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Zhibo Zhang
,
David B. Mechem
,
J. Christine Chiu
, and
Justin A. Covert

Abstract

Because of the coarse grid size of Earth system models (ESMs), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision–coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 km and time steps on the order of 20–30 min. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semianalytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rainwater tendency simulated by the SCE is roughly linear for time steps smaller than 10 min, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 min. After considering all uncertainties, the grid-mean and time-averaged rainwater tendency based on the parameterization schemes is mostly within a factor of 4 of the local benchmark results simulated by SCE.

Open access
Georg S. Voelker
,
Gergely Bölöni
,
Young-Ha Kim
,
Günther Zängl
, and
Ulrich Achatz

Abstract

Parameterizations for internal gravity waves in atmospheric models are traditionally subject to a number of simplifications. Most notably, they rely on both neglecting wave propagation and advection in the horizontal direction (single-column assumption) and an instantaneous balance in the vertical direction (steady-state assumption). While these simplifications are well justified to cover some essential dynamic effects and keep the computational effort small, it has been shown that both mechanisms are potentially significant. In particular, the recently introduced Multiscale Gravity Wave Model (MS-GWaM) successfully applied ray-tracing methods in a novel type of transient but columnar internal gravity wave parameterization (MS-GWaM-1D). We extend this concept to a three-dimensional version of the parameterization (MS-GWaM-3D) to simulate subgrid-scale nonorographic internal gravity waves. The resulting global wave model—implemented into the weather forecast and climate code Icosahedral Nonhydrostatic (ICON)—contains three-dimensional transient propagation with accurate flux calculations, a latitude-dependent background source, and convectively generated waves. MS-GWaM-3D helps reproduce expected temperature and wind patterns in the mesopause region in the climatological zonal mean state and thus proves a viable internal gravity wave (IGW) parameterization. Analyzing the global wave action budget, we find that horizontal wave propagation is as important as vertical wave propagation. The corresponding wave refraction includes previously missing but well-known effects such as wave refraction into the polar jet streams. On a global scale, three-dimensional wave refraction leads to a horizontal flow-dependent redistribution of waves such that the structures of the zonal mean wave drag and consequently the zonal mean winds are modified.

Open access
Danyang Wang
and
Daniel R. Chavas

Abstract

Tropical cyclones are known to expand to an equilibrium size on the f plane, but the expansion process is not understood. In this study, an analytical model for tropical cyclone outer-size expansion on the f plane is proposed. Conceptually, the storm expands because the imbalance between latent heating and radiative cooling drives a lateral inflow that imports absolute vorticity. Volume-integrated latent heating increases more slowly with size than radiative cooling, and hence, the storm expands toward an equilibrium size. The predicted expansion rate is given by the ratio of the difference in size from its equilibrium value rt ,eq to an environmentally determined time scale τ rt of 10–15 days. The model is fully predictive if given a constant rt ,eq, which can also be estimated environmentally. The model successfully captures the first-order size evolution across a range of numerical simulation experiments in which the potential intensity and f are varied. The model predictions of the dependencies of lateral inflow velocity and expansion rate on latent heating rate are also compared well with numerical simulations. This model provides a useful foundation for understanding storm size dynamics in nature.

Open access
Sofia Menemenlis
,
Gabriel A. Vecchi
,
Kun Gao
,
James A. Smith
, and
Kai-Yuan Cheng

Abstract

The extratropical stage of Hurricane Ida (2021) brought extreme subdaily rainfall and devastating flooding to parts of eastern Pennsylvania, New Jersey, and New York. We investigate the predictability and character of this event using 31-member ensembles of perturbed initial condition hindcasts with the Tropical Atlantic version of GFDL’s System for High-resolution prediction on Earth-to-Local Domains (T-SHiELD), a ∼13-km global weather forecast model with a ∼3-km nested grid. At lead times of up to 4 days, the ensembles are able to capture the most extreme observed hourly and daily rainfall accumulations but are negatively biased in the spatial extent of heavy precipitation. Large intraensemble differences in the magnitudes and locations of simulated extremes suggest that although impacts were highly localized, risks were widespread. In Ida’s tropical stage, interensemble spread in extreme hourly rainfall is well predicted by large-scale moisture convergence; by contrast, in Ida’s extratropical stage, the most extreme rainfall is governed by mesoscale processes that exhibit chaotic and diverse forms across the ensembles. Our results are relevant to forecasting and communication in advance of extratropical transition and imply that flood preparedness efforts should account for the widespread possibility of severe localized impacts.

Significance Statement

After making landfall in Louisiana, Hurricane Ida (2021) transitioned to an extratropical storm which brought extreme rainfall and unprecedented flooding to parts of the northeastern United States. To what extent were these impacts knowable in advance? We use a numerical weather model with very high resolution to produce ensemble hindcasts—simulations of a past weather event initialized with tiny perturbations to the initial conditions, representing dozens of equally plausible versions of Ida’s extratropical stage. We find that the observed hourly and daily rainfall maxima fall within the simulated outcomes of ensembles initialized with lead times of about 4 days or less. The location and intensity of the heaviest rainfall vary widely across these ensembles, suggesting that many locations across the Northeast were exposed to some likelihood of extreme rainfall.

Open access
David C. Fritts
,
Ling Wang
,
Tom Lund
, and
Marvin A. Geller

Abstract

A companion paper by Fritts et al. reviews extensive evidence for Kelvin–Helmholtz instability (KHI) “tube” and “knot” (T&K) dynamics at multiple altitudes in the atmosphere and in the oceans that reveal these dynamics to be widespread. A second companion paper by Fritts and Wang reveals KHI T&K events at larger and smaller scales to arise on multiple highly stratified sheets in a direct numerical simulation (DNS) of idealized, multiscale gravity wave–fine structure interactions. These studies reveal the diverse environments in which KHI T&K dynamics arise and suggest their potentially ubiquitous occurrence throughout the atmosphere and oceans. This paper describes a DNS of multiple KHI evolutions in wide and narrow domains enabling and excluding T&K dynamics. These DNSs employ common initial conditions but are performed for decreasing Reynolds numbers (Re) to explore whether T&K dynamics enable enhanced KHI-induced turbulence where it would be weaker or not otherwise occur. The major results are that KHI T&K dynamics extend elevated turbulence intensities and energy dissipation rates ε to smaller Re. We expect these results to have important implications for improving parameterizations of KHI-induced turbulence in the atmosphere and oceans.

Significance Statement

Turbulence due to small-scale shear flows plays important roles in the structure and variability of the atmosphere and oceans extending to large spatial and temporal scales. New modeling reveals that enhanced turbulence accompanies Kelvin–Helmholtz instabilities (KHIs) that arise on unstable shear layers and exhibit what were initially described as “tubes” and “knots” (T&K) when they were first observed in early laboratory experiments. We perform new modeling to explore two further aspects of these dynamics: 1) can KHI T&K dynamics increase turbulence intensities compared to KHI without T&K dynamics for the same initial fields and 2) can KHI T&K dynamics enable elevated turbulence and energy dissipation extending to more viscous flows? We show here that the answer to both questions is yes.

Open access
Ji-Hee Yoo
,
Hye-Yeong Chun
, and
In-Sun Song

Abstract

This study investigates the in-situ generation of planetary waves (PWs) by zonally asymmetric gravity wave drag (GWD) in the mesosphere using a fully nonlinear general circulation model extending to the lower thermosphere. To isolate the effects of GWD, we establish a highly idealized but efficient framework that excludes stationary PWs propagating from the troposphere and in-situ PWs generated by barotropic and baroclinic instabilities. The GWD is prescribed in a zonally sinusoidal form with a zonal wavenumber (ZWN) of either 1 or 2 in the lower mesosphere of the Northern Hemisphere mid-latitude. Our idealized simulations clearly show that zonally asymmetric GWD generates PWs by serving as a nonconservative source (Z′) of linearized disturbance quasi-geostrophic potential vorticity (q′). While Z′ initially amplifies PWs through enhancing q′ tendency, the subsequent zonal advection of q′ gradually balances with Z′, thereby attaining steady-state PWs. The GWD-induced PWs predominantly have the same ZWN as the applied GWD with minor contributions from higher ZWN components attributed to nonlinear processes. The amplitude of the induced PWs increases in proportion with the magnitude of the peak GWD, while it decreases in proportion to the square of ZWN. Moreover, the amplitude of PWs increases as the meridional range of GWD expands and as GWD shifts toward lower latitudes. These PWs deposit substantial positive Eliassen-Palm flux divergences (EPFD) of ∼30 m/s/day at their origin and negative EPFD of 5–10 m/s/day during propagation. In addition, the in situ PWs exhibit interhemispheric propagation following westerlies that extend into the Southern Hemisphere.

Open access
Free access
Ming Cai
,
Xiaoming Hu
,
Jie Sun
,
Feng Ding
, and
Jing Feng

Abstract

This paper introduces a climate feedback kernel, referred to as the “energy gain kernel” (EGK). EGK allows for separating the net longwave radiative energy perturbations given by a Planck feedback matrix explicitly into thermal energy emission perturbations of individual layers and thermal radiative energy flux convergence perturbations at individual layers resulting from the coupled atmosphere–surface temperature changes in response to the unit forcing in individual layers. The former is represented by the diagonal matrix of a Planck feedback matrix and the latter by EGK. Elements of EGK are all positive, representing amplified energy perturbations at a layer where forcing is imposed and energy gained at other layers, both of which are achieved through radiative thermal coupling within an atmosphere–surface column. Applying EGK to input energy perturbations, whether external or internal due to responses of nontemperature feedback processes to external energy perturbations, such as water vapor and albedo feedbacks, yields their total energy perturbations amplified through radiative thermal coupling within an atmosphere–surface column. As the strength of EGK depends exclusively on climate mean states, it offers a solution for effectively and objectively separating control climate state information from climate perturbations for climate feedback studies. Given that an EGK comprises critical climate mean state information on mean temperature, water vapor, clouds, and surface pressure, we envision that the diversity of EGK across different climate models could provide insight into the inquiry of why, under the same anthropogenic greenhouse gas increase scenario, different models yield varying degrees of global mean surface warming.

Significance Statement

The wide range of 2.5°–4.0°C in global warming projections by climate models hinders our ability to predict its impacts. The newly introduced energy gain kernel (EGK) provides critical information for climate mean infrared opacity, which is collectively determined by climate mean temperature, water vapor, clouds, and surface pressure fields. EGK is directly derived from physical principles without additional definition. EGK captures the temperature feedback’s amplification of energy perturbations initiated from both external forcing and internal nontemperature feedback processes. EGK allows for disentangling positive and negative aspects of temperature feedback, rectifying the common misconception in existing temperature kernels that portray temperature feedback as predominantly negative. The diversity of EGK across different climate models may help explain their varying global warming degrees.

Open access
Lihui Ji
and
Ana P. Barros

Abstract

A 3D numerical model was built to serve as a virtual microphysics laboratory (VML) to investigate rainfall microphysical processes. One key goal for the VML is to elucidate the physical basis of warm precipitation processes toward improving existing parameterizations beyond the constraints of past physical experiments. This manuscript presents results from VML simulations of classical tower experiments of raindrop collisional collection and breakup. The simulations capture large raindrop oscillations in shape and velocity in both horizontal and vertical planes and reveal that drop instability increases with diameter due to the weakening of the surface tension compared with the body force. A detailed evaluation against reference experimental datasets of binary collisions over a wide range of drop sizes shows that the VML reproduces collision outcomes well including coalescence, and disk, sheet, and filament breakups. Furthermore, the VML simulations captured spontaneous breakup, and secondary coalescence and breakup. The breakup type, fragment number, and size distribution are analyzed in the context of collision kinetic energy, diameter ratio, and relative position, with a view to capture the dynamic evolution of the vertical microstructure of rainfall in models and to interpret remote sensing measurements.

Significance Statement

Presently, uncertainty in precipitation estimation and prediction remains one of the grand challenges in water cycle studies. This work presents a detailed 3D simulator to characterize the evolution of drop size distributions (DSDs), without the space and functional constraints of laboratory experiments. The virtual microphysics laboratory (VML) is applied to replicate classical tower experiments from which parameterizations of precipitation processes used presently in weather and climate models and remote sensing algorithms were derived. The results presented demonstrate that the VML is a robust tool to capture DSD dynamics at the scale of individual raindrops (precipitation microphysics). VML will be used to characterize DSD dynamics across scales for environmental conditions and weather regimes for which no measurements are available.

Open access
Free access