Quantifying the Contribution of LUCC to Surface Energy Budget: A Case Study of Four Typical Cities in the Yellow River Basin in China

Chi, Qing; Zhou, Shenghui; Wang, Lijun; Zhu, Mengyao; Liu, Dandan; Tang, Weichao; Zhao, Xiao Dong; Xu, Suan; Ye, Siyu; Lee, Jay; Cui, Yaoping

doi:10.3390/atmos12111374

Cited by 6 publications

(6 citation statements)

References 44 publications

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“…Chi et al . (2021) selected four typical cities in the Yellow River Basin of China (Jinan, Zhengzhou, Lanzhou and Xining) to quantify the results of biogeophysical effects under land use and land cover change. By comparing the forced balance of energy intake and consumption between LUCC and four typical cities along the Yellow River Basin, the differences in energy budgets under different land use types are emphasized to address issues such as climate change.…”

Section: Discussionmentioning

confidence: 99%

Quantifying spatiotemporal variations and driving factors of the energy budget in the Loess Plateau

Gou

Liang

Yan

et al. 2022

Intl Journal of Climatology

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The land surface energy exchange indirectly describes the energy forcing effect of solar radiation on the atmospheric system. Exploring the exchange process is of great significance to understand the formation and change of weather and climate. Based on the ERA5 reanalysis data and a process‐based land surface model (the Ecosystem‐Atmosphere Simulation Scheme), this study analysed the spatiotemporal variations and influencing factors in the energy budget in the Loess Plateau (LP). The results showed that from 1990 to 2017, the average annual surface net radiation (Rn) and latent heat (LE) in the LP showed a decreasing trend. The Rn and LE presented an increased spatial pattern from northwest to southeast. On a monthly scale, the Grain for Green (GFG) project amplified the negative effect in the period of November to February and September, but diminished the negative effect in other months. Climate change contributed more to energy exchange than land cover change during the study period. Our results provide useful information for developing adaptive strategies for the region to adapt to global climate change.

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Section: Discussionmentioning

confidence: 99%

Quantifying spatiotemporal variations and driving factors of the energy budget in the Loess Plateau

Gou

Liang

Yan

et al. 2022

Intl Journal of Climatology

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“…Spatial distribution of LST and thermal environmental characteristics in the study area were primarily due to the combined effect of small regional topography and underlying surface properties. LULC has different physical properties, such as reflectivity, roughness, and humidity, which can affect the change in energy and material exchange between the ground and atmosphere, thereby altering the climate (Chi et al, 2021). The concept of source-sink is an important ecological process/pattern concept (Wu et al, 2022).…”

Section: Source-sink Effect On Lst In Xinjiangmentioning

confidence: 99%

“…It is multifaceted, and the complex geomorphic features of mountains and basins increase its spatial heterogeneity. In addition, owing to the obvious differences in heat budget processes, such as radiation, absorption, reflection, and transpiration, the effects of LST on the underlying surface and feedback mechanisms have significant spatial and temporal differentiation (Wang et al, 2015;Yu et al, 2020;Chi et al, 2021). Various meteorological factors participate in the energy exchange between the land surface and free atmosphere, and different ranges of the thermodynamic cycle in this process also affect the LST (Tian et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China

Zhang,

Cao,

Zhang

et al. 2024

J. Arid Land

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Land surface temperature (LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones (the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami (Tuha) Basin, and Pakakuna Mountain Group) using geographical detector (Geodetector) and geographically weighted regression (GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24°C/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09°C/10a in autumn, and showed a warming trend in other seasons. Digital elevation model (DEM), latitude, wind speed, precipitation, normalized difference vegetation index (NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover (LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.

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“…A good number of studies focused on LST trends in the landscapes [17]- [32], along with other trends like evapotranspiration [33,34], rainfall and vegetation [35], and water balance components like precipitation, snow cover and stream flows [34]. Studies of MODIS LST trends in urban areas or cities, especially larger in size, were also found [36]- [39]. In the urban/city, studies focused on UHI-urban heat island [40]- [43], SUHI-surface UHI [44]- [50], and urban expansion [51].…”

Section: A Modismentioning

confidence: 99%

Opportunities and Challenges of Spaceborne Sensors in Delineating Land Surface Temperature Trends: A Review

et al. 2023

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Understanding the land surface temperature (LST) trends is crucial for policymakers and stakeholders to develop adaptation and mitigation strategies suitable for a sustainable environment coping in the face of climate change. This article presents a systematic review of the studies related to delineating spaceborne sensor based LST trends, including information on the instruments and constellations of satellites (missions) that provide thermal infrared (TIR) and passive microwave (PMW) observations. About 99% of the studies used TIR, where 76% were MODIS (onboard Terra/Aqua) observations. Opportunities, challenges, and research gaps for using the TIR and PMW observations were also explored, with instruments onboard either polar-orbiting or geostationary satellites. We identified that calibrated dataset (e.g., processed, harmonized, and standardized) is extremely limited for each constellation, with multiple satellites and instruments, to make it fully useful for the entire mission period. A few problematic methodological concepts were identified, including using a few images in a longer time series. Using only a few images, acquired on different calendar months in different years, would not provide the true annual trends over the study period because they can be influenced by seasonal variations. To estimate the warming or cooling daytime, nighttime, or diurnal LST trends, the use of MODIS observations could be useful, even though it does not acquire images during the maximum or minimum temperature in a daily cycle. This article indicated further investigations into those research gaps and recommended directions to overcome most of these limitations.

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Quantifying the Contribution of LUCC to Surface Energy Budget: A Case Study of Four Typical Cities in the Yellow River Basin in China

Cited by 6 publications

References 44 publications

Quantifying spatiotemporal variations and driving factors of the energy budget in the Loess Plateau

Quantifying spatiotemporal variations and driving factors of the energy budget in the Loess Plateau

Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China

Opportunities and Challenges of Spaceborne Sensors in Delineating Land Surface Temperature Trends: A Review

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