Plateau Meteorology

Plateau Meteorology >

2020 , Vol. 39 >Issue 4: 706 - 718

DOI: https://doi.org/10.7522/j.issn.1000-0534.2020.00022

Temporal and Spatial Characteristics of Ground Surface Soil Heat Flux over the Qinghai-Tibetan Plateau

  • Cheng YANG ,
  • Tonghua WU ,
  • Jimin YAO ,
  • Ren LI ,
  • Changwei XIE ,
  • Guojie HU ,
  • Xiaofan ZHU ,
  • Junming HAO ,
  • Jie NI ,
  • Xiangfei LI ,
  • Wensi MA ,
  • Amin WEN ,
  • Chengpeng SHANG
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  • <sup>1.</sup>Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, State Key Laboratory of Cryospheric Sciences, Lanzhou 730000, Gansu, China;<sup>2.</sup>University of Chinese Academy of Science, Beijing 100049, China

Received date: 2019-11-18

  Online published: 2020-08-28

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Abstract

We have collected the measured data of 9 observation stations on the Qinghai-Tibetan Plateau.The measured data of these sites on the Qinghai-Tibetan Plateau were used to analyze the seasonal and daily variation characteristics of ground surface soil heat flux, and we discussed the reasons for the differences in the temporal characteristics of ground surface soil heat flux between stations.Then MODIS data (including the Terra Moderate Resolution Imaging Spectroradiometer vegetation indices version 6 data MOD13Q1 and the surface spectral reflectance of Terra Moderate Resolution Imaging Spectroradiometer bands 1 through 7 product MOD09CMG), daily land surface temperature dataset in Western China under all-sky condition with 1 km spatial resolution, and assimilation data (ITPCAS-SRad and ITPCAS-LRad) were applied to simulate the spatial distribution of ground surface soil heat flux over the Qinghai-Tibetan Plateau by the scheme Ma on 12 July and 16 October 2014, 1 January and 7 April 2015.The results shown that: The amplitude of ground surface soil heat flux varies with the season, the summer is larger, the winter is the smallest, and the amplitude between the stations is different from the underlying surface.The higher the coverage of the underlying surface, the smaller the amplitude; ground surface soil heat flux is positive in spring and summer and throughout the year, while ground surface soil heat flux in autumn and winter is negative.Ground surface soil heat flux is greater than 0, which means that the underground soil absorbs heat from the surface, otherwise, the underground soil releases heat.Ground surface soil heat flux on the the Qinghai-Tibetan Plateau shows an obvious daily variation curve of inverted U-shape, and its change of the night is relatively flat compared with the daytime.There is a significant seasonal difference in the duration of the daily variation curve of ground surface soil heat flux.The order of the four seasons is: summer > spring > autumn >winter.There is a good positive correlation between the spatial distribution characteristics of ground surface soil heat flux and that of land surface temperature on the the Qinghai-Tibetan Plateau.Station data shows that for every 1 °C increase in land surface temperature, ground surface soil heat flux will increase by 2 ~ 5 W·m-2.This study further deepens the understanding of ground surface soil heat flux over the Qinghai-Tibetan Plateau, in order to provide basis and help for the prediction of frozen soil evolution, accurate estimation of evapotranspiration and geogas interaction.

Key words： Ground surface soil; Qinghai-Tibetan Plat; the freezing-thawing; remote sensing-based; temporal and spatial

Cite this article

Cheng YANG , Tonghua WU , Jimin YAO , Ren LI , Changwei XIE , Guojie HU , Xiaofan ZHU , Junming HAO , Jie NI , Xiangfei LI , Wensi MA , Amin WEN , Chengpeng SHANG . Temporal and Spatial Characteristics of Ground Surface Soil Heat Flux over the Qinghai-Tibetan Plateau[J]. Plateau Meteorology, 2020 , 39(4) : 706 -718 . DOI: 10.7522/j.issn.1000-0534.2020.00022

References

[1]Amaty P M, Ma Y M, Cunbo H, al et, 2015.Recent trends (2003 -2013) of land surface heat fluxes on the southern side of the central Himalayas, Nepal[J].Journal of Geophysical Research: Atmospheres, 120, 11957-11970.DOI: 10.1002/2015jd023510.
[2]Bastiaanssen W G M, 2000.SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey[J].Journal of Hydrology, 229, 87-100.DOI: 10.1016/s0022-1694(99)00202-4.
[3]Carlson T N, Ripley D A, 1997.On the relation between NDVI, fractional vegetation cover, and leaf area index[J].Remote Sensing of Environment, 62, 241-252.DOI: 10.1016/s0034-4257(97)00104-1.
[4]Choudhury B J, Idso S B, Reginato R J, 1987.Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infrared-temperature based energy balance equation[J].Agricultural and Forest Meteorology, 39, 283-297.DOI: 10.1016/0168-1923(87)90021-9.
[5]Eugster W, Rouse W, Pielkesr R A, al et, 2000.Land-atmosphere energy exchange in arctic tundra and boreal forest: Available data and feedbacks to climate[J].Global Change Biology, 6(1): 84-115.DOI: 10.1046/j.1365-2486.2000.06015.x.
[6]Jackson R D, Moran M S, Gay L W, al et, 1987.Evaluating Evaporation from field crops using airborne radiometry and ground-based meteorological data[J].Irrigation Science, 8 (2): 81-90.DOI: 10.1007/BF00259473.
[7]Liang S, 2001.Narrowband to broadband conversions of land surface albedo I Algorithms[J].Remote Sensing of Environment, 76 (2), 213-238.DOI: 10.1016/s0034-4257(00)00205-4.
[8]Moran M S, Jackson R D, Raymond L H, al et, 1989.Mapping surface energy balance components by combining Landsat thermatic mapper and ground-based meteorological data[J].Remote Sensing of Environment, 30, 77-87.DOI: 10.1016/0034-4257(89)90049-7.
[9]Ma Y M, 2006.Determination of regional surface heat fluxes over heterogeneous landscapes by integrating satellite remote sensing with boundary layer observations[D].The Netherlands: Wageningen University, 1-181.
[10]Ma Y M, Ishikawa H, Tsukamoto O, al et, 2003.Regionalization of surface fluxes over heterogeneous landscape of the Tibetanan Plateau by using satellite remote sensing data[J].Journal of the Meteorological Society of Japan, 81(2): 277-293.DOI: 10.2151/jmsj.81.277.
[11]Osterkamp T, 1987.Freezing and thawing of soils and permafrost containing unfrozen water or brine[J].Water Resources Research, 23(12): 2279-2285.DOI: 10.1029/wr023i012p02279.
[12]Qi J G, Chehbouni A, Huete A, al et, 1994.A modified soil adjusted vegetation index[J].Remote Sensing of Environment, 48 (2), 119-126.DOI: 10.1016/0034-4257(94)90134-1.
[13]Su Z B, 2002.The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes[J].Hydrology and Earth System Sciences, 6(1), 85-100..
[14]Wu T H, Lin Z, Ren L, al et, 2013.Recent ground surface warming and its effects on permafrost on the central Qinghai-Tibetan Plateau[J].International Journal of Climatology, 33: 920-930.DOI: 10.1002/joc.3479.
[15]Tanaka K, Tamagawa I, Ishikawa H, al et, 2003.Surface energy budget and closure of the eastern Tibetanan Plateau during the GAME-Tibetan IOP 1998[J].Journal of Hydrology, 283: 169-183.
[16]Tsukamoto O, Sahashi K, Wang J M, 1995.Heat budget and evaptranspiration at an oasis surface surrounded by desert[J].Journal of the Meteorological Society of Japan, 73(5): 925-935..
[17]Yang C, Wu T H, Wang J M, al et, 2019.Estimating surface soil heat flux in permafrost regions using remote sensing-based models on the Northern Qinghai-Tibetanan Plateau under clear-sky conditions[J].Remote Sensing, 11 (4), 416.DOI: 10.3390/rs11040416.
[18]Yang C, Wu T H, Yao J M, al et, 2020.An assessment of using remote sensing-based models to estimate ground surface soil heat flux on the Tibetanan Plateau during the freeze-thaw process[J].Remote Sensing, 12, 501..
[19]Yang K, Wang J M, 2008.A temperature prediction-correction method for estimating surface soil heat flux from soil temperature and moisture data[J].Science in China (Series D: Earth Sciences), 05: 99-107.
[20]Yang K, He J, Tang W J, al et, 2010.On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetanan Plateau[J].Agricultural and Forest Meteorology, 150(1), 38-46.DOI: 10.1016/j.agrformet.2009. 08.004.
[21]Yao J M, Zhao L, Gu L L, al et, 2011.The surface energy budget in the permafrost region of the Tibetanan Plateau[J].Atmospheric Research, 102(4): 394-407.DOI: 10.1016/j.atmosres.2011. 09.001.
[22]Zhang X D, Zhou J, Frank-Michael G, al et, 2019.A method based on temporal component decomposition for estimating 1-km all-weather land surface temperature by merging satellite thermal infrared and passive microwave observations[J].IEEE Transactions on Geoscience and Remote Sensing, 57: 4670-4691..
[23]Zhong L, Ma Y M, Hu Z Y, al et, 2019.Estimation of hourly land surface heat fluxes over the Tibetanan Plateau[J].Atmospheric Chemistry and Physics, 19: 5529-5541..
[24]Zhou J, Zhang X D, Zhan W F, al et, 2017.A thermal sampling depth correction method for land surface temperature estimation from satellite passive microwave observation over barren land[J].IEEE Transactions on Geoscience and Remote Sensing, 55: 4743-4756..
[25]程国栋, 赵林, 2000.青藏高原开发中的冻土问题[J].第四纪研究, 20(6): 521-531．
[26]段丽君, 段安民, 胡文婷, 等, 2017.2014 年夏季青藏高原狮泉河与林芝降水低频振荡及陆—气过程日变化特征[J].大气科学, 41 (4): 767-783.
[27]谷良雷, 2011.青藏高原季节冻土区和多年冻土区地表能量收支和蒸散发对比研究[D].兰州: 中国科学院寒区旱区环境与工程研究所, 1-136.
[28]郝雅婕, 邓巧玲, 王艳霞, 等, 2019.元江干热河谷稀树灌丛土壤热通量特征[J].西北林学院学报, 34(5): 23-28.DOI: 10.3969/j.issn.1001-7431.2019.05.04.
[29]何杰, 2010.中国区域高时空分辨率地面气象要素数据集的建立[D].北京: 中国科学院青藏高原研究所, 1-78.
[30]胡隐樵, 高由禧, 王介民, 等, 1994.黑河实验(HEIFE)的一些研究成果[J].高原气象, 13(3): 225-236.
[31]季国良, 1999.青藏高原能量收支观测实验的新进展[J].高原气象, 18(3): 333-340．
[32]季国良, 1985.青藏高原主体的大气透明度特征[J].高原气象, 4(2): 122-129.
[33]季国良, 吕兰芝, 1995.藏北高原太阳辐射能收支的季节变化[J].太阳能学报, 16(4): 340-346.
[34]李黎, 吕世华, 范广洲, 2019.夏季青藏高原地表能量变化对高原低涡生成的影响分析[J].高原气象, 38(6): 1172-1180.DOI: 10.7.522 /j.issn.1000-0534.2018.00154.
[35]李明财, 罗天祥, 郭军, 等, 2008.藏东南高山林线冷杉原始林土壤热通量[J].山地学报, 26(4): 490-495.DOI: 10.3969/j.issn.1008-2786.2008.04.017.
[36]李宏毅, 肖子牛, 朱玉祥, 2018.藏东南地区草地下垫面湍流通量和辐射平衡各分量的变化特征[J].高原气象, 37(4): 923-935.DOI: 10.7252/j.issn.1000-0534.2017.2007.
[37]刘宏谊, 杨兴国, 张强, 等, 2009.敦煌戈壁冬夏季地表辐射与能量平衡特征对比研究[J].中国沙漠, 29(3): 558-565.
[38]马伟强, 马耀明, 胡泽勇, 等, 2005a.藏北高原地区辐射收支和季节变化与卫星遥感的对比分析[J].干旱区资源与环境, 1: 110-116.DOI: CNKI: SUN: GHZH.0.2005-01-021.
[39]马伟强, 马耀明, 李茂善, 等, 2005b.藏北高原地区地表辐射出支和能量平衡的季节变化[J].冰川冻土, 27(5): 673-679.http: //.
[40]沈志宝, 成天涛, 王可丽, 2002.青藏高原地面-对流层系统的能量收支[J].高原气象, 21(6): 20-25.
[41]覃志豪, 李文娟, 徐斌, 等, 2004.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感, 15(3): 28-32.
[42]陶诗言, 陈联寿, 徐祥德, 等, 1998.第二次靑藏高原大气科学试验理论硏究进展(一) [M].北京: 气象出版社, 1-348.
[43]吴国雄, 2004.我国青藏高原气候动力学研究的近期进展[J].第四纪研究, 24(1): 1-9.
[44]翁笃鸣, 高歌, 2001.利用卫星资料试作青藏高原地表净辐射场的气候反演[J].气象科学, 21 (2): 162-168.DOI: 10.3969/j.issn.1009-0827.2001.02.005.
[45]肖瑶, 赵林, 李韧, 等, 2011.青藏高原腹地高原多年冻土区能量收支各分量的季节变化特征[J].冰川冻土, 33(5): 79-85.
[46]杨成, 姚济敏, 赵林, 等, 2016.藏北高原多年冻土区地表反照率时空变化特征[J].冰川冻土, 38(6): 1518-1528.
[47]杨丽薇, 高晓清, 惠小英, 等, 2017．青藏高原中部聂荣亚寒带半干旱草地近地层湍流特征研究[J].高原气象, 36(4): 875-885.DOI: 10.7522 /j.issn.1000-0534.2016.00089.
[48]叶笃正, 高由禧, 等, 1979.青藏高原气象学[M].北京: 科学出版社, 30-55.
[49]章基嘉, 朱抱真, 朱福康, 等, 1988.青藏高原气象学进展[M].北京: 科学出版社, 92-123.
[50]仲雷, 马耀明, 马伟强, 等, 2006.珠峰北坡地区近地层大气湍流与地气能量交换特征[J].地球科学进展, 12: 84-94.
[51]仲雷, 马耀明, 马伟强, 等, 2011.西藏中部“一江两河”地区地表通量的卫星遥感估算[J].冰川冻土, 33(2): 309-317.
[52]朱志鹍, 马耀明, 胡泽勇, 等, 2015.青藏高原那曲高寒草甸生态系统CO2净交换及其影响因子[J].高原气象, 34(5): 1217-1223.DOI: 10.7522/j.issn.1000-0534.2014.00135.
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