scholarly journals Impact of frozen soil processes on soil thermal characteristics at seasonal to decadal scales over the Tibetan Plateau and North China

2020 ◽  
Author(s):  
Qian Li ◽  
Yongkang Xue ◽  
Ye Liu
Keyword(s):  
Tibetan Plateau ◽  
Soil Temperature ◽  
Temperature Profile ◽  
Land Surface ◽  
North China ◽  
Thermal Characteristics ◽  
Frozen Soil ◽  
The Tibetan Plateau ◽  
Soil Processes ◽  
Freeze Thaw

Abstract. Frozen soil processes are of great importance in controlling surface water and energy balances during the cold season and in cold regions. Over recent decades, considerable frozen soil degradation and surface soil warming have been reported over the Tibetan Plateau and North China, but most land surface models have difficulty in capturing the freeze-thaw cycle and few validations focus on the effects of frozen soil processes on soil thermal characteristics in these regions. This paper addresses these issues by introducing a physically more realistic and computationally more stable and efficient frozen soil module (FSM) into a land surface model—the third-generation Simplified Simple Biosphere model (SSiB3-FSM). To overcome the difficulties in achieving stable numerical solutions for frozen soil, a new semi-implicit scheme and a physics-based freezing-thawing scheme were applied to solve the governing equations. The performance of this model, as well as the effects of frozen soil process on the soil temperature profile and soil thermal characteristics, were investigated over the Tibetan Plateau and North China using observation and models. Results show that the SSiB3 model with the FSM produces more realistic soil temperature profile and its seasonal variation than that without FSM during the freezing and thawing periods. The freezing process in soil delays the winter cooling, while the thawing process delays the summer warming. The time lag and amplitude damping of temperature become more pronounced with increasing depth. These processes are well simulated in SSiB3-FSM. The freeze-thaw processes could increase the simulated phase lag days and land memory at different soil depths, as well as the soil memory change with the soil thickness. Furthermore, compared with observations, SSiB3-FSM produces a realistic change of maximum frozen soil depth at decadal scales. This study shows the soil thermal characteristics at seasonal to decadal scales over frozen ground can be greatly improved in SSiB3-FSM and SSiB3-FSM can be used as an effective model for TP and NC simulation during cold reasons.

scholarly journals Impact of frozen soil processes on soil thermal characteristics at seasonal to decadal scales over the Tibetan Plateau and North China

2021 ◽  
Vol 25 (4) ◽  
pp. 2089-2107
Author(s):  
Qian Li ◽  
Yongkang Xue ◽  
Ye Liu
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
North China ◽  
Thermal Characteristics ◽  
Cold Season ◽  
Frozen Soil ◽  
The Tibetan Plateau ◽  
Soil Processes ◽  
Frozen Ground ◽  
Freeze Thaw

Abstract. Frozen soil processes are of great importance in controlling surface water and energy balances during the cold season and in cold regions. Over recent decades, considerable frozen soil degradation and surface soil warming have been reported over the Tibetan Plateau and North China, but most land surface models have difficulty in capturing the freeze–thaw cycle, and few validations focus on the effects of frozen soil processes on soil thermal characteristics in these regions. This paper addresses these issues by introducing a physically more realistic and computationally more stable and efficient frozen soil module (FSM) into a land surface model – the third-generation Simplified Simple Biosphere Model (SSiB3-FSM). To overcome the difficulties in achieving stable numerical solutions for frozen soil, a new semi-implicit scheme and a physics-based freezing–thawing scheme were applied to solve the governing equations. The performance of this model as well as the effects of frozen soil process on the soil temperature profile and soil thermal characteristics were investigated over the Tibetan Plateau and North China using observation sites from the China Meteorological Administration and models from 1981 to 2005. Results show that the SSiB3 model with the FSM produces a more realistic soil temperature profile and its seasonal variation than that without FSM during the freezing and thawing periods. The freezing process in soil delays the winter cooling, while the thawing process delays the summer warming. The time lag and amplitude damping of temperature become more pronounced with increasing depth. These processes are well simulated in SSiB3-FSM. The freeze–thaw processes could increase the simulated phase lag days and land memory at different soil depths as well as the soil memory change with the soil thickness. Furthermore, compared with observations, SSiB3-FSM produces a realistic change in maximum frozen soil depth at decadal scales. This study shows that the soil thermal characteristics at seasonal to decadal scales over frozen ground can be greatly improved in SSiB3-FSM, and SSiB3-FSM can be used as an effective model for TP and NC simulation during cold season. Overall, this study could help understand the vertical soil thermal characteristics over the frozen ground and provide an important scientific basis for land–atmosphere interactions.

scholarly journals Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

2016 ◽  
Vol 10 (1) ◽  
pp. 287-306 ◽  
Author(s):  
W. Wang ◽  
A. Rinke ◽  
J. C. Moore ◽  
X. Cui ◽  
D. Ji ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Soil Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Ground Temperature ◽  
Diagnostic Methods ◽  
The Tibetan Plateau ◽  
Temperature Profiles ◽  
Land Surface Models ◽  
Surface Models

Abstract. We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

scholarly journals Evaluation of Eight Current Reanalyses in Simulating Land Surface Temperature from 1979 to 2003 in China

2017 ◽  
Vol 30 (18) ◽  
pp. 7379-7398 ◽  
Author(s):  
Chunlüe Zhou ◽  
Kaicun Wang ◽  
Qian Ma
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
North China Plain ◽  
North China ◽  
Northwest China ◽  
Warming Trend ◽  
The Tibetan Plateau ◽  
Precipitation Frequency ◽  
The North ◽  
The North China Plain

Abstract Land surface temperature Ts provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational Ts data makes assessing model simulations difficult. Here, the authors first examined the simulated Ts of eight current reanalyses based on homogenized Ts data collected at ~2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of Ts in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRA land versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of Ts over the north China plain and south China is mostly influenced by surface incident solar radiation Rs, followed by precipitation frequency, whereas the opposite is true over the northwest China, northeast China, and the Tibetan Plateau. This variable relationship is well captured by ERA-Interim, ERA-Interim land, MERRA, and JRA-55. The homogenized Ts data show a warming of 0.34°C decade−1 from 1979 to 2003 in China, varying between 0.25° and 0.42°C decade−1 for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of Ts over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of Ts over the north China plain and south China owing to their biases in simulating the Rs and precipitation frequency trends. This study provides a diagnostic method for examining the capability of current atmospheric/land reanalysis data in regional climate change studies.

scholarly journals Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

2015 ◽  
Vol 9 (2) ◽  
pp. 1769-1810 ◽  
Author(s):  
W. Wang ◽  
A. Rinke ◽  
J. C. Moore ◽  
X. Cui ◽  
D. Ji ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Soil Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Ground Temperature ◽  
Diagnostic Methods ◽  
The Tibetan Plateau ◽  
Temperature Profiles ◽  
Land Surface Models ◽  
Surface Models

Abstract. We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99–135 x 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2). However the uncertainty (1–128 x 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan Plateau.

scholarly journals On the freeze–thaw cycles of shallow soil and connections with environmental factors over the Tibetan Plateau

2021 ◽  
Author(s):  
Ning Li ◽  
Lan Cuo ◽  
Yongxin Zhang
Keyword(s):  
Tibetan Plateau ◽  
Soil Temperature ◽  
Coniferous Forest ◽  
Soil Layer ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Freeze Thaw ◽  
Shallow Soil ◽  
Thaw Cycle

Abstract Changes in the freeze–thaw cycles of shallow soil have important consequences for surface and subsurface hydrology, land–atmosphere energy and moisture interaction, carbon exchange, and ecosystem diversity and productivity. This work examines the shallow soil freeze–thaw cycle on the Tibetan Plateau (TP) using in–situ soil temperature observations in 0–20 cm soil layer during July 1982 – June 2017. The domain and layer averaged beginning frozen day is November 18 and delays by 2.2 days per decade; the ending frozen day is March 9 and advances by 3.2 days per decade; the number of frozen days is 109 and shortens by 5.2 days per decade. Altitude and latitude combined could explain the spatial patterns of annual mean freeze–thaw status well. Stations located near 0–ºC contour line experienced dramatic changes in freeze–thaw cycles as seen from subtropical mountain coniferous forest in the southern TP. Soil completely freezes from surface to 20–cm depth in 15 days while completely thaws in 10 days on average. Near–surface soil displays more pronounced changes than deeper soil. Surface air temperature strongly influences the shallow soil freeze – thaw status but snow exerts limited effects. Different thresholds in freeze–thaw status definition lead to differences in the shallow soil freeze–thaw status and multiple–consecutive–day approach appears to be more robust and reliable. Gridded soil temperature products could resolve the spatial pattern of the observed shallow soil freeze–thaw status to some extent but further improvement is needed.

scholarly journals A Simulation and Validation of CLM during Freeze-Thaw on the Tibetan Plateau

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Xuewei Fang ◽  
Siqiong Luo ◽  
Shihua Lyu ◽  
Boli Chen ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Frozen Soil ◽  
Surface Radiation ◽  
The Tibetan Plateau ◽  
Hydraulic Property ◽  
Freeze Thaw ◽  
Community Land Model ◽  
Thaw Cycle ◽  
Soil Hydraulic Property ◽  
Soil Hydraulic

The applicability of a new soil hydraulic property of frozen soil scheme applied in Community Land Model 4.5 (CLM4.5), in conjunction with an impedance factor for the presence of soil ice, was validated through two offline numerical simulations conducted at Madoi (GS) and Zoige (ZS) on the Tibetan Plateau (TP). Sensitivity analysis was conducted via replacing the new soil hydraulic property scheme in CLM4.5 by the old one, using default CLM4.5 runs as reference. Results indicated that the new parameterization scheme ameliorated the surface dry biases at ZS but enlarged the wet biases which existed at GS site due to ignoring the gravel effect. The wetter surface condition in CLM4.5 also leads to a warmer surface soil temperature because of the greater heat capacity of liquid water. In addition, the combined impact of new soil hydraulic property schemes and the ice impedance function on the simulated soil moisture lead to the more reasonable simulation of the starting dates of freeze-thaw cycle, especially at the thawing stage. The improvements also lead to the more reasonable turbulent fluxes simulations. Meanwhile, the decreased snow cover fraction in CLM4.5 resulted in a lower albedo, which tended to increase net surface radiation compared to previous versions. Further optimizing is needed to take the gravel into account in the numerical description of thermal-hydrological interactions.

scholarly journals Identifying Sensitive Model Parameter Combinations for Uncertainties in Land Surface Process Simulations over the Tibetan Plateau

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1724 ◽  
Author(s):  
Fei Peng ◽  
Guodong Sun
Keyword(s):  
Tibetan Plateau ◽  
Soil Temperature ◽  
Land Surface ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Model Parameters ◽  
The Tibetan Plateau ◽  
Surface Heat Fluxes ◽  
Sensitive Parameter

Model parameters are among the primary sources of uncertainties in land surface models (LSMs). Over the Tibetan Plateau (TP), simulations of land surface processes, which have not been well captured by current LSMs, can significantly affect the accurate representations of the weather and climate impacts of the TP in numerical weather prediction and climate models. Therefore, to provide guidelines for improving the performance of LSMs over the TP, it is essential to quantify the uncertainties in the simulated land surface processes associated with model parameters and detect the most sensitive parameters. In this study, five observational sites were selected to well represent the land surfaces of the entire TP. The impacts of 28 uncertain parameters from the common land model (CoLM) on the simulated surface heat fluxes (including sensible and latent heat fluxes) and soil temperature were quantified using the approach of conditional nonlinear optimal perturbation related to parameters (CNOP-P). The results showed that parametric uncertainties could induce considerable simulation uncertainties in surface heat fluxes and soil temperature. Thus, errors in parameters should be reduced. To inform future parameter estimation efforts, a three-step sensitivity analysis framework based on the CNOP-P was applied to identify the most sensitive parameter combinations with four member parameters for sensible and latent heat fluxes as well as soil temperature. Additionally, the most sensitive parameter combinations were screened out and showed variations with the target state variables and sites. However, the combinations also bore some similarities. Generally, three or four members from the most sensitive combinations were soil texture related. Furthermore, it was only at the wetter sites that parameters related to vegetation were contained in the most sensitive parameter combinations. In the future, studies on parameter estimations through multiobjective or single-objective optimization can be conducted to improve the performance of LSMs over the TP.

scholarly journals The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products

2011 ◽  
Vol 15 (7) ◽  
pp. 2303-2316 ◽  
Author(s):  
Z. Su ◽  
J. Wen ◽  
L. Dente ◽  
R. van der Velde ◽  
L. Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Soil Temperature ◽  
Land Surface ◽  
Regional Scale ◽  
The Tibetan Plateau ◽  
Humid Climate ◽  
Coarse Resolution ◽  
Reference Networks

Abstract. A plateau scale soil moisture and soil temperature observatory is established on the Tibetan Plateau for quantifying uncertainties in coarse resolution satellite and model products of soil moisture and soil temperature. The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) consists of three regional scale in-situ reference networks, including the Naqu network in a cold semiarid climate, the Maqu network in a cold humid climate and the Ngari network in a cold arid climate. These networks provide a representative coverage of the different climate and land surface hydrometeorological conditions on the Tibetan plateau. In this paper the details of the Tibet-Obs are reported. To demonstrate the uniqueness of the Tibet-Obs in quantifying and explaining soil moisture uncertainties in existing coarse satellite products, an analysis is carried out to assess the reliability of several satellite products for the Naqu and the Maqu network areas. It is concluded that global coarse resolution soil moisture products are useful but exhibit till now unreported uncertainties in cold and semiarid regions – use of them would be critically enhanced if uncertainties can be quantified and reduced using in-situ measurements.

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