scholarly journals Ensembles and probabilities: a new era in the prediction of climate change

2007 ◽  
Vol 365 (1857) ◽  
pp. 1957-1970 ◽  
Author(s):  
Mat Collins
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Central Importance ◽  
New Era ◽  
Sources Of Uncertainty ◽  
New Approaches ◽  
Physically Based ◽  
Reduce Emissions ◽  
Impacts Of Climate Change

Predictions of future climate are of central importance in determining actions to adapt to the impacts of climate change and in formulating targets to reduce emissions of greenhouse gases. In the absence of analogues of the future, physically based numerical climate models must be used to make predictions. New approaches are under development to deal with a number of sources of uncertainty that arise in the prediction process. This paper introduces some of the concepts and issues in these new approaches, which are discussed in more detail in the papers contained in this issue.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

The Threats to Food Security

2019 ◽  
pp. 61-84
Author(s):  
Gordon Conway ◽  
Ousmane Badiane ◽  
Katrin Glatzel
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Nitrous Oxide ◽  
Food Security ◽  
Greenhouse Gases ◽  
Acute Stress ◽  
Rural Livelihoods ◽  
Farm Household ◽  
Impacts Of Climate Change ◽  
Socioeconomic Challenges

This chapter explores threats to food security. It reveals many challenges arising from a range of threats external to the farm household, including severe biological threats from pests, disease, and weeds. Moreover, healthy, fertile soils are the cornerstone of food security and rural livelihoods, but African soils are degrading. Water is just as important for the productivity of plants, and lack of water leads to chronic and acute stress. Indeed, Africa is already battling the impacts of climate change. Rising temperatures and variable rainfall are increasing the exposure of smallholders to drought, famine, and disease. Agriculture is an important emitter of greenhouse gases (GHGs), not only carbon dioxide but also such powerful gases as methane and nitrous oxide. In addition, there are often severe socioeconomic challenges, including unstable and high prices of basic commodities. Finally, conflicts cause disruption to food security.

scholarly journals Assessment of the impacts of climate change on maize production in the Wami Ruvu basin of Tanzania

2016 ◽  
Vol 8 (1) ◽  
pp. 142-164 ◽  
Author(s):  
Philbert Luhunga ◽  
Ladslaus Chang'a ◽  
George Djolov
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Projections ◽  
Intergovernmental Panel ◽  
Lower Altitude ◽  
Rcp 8.5 ◽  
Maize Yields ◽  
The Impact ◽  
Impacts Of Climate Change

The IPCC (Intergovernmental Panel on Climate Change) assessment reports confirm that climate change will hit developing countries the hardest. Adaption is on the agenda of many countries around the world. However, before devising adaption strategies, it is crucial to assess and understand the impacts of climate change at regional and local scales. In this study, the impact of climate change on rain-fed maize (Zea mays) production in the Wami-Ruvu basin of Tanzania was evaluated using the Decision Support System for Agro-technological Transfer. The model was fed with daily minimum and maximum temperatures, rainfall and solar radiation for current climate conditions (1971–2000) as well as future climate projections (2010–2099) for two Representative Concentration Pathways: RCP 4.5 and RCP 8.5. These data were derived from three high-resolution regional climate models, used in the Coordinated Regional Climate Downscaling Experiment program. Results showed that due to climate change future maize yields over the Wami-Ruvu basin will slightly increase relative to the baseline during the current century under RCP 4.5 and RCP 8.5. However, maize yields will decline in the mid and end centuries. The spatial distribution showed that high decline in maize yields are projected over lower altitude regions due to projected increase in temperatures in those areas.

Book Reviews

2010 ◽  
Vol 48 (3) ◽  
pp. 781-786
Keyword(s):  
Climate Change ◽  
London School ◽  
New Era ◽  
The World ◽  
The Creation ◽  
Reduce Emissions ◽  
London School Of Economics ◽  
The Impact ◽  
Research Institute

Gary Yohe of Wesleyan University reviews “The Global Deal: Climate Change and the Creation of a New Era of Progress and Prosperity” by Nicholas Stern,. The EconLit Abstract of the reviewed work begins “Considers how to create a global deal to take action to reduce the impact and damage of climate change in the world. Discusses why there is a problem and how we can deal with it; the dangers; how emissions can be reduced, and at what cost; adapting to climate change; ethics, discounting, and the case for action; policies to reduce emissions; individuals, firms, communities--the power of example; the structure of a global deal; building and sustaining action; and a planet in peril. Stern is IG Patel Chair in Economics and Government and Chair of the Grantham Research Institute on Climate Change at the London School of Economics. Bibliography; index.”

scholarly journals Climate Change and "historical responsibilities"

2012 ◽  
Vol 15 (1) ◽  
pp. 201-206 ◽  
Author(s):  
José Goldemberg ◽  
Patricia Maria Guardabassi
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Co2 Emissions ◽  
Relative Contribution ◽  
Historical Responsibility ◽  
Copenhagen Accord ◽  
Reduce Emissions ◽  
Climate Convention

The historical responsibility of countries listed in the Annex I of the Convention on Climate Change has been used extensively as a justification for the lack of action of countries not included in Annex I to reduce their greenhouse gas emissions. We analyzed the contribution of non-Annex I countries to the CO2 emissions in the period 1850 - 2006 to assess their relative contribution to total CO2 emissions. In the period 1980 - 2006 non-Annex I countries represented 44% of the total but this contribution increased in the period 1990 - 2006 to 48%. If we extrapolate present trends to 2020 they will represent 56% in the period 1990 - 2020. The "historical responsibility" of Annex I countries is therefore decreasing. If we take 1990 as the starting year in which the Climate Convention recognized clearly that greenhouse gases are interfering dangerously with the climate system, it becomes very difficult to attribute "blame" and "guilt" to Annex I for their historical contributions. It becomes also quite clear the need of non-Annex I countries to engage with Annex I countries in the effort to reduce emissions. The Copenhagen Accord has no mention of "historical responsibilities".

scholarly journals The Coming Global Climate–Technology Revolution

2009 ◽  
Vol 23 (2) ◽  
pp. 53-75 ◽  
Author(s):  
Scott Barrett
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Global Climate ◽  
New Technology ◽  
Manhattan Project ◽  
Address Climate Change ◽  
Short Period ◽  
Technology Revolution ◽  
Reduce Emissions ◽  
Dangerous Climate Change

Emissions of CO2 and other greenhouse gases can be reduced significantly using existing technologies, but stabilizing concentrations will require a technological revolution—a “revolution” because it will require fundamental change, achieved within a relatively short period of time. Inspiration for a climate–technology revolution is often drawn from the Apollo space program or the Manhattan Project, but averting dangerous climate change cannot be “solved” by a single new technology, deployed by a single government. The technological changes needed to address climate change fundamentally will have to be pervasive; they will have to involve markets; and they will have to be global in scope. My focus in this paper is not on the moderate emission reductions that can be achieved using existing technologies, but on the breakthrough technologies that are needed to reduce emissions dramatically. The challenges are formidable. Indeed, it is possible that the revolution needed to dramatically reduce emissions of greenhouse gases will fail. Should the climate change abruptly, the incentive to “engineer” the climate will be strong. There will be a climate–technology revolution, but its nature will depend on the institutions we develop to address the challenge we face.

scholarly journals Assessing Future Impacts of Climate Change on Water Supply System Performance: Application to the Pozzillo Reservoir in Sicily, Italy

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2531 ◽  
Author(s):  
Peres ◽  
Modica ◽  
Cancelliere
Keyword(s):  
Climate Change ◽  
Water Supply ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Supply System ◽  
Water Supply System ◽  
Reservoir Inflow ◽  
Emissions Scenario ◽  
Impacts Of Climate Change

Climate change induced by greenhouse gas emissions is expected to alter the natural availability of water, affecting domestic, agricultural and industrial uses. This work aims at assessing the possible future impacts of climate change on precipitation, temperature and runoff, and to simulate the effects on reservoir demand–performance curves. To this aim, a modeling chain is set up, based on the combined use of regional climate models (RCMs) and water supply system simulation models. The methodology is applied to the Pozzillo reservoir, located in Sicily (Italy), which has experienced several droughts in the past. We use an RCM model that, based on a previous study, has proved to be the most reliable in the area, among those of the EURO-CORDEX initiative. RCM precipitation and temperature monthly time series are used to generate future reservoir inflow data, according to two representative concentration pathways, RCP4.5 (intermediate emissions scenario) and RCP8.5 (high emissions scenario) and a two-step bias correction procedure. Simulation of the reservoir indicated that, due to reservoir inflow reduction induced by climate change, performances of the Pozzillo reservoir are predicted to decrease significantly in the future, with impacts of RCP8.5 generally higher than RCP4.5.

scholarly journals FAIR v1.3: a simple emissions-based impulse response and carbon cycle model

2018 ◽  
Vol 11 (6) ◽  
pp. 2273-2297 ◽  
Author(s):  
Christopher J. Smith ◽  
Piers M. Forster ◽  
Myles Allen ◽  
Nicholas Leach ◽  
Richard J. Millar ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Response ◽  
Transient Climate Response ◽  
Carbon Cycle Model ◽  
Future Projections

Abstract. Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented, which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone and other agents. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. The constrained estimates of equilibrium climate sensitivity (ECS), transient climate response (TCR) and transient climate response to cumulative CO2 emissions (TCRE) are 2.86 (2.01 to 4.22) K, 1.53 (1.05 to 2.41) K and 1.40 (0.96 to 2.23) K (1000 GtC)−1 (median and 5–95 % credible intervals). These are in good agreement with the likely Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) range, noting that AR5 estimates were derived from a combination of climate models, observations and expert judgement. The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are somewhat sensitive to the prior distributions of ECS∕TCR parameters but less sensitive to the ERF from a doubling of CO2 or the observational temperature dataset used to constrain the ensemble. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. The range of temperature projections under RCP8.5 for 2081–2100 in the constrained FAIR model ensemble is lower than the emissions-based estimate reported in AR5 by half a degree, owing to differences in forcing assumptions and ECS∕TCR distributions.

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