Improving CLM4.5 simulations of land–atmosphere exchange during freeze–thaw processes on the Tibetan Plateau

Change in the near‐surface soil freeze/thaw cycle is critical for assessments of hydrological activity, ecosystems, and climate change. Previous studies investigated the near‐surface soil freeze/thaw cycle change mostly based on in situ observations and satellite monitoring. Here numerical simulation method is tested to estimate the long‐term change in the near‐surface soil freeze/thaw cycle in response to recent climate warming for its application to predictions. Four simulations are performed at 0.5° × 0.5° resolution from 1979 to 2009 using the Community Land Model version 4.5, each driven by one of the four atmospheric forcing data sets (i.e., one default Climate Research Unit‐National Centers for Environmental Prediction [CRUNCEP] and three newly developed Modern Era Retrospective‐Analysis for Research and Applications, Climate Forecast System Reanalysis, and European Centre for Medium‐Range Weather Forecasts Reanalysis Interim). The observations from 299 weather stations in both Russia and China are employed to validate the simulated results. The results show that all simulations reasonably reproduce the observed variations in the ground temperature, the freeze start and end dates, and the freeze duration (the correlation coefficients range from 0.47 to 0.99, and the Nash‐Sutcliffe efficiencies range from 0.19 to 0.98). Part of the simulations also exactly simulate the trends of the ground temperature, the freeze start and end dates, and the freeze duration. Of the four simulations, the results from the simulation using the CRUNCEP data set show the best overall agreement with the in situ observations, indicating that the CRUNCEP data set could be preferentially considered as the basic atmospheric forcing data set for future prediction. The simulated area‐averaged annual freeze duration shortened by 8.03 days on average from 1979 to 2009, with an uncertainty (one standard deviation) of 0.67 days caused by the different atmospheric forcing data sets. These results address the performance of numerical model in simulating the long‐term changes in the near‐surface soil freeze/thaw cycle and the role of different atmospheric forcing data sets in the simulation, which are useful for the prediction of future freeze/thaw dynamics.

Section: Data Model Experimental Design and Methodsmentioning

confidence: 99%

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

Guo

Wang

et al. 2018

“…Zeng et al (2005) highlighted undercanopy turbulent exchanges in arid and semiarid regions. A number of studies have dealt with the overestimated soil thermal conductivity by replacing the original parameterizations with adjusted schemes (Luo et al, 2017; Wang et al, 2013; Wang, Yang, et al, 2015; Yang et al, 2005; Zheng, van der Velde, Su, Wen, Wang, & Yang, 2017) and/or incorporating missing processes, such as soil organic matter (Chen et al, 2012; Zheng, van der Velde, Su, Wang, et al, 2015) and coarse‐fragment soils (Pan et al, 2017; Wu et al, 2018; Yi et al, 2018). The underestimation of the soil moisture is primarily attributed to an absence of stratification in the soil column (Yang et al, 2005), which generally exists in the QTP due to the accumulation of organic matter and plant roots in the top soils (Chen, Yang, et al, 2013; Qin, Wu, Wu, et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Improving the Noah‐MP Model for Simulating Hydrothermal Regime of the Active Layer in the Permafrost Regions of the Qinghai‐Tibet Plateau

Zhu

et al. 2020

Soil hydrothermal regime of the active layer in the permafrost regions of the Qinghai‐Tibet Plateau (QTP) is important to the underlying permafrost and the climate change dynamics in Asia. However, a large bias still exists in current land surface models in the representation of soil temperature and moisture. This study assessed and augmented the Noah land surface model with multiparameterization options (Noah‐MP) for simulating soil hydrothermal dynamics at the Tanggula (alpine meadow) and Beiluhe (alpine swamp) stations located in the permafrost regions of the QTP. The results showed that the default Noah‐MP tended to underestimate soil temperature and moisture. Specifically, the default model overestimated the snow depth and duration due to the low snow sublimation rate. This resulted in a cold deviation in the soil temperature at two stations. Such underestimation was reduced by introducing a scheme that considered the sublimation loss from wind. Moreover, the remaining cold bias in the soil profiles of two stations was greatly resolved by a combined scheme of roughness length for heat (Z0h) and undercanopy aerodynamic resistance (ra,g). A soil thermal conductivity scheme, which can produce more realistic soil thermal conductivity in frozen soil, further improved the deep soil temperature simulation. The consideration of soil organic matter could mitigate the underestimation of the shallow soil moisture to some extent, but this improvement was more obvious at the Tanggula station, which had coarser mineral soil than the Beiluhe station.

“…However, the simulation of the TP climate by using a regional climate model has provided inaccurate results, and poor TP simulation is partly caused by the imprecise description of land surface processes (Gao et al, ). Simulations of soil moisture and temperature in FT process over TP have been reported (e.g., Bao et al, , Luo et al, , , Wang & Shi, ), but, due to insufficiencies in observations, particularly in the western TP, the simulation results generally focus on one region (e.g., central TP) or a single location. However, the surface characteristics of the TP are heterogeneous and the processes of water and heat transport in different regions of TP vary (Ma et al, ).…”

Section: Introductionmentioning

confidence: 99%

Improved Simulation of Frozen‐Thawing Process in Land Surface Model (CLM4.5)

Yang

Wang

2018

Soil freezing-thawing cycle is a hallmark feature of the land surface over cold regions. Variations in soil moisture and temperature during frozen-thawing (FT) process are important for water and energy exchange between land and atmosphere. Results of regional simulations by Community Land Model version 4.5 (CLM4.5) over the Tibetan Plateau show that error of daily soil temperature is within 3°C and error of daily soil moisture is with 0.10 mm 3 /mm 3 in FT process, averaged at 10 sites of whole Tibetan Plateau. Single-point simulations show that model biases partly attribute to uncertainties of initial condition and soil category data; excluding impacts of model setting, large biases of soil moisture still exist during soil thawing, and CLM4.5 fails to simulate the diurnal cycle of soil moisture in this period. Modifications of the FT parameterizations in CLM4.5 are proposed, which include (1) use of virtual temperature (T v ) instead of constant freezing point to determine occurring of phase change, (2) introduction of phase change efficiency (ε) to optimize variation rate of soil temperature and moisture in FT process, and (3) consideration of inferred impacts of phase change on soil heat conduction. Single-point and global simulations show that compared to original parameterizations in CLM4.5, these modifications can reproduce the features of daily and diurnal variations in soil moisture and make simulation in FT process closer to the observations.