A modeling study of effective radiative forcing and climate response due to increased methane concentration

A modeling study of effective radiative forcing and climate response due to increased methane concentration Available online at www sciencedirect com + MODEL ScienceDirect Advances in Climate Change R[.]

+ MODEL Available online at www.sciencedirect.com ScienceDirect Advances in Climate Change Research xx (2016) 1e6 www.keaipublishing.com/en/journals/accr/ A modeling study of effective radiative forcing and climate response due to increased methane concentration XIE Bing a,b, ZHANG Hua a,b,*, YANG Dong-Dong c, WANG Zhi-Li d a Laboratory for Climate Studies of China Meteorological Administration, National Climate Center, China Meteorological Administration, Beijing 100081, China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China c College of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044, China d State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China b Received 27 July 2016; accepted December 2016 Abstract An atmospheric general circulation model BCC_AGCM2.0 and observation data from ARIS were used to calculate the effective radiative forcing (ERF) due to increased methane concentration since pre-industrial times and its impacts on climate The ERF of methane from 1750 to 2011 was 0.46 W m
2 by taking it as a well-mixed greenhouse gas, and the inhomogeneity of methane increased its ERF by about 0.02 W m
2 The change of methane concentration since pre-industrial led to an increase of 0.31  C in global mean surface air temperature and 0.02 mm d
1 in global mean precipitation The warming was prominent over the middle and high latitudes of the Northern Hemisphere (with a maximum increase exceeding 1.4  C) The precipitation notably increased (maximum increase of 1.8 mm d
1) over the ocean between 10 N and 20 N and significantly decreased (maximum decrease >e0.6 mm d
1) between 10 S and 10 N These changes caused a northward movement of precipitation cell in the Intertropical Convergence Zone (ITCZ) Cloud cover significantly increased (by approximately 4%) in the high latitudes in both hemispheres, and sharply decreased (by approximately 3%) in tropical areas Keywords: Methane; Effective radiative forcing; Climate change Introduction Global surface air temperatures have increased due to increases in emissions of anthropogenic greenhouse gases * Corresponding author Laboratory for Climate Studies of China Meteorological Administration, National Climate Center, China Meteorological Administration, Beijing 100081, China E-mail address: huazhang@cma.gov.cn (ZHANG H.) Peer review under responsibility of National Climate Center (China Meteorological Administration) Production and Hosting by Elsevier on behalf of KeAi (GHGs) since the start of the industrial era (IPCC, 2013; Zhang et al., 2014b) Methane (CH4), with a relatively short lifetime (about 12 years), is the most important anthropogenic GHG besides CO2 (IPCC, 2013) Although the burden of CH4 in the atmosphere is significantly smaller than that of CO2, the radiative efficiency (RE) of CH4 is 26.5 times as much as that of CO2 (Yashiro et al., 2008; Renaud and Caillol, 2011) The absorption of CH4 on radiative flux influence the temperature, especially near the Earth's surface The atmospheric CH4 concentration almost doubled from 1750 to 2011, the volume mixing ratio from 722  10
9 to 1803  10
9 (IPCC, 2013) CH4 increased rapidly until 2000 Then, after a decade of stabilization or slightly decreasing concentrations, the global CH4 concentration showed a well- http://dx.doi.org/10.1016/j.accre.2016.12.001 1674-9278/Copyright © 2017, National Climate Center (China Meteorological Administration) Production and hosting by Elsevier B.V on behalf of KeAi This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Please cite this article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration, Advances in Climate Change Research (2016), http://dx.doi.org/10.1016/j.accre.2016.12.001 + MODEL XIE B et al / Advances in Climate Change Research xx (2016) 1e6 defined increase again in 2007 (Dlugokencky et al., 2003; Rigby et al., 2008), measured using ground-based observations (Cunnold et al., 2002; Langenfelds et al., 2002; Dlugokencky et al., 2009) and aircraft profiles (Wecht et al., 2012; Worden et al., 2012) The IPCC Fifth Assessment Report (IPCC, 2013) showed that the radiative forcing (RF) of CH4 was 0.48 ± 0.05 W m
2 from 1750 to 2011 based on Myhre et al (1998) CH4 is well mixed in the atmosphere, but its concentrations vary with latitude and altitude, contributing to 2% of the uncertainty in its RF (Freckleton et al., 1998) In this study, we estimated the effective radiative forcing (ERF) and climate response due to changes in atmospheric methane concentration from 1750 to 2011 using the general circulation model BCC_AGCM2.0 from the National Climate Center of China Descriptions of model and method 2.1 Model We used the general circulation model BCC_AGCM2.0 developed by the National Climate Center of China The horizontal resolution of the model is approximately 2.8  2.8 , and the vertical direction includes 26 layers, with a rigid lid at 2.9 hPa This model was based on the Community Atmosphere Model Version (CAM3.0) from the National Center for Atmospheric Research, U.S BCC_AGCM2.0 contains several enhancements in the physics: BCC_AGCM2.0 uses the radiation scheme of BCC_RAD (Beijing Climate Center Radiative Transfer Model), developed by Zhang et al (2003, 2006a, 2006b), and the cloud overlap scheme of the Monte Carlo independent column approximation (Zhang et al., 2014a) These schemes increase the accuracy of the sub-grid cloud structure and its radiative transfer process Further details on BCC_AGCM2.0 can be found in Wu et al (2010) The model has been used to study the RFs and the subsequent effects on climate due to aerosols (e.g., Zhang et al., 2012; Wang et al., 2013a, 2013b, 2014, 2015; Zhao et al., 2015) and tropospheric ozone (Xie et al., 2016) 2.2 Satellite data CH4 profile data observed by the Atmospheric Infrared Sounder (AIRS) (URL: http://www.nasa.gov/mission_pages/ aqua) was used AIRS was onboard the Aqua spacecraft and launched by the National Aeronautic and Space Administration (NASA) in May 2002 An overview of the AIRS instrument is given by Aumann et al (2003) AIRS has 2378 channels, which cover from 649 to 1136, 1217 to 1613, and 2169 to 2674 cm
1 with high spectral resolution (l/ Dl ¼ 1200), and the absorption band of CH4 is included The AIRS dataset used in this study is on a global spatial resolution of 1  1 , and on vertical pressure levels from 1000 hPa to hPa (divided into 24 levels) More information about characterization and validation of methane products from AIRS can be found in Xiong et al (2008) and Zhang et al (2014c) 2.3 Experimental design Our aim was to calculate the ERF and climate response due to changes in atmospheric CH4 concentration To this end, five simulations (EXP1, EXP2, EXP3, EXP4, and EXP5) were conducted EXP1, EXP2 and EXP3 were used to calculate the ERF of CH4 at fixed sea surface temperature (SST) (Hurrell et al., 2008) The same model settings were used in these three simulations, only the CH4 concentrations were different (Table shows the details) The differences between EXP1 and EXP2 (EXP2 minus EXP1) were regarded as the ERF of well mixed CH4, and differences between EXP1 and EXP3 (EXP3 minus EXP1) were the ERF of CH4 with spatial variation Each simulation was run for 15 years Kristjansson et al (2005) reported that, after a period of adjustment (generally years for the model with prescribed SST and 30 years for the model with a coupled slab ocean model), the global mean surface air temperature reached equilibrium Therefore, the results from the last 10 years of the 15-year simulations of EXP1, EXP2 and EXP3 were used to calculate the ERF, as follows: ERF ẳ DFEXP2 or EXP3
DFEXP1 1ị where DF is the net radiation flux (the difference between incoming and outgoing shortwave and longwave radiative flux) at the top of the atmosphere (TOA) EXP4 and EXP5 were used to calculate the climate response of CH4 We used the same CH4 volume mixture ratios in EXP4 and EXP5 as in EXP1 and EXP2, respectively However, to consider the feedback of the oceans to CH4 forcing, a slab ocean model was coupled with BCC_AGCM2.0 in the simulations instead of using the fixed SST The two simulations were run for 70 years, and we used the results from the last 40 years to discuss the climate response due to changes in CH4 concentration Simulation results and analysis 3.1 ERF Human activities have increased anthropogenic emissions of CH4 since pre-industrial times, leading to increases in its atmospheric concentration and, subsequently, changes in its Table Experimental design Number EXP1 EXP2 EXP3 EXP4 EXP5 CH4 data a WMGHG 1750 WMGHG 2011b AIRS 2011c WMGHG 1750 WMGHG 2011 Sea temperature Running time Prescribed SST Prescribed SST Prescribed SST Slab ocean model Slab ocean model 15 15 15 70 70 years years years years years a CH4 concentration in 1750, as well mixed greenhouse gas, from IPCC AR5 b CH4 concentration in 2011, as well mixed greenhouse gas, from IPCC AR5 c CH4 concentration in 2011, observed by AIRS Please cite this article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration, Advances in Climate Change Research (2016), http://dx.doi.org/10.1016/j.accre.2016.12.001 + MODEL XIE B et al / Advances in Climate Change Research xx (2016) 1e6 3.2 Surface air temperature and cloud cover Fig Distribution of the effective radiative forcing (ERF) of well mixed atmospheric methane from 1750 to 2011 (units: W m
2) Shaded area represents the value at 0.05 significance level ERF Fig shows the simulated ERF (the difference between EXP2 and EXP1) due to change in CH4 as well mixed greenhouse gas (WMGHG) A well-defined positive ERF was generally observed near 60 in both hemispheres, with the maximum value of W m
2 However, the ERF was negative in western Siberia, southern Africa, Greenland, and most parts of South America, with a value of approximately
6 W m
2 over southern Africa The negative ERF in those areas might be explained by an increase in low cloud cover The simulated global mean CH4 ERF was 0.46 W m
2, which is consistent with the value reported in IPCC AR5 As Fig shown, CH4 concentrations vary with latitude and sharply decrease above the tropopause In lower troposphere, the concentration of methane was mainly in zonal division, and asymmetry on the Northern and Southern Hemispheres The volume mixing ratio of CH4 was reduced from north to south The asymmetry of CH4 concentration was becoming less distinct with the increase of altitude In the stratosphere, the volume mixing ratio was symmetrically distributed in both hemispheres, and it got less with the increasing latitude These spatial variations of CH4 had little impact on ERF (less than 0.02 W m
2) Fig Zonal distribution of the volume mixing ratio of CH4 in 2011 (10
6), observed by AIRS CH4 is a key long-lived GHG that strongly absorbs longwave radiation The ERF of CH4 is generally positive, leading to a warming effect on the Earth's climate system and thus the surface The difference between EXP5 and EXP4 showed that an increase in the atmospheric CH4 concentration since preindustrial times caused an increase of 0.31  C in global mean surface air temperature As shown in Fig 3a, the surface air temperature increased over the globe except for the small decreases in several high-latitude areas in both hemispheres Warming over the middle latitudes of the Northern Hemisphere was prominent, with the maximum temperature increase exceeding 1.4  C There was also significant warming (approximately 1.0  C) in the Antarctic area Fig 3b shows the response of the surface net radiation flux (SNRF) due to the change in CH4 The distribution of change in SNRF was consistent with that of surface temperature over the ocean There were significant increases in SNRF over the high latitudes in both hemispheres For example, the SNRF over the North Pacific Ocean increased by more than 6.0 W m
2, and the surface air temperature also increased significantly Changes in cloud cover and heat transportation can also affect surface air temperature Although the SNRF showed a welldefined decrease over the Indian Ocean, South Pacific, and the high latitudes of the Southern Hemisphere, the surface air temperature in the same regions did not change accordingly Fig 3c and d shows the changes in low-level (below 680 hPa) and high-level (above 440 hPa) cloud cover Changes in cloud cover directly affect SNRF, thereby influencing surface air temperature Increases in low-level cloud result in decreases in SNRF and a cooling effect at the surface, whereas increases in high-level cloud cause increases in surface air temperature due to high-level cloud's warming effect on the Earth's climate system As shown in Fig 1, the ERF was clearly negative in the western and southern regions of South America, and low-level cloud cover in these areas increased by about 20% (Fig 3c), resulting in marked decreases in surface temperature due to the scattering effect of low-level clouds to solar radiation The increase in temperature observed over the eastern Japan Sea and Mediterranean regions might be due to increase in high-level cloud cover (Fig 3d) Fig 3e and f shows the zonally averaged distributions of the changes in cloud cover and relative humidity There is a high level of correlation between the two variables The relative humidity showed significant increases in most of the troposphere near 70 N and between 10 N and 20 N in the lower troposphere in the Southern Hemisphere, in the higher troposphere in tropical areas, and in most of the troposphere over the Antarctic, and the cloud cover increased by 0.2%e1% in these regions These increases led to decreases in the SNRF (Fig 3b) In contrast, the relative humidity and cloud cover clearly decreased in the most of troposphere near 60 S and between 30 N and 40 N in the middle to upper troposphere near the equator and in most of stratosphere, resulting in increases in the SNRF (Fig 3b) in some areas Please cite this article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration, Advances in Climate Change Research (2016), http://dx.doi.org/10.1016/j.accre.2016.12.001 + MODEL XIE B et al / Advances in Climate Change Research xx (2016) 1e6 o C Wm-2 (c) (d) % % (f) Pressure (hPa) Prensure (hPa) (e) Fig Climate responses due to changes in atmospheric CH4 concentration since pre-industrial times Distribution of (a) surface air temperature, (b) surface net radiation flux, (c) low cloud, and (d) high cloud Zonal average distribution of (e) cloud and (f) relative humidity Shaded area represents the values at 0.05 significance level 3.3 Precipitation and surface water flux The increase in CH4 concentration resulted in a warming effect in the atmosphere and at the surface due to positive ERF at the TOA, which caused an increase of 0.02 kg m
2 d
1 in global mean surface water flux (SWF) (Fig 4b) The spatial distributions of the changes in SWF and SNRF were similar (Figs 2b and 3b) The SWF dramatically increased (by >0.12 kg m
2 d
1) over most areas of the ocean, especially in the northern Pacific, western Atlantic, and equatorial Pacific In contrast, the SWF showed well-defined decreases due to the decreased SNRF in most areas In particular, the SWF decreased by approximately 0.14 kg m
2 d
1 in eastern South America and central Africa Fig 4a shows the changes in precipitation due to CH4, which were notable in the Intertropical Convergence Zone Precipitation significantly increased (by >0.5 mm d
1, with a maximum increase of 1.8 mm d
1) over the ocean between 10 N and 20 N However, precipitation significantly decreased (maximum decrease >0.6 mm d
1) over the ocean between 10 S and 10 N Hence, there was a negative correlation between changes in precipitation over the tropics in each hemisphere, with precipitation increased in the Northern Hemisphere and decreased in the Southern Hemisphere Please cite this article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration, Advances in Climate Change Research (2016), http://dx.doi.org/10.1016/j.accre.2016.12.001 + MODEL XIE B et al / Advances in Climate Change Research xx (2016) 1e6 Fig Climate responses due to changes in atmospheric CH4 concentration since pre-industrial times Distribution of (a) precipitation and (b) surface water flux Shaded area represents the values at 0.05 significance level Conclusions The ERF and climate responses due to the change in atmospheric CH4 concentration from pre-industrial times (1750) to 2011 were investigated using the atmospheric general circulation model BCC AGCM2.0, in combination with CH4 volume mixture ratios from IPCC AR5 The global mean ERF for CH4 as WMGHG was 0.46 W m
2, and the spatial variation of methane influenced the ERF by 0.02 W m
2 The increase in atmospheric CH4 led to an increase of 0.31  C and 0.02 mm d
1 in global mean surface air temperature and precipitation, respectively Warming was significant in the middle and high latitudes, especially in the Northern Hemisphere, with the maximum warming exceeding 1.4  C The global distribution of change in precipitation was in line with that of changes in cloud cover, especially near the equator The precipitation notably increased (maximum increase of 1.8 mm d
1) over the tropical regions of the Northern Hemisphere and sharply decreased (maximum decrease >
0.6 mm d
1) between 10 S and 10 N, and these changes led the precipitation cell in ITCZ to move northward In the most of high latitudes in both hemispheres, cloud cover was significantly increased (by approximately 4%) and decreased (by approximately 3%) in tropical areas Acknowledgments This work was supported by the National Natural Science Foundation of China (41575002, 91644211) References Aumann, H., Chahine, M.T., Gautier, C., et al., 2003 AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems IEEE Trans Geosci Remote Sens 41, 253e264 Cunnold, D.M., Steele, L.P., Fraser, P.J., et al., 2002 In situ measurements of atmospheric methane at GAGE/AGAGE sites during 1985e2000 and resulting source inferences J Geophys Res Atmos 107 ACH20-1, Cite ID 4225 Dlugokencky, E., Houweling, S., Bruhwiler, L., et al., 2003 Atmospheric methane levels off: temporary pause or a new steady-state Geophys Res Lett 30 (19), 1992 http://dx.doi.org/10.1029/2003GL018126 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article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration, Advances in Climate Change... and decreased in the Southern Hemisphere Please cite this article in press as: XIE, B., et al., A modeling study of effective radiative forcing and climate response due to increased methane concentration,