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Global reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of O(10) $\mathcal{O}(10)$ km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the "Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics," or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions. Plain Language Summary: Modern global weather models are accurate in predicting atmospheric processes at scales of around 10 km or larger, but are less good at predicting smaller scale processes, like for example, the interaction between solar radiation, individual clouds, and the resulting clouds shadows that are cast onto the land surface. High spatio‐temporal resolution research models are able to capture these smaller scale processes, but require a coupling to a weather model to account for the day‐to‐day variability in our weather. In this paper, we present a framework to couple large to small scale models, and demonstrate both the benefits and challenges of using this coupled model setup. The coupled setup excels in capturing the aforementioned high frequency interactions between small clouds and surface solar radiation. However, the chaotic nature of broken to overcast clouds is proven difficult to represent. The coupled model setup is published as open‐source code, and is therefore freely available to the research community. Key Points: We developed an open‐source Python package named (LS)2D, designed to downscale the ERA5 reanalysis with turbulence and cloud‐resolving large‐eddy simulation (LESs)One month long experiments with (LS)2D and MicroHH over the Netherlands demonstrate both the skill and limitations of the coupled setupCapturing high‐frequency interactions between clouds and surface solar irradiance requires high resolution (O $\mathcal{O}$(10) m) LES [ABSTRACT FROM AUTHOR]

We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels. Plain Language Summary: Most atmospheric models currently represent the vegetated canopy as one slab layer at the lowest level of the model. This oversimplification leads to limitations in our understanding on how the canopy and the atmosphere interact, as well as when comparing and interpreting model output with real world observations largely influenced by the presence of a canopy. In this study we implemented a more realistic multilayer canopy scheme in a turbulence‐resolving atmospheric model. We focused and analyzed the features and changes that appear in atmospheric variables due to the presence of a three‐dimensional canopy. To do so we designed several numerical experiments to understand how to best represent the relevant physical and biological processes. We quantified the variability of light, humidity and temperature at leaf‐level, and discussed the large variability the features appearing in the lowest atmosphere by the presence of the canopy. We also compare our model simulations with a complete set of atmospheric observations taken inside and above the Amazonian rainforest, and find an overall good agreement. We finally propose future ways to improve the canopy scheme and, in general, simulations including a vegetated canopy. Key Points: We implemented a 1D multilayer canopy scheme at every gridpoint in the Dutch Atmospheric Large Eddy Simulation resolving leaf, canopy and boundary layer scales as a continuumThe model is compared against a data set gathered during the Amazonian dry season, showing that wind and temperature are better represented than humidityWe present the first Large Eddy Simulations validation of in‐canopy CO2 processes [ABSTRACT FROM AUTHOR]

The leaf photosynthesis models developed by Farquhar et al. (1980, https://doi.org/10.1007/BF00386231) (FvCB) and Goudriaan et al. (1985, https://doi.org/10.1007/978‐1‐4899‐3665‐3%5f10) (G85) are both used in Earth system and weather models to quantify ecosystem carbon assimilation. Despite their common role, a systematic comparison between these two photosynthesis models is currently lacking in scientific literature. In this technical report we compared the two models in a systematic way. Hereto we performed a comparative analysis of the model structures as well as the modeled responses of photosynthesis to light and CO2 at leaf level. To facilitate future model comparison, we also constructed a lookup table that presents FvCB model parameters fitted to CO2‐response curves from G85 in a wide natural range in photosynthetic capacity at standardized temperature. The structure of the FvCB model differs fundamentally from the G85 model as the FvCB model considers rate‐limiting processes due to Rubisco capacity, electron transport and triose phosphate utilization in parallel, whereas the G85 model considers Rubisco activity and triose phosphate utilization limitation to act in series scaled with quantum use efficiency. The models also differ fundamentally in terms of the parametrization of dark respiration. Still, both models calculate near‐similar responses of photosynthesis to changes in light and CO2 across a wide range in photosynthetic capacity with only two free parameters each. Our work thereby highlights functional similarities between these model approaches despite fundamental differences in model structure. Hence, standardized parameter sets that yield similar photosynthesis responses to light and CO2 may facilitate intercomparison of Earth system and weather models. Plain Language Summary: In Earth system and weather models the exchange of CO2 between the vegetation and the atmosphere is primarily determined by photosynthesis at leaf level. Two commonly applied representations of leaf photosynthesis are based on the models of Farquhar et al. (1980, https://doi.org/10.1007/BF00386231) (FvCB) and Goudriaan et al. (1985, https://doi.org/10.1007/978‐1‐4899‐3665‐3%5f10) (G85). A systematic comparison between the two model approaches is currently lacking in scientific literature. The objective of our technical report is to provide such a comparison and thereby to contribute to an exchange of ideas, data and applications between users of the respective models. We found that the two models calculate a similar response of net photosynthesis to light and CO2, despite having considerable differences in their model structure and representation of physiological processes. The main difference in model structure is that the limitations to photosynthesis in the FvCB model are applied in parallel, whereas in the G85 model they are in series. We also present a lookup table to express parameters from the G85 model in terms of their equivalent FvCB parameters. This technical report thereby contributes to the comparison of models used across the Earth system and weather modeling communities. Key Points: We compare two leaf photosynthesis models, based on different biophysical assumptions, that are both used in Earth system and weather modelingThe two models calculate a near‐similar response of net photosynthesis to light and CO2 despite having considerable differences in their structure and process representation. This finding is significant across a wide range of naturally occurring photosynthetic capacities in vegetationThrough a flowchart, a comparison of photosynthetic response to light and CO2 and a parameter conversion table, we aim to enable more communication and exchange of data between users of the two models within the Earth system and weather modeling communities [ABSTRACT FROM AUTHOR]

The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation. Plain Language Summary: Clouds and forest in the Amazonian rainforest region are closely related. We investigated the final month of the Amazonian dry season in order to study interactions between the rainforest and the overlying atmosphere, placing particular emphasis on studying small spatiotemporal effects, such as that of cloud shading on photosynthesis. We employed three different methods: a cloud‐turbulence resolving model, a global weather model, and a complete set of canopy‐top and atmospheric observations. We holistically studied these relationships by systematically analyzing the characteristics of incoming solar radiation, evapotranspiration, and cloud cover and thickness. This comparison enabled us to make two relevant findings related to these diurnal carbon and cloud cycles. First, we observed that photosynthesis is offset by the soil carbon dioxide efflux earlier than the two models calculations. With respect to cloud formation and intensification, we showed quantitatively that the inefficiently modeled moisture transport leads to less active shallow convection, which may be insufficient to trigger deep convection. This systematic study paves the way for more comprehensive studies that would include more complex descriptions of microphysics processes and radiation, as well as chemistry and aerosol formation. Key Points: Explicit interactions between carbon uptake and clouds on subdaily and subkilometer scales are modeled and validatedNEE observations show an early afternoon shift from a CO2 sink to a source, whereas in the model results, the CO2 uptake is longerObservations and DALES results show enhancement of moisture transport at cloud base that favors triggering afternoon deep convection [ABSTRACT FROM AUTHOR]

One‐dimensional radiative transfer solvers are computationally much more efficient than full three‐dimensional radiative transfer solvers but do not account for the horizontal propagation of radiation and thus produce unrealistic surface irradiance fields in models that resolve clouds. Here, we study the impact of using a 3‐D radiative transfer solver on the direct and diffuse solar irradiance beneath clouds and the subsequent effect on the surface fluxes. We couple a relatively fast 3‐D radiative transfer approximation (TenStream solver) to the Dutch Atmosphere Large‐Eddy Simulation (DALES) model and perform simulations of a convective boundary layer over grassland with either 1‐D or 3‐D radiative transfer. Based on a single case study, simulations with 3‐D radiative transfer develop larger and thicker clouds, which we attribute mainly to the displaced clouds shadows. With increasing cloud thickness, the surface fluxes decrease in cloud shadows with both radiation schemes but increase beneath clouds with 3‐D radiative transfer. We find that with 3‐D radiative transfer, the horizontal length scales dominating the spatial variability of the surface fluxes are over twice as large as with 1‐D radiative transfer. The liquid water path and vertical wind velocity in the boundary layer are also dominated by larger length scales, suggesting that 3‐D radiative transfer may lead to larger convective thermals. Our case study demonstrates that 3‐D radiative effects can significantly impact dynamic heterogeneities induced by cloud shading. This may change our view on the coupling between boundary‐layer clouds and the surface and should be further tested for generalizability in future studies. Plain Language Summary: Solar radiation warms the surface and provides energy for evaporation and biological processes, resulting in the release of heat and moisture to the atmosphere. This upward transport of warm and moist air eventually leads to the formation of clouds, which then alter the spatial distribution of solar radiation at the surface by partly reflecting and absorbing the incoming sunlight. Most previous studies that simulated these complex interactions between clouds, solar radiation, and the surface used 1‐D radiation models. These are faster than 3‐D radiation models but produce unrealistic surface solar radiation fields by only considering the vertical propagation of radiation. In this study, we use a relatively fast 3‐D radiation model to simulate the formation of clouds and the surface heat and moisture fluxes. In our simulations, 3‐D radiation results in thicker and wider clouds than 1‐D radiation, predominantly because clouds no longer shade the surface beneath them when radiation propagates under an angle. Unlike in simulations with 1‐D radiation, we find higher surface fluxes below clouds than under clear‐sky and higher surface fluxes with increasing cloud thickness in simulations with 3‐D radiation. Our results show that 3‐D radiation may strongly impact the coupling between clouds and the land surface. Key Points: We couple a 3‐D radiative transfer solver to a LES with an interactive vegetated surfaceDisplaced cloud shadows with 3‐D radiative transfer result in thicker and larger cloudsHeterogeneities in the surface heat fluxes are larger with 3‐D than with 1‐D radiative transfer [ABSTRACT FROM AUTHOR]

The article presents a study which examined the relationships between rice architecture, physiology, and microclimate under present and future microenvironments as of March 2020 to determine the micrometeorological effects of rice variety choices in atmospheric carbon dioxide (CO2) and climate change. It discusses the use of the rice varieties Takanari and Koshihikari to determine the relation between plant physiology and microclimate.

The effects of increases in carbon dioxide and temperature on the vegetation‐atmosphere‐cloud interaction are studied with a bottom‐up approach. Using the 3‐D large‐eddy simulation technique coupled with a CO2‐sensitive dynamic plant physiological submodel, we aimed to spatially and temporally understand the surface and vegetation forcing on the coupled land‐atmosphere interactions in future scenarios. Four simulations were designed: a control simulation for current conditions, an enhanced carbon dioxide simulation (current +200 ppm), an elevated temperature simulation (current +2 K), and a simulation covering the combination of both elevations in temperature and CO2. With elevations in carbon dioxide, plant transpiration is reduced due to stomatal closure, resulting in reduced latent‐ and increased sensible heat fluxes. Although no effects on cloud cover were found in this simulation, the in‐cloud moisture flux was enhanced. Elevations in temperature yielded opposite results with reduced sensible and increased latent heat fluxes, which reduced the turbulent kinetic energy and buoyancy rates, thereby negatively impacting cloud formation. Our future climate mimicking simulation shows minimal changes in the regional energy balance due to offsetting effects between increased temperature and [CO2], while plant photosynthesis increased and transpiration decreased. The atmospheric boundary layer was drier, even though surface fluxes were very similar current conditions, thereby hampering cloud formation and development. Our results highlight the necessity of small scales and interactions, which require a bottom‐up approach to be able to accurately capture the nonlinear plant‐atmosphere interactions. Key Points: Ignoring subgrid‐scale processes can lead to serious misrepresentation of plant‐atmosphere interactions that drive the future atmosphereElevations in temperature and CO2 nonlinearly affect plant physiology that drive the surface energy balance and atmospheric stateIn future atmospheres, we find strong reductions in boundary layer cloud cover and moisture transport [ABSTRACT FROM AUTHOR]

Abstract: Carbon exchange over croplands plays an important role in the European carbon cycle over daily to seasonal time scales. A better description of this exchange in terrestrial biosphere models—most of which currently treat crops as unmanaged grasslands—is needed to improve atmospheric CO2 simulations. In the framework we present here, we model gross European cropland CO2 fluxes with a crop growth model constrained by grain yield observations. Our approach follows a two‐step procedure. In the first step, we calculate day‐to‐day crop carbon fluxes and pools with the WOrld FOod STudies (WOFOST) model. A scaling factor of crop growth is optimized regionally by minimizing the final grain carbon pool difference to crop yield observations from the Statistical Office of the European Union. In a second step, we re‐run our WOFOST model for the full European 25 × 25 km gridded domain using the optimized scaling factors. We combine our optimized crop CO2 fluxes with a simple soil respiration model to obtain the net cropland CO2 exchange. We assess our model's ability to represent cropland CO2 exchange using 40 years of observations at seven European FluxNet sites and compare it with carbon fluxes produced by a typical terrestrial biosphere model. We conclude that our new model framework provides a more realistic and strongly observation‐driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal and serve as a new cropland component in the CarbonTracker Europe inverse model. [ABSTRACT FROM AUTHOR]

Numerical simulations of the tropical mesoscales often exhibit a self-reinforcing feedback between cumulus convection and shallow circulations, which leads to the self-aggregation of clouds into large clusters. We investigate whether this basic feedback can be adequately captured by large-eddy simulations (LESs). To do so, we simulate the non-precipitating, cumulus-topped boundary layer of the canonical "BOMEX" case over a range of numerical settings in two models. Since the energetic convective scales underpinning the self-aggregation are only slightly larger than typical LES grid spacings, aggregation timescales do not converge even at rather high resolutions (<100 m). Therefore, high resolutions or improved sub-filter scale models may be required to faithfully represent certain forms of trade-wind mesoscale cloud patterns and self-aggregating deep convection in large-eddy and cloud-resolving models, and to understand their significance relative to other processes that organize the tropical mesoscales., (© 2022 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.)