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Land-sea warming contrast: the role of the horizontal energy transport

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In this study we investigate the role of the mechanisms at play in the magnitude of the land-sea warming contrast and its intermodel spread in the fifth coupled models intercomparison project (CMIP5) simulations. In this aim, an energy-balance model (EBM), with one box representing the land area and two other boxes the near-surface and the deep ocean, is developed. In particular, a simple parameterization of the horizontal energy transport (HET) change between these two regions is proposed. The EBM is shown to capture the variation of the land and the ocean temperature responses and of the land-sea warming ratio in different idealized climate change experiments. By using this framework, we first show that the land-sea warming contrast is explained by the asymmetry in the strength of the HET between the land and ocean and not by land-sea differences in radiative feedbacks. Then we use a method of analysis of variance to infer the contributors to the intermodel spread in the land-sea warming ratio of climate models participating to CMIP5. The main contributor is found to be the HET with a contribution of about 70 %. Finally, our results suggest that the asymmetric character of the HET dependency to the land and the ocean temperature responses may be primarily explained by the land-sea differences in surface specific humidity change for a given temperature change.

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  • Bates JR (1999) A dynamical stabilizer in the climate system: a mechanism suggested by a simple model. Tellus A 51:349–372

    Article  Google Scholar 

  • Bates JR (2007) Some considerations of the concept of climate feedback. Q J R Meteorol Soc 133:545–560

    Article  Google Scholar 

  • Beltrami H, Smerdon J, Pollack H, Huang S (2002) Continental heat gain in the global climate system. Geophys Res Lett 29:1167

    Article  Google Scholar 

  • Boer GJ, Yu B (2003) Climate sensitivity and response. Clim Dyn 20:415–429

    Google Scholar 

  • Byrne MP, O’Gorman PA (2013a) Land-ocean warming contrast over a wide range of climates: convective quasi-equilibrium theory and idealized simulations. J Clim 26:4000–4016

    Article  Google Scholar 

  • Byrne MP, O’Gorman PA (2013b) Link between land-ocean warming contrast and surface relative humidities in simulations with coupled climate models. Geophys Res Lett 40:5223–5227

    Article  Google Scholar 

  • Compo GP, Sardeshmukh PD (2009) Oceanic influences on recent continental warming. Clim Dyn 32:333–342

    Article  Google Scholar 

  • Crook JA, Forster PM, Stuber N (2011) Spatial patterns of modeled climate feedback and contributions to temperature response and polar amplification. J Clim 24:3575–3592

    Article  Google Scholar 

  • Dommenget D (2009) The ocean’s role in continental climate variability and change. J Clim 22:4939–4952

    Article  Google Scholar 

  • Dommenget D (2012) Comments on the relationship between land-ocean surface temperature contrast and radiative forcing. J Clim 25:3437–3440

    Article  Google Scholar 

  • Drost F, Karoly D, Braganza K (2012) Communicating global climate change using simple indices: an update. Clim Dyn 39:989–999

    Article  Google Scholar 

  • Fasullo JT (2010) Robust land-ocean contrasts in energy and water cycle feedbacks. J Clim 23:4677–4693

    Article  Google Scholar 

  • Forster PM, Blackburn M, Glover R, Shine KP (2000) An examination of climate sensitivity for idealised climate change experiments in an intermediate general circulation model. Clim Dyn 16:833–849

    Article  Google Scholar 

  • Geoffroy O, Saint-Martin D, Ribes A (2012) Quantifying the sources of spread in climate change experiments. Geophys Res Lett 39:L24703

    Google Scholar 

  • Geoffroy O, Saint-Martin D, Olivié DJL, Voldoire A, Bellon G, Tytéca S (2013a) Transient climate response in a two-layer energy-balance model. Part I : analytical solution and parameter calibration using CMIP5 AOGCM experiments. J Clim 26:1841–1857

    Article  Google Scholar 

  • Geoffroy O, Saint-Martin D, Bellon G, Voldoire A, Olivié DJL, Tytéca S (2013b) Transient climate response in a two-layer energy-balance model. Part II : representation of the efficacy of deep-ocean heat uptake and validation for CMIP5 AOGCMs. J Clim 26:1859–1876

    Article  Google Scholar 

  • Geoffroy O, Saint-Martin D, Voldoire A, Salas-Mélia D, Sénési S (2014a) Adjusted radiative forcing and global radiative feedbacks in CNRM-CM5, a closure of the partial decomposition. Clim Dyn 42:1807–1818

    Article  Google Scholar 

  • Geoffroy O, Saint-Martin D (2014b) Pattern decomposition of the transient climate response. Tellus A 66:23393

    Article  Google Scholar 

  • Gregory JM (2000) Vertical heat transports in the ocean and their effect on time-dependent climate change. Clim Dyn 16:505–515

    Article  Google Scholar 

  • Gregory JM et al (2004) A new method for diagnosing radiative forcing and climate sensitivity. Geophys Res Lett 31:L03205

    Google Scholar 

  • Gregory JM, Webb MJ (2008) Tropospheric adjustment induces a cloud component in \({\rm CO}_{2}\) forcing. J Clim 21:58–71

    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, AUG Geophysical Union Monograph 29, Maurice Ewing, vol 5. American Geophysical Union, Washington D.C, pp 130–163

  • Hansen J, Sato M, Ruedy R (1997) Radiative forcing and climate response. J Geophys Res 102:6831–6864

    Article  Google Scholar 

  • Hansen J et al (2005) Efficacy of climate forcings. J Geophys Res 110:D18104

    Article  Google Scholar 

  • Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19:5686–5699

    Article  Google Scholar 

  • Held IM, Winton M, Takahashi K, Delworth T, Zeng F, Vallis GK (2010) Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing. J Clim 23:2418–2427

    Article  Google Scholar 

  • Huntingford C, Cox PM (2000) An analogue model to derive additional climate change scenarios from existing GCM simulations. Clim Dyn 16:575–586

    Article  Google Scholar 

  • Hwang Y-T, Frierson DMW (2010) Increasing atmospheric poleward energy transport with global warming. Geophys Res Lett 37:L24807

    Google Scholar 

  • Joshi MM, Gregory JM, Webb MJ, Sexton DMH, Johns TC (2008) Mechanisms for the land/sea warming contrast exhibited by simulations of climate change. Clim Dyn 30:455–465

    Article  Google Scholar 

  • Joshi MM, Lambert FH, Webb MJ (2013) An explanation for the difference between twentieth and twenty-first century land-sea warming ratio in climate models. Clim Dyn 41:1853–1869

    Article  Google Scholar 

  • Lambert FH, Chiang JCH (2007) Control of land-ocean temperature contrast by ocean heat uptake. Geophys Res Lett 34:L13704

    Google Scholar 

  • Lambert FH, Webb MJ, Joshi MM (2011) The relationship between land-ocean surface temperature contrast and radiative forcing. J Clim 24:3239–3256

    Article  Google Scholar 

  • Manabe S, Stouffer RJ, Spelman MJ, Bryan K (1991) Transient responses of a coupled ocean–atmosphere model to gradual changes of atmospheric \({\rm CO}_{2}\). Part I: annual mean response. J Clim 4:785–818

    Article  Google Scholar 

  • Manabe S, Spelman MJ, Stouffer RJ (1992) Transient responses of a coupled ocean–atmosphere model to gradual changes of atmospheric \({\rm CO}_{2}\). Part II: seasonal response. J Clim 5:105–126

    Article  Google Scholar 

  • Rose BEJ, Armour KC, Battisti DS, Feldl N, Koll DDB (2014) The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake. Geophys Res Lett 41:1071–1078

    Article  Google Scholar 

  • Sherwood S, Bony S, Boucher O, Bretherton CS, Forster P, Gregory J, Stevens B (2014) Adjustments in the forcing-feedback framework for understanding climate change. Bull Am Meteorol Soc (in press). doi:10.1175/BAMS-D-13-00167.1

  • Sobel AH, Bretherton CS (2000) Modeling tropical precipitation in a single column. J Clim 13:4378–4392

    Article  Google Scholar 

  • Sutton RT, Dong BW, Gregory JM (2007) Land-sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations. Geophys Res Lett 34:L02701

    Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2011) An overview of CMIP5 and the experiment design. Am Meteorol Soc Bull. doi:10.1175/BAMS-D-11-00094.1

  • Vial J, Dufresne J-L, Bony S (2014) On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim Dyn 41:3339–3362

    Article  Google Scholar 

  • Voldoire A, Sanchez-Gomez E, Salas y Mélia D, Decharme B, Cassou C, Sénési S, Valcke S, Beau I, Alias A, Chevallier M, Déqué M, Deshayes J, Douville H, Fernandez E, Madec G, Maisonnave E, Moine M-P, Planton S, Saint-Martin D, Szopa S, Tyteca S, Alkama R, Belamari S, Braun A, Coquart L, Chauvin F (2013) The CNRM-CM5.1 global climate model: description and basic evaluation. Clim Dyn 40:2091–2121

    Article  Google Scholar 

  • Winton M, Takahashi K, Held IM (2010) Importance of ocean heat uptake efficacy to transient climate change. J Clim 23:2333–2344

    Article  Google Scholar 

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We gratefully thank two anonymous reviewers for their constructive comments and suggestions that helped to improve the manuscript. We also thank Laura Watson for comments on the manuscript and Bjorn Stevens for an inspiring discussion on this topic. This work was supported by the Project MORDICUS. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison which provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank the climate modeling groups for producing and making available their model output.

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Correspondence to Olivier Geoffroy.



1.1 Non-linear LO-EBM

As in Held et al. (2010) and Geoffroy et al. (2013b), two additional climate response parameters, \(\lambda _{o}^{d}\) and \(\lambda _{l}^{d}\) (which can be related to that associated with the \({\mathrm {CO}}_{2}\) forcing with an efficacy factor), and two HET parameters, \(\alpha _o^{d}\) and \(\alpha _l^{d}\), are introduced to take into account the non-linear evolutions:

$$\begin{aligned} 0 \,= \, & {} {\mathcal {F}}_l -\lambda _l \left( \varDelta T_{l}-\varDelta T_{l}^{d}\right) + \frac{\alpha _{o}}{f_l} \left( \varDelta T_{o}-\varDelta T_{o}^{d}\right) -\frac{\alpha _{l}}{f_l} \left( \varDelta T_{l}-\varDelta T_{l}^{d}\right) \end{aligned}$$
$$\begin{aligned} 0= & {} -\lambda _{l}^{d} \varDelta T_{l}^{d}+ \frac{\alpha _{o}^{d}}{f_l} \varDelta T_{o}^{d} -\frac{\alpha _{l}^{d}}{f_l} \varDelta T_{l}^{d},\end{aligned}$$
$$\begin{aligned} C_o \frac{d \varDelta T_{o}}{dt} \,= \, & {} {\mathcal {F}}_o - \lambda _o \left( \varDelta T_{o}-\varDelta T_{o}^{d}\right) - \frac{\alpha _{o}}{1-f_l} \left( \varDelta T_{o}-\varDelta T_{o}^{d}\right) +\frac{\alpha _{l}}{1-f_l} \left( \varDelta T_{l}-\varDelta T_{l}^{d}\right) \end{aligned}$$
$$\begin{aligned} 0= & {} - \lambda _o^{d} \varDelta T_{o}^{d}- \frac{\alpha _{o}^{d}}{1-f_l} \varDelta T_{o}^{d} +\frac{\alpha _{l}^{d}}{1-f_l} \varDelta T_{l}^{d}- \gamma \left( \varDelta T_{o} - \varDelta T_{do}\right) . \end{aligned}$$

where \(\varDelta T_{o}^{d}\) and \(\varDelta T_{l}^{d}\) are the mean surface air temperature responses associated with the deep-ocean heat-uptake, over the ocean and over the land, respectively.

By adding Eqs. 24 and 25 and using Eqs. 27 and 28, the system of equations for \(\varDelta T_o\) reads:

$$\begin{aligned} C_o \frac{d \varDelta T_{o}}{dt}=\, & {} {\mathcal {F}}_o^{*} - \lambda _o^{*} \varDelta T_o - \gamma _o^{*} (\varDelta T_o - \varDelta T_{do}),\end{aligned}$$
$$\begin{aligned} C_{do}^{*} \frac{d \varDelta T_{do}}{dt}=\, & {} \gamma _o^{*} (\varDelta T_o - \varDelta T_{do}) \end{aligned}$$


$$\begin{aligned} {\mathcal {F}}_o^{*}=\, & {} {\mathcal {F}}_o+\frac{\alpha _l}{1-f_l} \varDelta T_l^{adj}\end{aligned}$$
$$\begin{aligned} \lambda _o^{*}=\, & {} \lambda _o +\frac{\alpha _o}{1-f_l} - \frac{\alpha _l}{1-f_l}\frac{\alpha _o/f_l}{\lambda _l+\alpha _l/f_l}\end{aligned}$$
$$\begin{aligned} \lambda _o^{d*}=\, & {} \lambda _o^{d} +\frac{\alpha _o^{d}}{1-f_l} - \frac{\alpha _l^{d}}{1-f_l}\frac{\alpha _o^{d}/f_l}{\lambda _l^{d}+\alpha _l/f_l}\end{aligned}$$
$$\begin{aligned} \gamma _o^{*}=\, & {} \gamma _o \frac{\lambda _o^{*}}{\lambda _o^{d*}}\end{aligned}$$
$$\begin{aligned} C_{do}^{*}=\, & {} C_{do} \frac{\lambda _o^{*}}{\lambda _o^{d*}} \end{aligned}$$

The analytical solution of this system for an abrupt and a linear forcing is given in Geoffroy et al. (2013a, b).

From Eqs. 24 and 25, the land surface air temperature response \(\varDelta T_l\) reads:

$$\begin{aligned} \varDelta T_{l} = \varDelta T_{l}^{adj} + \frac{\alpha _o / f_l}{\lambda _l + \alpha _l/f_l}(\varDelta T_{o}-\varDelta T_{o}^{d}) + \frac{\alpha _o^{d} / f_l}{\lambda _l^{d} + \alpha _l^{d}/f_l}\varDelta T_{o}^{d}, \end{aligned}$$

The formula of \(\varDelta T_{l}^{adj}\) is unchanged (but the values of the parameters are different) and the formula of \(\phi\) has an additional term.

The calibration of the parameters is performed iteratively by using the linear LO-EBM as initial values. Then, the following iterations are performed in three steps:

  1. 1.

    The radiative parameters \({\mathcal {F}}_l, \lambda _l, \lambda _l^{d},{\mathcal {F}}_o, \lambda _o, \lambda _o^{d}\) are computed from a multilinear regression of \(\varDelta N_i\) against \(\varDelta T_i\) (value of the climate model) and \(\varDelta T_{i}^{d}\) (analytical solution) for the land and the ocean region (\(i=l\) and \(i=o\), respectively).

  2. 2.

    The thermal inertia parameters \(C_o\), \(C_{do}\) and \(\gamma _o\) are calculated from two fits of \(\varDelta T_o\) against time as in Geoffroy et al. (2013a) and Geoffroy et al. (2013b).

  3. 3.

    The HET parameters are computed by multilinear regression of \(\varDelta T_l\) against \((\varDelta T_{o}-\varDelta T_{o}^{d})\) and \(\varDelta T_o^{d}\). Equation 35 can be written as the following:

    $$\begin{aligned} \varDelta T_l= \varDelta T_l^{adj} + k_{eq} (\varDelta T_{o}-\varDelta T_{o}^{d}) + k_d (\varDelta T_{o}^{d}). \end{aligned}$$

    Hence, the intercept of the multilinear regression gives \(\alpha _l\) (Eq. 12) then \(k_{eq}\) gives \(\alpha _o\) (Eq. 35) and \(\alpha _l^{d}\) and \(\alpha _o^{d}\) are computed from \(k_d\) by assuming \(\alpha _l/\alpha _o=\alpha _l^{d}/\alpha _o^{d}\).

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Geoffroy, O., Saint-Martin, D. & Voldoire, A. Land-sea warming contrast: the role of the horizontal energy transport. Clim Dyn 45, 3493–3511 (2015).

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