Abstract

Wind and turbulence effects on raindrop fall speeds were elucidated using field observations over a 2-yr time period. Motivations for this study include the recent observations of raindrop fall speed deviations from the terminal fall speed predictions (V_t ) based upon laboratory studies and the utilizations of these predictions in various important meteorological and hydrological applications. Fall speed (V_f ) and other characteristics of raindrops were observed using a high-speed optical disdrometer (HOD), and various rainfall and wind characteristics were observed using a 3D ultrasonic anemometer, a laser-type disdrometer, and rain gauges. A total of 26 951 raindrops were observed during 17 different rainfall events, and of these observed raindrops, 18.5% had a subterminal fall speed (i.e., 0.85V_t ≥ V_f ) and 9.5% had a superterminal fall speed (i.e., 1.15V_t ≤ V_f ). Our observations showed that distributions of sub- and superterminal raindrops in the raindrop size spectrum are distinct, and different physical processes are responsible for the occurrence of each. Vertical wind speed, wind shear, and turbulence were identified as the important factors, the latter two being the dominant ones, for the observed fall speed deviations. Turbulence and wind shear had competing effects on raindrop fall. Raindrops of different sizes showed different responses to turbulence, indicating multiscale interactions between raindrop fall and turbulence. With increasing turbulence levels, while the raindrops in the smaller end of the size spectrum showed fall speed enhancements, those in the larger end of the size spectrum showed fall speed reductions. The effect of wind shear was to enhance the raindrop fall speed toward a superterminal fall.

Abstract

A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC cloud model (MONC) using two averaging flavours, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky-Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-grey-zone and grey-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale and stability dependent profile of the subfilter turbulence length-scale across the chosen resolution range. At grey-zone resolutions the adaptive length scales can better represent the early pre-cloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result the initialisation and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary-layer which fails to ventilate moisture from the boundary layer resulting in the delayed spin-up of the cloud layer. Moreover, strong down-gradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for non-local transports, leading to over-energetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behaviour.

Abstract

“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, inter-scale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the mid-latidtudes and a pair of ECHAM5 models of the Tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with inter-model connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. For supermodels of both types, power spectra indicate enhanced inter-scale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.

Abstract

Airborne microphysical measurements of a frontal precipitation event in North China were used to evaluate five microphysics schemes for predicting the bulk properties of ice particles. They are the Morrison and Thompson schemes, which use predetermined categories, the 1-ice- and 2-ice-category configurations of the Predicted Particle Properties (P3) scheme and the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL) scheme, which model the evolution of particle properties, and the spectral bin fast version (SBM_fast) microphysics scheme within the Weather Research and Forecasting (WRF) model. WRF simulations with these schemes successfully reproduced the observed temperature and the liquid and total water content profiles at corresponding times and locations, allowing for a credible comparison of the predictions of particle properties with the aircraft measurements. The simulated results with the 1-ice-category P3 scheme are in good agreement with the observations for all the particle properties we examined. The 2-ice-category P3 scheme overestimates the spectrum width and underestimates the number concentration, which can be alleviated by reducing the ice collection efficiency. The simulation with the SBM_fast scheme deviates from the observed ice particle size distributions since the mass-diameter relationship of snow-sized particles adopted in this scheme may not be applicable to this stratiform cloud case.

Abstract

Much of our conceptual understanding of midlatitude atmospheric motion comes from two-layer quasi-geostrophic (QG) models. Traditionally, these QG models don’t include moisture, which accounts for an estimated 30-60% of the available energy of the atmosphere. The atmospheric moisture content is expected to increase under global warming, and therefore a theory for how moisture modifies atmospheric dynamics is crucial. We use a two-layer moist QG model with convective adjustment as a basis for analyzing how latent heat release and large-scale moisture gradients impact the scalings of a midlatitude system at the synoptic scale. In this model, the degree of saturation can be tuned independently of other moist parameters by enforcing a high rate of evaporation from the surface. This allows for study of the effects of latent heat release at saturation, without the intrinsic nonlinearity of precipitation. At saturation, this system is equivalent to the dry QG model under a rescaling of both length and time. This predicts that the most unstable mode shifts to smaller scales, the growth rates increase, and the inverse cascade extends to larger scales. We verify these results numerically and use them to verify a framework for the complete energetics of a moist system. We examine the spectral features of the energy transfer terms. This analysis shows that precipitation generates energy at small scales, while dry dynamics drive a significant broadening to larger scales. Cascades of energy are still observed in all terms, albeit without a clearly defined inertial range.

Abstract

The position and strength of the Hadley cell circulation determine the habitable zones in the tropics, yet our understanding of and ability to predict changes in the circulation is limited. One potentially important source of uncertainty is the dependence of the Hadley cell on turbulent drag. Here, the sensitivity of the Hadley cell and associated features such as the intertropical convergence zone to variations in the magnitude of the turbulent drag is explored with an atmospheric general circulation model in aquaplanet configuration. The tropical circulation and precipitation, and extratropical features such as the polar jet stream, displayed a strong sensitivity to the strength of the parameterized turbulent drag, with distinct low- or high-drag regimes. However, the response of the meridional heat transport produced a surprising departure from previous expectations: with greater drag, simulations exhibited less heat transport than low-drag simulations, which is in the opposite sense to that from Held and Hou. This may be due to the energetic constraints in the present model framework. When exposed to a uniform global warming, the response of the ITCZ precipitation depends strongly on the choice of drag, whereas most simulations exhibit a poleward expansion of the subtropics.

Abstract

Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius r _eff and cloud droplet number concentration N_c from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (N_c , r _eff, and LWC) via the prescribed bulk hygroscopicity of aerosols ( $\overline{\kappa }$ ) and aerosol size distribution characteristics. N_c , r _eff, and liquid water path (LWP) are positively correlated to $\overline{\kappa }$ and aerosol number concentration (N_a ) while cloud fractional cover (CFC) is insensitive to $\overline{\kappa }$ and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

Abstract

Asymmetric dynamics in tropical cyclones (TCs) are vital to understanding intensity change and convective distribution at landfall. The growth of barotropic-convective instability (e.g., mesovortices), vortical hot towers, and vortex Rossby waves (VRWs) have been considered through numerical modeling studies, often by mean-eddy partitioning of the tangential wind tendency. Unfortunately, few observational datasets exist that are sufficient for such study.

A University of Oklahoma Shared Mobile Atmospheric Research and Teaching Radar observed Major Hurricane Harvey (2017) as it intensified just before landfall near Port Aransas, TX. Combined with a coastal WSR-88D radar, dual-Doppler derived kinematic analyses were constructed every ~6 minutes at 1 km spatial resolution during hurricane Harvey’s landfall. In this study, observations of asymmetric mesovortices on the interior edge of Harvey’s eyewall are documented. The asymmetries promoted a dual exchange of vorticity in the TC eyewall and represent an example of an eddy mechanism of intensity change on various time scales. Considering the combined effects of resolvable asymmetries, we examine the change in the tangential wind as a function of mean-eddy kinematics before and after landfall. Before landfall, the low-level eddy contribution was positive to the low-level tangential wind tendency. Following landfall, the contribution from the low-level eddy became weakly positive to weakly negative. Finally, the evolution of some asymmetric features in Harvey’s eyewall are shown to manifest in a VRW-like response that initiates rainbands just outside of Harvey’s eyewall.

Abstract

For modern Earth, the annual-mean equatorial winds in the upper troposphere are flowing from east to west (i.e., easterly winds). This is mainly due to the deceleration effect of the seasonal cross-equatorial Hadley cells, against the relatively weaker acceleration effect of coupled Rossby and Kelvin waves excited from tropical convection and latent heat release. In this work, we examine the evolution of equatorial winds during the past 250 million years using one global Earth system model, the Community Earth System Model version 1.2.2 (CESM1.2.2). Three climatic factors different from the modern Earth—solar constant, atmospheric CO₂ concentration, and land–sea configuration—are considered in the simulations. We find that the upper-tropospheric equatorial winds change sign to westerly flows (called equatorial superrotation) in certain eras, such as 250–230 and 150–50 Ma. The strength of the superrotation is below 4 m s⁻¹, comparable to the magnitude of the present-day easterly winds. In general, this phenomenon occurs in a warmer climate within which the tropical atmospheric circulation shifts upward in altitude, stationary and/or transient eddies are relatively stronger, and/or the Hadley cells are relatively weaker, which in turn are due to the changes of the three factors, especially CO₂ concentration and land–sea configuration.

Abstract

Using detailed radar observation data for Typhoon Faxai, which made landfall in the Tokyo metropolitan area in 2019, a sensitivity test of the boundary layer (BL) schemes for a numerical weather prediction (NWP) model was conducted for gray-zone numerical simulations with a grid spacing of 250 m. We compared the results of our simulations using an NWP model with radar observations that captured the BL and the secondary circulation structures of Faxai. We used three BL schemes based on a Reynolds-averaged model, the gray-zone model, and a large-eddy simulation (LES) model: the Mellor–Yamada–Nakanishi–Niino level 3 (MYNN3) scheme, the Anisotropic Deardorff Model (ADM) scheme, and the Deardorff (DDF) scheme, respectively. The turbulence kinetic energy was the smallest, and the inflow near Earth’s surface the strongest, in the gray-zone simulation with the DDF scheme. This simulation also produced values for BL thickness and secondary circulation that were the closest to observation and reproduced horizontal roll structures whose scale was larger than the observation. Neither experiment using the MYNN3 scheme or the ADM scheme produced rolls, but the parameterized turbulence seemed to estimate the effects of the rolls. However, their BL heights were higher than observed, suggesting that the MYNN3 and ADM schemes are not appropriate for a 250 m grid simulation of the present case. These results are also confirmed against LES with 50 m grid spacing in which the DDF scheme is used. In summary, this study provides insights into the interpretation of the properties of BL schemes in the gray zone.