The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and Key Points: • Updated Community Land Model has more hydrological and ecological process fidelity and more comprehensive representation of land management. • The model is systematically evaluated using International Land Model Benchmarking system and shows marked improvement over prior versions. parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5. Plain Language Summary The Community Land Model (CLM) is the land component of the widely used Community Earth System Model (CESM). Here, we introduce model developments included in CLM version 5 (CLM5), the default land component for CESM2 which will be used for the Coupled Model Intercomparison Project (CMIP6). CLM5 includes many new and updated processes including (1) hydrology and snow features such as spatially explicit soil depth, canopy snow processes, a simple firn model, and a more mechanistic river model, (2) plant hydraulics and hydraulic redistribution, (3) revised nitrogen cycling with flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake, (4) expansion to six crop types (global) and time-evolving irrigated areas and fertilization rates, (5) improved urban building energy model, and (6) carbon isotopes. New optional features include a demographically structured dynamic vegetat...

Abstract. Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin–Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

Agricultural expansion and management have greatly increased global food production and altered Earth's climate by changing physical and biogeochemical properties of terrestrial ecosystems. Few Earth system models represent agricultural management practices due to the complexity of the interactions between human decisions and biological processes on global scales. We describe the new capabilities of representing crop distributions and management in the Community Land Model (CLM) Version 5, which includes time‐varying spatial distributions of major crop types and their management through fertilization and irrigation, and temperature‐based phenological triggers. Including active crop management increases peak growing season gross primary productivity (GPP), increases the amplitude of Northern Hemisphere net ecosystem exchange, and changes seasonal and annual patterns of latent and sensible heat fluxes. The CLM5 crop model simulates the global observed historical trend of crop yields with relative fidelity from 1850 to 1990. Cropland expansion was important for increasing crop production, especially during the first century of the simulations, while fertilization and irrigation were important for increasing yields from 1950 onward. From 1990 to present day, observed crop production continued to increase while CLM5 production levels off, likely because intensification practices are not represented in the model. Specifically, CLM does not currently include increasing planting density, crop breeding and genetic modification, representations of tillage, or other management practices that may also affect crop‐climate and crop‐carbon cycle interactions and alter trends in yields. These results highlight the importance of including crop management in Earth system models, particularly as global data sets for parameterization and evaluation become more readily available.

Biases in land‐atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land‐atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single‐column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off‐line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture‐evaporative fraction (EF) and LAI‐EF correlations in off‐line CLM4.5 and reduced the root‐mean‐square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of −1.3°C, and a corresponding dry bias in precipitation was reduced from −111 mm to −23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

spaceAbstract In this study, we coupled Version 4.0 of the Community Land Model that includes crop growth and man-agement (CLM4crop) into the Weather Research and Fore-casting (WRF) model Version 3.3 to better represent inter-actions between climate and agriculture. We evaluated the performance of the coupled model (WRF3.3-CLM4crop) by comparing simulated crop growth and surface climate to multiple observational datasets across the continental United States. The results showed that although the model with dynamic crop growth overestimated leaf area index (LAI) and growing season length, interannual variability in peak LAI was improved relative to a model with prescribed crop LAI and growth period, which has no environmental sensi-tivity. Adding irrigation largely improved daily minimum temperature but the RMSE is still higher over irrigated land than nonirrigated land. Improvements in climate variables were limited by an overall model dry bias. However, with addition of an irrigation scheme, soil moisture and surface energy flux partitioning were largely improved at irrigated sites. Irrigation effects were sensitive to crop growth: the spacecase with prescribed crop growth underestimated irrigation water use and effects on temperature and overestimated soil evaporation relative to the case with dynamic crop growth in moderately irrigated regions. We conclude that studies exam-ining irrigation effects on weather and climate using coupled climate-land surface models should include dynamic crop growth and realistic irrigation schemes to better capture land surface effects in agricultural regions.

Biogenic volatile organic compounds (BVOC) play an important role in global environmental chemistry and climate. In the present work, biogenic emissions from China in 2017 were estimated based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The effects of BVOC emissions on ozone and secondary organic aerosol (SOA) formation were

No abstract

No abstract