Path Independence of Carbon Budgets When Meeting a Stringent Global Mean Temperature Target After an Overshoot

Katarzyna B. Tokarska; Kirsten Zickfeld; Joeri Rogelj

doi:10.1029/2019ef001312

Estimates of Uncertainty in Predictions of Global Mean Surface Temperature

Journal of Climate ◽

10.1175/jcli4012.1 ◽

2007 ◽

Vol 20 (5) ◽

pp. 843-855 ◽

Cited By ~ 19

Author(s):

J. A. Kettleborough ◽

B. B. B. Booth ◽

P. A. Stott ◽

M. R. Allen

Keyword(s):

Twentieth Century ◽

Energy Balance ◽

Temperature Change ◽

Radiative Forcing ◽

Balance Model ◽

Future Climate Change ◽

Model Parameters ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

Abstract A method for estimating uncertainty in future climate change is discussed in detail and applied to predictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of twentieth-century warming. These estimates are then projected forward in time using a linear, compact relationship between twentieth-century warming and twenty-first-century warming. This relationship is established from a large ensemble of energy balance models. By varying the energy balance model parameters an estimate is made of the error associated with using the linear relationship in forecasts of twentieth-century global mean temperature. Including this error has very little impact on the forecasts. There is a 50% chance that the global mean temperature change between 1995 and 2035 will be greater than 1.5 K for the Special Report on Emissions Scenarios (SRES) A1FI scenario. Under SRES B2 the same threshold is not exceeded until 2055. These results should be relatively robust to model developments for a given radiative forcing history.

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Analytical solution for the effect of increasing CO2 on global mean temperature

Nature ◽

10.1038/316657b0 ◽

1985 ◽

Vol 316 (6029) ◽

pp. 657-657 ◽

Cited By ~ 1

Author(s):

T. M. L. Wigley ◽

M. E. Schlesinger

Keyword(s):

Analytical Solution ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

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Variability of surface climate in simulations of past and future

10.5194/egusphere-egu2020-8592 ◽

2020 ◽

Author(s):

Kira Rehfeld ◽

Raphaël Hébert ◽

Juan M. Lora ◽

Marcus Lofverstrom ◽

Chris M. Brierley

Keyword(s):

Climate Variability ◽

Temperature Change ◽

Temperature Variability ◽

Last Interglacial ◽

Global Mean Temperature ◽

Extreme Precipitation Events ◽

Mean Temperature ◽

Project Phases ◽

Intercomparison Project ◽

Global Mean

It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios. Yet comparatively little is known about future changes in climate variability. We explore changes in climate variability over the large range of climates simulated in the framework the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phases 3 and 4 (PMIP3/4).&#160; This consists of time slice simulations for the Pliocene, Last Interglacial, Last Glacial Maximum, the Mid Holocene and idealized warming experiments (1% CO2 and abrupt 4xCO2), and encompasses climates with a range of 12&#176;C of global mean temperature change. We examine climate variability from different perspectives: from local interannual change, to coherent climate modes and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. Meanwhile only over tropical land is the change in the interannual temperature variability positively correlated to temperature change, and then weakly. In general, temperature variability is inversely related to mean temperature change - with analysis of power spectra demonstrating that this holds from intra-seasonal to multi-decadal timescales. We systematically investigate changes in the standard deviation of modes of climate variability. Overall, no generalisable pattern emerges. Several modes do show, sometimes weak, increasing variability with global mean temperature change (most notably the Atlantic Zonal Mode), but also the El Ni&#241;o/Southern Oscillation indices (NINO3.4 and NINO4). The annular modes in the Northern (Southern) hemisphere show only weakly increasing (decreasing) relationships. By compositing extreme precipitation events across the ensemble, we demonstrate that the atmospheric drivers dominating rainfall variability in Mediterranean climates persist throughout palaeoclimate and future simulations. The robust nature of the response of climate variability in model simulations, between both cold and warm climates and across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.

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Pacific variability reconciles observed and modelled global mean temperature increase since 1950

Climate Dynamics ◽

10.1007/s00382-020-05493-y ◽

2020 ◽

Author(s):

Martin B. Stolpe ◽

Kevin Cowtan ◽

Iselin Medhaug ◽

Reto Knutti

Keyword(s):

Global Warming ◽

Temperature Change ◽

Temperature Increase ◽

Global Temperature ◽

Global Mean Temperature ◽

Mean Temperature ◽

The Pacific ◽

Global Warming Hiatus ◽

Warming Hiatus ◽

Global Mean

Abstract Global mean temperature change simulated by climate models deviates from the observed temperature increase during decadal-scale periods in the past. In particular, warming during the ‘global warming hiatus’ in the early twenty-first century appears overestimated in CMIP5 and CMIP6 multi-model means. We examine the role of equatorial Pacific variability in these divergences since 1950 by comparing 18 studies that quantify the Pacific contribution to the ‘hiatus’ and earlier periods and by investigating the reasons for differing results. During the ‘global warming hiatus’ from 1992 to 2012, the estimated contributions differ by a factor of five, with multiple linear regression approaches generally indicating a smaller contribution of Pacific variability to global temperature than climate model experiments where the simulated tropical Pacific sea surface temperature (SST) or wind stress anomalies are nudged towards observations. These so-called pacemaker experiments suggest that the ‘hiatus’ is fully explained and possibly over-explained by Pacific variability. Most of the spread across the studies can be attributed to two factors: neglecting the forced signal in tropical Pacific SST, which is often the case in multiple regression studies but not in pacemaker experiments, underestimates the Pacific contribution to global temperature change by a factor of two during the ‘hiatus’; the sensitivity with which the global temperature responds to Pacific variability varies by a factor of two between models on a decadal time scale, questioning the robustness of single model pacemaker experiments. Once we have accounted for these factors, the CMIP5 mean warming adjusted for Pacific variability reproduces the observed annual global mean temperature closely, with a correlation coefficient of 0.985 from 1950 to 2018. The CMIP6 ensemble performs less favourably but improves if the models with the highest transient climate response are omitted from the ensemble mean.

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Exploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical–dynamical atmospheric model

Nonlinear Processes in Geophysics ◽

10.5194/npg-26-1-2019 ◽

2019 ◽

Vol 26 (1) ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Sonja Totz ◽

Stefan Petri ◽

Jascha Lehmann ◽

Erik Peukert ◽

Dim Coumou

Keyword(s):

Temperature Gradient ◽

Large Scale ◽

Planetary Waves ◽

Hadley Cell ◽

Storm Tracks ◽

Meridional Temperature Gradient ◽

Jet Streams ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

Abstract. Climate and weather conditions in the mid-latitudes are strongly driven by the large-scale atmosphere circulation. Observational data indicate that important components of the large-scale circulation have changed in recent decades, including the strength and the width of the Hadley cell, jets, storm tracks and planetary waves. Here, we use a new statistical–dynamical atmosphere model (SDAM) to test the individual sensitivities of the large-scale atmospheric circulation to changes in the zonal temperature gradient, meridional temperature gradient and global-mean temperature. We analyze the Northern Hemisphere Hadley circulation, jet streams, storm tracks and planetary waves by systematically altering the zonal temperature asymmetry, the meridional temperature gradient and the global-mean temperature. Our results show that the strength of the Hadley cell, storm tracks and jet streams depend, in terms of relative changes, almost linearly on both the global-mean temperature and the meridional temperature gradient, whereas the zonal temperature asymmetry has little or no influence. The magnitude of planetary waves is affected by all three temperature components, as expected from theoretical dynamical considerations. The width of the Hadley cell behaves nonlinearly with respect to all three temperature components in the SDAM. Moreover, some of these observed large-scale atmospheric changes are expected from dynamical equations and are therefore an important part of model validation.

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An Assessment of Global Macroeconomic Impacts Caused by Sea Level Rise Using the Framework of Shared Socioeconomic Pathways and Representative Concentration Pathways

Sustainability ◽

10.3390/su12093737 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3737

Author(s):

Osamu Nishiura ◽

Makoto Tamura ◽

Shinichiro Fujimori ◽

Kiyoshi Takahashi ◽

Junya Takakura ◽

...

Keyword(s):

Climate Change ◽

Sea Level Rise ◽

Sea Level ◽

Low Income ◽

Temperature Increase ◽

General Circulation ◽

Economic Losses ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

Coastal areas provide important services and functions for social and economic activities. Damage due to sea level rise (SLR) is one of the serious problems anticipated and caused by climate change. In this study, we assess the global economic impact of inundation due to SLR by using a computable general equilibrium (CGE) model that incorporates detailed coastal damage information. The scenario analysis considers multiple general circulation models, socioeconomic assumptions, and stringency of climate change mitigation measures. We found that the global household consumption loss proportion will be 0.045%, with a range of 0.027−0.066%, in 2100. Socioeconomic assumptions cause a difference in the loss proportion of up to 0.035% without greenhouse gas (GHG) emissions mitigation, the so-called baseline scenarios. The range of the loss proportion among GHG emission scenarios is smaller than the differences among the socioeconomic assumptions. We also observed large regional variations and, in particular, the consumption losses in low-income countries are, relatively speaking, larger than those in high-income countries. These results indicate that, even if we succeed in stabilizing the global mean temperature increase below 2 °C, economic losses caused by SLR will inevitably happen to some extent, which may imply that keeping the global mean temperature increase below 1.5 °C would be worthwhile to consider.

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Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

10.5194/gmd-2017-33 ◽

2017 ◽

Author(s):

Richard Wartenburger ◽

Martin Hirschi ◽

Markus G. Donat ◽

Peter Greve ◽

Andy J. Pitman ◽

...

Keyword(s):

Water Cycle ◽

Regional Climate ◽

Coupled Model ◽

Climate Extremes ◽

Global Mean Temperature ◽

Mean Temperature ◽

Intercomparison Project ◽

Projected Changes ◽

Regional Analyses ◽

Global Mean

Abstract. This article extends a previous study (Seneviratne et al., 2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global temperature targets, such as the 2 degree and 1.5 degree limits agreed within the 2015 Paris Agreement.

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Scenarios towards limiting global mean temperature increase below 1.5 °C

Nature Climate Change ◽

10.1038/s41558-018-0091-3 ◽

2018 ◽

Vol 8 (4) ◽

pp. 325-332 ◽

Cited By ~ 230

Author(s):

Joeri Rogelj ◽

Alexander Popp ◽

Katherine V. Calvin ◽

Gunnar Luderer ◽

Johannes Emmerling ◽

...

Keyword(s):

Temperature Increase ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

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A new approach for assessing climate change impacts in ecotron experiments

10.5194/bg-2019-267 ◽

2019 ◽

Author(s):

Inne Vanderkelen ◽

Jakob Zschleischler ◽

Lukas Gudmundsson ◽

Klaus Keuler ◽

Francois Rineau ◽

...

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Global Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

New Approach ◽

Global Mean Temperature ◽

Mean Temperature ◽

Global Mean

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.

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Crossbreeding Earth System Models with an Emulator for Regionally-optimized Land Temperature Projections

10.5194/egusphere-egu2020-9835 ◽

2020 ◽

Author(s):

Lea Beusch ◽

Lukas Gudmundsson ◽

Sonia I. Seneviratne

Keyword(s):

Grid Point ◽

Initial Condition ◽

Earth System ◽

Local Response ◽

System Models ◽

Spatially Resolved ◽

Global Mean Temperature ◽

Mean Temperature ◽

Earth System Models ◽

Global Mean

Earth System Models (ESMs) are invaluable tools to study the climate system&#8217;s response to a specific greenhouse gas emission scenario, but their projections are associated with internal climate variability and model uncertainty. To account for these uncertainties, large single-model initial-condition ensembles and multi-model ensembles are created and observations are used to constrain their projections. However, ensemble size is usually limited since ESM simulations are computationally costly. Climate change impact and integrated assessment models, on the other hand, could profit from more realizations which are consistent with observations and the associated improved sampling of the constrained phase space.Here, we employ MESMER, a Modular Earth System Model Emulator with spatially Resolved output, to generate stochastic realizations of land temperature field time series at a yearly resolution at a negligible computational cost (Beusch et al., 2019). MESMER successfully approximates large multi-model initial-condition ensembles on grid-point to regional scales if it is trained with runs from each contained ESM. Here, we create 1000 emulations per ESM for models of the 6th phase of the Coupled Model Intercomparison Project (CMIP6) covering the historical time period and the high-end emission scenario SSP585 (1870 &#8211; 2100) (Beusch et al., submitted). The resulting ensemble is referred to as a &#8220;superensemble&#8221;.The modular framework of MESMER opens new avenues for validating and constraining ESM ensembles (Beusch et al., submitted). Within the emulator, the local warming signal is expressed as a combination of the global mean temperature trend and the local response to this global trend. These two features can be validated separately by comparison to observations. It is found that ESMs which perform well in terms of global mean temperature trend do not necessarily perform well in terms of local response and vice versa. Additionally, different ESMs perform well in different regions. The most naive approach would be to base temperature projections solely on ESMs which perform well on both global and regional scales. However, this would result in discarding valuable information from many ESMs which perform well at only one of the scales. To circumvent this issue, we therefore propose to use MESMER to combine all global mean temperature trends with all local modules that are consistent with observations. Thereby, we obtain a regionally-optimized &#8220;crossbred&#8221; superensemble which constitutes a large recombined multi-model initial-condition ensemble and makes full use of all ESM features which are consistent with observations. The regionally diverse behavior of the crossbred superensemble highlights the importance of considering spatially resolved temperature projections.&#160;L. Beusch, L. Gudmundsson, and S. I. Seneviratne: Emulating Earth System Model Temperatures: from Global Mean Temperature Trajectories to Grid-point Level Realizations on Land, doi: 10.5194/esd-2019-34, 2019 (accepted for ESD).L. Beusch, L. Gudmundsson, and S. I. Seneviratne: Crossbreeding CMIP6 Earth System Models with an Emulator for Regionally-optimized Land Temperature Projections, submitted.

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