Federation[J].Clim.Change,1999,42:219-242
[18]Frith P,Alexander L V,Della-Marta P,et al.Observed coherent changes in climate extremes during the second half of the 20th century[J].Clim.Res.,2002,19:193-212.
[19]Manton M J,Della-Marta P M,Haylock M R,etal.Trend in extreme daily rainfall and temperature in southeast Asia and the South Pacific:1961-1998[J].Int.J.Climatol.,2001,21:269-284.
[20]Mearns and Katz R.W.Extreme high-temperature events in their probalities changes in mean temperature.Climate and Appl.Meteo,1984,23(2):1601-1613.
[21]Katz,R.W,B.G.Browns,Extreme events in a changing climate:Variability is more impotant than averages,Climatic Change,21,289-302,1992.
[22]Zhai Panmao,Pan Xiaohua.Change in extreme temperature and precipitation over Northern China during the second half of the20th century[J].Acta Geographica Sinica,2003,58(supp.1):1-10.
[翟盘茂,潘晓华.中国北方近50年温度和降水极端事件变化[J].地理学报,2003,58(增刊):1-10.
[23]Zhai Panmao,Ren Fumin.On changes ofChina'smaxmum andminimum temperatures in the recent 40 years[J].ActaMeteoro-logica Sinica,1997,55(4):418-429.
[翟盘茂,任福民.中国近四十年最高最低温度变化[J].气象学报,1997,55(4):418-429.
[24]Ren Fumin,Zhai Panmao.Study on changes ofChina's extremetemperature during 1951-1990[J].Scientia Atmospheric Sinica,1998,22(2):217-226.
[任福民,翟盘茂.1951-1990年中国极端温度变化分析[J].大气科学,1998,22(2):217-226.
[25]Zhai Panmao,ZouXuka.i Change in temperature and precipitati-on and their impacts on drought in China during 1951-2003[J].Advances in Climate ChangeResearch,2005,1(1):16-18.
[翟盘茂,邹旭恺.1951-2003年中国气温和降水变化及其对干旱的影响[J].气候变化研究进展,2005,1(1):16-18.
[21]Pan Xiaohua,Zhai Panmao.Analysis of surface air temperature extremum[J].Meteorological Monthly,2002,28(10):28-31.
[潘晓华,翟盘茂.气候 极端值的选取与分析[J].气象,2002,28(10):28-31.
[26]Tang Hongyu,ZhaiPanmao,Wang Zhenyu.On change in mean maximum temperature,minimum temperature and diurnal range in China during 1951-2002[J].Climatic and EnvironmentalRe-search,2005,10(4):728-735.
[唐红玉,翟盘茂,王振宇.1951-2002年中国平均最高、最低气温及日较差变化[J].气候与环境研究,2005,10(4):728-735.
[27]Wang Yawe,i Zhai Panmao,Tian Hua.Extreme high temperatures in Southern China in 2003 under the background of climate change[J].Meteorological Monthly,2006,32(10):27-33.
[王亚伟,翟盘茂,田华.近40年南方高温变化特征与2003年的高温事件[J].气象,2006,32(10):27-33.
[28]Ma Zhuguo.Variation of frostdays and its relationship to regional warming in Northern China[J].Acta Geographica Sinic,2003,58(supp.l):31-37.
马柱国.中国北方地区霜冻日的变化与区域增暖相互关系[J].地理学报,2003,58(增刊):31-37.
[29]Ma Zhuguo,Hua Lijuan,Ren Xiaobo.The extreme dry/wet events in Northern China during recent 100 years[J].Acta Geographical Sinic,2003,58(supp.l):69-74.
[马柱国,华丽娟,任小波.中国近代北方极端干湿事件的演变规律[J].地理学报,2003,58(增刊):69-74.
[30]Hua Lijuan,Ma Zhuguo,Zeng Zhaome.i The comparative analysis of the changes of extreme temperature and extreme diurnal temperature range of large cities and small towns in Eastern China[J].Scientia Atmospheric Sinica,2006,30(1):80-92.
[华丽娟,马柱国,曾昭美.中国东部地区大城市和小城镇极端温度及日较差变化对比分析[J].大气科学,2006,30(1):80-92.
[31]Yan Zhongwe,i YangCh.i Geographic patterns of extreme climate changes in China during 1951-1997[J].Climatic and Environmental Research,2000,5(3):265-270.
[严中伟,杨赤.近几十年中国极端气候变化格局[J].气候与环境研究,2000,5(3):265-270.
[32]Yan ZW,Yang C,Jones P.Influence of inhomogeneity on the estimation of mean and extreme temperature trends in Beijing and Shanghai[J].Advances in Atmospheric Sciences,2001,18(3):309-322.
[33]邓自旺,定裕国,陈业国.全球气候变化对长江三角洲极端高温事件概率的影响[J].南京气象学院学报,2000,23(1):42-47.
[34]HuRu ji,FanZili,WangYajun.Assessment about the impact of climate change on environment in Xin jiang since recent 50 years[J].AridLandGeo graphy,2001,24(2):97-103.
(胡汝骥,樊自立,王亚俊.近50a新疆气候变化对环境影响评估[J].干旱区地理,2001,24(2):97-103.
[35]施能,陈家其,屠其璞.中国近100年来4个年代际的气候变化特征[J].气象学报,1995,53(4):431-439.
[36]丁裕国,刘吉峰,张耀存.基于概率加权估计的中国极端气温时空分布模拟试验[J].大气科学,2004,28(5):770-782.
[37]苏志,李艳兰,涂方旭,等.广西冬季极端最低气温的概率分布模型选择及其极值和重现期计算[J].广西科学,2002,9(1):73-77.
[38]陈建昌,郭化文,魏牲生,等.用Jenkinson法推算山东年最大日雨量重现期值的初探[J].应用气象学报,1995(4):486-488.
[39]杨水泉.用极值分布计算黔南最大一日降水量的重现期[J].贵州气象,1997(6).
[40]程乾,张惠生,黄显金,等.吐鲁番一日最大降水量年极值频率分布[J].新疆气象,1998(1).
[41]郭兆夏,符昱,王军,等.陕西苹果主产区日最低(最高)气温的空间插值[J].陕西气象,2008(5):24-26.
[42]党安荣,贾海峰,易善桢.等著.ArcGIS 9 Desktop地理信息系统应用指南[M].北京:清华大学出版社,2007.
[43]Visual Basic程序设计教程,罗朝盛,人民邮电出版社,2005.
[44]唐启义,冯明光.实用统计分析及其DPS数据处理系统.北京:科学出版社,2002.1-647.
[45]林少宫.基础概率与数理统计.第2版.北京:人民教育出版社,1978.262-271.
[46]屠其璞,丁裕国.气象应用概率统计学[M].北京:气象出版社,1984.196-206.
[47]谭冠日,严济远,朱瑞兆,应用气候.上海:上海科学技术出版社,1985.54-70.
[48]张学文,马力.熵气象学[M].北京:气象出版社,1992.154-190.
[49]马开玉,张耀存.陈星.现代应用统计学[M].北京:气象出版社,2004.177-200.
[50]朱求安,张万昌,余钧辉.基于GIS的空间插值方法研究[J].江西师范大学学报:自然科学版,2004,28(2):184.
[51]冯锦明,赵天保,张英娟.基于台站降水资料对不同空间内插方法的比较[J].气候与环境研究,2004,9(2):261-277.
[52]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值[J].地理学报,2002,57(1):47-56.
[53]杨晓霞,沈桐立,徐文金,等.最优插值客观分析方法[J].南京气象学院学报,1991,14(4):566-574.
[54]周锁铨,缪启龙,吴战平.山区平均气温细网格插值方法的比较[J].南京气象学院学报,1994,17(4):488-492.
[55]潘晓滨,魏绍远,马华平,等.逐次最优插值方案及其试验[J].气象科学,1996,16(1):30-39.
[56]李培军,张维峰,郭洪涛,等.气象资料三维化技术中的插值问题[J].气象科学,2005,25(6):617-623.
[57]李兆芹,益平,姚克敏.NCEP/NCAR再分析温度资料在农业气象中的应用可行性[J].南京气象学院学报,2004,27(6):420-427.
[58]Oliver M A,W ebster R.Kriging:a method of interpolation forgeographical information system[J].Int J Geographical Information Systems,1990,4(3):313-332.
[59]KarnieliA D.App lication of kriging technique to areal p recip itation mapp ing in A rizona[J].GeoJournal,1990,22(4):391-398.
[60]M ardiklsM G,Kalivas D P,Kollias V J.Comparison of interpolation methods for the p rediction of reference evapotransp irationan app lication in greece[J].W ater Resources M anagement,2005,19(33):251-278.
[61]Pardo-Iguzquiza E,D ow d P A.The second order stationary universal kriging model revisited[J].Mathematical Geology,199830(4):347-378.
[62]常文渊,戴新刚.地质统计学在气象要素场插值的实例研究[J].地球物理学报,2004,47(6):40-47.
[63]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值中的应用[J].地理研究,2001,20(4):446-452.
[64]潘永地,徐为根.沿海丘陵地区面雨量估算插值方法试验比较[J].气象科学,2005,25(2):124-132.
[65]李丽娟,王娟,李海滨.无定河流域降雨量空间变异性研究[J].地理研究,2002,21(4):434-440.
[66]冯仲科.空间数据的最佳内插法(Kriging法)及其在GIS中应用的构想[J].测绘科学,1995(3):22-26.
[67]刘峰.应用Kriging算法实现气象资料空间内插[J].气象科技,2004,32(2):110-115.
[68]尤卫红,夏欣健,赵宁坤.云南逐月雨量和气温的格点数据资料场建立[J].云南地理环境研究,2004,16(1):14-18.
[69]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值[J].地理学报,2002,57(1):47-56.
[70]庄立伟,王石立.东北地区逐日气象要素的空间插值方法应用研究[J].应用气象学报,2003,14(5):605-615.
[71]魏凤英,曹鸿兴.我国月降水和气温网格点资料的处理和分析[J].气象,1994,20(10):26-30.
[72]Dirks K N,Hay J E,Stow C D,et al.High-resolution studies of rainfall on Norfolk Sland.Part Ⅱ:Interpolation of rainfall data.JHydrol,1998,208:187-193.
[73]尚宗波,高凉,杨奠安.利用中国气候信息系统研究年降水量空间分布规律.生态学报,2001,21(5):689-694.
[74]薛根元,周锁铨,余越辉,等.复杂地形条件下气候变量空间分析方案研究.科技导报,2004,22(8):42-46.
[75]傅抱璞.地形和海拔高度对降水的影响.地理学报,1992,47:302-314.
[76]张连强,赵有中,欧阳宗继,等.运用地理因子推算山区局地降水量的研究.中国农业气象,1996,17(2):6-10.
[77]蒋忠信.山地降水垂直分布模式讨论.地理研究,1989,7(1):73-77.
[78]梁天刚,王兮之,戴若兰.多年平均降水资源空间变化模拟方法的研究.西北植物学报,2002,20(5):856-86.
[79]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值.地理学报,2002,(1):47-56.
[80]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值中的应用.地理研究,2001,(9):446-452.
[81]黄杏元,马劲松,汤勤.地理信息系统概论[M].北京:高等教育出版社,2001
[82]封志明,杨艳昭,丁晓强.气象要素空间插枝方法优化.地理研究,2004,23(3):357-364.
[83]杨昌军,陈渭民,罗玲,等.高斯权重法在温度场插值中的应用研究[J].南京气象学院学报1994,20(10):26-30
[84]傅抱璞,虞静明,卢其尧.山地气候资源与开发利用[M].南京:南京大学出版社,1996.203-232.
[85]朱会义,贾绍凤.降水信息空间插值的不确定性分析[J].地理科学进展,2004,23(2):34-42.
[86]杨昕,汤国安,王春,等.基于DEM的山区气温地形修正模型-以陕西省耀县为例[J].地理科学,2007,08(27):525-530.
[87]田武文,黄祖英,胡春娟.2006.西安市气候变暖与城市效应问题研究[J].应用气象学报,17(4):438-443.