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Ming Zhao

Abstract

Atmospheric rivers (ARs), tropical storms (TSs), and mesoscale convective systems (MCSs) are important weather phenomena that often threaten society through heavy precipitation and strong winds. Despite their potentially vital role in global and regional hydrological cycles, their contributions to long-term mean and extreme precipitation have not been systematically explored at the global scale. Using observational and reanalysis data, and NOAA’s Geophysical Fluid Dynamics Laboratory’s new high-resolution global climate model, we quantify that despite their occasional (13%) occurrence globally, AR, TS, and MCS days together account for ∼55% of global mean precipitation and ∼75% of extreme precipitation with daily rates exceeding its local 99th percentile. The model reproduces well the observed percentage of mean and extreme precipitation associated with AR, TS, and MCS days. In an idealized global warming simulation with a homogeneous SST increase of 4 K, the modeled changes in global mean and regional distribution of precipitation correspond well with changes in AR/TS/MCS precipitation. Globally, the frequency of AR days increases and migrates toward higher latitudes while the frequency of TS days increases over the central Pacific and part of the south Indian Ocean with a decrease elsewhere. The frequency of MCS days tends to increase over parts of the equatorial western and eastern Pacific warm pools and high latitudes and decreases over most part of the tropics and subtropics. The AR/TS/MCS mean precipitation intensity increases by ∼5% K−1 due primarily to precipitation increases in the top 25% of AR/TS/MCS days with the heaviest precipitation, which are dominated by the thermodynamic component with the dynamic and microphysical components playing a secondary role.

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Ming Zhao

Abstract

Despite a relatively low climate sensitivity indicated by atmospheric-only simulations with uniform sea surface temperature (SST) warming, GFDL’s new climate model CM4.0 participating in CMIP6 and the seasonal-to-decadal prediction system SPEAR, both of which use an identical atmospheric model AM4.0, produce relatively high effective climate sensitivity (EffCS). The substantial increase in CM4.0’s EffCS is found to be caused by additional positive forcing associated with the CO2 fertilization effect on vegetation, enhanced positive feedback due to stronger reduction in Southern Hemisphere (SH) sea ice concentration (SIC), and clouds whose feedback depends on SST warming patterns. Compared to a SPEAR run using a static vegetation model (SPEAR-SV), CM4.0 produces roughly 30% larger EffCS, among which roughly 1/3 of the increase is due to dynamical vegetation with the rest due primarily to changes in SIC. Although cloud feedback does not explain the key feedback differences among CM4.0, SPEAR, and SPEAR-SV, it is the primary cause of the models’ increase (less negative) in TOA net feedback during the later period of their quadrupling CO2 simulations due to changes in their SST warming patterns. Moreover, CM4.0’s SST warming pattern and its effects on cloud feedback appear to be the leading cause of CM4.0’s EffCS increase compared to the earlier generation GFDL model ESM2M, which produces one of the lowest EffCS values among CMIP5 models. In comparison, CM4.0’s enhanced reduction in SH SICs plays a slightly less important role in its increase in EffCS compared to ESM2M.

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Ming Zhao

Abstract

A 50-km-resolution GFDL AM4 well captures many aspects of observed atmospheric river (AR) characteristics including the probability density functions of AR length, width, length–width ratio, geographical location, and the magnitude and direction of AR mean vertically integrated vapor transport (IVT), with the model typically producing stronger and narrower ARs than the ERA-Interim results. Despite significant regional biases, the model well reproduces the observed spatial distribution of AR frequency and AR variability in response to large-scale circulation patterns such as El Niño–Southern Oscillation (ENSO), the Northern and Southern Hemisphere annular modes (NAM and SAM), and the Pacific–North American (PNA) teleconnection pattern. For global warming scenarios, in contrast to most previous studies that show a large increase in AR length and width and therefore the occurrence frequency of AR conditions at a given location, this study shows only a modest increase in these quantities. However, the model produces a large increase in strong ARs with the frequency of category 3–5 ARs rising by roughly 100%–300% K−1. The global mean AR intensity as well as AR intensity percentiles at most percent ranks increases by 5%–8% K−1, roughly consistent with the Clausius–Clapeyron scaling of water vapor. Finally, the results point out the importance of AR IVT thresholds in quantifying modeled AR response to global warming.

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Ming Zhao

Abstract

This study explores connections between process-level modeling of convection and global climate model (GCM) simulated clouds and cloud feedback to global warming through a set of perturbed-physics and perturbed sea surface temperature experiments. A bulk diagnostic approach is constructed, and a set of variables is derived and demonstrated to be useful in understanding the simulated relationship. In particular, a novel bulk quantity, the convective precipitation efficiency or equivalently the convective detrainment efficiency, is proposed as a simple measure of the aggregated properties of parameterized convection important to the GCM simulated clouds. As the convective precipitation efficiency increases in the perturbed-physics experiments, both liquid and ice water path decrease, with low and middle cloud fractions diminishing at a faster rate than high cloud fractions. This asymmetry results in a large sensitivity of top-of-atmosphere net cloud radiative forcing to changes in convective precipitation efficiency in this limited set of models.

For global warming experiments, intermodel variations in the response of cloud condensate, low cloud fraction, and total cloud radiative forcing are well explained by model variations in response to total precipitation (or detrainment) efficiency. Despite significant variability, all of the perturbed-physics models produce a sizable increase in precipitation efficiency to warming. A substantial fraction of the increase is due to its convective component, which depends on the parameterization of cumulus mixing and convective microphysical processes. The increase in convective precipitation efficiency and associated change in convective cloud height distribution owing to warming explains the increased cloud feedback and climate sensitivity in recently developed Geophysical Fluid Dynamics Laboratory GCMs. The results imply that a cumulus scheme using fractional removal of condensate for precipitation and inverse calculation of the entrainment rate tends to produce a lower climate sensitivity than a scheme using threshold removal for precipitation and the entrainment rate formulated inversely dependent on convective depth.

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Wenhao Dong
,
Ming Zhao
,
Yi Ming
, and
V. Ramaswamy

Abstract

The characteristics of tropical mesoscale convective systems (MCSs) simulated with a finer-resolution (~50 km) version of the Geophysical Fluid Dynamics Laboratory (GFDL) AM4 model are evaluated by comparing with a comprehensive long-term observational dataset. It is shown that the model can capture the various aspects of MCSs reasonably well. The simulated spatial distribution of MCSs is broadly in agreement with the observations. This is also true for seasonality and interannual variability over different land and oceanic regions. The simulated MCSs are generally longer-lived, weaker, and larger than observed. Despite these biases, an event-scale analysis suggests that their duration, intensity, and size are strongly correlated. Specifically, longer-lived and stronger events tend to be bigger, which is consistent with the observations. The same model is used to investigate the response of tropical MCSs to global warming using time-slice simulations forced by prescribed sea surface temperatures and sea ice. There is an overall decrease in occurrence frequency, and the reduction over land is more prominent than over ocean.

Open access
Spencer A. Hill
,
Yi Ming
, and
Ming Zhao

Abstract

How the globally uniform component of sea surface temperature (SST) warming influences rainfall in the African Sahel remains insufficiently studied, despite mean SST warming being among the most robustly simulated and theoretically grounded features of anthropogenic climate change. A prior study using the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) AM2.1 atmospheric general circulation model (AGCM) demonstrated that uniform SST warming strengthens the prevailing northerly advection of dry Saharan air into the Sahel. The present study uses uniform SST warming simulations performed with 7 GFDL and 10 CMIP5 AGCMs to assess the robustness of this drying mechanism across models and uses observations to assess the physical credibility of the severe drying response in AM2.1. In all 17 AGCMs, mean SST warming enhances the free-tropospheric meridional moisture gradient spanning the Sahel and with it the Saharan dry-air advection. Energetically, this is partially balanced by anomalous subsidence, yielding decreased precipitation in 14 of the 17 models. Anomalous subsidence and precipitation are tightly linked across the GFDL models but not the CMIP5 models, precluding the use of this relationship as the start of a causal chain ending in an emergent observational constraint. For AM2.1, cloud–rainfall covariances generate radiative feedbacks on drying through the subsidence mechanism and through surface hydrology that are excessive compared to observations at the interannual time scale. These feedbacks also act in the equilibrium response to uniform warming, calling into question the Sahel’s severe drying response to warming in all coupled models using AM2.1.

Open access
Ming Zhao
and
Philip H. Austin

Abstract

This paper is the first in a two-part series in which the life cycles of numerically simulated shallow cumulus clouds are systematically examined. The life cycle data for six clouds with a range of cloud-top heights are isolated from an equilibrium trade cumulus field generated by a large-eddy simulation (LES) with a uniform resolution of 25 m. A passive subcloud tracer is used to partition the cloud life cycle transport into saturated and unsaturated components; the tracer shows that on average cumulus convection occurs in a region with time-integrated volume roughly 2 to 3 times that of the liquid-water-containing volume. All six clouds exhibit qualitatively similar vertical mass flux profiles with net downward mass transport at upper levels and net upward mass flux at lower levels. This downward mass flux comes primarily from the unsaturated cloud-mixed convective region during the dissipation stage and is evaporatively driven. Unsaturated negatively buoyant cloud mixtures dominate the buoyancy and mass fluxes in the upper portion of all clouds while saturated positively buoyant cloud mixtures dominate the fluxes at lower levels. Small and large clouds have distinct vertical profiles of heating/cooling and drying/moistening, with small clouds cooling and moistening throughout their depth, while larger clouds cool and moisten at upper levels and heat and dry at lower levels. The simulation results are compared to the predictions of conceptual models commonly used in shallow cumulus parameterizations.

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Ming Zhao
and
Philip H. Austin

Abstract

This paper is the second in a two-part series in which life cycles of six numerically simulated shallow cumulus clouds are systematically examined. The six clouds, selected from a single realization of a large-eddy simulation, grow as a series of pulses/thermals detached from the subcloud layer. All six clouds exhibit a coherent vortical circulation and a low buoyancy, low velocity trailing wake. The ascending cloud top (ACT), which contains this vortical circulation, is associated with a dynamic perturbation pressure field with high pressure located at the ascending frontal cap and low pressure below and on the downshear side of the maximum updrafts. Examination of the thermodynamic and kinematic structure, together with passive tracer experiments, suggests that this vortical circulation is primarily responsible for mixing between cloud and environment. As the cloud ACTs rise through the sheared environment, the low pressure, vortical circulation, and mixing are all strongly enhanced on the downshear side and weakened on the upshear side. Collapse of the ACT also occurs on the downshear side, with subsequent thermals ascending on the upshear side of their predecessors. The coherent core structure is maintained throughout the ACT ascent; mixing begins to gradually dilute the ACT core only in the upper half of the cloud's depth. The characteristic kinematic and dynamic structure of these simulated ACTs, together with their mixing behavior, corresponds closely to that of shedding thermals. These shallow simulated clouds, however, reach a maximum height of only about four ACT diameters so that ACT mixing differs from predictions of self-similar laboratory thermals.

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Isaac M. Held
and
Ming Zhao

Abstract

Rotating radiative–convective equilibrium, using the column physics and resolution of GCMs, is proposed as a useful framework for studying the tropical storm–like vortices produced by global models. These equilibria are illustrated using the column physics and dynamics of a version of the GFDL Atmospheric Model 2 (AM2) at resolutions of 220, 110, and 55 km in a large 2 × 104 km square horizontally homogeneous domain with fixed sea surface temperature and uniform Coriolis parameter. The large domain allows a number of tropical storms to exist simultaneously. Once equilibrium is attained, storms often persist for hundreds of days. The number of storms decreases as sea surface temperatures increase, while the average intensity increases. As the background rotation is decreased, the number of storms also decreases. At these resolutions and with this parameterization of convection, a dense collection of tropical storms is always the end state of moist convection in the cases examined.

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Ming Zhao
and
Philip H. Austin

Abstract

Episodic mixing and buoyancy-sorting (EMBS) models have been proposed as a physically more realistic alternative to entraining plume models of cumulus convection. Applying these models to shallow nonprecipitating clouds requires assumptions about the rate at which undilute subcloud air is eroded into the environment, an algorithm to calculate the eventual detrainment level of cloud–environment mixtures, and the probability distribution of mixing fraction. A diagnostic approach is used to examine the sensitivity of an EMBS model to these three closure assumptions, given equilibrium convection with known large-scale forcings taken from phase III of the Barbados Oceanographic Meteorological Experiment (BOMEX). The undilute eroding rate (UER) is retrieved and found to decrease exponentially with height above cloud base, suggesting a strong modulation by the cloud size distribution. The EMBS model is also used to calculate convective transport by individual clouds of varying thickness. No single cloud from this ensemble can balance the large-scale BOMEX forcing; the observed equilibrium requires a population of clouds with a cloud size distribution that is maximum for small clouds and decreases monotonically with cloud size.

The EMBS model depends sensitively on the assumptions governing the detrainment of positively buoyant mixtures. In particular, given the requirement that positively buoyant mixtures detrain at their neutral buoyancy level, there is no positive definite undilute eroding rate that is consistent with the BOMEX forcing. The model is less sensitive to the assumed distribution of cloud–environment mixtures, given a multiple mixing treatment of positively buoyant parcels and detrainment at the unsaturated neutral buoyancy level.

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