Fumin Ren

Developed and developing world responsibilities for historical climate change and CO2 mitigation

At the United Nations Framework Convention on Climate Change Conference in Cancun, in November 2010, the Heads of State reached an agreement on the aim of limiting the global temperature rise to 2 °C relative to preindustrial levels. They recognized that long-term future warming is primarily constrained by cumulative anthropogenic greenhouse gas emissions, that deep cuts in global emissions are required, and that action based on equity must be taken to meet this objective. However, negotiations on emission reduction among countries are increasingly fraught with difficulty, partly because of arguments about the responsibility for the ongoing temperature rise. Simulations with two earth-system models (NCAR/CESM and BNU-ESM) demonstrate that developed countries had contributed about 60–80%, developing countries about 20–40%, to the global temperature rise, upper ocean warming, and sea-ice reduction by 2005. Enacting pledges made at Cancun with continuation to 2100 leads to a reduction in global temperature rise relative to business as usual with a 1/3–2/3 (CESM 33–67%, BNU-ESM 35–65%) contribution from developed and developing countries, respectively. To prevent a temperature rise by 2 °C or more in 2100, it is necessary to fill the gap with more ambitious mitigation efforts.

The Atlas of Climate Change: Based on SEAP-CMIP5

Data and Methodology.- Climate change simulation and projection based on CMIP5.- Attribution of responsibility for climate change from developed/developing countries.

Atlas of climate change : responsibility and obligation of human society

This atlas and reference resource assembles the latest research findings on the responsibility and obligation of human society for historical climate change. It clearly and quantitatively estimates to what extent the developed and developing world are responsible for historical climate change with regard to anthropogenic carbon and sulfur emissions as well as global carbon trade, and so provides a potential tool to address the controversial issue of carbon emission reduction in international climate negotiations. Since the quantitative attribution of historical climate change is calculated based on CMIP5 models, the fidelity of these models in representing the observed climate change is also evaluated. In addition to evaluation, future climate change based on CMIP5 models is also shown both on global and regional scales (especially for China and its surrounding areas ) in terms of surface air temperature, precipitation, sea surface temperature, atmospheric circulations and Arctic Sea ice. The atlas also makes various comparisons among different multi-model ensemble methods in order to obtain the most reliable estimation.

Climate Change: Historical Simulations and Projections

Sections 2.1 and 2.2 present the evaluations of CMIP5 models in reproducing the historical climate change and projections of future climate change under three scenarios of RCP2.6, RCP4.5, and RCP8.5 in terms of surface air temperature and precipitation over the globe and China; Sect. 2.3 presents the atmospheric circulations over the Asia-Pacific region in terms of the East Asian Summer Monsoon (EASM) (Guo, Acta Geograph Sin 38(3):208–217, 1983), Western Pacific Subtropical High (WPSH) area and strength (Liu et al., J Appl Meteorol Sci 23(4):414–423, 2012), Arctic Oscillation (AO) (Thompson and Wallace, Geophys Res Lett 25:1297–1300, 1998), and Siberian High (SH) (Wu and Wang, Geophys Res Lett 29(19):1897, 2002); and Sect. 2.4 presents the climate extremes in China. The analyzed climate extreme elements include surface air maximum temperature and surface air minimum temperature, consecutive dry days – maximum number of consecutive days with less than 1 mm of precipitation (CDD) – and simple daily precipitation intensity (SDII) (Frisch et al., Clim Res 19:193–212, 2002). The historical climatology is set to long-term mean over 1986–2005. In projection, the uncertainty range is given described by one inter-model standard deviation.

Responsibilities for Climate Change Induced from Developed and Developing World Anthropogenic Sulfur Emissions

This chapter shows the results of the impacts of anthropogenic sulfur emissions from Annex I and non-Annex I countries for the period of 1850–2005. These numerical experiments named Both, Ann1, Non1, and Zero are performed based on NCAR/CESM1_0_2 model. The analyzed climate elements involve aerosol concentration, aerosol optical depth, air temperature, precipitation, cloud, solar flux, sea level pressure, zonal circulation, sea ice extent, etc.

Transferred Responsibility for Historical Climate Change Induced from Carbon Trade Between Developed and Developing World

This chapter shows the results of attribution experiments which assess the influences of transferred carbon emissions along with international trade on the historical responsibility of developed/developing countries and on the potential mitigation ability of the Kyoto Protocol. These numerical experiments are performed based on NCAR/CESM1_0_2 model for the period of 1990–2005.

Responsibility for Historical Climate Change Induced from Developed and Developing World Anthropogenic Carbon Emissions

This chapter shows the results of attribution experiments which assess the contributions of historical anthropogenic carbon emissions to global warming from developed and developing countries. These numerical experiments are performed based on NCAR/CESM1_0_2 model for the period of 1850–2011.

Data and Methods

This chapter introduces the data and methods utilized in the computation in the following chapters, as well as the experimental designs of numerical simulations in Chaps. 4, 5, and 6.

Comparisons Among Multi-model Ensemble Based on Different Ensemble Methods and Ensemble Member Sizes

In this chapter, the results of three different multi-model ensemble mean methods are compared. In Sect. 3.1, the global mean surface air temperature and precipitation from multi-model weighted mean and equal-weighted mean are compared. The weight is given according to the correlation coefficients and relative bias between model and observation. The results from the multi-model weighted mean and the equal-weighted mean show no significant difference. In Sect. 3.2, the surface air temperature and precipitation in China from multi-model equal-weighted mean and Bayesian model averaging (BMA) method are compared. BMA is a multi-model ensemble method which considered each model’s posterior distributions and then weighted by posterior model probability. In our calculation, the training of BMA is based on observational data (derived from CRUTS 3.21) for the period of 1961–1990. The multi-model ensemble mean in Sects. 3.1 and 3.2 is calculated based on 22 CMIP5 models described in Chap. 1.

Attribution of Responsibility for Historical Climate Change from Developed/Developing Countries

This chapter shows the results of attribution study which assesses the contributions of historical greenhouse gas emissions to global warming from developed and developing countries; and projection study which assess the effects of emission reduction commitments after the Cancun Agreement on future global warming. These numerical experiment is performed based on NCAR/CESM1_0_2 model. The analyzed climate elements involve air temperature, precipitation, sea level pressure, geopotential height and cryosphere related elements, etc.