复杂山区地表温度模拟及影响——以内蒙古大青山为例

doi:10.13866/j.azr.2024.05.05

干旱区研究 ›› 2024, Vol. 41 ›› Issue (5): 765-775.doi: 10.13866/j.azr.2024.05.05

复杂山区地表温度模拟及影响——以内蒙古大青山为例

赵立超¹^,²(), 张成福¹^,²(), 贺帅¹^,², 苗林¹^,², 冯霜¹^,², 潘思涵³

1.内蒙古农业大学沙漠治理学院，内蒙古呼和浩特 010018
2.荒漠生态系统保护与修复国家林业和草原局重点实验室，内蒙古呼和浩特 010019
3.巴彦淖尔市林业和草原局，内蒙古巴彦淖尔 015000

收稿日期:2023-12-01 修回日期:2024-01-31 出版日期:2024-05-15 发布日期:2024-05-29
通讯作者: 张成福. E-mail: chengfuzhang@imau.edu.cn
作者简介:赵立超（1998-），男，硕士研究生，主要从事水土保持研究. E-mail: zhaolichao@emails.imau.edu.cn
基金资助:
自治区自然科学基金(RZ2200001285)

Simulation of land surface temperature in complex mountainous terrain and the influence of environmental factors: A case study in Daqingshan, Inner Mongolia

ZHAO Lichao¹^,²(), ZHANG Chengfu¹^,²(), HE Shuai¹^,², MIAO Lin¹^,², FENG Shuang¹^,², PAN Sihan³

1. College of Desert Management, Inner Mongolia Agricultural University, Hohhot 010018, Inner Mongolia, China
2. Key Laboratory of Desert Ecosystem Protection and Restoration, National Forestry and Grassland Administration, Hohhot 010019, Inner Mongolia, China
3. Bayannaoer Forestry and Grassland Bureau, Bayannaoer 015000, Inner Mongolia, China

Received:2023-12-01 Revised:2024-01-31 Online:2024-05-15 Published:2024-05-29

摘要/Abstract

摘要：

地表温度（LST）是影响植物分布和生态系统过程的重要因素。本研究利用天气研究与预测模式（WRF）模拟大青山保护区的高时空分辨率LST，通过气象站点观测值和MODIS LST值对比验证模拟结果的准确性，并通过综合影响因素和单一影响因素分析LST与环境因子之间的关系。综合影响因素分析是基于区域模拟LST和区域环境因子进行的分析；单一影响因素分析是首先固定其他环境因子，然后分析LST和单一环境因子的关系。结果表明：模拟值与3个站点观测值相关系数均超过0.97（P<0.001），与MODIS LST空间相关性为0.73（P<0.05），表明WRF在山区有很好的实用性。经综合影响因素分析，年均LST与高程的相关性最大（R>0.97），与2 m气温和2 m水汽混合比次之（R>0.8），与植被覆盖度和坡度较小（R>0.3），其他因素影响微弱。经单一影响因素分析，在春夏秋冬4个季节，随高程升高LST下降速率分别为0.83 K·(100m)^-1、0.79 K·(100m)^-1、0.80 K·(100m)^-1、0.32 K·(100m)^-1；坡度每增加10°，LST在春夏秋冬分别升高-0.05 K、0.17 K、-0.14 K、0.02 K；植被覆盖度每增加10%，LST在夏冬两季分别升高0.31 K、1.41 K，其他季节则没影响；坡向对4个季节平均LST的影响均为南>西南>东南>西>东>西北>东北>北；年均LST与2 m水汽混合比呈对数关系，与2 m气温呈指数关系。研究结果可为大青山自然保护区管理提供基础数据，也为山地研究提供可借鉴的方法。

关键词: WRF模式, 地表温度, 环境因子, 内蒙古大青山

Abstract:

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.

Key words: WRF model, land surface temperature, environmental factors, Daqingshan of Inner Mongolia

赵立超, 张成福, 贺帅, 苗林, 冯霜, 潘思涵. 复杂山区地表温度模拟及影响——以内蒙古大青山为例[J]. 干旱区研究, 2024, 41(5): 765-775.

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.

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参数化方案	方案名称
微物理过程	Thompson^[19]
积云参数化	Tiedtke^[20]
边界层	YSU^[21]
表面层	MM5^[22]
陆面过程	CLM4^[23]
长短波辐射	RRTMG^[24]

特征变量	设定值
高程/m	1400~1600
坡度/（°）	0~20
坡向/（°）	157.5~202.5（南）
植被覆盖/%	10~30
土地利用	草地

地表温度	2 m气温	2 m水汽混合比	植被覆盖度	高程	坡度
春季平均	0.97^**	0.60^**	-0.33^**	-0.97^**	-0.29^**
夏季平均	0.96^**	0.65^**	-0.27^**	-0.92^**	-0.25^**
秋季平均	0.98^**	0.70^**	-0.25^**	-0.98^**	-0.32^**
冬季平均	0.12^**	0.03^**	0.08^**	-0.62^**	-0.27^**
年平均	0.87^**	0.81^**	-0.32^**	-0.97^**	-0.30^**

复杂山区地表温度模拟及影响——以内蒙古大青山为例

Simulation of land surface temperature in complex mountainous terrain and the influence of environmental factors: A case study in Daqingshan, Inner Mongolia

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