Spatiotemporal impact of soil moisture on air temperature across the Tibet Plateau

Fan, Keke; Zhang, Qiang; Singh, Vijay P.; Sun, Peng; Song, Changchun; Zhu, Xiudi; Yu, Hui; Shen, Zexi

doi:10.1016/j.scitotenv.2018.08.399

Cited by 38 publications

(15 citation statements)

References 32 publications

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“…Soil moisture (SM) plays a critical role in terrestrial hydrological cycle and land‐atmosphere energy interactions (Dorigo & De Jeu, 2016; Lakshmi et al, 2004; Mohanty et al, 2017; Robinson et al, 2008; Rowell, 1994; Seneviratne et al, 2011; Walker & Rowntree, 1977). Meanwhile, it is significant to acquire accurate SM information, which could be effectively applied in the agricultural related researches, such as drought and flood warning, crop growth analysis, and yield estimation (Fan et al, 2019; Mohanty, 2013; Wang et al, 2016; Zhang et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Downscaling Satellite Retrieved Soil Moisture Using Regression Tree‐Based Machine Learning Algorithms Over Southwest France

Liu

Xia

Yao

et al. 2020

Earth and Space Science

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Satellite retrieved soil moisture (SM) shows great potential in hydrological, meteorological, ecological, and agricultural applications, while the coarse resolution limits its utilization in regional scale. The regression tree-based machine learning algorithms reveal promising capability in SM downscaling. However, it lacks systematic study dedicated to intercomparisons of algorithms to explicitly illuminate their characteristics. In this study, comparisons are made to systematically evaluate performances of classification and regression tree (CART), random forest (RF), gradient boost decision tree (GBDT), and extreme gradient boost (XGB) in Soil Moisture Active Passive (SMAP) SM downscaling in southwest France. The results show that the four algorithms downscaled SM are capable of capturing spatial distribution features of the original SMAP SM. The downscaled regions with favorable accuracy are mostly situated in the dominant Mediterranean climate zone with moderate vegetation coverage and mild topography variation. The best results are obtained by GBDT in grassland with R value of 0.77 and ubRMSE value of 0.04 m 3 /m 3. The RF and XGB also achieve good performances. On the whole, the GBDT approach is robust and reliable, which could downscale SM with superior correlation and smaller bias than the others. Besides, it achieves higher accuracy than the original SMAP in grassland and shrubland. The feature importance index of each explainable variable fluctuates regularly among different seasons and models. This study proves the outstanding performance of GBDT in SMAP SM downscaling and is expected to act as a valuable reference for studies focusing on SM scale conversion algorithms.

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Section: Introductionmentioning

confidence: 99%

Downscaling Satellite Retrieved Soil Moisture Using Regression Tree‐Based Machine Learning Algorithms Over Southwest France

Liu

Xia

Yao

et al. 2020

Earth and Space Science

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“…During sunny days, the CABL height over continents generally attains its peak altitude of 1-3 km in the afternoon (Von and Teixeira 2013;Wang and Wang 2016). Observations carried out at various geographical locations and numerical atmospheric modelling studies have shown the influence of land-surface conditions (soil moisture, soil temperature) and energy balance terms (shortwave, longwave, and net radiative fluxes; sensible and latent heat fluxes) on atmospheric temperature, instability, and ABL height (Driedonks 1982;Garratt 1992;Kuwagata et al 1994;Svensson et al 2011;Pal and Haeffelin 2015;Dang et al 2016;Davy 2018;Anjos and Lopes 2019;Fan et al 2019;Liu and Pu 2019;Pal and Lee, 2019;Davis et al 2020). Discerning the effects of these parameters in the time evolution of the ABL height is essential for understanding the physical processes and the modelling of ABL development (Svensson et al 2011;Pal and Haeffelin 2015;Davis et al 2020), but is complex since a majority of these parameters are nonlinearly coupled.…”

Section: Introductionmentioning

confidence: 99%

“…The morning rise in sensible heat flux is mainly controlled by the absorption of downwelling shortwave flux at the surface and the corresponding increase in soil skin temperature. The soil skin temperature at a given instant is the result of a balance between the net radiative flux, vertical heat flux (sensible and latent heat flux), and ground heat flux, while the near-surface air temperature depends on the soil skin temperature and sensible heat flux (Fan et al 2019;Liu and Pu 2019). In addition to the above, over coastal regions, the advection of marine air can significantly reduce the air temperature (Wang et al 2017;Wu et al 2018;Reddy et al 2020).…”

Section: Introductionmentioning

confidence: 99%

The Convective-Atmospheric-Boundary-Layer Height and its dependence upon Meteorological Variables At a Tropical Coastal Station during Onshore and Offshore Flows

Davis

Rajeev

Namboodiri

2021

Boundary-Layer Meteorol

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The height of the atmospheric boundary layer (ABL) plays a crucial role in the vertical transport of energy, moisture, and pollutants from the surface. We investigate the development of the convective ABL (CABL) height over a tropical coastal station and quantify its variations with the shortwave radiative flux, near-surface air temperature (T air ), soil skin temperature, soil moisture content, lower tropospheric thermal structure, and virtual potential temperature lapse rate (VPLR) during onshore and offshore flows, based on multi-year (2012-2017) observations carried out using a microwave radiometer profiler and in situ probes at Thumba (8.5°N, 77°E), located in the south-west of Indian Peninsula. The maximum CABL height increases linearly with the VPLR at the rate of 140 to 200 m per °C km −1 (correlation coefficient of 0.82 to 0.92) during different seasons. The delayed onset of daytime onshore flow results in a greater CABL height as continental conditions persist longer, allowing more CABL growth, whereas the earlier arrival of the onshore flow leads to early development of a thermal internal boundary layer with a lower CABL height. When offshore flow prevails, the CABL develops like the continental CABL, with a peak CABL height greater than that during onshore flow by about 300 m. The onset of onshore flow lowers the daytime increase in T air by about 2 °C. Such quantifications for distinct flow conditions are very sparse over tropical coastal regions and would be useful for understanding coastal air-pollution dispersal as well as validation and improvements in numerical modelling of the CABL under different wind conditions.

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“…Sustainable ecological restoration and protection at different scales have been widely accepted and implemented as an important means to deal with environmental degradation (Bai et al, 2020). Soil moisture is the factor that has the greatest impact on the above-ground biomass of alpine grasslands in permafrost regions of the Qinghai-Tibet Plateau (Fan et al, 2019). Through remote sensing quantitative inversion methods, large-scale longsequence data can be obtained to facilitate macroscopic and dy- namic monitoring of soil moisture changes (Dong et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Distribution Characteristics of Soil Moisture in the Three Rivers Headwaters Region, China

Cao¹,

Jin²

2021

J ENVIRON INFORM LET

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The change of soil moisture has significant influence on the surface energy distribution and evapotranspiration process and causes the climatic environment changes. It is thus urgent to detect soil moisture facing climate change problems. Based on apparent thermal inertia method, the GLDAS soil moisture of the layer in 0 ~ 10 cm, 10 ~ 40 cm, 40 ~ 100 cm, 100 ~ 200 cm under the ground surface are proceeded for downscaling and the monthly soil moisture are obtained by combination of MODIS data. Statistics of precipitation and temperature of 13 meteorological stations in the Three River Headwater Region (TRHR) are collected to analyze the correlation between soil moisture change and temperature and precipitation. The correlation between soil moisture and evapotranspiration (ET) are analyzed by using the surface energy balance system model to calculate the average evapotranspiration in the study area. The result indicated that (1) Apparent thermal inertia (ATI) is positively correlated with soil depths in the four layers below the surface and has the best correlation with 0 ~ 10 cm soil moisture. Soil moisture increases with soil depth. Soil moisture is lowest under 0 ~ 10 cm depth while highest under 10 ~ 40 cm on average. (2) In terms of spatial distribution of TRHR, soil moisture is higher in the northwest and southeast, but lower in the southwest and northeast than average. The temporal variation of the soil moisture in one year was high in summer and low in winter, and the average annual soil moisture increased with time. (3) Soil moisture is negatively correlated with temperature and positively correlated with precipitation. There is a positive correlation between soil moisture and evapotranspiration. The linear regression coefficient of determination R 2 is 0.8489.

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Spatiotemporal impact of soil moisture on air temperature across the Tibet Plateau

Cited by 38 publications

References 32 publications

Downscaling Satellite Retrieved Soil Moisture Using Regression Tree‐Based Machine Learning Algorithms Over Southwest France

Downscaling Satellite Retrieved Soil Moisture Using Regression Tree‐Based Machine Learning Algorithms Over Southwest France

The Convective-Atmospheric-Boundary-Layer Height and its dependence upon Meteorological Variables At a Tropical Coastal Station during Onshore and Offshore Flows

Distribution Characteristics of Soil Moisture in the Three Rivers Headwaters Region, China

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