The climate response to anthropogenic forcing has long been one of the dominant uncertainties in predicting future climate change (Houghton et al, 2001). Many observationally-based estimates of climate sensitivity (S) have been presented in recent years, with most of them assigning significant probability to extremely high sensitivity, such as P(S>6C)>5%.
However, closer examination reveals that these estimates are based on a number of implausible implicit assumptions. We explain why these estimates cannot be considered credible and therefore have no place in the decision-making process. In fact, when basic probability theory is applied and reasonable assumptions are made, much greater confidence in a moderate value for S (~2.5C) is easily justified, with S very unlikely to be as high as 4.5C.
Equilibrium climate sensitivity (ECS) is a key predictor of climate change. However, it is not very well constrained, either by climate models or by observational data. The reasons for this include strong internal variability and forcing on many time scales. In practise this means that the 'equilibrium' will only be relative to fixing the slow feedback processes before comparing palaeoclimate sensitivity estimates with estimates from model simulations. In addition, information from the late Pleistocene ice age cycles indicates that the climate cycles between cold and warm regimes, and the clim…
The Earth's equilibrium climate sensitivity has received much attention because of its relevance and importance for global warming policymaking. This paper focuses on the Earth's \emph{thermal inertia time scale} which has received relatively little attention. The difference between the observed transient climate sensitivity and the equilibrium climate sensitivity is shown to be proportional to the thermal inertia time scale, and the numerical value of the proportionality factor is determined using recent observational data. Many useful policymaking insights can be extracted from the resulting…
Cenozoic temperature, sea level and CO2 co-variations provide insights into climate sensitivity to external forcings and sea level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise paleoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity 3 +/- 1°C for 4 W/m2 CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperat…
When evaluating the effect of CO2 changes on the earth's climate, it is widely assumed that instantaneous radiative forcing from a doubling of a given CO2 concentration (IRF2xCO2) is constant and that variances in climate sensitivity arise from differences in radiative feedbacks, or a dependence of these feedbacks on the climatological base-state. In this paper, we show that the IRF2xCO2 is not constant, but also depends on the climatological base-state, increasing by ~25% for every doubling of CO2, and has increased by ~10% since the pre-industrial era primarily due to stratospheric cooling, …
Palaeo data have been frequently used to determine the equilibrium (Charney) climate sensitivity $S^a$, and - if slow feedback processes (e.g. land ice-albedo) are adequately taken into account - they indicate a similar range as estimates based on instrumental data and climate model results. Most studies implicitly assume the (fast) feedback processes to be independent of the background climate state, e.g., equally strong during warm and cold periods. Here we assess the dependency of the fast feedback processes on the background climate state using data of the last 800 kyr and a conceptual cli…
A climate state close to a tipping point will have a degenerate linear response to perturbations, which can be associated with extreme values of the equilibrium climate sensitivity (ECS). In this paper we contrast linearized (`instantaneous') with fully nonlinear geometric (`two-point') notions of ECS, in both presence and absence of tipping points. For a stochastic energy balance model of the global mean surface temperature with two stable regimes, we confirm that tipping events cause the appearance of extremes in both notions of ECS. Moreover, multiple regimes with different mean sensitiviti…
The economic impacts of climate change are highly uncertain. Two of the most important uncertainties are the sensitivity of the climate system and the so-called damage functions, which relate climate change to economic damages and benefits. Despite broad awareness of these uncertainties, it is unclear which of them is most important, both on the global as well as the regional level. Here we apply different damage functions to data from climate models with vastly different climate sensitivities, and find that uncertainty in both climate sensitivity and economic damage per degree of warming are …
One of the most used metrics to gauge the effects of climate change is the equilibrium climate sensitivity, defined as the long-term (equilibrium) temperature increase resulting from instantaneous doubling of atmospheric CO$_2$. Since global climate models cannot be fully equilibrated in practice, extrapolation techniques are used to estimate the equilibrium state from transient warming simulations. Because of the abundance of climate feedbacks - spanning a wide range of temporal scales - it is hard to extract long-term behaviour from short-time series; predominantly used techniques are only c…
A review of some of the evidence for the IPCC's conclusion that doubling CO$_2$ levels will warm Earth significantly, in contrast to the claims of a recent article$^1$. Simply looking at raw temperature and CO$_2$ data over the past 150 years gives a transient response of roughly 2 K per doubling, in good agreement with IPCC conclusions based on far more extensive analysis. The 0.58 K of Ref. 1 is very unlikely.
Stochastic schemes, designed to represent unresolved sub-grid scale variability, are frequently used in short and medium-range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the 'stoc…
In this paper we derive a new formula for the global temperature change and major feedback portions in the climate response. In our earlier paper we calculated from the experimental values the sensitivity about ${\rm 0.058~K/(W/m^2)}$. This means the negative feedback which reduced the sensitivity by factor $2.13$. In this paper we explain and derive the major portions in the feedback coefficient using the observed energy budget at the top of the climate and on the surface of the earth. The results also support strongly our earlier results of the low climate sensitivity ($ΔT_{\rm 2CO_2}\approx…
Climate sensitivity is defined as the change in global mean equilibrium temperature after a doubling of atmospheric CO2 concentration and provides a simple measure of global warming. An early estimate of climate sensitivity, 1.5-4.5°C, has changed little subsequently, including the latest assessment by the Intergovernmental Panel on Climate Change. The persistence of such large uncertainties in this simple measure casts doubt on our understanding of the mechanisms of climate change and our ability to predict the response of the climate system to future perturbations. This has motivated continu…
Cloud processes are the largest source of uncertainty in quantifying the global temperature response to carbon dioxide rise. Still, the role of precipitation efficiency (PE) -- surface rain per unit column -- integrated condensation -- is yet to be quantified. Here we use 36 limited-domain cloud resolving simulations from the Radiative-Convective Equilibrium Model Intercomparison Project to show that they strongly imply climate warming will result in increases to net precipitation efficiency. We then analyze 35 General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Ph…
The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's respon…
Considerations of Earth climate sensitivity based on peculiarities of planetary heat capacity using system identification method: Runaway greenhouse effect scenario is still possible
Anthropogenic Heat in Urban Climate Systems: Forcing, Sensitivity, and Feedback
Institute of Science Tokyo（东京科学大学）；University College London（伦敦大学学院）；National Institute for Environmental Studies（国立环境研究所）；Hong Kong University of Science and Technology（香港科技大学）；Boston University（波士顿大学）；Arizona State University（亚利桑那州立大学）
The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate. However, the sensitivity of precipitation extremes to warming remains uncertain when convection is important, and it may be higher in the tropics than the extratropics. Several physical contributions govern the response of precipitation extremes. The thermodynamic contribution is rob…
Climate response metrics are used to quantify the Earth's climate response to anthropogenic changes of atmospheric CO2. Equilibrium Climate Sensitivity (ECS) is one such metric that measures the equilibrium response to CO2 doubling. However, both in their estimation and their usage, such metrics make assumptions on the linearity of climate response, although it is known that, especially for larger forcing levels, response can be nonlinear. Such nonlinear responses may become visible immediately in response to a larger perturbation, or may only become apparent after a long transient. In this pa…
We revisit a recent claim that the Earth's climate system is characterized by sensitive dependence to parameters; in particular, that the system exhibits an asymmetric, large-amplitude response to normally distributed feedback forcing. Such a response would imply irreducible uncertainty in climate change predictions and thus have notable implications for climate science and climate-related policy making. We show that equilibrium climate sensitivity in all generality does not support such an intrinsic indeterminacy; the latter appears only in essentially linear systems. The main flaw in the ana…
The two main drivers of climate change on sub-Milankovic time scales are re-assessed by means of a multiple regression analysis. Evaluating linear combinations of the logarithm of carbon dioxide concentration and the geomagnetic aa-index as a proxy for solar activity, we reproduce the sea surface temperature (HadSST) since the middle of the 19th century with an adjusted $R^2$ value of around 87 per cent for a climate sensitivity (of TCR type) in the range of 0.6 K until 1.6 K per doubling of CO$_2$. The solution of the regression is quite sensitive: when including data from the last decade, th…
Sensitivity of the ECMWF seasonal forecast model to CO2 and anthropogenic aerosol forcings: Experimental design and impact on climate trends
ECMWF（欧洲中期天气预报中心）；Department of Meteorology and Geophysics, University of Vienna（维也纳大学气象与地球物理系）；NCAS, University of Oxford, Atmospheric, Oceanic and Planetary Physics（牛津大学大气、海洋和行星物理国家环境科学研究中心）
Finite-Response Complementarity in Fluctuation Constraints on Climate Sensitivity
Yunnan Key Laboratory of Complex Systems and Brain-Inspired Intelligence, Kunming University of Science and Technology（昆明理工大学云南省复杂系统与脑启发智能重点实验室）；Faculty of Science, Kunming University of Science and Technology（昆明理工大学理学院）
We examine the results linking cosmic ray flux (CRF) variations to global climate change. We then proceed to study various periods over which there are estimates for the radiative forcing, temperature change and CRF variations relative to today. These include the Phanerozoic as a whole, the Cretaceous, the Eocene, the Last Glacial Maximum, the 20th century, as well as the 11-yr solar cycle. This enables us to place quantitative limits on climate sensitivity to both changes in the CRF, Phi_CR, and the radiative budget, F, under equilibrium. Under the assumption that the CRF is indeed a climate …
The atmospheres of rocky exoplanets are close to being characterized by astronomical observations, in part due to the commissioning of the James Webb Space Telescope. These observations compel us to understand exoplanetary atmospheres, in the voyage to find habitable planets. With this aim, we investigate the effect that CO$_2$ partial pressure (pCO$_2$) has on exoplanets' climate variability, by analyzing results from ExoCAM model simulations of the tidally locked TRAPPIST-1e exoplanet, an Earth-like aqua-planet and Earth itself. First, we relate the differences between the planets to their e…
There is as yet no theoretical framework to guide the search for emergent constraints. As a result, there are significant risks that indiscriminate data-mining of the multidimensional outputs from GCMs could lead to spurious correlations and less than robust constraints on future changes. To mitigate against this risk, Cox et al (hereafter CHW18) proposed a theory-motivated emergent constraint, using the one-box Hasselmann model to identify a linear relationship between ECS and a metric of global temperature variability involving both temperature standard deviation and autocorrelation ($Ψ$). A…
We consider the effect of different temporal error structures on the inference of equilibrium climate sensitivity\footnote{ECS is defined as the realized equilibrium surface warming---globally-averaged surface air temperature---for a doubling of CO$_2$}(ECS), in the context of an energy balance model (EBM) that is commonly employed in analyzing earth system models (ESM) and observations. We consider error structures ranging from uncorrelated (IID normal) to AR(1) to Gaussian correlation (Gaussian Process GP) to analyze the abrupt 4xCO$_2$ CMIP5 experiment in twenty-one different ESMs. For seve…
Ensemble forecasting is a technique devised to palliate sensitivity to initial conditions in nonlinear dynamical systems. The basic idea to avoid this sensitivity is to run the model many times under several slightly-different initial conditions, merging the resulting forecast in a combined product. We argue that this blending procedure is unphysical, and that a single trajectory should be chosen instead. We illustrate our case with a climate model. While most of the current climate simulations use the ensemble average technique as merging procedure, this paper shows that this choice presents …
Climate models are thought to solve boundary value problems unlike numerical weather prediction, which is an initial value problem. However, climate internal variability (CIV) is thought to be relatively important at near-term (0-30 year) prediction horizons, especially at higher resolutions. The recent availability of significant numbers of multi-model (MME) and multi-initial condition (MICE) ensembles allows for the first time a direct sensitivity analysis of CIV versus model response variability (MRV). Understanding the relative agreement and variability of MME and MICE ensembles for multip…
Machine Learning based Parameter Sensitivity of Regional Climate Models -- A Case Study of the WRF Model for Heat Extremes over Southeast Australia
Commonwealth Scientific and Industrial Research Organisation（联邦科学与工业研究组织）；Massachusetts Institute of Technology（麻省理工学院）；TU Delft（代尔夫特理工大学）；Harry Butler Institute, Murdoch University（默多克大学哈里·巴特勒研究所）；University of New South Wales（新南威尔士大学）；NSW Bushfire and Natural Hazards Research Centre（新南威尔士州丛林大火与自然灾害研究中心）
The teleconnection between European climate and Atlantic Multidecadal Variability (AMV) remains difficult to isolate in observations because of internal variability and anthropogenically-forced signals. Using model sensitivity experiments proposed within the CMIP6/DCPP-C framework, the wintertime AMV/Europe teleconnection is investigated in large ensembles of pacemaker-type simulations in the CNRM-CM5 global circulation model. To evaluate the sensitivity of the model response to the AMV amplitude, experiments with AMV-forcing pattern multiplied by 2 and 3 (hereafter 2xAMV and 3xAMV, respective…
We determine the volcano climate sensitivity and response time for the Mount Pinatubo eruption. This is achieved using observational measurements of the temperature anomalies of the lower troposphere and the aerosol optical density (AOD) in combination with a radiative forcing proxy for AOD. Using standard linear response theory we find sensitivity = 0.18 +- 0.04 K/(W/m2), which implies a negative feedback of -1.0 +- 0.4. The intrinsic response time is 5.8+-1.0 months. Both results are contrary to the conventional paradigm that includes long response times and positive feedback. In addition, w…
Precipitation and its response to forcings is an important aspect of planetary climate system. In this study, we examine the strength of precipitation in the experiments with different atmospheric masses and their response to surface warming, using three global atmospheric general circulation models (GCMs) and one regional cloud-resolving model (CRM). We find that precipitation is weaker when atmospheric mass is larger for a given surface temperature. Furthermore, the increasing rate of precipitation with increasing surface temperature under a larger atmospheric mass is smaller than that under…
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
Mila Quebec AI Institute（魁北克人工智能研究所）；McGill University（麦吉尔大学）；University of Osnabrück（奥斯纳布吕克大学）；University of Montreal（蒙特利尔大学）；Intel Labs（英特尔实验室）；German Aerospace Center（德国航空航天中心）；Technische Universität Berlin（柏林工业大学）
Paleoclimate data show that climate sensitivity is ~3 deg-C for doubled CO2, including only fast feedback processes. Equilibrium sensitivity, including slower surface albedo feedbacks, is ~6 deg-C for doubled CO2 for the range of climate states between glacial conditions and ice-free Antarctica. Decreasing CO2 was the main cause of a cooling trend that began 50 million years ago, large scale glaciation occurring when CO2 fell to 450 +/- 100 ppm, a level that will be exceeded within decades, barring prompt policy changes. If humanity wishes to preserve a planet similar to that on which civiliza…
Climate models are critical tools for developing strategies to manage the risks posed by sea-level rise to coastal communities. While these models are necessary for understanding climate risks, there is a level of uncertainty inherent in each parameter in the models. This model parametric uncertainty leads to uncertainty in future climate risks. Consequently, there is a need to understand how those parameter uncertainties impact our assessment of future climate risks and the efficacy of strategies to manage them. Here, we use random forests to examine the parametric drivers of future climate r…
For accurate forecast of climate change, sea ice mass balance, ocean circulation and sea- atmosphere interactions is required to have long term records of Sea Ice Thickness (SIT). Different approaches have been applied to retrieve SIT and only satellite altimetry, radar or laser, have been proven to provide hemispheric estimates of SIT distribution over a sufficient thickness range. To simplify the algorithm for SIT retrieval from RA, constant ice density has been applied until now, which lead to different results for derived SIT and SID, in dependence on input information for sea ice density …
Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest. We perform our study on a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO$_2$ increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic quantiti…
We explore the effects of seasonal variability for the climate of Earth-like planets as determined by the two parameters polar obliquity and orbital eccentricity using a general circulation model of intermediate complexity. In the first part of the paper we examine the consequences of different values of obliquity and eccentricity for the spatio-temporal patterns of radiation and surface temperatures as well as for the main characteristics of the atmospheric circulations. In the second part we analyse the associated implications for the habitability of planets close to the outer edge of the ha…
The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. We show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied to analyze the climatic response. We choose as test bed the Lorenz 96 model, which has a well-recognized prototypical value. We recapitulate the main aspects of the respon…
Spectral PCA (sPCA), in contrast to classical PCA, offers the advantage of identifying organized spatio-temporal patterns within specific frequency bands and extracting dynamical modes. However, the unavoidable tradeoff between frequency resolution and robustness of the PCs leads to high sensitivity to noise and overfitting, which limits the interpretation of the sPCA results. We propose herein a simple non-parametric implementation of the sPCA using the continuous analytic Morlet wavelet as a robust estimator of the cross-spectral matrices with good frequency resolution. To improve the interp…
