Simulation of land surface temperature in complex mountainous terrain and the influence of environmental factors: A case study in Daqingshan, Inner Mongolia
Received date: 2023-12-01
Revised date: 2024-01-31
Online published: 2024-05-29
This study aimed to spatially and temporally characterize not only land surface temperature (LST) in the complex mountainous terrain of Daqingshan, Inner Mongolia but also the environmental factors affecting it. We used the Weather Research and Forecasting Mode (WRF) used to obtain LST data with high temporal and spatial resolution and analyze the variation of mountain influencing factors. The accuracy of the WRF simulated LST (WRF LST) was verified by the observation values of meteorological stations and MODIS LST values, and the relationship between LST and environmental factors was analyzed by the method of comprehensive impact factor analysis and the method of single impact factor analysis. The comprehensive impact factor analysis is based on regional WRF LST and regional environmental factors. Single impact factor analysis achieves the relationship between WRF LST and single environmental factors by fixing other environmental factors. The results revealed that the correlation coefficients between the simulated and observed values were >0.97 (P<0.001) and the spatial correlation with MODIS LST was 0.73 (P<0.05), indicating that WRF has good practicability in mountainous areas. After comprehensive impact factor analysis, it was found the annual WRF LST had the greatest correlation with elevation (R>0.97), followed by temperature at 2 m and water/air mixing ratio at 2 m (R>0.8), vegetation coverage and slope (R>0.3), and other factors. By single impact factor analysis, LST decrease rate with elevation was 0.83 K·(100m)-1, 0.79 K·(100m)-1, 0.80 K·(100m)-1 and 0.32 K·(100m)-1 in spring, summer, autumn and winter, and it increased by -0.05 K, 0.17 K, -0.14 K, and 0.02 K for every 10° increase in slope in spring, summer fall winter, respectively. LST also increased for every 10% increase in vegetation cover by 0.31 K, 1.41 K in summer and winter, and was not correlated with fall. The slope direction and average LST for the four seasons were south>southwest>southeast>west>east>northwest>northeast>north. The 2 m water-air mixing ratio increased logarithmically with LST, while the 2 m air temperature increased exponentially with LST. This study demonstrated that the WRF model can be used to simulate the spatial and temporal distribution of LST in mountainous terrain and analyze the LST relationship in complex mountain environments.
ZHAO Lichao , ZHANG Chengfu , HE Shuai , MIAO Lin , FENG Shuang , PAN Sihan . Simulation of land surface temperature in complex mountainous terrain and the influence of environmental factors: A case study in Daqingshan, Inner Mongolia[J]. Arid Zone Research, 2024 , 41(5) : 765 -775 . DOI: 10.13866/j.azr.2024.05.05
[1] | 宋海燕. CLM5. 0对东北地区地表温度的数值模拟及评估[J]. 哈尔滨师范大学自然科学学报, 2021, 37(2): 90-94. |
[Song Haiyan. Numerical simulation and evaluation of surface temperature in Northeast China by CLM5.0[J]. Natural Science Journal of Harbin Normal University, 2021, 37(2): 90-94.] | |
[2] | Wu J, Xia L, Awange J, et al. Downscaling land surface temperature: A framework based on geographically and temporally neural network weighted autoregressive model with spatio-temporal fused scaling factors[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 187(5): 259-272. |
[3] | Hrisko J, Ramamurthy P, Yu Y, et al. Urban air temperature model using GOES-16 LST and a diurnal regressive neural network algorithm[J]. Remote Sensing of Environment, 2020, 237(1): 111495. |
[4] | Dandan W, Yunhao C, Leiqiu H, et al. Modeling the angular effect of MODIS LST in urban areas: A case study of toulouse, France[J]. Remote Sensing of Environment, 2021, 257(2): 8-9 |
[5] | Westermann S, Langer M, Boike J. Spatial and temporal variations of summer surface temperatures of high-arctic tundra on Svalbard—Implications for MODIS LST based permafrost monitoring[J]. Remote Sensing of Environment: An Interdisciplinary Journal, 2011, 115(3): 908-922. |
[6] | Jimenez-Munoz J C, Sobrino J A, Sobrino, et al. Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(10): 1840-1843. |
[7] | Sen S C, Zhi X C, Qi W C, et al. A simple retrieval method of land surface temperature from AMSR-E passive microwave data—A case study over southern China during the strong snow disaster of 2008[J]. International Journal of Applied Earth Observations and Geoinformation, 2010, 13(1): 140-151. |
[8] | Efstathiou G, Zoumakis N, Melas D, et al. Sensitivity of WRF to boundary layer parameterizations in simulating a heavy rainfall event using different microphysical schemes. Effect on large-scale processes[J]. Atmospheric Research, 2013, 5(4): 132-133. |
[9] | 屠妮妮, 何光碧, 张利红. WRF模式中不同积云对流参数化方案对比试验[J]. 高原山地气象研究, 2011, 31(2): 18-25. |
[Tu Nini, He Guangbi, Zhang Lihong. Simulation test on the effects of various cumulus parameterization schemes in WRF model[J]. Plateau and Mountain Meteorological Research, 2011, 31(2): 18-25.] | |
[10] | Jin J, Miller L N, Schlegel N. Sensitivity study of four land surface schemes in the WRF model[J]. Advances in Meteorology, 2010, 1(1): 185-194. |
[11] | Wen X, Lu S, Jin J. Integrating remote sensing data with WRF for improved simulations of oasis effects on local weather processes over an arid region in northwestern China[J]. Journal of Hydrometeorology, 2012, 13(2): 573-587. |
[12] | 王雪莹, 谷黄河, 代斌, 等. 不同水平分辨率区域气候模式对青藏高原气候特征模拟[J]. 干旱区研究, 2024, 41(3): 363-374. |
[Wang Xueying, Gu Huanghe, Dai Bin, et al. Simulation of climate characteristics in the Tibetan Plateau by regional climate models at different horizontal resolutions[J]. Arid Zone Research, 2024, 41(3): 363-374.] | |
[13] | 张祎. 长江流域土地利用/覆被变化对地表温度的影响[D]. 武汉: 中国地质大学, 2018. |
[Zhang Yi. The Influence of LUCC on the Land Surface Temperature in Yangtze River Basin[D]. Wuhan: China University of Geosciences, 2018.] | |
[14] | Cao Q, Yu D, Georgescu M, et al. Impacts of land use and land cover change on regional climate: A case study in the agro-pastoral transitional zone of China[J]. Environmental Research Letters, 2016, 10(12): 124025. |
[15] | 王明娜, 韩哲, 张庆云. 21世纪初中国北方半干旱区土地利用变化对地表温度的影响[J]. 气候与环境研究, 2016, 21(1): 65-77. |
[Wang Mingna, Han Zhe, Zhang Qingyun. Impact of land use and cover change in the semi-arid regions of China on the temperature in the early 21st century[J]. Climatic and Environmental Research, 2016, 21(1): 65-77.] | |
[16] | 杜皓阳, 胡琪, 张弛, 等. 哈密绿洲土地利用变化对区域环境的影响[J]. 干旱区研究, 2018, 35(3): 568-578. |
[Du Haoyang, Hu Qi, Zhang Chi, et al. Effects of land use/cover change on regional environment in the Hami Oasis[J]. Arid Zone Research, 2018, 35(3): 568-578.] | |
[17] | 肖尧, 马明国, 闻建光, 等. 复杂地表地表温度反演研究进展[J]. 遥感技术与应用, 2021, 36(1): 33-43. |
[Xiao Yao, Ma Mingguo, Wen Jianguang, et al. Progress in land surface temperature retrieval over complex surface[J]. Remote Sensing Technology and Application, 2021, 36(1): 33-43.] | |
[18] | 胡尔查, 王晓江, 铁牛, 等. 内蒙古大青山国家级自然保护区植被归一化指数时空变化及其与环境因子的关系[J]. 生态学报, 2022, 42(14): 5945-5955. |
[Hu Ercha, Wang Xiaojang, Tie Niu, et al. Spatio-temporal variation of NDVI and influencing factors in the Daqing Mountain National Nature Reserve, lnner Mongolia[J]. Acta Ecologica Sinica, 2022, 42(14): 5945-5955.] | |
[19] | Thompson, Gregory, Field, et al. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization[J]. Monthly Weather Review, 2008, 136, (12): 5095-5115. |
[20] | Tiedtke M. A comprehensive mass flux scheme for cumulus parameterization in large-scale models[J]. Monthly Weather Review, 1989, 117(8): 1779-1800. |
[21] | Hong Y S, Noh Y, Dudhia J. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. American Meteorological Society, 2006, 134(9): 2318-2341. |
[22] | Jiménez P, Dudhia J, González-Rouco J, et al. A revised scheme for the WRF surface layer formulation[J]. Monthly Weather Review, 2012, 140(3): 898-918. |
[23] | Lawrence, David M, Oleson, et al. Parameterization improvements and functional and structural advances in version 4 of the community land model[J]. Journal of Advances in Modeling Earth Systems, 2011, 3(3): 1-27. |
[24] | Iacono M J, Delamere J S, Mlawer E J, et al. Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models[J]. Journal of Geophysical Research: Atmospheres, 2008, 113(13): 11-19 |
[25] | 王澄海, 孙超. 一个基于WRF+CLM区域气候模式(WRFC)的建立及初步试验[J]. 高原气象, 2013, 32(6): 1626-1637. |
[Wang Chenghai, Sun Chao. Design and preliminary test of the regional climate model (WRFC) based on coupling WRF 3.2 and CLM 4.0[J]. Plateau Meteorology, 2013, 32(6): 1626-1637.] | |
[26] | 张小培, 银燕. 复杂地形地区WRF模式四种边界层参数化方案的评估[J]. 大气科学学报, 2013, 36(1): 68-76. |
[Zhang Xiaopei, Yin Yan. Evaluation of the four PBL schemes in WRF model over complex topographic areas[J]. Transactions of Atmospheric Sciences, 2013, 36(1): 68-76.] | |
[27] | Wan Z, Dozier J. A generalized split-window algorithm for retrieving land-surface temperature from space[J]. IEEE Transactions on Geoscience & Remote Sensing, 1996, 34(4): 892-905. |
[28] | 曹明奎, 李克让. 陆地生态系统与气候相互作用的研究进展[J]. 地球科学进展, 2000, 15(4): 446-452. |
[Cao Mingkui, Li Kerang. Perspective on terrestrial ecosystem-climate interaction[J]. Advances in Earth Science, 2000, 15(4): 446-452.] | |
[29] | 刘祯, 曾燕, 邱新法, 等. 基于MODIS LST的0 cm地温空间扩展研究[J]. 气象科学, 2014, 34(1): 10-16. |
[Liu Zhen, Zeng Yan, Qiu Xinfa, et al. Spatialization of 0 cm ground temperature based on MODIS LST[J]. Journal of the Meteorological Sciences, 2014, 34(1): 10-16.] | |
[30] | 任余龙, 李振朝, 蒋俊霞, 等. 三种土壤导热率模型对中国北方地表温度的模拟[J]. 高原气象, 2022, 41(5): 1315-1324. |
[Ren Yulong, Li Zhenchao, Jiang Junxia, et al. Simulation of land surface temperature in northern China by three soil thermal conductivity models[J]. Plateau Meteorology, 2022, 41(5): 1315-1324.] | |
[31] | 李斌, 王慧敏, 秦明周, 等. NDVI、NDMI与地表温度关系的对比研究[J]. 地理科学进展, 2017, 36(5): 585-596. |
[Li Bin, Wang Huimin, Qin Mingzhou, et al. Comparative study on the correlations between NDVI, NDMI and LST[J]. Progress in Geography, 2017, 36(5): 585-596.] | |
[32] | 罗瑶, 彭文甫, 董永波, 等. 基于地理探测器下的川西高原地表温度空间格局及影响因子分析——以西昌市为例[J]. 干旱区地理, 2020, 43(3): 738-749. |
[Luo Yao, Peng Wenfu, Dong Yongbo, et al. Geographical exploration of the spatial pattern of the surface temperature and its influencing factors in western Sichuan Plateau: A case of Xichang City[J]. Arid Land Geography, 2020, 43(3): 738-749.] | |
[33] | 焦欢, 丁忆, 段松江, 等. 三峡库区植被覆盖度与地表温度的空间耦合季节分异研究[J]. 生态与农村环境学报, 2022, 38(12): 1604-1612. |
[Jiao Huan, Ding Yi, Duan Songjiang, et al. Study on spatial coupling seasonal differentiation of vegetation coverage and land surface temperature in the three gorges reservoir area[J]. Journal of Ecology and Rural Environment, 2022, 38(12): 1604-1612.] |
/
〈 | 〉 |