Search

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]

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]

Abstract: The convective boundary layer (CBL) is characterised by narrow vigorous thermals (updraft motions) surrounded by relatively large subsidence motions. In such a flow, reactants are normally segregated and their chemical transformations depend on the ability of atmospheric turbulence to mix them. This process is particularly important when the time-scale of the chemical transformation is similar to the turbulent characteristic time scale. For large atmospheric models, the segregation occurs at scales smaller than the grid length. As a result, instantaneous and homogeneous mixing of the reactants is normally assumed. This paper is aimed at the study of this assumption and to apply a parameterisation of an effective reaction rate accounting for the inefficient mixing due to convective turbulence in the CBL. We simulate a growing CBL with two models that use different physical assumptions. The first one, the so-called mixed-layer model, assumes an instantaneous and homogeneous mixing of the reactants in the boundary layer (BL). The second one, a three-dimensional large eddy simulation (LES) model, explicitly solves atmospheric turbulent motions and describes the heterogeneity of the mixing due to the turbulent characteristics of the CBL. By comparing their results in a simple case, i.e. a second-order chemical reaction, we show that the heterogeneous mixing due to convective turbulence has an important impact on the chemical transformations by slowing down the reaction rate. By introducing effective reaction rates through a parameterisation which accounts for this inefficient mixing, the mixed-layer model results improve significantly. We extend our study to a chemical mechanism that accounts for the ozone formation and depletion in the CBL. We show that the reaction rate can be slowed down or increased depending on whether the reactants are transported in opposite directions or not. We propose coefficients to be used to calculate the effective reaction rates in large-scale or mixed-layer models. [Copyright &y& Elsevier]

We investigate the interaction between the ammonium nitrate aerosol ( N A O 3 ) abundance and convective boundary-layer (CBL) dynamics by means of a large-eddy simulation (LES) framework. In our LES model the CBL dynamics is solved coupled with radiation, chemistry, and surface exchange. Concerning the aerosol coupling we assume a simplified representation that accounts for black carbon, aerosol water and inorganic aerosols, focusing on the semi-volatile ammonium nitrate aerosol within the CBL. The aerosol absorption and scattering of shortwave radiation is also taken into consideration. We use a data set of observations taken at the Cabauw Experimental Site for Atmospheric Research during the IMPACT/EUCAARI (European Integrated Project on Aerosol, Cloud, Climate, and Air Quality Interactions) campaign to successfully evaluate our LES approach. We highlight that our LES framework reproduces the observations of the ratio between gas-phase nitrate and total nitrate at the surface, with a diurnally-averaged overestimation of only ≈12%. We show that the dependence between gas-aerosol conversion of nitrate and CBL (thermo)dynamics produces highly non-linear concentration and turbulent flux vertical profiles. The flux profiles maximize at around 1/3 of the CBL. Close to the surface, we show that the outgassing of N A O 3 affects the dry deposition of nitrate. This outgassing is responsible for the high deposition velocities obtained from the concentration and flux measurements during observational campaigns. To account for the influence of CBL (thermo)dynamics on gas-aerosol conversion we propose an effective turbulent exchange coefficient based on an analysis of the flux budget equation of aerosol nitrate calculated by our LES. The implementation of this effective turbulent exchange coefficient in a 1D model leads to a better agreement with the LES results and with surface observations. [ABSTRACT FROM AUTHOR]