globalchange  > 全球变化的国际研究计划
DOI: doi:10.1038/nclimate2880
论文题名:
Response of Arctic temperature to changes in emissions of short-lived climate forcers
作者: M. Sand
刊名: Nature Climate Change
ISSN: 1758-682X
EISSN: 1758-6802
出版年: 2015-11-30
卷: Volume:6, 页码:Pages:286;289 (2016)
语种: 英语
英文关键词: Atmospheric science ; Climate-change impacts
英文摘要:

There is growing scientific1, 2 and political3, 4 interest in the impacts of climate change and anthropogenic emissions on the Arctic. Over recent decades temperatures in the Arctic have increased at twice the global rate, largely as a result of ice–albedo and temperature feedbacks5, 6, 7, 8. Although deep cuts in global CO2 emissions are required to slow this warming, there is also growing interest in the potential for reducing short-lived climate forcers (SLCFs; refs 9,10). Politically, action on SLCFs may be particularly promising because the benefits of mitigation are seen more quickly than for mitigation of CO2 and there are large co-benefits in terms of improved air quality11. This Letter is one of the first to systematically quantify the Arctic climate impact of regional SLCFs emissions, taking into account black carbon (BC), sulphur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOCs), organic carbon (OC) and tropospheric ozone (O3), and their transport processes and transformations in the atmosphere. This study extends the scope of previous works2, 12 by including more detailed calculations of Arctic radiative forcing and quantifying the Arctic temperature response. We find that the largest Arctic warming source is from emissions within the Asian nations owing to the large absolute amount of emissions. However, the Arctic is most sensitive, per unit mass emitted, to SLCFs emissions from a small number of activities within the Arctic nations themselves. A stringent, but technically feasible mitigation scenario for SLCFs, phased in from 2015 to 2030, could cut warming by 0.2 (±0.17)K in 2050.

We focus on the Arctic impact of climate forcers with atmospheric lifetimes shorter than the typical hemispheric mixing times (about one month): BC and ozone precursors (CO and VOCs) that predominantly lead to warming, as well as co-emitted species that cause cooling (SO2, OC, and NOx). We omit methane and HFCs as their lifetimes are longer, although some other studies on SLCFs have included these species as well. In the Arctic, the effects of BC include both the warming from absorption of solar radiation in the atmosphere and absorption of radiation from deposition on snow/ice13, 14, 15. The Arctic warming from BC is highly variable with season of emission, physical transport into the Arctic, and the deposition to snow and ice16. In addition, processes that emit BC also co-emit other particles and gases that lead to sulphate and OC aerosols. Ozone precursors (CO, NOx and VOCs) affect climate through the formation of ozone, a potent greenhouse gas, while also changing the oxidizing capacity of the atmosphere (and thus the lifetime and levels of, for example, methane)17.

Using several chemical transport models we perform detailed radiative forcing calculations from emissions of these species. Geographically, we separate emissions into seven source regions that correspond with the national groupings of the Arctic Council, the leading body organizing international policy in the region (the United States, Canada, the Nordic countries, the rest of Europe, Russia, East and South Asia, and the rest of the world). We look at six main sectors known to account for nearly all of these emissions: households (domestic), energy/industry/waste, transport, agricultural fires, grass/forest fires, and gas flaring. The models have different treatments of SLCFs, and have simulated the years 2006–2010 with prescribed sea surface temperatures. To estimate the Arctic surface temperature we apply regional climate sensitivities (RCSs), the temperature response per unit of radiative forcing for each SLCF (refs 18,19,20,21). The RCSs are defined in four broad latitude bands (60°–90°N, 28°–60°N, 28°S–28°N, 90°–28°S) to account for contributions by local and remote forcing to surface temperature changes in each band. For example, BC at midlatitudes may increase the transport of heat into the Arctic by locally warming the atmosphere and increasing the north–south temperature gradient18, 22. The RCS concept applied here accounts for this.

The simulations employ anthropogenic emissions of SLCFs from the ECLIPSE emission data set V4.0a (refs 23,24) for the year 2010. Using the RCS method we estimate the total equilibrium Arctic surface temperature response to all (natural and anthropogenic) global 2010 emissions of SLCFs to be −0.44K, with a model range of −1.02 to −0.04K. Of this 0.48 (0.33–0.66) K is due to BC in atmosphere and snow, −0.18 (−0.30–0.03)K is due to OC, −0.85 (−0.57 to −1.29)K is due to sulphate and 0.05 (0.04–0.05)K is due to ozone. We can compare the total impact to the CMIP5 multi-model ensemble historical simulations. A cooling of −1.8K has been estimated in the Arctic between 1913 and 2012 due to all anthropogenic forcing agents other than greenhouse gases25, whereas using the six best CMIP5 models (ranked based on the least square errors between the simulations and observations in the Arctic), a cooling trend of −0.1K per decade from 1900 to 2005 has been reported1. These numbers are higher (negative) compared to ours, but they also include more climate forcers. Also note that our temperature response is an equilibrium result, whereas the CMIP5 calculations are from transient simulations.

Figure 1 shows the annual mean Arctic surface temperature response from current emissions separated into the different emission sectors, regions and components. The largest single contribution to warming in the Arctic originates from Asian domestic emissions, followed by Russian flaring emissions. Generally, the energy sector has a cooling effect due to the relatively large direct and indirect aerosol effects of SO2 emissions. The doughnut chart in Fig. 1 reports the fractions of the Arctic warming/cooling that are due to radiative forcing within the Arctic or outside the region—showing that most of the Arctic warming effects from Asian emissions are due to radiative forcing exerted outside the Arctic, whereas most emissions from Arctic nations such as Russia and the Nordic countries affect the Arctic more directly.

Figure 1: Model-mean annual Arctic equilibrium surface temperature response.
Model-mean annual Arctic equilibrium surface temperature response.

Each bar represents the different emission sectors for each source region specified on the x axis. The emission sectors are, in order from left to right: domestic, energy/industry/waste, transport, agricultural waste burning, grass/forest fires, and flaring. The black dots are the total temperature response and the crosses represent the model spread (of total response) as a root-mean-square error. The doughnuts illustrate how much of the Arctic warming (red) and cooling (blue) comes from forcing within the Arctic (solid fill) versus outside the Arctic (striped).

The five models used for forcing calculations are CAM5.2, CanAM4.2, NorESM, Oslo-CTM2 and SMHI-MATCH (see Supplementary Table 1 for details). All models are run with the same 2010 emissions (GAINS v4.0a ECLIPSE compiled by IIASA) for the years 2006–2010 with prescribed sea surface temperatures (2006 is used as spin-up). The domestic sector is monthly weighted based on spatially distributed global temperature data from the Climatic Research Unit at the University of East Anglia. The emissions data set is available from www.geiacenter.org. The emissions are separated into six sectors (domestic, industry/energy/waste, transport, flaring, forest fires, and agricultural waste burning) and seven source regions (United States, Canada, Russia, the Nordic countries, rest of Europe, East + South Asia, and the rest of the world). To calculate the burden change and radiative forcing in the Arctic to all the regions and sectors in this study, the models have been run with and without each region/sector combination. Tables of the forcing calculations and the emissions are provided in the Supplementary Information.

We have calculated the Arctic equilibrium surface temperature response by translating the independently diagnosed radiative forcings from each model through the use of sensitivity coefficients. These regional climate sensitivity coefficients (RCSs) were estimated with the NASA-GISS model18 and extended further in following study20. The RCSs are defined in four latitude bands; the southern hemisphere (90°–28°S), the tropics (28°S–28°N), the midlatitudes (28°–60°N), and the Arctic (60°–90°N). Supplementary Table 3 shows the RCSs for the Arctic response region. The temperature calculations have been done separately for BC, ozone and scattering aerosols (OC and sulphate) and have units of KW−1m2 averaged horizontally in each latitude band.

The Arctic equilibrium annual mean surface temperature change (ΔT) by emission of component (cE), in region (r) and from source (s), is estimated from the modelled RF(j, cF, r, s), where j denotes the latitude band of the radiative forcing by:

Here cE denotes the emitted component (for example, BC) and cF denotes the forcing mechanisms caused by the emissions cE. For BC the cF includes both forcing by the direct absorption in the atmosphere and the albedo effect of BC deposition on snow. The RCSs (in units of KW−1m2) give the Arctic equilibrium temperature response to a unit forcing by component/mechanism cF, exerted in latitude band j. The analysis of temperature response in the three non-Arctic latitude bands is beyond the scope of this paper, but can readily be calculated by equation (1) using radiative forcings and RCSs for the non-Arctic bands.

In this study a more detailed treatment of the response to BC forcing in the Arctic is adopted. For forcing by absorption of short-wave radiation, in particular in a stably stratified atmosphere (that is, by BC in the Arctic atmosphere), the climate efficacy (that is, the RCS coefficients) depends strongly on the altitude of the absorption causing the radiative forcing21, 22. For example, BC at higher altitudes in the Arctic probably cools the surface, despite exerting a positive TOA forcing, whereas BC at lower altitudes causes strong surface warming18, 21, 22. To take this into account we have derived vertically resolved radiative forcings in the Arctic (for each model) and applied these in combination with vertical climate sensitivity factors21. For the effect of the forcing by BC in the Arctic atmosphere the surface temperature change is given by

The total temperature effect of BC forcing in the atmosphere is then given by the sum of (1) and (2), where in (1) the contribution by forcing in the Arctic is neglected and represented by (2). For all other components and forcing mechanisms the total effect is given by equation (1).

To derive the model mean estimate for the Arctic surface temperature response to the emissions from the different sources, regions and sectors, as given in Fig. 1, first the individual model estimates for all emissions from the sector and region (for example, from transportation in the US) are given by

where the ΔT(cE, r, s) are estimated by Eqs (1) and (2). Finally, the model mean is calculated by averaging over the models.

For indirect cloud forcings from OC and sulphate we have used scattering aerosol RCSs. The sensitivity factors for BC in snow in the Arctic are from a study with idealized simulations with CESM1.0.3 (ref. 21), whereas for the other regions the effect of BC in snow was set to three times the atmospheric BC factor, based on efficacy factors found in other studies15, 31. We have scaled the RCSs obtained by the CESM model (that is, BC in atmosphere and snow in the Arctic) to the global climate sensitivity of the GISS model. The equilibrium global climate sensitivity for the NASA-GISS model it is 2.9K, whereas for CESM it is 4.0K (ref. 32). We have therefore scaled the CESM obtained results by 0.725.

The mitigation scenario starts from 2015 and gives annual changes in emissions of all SLCFs (including co-emitted species). From the equilibrium temperature estimates described above we have calculated the regional climate response as given in Fig. 3. In equation (4) the RCSn are the normalized regional climate sensitivity coefficients in units of KW−1m−2 (Tgyr−1)−1. To estimate the transient response to the mitigation of the emissions we represent the inertia of the climate system by an impulse response function (IRF) for climate33. The full IRF includes both the global climate sensitivity and the temporal evolution of the response in the climate system to a forcing. To keep the estimate of the transient response consistent with the global climate sensitivity used for the equilibrium estimates using the RCSs in equation (1) we have normalized the IRF with their climate sensitivity (1.06KW−1m2) to obtain IRFN (units yr−1). The full Arctic response in year t is then given by

The original IRF is given by (in units of KW−1m2yr):

where c1 = 0.631KW−1m2, c2 = 0.429KW−1m2, τ1 = 8.4 years and τ2 = 409.5 years. By normalizing with the global sensitivity we get

where c1′ = 0.595 and c2′ = 0.405 (dimensionless).

Additional descriptions of the uncertainty estimates along with tables of the forcing calculations, emissions, the RCSs and the models used are given in the Supplementary Information.

  1. Fyfe, J. C. et al. One hundred years of Arctic surface temperature variation due to anthropogenic influence. Sci. Rep. 3, 2645 (2013).
  2. Quinn, P. K. et al. The Impact of Black Carbon on Arctic Climate (Arctic Monitoring and Assessment Programme (AMAP), 2011).
  3. Time to Act to Reduce Short-lived Climate Pollutants (Climate and Clean Air Coalition, UNEP, 2014); http://www.unep.org/ccac/Portals/50162/docs/publications/Time_To_Act/SLCP_TimeToAct_lores.pdf.
  4. Summary for Policy-makers: Arctic Climate Issues 2015 (Monitoring and Assessment Programme (AMAP), 2015).
  5. Hartmann, D. L. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 159254 (IPCC, Cambridge Univ. Press, 2013).
  6. Screen, J. A. & Simmonds, I. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature 464, 13341337 (2010).
  7. URL:
http://www.nature.com/nclimate/journal/v6/n3/full/nclimate2880.html
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/4510
Appears in Collections:全球变化的国际研究计划
科学计划与规划
气候变化事实与影响
气候变化与战略

Files in This Item:
File Name/ File Size Content Type Version Access License
nclimate2880.pdf(606KB)期刊论文作者接受稿开放获取View Download

Recommended Citation:
M. Sand. Response of Arctic temperature to changes in emissions of short-lived climate forcers[J]. Nature Climate Change,2015-11-30,Volume:6:Pages:286;289 (2016).
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[M. Sand]'s Articles
百度学术
Similar articles in Baidu Scholar
[M. Sand]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[M. Sand]‘s Articles
Related Copyright Policies
Null
收藏/分享
文件名: nclimate2880.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.