scholarly journals Climate Warming in Response to Emission Reductions Consistent with the Paris Agreement

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Fang Wang ◽  
Katarzyna B. Tokarska ◽  
Jintao Zhang ◽  
Quansheng Ge ◽  
Zhixin Hao ◽  
...  
Keyword(s):  
Climate Warming ◽  
Temperature Increase ◽  
Climate Model ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
The Arctic ◽  
Emission Reductions ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

To limit global warming to well below 2°C in accord with the Paris Agreement, countries throughout the world have submitted their Intended Nationally Determined Contributions (INDCs) outlining their greenhouse gas (GHG) mitigation actions in the next few decades. However, it remains unclear what the resulting climate change is in response to the proposed INDCs and subsequent emission reductions. In this study, the global and regional warming under the updated INDC scenarios was estimated from a range of comprehensive Earth system models (CMIP5) and a simpler carbon-climate model (MAGICC), based on the relationship of climate response to cumulative emissions. The global GHG emissions under the updated INDC pledges are estimated to reach 14.2∼15.0 GtC/year in 2030, resulting in a global mean temperature increase of 1.29∼1.55°C (median of 1.41°C) above the preindustrial level. By extending the INDC scenarios to 2100, global GHG emissions are estimated to be around 6.4∼9.0 GtC/year in 2100, resulting in a global mean temperature increase by 2.67∼3.74°C (median of 3.17°C). The Arctic warming is projected to be most profound, exceeding the global average by a factor of three by the end of this century. Thus, climate warming under INDC scenarios is projected to greatly exceed the long-term Paris Agreement goal of stabilizing the global mean temperature at to a low level of 1.5‐2.0°C above the pre-industrial. Our study suggests that the INDC emission commitments need to be adjusted and strengthened to bridge this warming gap.

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

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.

scholarly journals Scenarios towards limiting global mean temperature increase below 1.5 °C

2018 ◽  
Vol 8 (4) ◽  
pp. 325-332 ◽  
Author(s):  
Joeri Rogelj ◽  
Alexander Popp ◽  
Katherine V. Calvin ◽  
Gunnar Luderer ◽  
Johannes Emmerling ◽  
...  
Keyword(s):  
Temperature Increase ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

A new approach for assessing climate change impacts in ecotron experiments

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.

scholarly journals Uncertainty in the relationship between climate forcing and hydrological response in UK catchments

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals The relationship between climate forcing and hydrological response in UK catchments

2010 ◽  
Vol 7 (5) ◽  
pp. 7633-7667 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, it is likely that the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals Solar geoengineering to limit the rate of temperature change

2014 ◽  
Vol 372 (2031) ◽  
pp. 20140134 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ken Caldeira ◽  
David W. Keith
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Rate Of Change ◽  
Change Analysis ◽  
Rates Of Change ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Solar Geoengineering ◽  
Allowable Rate ◽  
Global Mean

Solar geoengineering has been suggested as a tool that might reduce damage from anthropogenic climate change. Analysis often assumes that geoengineering would be used to maintain a constant global mean temperature. Under this scenario, geoengineering would be required either indefinitely (on societal time scales) or until atmospheric CO 2 concentrations were sufficiently reduced. Impacts of climate change, however, are related to the rate of change as well as its magnitude. We thus describe an alternative scenario in which solar geoengineering is used only to constrain the rate of change of global mean temperature; this leads to a finite deployment period for any emissions pathway that stabilizes global mean temperature. The length of deployment and amount of geoengineering required depends on the emissions pathway and allowable rate of change, e.g. in our simulations, reducing the maximum approximately 0.3°C per decade rate of change in an RCP 4.5 pathway to 0.1°C per decade would require geoengineering for 160 years; under RCP 6.0, the required time nearly doubles. We demonstrate that feedback control can limit rates of change in a climate model. Finally, we note that a decision to terminate use of solar geoengineering does not automatically imply rapid temperature increases: feedback could be used to limit rates of change in a gradual phase-out.

On the scaling of climate impact indicators with global mean temperature increase: a case study of terrestrial ecosystems and water resources

2017 ◽  
Vol 141 (4) ◽  
pp. 775-782 ◽  
Author(s):  
Akemi Tanaka ◽  
Kiyoshi Takahashi ◽  
Hideo Shiogama ◽  
Naota Hanasaki ◽  
Yoshimitsu Masaki ◽  
...  
Keyword(s):  
Water Resources ◽  
Temperature Increase ◽  
Terrestrial Ecosystems ◽  
Climate Impact ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Impact Indicators ◽  
Global Mean

scholarly journals Carbon Dioxide Emission Pathways Avoiding Dangerous Ocean Impacts

2012 ◽  
Vol 4 (3) ◽  
pp. 212-229 ◽  
Author(s):  
K. Kvale ◽  
K. Zickfeld ◽  
T. Bruckner ◽  
K. J. Meissner ◽  
K. Tanaka ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Ocean Acidification ◽  
Sea Level Rise ◽  
Sea Level ◽  
Co2 Emissions ◽  
Climate Model ◽  
Ice Sheet ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract Anthropogenic emissions of greenhouse gases could lead to undesirable effects on oceans in coming centuries. Drawing on recommendations published by the German Advisory Council on Global Change, levels of unacceptable global marine change (so-called guardrails) are defined in terms of global mean temperature, sea level rise, and ocean acidification. A global-mean climate model [the Aggregated Carbon Cycle, Atmospheric Chemistry and Climate Model (ACC2)] is coupled with an economic module [taken from the Dynamic Integrated Climate–Economy Model (DICE)] to conduct a cost-effectiveness analysis to derive CO2 emission pathways that both minimize abatement costs and are compatible with these guardrails. Additionally, the “tolerable windows approach” is used to calculate a range of CO2 emissions paths that obey the guardrails as well as a restriction on mitigation rate. Prospects of meeting the global mean temperature change guardrail (2° and 0.2°C decade−1 relative to preindustrial) depend strongly on assumed values for climate sensitivity: at climate sensitivities >3°C the guardrail cannot be attained under any CO2 emissions reduction strategy without mitigation of non-CO2 greenhouse gases. The ocean acidification guardrail (0.2 unit pH decline relative to preindustrial) is less restrictive than the absolute temperature guardrail at climate sensitivities >2.5°C but becomes more constraining at lower climate sensitivities. The sea level rise and rate of rise guardrails (1 m and 5 cm decade−1) are substantially less stringent for ice sheet sensitivities derived in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report, but they may already be committed to violation if ice sheet sensitivities consistent with semiempirical sea level rise projections are assumed.

scholarly journals Exploring interaction effects from mechanisms between climate and land-use changes and the projected consequences on biodiversity

2021 ◽  
Vol 30 (12) ◽  
pp. 3685-3696
Author(s):  
Sarahi Nunez ◽  
Rob Alkemade
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Temperature Increase ◽  
Meta Analysis ◽  
Interaction Effects ◽  
Climate Change Effects ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

AbstractChanges in climate and land use are major drivers of biodiversity loss. These drivers likely interact and their mutual effects alter biodiversity. These interaction mechanisms are rarely considered in biodiversity assessments, as only the combined individual effects are reported. In this study, we explored interaction effects from mechanisms that potentially affect biodiversity under climate change. These mechanisms entail that climate-change effects on, for example, species abundance and species’ range shifts depend on land-use change. Similarly, land-use change impacts are contingent on climate change. We explored interaction effects from four mechanisms and projected their consequences on biodiversity. These interactions arise if species adapted to modified landscapes (e.g. cropland) differ in their sensitivity to climate change from species adapted to natural landscapes. We verified these interaction effects by performing a systematic literature review and meta-analysis of 42 bioclimatic studies (with different increases in global mean temperature) on species distributions in landscapes with varying cropland levels. We used the Fraction of Remaining Species as the effect-size metric in this meta-analysis. The influence of global mean temperature increase on FRS did not significantly change with different cropland levels. This finding excluded interaction effects between climate and landscapes that are modified by other land uses than cropping. Although we only assessed coarse climate and land-use patterns, global mean temperature increase was a good, significant model predictor for biodiversity decline. This emphasizes the need to analyse interactions between land-use and climate-change effects on biodiversity simultaneously in other modified landscapes. Such analyses should also integrate other conditions, such as spatial location, adaptive capacity and time lags. Understanding all these interaction mechanisms and other conditions will help to better project future biodiversity trends and to develop coping strategies for biodiversity conservation.

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