Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and economics.First of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of China.Simulations of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the observations.Under a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ region.Population exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown areas.Furthermore,changes in population exposure to temperature extremes were mainly dominated by future population changes.Finally,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ region.This study helps to provide relevant policies to respond future climate risks over the JJJ region.

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.

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.

模拟多年冻土活动层厚度对气候变化的响应

在气候变化背景下,活动层厚度的变化会对多年冻土区水文,生态,寒区工程等产生较大的影响.本研究利用中科院气候系统模式CAS-FGOALS-g3和陆面过程模式CAS-LSM模拟分析了活动层厚度的变化趋势和相对变化.结果表明:活动层厚度整体上呈现出增加的趋势.1979-2014年,多年冻土区活动层厚度的区域平均为1.08 m,变化趋势为0.33 cm yr-1,其变化趋势与2 m气温变化趋势基本一致,相对变化范围为1%-58%,平均为10.9%.在未来四种不同的气候情景(SSP-2.6,SSP2-4.5,SSP3-7.0和SSP5-8.5)下,到2100年预计活动层厚度的相对变化分别为10.3%,14.6%,30.1%和51%.

Ensemble Simulation of Land Evapotranspiration in China Based on a Multi-Forcing and Multi-Model Approach

In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).

Numerical simulation based on two-directional freeze and thaw algorithm for thermal diffusion model

Freeze-thaw processes significantly modulate hydraulic and thermal char- acteristics of soil. The changes in the frost and thaw fronts （FTFs） affect the water and energy cycles between the land surface and the atmosphere. Thus, the frozen soil com- prising permafrost and seasonally frozen soil has important effects on the land surface hydrology in cold regions. In this study, a two-directional freeze and thaw algorithm is incorporated into a thermal diffusion equation for simulating FTFs. A local adaptive variable-grid method is used to discretize the model. Sensitivity tests demonstrate that the method is stable and FTFs can be tracked continuously. The FTFs and soil tempera- ture at the Qinghai-Tibet Plateau D66 site are simulated hourly from September 1, 1997 to September 22, 1998. The results show that the incorporated model performs much better in the soil temperature simulation than the original thermal diffusion equation, showing potential applications of the method in land-surface process modeling.

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.

Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China

In this study, the CERES(Crop Estimation through Resource and Environment Synthesis) crop model was coupled with CLM3.5, the land module of the regional climate model RegCM4. The new coupled model was named RegCM4_CERES; and in this model, crop type was further divided into winter wheat, spring wheat, spring maize, summer maize, early rice, late rice,single rice, and other crop types based on each distribution fraction. The development of each crop sub-type was simulated by the corresponding crop model separately, with each planting and harvesting date. A simulation test using RegCM4_CERES was conducted across China from 1999 to 2008; a control test was also performed using the original RegCM4. Data on crop LAI(leaf area index), soil moisture at 10 cm depth, precipitation, and 2 m air temperature were collected to evaluate the performance of RegCM4_CERES. The evaluation provided comparison of single-station time series, regional distributions,seasonal variations, and statistical indices for RegCM4_CERES. The results revealed that the coupled model had an excellent ability to simulate the phonological changes and spatial variations in crops. The consideration of dynamic crop development in RegCM4_CERES corrected the wet bias of the original RegCM4 over North China and the cold bias over South China.However, the degree of improvement was minimal and the statistical indices for RegCM4_CERES were roughly the same as the original RegCM4.

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.

Incorporation of a Dynamic Root Distribution into CLM4.5： Evaluation of Carbon and Water Fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen （CN） interactions （CLM4.5-CN） to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 （BRSa3） site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production （GPP） and latent heat flux （LE） for the dry season, and improved the carbon （C） and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m^-2 d^-1, net ecosystem exchange by 1.96 g C m^-2 d^-1, LE by 5.0 W m^-2, and soil moisture by 0.03 m^3 m^-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses （including GPP and LE） to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.

Improving microwave brightness temperature predictions based on Bayesian model averaging ensemble approach

The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.

The Chinese carbon cycle data-assimilation system(Tan-Tracker)

In this study,the Chinese carbon cyle dataassimilation system Tan-Tracker is developed based on the atmospheric chemical transport model(GEOS-Chem)platform.Tan-Tracker is a dual-pass data-assimilation system in which both CO2concentrations and CO2fluxes are simultaneously assimilated from atmospheric observations.It has several advantages,including its advanced data-assimilation method,its highly efficient computing performance,and its simultaneous assimilation of CO2concentrations and CO2fluxes.Preliminary observing system simulation experiments demonstrate its robust performance with high assimilation precision,making full use of observations.The Tan-Tracker system can only assimilate in situ observations for the moment.In the future,we hope to extend Tan-Tracker with functions for using satellite measurements,which will form the quasioperational Chinese carbon cycle data-assimilation system.

Impacts of hydraulic redistribution on eco-hydrological cycles： A case study over the Amazon basin

Hydraulic redistribution(HR)refers to the process of soil water transport through the low-resistance pathway provided by plant roots.It has been observed in field studies and proposed to be one of the processes that enable plants to resist water limitations.However,most land-surface models(LSMs)currently do not include this underground root process.In this study,a HR scheme was incorporated into the Community Land Model version 4.5(CLM4.5)to investigate the effect of HR on the eco-hydrological cycle.Two paired numerical simulations(with and without the new HR scheme)were conducted for the Tapajos National Forest km83(BRSa3)site and the Amazon.Simulations for the BRSa3 site in the Amazon showed that HR during the wet season was small,<0.1 mm day^(–1),transferring water from shallow wet layers to deep dry layers at night;however,HR in the dry season was more obvious,up to 0.3 mm day^(–1),transferring water from deep wet layers to shallow dry layers at night.By incorporating HR into CLM4.5,the new model increased gross primary production(GPP)and evapotranspiration(ET)by 10%and 15%,respectively,at the BRSa3 site,partly overcoming the underestimation.For the Amazon,regional analysis also revealed that vegetation responses(including GPP and ET)to seasonal drought and the severe drought of 2005 were better captured with the HR scheme incorporated.

A Soil Moisture Data Assimilation System for Pakistan Using PODEn4DVar and CLM4.5

Soil moisture is an important state variable for land–atmosphere interactions.It is a vital land surface variable for research on hydrology,agriculture,climate,and drought monitoring.In current study,a soil moisture data assimilation framework has been developed by using the Community Land Model version 4.5(CLM4.5)and the proper orthogonal decomposition(POD)-based ensemble four-dimensional variational assimilation(PODEn4 DVar)algorithm.Assimilation experiments were conducted at four agricultural sites in Pakistan by assimilating in-situ soil moisture observations.The results showed that it was a reliable system.To quantify further the feasibility of the data assimilation(DA)system,soil moisture observations from the top four soil-depths(0–5,5–10,10–20,and 20–30 cm)were assimilated.The evaluation results indicated that the DA system improved soil moisture estimation.In addition,updating the soil moisture in the upper soil layers of CLM4.5 could improve soil moisture estimation in deeper soil layers[layer 7(L7,62.0 cm)and layer 8(L8,103.8 cm)].To further evaluate the DA system,observing system simulation experiments(OSSEs)were designed for Pakistan by assimilating daily observations.These idealized experiments produced statistical results that had higher correlation coefficients,reduced root mean square errors,and lower biases for assimilation,which showed that the DA system is able to produce and improve soil moisture estimation in Pakistan.