Coupling of the Calculated Freezing and Thawing Front Parameterization in the Earth System Model CAS-ESM

The soil freezing and thawing process affects soil physical properties,such as heat conductivity,heat capacity,and hydraulic conductivity in frozen ground regions,and further affects the processes of soil energy,hydrology,and carbon and nitrogen cycles.In this study,the calculation of freezing and thawing front parameterization was implemented into the earth system model of the Chinese Academy of Sciences(CAS-ESM)and its land component,the Common Land Model(CoLM),to investigate the dynamic change of freezing and thawing fronts and their effects.Our results showed that the developed models could reproduce the soil freezing and thawing process and the dynamic change of freezing and thawing fronts.The regionally averaged value of active layer thickness in the permafrost regions was 1.92 m,and the regionally averaged trend value was 0.35 cm yr–1.The regionally averaged value of maximum freezing depth in the seasonally frozen ground regions was 2.15 m,and the regionally averaged trend value was–0.48 cm yr–1.The active layer thickness increased while the maximum freezing depth decreased year by year.These results contribute to a better understanding of the freezing and thawing cycle process.

Changes in Water Use Efficiency Caused by Climate Change,CO_(2) Fertilization,and Land Use Changes on the Tibetan Plateau

Terrestrial ecosystem water use efficiency(WUE)is an important indicator for coupling plant photosynthesis and transpiration,and is also a key factor linking the carbon and water cycles between the land and atmosphere.However,under the combination of climate change and human intervention,the change in WUE is still unclear,especially on the Tibetan Plateau(TP).Therefore,satellite remote sensing data and process-based terrestrial biosphere models(TBMs)are used in this study to investigate the spatiotemporal variations of WUE over the TP from 2001 to 2010.Then,the effects of land use and land cover change(LULCC)and CO_(2) fertilization on WUE from 1981-2010 are assessed using TBMs.Results show that climate change is the leading contributor to the change in WUE on the TP,and temperature is the most important factor.LULCC makes a negative contribution to WUE(-20.63%),which is greater than the positive contribution of CO_(2) fertilization(11.65%).In addition,CO_(2) fertilization can effectively improve ecosystem resilience on the TP.On the northwest plateau,the effects of LULCC and CO_(2) fertilization on WUE are more pronounced during the driest years than the annual average.These findings can help researchers understand the response of WUE to climate change and human activity and the coupling of the carbon and water cycles over the TP.

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

Simulated response of the active layer thickness of permafrost to climate change

The active layer thickness(ALT)in permafrost regions,which affects water and energy exchange,is a key variable for assessing hydrological processes,cold-region engineering,and climate change.In this study,the authors analyzed the variation trends and relative changes of simulated ALTs using the Chinese Academy of Sciences Land Surface Model(CAS-LSM)and the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model,gridpoint version 3(CAS-FGOALS-g3).Firstly,the simulated ALTs produced by CAS-LSM were shown to be reasonable by comparing them with Circumpolar Active Layer Monitoring observations.Then,the authors simulated the ALTs from 1979 to 2014,and their relative changes across the entire Northern Hemisphere from 2015 to 2100.It is shown that the ALTs have an increasing trend.From 1979 to 2014,the average ALTs and their variation trends over all permafrost regions were 1.08 m and 0.33 cm yr-1,respectively.The relative changes of the ALTs ranged from 1%to 58%,and the average relative change was 10.9%.The variation trends of the ALTs were basically consistent with the variation trends of the 2-m air temperature.By 2100,the relative changes of ALTs are predicted to be 10.3%,14.6%,30.1%,and 51%,respectively,under the four considered hypothetical climate scenarios(SSP-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).This study indicates that climate change has a substantial impact on ALTs,and our results can help in understanding the responses of the ALTs of permafrost due to climate change.

Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities

With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.

CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

The datasets of the five Land-offline Model Intercomparison Project(LMIP)experiments using the Chinese Academy of Sciences Land Surface Model(CAS-LSM)of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3(CAS FGOALS-g3)are presented in this study.These experiments were forced by five global meteorological forcing datasets,which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project(LS3MIP)of CMIP6.These datasets have been released on the Earth System Grid Federation node.In this paper,the basic descriptions of the CAS-LSM and the five LMIP experiments are shown.The performance of the soil moisture,snow,and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations.Results show that their mean states,spatial patterns,and seasonal variations can be reproduced well by the five LMIP simulations.It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

气候变化背景下青藏高原内流区湖泊水储量或将持续增加

青藏高原内流区湖泊广布,是气候变化的敏感指示器.准确估算青藏高原的湖泊水储量变化对研究湖泊生态系统和水资源变化至关重要.然而青藏高原高寒缺氧、地形条件复杂,限制了该地区对湖泊水储量的长期实地观测.基于重力卫星数据和高分辨率陆面过程模拟,本研究估算了青藏高原内流区18个大型湖泊(大于300 km^(2))2002~2018期间的湖泊水储量变化,并利用机器学习模型预估了未来湖泊水储量的变化.结果表明,18个湖泊的水储量在2002~2018年间以约26.92 mm/a的速度增加;在中等排放情景下(SSP245),青藏高原内流区湖泊未来水储量增加趋势将变缓,到21世纪中叶,湖泊水储量的增长速率将下降到过去20年的40%左右.研究结果有助于更好地理解气候变化对高原湖泊水储量的影响,为气候变化背景下水资源适应性管理提供科学支撑.