scholarly journals Improvement of land surface temperature simulation over the Tibetan Plateau and the associated impact on circulation in East Asia

2015 ◽  
Vol 17 (2) ◽  
pp. 162-168 ◽  
Author(s):  
Haifeng Zhuo ◽  
Yimin Liu ◽  
Jiming Jin
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
East Asia ◽  
Land Surface Temperature ◽  
Land Surface ◽  
The Tibetan Plateau

scholarly journals Lake area monitoring based on land surface temperature in the Tibetan Plateau from 2000 to 2018

2020 ◽  
Vol 15 (8) ◽  
pp. 084033 ◽  
Author(s):  
Wei Zhao ◽  
Donghong Xiong ◽  
Fengping Wen ◽  
Xiaodan Wang
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
The Tibetan Plateau ◽  
Lake Area ◽  
Area Monitoring

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

scholarly journals Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 376 ◽  
Author(s):  
Yuanyuan Hu ◽  
Lei Zhong ◽  
Yaoming Ma ◽  
Mijun Zou ◽  
Kepiao Xu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Geostationary Satellite ◽  
The Tibetan Plateau

scholarly journals Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): Organization and Experimental design

2021 ◽  
Author(s):  
Yongkang Xue ◽  
Tandong Yao ◽  
Aaron A. Boone ◽  
Ismaila Diallo ◽  
Ye Liu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Yangtze River Basin ◽  
Seasonal Prediction ◽  
High Mountain ◽  
The Tibetan Plateau

Abstract. Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

scholarly journals Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11040
Author(s):  
Xiaogang Ma ◽  
Jiming Jin ◽  
Lingjing Zhu ◽  
Jian Liu
Keyword(s):  
Thermal Conductivity ◽  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Soil Layer ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Soil Thermal Conductivity ◽  
Community Land Model

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0–10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.

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