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1. Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

   https://doi.org/10.1029/2022MS003304  

   Thomas, Subin ; Yang, Fan ; Ovchinnikov, Mikhail ; Cantrell, Will ; Shaw, Raymond A. ( February 2023 , Journal of Advances in Modeling Earth Systems)

   The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights ofH = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale asH^1/3, consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales asH^2/3. Temperature and other scalar fluctuations scale asH^−3/7. Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., asH²for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

    

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2. Tropical Cyclogenesis From Self‐Aggregated Convection in Numerical Simulations of Rotating Radiative‐Convective Equilibrium

   https://doi.org/10.1029/2019MS002020  

   Carstens, Jacob D. ; Wing, Allison A. ( May 2020 , Journal of Advances in Modeling Earth Systems)

   In a modeled environment of rotating radiative‐convective equilibrium (RCE), convective self‐aggregation may take the form of spontaneous tropical cyclogenesis. We investigate the processes leading to tropical cyclogenesis in idealized simulations with a three‐dimensional cloud‐permitting model configured in rotating RCE, in which the background planetary vorticity is varied acrossf‐plane cases to represent a range of deep tropical and near‐equatorial environments. Convection is initialized randomly in an otherwise homogeneous environment, with no background wind, precursor disturbance, or other synoptic‐scale forcing. We examine the dynamic and thermodynamic evolution of cyclogenesis in these experiments and compare the physical mechanisms to current theories. All simulations with planetary vorticity corresponding to latitudes from 10°–20° generate intense tropical cyclones, with maximum wind speeds of 80 m s⁻¹or above. Time to genesis varies widely, even within a five‐member ensemble of 20° simulations, indicating large stochastic variability. Shared across the 10°–20° group is the emergence of a midlevel vortex in the days leading to genesis, which has dynamic and thermodynamic implications on its environment that facilitate the spin‐up of a low‐level vortex. Tropical cyclogenesis is possible in this model at values of Coriolis parameter as low as that representative of 1°. In these experiments, convection self‐aggregates into a quasicircular cluster, which then begins to rotate and gradually strengthen into a tropical storm, aided by strong near‐surface inflow that is already established days prior. Other experiments at these lower Coriolis parameters instead self‐aggregate into a nonrotating elongated band and fail to undergo cyclogenesis over the 100‐day simulation.

    

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3. Understanding Atypical Midlevel Wind Speed Maxima in Hurricane Eyewalls

   https://doi.org/10.1175/JAS-D-19-0191.1  

   Stern, Daniel P. ; Kepert, Jeffrey D. ; Bryan, George H. ; Doyle, James D. ( May 2020 , Journal of the Atmospheric Sciences)

   In tropical cyclones (TCs), the peak wind speed is typically found near the top of the boundary layer (approximately 0.5–1 km). Recently, it was shown that in a few observed TCs, the wind speed within the eyewall can increase with height within the midtroposphere, resulting in a secondary local maximum at 4–5 km. This study presents additional evidence of such an atypical structure, using dropsonde and Doppler radar observations from Hurricane Patricia (2015). Near peak intensity, Patricia exhibited an absolute wind speed maximum at 5–6-km height, along with a weaker boundary layer maximum. Idealized simulations and a diagnostic boundary layer model are used to investigate the dynamics that result in these atypical wind profiles, which only occur in TCs that are very intense (surface wind speed > 50 m s⁻¹) and/or very small (radius of maximum winds < 20 km). The existence of multiple maxima in wind speed is a consequence of an inertial oscillation that is driven ultimately by surface friction. The vertical oscillation in the radial velocity results in a series of unbalanced tangential wind jets, whose magnitude and structure can manifest as a midlevel wind speed maximum. The wavelength of the inertial oscillation increases with vertical mixing length l_∞in a turbulence parameterization, and no midlevel wind speed maximum occurs when l_∞is large. Consistent with theory, the wavelength in the simulations scales with (2 K/ I)^1/2, where K is the (vertical) turbulent diffusivity, and I²is the inertial stability. This scaling is used to explain why only small and/or strong TCs exhibit midlevel wind speed maxima.

    

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4. Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model

   https://doi.org/10.5194/acp-21-10413-2021  

   Im, Ulas ; Tsigaridis, Kostas ; Faluvegi, Gregory ; Langen, Peter L. ; French, Joshua P. ; Mahmood, Rashed ; Thomas, Manu A. ; von Salzen, Knut ; Thomas, Daniel C. ; Whaley, Cynthia H. ; et al ( January 2021 , Atmospheric Chemistry and Physics)

   null (Ed.)

   Abstract. The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990–2014) and future (2015–2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (>60∘ N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50 %, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO42- burdens decrease significantly in all simulations by 10 %–60 % following the reductions of 7 %–78 % in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030–2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol–radiation interactions (RFARI) of -0.39±0.01 W m−2, which is −0.08 W m−2 larger than the 1990–2010 mean forcing (−0.32 W m−2), of which -0.24±0.01 W m−2 was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of −0.35 to −0.40 W m−2 for the same period, which is −0.01 to −0.06 W m−2 larger than the 1990–2010 mean forcing of −0.35 W m−2. The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for −0.24 to −0.26 W m−2 of the net RFARI in 2030–2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6 ∘C in the Eclipse ensemble and 1.9 to 2.6 ∘C in the CMIP6 ensemble, compared to the 1990–2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change. 

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5. On the Sensitivity of Large-Eddy Simulations of the Atmospheric Boundary Layer Coupled with Realistic Large-Scale Dynamics

   https://doi.org/10.1175/MWR-D-23-0101.1  

   Giani, Paolo ; Crippa, Paola ( April 2024 , Monthly Weather Review)

   We present a new ensemble of 36 numerical experiments aimed at comprehensively gauging the sensitivity of nested large-eddy simulations (LES) driven by large-scale dynamics. Specifically, we explore 36 multiscale configurations of the Weather Research and Forecasting (WRF) Model to simulate the boundary layer flow over the complex topography at the Perdigão field site, with five nested domains discretized at horizontal resolutions ranging from 11.25 km to 30 m. Each ensemble member has a unique combination of the following input factors: (i) large-scale initial and boundary conditions, (ii) subgrid turbulence modeling in thegray zoneof turbulence, (iii) subgrid-scale (SGS) models in LES, and (iv) topography and land-cover datasets. We probe their relative importance for LES calculations of velocity, temperature, and moisture fields. Variance decomposition analysis unravels large sensitivities to topography and land-use datasets and very weak sensitivity to the LES SGS model. Discrepancies within ensemble members can be as large as 2.5 m s⁻¹for the time-averaged near-surface wind speed on the ridge and as large as 10 m s⁻¹without time averaging. At specific time points, a large fraction of this sensitivity can be explained by the different turbulence models in the gray zone domains. We implement a horizontal momentum and moisture budget routine in WRF to further elucidate the mechanisms behind the observed sensitivity, paving the way for an increased understanding of the tangible effects of the gray zone of turbulence problem.

   Several science and engineering applications, including wind turbine siting and operations, weather prediction, and downscaling of climate projections, call for high-resolution numerical simulations of the lowest part of the atmosphere. Recent studies have highlighted that such high-resolution simulations, coupled with large-scale models, are challenging and require several important assumptions. With a new set of numerical experiments, we evaluate and compare the significance of different assumptions and outstanding challenges in multiscale modeling (i.e., coupling large-scale models and high-resolution atmospheric simulations). The ultimate goal of this analysis is to put each individual assumption into the wider perspective of a realistic problem and quantify its relative importance compared to other important modeling choices.

    

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