In this study, we explore the relationship between anvil cloud fraction and horizontal model resolution in small domain radiative-convective equilibrium (RCE) simulations, building on the findings of \citeA{jeevanjee22}. Using the System of Atmosphere Modeling (SAM) model, we find that finer resolutions yield higher anvil cloud fractions due to larger convective updrafts mass flux and increased mass detrainment at anvil levels. Employing two different microphysics schemes, we illustrate that finer resolution can enhance mass flux through either stronger cloud evaporation or weaker upper-troposphere stability, as the consequence of enhanced horizontal mixing. Moreover, we refine an analytical zero-buoyancy plume model to investigate the effects of adjusting entrainment rate and evaporation rate on vertical atmosphere profiles in a simple theoretical framework. Our solutions of the zero-buoyancy plume model suggest that stronger horizontal mixing can lead to larger convective updraft mass flux, consistent with the analysis in numerical simulations. We also observe the likelihood of atmospheric profiles converging at a grid size of approximately 100m, potentially as a result of converging entrainment rate and mixing strength. These insights have implications for global storm-resolving simulations, implying a possible convergence of high cloud and deep convection properties as the horizontal resolution approaches around 100m.

Observations reveal a clear difference in the intensity of deep convection over tropical land and ocean. This observed land-ocean contrast provides a natural benchmark for evaluating the fidelity of global storm-resolving models (GSRMs; global models with horizontal resolution on the order of kilometers), and GSRMs provide a potentially valuable tool for probing unresolved scientific questions about the origin of the observed land-ocean contrast. However, land-ocean differences in convective intensity have received relatively little attention in GSRM research. Here, we show that the strength of the land-ocean contrast simulated by GSRMs is strongly sensitive to details of GSRM implementations, and not clearly governed by any of several hypothesized drivers of the observed land-ocean contrast. We first examine DYAMOND Summer GSRM simulations, and show that only a subset produce a clear land-ocean contrast in the frequency of strong updrafts. We then show that the use of a sub-grid shallow convection scheme can determine whether or not the GSRM X-SHiELD produces a clear land-ocean contrast. Finally, we show that three hypothesized drivers of the observed land-ocean contrast all fail to explain why a land-ocean contrast is present in X-SHiELD simulations with sub-grid shallow convection disabled. These results provide encouraging evidence that GSRMs can mimic the observed land-ocean convective intensity contrast. However, they also show that their ability to do so can be sensitive to uncertain sub-grid parameterizations, and suggest that existing theory may not fully capture drivers of the land-ocean contrast simulated by some GSRMs.

As Earth warms, the tropopause is expected to rise, but predictions of its temperature change are less certain. One theory ties tropopause temperature to outgoing longwave radiation (OLR), but this contradicts simulations that exhibit a Fixed Tropopause Temperature (FiTT) even as OLR increases. Another theory ties tropopause temperature to upper tropospheric moisture, but is not precise enough to make quantitative predictions. Here, we argue that tropopause temperature, defined by where radiative cooling becomes negligible, is set by water vapor’s maximum spectroscopic absorption and Clausius-Clapeyron scaling. This “thermospectric constraint’ makes quantitative predictions for tropopause temperature that are borne out in single column and general circulation model experiments where the spectroscopy is modified and the tropopause changes in response. This constraint underpins the FiTT hypothesis, shows how tropopause temperature can decouple from OLR, suggests a way to relate the temperatures of anvil clouds and the tropopause, and shows how spectroscopy manifests in Earth’s general circulation.

A document by Nadir Jeevanjee. Click on the document to view its contents.

Estimates of Earth’s clear-sky longwave feedback from climate models and observations robustly give a value of approximately -2 W/m^2/K, suggesting that this feedback can be estimated from first principles. Here we derive an analytical model for Earth’s clear-sky longwave feedback based on a novel spectral decomposition that splits the feedback into components from surface emission, CO2, H2O, and the H2O continuum. Analytic expressions are given for each of these terms based on their underlying physics, and the model can also be framed in terms of Simpson’s Law and deviations therefrom. We validate the model by reproducing line-by-line radiative transfer calculations across a wide range of climates, as well as the spatial dependence of the clear-sky feedback from radiative kernels. The latter result motivates us to estimate the spatial pattern of Earth’s clear-sky longwave feedback from reanalysis data, which shows good agreement with climate model data. Together, these results show that Earth’s clear-sky longwave feedback, its spatial variations, and its state-dependence across past and future climates can be successfully understood from only a handful of physical principles.

Using model simulations, we demonstrate that the response of top-of-atmosphere radiative fluxes to localized tropical sea surface temperature (SST) perturbations exhibits numerous non-linearities. Most pronounced is an ‘asymmetry’ in the response to positive and negative SST perturbations. Additionally, we identify a ‘magnitude-dependence’ of response on the size of the SST perturbation. We then explain how these non-linearities arise as a robust consequence of convective quasi-equilibrium and weak (but non-zero) temperature gradients in the tropical free-troposphere, which we encapsulate in a ‘circus tent’ model of the tropical atmosphere. These results demonstrate that the climate response to SST perturbations is fundamentally non-linear, and highlight potential deficiencies in work which has assumed linearity in the response.

Tropical anvil clouds are an important player in Earth’s climate and climate sensitivity, but simulations of anvil clouds are uncertain. Here we pinpoint one source of uncertainty by demonstrating a marked increase of anvil cloud fraction with resolution in cloud-resolving simulations of radiative-convective equilibrium. This increase in cloud fraction can be traced back to the resolution dependence of horizontal mixing between clear and cloudy air. A mixing timescale is diagnosed for each simulation using the cloud fraction theory of Seeley et al. (2019), and is found to scale linearly with grid spacing, as expected from a simple scaling law. Thus mixing becomes more efficient with increasing resolution, generating more evaporation, decreased precipitation efficiency, greater mass flux, and hence greater detrainment and cloud fraction.The decrease in precipitation efficiency also yields a marked increase in relative humidity with resolution.

Tropical cyclone (TC) potential intensity (PI) theory has a well known form, consistent with a Carnot cycle interpretation of TC energetics, which relates PI to mean environmental conditions: the difference between surface and TC outflow temperatures and the air–sea enthalpy disequilibrium. PI has also been defined as a difference in convective available potential energy (CAPE) between two parcels, and quantitative assessments of future changes make use of a numerical algorithm based on this definition. Here, an analysis shows the conditions under which these Carnot and CAPE-based PI definitions are equivalent. There are multiple conditions, not previously enumerated, which in particular reveal a role for irreversible entropy production from surface evaporation. This mathematical analysis is verified by numerical calculations of PI’s sensitivity to large changes in surface-air relative humidity. To gain physical insight into the connection between the CAPE and Carnot formulations of PI, we use a recently developed analytic theory for CAPE to derive, starting from the CAPE-based definition, a new approximate formula for PI which nearly recovers the previous Carnot PI formula. The derivation shows that the difference in undilute buoyancies of saturated and environmental parcels which determines CAPE PI can in fact be expressed as a difference in the parcels’ surface moist static energy, providing a physical link between the Carnot and CAPE formulations of PI. This combination of analysis and physical interpretation builds confidence in previous numerical CAPE-based PI calculations that use climate model projections of the future tropical environment.

We spectrally resolve the conventional clear-sky temperature and water vapor feedbacks in an idealized single-column framework, and show that the well-known partial compensation of these feedbacks is actually due to an almost perfect cancellation of the spectral feedbacks at wavenumbers where H2O is optically thick. This cancellation is a natural consequence of ‘Simpson’s Law’, which says that H2O emission temperatures do not change with surface warming if RH is fixed. We provide an explicit formulation and validation of Simpson’s Law, and furthermore show that this spectral cancellation of feedbacks is naturally incorporated in the alternative RH-based framework proposed by Held and Shell (2012) and Ingram (2012, 2013), thus bolstering the case for switching from conventional to RH-based feedbacks. We also find a negligible RH-based clear-sky lapse rate feedback, suggesting that the impact of changing lapse rates depends crucially on whether relative or specific humidity is held fixed

Tropical convection is expected to decrease with warming, in a variety of ways. Specific incarnations of this idea include the ‘stability-iris’ hypothesis, as well as the decrease of both tropospheric and cloud-base mass fluxes with warming. This paper seeks to encapsulate these phenomena into three ‘rules’, and to explore their interrelationships and robustness, using both analytical reasoning as well as cloud-resolving and global climate simulations. We find that each of these rules can be derived analytically from the usual expression for clear-sky subsidence, so they all embody the same essential physics. But, these rules do not all provide the same degree of constraint: the stability-iris effect is not entirely robust due to relatively unconstrained microphysical degrees of freedom, and similarly the decrease in cloud-base mass flux is not entirely robust due to unconstrained effects of entrainment and detrainment. Tropospheric mass fluxes, on the other hand, are shown to be well-constrained theoretically, and when evaluated in temperature coordinates they exhibit a monotonic decrease with warming, at all levels and across a hierarchy of models.

The linearity of the global-mean outgoing longwave radiation (OLR) with surface temperature has important implications for climate sensitivity. Global climate models robustly produce a 1.9 W/m2/K of global-mean longwave clear-sky (LWCS) feedback. This number is consistent with idealized single-column atmospheric models. However, there is considerable spatial variation in the LWCS feedback including negative values over tropical oceans known as the “super-greenhouse effect” which is compensated by larger values in the subtropics/extratropics. Therefore it is unclear how the idealized model results are relevant for the global-mean LWCS feedback in comprehensive climate models. Here we show with a simple analytical theory and model output that the compensation of this spatial variability to produce a robust global-mean feedback can be explained by two facts: 1) when conditioned upon free-tropospheric column relative humidity (RH), the LWCS feedback is independent of RH, and 2) the global histogram of column RH is largely invariant under warming.

Understanding how the outgoing long-wave radiation (OLR) depends on surface temperature is a climate problem of long standing. Various studies have suggested that clear-sky OLR varies linearly with surface temperature, with a longwave clear-sky feedback that is independent of surface temperature and relative humidity. However, this uniformity lies in tension with the notion that humidity controls tropical stability (e.g. the “furnace” and “radiator fins” of Pierrehumbert, 1995). Here we explore the state-dependence of longwave clear-sky feedback as a function of both surface temperature and column relative humidity. We find that a strong relative humidity-dependence in the feedback emerges above 275 K, stemming from the closing of the H2O window. We construct a simple model for estimating the all-sky feedback and find that although clouds lower the zonal-mean longwave feedback, the dependence on humidity remains significant.