Spatial and temporal variation of land surface temperature in Taklamakan desert

doi:10.14088/j.cnki.issn0439-8114.2022.05.027

Abstract

Abstract: The surface temperature （LST） is one of the important climate variables and an important parameter of the ground-gas interaction of land surface processes. This paper used the observed data in 2017 in the hinterland of the Taklamakan desert to analyze the annual variation characteristics of surface temperature in this area. The results showed that the surface temperature in the desert hinterland had obvious seasonal changes, and the diurnal temperature fluctuated greatly. The annual average daily temperature highest value appeared in July, the lowest value appeared in January, and the day temperature variation characteristics of the four seasons were basically the same. The daily lowest temperature all appeared at 6 o’clock local time, and the highest temperature appeared at 13 o’clock. CLDAS was validated by the measured surface temperature of the applicability of the product in the desert, under the four kinds of different weather and the observation value of correlation coefficients were greater than 0.8, in clear weather, the correlation coefficient of 0.99, so using CLDAS products of the Taklamakan desert areas sunny spatial and temporal variation analysis and research, the surface temperature of the desert regions of the temperature change was highly affected by the changes in solar radiation, temperature difference between day and night 6 ℃ higher than around the desert oasis.

Key words: Taklimakan desert, land surface temperature, CLDAS

CLC Number:

P423.3

WANG Yuan-hong, WU Xin-ping, ALI Mamtimin, LIU Kai-lu, LIU Yong-qiang. Spatial and temporal variation of land surface temperature in Taklamakan desert[J]. HUBEI AGRICULTURAL SCIENCES, 2022, 61(5): 152-159.

References 31

[1]	VOOGT J A,OKE T R.Thermal remote sensing of urban climates[J]. Remote sensing of environment, 2003, 86(3): 370-384.
[2]	WILLIAM L C, ERIC A S, HARRY J C. Estimation of surface heat and moisture fluxes over a prairie grassland: 4. impact of satellite remote sensing of slow canopy variables on performance of a hybrid biosphere model[J]. Journal of geophysical research:Atmospheres, 1993, 98(D3):http://d.scholar.cnki.net/detail/SJCRKD_U/SJCR140625003754514979.
[3]	GARRATT J R.Observed screen (air) and GCM surface/screen temperatures:Implications for outgoing longwave fluxes at the surface[J]. Journal of climate, 1995, 8(5):1360-1368.
[4]	SHUJIANG M, TAPPER N.Land surface temperature and characteristics for a rain garden in soil moisture distribution Fitzroy Gardens, Melbourne[J]. Journal of southeast university, 2017(33): 355-361.
[5]	BAYUAJI L, WATANABE H, TONOOKA H, et al.Study on land surface temperature characteristics of hot mud eruption in East Java, Indonesia[J]. IIReSES, 2010, 6(1):390-401.
[6]	刘树华, 李新荣, 刘立超, 等. 陆面过程参数化模式的研究[J]. 中国沙漠, 2001, 21(3): 303-311.
[7]	房云龙, 孙菽芬, 李倩,等. 干旱区陆面过程模型参数优化和地气相互作用特征的模拟研究[J]. 大气科学, 2010, 34(2): 290-306.
[8]	刘野. 关键陆面参数的估算和优化及其在区域模拟中的应用[D]. 南京:南京大学, 2015.
[9]	李可相, 陈远, 谢刚,等. 贵阳市郊区耕地地表温度特征分析[J]. 农业与技术, 2020, 40(19): 101-103.
[10]	管延龙, 王让会, 李成,等. 基于MODIS数据的天山区域地表温度时空特征[J]. 应用生态学报, 2015, 26(3): 681-688.
[11]	何冬燕, 田红, 邓伟涛. 青藏高原不同季节地表温度变化特征分析[J]. 南京信息工程大学学报(自然科学版),2014,6(6): 558-569.
[12]	杨明, 李维亮, 刘煜, 等. 近50年我国西部地区气象要素的变化特征[J]. 应用气象学报, 2010, 21(2): 198-205.
[13]	王佳琳, 潘志华, 韩国琳, 等. 1961-2010年中国0cm地温变化特征及其与气温变化的关系[J]. 资源科学, 2016, 38(9): 1733-1741.
[14]	朱智, 师春香, 张涛, 等. 多种再分析地表温度资料在中国区域的适用性分析[J]. 冰川冻土, 2015, 37(3): 614-624.
[15]	秦艳慧, 吴通华, 李韧, 等. ERA-Interim地表温度资料在青藏高原多年冻土区的适用性[J]. 高原气象, 2015, 34(3): 666-675.
[16]	赵松乔, 夏训诚, 胡文康,等. 塔克拉玛干沙漠及其周缘地区的研究新进展[J]. 干旱区研究, 1993(3): 1-9.
[17]	房彦杰. 基于Fryberger方法的塔克拉玛干沙漠输沙势时空分布特征分析[D]. 成都:四川师范大学, 2015.
[18]	卫翔谦. 干旱半干旱区下垫面参数变化对东亚气候的敏感性研究[D].兰州:兰州大学, 2016.
[19]	霍文, 金莉莉, 王囝囝, 等. 沙漠陆面过程与沙漠小气候研究进展[J]. 沙漠与绿洲气象, 2016, 10(5): 87-94.
[20]	张强,张杰,乔娟,等. 我国干旱区深厚大气边界层与陆面热力过程的关系研究[J]. 中国科学:地球科学,2011,41(9):1365-1374.
[21]	崔彩霞, 杨青, 杨莲梅. MODIS资料用于塔克拉玛干沙漠地表温度计算方法初探[J]. 中国沙漠, 2003(5): 120-123.
[22]	张杰. 塔克拉玛干沙漠腹地沙丘表面温度特征初探[J]. 中国沙漠, 2003(5): 116-119.
[23]	黄洁, 金莉莉, 李振杰,等. 南疆沙漠腹地地温变化特征[J]. 干旱区资源与环境, 2013, 27(1): 148-153.
[24]	艾力·买买提明. 乌鲁木齐沙漠气象研究所已取得第一批沙尘暴追踪试验观测资料[J]. 沙漠与绿洲气象, 2007(2): 39.
[25]	CHEN Y, YANG K, ZHOU D, et al.Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length[J]. Journal of hydrometeorology, 2010, 11(4): 995-1006.
[26]	YANG K, KOIKE T, ISHIKAWA H, et al.Turbulent flux transfer over bare-soil surfaces: Characteristics and parameterization[J]. Journal of applied meteorology &climatology, 2008, 47(1):276-290.
[27]	李火青, 吴新萍, 买买提艾力·买买提依明,等. 利用FTIR和MODIS数据估算塔克拉玛干沙漠宽波段地表比辐射率[J]. 光谱学与光谱分析, 2016, 36(8): 2414-2419.
[28]	SHI C X, XIE Z H, QIAN H, et al.China land soil moisture EnKF data assimilation based on satellite remote sensing data[J]. Sci China earth Sci, 2011,Doi:10.1007/s11430-010-4160-3.
[29]	HAN S, LIU B C, SHI C X, et al.Evaluation of CLDAS and GLDAS datasets for near-surface air temperature over major land areas of China[J]. Sustainability,MDPI,2020, 12(10):1-19.
[30]	张超, 吴国周, 宋海清, 等. 基于CLDAS温度适宜度指标空间化方法[J]. 气象科技, 2017, 45(3): 555-560.
[31]	朱智,师春香,梁晓, 等. 基于高时空分辨率驱动数据的中国区域土壤温度模拟与评估[J]. 江苏农业科学, 2017, 45(5): 228-233.