scholarly journals Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4200 ◽  
Author(s):  
Anyuan Li ◽  
Caichu Xia ◽  
Chunyan Bao ◽  
Guoan Yin
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Ground Surface ◽  
Tibet Plateau ◽  
Active Layer Thickness ◽  
Permafrost Region ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Warm Bias ◽  
Qinghai Tibet Plateau

It is essential to monitor the ground temperature over large areas to understand and predict the effects of climate change on permafrost due to its rapid warming on the Qinghai-Tibet Plateau (QTP). Land surface temperature (LST) is an important parameter for the energy budget of permafrost environments. Moderate Resolution Imaging Spectroradiometer (MODIS) LST products are especially valuable for detecting permafrost thermal dynamics across the QTP. This study presents a comparison of MODIS-LST values with in situ near-surface air temperature (Ta), and ground surface temperature (GST) obtained from 2014 to 2016 at five sites in Beiluhe basin, a representative permafrost region on the QTP. Furthermore, the performance of the thermal permafrost model forced by MODIS-LSTs was studied. Averaged LSTs are found to strongly correlated with Ta and GST with R2 values being around 0.9. There is a significant warm bias (4.43–4.67 °C) between averaged LST and Ta, and a slight warm bias (0.67–2.66 °C) between averaged LST and GST. This study indicates that averaged MODIS-LST is supposed to be a useful data source for permafrost monitoring. The modeled ground temperatures and active-layer thickness have a good agreement with the measurements, with a difference of less than 1.0 °C and 0.4 m, respectively.

scholarly journals The ERA5-Land soil temperature bias in permafrost regions

2020 ◽  
Vol 14 (8) ◽  
pp. 2581-2595 ◽  
Author(s):  
Bin Cao ◽  
Stephan Gruber ◽  
Donghai Zheng ◽  
Xin Li
Keyword(s):  
Soil Temperature ◽  
Land Surface ◽  
Soil Column ◽  
Land Surface Model ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Warm Bias ◽  
Temperature Bias ◽  
Permafrost Regions

Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (<1.89 m) permafrost area. This is thought to be due in part to the shallow soil column and coarse vertical discretization of the land surface model and to warmer simulated soil. The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with maximum snow height. A review of the ERA5L snow parameterization and a simulation example both point to a low bias in ERA5L snow density as a possible cause for the warm bias in soil temperature. The apparent disagreement of station-based and areal evaluation techniques highlights challenges in our ability to test permafrost simulation models. While global reanalyses are important drivers for permafrost simulation, we conclude that ERA5L soil data are not well suited for informing permafrost research and decision making directly. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.

scholarly journals PIC v1.3: comprehensive R package for computing permafrost indices with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau

2018 ◽  
Vol 11 (6) ◽  
pp. 2475-2491 ◽  
Author(s):  
Lihui Luo ◽  
Zhongqiong Zhang ◽  
Wei Ma ◽  
Shuhua Yi ◽  
Yanli Zhuang
Keyword(s):  
Ground Surface ◽  
R Package ◽  
Frozen Soil ◽  
Tibet Plateau ◽  
Trend Test ◽  
Active Layer Thickness ◽  
Permafrost Degradation ◽  
Spatial Trends ◽  
The Impact ◽  
Qinghai Tibet Plateau

Abstract. An R package was developed for computing permafrost indices (PIC v1.3) that integrates meteorological observations, gridded meteorological datasets, soil databases, and field measurements to compute the factors or indices of permafrost and seasonal frozen soil. At present, 16 temperature- and depth-related indices are integrated into the PIC v1.3 R package to estimate the possible trends of frozen soil in the Qinghai–Tibet Plateau (QTP). These indices include the mean annual air temperature (MAAT), mean annual ground surface temperature (MAGST), mean annual ground temperature (MAGT), seasonal thawing–freezing n factor (nt∕nf), thawing–freezing degree-days for air and the ground surface (DDTa∕DDTs∕DDFa∕DDFs), temperature at the top of the permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freeze depth. PIC v1.3 supports two computational modes, namely the stations and regional calculations that enable statistical analysis and intuitive visualization of the time series and spatial simulations. Datasets of 52 weather stations and a central region of the QTP were prepared and simulated to evaluate the temporal–spatial trends of permafrost with the climate. More than 10 statistical methods and a sequential Mann–Kendall trend test were adopted to evaluate these indices in stations, and spatial methods were adopted to assess the spatial trends. Multiple visual methods were used to display the temporal and spatial variability of the stations and region. Simulation results show extensive permafrost degradation in the QTP, and the temporal–spatial trends of the permafrost conditions in the QTP are close to those of previous studies. The transparency and repeatability of the PIC v1.3 package and its data can be used and extended to assess the impact of climate change on permafrost.

scholarly journals Urban Morphological Controls on Surface Thermal Dynamics: A Comparative Assessment of Major European Cities with a Focus on Athens, Greece

Climate ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 131
Author(s):  
Ilias Agathangelidis ◽  
Constantinos Cartalis ◽  
Mat Santamouris
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Negative Relationship ◽  
Urban Surface ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Surface Parameters ◽  
European Cities ◽  
The City

Variations in urban form lead to the development of distinctive intra-urban surface thermal patterns. Previous assessment of the relation between urban structure and satellite-based Land Surface Temperature (LST) has generally been limited to single-city cases. Here, examining 25 European cities (June–August 2017), we estimated the statistical association between surface parameters—the impervious fraction (λimp), the building fraction (λb), and the building height (H)—and the neighborhood scale (1000 × 1000 m) LST variations, as captured by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Correlation analysis, multiple linear regression, and spatial regression were used. As expected, λimp had a consistent positive influence on LSTs. In contrast, the relation of LST with λb and H was generally weaker or negative in the daytime, whereas at night it shifted to a robust positive effect. In particular, daytime LSTs of densely built, high-rise European districts tended to have lower values. This was especially the case for the city of Athens, Greece, where a more focused analysis was conducted, using further surface parameters and the Local Climate Zone (LCZ) scheme. For the urban core of the city, the canyon aspect ratio H/W had a statistically significant (p <0.01) negative relationship with LST by day (Spearman’s rho = −0.68) and positive during nighttime (rho = 0.45). The prevailing intra-urban surface thermal variability in Athens was well reproduced by a 5-day numerical experiment using the meteorological Weather Research and Forecasting Model (WRF) model and a modified urban parameterization scheme. Although the simulation resulted in some systematic errors, the overall accuracy of the model was adequate, regarding the surface temperature (RMSE = 2.4 K) and the near-surface air temperature (RMSE = 1.7 K) estimations.

scholarly journals Numerical Mapping and Modeling Permafrost Thermal Dynamics across the Qinghai-Tibet Engineering Corridor, China Integrated with Remote Sensing

2018 ◽  
Vol 10 (12) ◽  
pp. 2069 ◽  
Author(s):  
Guoan Yin ◽  
Hao Zheng ◽  
Fujun Niu ◽  
Jing Luo ◽  
Zhanju Lin ◽  
...  
Keyword(s):  
Air Temperature ◽  
Field Measurements ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Region ◽  
Infrastructure Development ◽  
High Mountains ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Discontinuous Permafrost

Permafrost thermal conditions across the Qinghai–Tibet Engineering Corridor (QTEC) is of growing interest due to infrastructure development. Most modeling of the permafrost thermal regime has been conducted at coarser spatial resolution, which is not suitable for engineering construction in a warming climate. Here we model the spatial permafrost thermal dynamics across the QTEC from the 2010 to the 2060 using the ground thermal model. Soil properties are defined based on field measurements and ecosystem types. The climate forcing datasets are synthesized from MODIS-LST products and the reanalysis product of near-surface air temperature. The climate projections are based on long-term observations of air temperature across the QTEC. The comparison of model results to field measurements demonstrates a satisfactory agreement for the purpose of permafrost thermal modeling. The results indicate a discontinuous permafrost distribution in the QTEC. Mean annual ground temperatures (MAGT) are lowest (<−2.0 °C) for the high mountains. In most upland plains, MAGTs range from −2.0 °C to 0 °C. For high mountains, the average active-layer thickness (ALT) is less than 2.0 m, while the river valley features ALT of more than 4.0 m. For upland plains, the modeled ALTs generally range from 3.0 m to 4.0 m. The simulated results for the future 50 years suggest that 12.0%~20.2% of the permafrost region will be involved in degradation, with an MAGT increase of 0.4 °C~2.3 °C, and the ALT increasing by 0.4 m~7.3 m. The results of this study are useful for the infrastructure development, although there are still several improvements in detailed forcing datasets and a locally realistic model.

Numerical Simulation of the Change of Gas Hydrate Layer of Qinghai-Tibet Plateau in Global Warming Situation

2011 ◽  
Vol 335-336 ◽  
pp. 302-307
Author(s):  
Yan Chao Qiao ◽  
Zi Qi Guo ◽  
Bao Gang Zhang ◽  
Yao Lin Shi
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Gas Hydrate ◽  
Heat Conduction Equation ◽  
Ground Surface ◽  
Tibet Plateau ◽  
Ground Surface Temperature ◽  
Hydrate Layer ◽  
Major Factors ◽  
Qinghai Tibet Plateau

Using finite element method, we solve the heat conduction equation. In our calculation, we use 0.02 and 0.052 °C/year as temperature rising rate (Gt) in order to get the change of gas hydrate layer of Qinghai-Tibet Plateau (QTP) in global warming situation. Our calculation’s major results are as follows: Our calculation demonstrates the gas hydrate layer’s surface temperature is one of the major factors which influence the thickness of gas hydrate layer (TGH). When Gt=0.02 and 0.052°C/year, the changes of TGH are almost same. The lower the ground surface temperature (GST), the more change of TGH. Therefore we need to monitor the Qiangtang plateau which has low surface temperature and good organic material.

Sign in / Sign up

Export Citation Format

Share Document