基于多源数据集估算缺资料地区地表净辐射及其时空变化特征
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摘要
本文以黄河源区为例,利用ITPCAS气象要素驱动数据集和GLASS地表反照率数据集,基于Penman-Monteith公式估算缺资料地区1979-2015年逐日地表净辐射(Rn),用GIS空间分析技术与Mann-Kendall趋势分析方法揭示其时间动态特征与空间演变规律。结果表明:1)对比ITPCAS气象要素驱动数据集和气象站数据估算的Rn,其相关系数均在0.98以上,均方根误差处于1.29～1.77之间;2)黄河源区年和四季Rn均呈下降趋势,每10年均降幅为-0.067MJ·m~(-2)·d~(-1),秋季降幅最小,春、冬降幅最大;黄河源区Rn年内呈单峰型,最大值出现在5月(14.31MJ·m~(-2)·d~(-1)),最小值出现在12月(3.34MJ·m~(-2)·d~(-1));3)年和各季节Rn值及变化趋势的空间分布相似;年平均Rn的大部分地区(91.6%)呈下降趋势,其中冬季Rn下降最明显,秋季Rn下降最不明显;4)黄河源区Rn在4 000～4 500m的区域内最大,而在4 500m以上最小;除了秋季Rn在3 500～4 000m区域外,其余季节在所有DEM分区中皆呈现下降趋势。
By using ITPCAS Meteorological Forcing Dataset and GLASS surface albedo dataset,PenmanMonteith formula was used to estimate daily surface net radiation(Rn)in ungauged region during 1979-2015,the source region of the Yellow River is taken as a case study.GIS spatial analysis technology and Mann-Kendall trend analysis method are used to reveal regional Rnspatiotemporal dynamic characteristics.The results show that 1)By comparing Rnestimated by ITPCAS Forcing Dataset with Rnestimated by weather station data,the correlation coefficients of all sites are above 0.98,with the values of root mean square error between 1.29～1.77;2)Annual/seasonal Rnvalues decline visibly with a fluctuant process in the source region of the Yellow River,with the changing rate of the annual Rnreaching 0.067MJ·m~(-2)·d~(-1) every 10 years.The maximum downtrend(-0.075MJ·m~(-2)·d~(-1) every 10years)is in spring and winter,while the minimum downtrend(-0.039MJ·m~(-2)·d~(-1) every 10years)is in autumn.Regional mean monthly Rnhas a single peak with the maximum value(14.31MJ·m~(-2)·d~(-1))in May and the minimum value(3.34MJ·m~(-2)·d~(-1))in December;3)The spatial distribution of Rnvalue and annual/seasonal variation trend is similar.The annual mean Rnin the most areas(91.6%)displays a downward trend.In the seasonal scale,the decline of Rnis most obvious in winter,while in autumn it is least obvious;4)The maximum values of Rnare in the 4 000～4 500 marea,and the minimum values are in a region of more than4 500 m.Except the region of 3 500～4 000 min autumn,the rest areas in all seasons showe a downward trend.
By using ITPCAS Meteorological Forcing Dataset and GLASS surface albedo dataset,PenmanMonteith formula was used to estimate daily surface net radiation(Rn)in ungauged region during 1979-2015,the source region of the Yellow River is taken as a case study.GIS spatial analysis technology and Mann-Kendall trend analysis method are used to reveal regional Rnspatiotemporal dynamic characteristics.The results show that 1)By comparing Rnestimated by ITPCAS Forcing Dataset with Rnestimated by weather station data,the correlation coefficients of all sites are above 0.98,with the values of root mean square error between 1.29～1.77;2)Annual/seasonal Rnvalues decline visibly with a fluctuant process in the source region of the Yellow River,with the changing rate of the annual Rnreaching 0.067MJ·m~(-2)·d~(-1) every 10 years.The maximum downtrend(-0.075MJ·m~(-2)·d~(-1) every 10years)is in spring and winter,while the minimum downtrend(-0.039MJ·m~(-2)·d~(-1) every 10years)is in autumn.Regional mean monthly Rnhas a single peak with the maximum value(14.31MJ·m~(-2)·d~(-1))in May and the minimum value(3.34MJ·m~(-2)·d~(-1))in December;3)The spatial distribution of Rnvalue and annual/seasonal variation trend is similar.The annual mean Rnin the most areas(91.6%)displays a downward trend.In the seasonal scale,the decline of Rnis most obvious in winter,while in autumn it is least obvious;4)The maximum values of Rnare in the 4 000～4 500 marea,and the minimum values are in a region of more than4 500 m.Except the region of 3 500～4 000 min autumn,the rest areas in all seasons showe a downward trend.
引文
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[2]高扬子,何洪林,张黎,等.近50年中国地表净辐射的时空变化特征分析[J].地球信息科学学报,2013,15(1):1-10.GAO Yangzi,HE Honglin,ZHANG Li,et al.Spatiotemporal variation characteristics of surface net radiation in China over the past 50years[J].Journal of Geo-Information Science,2013,15(1):1-10.
[3]陈征,胡德勇,蒋卫国,等.基于GLASS数据估算中国陆表净辐射及其空间分布分析[J].地理研究,2016,35(1):25-36.CHEN Zheng,HU Deyong,JIANG Weiguo,et al.Land surface radiation budget parameterization and spatial analysis over China using GLASS data[J].Geopraphical Research,2016,35(1),25-36.
[4]ALADOS I,FOYO-MORENO I,OLMO F J,et al.Relationship between net radiation and solar radiation for semi-arid shrub-land[J].Agricultural and Forest Meteorology,2003,116(3/4):221-227.
[5]WANG Kaicun,LIANG Shunlin.An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation,vegetation index,temperature,and soil moisture[J].Journal of Hydrometeorology,2008,9(4):712-727.
[6]LLASAT M C,SNYDER R I.Data error effects on net radiation and evapotranspiration estimation[J].Agricultural and Forest Meteorology,1998,91(3/4):209-221.
[7]武荣盛,马耀明.青藏高原不同地区辐射特征对比分析[J].高原气象,2010,29(2):251-259.WU Rongsheng,MA Yaoming.Comparative analyses on radiation characteristics in different areas over the Tibetan Plateau[J].Plateau Meteorology,2010,29(2):251-259.
[8]OZGOREN M,BILGILI M,SAHIN B.Estimation of global solar radiation using ANN over Turkey[J].Expert Systems with Applications, 2012, 39(5):5043-5051.
[9] HOU Jiangtao,JIA Gensuo,ZHAO Tianbao,et al.Satellite-based estimation of daily average net radiation under clear-sky conditions[J].Advances in Atmospheric Sciences,2014,31(3):705-720.
[10]FAUSTO M A,MACHADO N G,NOGUEIRA J DE S,et al.Net radiation estimated by remote sensing in Cerrado areas in the Upper Paraguay River Basin[J].Journal of Applied Remote Sensing, 2014, 8(1):083541.
[11]BISHT G,Bras R L.Estimation of net radiation from the MODIS data under all sky conditions Southern Great Plains case study[J].Remote Sensing of Environment,2010,114(7):1522-1534.
[12]蓝永超,鲁承阳,喇承芳,等.黄河源区气候向暖湿转变的观测事实及其水文响应[J].冰川冻土,2013,35(4):920-928.LAN Yongchao,LU Chengyang,LA Chengfang,et al.The fact of climate shift to warm-humid in the source regions of the Yellow River and its hydrologic response[J].Journal of Glaciology and Geocryology,2013,35(4):920-928.
[13] ZHANG Xiaotong,LIANG Shunlin, WANG Kaichun,et al.Analysis of global land surface shortwave broadband albedo from multiple data sources[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2010,3(3):296-305.
[14]LIU Qiang,WANG Lizhao,QU Ying,et al.Preliminary evaluation of the long-term GLASS albedo product[J].International Journal of Digital Earth,2013,6(S1):69-95.
[15]ALLEN R G,PEREIRA L S,RAES D,et al.Crop evapotranspiration-guidelines for computing crop water requirements[M].FAO Irrigation and Drainage Paper56.Food and Agriculture Organization of the United Nations,Rome,1998,300,6541.
[16]叶晶,刘辉志,李万彪,等.利用MODIS数据直接估算晴空区干旱与半干旱地表净辐射通量[J].北京大学学报(自然科学版),2010,46(6):942-950.YE Jing,LIU Huizhi,LI Wanbiao,et al.Estimation of the net radiation over arid and semiarid areas only using MODIS data for clear sky days[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2010,46(6):942-950.
[17]JIMENEZ-MUNOZ J C,SOBRINO J A,MATTAR C.Recent trends in solar energy and net radiation at global scale[J].Ecological Modelling,2012,228(1):59-65.
[18]LIANG F,XIA X.Long-term trends in solar radiation and the associated climatic factors over China for 1961-2000[J]. Annales Geophysicae,2005,23(7):2425-2432.
[19]李培基.青藏高原积雪对全球变暖的响应[J].地理学报,1996,51(3):260-265.LI Peiji.Response of Tibetan snow cover to global warming[J].Acta Geographica Sinica,1996,51(3):260-265.