Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Observational estimation of radiative feedback to surface air temperature over Northern High Latitudes

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The high-latitude climate system contains complicated, but largely veiled physical feedback processes. Climate predictions remain uncertain, especially for the Northern High Latitudes (NHL; north of 60°N), and observational constraint on climate modeling is vital. This study estimates local radiative feedbacks for NHL based on the CERES/Terra satellite observations during March 2000–November 2014. The local shortwave (SW) and longwave (LW) radiative feedback parameters are calculated from linear regression of radiative fluxes at the top of the atmosphere on surface air temperatures. These parameters are estimated by the de-seasonalization and 12-month moving average of the radiative fluxes over NHL. The estimated magnitudes of the SW and the LW radiative feedbacks in NHL are 1.88 ± 0.73 and 2.38 ± 0.59 W m−2 K−1, respectively. The parameters are further decomposed into individual feedback components associated with surface albedo, water vapor, lapse rate, and clouds, as a product of the change in climate variables from ERA-Interim reanalysis estimates and their pre-calculated radiative kernels. The results reveal the significant role of clouds in reducing the surface albedo feedback (1.13 ± 0.44 W m−2 K−1 in the cloud-free condition, and 0.49 ± 0.30 W m−2 K−1 in the all-sky condition), while the lapse rate feedback is predominant in LW radiation (1.33 ± 0.18 W m−2 K−1). However, a large portion of the local SW and LW radiative feedbacks were not simply explained by the sum of these individual feedbacks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Alexeev V, Langen PL, Bates JR (2005) Polar amplification of surface warming on an aquaplanet in “ghost forcing” experiments without sea ice feedbacks. Clim Dyn 24:655–666

    Article  Google Scholar 

  • Brown PT, Li W, Jiang JH, Su H (2016) Unforced surface air temperature variability and its contrasting relationship with the anomalous TOA energy flux at local and global spatial scales. J Clim 29:925–940

    Article  Google Scholar 

  • Burt MA, Randall DA, Branson MD (2016) Dark warming. J Clim 29:705–719

    Article  Google Scholar 

  • Cesana G, Kay J, Chepfer H, English J, Boer G (2012) Ubiquitous low-level liquid-containing Arctic clouds: new observations and climate model constraints from CALIPSO-GOCCP. Geophys Res Lett 39

  • Cess RD (1976) Climate change: an appraisal of atmospheric feedback mechanisms employing zonal climatology. J Atmos Sci 33:1831–1843

    Article  Google Scholar 

  • Chapin FS, Randerson JT, McGuire AD, Foley JA, Field CB (2008) Changing feedbacks in the climate–biosphere system. Front Ecol Environ 6:313–320

    Article  Google Scholar 

  • Choi Y-S, Song H-J (2012) On the numerical integration of a randomly forced system: variation and feedback estimation. Theor Appl Climatol 110:97–101

    Article  Google Scholar 

  • Choi Y-S, Ho C-H, Park C-E, Storelvmo T, Tan I (2014a) Influence of cloud phase composition on climate feedbacks. J Geophys Res 119:3687–3700

    Article  Google Scholar 

  • Choi Y-S, Kim B-M, Hur S-K, Kim S-J, Kim J-H, Ho C-H (2014b) Connecting early summer cloud-controlled sunlight and late summer sea ice in the Arctic. J Geophys Res 119

  • Choi Y-S, Cho H, Ho C-H, Lindzen RS, Park SK, Yu X (2014c) Influence of non-feedback variations of radiation on the determination of climate feedback. Theor Appl Climatol 115:355–364

    Article  Google Scholar 

  • Christensen MW, Behrangi A, L’Ecuyer T, Wood NB, Lebsock MD, Stephens GL (2016) Arctic observation and reanalysis integrated system: a new data product for validation and climate study. Bull Am Meteorol Soc

  • Chylek P, Folland CK, Lesins G, Dubey MK, Wang M (2009) Arctic air temperature change amplification and the Atlantic Multidecadal Oscillation. Geophys Res Lett 36

  • Comiso JC, Hall DK (2014) Climate trends in the Arctic as observed from space. WIREs Clim Change 5:389–409

    Article  Google Scholar 

  • Cronin TW, Tziperman E (2015) Low clouds suppress Arctic air formation and amplify high-latitude continental winter warming. Proc Natl Acad Sci USA 112:11490–11495

    Article  Google Scholar 

  • Dee D, Uppala S, Simmons A, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M, Balsamo G, Bauer P (2011) The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Dessler A (2013) Observations of climate feedbacks over 2000–10 and comparisons to climate models. J Clim 26:333–342

    Article  Google Scholar 

  • Donohoe A, Armour KC, Pendergrass AG, Battisti DS (2014) Shortwave and longwave radiative contributions to global warming under increasing CO2. Proc Natl Acad Sci USA 111:16700–16705

    Article  Google Scholar 

  • Eastman R, Warren SG (2010) Arctic cloud changes from surface and satellite observations. J Clim 23:4233–4242

    Article  Google Scholar 

  • Forster PMF, Gregory JM (2006) The climate sensitivity and its components diagnosed from Earth radiation budget data. J Clim 19:39–52

    Article  Google Scholar 

  • Frankignoul C (1999) A cautionary note on the use of statistical atmospheric models in the middle latitudes: comments on “Decadal variability in the North Pacific as simulated by a hybrid coupled model”. J Clim 12:1871–1872

    Article  Google Scholar 

  • Frankignoul C, Czaja A, L’Heveder B (1998) Air-sea feedback in the North Atlantic and surface boundary conditions for ocean models. J Clim 11:2310–2324

    Article  Google Scholar 

  • Ghatak D, Miller J (2013) Implications for Arctic amplification of changes in the strength of the water vapor feedback. J Geophys Res 118:7569–7578

    Google Scholar 

  • Graversen RG, Mauritsen T, Tjernström M, Källén E, Svensson G (2008) Vertical structure of recent Arctic warming. Nature 451:53–56

    Article  Google Scholar 

  • Graversen RG, Langen PL, Mauritsen T (2014) Polar amplification in CCSM4: Contributions from the lapse rate and surface albedo feedbacks. J Clim 27:4433–4450

    Article  Google Scholar 

  • Gregory J, Ingram W, Palmer M, Jones G, Stott P, Thorpe R, Lowe J, Johns T, Williams K (2004) A new method for diagnosing radiative forcing and climate sensitivity. Geophys Res Lett 31

  • Hall A (2004) The role of surface albedo feedback in climate. J Clim 17:1550–1568

    Article  Google Scholar 

  • Hansen J, Lacis A, Rind D, Russell G, Stone P, Fung I, Ruedy R, Lerner J (1984) Climate sensitivity: analysis of feedback mechanisms. In: Hansen JE, Takahashi T (eds) Climate processes and climate sensitivity. American Geophysical Union, Washington DC, pp 130–163

    Chapter  Google Scholar 

  • Hansen J, Nazarenko L, Ruedy R, Sato M, Willis J, Del Genio A, Koch D, Lacis A, Lo K, Menon S (2005) Earth’s energy imbalance: confirmation and implications. Science 308:1431–1435

    Article  Google Scholar 

  • Holland MM, Bitz CM (2003) Polar amplification of climate change in coupled models. Clim Dyn 21:221–232

    Article  Google Scholar 

  • Hwang YT, Frierson DM, Kay JE (2011) Coupling between Arctic feedbacks and changes in poleward energy transport. Geophys Res Lett 38

  • Jonko AK, Shell KM, Sanderson BM, Danabasoglu G (2012) Climate feedbacks in CCSM3 under changing CO2 forcing. Part I: adapting the linear radiative kernel technique to feedback calculations for a broad range of forcings. J Clim 25:5260–5272

    Article  Google Scholar 

  • Kato S, Loeb NG, Minnis P, Francis JA, Charlock TP, Rutan DA, Clothiaux EE, Sun-Mack S (2006) Seasonal and interannual variations of top-of-atmosphere irradiance and cloud cover over polar regions derived from the CERES data set. Geophys Res Lett 33

  • Kay JE, Gettelman A (2009) Cloud influence on and response to seasonal Arctic sea ice loss. J Geophys Res. doi:10.1029/2009JD011773

  • Kay JE, L’Ecuyer T (2013) Observational constraints on Arctic Ocean clouds and radiative fluxes during the early 21st century. J Geophys Res 118:7219–7236

    Article  Google Scholar 

  • Kim Y, Choi Y-S, Kim B-M, Kim H (2015) Influence of altered low cloud parameterizations for seasonal variation of Arctic cloud amount on climate feedbacks. Clim Dyn 47:1661–1672

    Article  Google Scholar 

  • Knutti R, Hegerl GC (2008) The equilibrium sensitivity of the Earth’s temperature to radiation changes. Nat Geosci 1:735–743

    Article  Google Scholar 

  • Langen PL, Alexeev VA (2007) Polar amplification as a preferred response in an idealized aquaplanet GCM. Clim Dyn 29:305–317

    Article  Google Scholar 

  • Lindzen RS, Choi Y-S (2009) On the determination of climate feedbacks from ERBE data. Geophys Res Lett 36

  • Lindzen RS, Choi Y-S (2011) On the observational determination of climate sensitivity and its implications. Asia Pac J Atmos Sci 47:377–390

    Article  Google Scholar 

  • Manabe S, Wetherald RT (1975) The effect of doubling the CO2 concentration on the climate of a general circulation model

  • Masters T (2012) On the determination of the global cloud feedback from satellite measurements. Earth Syst Dyn 3:97–107

    Article  Google Scholar 

  • Meehl GA, Teng H, Arblaster JM (2014) Climate model simulations of the observed early-2000s hiatus of global warming. Nat Clim Change 4:898–902

    Article  Google Scholar 

  • Murphy DM (2010) Constraining climate sensitivity with linear fits to outgoing radiation. Geophys Res Lett 37

  • Pithan F, Mauritsen T (2014) Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nat Geosci 7:181–184

    Article  Google Scholar 

  • Rigor IG, Colony RL, Martin S (2000) Variations in surface air temperature observations in the Arctic, 1979–97. J Clim 13:896–914

    Article  Google Scholar 

  • Rind D (2008) The consequences of not knowing low-and high-latitude climate sensitivity. Bull Am Meteorol Soc 89:855

    Article  Google Scholar 

  • Santer BD, Bonfils C, Painter JF, Zelinka MD, Mears C, Solomon S, Schmidt GA, Fyfe JC, Cole JN, Nazarenko L (2014) Volcanic contribution to decadal changes in tropospheric temperature. Nat Geosci 7:185–189

    Article  Google Scholar 

  • Screen JA, Simmonds I (2010) The central role of diminishing sea ice in recent Arctic temperature amplification. Nature 464:1334–1337

    Article  Google Scholar 

  • Sedlar J, Tjernström M, Mauritsen T, Shupe MD, Brooks IM, Persson POG, Birch CE, Leck C, Sirevaag A, Nicolaus M (2011) A transitioning Arctic surface energy budget: the impacts of solar zenith angle, surface albedo and cloud radiative forcing. Clim Dyn 37:1643–1660

    Article  Google Scholar 

  • Serreze M, Barrett A, Stroeve J, Kindig D, Holland M (2009) The emergence of surface-based Arctic amplification. Cryosphere 3:11

    Article  Google Scholar 

  • Shell KM, Kiehl JT, Shields CA (2008) Using the radiative kernel technique to calculate climate feedbacks in NCAR’s Community Atmospheric Model. J Clim 21:2269–2282

    Article  Google Scholar 

  • Skific N, Francis JA (2013) Drivers of projected change in Arctic moist static energy transport. J Geophys Res 118:2748–2761

    Google Scholar 

  • Soden BJ, Held IM (2006) An assessment of climate feedbacks in coupled ocean-atmosphere models. J Clim 19:3354–3360

    Article  Google Scholar 

  • Soden BJ, Held IM, Colman R, Shell KM, Kiehl JT, Shields CA (2008) Quantifying climate feedbacks using radiative kernels. J Clim 21:3504–3520

    Article  Google Scholar 

  • Spencer RW, Braswell WD (2011) On the misdiagnosis of surface temperature feedbacks from variations in Earth’s radiant energy balance. Remote Sens 3:1603–1613

    Article  Google Scholar 

  • Spielhagen RF, Werner K, Sørensen SA, Zamelczyk K, Kandiano E, Budeus G, Husum K, Marchitto TM, Hald M (2011) Enhanced modern heat transfer to the Arctic by warm Atlantic water. Science 331:450–453

    Article  Google Scholar 

  • Trenberth KE, Zhang Y, Fasullo JT, Taguchi S (2015) Climate variability and relationships between top-of-atmosphere radiation and temperatures on Earth. J Geophys Res 120:3642–3659

    Google Scholar 

  • van der Linden E, Bintanja R, Hazeleger W, Katsman C (2014) The role of the mean state of Arctic Sea ice on near-surface temperature trends. J Clim 27:2819–2841

    Article  Google Scholar 

  • Vavrus S (2004) The impact of cloud feedbacks on Arctic climate under greenhouse forcing. J Clim 17:603–615

    Article  Google Scholar 

  • Wielicki BA, Barkstrom BR, Harrison EF, Lee III RB, Louis Smith G, Cooper JE (1996) Clouds and the Earth’s Radiant Energy System (CERES): an earth observing system experiment. Bull Am Meteorol Soc 77:853–868

    Article  Google Scholar 

  • Winton M (2008) Sea ice—albedo feedback and nonlinear Arctic climate change. Arctic Sea Ice Decline. American Geophysical Union, Washington, DC, pp 111–131

    Google Scholar 

  • Yamanouchi T, Kawaguchi S (1984) Longwave radiation balance under a strong surface inversion in the Katabatic Wind Zone, Antarctica. J Geophys Res 89:11771–11778

    Article  Google Scholar 

  • Zelinka MD, Klein SA, Hartmann DL (2012) Computing and partitioning cloud feedbacks using cloud property histograms. Part I: cloud radiative kernels. J Clim 25:3715–3735

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the GEMS program of the Ministry of Environment, Korea and the Eco Innovation Program of KEITI (2012000160003) and the Korea Meteorological Administration Research and Development Program, under Grant KMIPA2015-6110. Authors Y.-S. Choi, J. H. Jiang, and H. Su acknowledge the support of the Jet Propulsion Laboratory, California Institute of Technology, sponsored by the National Aeronautics and Space Administration (NASA). W. Kim acknowledges the support of the APEC Climate Center. The authors thank the Clouds and the Earth’s Radiant Energy System (CERES) and ERA-Interim reanalysis data production teams for providing their data.

Author information

Authors and Affiliations

  1. Department of Atmospheric Science and Engineering, Ewha Womans University, Engineer B 353, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, 03760, Republic of Korea

    Jiwon Hwang & Yong-Sang Choi

  2. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    Yong-Sang Choi, Hui Su & Jonathan H. Jiang

  3. Climate Prediction Department, APEC Climate Center, Busan, Republic of Korea

    WonMoo Kim

Authors
  1. Jiwon Hwang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong-Sang Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. WonMoo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hui Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jonathan H. Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yong-Sang Choi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hwang, J., Choi, YS., Kim, W. et al. Observational estimation of radiative feedback to surface air temperature over Northern High Latitudes. Clim Dyn 50, 615–628 (2018). https://doi.org/10.1007/s00382-017-3629-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-017-3629-6

Keywords

Search

Navigation