scholarly journals Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models

2020 ◽  
Vol 33 (18) ◽  
pp. 7755-7775 ◽  
Author(s):  
Yue Dong ◽  
Kyle C. Armour ◽  
Mark D. Zelinka ◽  
Cristian Proistosescu ◽  
David S. Battisti ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Sensitivity ◽  
Atmospheric Model ◽  
Warm Pool ◽  
Cmip5 Models ◽  
Fast Time ◽  
Pattern Effect ◽  
Surface Warming ◽  
Early Portion ◽  
Radiative Feedbacks

AbstractRadiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. This study investigates intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the west Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.

Effective forcing in CMIP5 assuming nonconstant feedback parameter and linear response

2020 ◽  
Author(s):  
Hege-Beate Fredriksen
Keyword(s):  
Time Scales ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Temperature Response ◽  
Previous Method ◽  
Cmip5 Models ◽  
Nonlinear Feedback ◽  
Geophysical Research ◽  
Linear Temperature ◽  
Feedback Parameter

<p>We investigate a new algorithm for estimating time-evolving global forcing in climate models. The method is an extension of a previous method by Forster et al. (2013), but here we also allow for a globally nonlinear feedback. We assume the nonlinearity of this global feedback can be explained as a time-scale dependence, associated with linear temperature responses to the forcing on different time scales, as in Proistosescu and Huybers (2017). With this method we obtain stronger forcing estimates than previously believed for the representative concentration pathway experiments in CMIP5 models. The reason for the higher future forcing is that the global feedback has a higher magnitude at the smaller time scales than at the longer time scales – this is closely related to provided arguments for the equilibrium climate sensitivity showing changes with time.</p><p>We find also that the linear temperature response to our new forcing predicts the modelled response quite well, although the response is a little overestimated for some CMIP5 models. Finally, we discuss the assumptions made in our study, and consistency of our assumptions with other leading hypotheses for why the global feedback is nonlinear.</p><p> </p><p>References:</p><p>Forster, P. M., T. Andrews, P. Good, J. M. Gregory, L. S. Jackson, and M. Zelinka (2013), Evaluating adjusted forcing and model spread for historical and future scenarios in the cmip5 generation of climate models, Journal of Geophysical Research, 118, 1139–1150, doi:10.1002/jgrd.50174.</p><p>Proistosescu, C., and P. J. Huybers (2017), Slow climate mode reconciles historical and model-based estimates of climate sensitivity, Sci. Adv., 3, e1602, 821, doi:10.1126/sciadv.1602821</p>

Discrepancy in radiative feedbacks between models and observations tied to models inability to reproduce historical surface temperature patterns over the tropical Indo-Pacific.

2020 ◽  
Author(s):  
Cristian Proistosescu ◽  
Yue Dong ◽  
Malte Stuecker ◽  
Kyle Armour ◽  
Robb Wills ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Atmospheric Model ◽  
Natural Variability ◽  
Forced Response ◽  
Large Ensemble ◽  
Radiative Feedback ◽  
Wide Range ◽  
Radiative Feedbacks

<p>How much Earth warms in response to radiative forcing is determined by the net radiative feedback, which quantifies how much more energy is radiated to space for a given increase in surface temperature.  Estimates from present day observations of temperature and earth's energetic imbalance yield a strongly negative radiative feedback, or, equivalently, a very low climate sensitivity, which lies outside the range of climate sensitivity in coupled climate models. This discrepancy in radiative feedbacks can be linked to discrepancies between models and observations in the pattern of historical sea-surface temperature (SST) anomalies driving tropical atmospheric circulation and radiative damping.  Indeed, we find that an atmospheric model (CAM5) forced with observed SSTs yields a net feedback that is consistent with observational estimates, but up to three times more negative than that from the same period (2000-2017) in historical simulations where the same atmospheric model is coupled to a dynamical ocean model (CESM1). </p><p>To understand the role natural variability can play in this discrepancy, we compare the radiative feedbacks generated by the observed pattern of SSTs to those within the CESM1 large ensemble over the same period. The large ensemble produces a wide range of feedbacks due to internal variability alone. Yet, global radiative feedbacks (cloud feedbacks in particular) generated by observed warming patterns are far outside the range of natural variability in the large ensemble. Using both a Green's function approach, as well as a simple metric based on the East-West tropical pacific gradient, we show that none of the control simulations of CMIP5 climate models can generate sufficiently large natural variability to explain the discrepancy between models and observations. We conclude that the discrepancy in SST patterns, and the resulting discrepancy in radiative feedbacks, is caused by an deficiency in models' ability to simulate either natural variabilty or the forced response over the recent historical period. We will also show preliminary analysis from CMIP6 simulations.</p>

scholarly journals Dependence of Climate Response on Meridional Structure of External Thermal Forcing

2014 ◽  
Vol 27 (14) ◽  
pp. 5593-5600 ◽  
Author(s):  
Sarah M. Kang ◽  
Shang-Ping Xie
Keyword(s):  
Mixed Layer ◽  
Atmospheric Stability ◽  
Atmospheric Model ◽  
Thermal Forcing ◽  
Surface Warming ◽  
Mixed Layer Ocean ◽  
Radiative Feedbacks ◽  
The Tropics ◽  
The Given ◽  
Global Surface

Abstract This study shows that the magnitude of global surface warming greatly depends on the meridional distribution of surface thermal forcing. An atmospheric model coupled to an aquaplanet slab mixed layer ocean is perturbed by prescribing heating to the ocean mixed layer. The heating is distributed uniformly globally or confined to narrow tropical or polar bands, and the amplitude is adjusted to ensure that the global mean remains the same for all cases. Since the tropical temperature is close to a moist adiabat, the prescribed heating leads to a maximized warming near the tropopause, whereas the polar warming is trapped near the surface because of strong atmospheric stability. Hence, the surface warming is more effectively damped by radiation in the tropics than in the polar region. As a result, the global surface temperature increase is weak (strong) when the given amount of heating is confined to the tropical (polar) band. The degree of this contrast is shown to depend on water vapor– and cloud–radiative feedbacks that alter the effective strength of prescribed thermal forcing.

scholarly journals Attributing Historical and Future Evolution of Radiative Feedbacks to Regional Warming Patterns using a Green’s Function Approach: The Preeminence of the Western Pacific

2019 ◽  
Vol 32 (17) ◽  
pp. 5471-5491 ◽  
Author(s):  
Yue Dong ◽  
Cristian Proistosescu ◽  
Kyle C. Armour ◽  
David S. Battisti
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Climate Sensitivity ◽  
Climate Model ◽  
Global Climate Model ◽  
Western Pacific ◽  
Surface Warming ◽  
The Future ◽  
Radiative Feedbacks ◽  
The Western Pacific

Abstract Global radiative feedbacks have been found to vary in global climate model (GCM) simulations. Atmospheric GCMs (AGCMs) driven with historical patterns of sea surface temperatures (SSTs) and sea ice concentrations produce radiative feedbacks that trend toward more negative values, implying low climate sensitivity, over recent decades. Freely evolving coupled GCMs driven by increasing CO2 produce radiative feedbacks that trend toward more positive values, implying increasing climate sensitivity, in the future. While this time variation in feedbacks has been linked to evolving SST patterns, the role of particular regions has not been quantified. Here, a Green’s function is derived from a suite of simulations within an AGCM (NCAR’s CAM4), allowing an attribution of global feedback changes to surface warming in each region. The results highlight the radiative response to surface warming in ascent regions of the western tropical Pacific as the dominant control on global radiative feedback changes. Historical warming from the 1950s to 2000s preferentially occurred in the western Pacific, yielding a strong global outgoing radiative response at the top of the atmosphere (TOA) and thus a strongly negative global feedback. Long-term warming in coupled GCMs occurs preferentially in tropical descent regions and in high latitudes, where surface warming yields small global TOA radiation change but large global surface air temperature change, and thus a less-negative global feedback. These results illuminate the importance of determining mechanisms of warm pool warming for understanding how feedbacks have varied historically and will evolve in the future.

scholarly journals Potential Problems Measuring Climate Sensitivity from the Historical Record

2020 ◽  
Vol 33 (6) ◽  
pp. 2237-2248 ◽  
Author(s):  
Andrew E. Dessler
Keyword(s):  
Climate Sensitivity ◽  
Internal Variability ◽  
Historical Record ◽  
Cloud Feedback ◽  
Historical Period ◽  
Pattern Effect ◽  
Surface Warming ◽  
Two Factors ◽  
Low Cloud ◽  
The Impact

AbstractThis study investigates potential biases between equilibrium climate sensitivity inferred from warming over the historical period (ECShist) and the climate system’s true ECS (ECStrue). This paper focuses on two factors that could contribute to differences between these quantities. First is the impact of internal variability over the historical period: our historical climate record is just one of an infinity of possible trajectories, and these different trajectories can generate ECShist values 0.3 K below to 0.5 K above (5%–95% confidence interval) the average ECShist. Because this spread is due to unforced variability, I refer to this as the unforced pattern effect. This unforced pattern effect in the model analyzed here is traced to unforced variability in loss of sea ice, which affects the albedo feedback, and to unforced variability in warming of the troposphere, which affects the shortwave cloud feedback. There is also a forced pattern effect that causes ECShist to depart from ECStrue due to differences between today’s transient pattern of warming and the pattern of warming at 2×CO2 equilibrium. Changes in the pattern of warming lead to a strengthening low-cloud feedback as equilibrium is approached in regions where surface warming is delayed: the Southern Ocean, eastern Pacific, and North Atlantic near Greenland. This forced pattern effect causes ECShist to be on average 0.2 K lower than ECStrue (~8%). The net effect of these two pattern effects together can produce an estimate of ECShist as much as 0.5 K below ECStrue.

scholarly journals Sensitivity of Polar Amplification to Varying Insolation Conditions

2018 ◽  
Vol 31 (12) ◽  
pp. 4933-4947 ◽  
Author(s):  
Doyeon Kim ◽  
Sarah M. Kang ◽  
Yechul Shin ◽  
Nicole Feldl
Keyword(s):  
Energy Transport ◽  
Longwave Radiation ◽  
Atmospheric Model ◽  
Static Stability ◽  
Lapse Rate ◽  
Polar Surface ◽  
Surface Warming ◽  
Polar Amplification ◽  
Rate Feedback ◽  
Radiative Feedbacks

The mechanism of polar amplification in the absence of surface albedo feedback is investigated using an atmospheric model coupled to an aquaplanet slab ocean forced by a CO2 doubling. In particular, we examine the sensitivity of polar surface warming response under different insolation conditions from equinox (EQN) to annual mean (ANN) to seasonally varying (SEA). Varying insolation greatly affects the climatological static stability. The equinox condition, with the largest polar static stability, exhibits a bottom-heavy vertical profile of polar warming response that leads to the strongest polar amplification. In contrast, the polar warming response in ANN and SEA exhibits a maximum in the midtroposphere, which leads to only weak polar amplification. The midtropospheric warming maximum, which results from an increased poleward atmospheric energy transport in response to the tropics-to-pole energy imbalance, contributes to polar surface warming via downward clear-sky longwave radiation. However, it is cancelled by negative cloud radiative feedbacks locally. Furthermore, the polar lapse rate feedback, calculated from radiative kernels, is negative due to the midtropospheric warming maximum, and hence is not able to promote the polar surface warming. On the other hand, the polar lapse rate feedback in EQN is positive due to the bottom-heavy warming response, contributing to the strong polar surface warming. This contrast suggests that locally induced positive radiative feedbacks are necessary for strong polar amplification. Our results demonstrate how interactions among climate feedbacks determine the strength of polar amplification.

scholarly journals Slow and Fast Time Scales in Cardiomyocyte Beating

2019 ◽  
Vol 116 (3) ◽  
pp. 162a
Author(s):  
Ohad Cohen ◽  
Samuel Safran
Keyword(s):  
Time Scales ◽  
Fast Time

How do polar clouds and precipitation affect global warming?

2021 ◽  
Author(s):  
Jennifer Kay
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Research Problem ◽  
Cloud Feedback ◽  
Polar Regions ◽  
Unsolved Research Problem ◽  
Cloud Feedbacks ◽  
Surface Warming ◽  
Polar Clouds ◽  
Radiative Feedbacks

<p>Understanding the influence of clouds and precipitation on global warming remains an important unsolved research problem. This talk presents an overview of this topic, with a focus on recent observations, theory, and modeling results for polar clouds. After a general introduction, experiments that disable cloud radiative feedbacks or “lock the clouds” within a state‐of‐the‐art,  well‐documented, and observationally vetted climate model will be presented. Through comparison of idealized greenhouse warming experiments with and without cloud locking, the sign and magnitude cloud feedbacks can be quantified. Global cloud feedbacks increase both global and Arctic warming by around 25%. In contrast, disabling Arctic cloud feedbacks has a negligible influence on both Arctic and global surface warming. Do observations and theory support a positive global cloud feedback and a weak Arctic cloud feedback?  How does precipitation affect polar cloud feedbacks? What are the implications especially for climate change in polar regions?  </p>

Drivers of (non-)linear Eocene surface warming in the DeepMIP ensemble

2021 ◽  
Author(s):  
Sebastian Steinig ◽  
Jiang Zhu ◽  
Ran Feng ◽  
Keyword(s):  
Temperature Gradient ◽  
Heat Transport ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Large Scale ◽  
Surface Albedo ◽  
Early Eocene ◽  
Meridional Heat Transport ◽  
Surface Warming ◽  
Global Mean

<p>The early Eocene greenhouse represents the warmest interval of the Cenozoic and therefore provides a unique opportunity to understand how the climate system operates under elevated atmospheric CO<sub>2</sub> levels similar to those projected for the end of the 21st century. Early Eocene geological records indicate a large increase in global mean surface temperatures compared to present day (by ~14°C) and a greatly reduced meridional temperature gradient (by ~30% in SST). However, reproducing these large-scale climate features at reasonable CO<sub>2</sub> levels still poses a challenge for current climate models. Recent modelling studies indicate an important role for shortwave (SW) cloud feedbacks to drive increases in climate sensitivity with global warming, which helps to close the gap between simulated and reconstructed Eocene global warmth and temperature gradient. Nevertheless, the presence of such state-dependent feedbacks and their relative strengths in other models remain unclear.</p><p>In this study, we perform a systematic investigation of the simulated surface warming and the underlying mechanisms in the recently published DeepMIP ensemble. The DeepMIP early Eocene simulations use identical paleogeographic boundary conditions and include six models with suitable output: CESM1.2_CAM5, GFDL_CM2.1, HadCM3B_M2.1aN, IPSLCM5A2, MIROC4m and NorESM1_F. We advance previous energy balance analysis by applying the approximate partial radiative perturbation (APRP) technique to quantify the individual contributions of surface albedo, cloud and non-cloud atmospheric changes to the simulated Eocene top-of-the-atmosphere SW flux anomalies. We further compare the strength of these planetary albedo feedbacks to changes in the longwave atmospheric emissivity and meridional heat transport in the warm Eocene climate. Particular focus lies in the sensitivity of the feedback strengths to increasing global mean temperatures in experiments at a range of atmospheric CO<sub>2</sub> concentrations between x1 to x9 preindustrial levels.</p><p>Preliminary results indicate that all models that provide data for at least 3 different CO<sub>2</sub> levels show an increase of the equilibrium climate sensitivity at higher global mean temperatures. This is associated with an increase of the overall strength of the positive SW cloud feedback with warming in those models. This nonlinear behavior seems to be related to both a reduction and optical thinning of low-level clouds, albeit with intermodel differences in the relative importance of the two mechanisms. We further show that our new APRP results can differ significantly from previous estimates based on cloud radiative forcing alone, especially in high-latitude areas with large surface albedo changes. We also find large intermodel variability and state-dependence in meridional heat transport modulated by changes in the atmospheric latent heat transport. Ongoing work focuses on the spatial patterns of the climate feedbacks and the implications for the simulated meridional temperature gradients.</p>

Time-scale dependence of climate-carbon cycle feedbacks for weak perturbations in CMIP5 models

2021 ◽  
Author(s):  
Guilherme Torres Mendonça ◽  
Julia Pongratz ◽  
Christian Reick
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Time Scales ◽  
Radiative Forcing ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Ice Age ◽  
Cmip5 Models ◽  
Global Carbon ◽  
Different Time Scales

<p>The increase in atmospheric CO2 driven by anthropogenic emissions is the main radiative forcing causing climate change. But this increase is not only a result from emissions, but also from changes in the global carbon cycle. These changes arise from feedbacks between climate and the carbon cycle that drive CO2 into or out of the atmosphere in addition to the emissions, thereby either accelerating or buffering climate change. Therefore, understanding the contribution of these feedbacks to the global response of the carbon cycle is crucial in advancing climate research. Currently, this contribution is quantified by the α-β-γ framework (Friedlingstein et al., 2003). But this quantification is only valid for a particular perturbation scenario and time period. In contrast, a recently proposed generalization (Rubino et al., 2016) of this framework for weak perturbations quantifies this contribution for all scenarios and at different time scales. </p><p>Thereby, this generalization provides a systematic framework to investigate the response of the global carbon cycle in terms of the climate-carbon cycle feedbacks. In the present work we employ this framework to study these feedbacks and the airborne fraction in different CMIP5 models. We demonstrate (1) that this generalization of the α-β-γ framework consistently describes the linear dynamics of the carbon cycle in the MPI-ESM; and (2) how by this framework the climate-carbon cycle feedbacks and airborne fraction are quantified at different time scales in CMIP5 models. Our analysis shows that, independently of the perturbation scenario, (1) the net climate-carbon cycle feedback is negative at all time scales; (2) the airborne fraction generally decreases for increasing time scales; and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all time scales. This last result therefore emphasizes the need to improve our understanding of this particular feedback.</p><p><strong>References:</strong></p><p>P. Friedlingstein, J.-L. Dufresne, P. Cox, and P. Rayner. How positive is the feedback between climate change and the carbon cycle? Tellus B, 55(2):692–700, 2003.</p><p>M. Rubino, D. Etheridge, C. Trudinger, C. Allison, P. Rayner, I. Enting, R. Mulvaney, L. Steele, R. Langenfelds, W. Sturges, et al. Low atmospheric CO2 levels during the Little Ice Age due to cooling-induced terrestrial uptake. Nature Geoscience, 9(9):691–694, 2016.</p>

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