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Surface solar radiation (SSR), as a primary component of heat budget between land and atmosphere, controls both water and energy exchanges. However, the sub‐grid terrain radiative effect (STRE) which exerts critical influences on SSR simulation is usually extremely simplified or even ignored in most current land surface models (LSMs) due to the heavy computational burden. In this study, we developed a physically realistic and computationally efficient three dimensional (3D) STRE scheme and implemented it into the Common Land Model (CoLM) to indicate its quantitative influences on surface energy budget, land surface temperature (LST), soil temperature, and moisture simulations over the Heihe River Basin, Tibetan Plateau. Results show that the CoLM coupled with 3D‐STRE scheme shows more realistic description of SSR and improves the simulation of soil thermal and moist features at both single‐point and regional scales. Compared to the results without 3D‐STRE, the inclusion of 3D‐STRE scheme efficiently diminishes the overestimation of SSR, which leads to the root mean square error (RMSE) of LST simulation reduced by 17.1% due to significant improvements in valley areas. Adopting 3D‐STRE scheme also improves the pattern and amplitude of temporal variability of simulated soil temperature (moisture) at 37 sites with the mean Taylor score increased by 3.6–3.7% (14.0–14.3%). These results emphasize the importance of considering the 3D‐STRE scheme in LSMs and are significantly helpful to deepen our understanding of surface heat exchanges and improve the representations of land surface processes over complex terrain. Plain Language Summary: Topography exerts remarkable influences on the land surface solar radiation (SSR) over complex terrain, which controls both water and energy exchanges between land and atmosphere. However, the parameterization of sub‐grid topographical effects on SSR are usually extremely simplified or even ignored in most current numerical models due to the heavy computational burden. In this study, we developed a parameterization with much more real physical processes, simple parameters and high computational efficiency to consider the impact of sub‐grid topography on SSR, it tends to show widely potential application in land process and climate modeling. Taking the Heihe River Basin in China as an example, we found that the land surface model coupled with this scheme shows more realistic description of SSR and significantly improves the simulations of soil thermal and moist features. These results highlight the necessity of considering the sub‐grid topographical effects on SSR simulation in land surface modeling and are obviously helpful to advance our understanding of the surface heat exchanges and improve the representations of land surface processes over complex terrain areas. Key Points: A 3D sub‐grid terrain radiative effect (STRE) scheme is developedThe 3D STRE scheme can show more realistic description of the land surface solar radiationThe CoLM coupled with the 3D STRE scheme significantly improved the simulation of soil thermal and moist features over complex terrain areas [ABSTRACT FROM AUTHOR]

The root water uptake (RWU) rate of plants is influenced by various environmental factors. Low soil temperature stress can reduce RWU rate by inhibiting the growth of plant roots and increasing the hydraulic resistance of water transport among the soil‐plant‐atmosphere continuum. Given that low soil temperature stress is not accounted for in current land surface models (LSMs); in this study, we introduce three functions to represent low soil temperature stress, and modify the RWU scheme of the Common Land Model to quantify the role of low soil temperature stress on water and energy exchange between land and atmosphere. The simulated water and energy fluxes are evaluated using both in situ and global observational data sets. The results from in situ simulations show that ignoring effects of low soil temperature stress, latent, and sensible heat fluxes in spring are overestimated and underestimated, respectively, with the root mean square error up to 40 W/m2. By incorporating the low soil temperature stress functions into the RWU scheme, nearly 40% of the simulated errors are reduced. The global simulated results also highlight the importance of accounting for low soil temperature stress on increasing the accuracy of the modeled latent heat flux over high latitude areas. While uncertainties from related physical processes and parameters warrant further investigations, our results indicate that consideration of low soil temperature stress significantly affects water and energy transport from land to atmosphere by restricting RWU rate, emphasizing the need to integrate it in LSMs to increase the model reliability, especially over cold regions. Plain Language Summary: Plants obtain water from the soil through their roots, but the process of obtaining water is affected by a variety of factors. The low temperature in the soil is one of the important influencing factors, which usually reduces the rate of water absorption by plant roots. However, this influence factor is not considered in current land surface process model. Here, we propose three empirical functions that can represent the effects of low soil temperature, incorporate them into the Common Land Model (CoLM), and validate the impact of these functions in the model by using the local and global observation data. The results of numerical experiments show that considering the effect of low soil temperature on root water uptake in CoLM can improve the model performance on simulating water and energy exchange between land and atmosphere over many areas. Key Points: Three functions to characterize the low soil temperature stress were introduced in the Common Land Model (CoLM)By considering the low soil temperature stress in the CoLM, the bias in energy flux simulation is significantly decreasedThe low soil temperature stress functions were evaluated in both site and global scale [ABSTRACT FROM AUTHOR]

To improve the performance of the second generation of Beijing Climate Center Atmosphere‐Vegetation Interaction Model (BCC_AVIM2.0) with a fine resolution (~45 km) over lake‐rich areas, the default lake scheme in BCC_AVIM2.0 is replaced by the Common Land Surface Model (CoLM)‐Lake scheme with much more realistic treatments of the energy exchanges in the snow‐ice‐water‐sediment system relative to the default lake scheme. Results show that the lake surface temperature (LST) biases produced by BCC_AVIM2.0 with the default lake scheme can be largely reduced by adopting the CoLM‐Lake scheme in winter due to much more realistically simulated vertical water temperature profiles over the Great Lakes region. The spatial distributions and seasonal variations of the LST simulations can also be significantly improved by the CoLM‐Lake scheme within BCC_AVIM2.0. The performances of BCC_AVIM2.0 in simulating the lake ice in winter can be largely improved by replacing the default lake scheme with the CoLM‐Lake scheme. The improvements in the LST simulated by BCC_AVIM2.0 with the CoLM‐Lake scheme further lead to reduced biases in the simulated ground surface temperature. The simulations of air temperature and precipitation in the coupled model are also improved by adopting the CoLM‐Lake scheme over the Great Lakes region, which indicates the improvements in simulating the energy and water exchange between the atmosphere and lakes. This study highlights the importance of a more realistic lake scheme in simulating the ground surface temperature and the energy exchanges between the atmosphere and lakes. Key Points: The default lake scheme in BCC_AVIM2.0 is replaced by the CoLM‐Lake schemeLake water temperature biases produced by the default lake scheme are largely reduced by adopting the CoLM‐Lake schemeLarge improvements in simulating lake ice are obtained by adopting the CoLM‐Lake scheme in BCC_AVIM2.0 [ABSTRACT FROM AUTHOR]

The ability of FLake, WRF‐Lake, and CoLM‐Lake models in simulating the thermal features of Lake Nam Co in Central Tibetan Plateau has been evaluated in this study. All the three models with default settings exhibited distinct errors in the simulated vertical temperature profile. Then model calibration was conducted by adjusting three (four) key parameters within FLake and CoLM‐Lake (WRF‐Lake) in a series of sensitive experiments. Results showed that each model's performance is sensitive to the key parameters and becomes much better when adjusting all the key parameters relative to tuning single parameter. Overall, setting the temperature of maximum water density to 1.1 °C instead of 4 °C in the three models consistently leads to improved vertical thermal structure simulation during cold seasons; reducing the light extinction coefficient in FLake results in much deeper mixed layer and warmer thermocline during warm seasons in better agreement with the observation. The vertical thermal structure can be clearly improved by decreasing the light extinction coefficient and increasing the turbulent mixing in WRF‐Lake and CoLM‐Lake during warm seasons. Meanwhile, the modeled water temperature profile in warm seasons can be significantly improved by further replacing the constant surface roughness lengths by a parameterized scheme in WRF‐Lake. Further intercomparison indicates that among the three calibrated models, FLake (WRF‐Lake) performs the best to simulate the temporal evolution and intensity of temperature in the layers shallower (deeper) than 10 m, while WRF‐Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths. Key Points: The performance of three one‐dimensional lake models in simulating the thermal structure of Nam Co Lake is evaluated and improvedKey processes related to the simulated thermal regime of alpine lakes on the Tibetan Plateau are indicated and revealed [ABSTRACT FROM AUTHOR]

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model (CoLM) over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise (30 min) to monthly. A comparison between the simulations and observations indicated that CoLM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes. A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas CoLM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. CoLM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why CoLM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, CoLM performs best for evergreen broadleaf forests and worst for croplands and wetlands. [ABSTRACT FROM AUTHOR]

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas. [ABSTRACT FROM AUTHOR]

Previous research found that the warming rate observed for the period 1979-2012 increases dramatically with decreasing vegetation greenness over land between 50°S and 50°N, with the strongest warming rate seen over the driest regions such as the Sahara desert and the Arabian Peninsula, suggesting warming amplification over deserts. To further this finding, this paper explores possible mechanisms for this amplification by analyzing observations, reanalysis data and historical simulations of global coupled atmosphere-ocean general circulation models. We examine various variables, related to surface radiative forcing, land surface properties, and surface energy and radiation budget, that control the warming patterns in terms of large-scale ecoregions. Our results indicate that desert amplification is likely attributable primarily to enhanced longwave radiative forcing associated with a stronger water vapor feedback over drier ecoregions in response to the positive global-scale greenhouse gas forcing. This warming amplification and associated downward longwave radiation at the surface are reproduced by historical simulations with anthropogenic and natural forcings, but are absent if only natural forcings are considered, pointing to new potential fingerprints of anthropogenic warming. These results suggest a fundamental pattern of global warming over land that depend on the dryness of ecosystems in mid- and low- latitudes, likely reflecting primarily the first order large-scale thermodynamic component of global warming linked to changes in the water and energy cycles over different ecosystems. This finding may have important implications in interpreting global warming patterns and assessing climate change impacts. [ABSTRACT FROM AUTHOR]

The process of solar radiative transfer at the land surface is important to energy, water, and carbon balance, especially for vegetated areas. Currently the most commonly used two-stream model considers the plant functional types (PFTs) within a grid to be independent of each other and their leaves to be horizontally homogeneous. This assumption is unrealistic in most cases. To consider canopy three-dimensional (3D) structural effects, a new framework of 3D canopy radiative transfer model was developed and validated by numerical simulations and shows a good agreement. A comparison with the two-stream model in the offline Community Land Model (CLM4.0) shows that an increase of canopy absorption mainly happens with sparse vegetation or with multilayer canopies with a large sun zenith angle θsun and is due to increases of the ground and sky shadows and of the optical pathlength because of the shadow overlapping between bushes and canopy layers. A decrease of canopy absorption occurs in densely vegetated areas with small θsun. For a one-layer canopy, these decreases are due to crown shape effects that enhance the transmission through the canopy edge. For a multilayer canopy, aside from these shape effects, transmission is also increased by the decreased ground shadow due to the shadow overlapping between layers. Ground absorption usually changes with opposite sign as that of the canopy absorption. Somewhat lower albedos are found over most vegetated areas throughout the year. The 3D model also affects the calculation of the fraction of sunlit leaves and their corresponding absorption. [ABSTRACT FROM AUTHOR]

Highlights: [•] Only 960 simulations are required to identify 5 most sensitive parameters for simulated annual GPP and LE out of 22. [•] Over 80% of the variance of GPP can be explained by 5 most sensitive parameters to simulation of annual GPP. [•] Over 70% of the variance of LE can be explained by 5 most sensitive parameters to simulation of annual LE. [•] Maximum carboxylation rate (v cmax), canopy leaf area index (LAI) and quantum use efficiency (α) are 3 most important parameters for GPP of most PFTs. [•] An empirical model in the leaf stomatal conductance model (a 1), maximum carboxylation rate (v cmax) and LAI are 3 most important parameters for annual LE of most PFTs. [ABSTRACT FROM AUTHOR]