On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water would also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble

Cloud feedback mechanisms and their representation in global climate models

Cloud feedback—the change in top‐of‐atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO2 forcing simulated by global climate models (GCMs). We review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global‐mean cloud feedback in GCMs results from three main effects: (1) rising free‐tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high‐latitude low cloud optical depth (a negative SW effect). These cloud responses simulated by GCMs are qualitatively supported by theory, high‐resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper‐tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large‐scale subsidence, and lower‐tropospheric stability on the boundary‐layer moisture budget. High‐latitude low cloud optical depth increases are dominated by phase changes in mixed‐phase clouds. The causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection

Causes of Higher Climate Sensitivity in CMIP6 Models

Equilibrium climate sensitivity, the global surface temperature response to CO urn:x-wiley:grl:media:grl60047:grl60047-math-0001 doubling, has been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global climate models (GCMs), which attempt to represent all relevant physical processes, provide the most direct means of estimating climate sensitivity via CO urn:x-wiley:grl:media:grl60047:grl60047-math-0002 quadrupling experiments. Here we show that the closely related effective climate sensitivity has increased substantially in Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8–5.6 K across 27 GCMs and exceeding 4.5 K in 10 of them. This (statistically insignificant) increase is primarily due to stronger positive cloud feedbacks from decreasing extratropical low cloud coverage and albedo. Both of these are tied to the physical representation of clouds which in CMIP6 models lead to weaker responses of extratropical low cloud cover and water content to unforced variations in surface temperature. Establishing the plausibility of these higher sensitivity models is imperative given their implied societal ramifications

Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models

Increasing optical depth poleward of 45° is a robust response to warming in global climate models. Much of this cloud optical depth increase has been hypothesized to be due to transitions from ice‐dominated to liquid‐dominated mixed‐phase cloud. In this study, the importance of liquid‐ice partitioning for the optical depth feedback is quantified for 19 Coupled Model Intercomparison Project Phase 5 models. All models show a monotonic partitioning of ice and liquid as a function of temperature, but the temperature at which ice and liquid are equally mixed (the glaciation temperature) varies by as much as 40 K across models. Models that have a higher glaciation temperature are found to have a smaller climatological liquid water path (LWP) and condensed water path and experience a larger increase in LWP as the climate warms. The ice‐liquid partitioning curve of each model may be used to calculate the response of LWP to warming. It is found that the repartitioning between ice and liquid in a warming climate contributes at least 20% to 80% of the increase in LWP as the climate warms, depending on model. Intermodel differences in the climatological partitioning between ice and liquid are estimated to contribute at least 20% to the intermodel spread in the high‐latitude LWP response in the mixed‐phase region poleward of 45°S. It is hypothesized that a more thorough evaluation and constraint of global climate model mixed‐phase cloud parameterizations and validation of the total condensate and ice‐liquid apportionment against observations will yield a substantial reduction in model uncertainty in the high‐latitude cloud response to warming

A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

The extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m−2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m−2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks

A large ozone-circulation feedback and its implications for global warming assessments.

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever1. Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations1,2. Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks3-5.We thank the European Research Council for funding through the ACCI project, project number 267760. The model development was part of the QESM-ESM project supported by the UK Natural Environment Research Council (NERC) under contract numbers RH/H10/19 and R8/H12/124. We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the UK Met Office and NERC. A.C.M. acknowledges support from an AXA Postdoctoral Research Fellowship.This is the accepted manuscript. The final version is available from Nature Publishing at http://www.nature.com/nclimate/journal/v5/n1/full/nclimate2451.html

Sea-ice-free Arctic during the Last Interglacial supports fast future loss

The Last Interglacial (LIG), a warmer period 130-116 ka before present, is a potential analog for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4-5 °C higher than the preindustrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show the latest version of the fully-coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the longstanding puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice

Small global-mean cooling due to volcanic radiative forcing

In both the observational record and atmosphere-ocean general circulation model (AOGCM) simulations of the last ∼∼ 150 years, short-lived negative radiative forcing due to volcanic aerosol, following explosive eruptions, causes sudden global-mean cooling of up to ∼∼ 0.3 K. This is about five times smaller than expected from the transient climate response parameter (TCRP, K of global-mean surface air temperature change per W m−2 of radiative forcing increase) evaluated under atmospheric CO2 concentration increasing at 1 % yr−1. Using the step model (Good et al. in Geophys Res Lett 38:L01703, 2011. doi:10.​1029/​2010GL045208), we confirm the previous finding (Held et al. in J Clim 23:2418–2427, 2010. doi:10.​1175/​2009JCLI3466.​1) that the main reason for the discrepancy is the damping of the response to short-lived forcing by the thermal inertia of the upper ocean. Although the step model includes this effect, it still overestimates the volcanic cooling simulated by AOGCMs by about 60 %. We show that this remaining discrepancy can be explained by the magnitude of the volcanic forcing, which may be smaller in AOGCMs (by 30 % for the HadCM3 AOGCM) than in off-line calculations that do not account for rapid cloud adjustment, and the climate sensitivity parameter, which may be smaller than for increasing CO2 (40 % smaller than for 4 × CO2 in HadCM3)

Clouds, circulation and climate sensitivity

Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks