Community Land Model Version Research Articles

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Abstract. Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicate the need to improve the representation of these variables in CLM5 to increase the model sensitivity to drought stress and other crop stressors.

Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes

Abstract. Wildfires influence not only ecosystems but also carbon and water fluxes on Earth. Yet, the fire processes including the occurrence and consequences of fires are still limitedly represented in land surface models (LSMs). In particular, the performance of LSMs in estimating burned areas across high northern latitudes is poor. In this study, we employed the daily burned areas from the satellite-based Global Fire Emissions Database (version 4) (GFED4) into the Community Land Model (version 5.0) with a biogeochemistry module (CLM5-BGC) to identify the effects of accurate fire simulation on carbon and water fluxes over Alaska and Eastern Siberia. The results showed that the simulated carbon emissions with burned areas from GFED4 (i.e., experimental run) were significantly improved in comparison to the default CLM5-BGC simulation, which resulted in opposite signs of the net ecosystem exchange for 2004, 2005, and 2009 over Alaska between the default and experimental runs. Also, we identified that carbon emissions were more sensitive to the wildfires in Alaska than in Eastern Siberia, which could be explained by the vegetation distribution (i.e., tree cover ratio). In terms of water fluxes, canopy transpiration in Eastern Siberia was relatively insensitive to the size of the burned area due to the interaction between leaf area and soil moisture. This study uses CLM5-BGC to improve our understanding of the role of burned areas in ecohydrological processes at high latitudes. Furthermore, we suggest that the improved approach will be required for better predicting future carbon fluxes and climate change.

Modeling Urban Heat Islands and Thermal Comfort During a Heat Wave Event in East China With CLM5 Incorporating Local Climate Zones

AbstractThe urban expansion‐induced heat can exacerbate heat stress for urban dwellers, especially during heat waves. With a focus on the intra‐urban variability of urban heat islands (UHIs) and thermal comfort, the urban parameterization within the Community Land Model version 5 (CLM5) was modified incorporating the local climate zones (LCZs) framework, named CLM5‐LCZs, to simulate the urban climate during a heat wave (HW) event in the summer of 2013. The evaluation of model performance demonstrated that it did a reasonable job of simulating surface energy balance and thermal regimes in cities against observational fluxes from a flux tower measurement site and temperatures from automatic meteorological stations in Nanjing, China. Then we investigated the characteristics and causes of UHIs associated with local background climate, intra‐urban inhomogeneity and HW intensity in East China. The results exhibited that daytime and nighttime canopy urban heat island intensity (CUHII) were highest in the Compact Low Rise (LCZ3) and the Compact High Rise (LCZ1) areas, respectively, while surface urban heat island intensity (SUHII) peaked in the Large Low Rise (LCZ8) and the Compact High Rise (LCZ1) areas during daytime and nighttime, respectively. Urban dwellers were easier exposed to serious heat environment in LCZ3 and LCZ1 areas over the north subtropical climate zone. Contrasts of CUHII and SUHII among different urban classes could exceed 1.7°C and 5.4°C. The intra‐urban heterogeneity may alter the dominant factors controlling SUHII, which were also modulated by local climate and HW intensity. Unlike other controlling factors, the impact of local climate on the contribution from the urban‐rural contrast of convection efficiency was larger than urban features. Overall, CLM5‐LCZs displayed potential of implementing detailed simulations for inter‐ and intra‐city UHIs at a larger scale, and enhancing the capabilities in modeling urban climate and exploring the causes and controls of UHIs.

Matrix Approach to Accelerate Spin‐Up of CLM5

AbstractNumerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin‐up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi‐Analytical Spin‐Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin‐up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin‐up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin‐up on site and globally in comparison with other spin‐up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables

Abstract. This study evaluates water and energy fluxes and variables in combination with parameter optimization of version 5 of the state-of-the-art Community Land Model (CLM5) land surface model, using 6 years of hourly observations of latent heat flux, sensible heat flux, groundwater recharge, soil moisture and soil temperature from an agricultural observatory in Denmark. The results show that multi-objective calibration in combination with truncated singular value decomposition and Tikhonov regularization is a powerful method to improve the current practice of using lookup tables to define parameter values in land surface models. Using measurements of turbulent fluxes as the target variable, parameter optimization is capable of matching simulations and observations of latent heat, especially during the summer period, whereas simulated sensible heat is clearly biased. Of the 30 parameters considered, the soil texture, monthly leaf area index (LAI) in summer, stomatal conductance and root distribution have the highest influence on the local-scale simulation results. The results from this study contribute to improvements of the model characterization of water and energy fluxes. This work highlights the importance of performing parameter calibration using observations of hydrologic and energy fluxes and variables to obtain the optimal parameter values for a land surface model.

The Evaluation of Snow Depth Simulated by Different Land Surface Models in China Based on Station Observations

Snow plays an important role in catastrophic weather, climate change, and water recycling. In order to analyze the ability of different land surface models to simulate snow depth in China, we used atmospheric forcing data from the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) to drive the CLM3.5 (the Community Land Model version 3.5), Noah (NCEP, OSU, Air Force and Office of Hydrology Land Surface Model), and Noah-MP (the community Noah land surface model with multi-parameterization options) land surface models. We also used 2380 daily snow-depth site observations of CMA to analyze the simulation effects of different models on the snow depth in China and different regions during the periods of snow accumulation and snowmelt from 2015 to 2019. The results show that CLM3.5, Noah, and Noah-MP can simulate the spatial distribution of the snow depth in China, but there are some differences between the models. In particular, the snow depth and snow cover simulated by CLM3.5 are lower than those simulated by Noah and Noah-MP in Northwest China and the Tibetan Plateau. From the overall quantitative assessment results for China, the snow depth simulated by CLM3.5 is underestimated, while that simulated by Noah is overestimated. Noah-MP has the best overall performance; for example, the biases of the three models during the snow-accumulation periods are −0.22 cm, 0.27 cm, and 0.15 cm, respectively. Furthermore, the three models perform differently in the three snowpack regions of Northeast China, Northwest China, and the Tibetan Plateau; Noah-MP has the best snow-depth performance in Northeast China, while CLM3.5 has the best snow-depth performance in the Tibetan Plateau region. Noah-MP performs best in the snow-accumulation period, and Noah performs best in the snowmelt period for Northwest China. In conclusion, no single model can perform optimally for snow simulations in different regions of China and at different times of the year, and the multi-model integration of snow may be an effective way to obtain high-quality snow simulation results. So this study provides some scientific references for the spatiotemporal evolution of snow in the context of climate change, monitoring and analysis of snow, the study of land surface models for snow, and the sustainable development and utilization of snow resources in China and other regions.

Impact of Climate Change on the Spatio-Temporal Variation in Groundwater Storage in the Guangdong–Hong Kong–Macao Greater Bay Area

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is one of the world’s four major bay areas. Groundwater is indispensable in ensuring water supply for human production and living, as well as social and economic development. Studying the spatial–temporal variation in groundwater storage (GWS) and exploring the impact of climate change on GWS is of great significance for water resource management in the GBA. In this work, we conducted a simulation using the Community Land Model version 5.0 (CLM5.0) and combined it with Gravity Recovery and Climate Experiment (GRACE) data to calculate GWS in the GBA. In addition, based on the multiple linear regression model, we quantitatively assessed the effects of different climate factors on the change in GWS in the GBA. Comparisons with groundwater wells, automatic weather stations, and satellite observations demonstrated reasonable results. Our results showed that precipitation and evapotranspiration are the main factors affecting the change in GWS in the GBA. Precipitation dominates GWS anomaly changes in areas where wetting and precipitation vary drastically, such as the northern part of Foshan. GWS is closely related to evapotranspiration, in which water and heat changes are significant.

Climatic and anthropogenic controls on groundwater dynamics in the Mekong River Basin

Groundwater depletion is a worldwide concern and an emerging issue in regions such as the Mekong River Basin (MRB). However, even the natural dynamics of groundwater in the MRB is yet to be fully explored, making the quantification of groundwater response to climate variability and anthropogenic activities a major scientific challenge. Here, we examine various groundwater mechanisms in the MRB, focusing on groundwater flow processes that are modulated by climate variability, physiographic features, and key drivers of groundwater-surface water interactions. We further quantify the influence of anthropogenic activities on groundwater dynamics. We use the Community Land Model version 5 (CLM5) at 0.05° (∼5km) spatial resolution with an improved representation of groundwater processes, including lateral groundwater flow and aquifer pumping for irrigation. Results indicate high spatial heterogeneity in groundwater recharge and discharge across the basin governed by climate and subsurface characteristics. A pronounced seasonality is found in groundwater recharge due to precipitation; ∼52% of wet season precipitation recharges groundwater, with substantial carryover to the consecutive dry season that alleviates soil moisture. Importantly, groundwater discharge is a dominant source of streamflow all year round, which suggests a strong surface water-groundwater coupling in the MRB. Finally, our results indicate that irrigation pumping is directly altering groundwater flows and storages; climate variability smoothens pumping effects over long times, but the model simulates region-wide groundwater depletion (up to 1 m/year) in the Mekong Delta during dry years. Our study provides key insights on the evolving groundwater systems in the MRB, also advancing process-based groundwater modeling capabilities.

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

AbstractLand surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance.

Characteristics of near‐surface soil freeze–thaw status using high resolution CLM5.0 simulations on the Tibetan Plateau

AbstractSoil freeze–thaw alternation is a natural characteristic of the Tibetan Plateau (TP), and plays an important role in surface energy balance and eco‐hydrological processes. The soil freeze–thaw process on the TP has changed significantly owing to global warming, affecting the alpine ecosystem structure and function. This study used high‐resolution atmospheric forcing datasets to drive the Community Land Model version 5.0 (CLM5.0) to simulate the near‐surface soil freeze–thaw status between 1979 and 2020. The simulated results were compared with in situ observations, and then the spatiotemporal distribution of the freeze start‐date (FSD), freeze end‐date (FED), freeze duration (FD), and thaw duration (TD) at a depth of 0.1 m were analyzed. The Nash–Sutcliffe efficiency coefficients (NSEs) of FSD, FED, FD, and TD between simulations and in situ observations were 0.77, 0.90, 0.98 and 0.92, and the correlation coefficients of FSD, FED, FD, TD were 0.97, 0.99, 0.99 and 0.98, respectively. The spatial distribution of FSD and TD was characterized by gradually increasing from northwest to southeast while FED and FD exhibited the opposite characteristics. FSD, FED, FD, and TD changed at an area‐mean rate of 1.1, −1.4, −2.5, and 2.5 days decade−1, respectively. This study provides an important reference for analyzing and predicting the changes in near surface soil freeze–thaw status on the TP under the warming climate.

Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States

Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.

Buffering effect of global vegetation on the air-land exchange of mercury: Insights from a novel terrestrial mercury model based on CESM2-CLM5

The vegetation uptake of atmospheric elemental mercury [Hg(0)] and its subsequent littering are critical processes of the terrestrial Hg cycles. There is a large uncertainty in the estimated global fluxes of these processes due to the knowledge gap in the underlying mechanisms and their relationship with environmental factors. Here, we develop a new global model based on the Community Land Model Version 5 (CLM5-Hg) as an independent component of the Community Earth System Model 2 (CESM2). We explore the global pattern of gaseous elemental Hg [Hg(0)] uptake by vegetation and the spatial distribution of litter Hg concentration constrained by observed datasets as well as its driving mechanism. The annual vegetation uptake of Hg(0) is estimated as 3132 Mg yr−1, which is considerably higher than previous global models. The scheme of dynamic plant growth including stomatal activities substantially improves the estimation for global terrestrial distribution of Hg, compared to the leaf area index (LAI) based scheme that is often used by previous models. We find the global distribution of litter Hg concentrations driven by vegetation uptake of atmospheric Hg(0), which are simulated to be higher in East Asia (87 ng/g) than in the Amazon region (63 ng/g). Meanwhile, as a significant source for litter Hg, the formation of structural litter (cellulose litter + lignin litter) results in a lagging effect between Hg(0) deposition and litter Hg concentration, implying the buffering effect of vegetation on the air-land exchange of Hg. This work highlights the importance of vegetation physiology and environmental factors in understanding the vegetation sequestration of atmospheric Hg globally, and calls for greater efforts to protect forests and afforestation.

Improved Performance of CLM5.0 Model in Frozen Soil Simulation Over Tibetan Plateau by Implementing the Vegetation Emissivity and Gravel Hydrothermal Schemes

AbstractFrozen soil is widely distributed over the Tibetan Plateau (TP) and has significant impacts on the regional climate and ecosystem. However, the Community Land Model version 5 (CLM5.0) produces evident cold bias in the frozen soil simulation over TP. In this study, an improved vegetation emissivity scheme and a gravel hydrothermal scheme have been implemented into CLM5.0 model, and their synergistic influences on the frozen soil simulation over TP have been systematically addressed and revealed. Results show that adopting the vegetation emissivity scheme, the gravel hydrothermal scheme, and both can remarkably reduce the cold bias in the frozen soil simulated by the original CLM5.0 model, and the column mean root‐mean‐square error (RMSE) can be reduced by 12.88%, 20.68%, and 31.11% at Arou site and 25.03%, 10.15%, and 36.87% at Maqu site, respectively. The reductions of column mean RMSE for the modeled soil temperature regionally averaged over TP induced by the adoption of vegetation emissivity scheme, the gravel hydrothermal scheme, and both are 32.34%, 6.75%, and 30.18%, respectively. The underlying physical mechanisms are related to the improved representation of the soil hydrothermal processes above or in the soil. The improved vegetation emissivity scheme improves the soil surface long‐wave radiation heat transfer process, while the gravel hydrothermal scheme improves the hydrothermal properties within the soil. Overall, improving the surface long‐wave radiation heat transfer and the internal soil hydrothermal properties can obviously enhance the performance of CLM5.0 model in simulating the soil freeze–thaw processes.

On the role of land-surface hydrology schemes in simulating the daily maximum and minimum air temperatures of Australia using a regional climate model (RegCM4)

AbstractThe present study addresses the possible effects of soil moisture changes on the simulated daily maximum and minimum air temperatures of Australia for a duration of 13 years. Therefore, the community land model version 4.5 (CLM4.5; coupled to the RegCM4) was used to represent the soil moisture and processes associated with it. The CLM4.5 has two land-surface hydrology schemes: TOPMODEL (TOP) and Variable Infiltration Capacity (VIC) and two simulations were conducted, namely: TOP and VIC. The results showed that VIC has lower soil moisture than TOP, leading to a decrease in vegetation transpiration, evaporation, and an increase in soil evaporation relative to TOP. However, there is no considerable difference between the two simulations compared with reanalysis products. In comparison to in-situ measurements, the RegCM4 can reasonably model the climatological annual cycle of mean air temperature (TMP) and its performance varies with the study site (e.g., RegCM4 overestimates TMP by 2.76 and 5.46 °C at Yanco and Tumbarumba, respectively). In summary, the simulated maximum and minimum air temperatures are sensitive to the physical parameterization of RegCM4 rather than variations in soil moisture. Likewise, improvements to the land-surface hydrology schemes TOP/VIC are required to better model Australia's daily maximum and minimum air temperatures.

Dynamic downscaling of climate simulations and projected changes in tropical South America using RegCM4.7

AbstractHigh‐resolution (dx = 25 km) simulations of the regional climate model RegCM4.7 coupled with the Community Land Model version 4.5 (CLM4.5) under low (RCP2.6) and high (RCP8.5) emissions scenarios, which interact with the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (AR5‐IPCC), were carried out over tropical South America (TSA). These simulations were produced through boundary conditions from simulations driven by the general circulation model HadGEM2‐ES. With the goal of verifying the added value (AV) of RegCM4.7, reproducing in an adequate and coherent way the regional aspects of the historical period (1986–2005), as well as evaluating the regional aspects simulated by the model in the scope of the change projections for the far‐future (2080–2099). For this study, the climate in the TSA was characterized based on the variables of precipitation and near‐surface air temperature. For the evaluation of the spatial–temporal representation, frequency and distribution of the regional and global simulation, the high‐resolution observational dataset of the Climate Research Unit version ts4.02 (CRU) was used. Although some differences and biases still persist, RegCM4.7 presents AV in the spatial representation of precipitation and temperature over the northeast region of Brazil and part of the Andes, especially in winter. However, it does not adequately represent precipitation over the Amazon Basin, especially in summer. Results for future projections indicate that the more refined simulation of RegCM4.7 improves the projected change patterns of the coarser resolution simulation of HadGEM2‐ES and even modifies the precipitation signal in some cases. Both models project increase temperature with greater magnitude for RCP8.5. RegCM4.7 presents a much more refined and realistic spatial distribution. HadGEM2‐ES simulates the major aspects of climate enough to consider forcing RegCM4.7 to generate simulations with better performance and more realistic projections.

The urban heat island and thermal heat stress correlate with climate dynamics and energy budget variations in multiple urban environments

Rising temperatures that occur in cities resulted in the urban heat island (UHI) which could also amplify the thermal heat stress, leading to climate-related human mortality. Our study investigated the UHI effect and thermal heat stress of heat index (HI) in the U.S. cities of arid, continental, temperate, and tropical climate zones. A long-term simulation of the UHI and HI was conducted using Community Land Model version 5.0 from 1990 to 2014. The relationship between UHI and HI with climate and energy flux variables are analyzed with divided study periods (1990–2000 and 2001–2014) for the urban impact assessment. Higher sensible heat was reported, particularly in the arid and tropical cities. Further, temperate climate showed increasing annual trends for UHI and ΔHI (urban-rural difference of HIs). The later period (2001–2014) demonstrated greater UHI and ΔHI trends, implying a notable change in climate and urban expansion. The UHI, ranging from 0.73 °C to 2.07 °C, was more intense compared with ΔHI, at 0.14 °C to 1.23 °C. The UHI was positively correlated with temperatures in hot cities, while precipitation is the main driver in the continental city. For ΔHI, the relationship with temperatures were dominant in all climate zones.

The impacts of roughness length on the simulation of land-atmosphere water and heat exchanges over the Yarlung Zangbo Grand canyon region

Precipitation has a significant influence on the topsoil moisture and further impacts the land-atmospheric water and heat exchange process over the Yarlung Zangbo Grand Canyon region (YGC) where exhibits one of the highest frequencies of convective activity in China. The simulated performance of the Community Land Model version 5.0 (CLM5.0) on turbulent fluxes under seven roughness heights for heat transfer (Z0h) schemes at Motuo and Pailong stations over the YGC was evaluated. The results indicate that the CLM5.0 significantly overestimates the surface sensible heat flux (H) while the simulation performance of surface latent heat flux (LE) is better than H. By comparing and analyzing the simulation results, the Z0h schemes suitable for the YGC are selected optimally. The Zeng et al. (J. Hydrometeorol., 2012, 13, 1359–1370) scheme (Z12) is more suitable for the simulations of H, with the simulated RMSE of H at Motuo and Pailong stations on typical sunny days being only 21.63 and 15.13 W m−2, respectively, 81.51% and 76.96% lower than the original Z0h scheme of CLM5.0. The Garratt, J., R and Francey, R., J (Boundary. Layer. Meteorol., 1978, 15, 399–421) scheme (G78) is more suitable for simulating LE in the YGC. The simulated BIAS and RMSE of LE at Motuo station were 9.80% and 21.90% lower than that under the default scheme of CLM5.0 on typical cloudy days. In addition, except for the G78 and CLM5.0 default scheme, the Z0h under the other schemes showed obvious diurnal variation characteristics, and H was positively sensitive to Z0h, while LE was the opposite. Consequently, the optimal Z0h schemes are of great application value for further comparative analysis of the water and heat exchange process between the Grand Canyon land surface and the atmosphere, to better reveal the mechanism of land-atmosphere interactions in the YGC.

Evaluating the Impact of Soil Enthalpy upon the Thawing Process of the Active Layer in Permafrost Regions of the Qinghai–Tibet Plateau Using CLM5.0

The hydrothermal dynamics of the active layer is a key issue in the study of surface processes in permafrost regions. Even though the soil energy budget is controlled by thermal conduction and latent heat transfer, few studies have focused on their effects upon the active layer thickness (ALT). In the present study, the community land model (CLM) version 5.0 is used to simulate the soil temperature and moisture of the active layers at the Tanggula (TGL) and Beiluhe (BLH) stations in permafrost regions of the Qinghai–Tibet Plateau based on the theory of soil enthalpy in order to estimate the soil energy state and analyze the energy changes in the active layer during freezing and thawing. The results indicate that the soil enthalpy has significant seasonal variation characteristics, which accurately reflected the freezing and thawing processes of the active layer. The change in soil enthalpy is significantly related to the thawing depth of the active layer in TGL and BLH, and its changing process can be expressed as an exponential relationship. Near the surface, the variation of the energy due to temperature gradient and actual evaporation can also be expressed as an exponential relationship. The promoting effect of heat conduction on the ALT is greater than the inhibiting effect of latent heat transfer, with the energy contribution from the phase change accounting for about 20–40% of the energy due to the temperature gradient. The thawing depth increases by 14.16–18.62 cm as the energy due to the temperature gradient increases by 1 MJ/m2 and decreases by 2.75–7.16 cm as the energy due to the phase change increases by 1 MJ/m2. Thus, the present study quantifies the effects of soil energy upon the ALT and facilitates an understanding of the hydrothermal processes in soils in permafrost regions.

Prediction of water resources change trend in the Three Gorges Reservoir Area under future climate change

In this study, the water intake module and the confluence module were added to the Community Land Model version 4.5 (CLM 4.5), forming the Community Land Model-Dualistic Water Cycle (CLM-DWC) model (land surface hydrological model). It solved the problem that the influence of human activities was not considered in the existing hydrological coupling simulation process, which so as to the inaccuracy of the simulation process. The CLM-DWC model was driven by the average results of five Global Climate Models (GCMs) ensemble to form the “atmosphere-land-hydrology” fully coupled model to predict the temporal and spatial variation trends of water resources in the Three Gorges Reservoir Area (TGRA) from 2021 to 2050 under Representative Concentration Pathway (RCP) 2.6, RCP4.5 and RCP8.5. In the future scenarios, in terms of spatial distribution, the runoff, surface water and groundwater all indicated the high at the belly of the reservoir and low at the head and tail of the reservoir, which were in good consistency with the baseline period. In terms of intra-annual distribution and inter-annual variability, runoff depth increases by 20.8 mm at RCP4.5 compared with the baseline period, and it tended to decrease under RCP2.6 and RCP8.5. At the same time, under the three scenarios, the average increase of surface water was 3.44 %, groundwater decreases by an average of 11.72 %. Accurately predicting the change trend of water resources in the TGRA under climate change has great significance for future water resources management and planning in the reservoir area.

Responses of Soil Freeze–Thaw Processes to Climate on the Tibetan Plateau from 1980 to 2016

Soil freeze–thaw processes are remarkable features of the land surface across the Tibetan Plateau (TP). Soil moisture and temperature fluctuate during the freeze–thaw cycle, affecting the soil water and energy exchange between the land and atmosphere. This study investigates variations in the soil temperature, humidity, and freeze–thaw state and their responses to air temperature and precipitation on the TP from 1981 to 2016. Regional simulations of the TP using Community Land Model version 4.5 demonstrate that the climate of the TP has become warmer and wetter over the past 37 years, with increases in both regional average temperature and precipitation. Using empirical orthogonal function analysis and the Mann–Kendall trend test of air temperature, we show that 1980–1998 was relatively cold, and 1999–2016 was relatively warm. Soil temperature and moisture in most areas of the TP were affected by air temperature and precipitation, and both showed an upward trend during the past 37 years. Overall, from 1981 to 2016, the freezing date of the TP has become delayed, the thawing date has been hastened, and the duration of the freeze–thaw state has shortened. The surface soil freezes and thaws first, and these processes pervade deeper soil with the passage of time; freeze–thaw processes have an obvious hysteresis. Precipitation and air temperature had marked effects on the freeze–thaw processes. Higher air temperatures delay the freezing date, hasten the thawing date, and shorten the freeze–thaw period. Areas with the highest precipitation saw late soil freeze, early thaw, and the shortest freeze–thaw duration. Areas with less vegetation froze earlier and thawed later. The freeze–thaw duration increased in the northwest of the plateau and decreased on the rest of the plateau. This article informs research on frozen soil change in the context of global warming.