scholarly journals Variability of surface climate in simulations of past and future

2020 ◽  
Author(s):  
Kira Rehfeld ◽  
Raphaël Hébert ◽  
Juan M. Lora ◽  
Marcus Lofverstrom ◽  
Chris M. Brierley
Keyword(s):  
Climate Variability ◽  
Temperature Change ◽  
Rainfall Variability ◽  
Coupled Model ◽  
Temperature Variability ◽  
Global Mean Temperature ◽  
Extreme Precipitation Events ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Global Mean

Abstract. 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 by the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3). This consists of time slices of the Last Glacial Maximum, the Mid Holocene and idealized warming experiments (1 % CO2) and abrupt4×CO2), and encompasses climates with a range of 12 K of global mean temperature change. We examine climate variability from different perspectives: the local interannual change, 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, such as the North Atlantic Oscillation, with global mean temperature change. While several modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalisable pattern emerges. 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, 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.

scholarly journals Variability of surface climate in simulations of past and future

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

<p>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). <br>This consists of time slice simulations for the Pliocene, Last Interglacial, Last Glacial Maximum, the Mid Holocene and idealized warming experiments (1% CO<sub>2</sub> and abrupt 4xCO<sub>2</sub>), and encompasses climates with a range of 12°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 Niño/Southern Oscillation indices (NINO3.4 and NINO4). The annular modes in the Northern (Southern) hemisphere show only weakly increasing (decreasing) relationships. <br>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.</p>

scholarly journals Variability of surface climate in simulations of past and future

2020 ◽  
Vol 11 (2) ◽  
pp. 447-468 ◽  
Author(s):  
Kira Rehfeld ◽  
Raphaël Hébert ◽  
Juan M. Lora ◽  
Marcus Lofverstrom ◽  
Chris M. Brierley
Keyword(s):  
Climate Variability ◽  
Temperature Change ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Temperature Variability ◽  
Climate Modes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Global Mean

Abstract. 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. This study explores changes in climate variability over the large range of climates simulated by the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3), including time slices of the Last Glacial Maximum, the mid-Holocene, and idealized experiments (1 % CO2 and abrupt4×CO2). These states encompass climates within a range of 12 ∘C in global mean temperature change. We examine climate variability from the perspectives of local interannual change, 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. At the global scale, temperature variability is inversely related to mean temperature change on intra-seasonal to multidecadal timescales. This decrease is stronger over the oceans, while there is increased temperature variability over subtropical land areas (40∘ S–40∘ N) in warmer simulations. We systematically investigate changes in the standard deviation of modes of climate variability, including the North Atlantic Oscillation, the El Niño–Southern Oscillation, and the Southern Annular Mode, with global mean temperature change. While several climate modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalizable pattern emerges. By compositing extreme precipitation years across the ensemble, we demonstrate that the same large-scale modes influencing rainfall variability in Mediterranean climates persist throughout paleoclimate and future simulations. The robust nature of the response of climate variability, between cold and warm climates as well as across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.

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

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.

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

2017 ◽  
Vol 10 (9) ◽  
pp. 3609-3634 ◽  
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 fifth 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 mean temperature targets, such as the 2 and 1.5° limits agreed within the 2015 Paris Agreement.

scholarly journals Revisiting Whether Recent Surface Temperature Trends Agree with the CMIP5 Ensemble

2016 ◽  
Vol 29 (24) ◽  
pp. 8673-8687 ◽  
Author(s):  
Marena Lin ◽  
Peter Huybers
Keyword(s):  
Surface Temperature ◽  
Linear Trend ◽  
Coupled Model ◽  
Global Trends ◽  
Global Mean Temperature ◽  
Temperature Trends ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Slope Estimator ◽  
Global Mean

Abstract In an earlier study, a weaker trend in global mean temperature over the past 15 years relative to the preceding decades was characterized as significantly lower than those contained within the phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensemble. In this study, divergence between model simulations and observations is estimated using a fixed-intercept linear trend with a slope estimator that has one-third the noise variance compared to simple linear regression. Following the approach of the earlier study, where intermodel spread is used to assess the distribution of trends, but using the fixed-intercept trend metric demonstrates that recently observed trends in global mean temperature are consistent () with the CMIP5 ensemble for all 15-yr intervals of observation–model divergence since 1970. Significant clustering of global trends according to modeling center indicates that the spread in CMIP5 trends is better characterized using ensemble members drawn across models as opposed to using ensemble members from a single model. Despite model–observation consistency at the global level, substantial regional discrepancies in surface temperature trends remain.

scholarly journals Estimates of Uncertainty in Predictions of Global Mean Surface Temperature

2007 ◽  
Vol 20 (5) ◽  
pp. 843-855 ◽  
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.

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

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.

scholarly journals Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

2020 ◽  
Vol 13 (11) ◽  
pp. 5175-5190
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Phase 1 ◽  
Temperature Response ◽  
Earth System ◽  
Model Intercomparison ◽  
Radiative Forcings ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
Global Mean

Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

scholarly journals Nonlinear climate sensitivity and its implications for future greenhouse warming

2016 ◽  
Vol 2 (11) ◽  
pp. e1501923 ◽  
Author(s):  
Tobias Friedrich ◽  
Axel Timmermann ◽  
Michelle Tigchelaar ◽  
Oliver Elison Timm ◽  
Andrey Ganopolski
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Model Simulation ◽  
Coupled Model ◽  
Glacial Cycles ◽  
Global Mean Temperature ◽  
Surface Temperatures ◽  
Intercomparison Project ◽  
Future Warming ◽  
Global Mean

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations andSusing a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal thatSis strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.

scholarly journals Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

2013 ◽  
Vol 4 (1) ◽  
pp. 95-108 ◽  
Author(s):  
B. B. B. Booth ◽  
D. Bernie ◽  
D. McNeall ◽  
E. Hawkins ◽  
J. Caesar ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temperature Change ◽  
Climate Sensitivity ◽  
Global Climate ◽  
Global Climate Model ◽  
Design Decision ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Atmospheric Feedbacks ◽  
Global Mean

Abstract. We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

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