A global hybrid coupled model based on Atmosphere-SST feedbacks

Abstract

A global hybrid coupled model is developed, with the aim of studying the
effects of ocean-atmosphere feedbacks on the stability of the Atlantic
meridional overturning circulation. The model includes a global ocean general
circulation model and a statistical atmosphere model. The statistical
atmosphere model is based on linear regressions of data from a fully coupled
climate model on sea surface temperature both locally and hemispherically
averaged, being the footprint of Atlantic meridional overturning variability.
It provides dynamic boundary conditions to the ocean model for heat, freshwater
and wind-stress. A basic but consistent representation of ocean-atmosphere
feedbacks is captured in the hybrid coupled model and it is more than ten times
faster than the fully coupled climate model. The hybrid coupled model reaches a
steady state with a climate close to the one of the fully coupled climate
model, and the two models also have a similar response (collapse) of the
Atlantic meridional overturning circulation to a freshwater hosing applied in
the northern North Atlantic.

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A global hybrid coupled model based on
Atmosphere–SST feedbacks
Andrea A. Cimatoribus
Royal Netherlands Meteorological Institute,
De Bilt, The Netherlands
cimatori@knmi.nl
Sybren S. Drijfhout
Royal Netherlands Meteorological Institute,
De Bilt, The Netherlands
Henk A. Dijkstra
Institute for Marine and Atmospheric research Utrecht,
Utrecht University, Utrecht, The Netherlands
Submitted to Climate Dynamics
February 25, 2011
A global hybrid coupled model is developed, with the aim of studying the effects of
ocean–atmosphere feedbacks on the stability of the Atlantic meridional overturning
circulation. The model includes a global ocean general circulation model and a
statistical atmosphere model. The statistical atmosphere model is based on linear
regressions of data from a fully coupled climate model on sea surface temperature
both locally and hemispherically averaged, being the footprint of Atlantic meridional
overturning variability. It provides dynamic boundary conditions to the ocean model
for heat, freshwater and wind–stress. A basic but consistent representation of ocean–
atmosphere feedbacks is captured in the hybrid coupled model and it is more than
ten times faster than the fully coupled climate model. The hybrid coupled model
reaches a steady state with a climate close to the one of the fully coupled climate
model, and the two models also have a similar response (collapse) of the Atlantic
meridional overturning circulation to a freshwater hosing applied in the northern
North Atlantic.
1 Introduction
Since the pioneering work by Stommel (1961) on a conceptual model of the ther-
mohaline circulation, the problem of the stability of the Atlantic Meridional Over-
turning Circulation (AMOC) has become one of the main issues in climate research.
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A collapse of the AMOC is often used to explain abrupt changes in past climate
records. In recent years, a possible AMOC collapse in response to increased fresh-
water forcing in the northern North Atlantic, expected as a consequence of global
warming, has been identified as a low probability but high risk future climate event
(Broecker, 1997; Clark et al., 2002; Alley et al., 2003).
An abrupt collapse of the AMOC, in response to a quasi–equilibrium increase in
freshwater forcing in the North Atlantic, has been reported in different ocean and
climate models of intermediate complexity (EMICs) (Rahmstorf et al., 2005). This
implies a non–linear response of the ocean to the freshwater forcing, with a sudden
collapse of the overturning above a threshold value of the freshwater forcing. The
EMIC results are challenged by the model experiments of Yin et al. (2006) and by
IPCC–AR4 general circulation model (GCM) results, as analysed in Schmittner et al.
(2005). In the latter, it is found that the AMOC strength decreases approximately
linearly in response to a CO2increase according to the SRES–A1B scenario and there
is no collapse. It must be noted that the simulations to detect possible multiple
equilibria regimes of the AMOC in these GCMs have not been done. The near–
linear response to the gradual freshwater flux perturbation as found in Schmittner
et al. (2005) does not rule out the possibility of a sudden collapse with a stronger
freshwater flux.
However, from the GCM results it has been suggested that the existence of a
multiple equilibria regime is an artifact of ocean–only models, and in particular of
poor (or absent) representation of ocean–atmosphere interactions. In an ocean–only
model, the salt advection feedback is the central feedback affecting the stability of the
AMOC. When an atmosphere is coupled to the ocean model, other feedbacks, due
to the ocean–atmosphere interaction, become relevant. The effect of these feedbacks
may eventually overcome the effect of the salt–advection feedback, and remove the
multiple equilibria found in ocean–only models and EMICS.
In some models, the response of the atmosphere to AMOC changes may indeed
act to stabilise the present day AMOC (Vellinga et al., 2002; Stouffer et al., 2006).
In particular, the southward shift of the intertropical convergence zone would en-
hance the surface salinity of the Atlantic north of the equator, increasing the north-
ward salinity transport by the northern hemispheric gyres (Krebs and Timmermann,
2007; Vellinga et al., 2002). The decrease in the atmospheric temperature of the
Northern Hemisphere (NH), as a consequence of the AMOC collapse, may also play
a role (Stouffer et al., 2006). Lower atmospheric temperatures would determine
stronger heat extraction from the ocean and, consequently, higher densities of sur-
face waters. This effect may be more than compensated by the insulating effect of
a NH ice cover extending more to the south (Vellinga et al., 2002). The potential
impact of changes in the wind–stress, in particular zonal wind–stress, has recently
been investigated in Arzel et al. (2010), but the magnitude of the changes induced
by the wind–stress feedback remains unclear.
The question that must be answered is: “Do the atmospheric feedbacks remove the
multiple equilibria regime of AMOC, as found in ocean–only models and EMICs?”
The first step to try to answer this question is, in our view, to find a simple, but quan-
titative, description of these atmospheric feedbacks, extending that of box–model
representations (Nakamura et al., 1994). Only when a quantitative description of
the feedbacks is available, it is possible to assess the impact of the ocean–atmosphere
interaction on the stability properties of the AMOC. Studies to isolate the effect of
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the different feedbacks using a GCM are computationally expansive. Furthermore,
the complexity of a full GCM can hinder the understanding of the relevant processes
in the system. For these reasons, simpler atmospheric models are needed to provide
dynamic boundary conditions to full ocean GCMs. Their design can benefit from
the fact that the atmosphere, on the ocean time scales, can effectively be treated as
a “fast” component that adjusts to the ocean anomalies. These coupled models are
often referred to as “hybrid coupled models” (HCMs).
Since the main known atmosphere–ocean coupled mode of variability is the El
Ni˜ no Southern Oscillation (ENSO), HCMs have been developed mainly to study
this phenomenon, focusing on the interaction between wind and sea surface temper-
ature (SST) in the tropical oceans. In this framework, the main atmosphere–ocean
interaction to include in the model is the change in the zonal winds over the equato-
rial Pacific in response to SST anomalies (Cane, 1986). Barnett et al. (1993) used
a statistical model of the wind–stress based on an empirical orthogonal function
decomposition of real data, coupled to a regional GCM of the equatorial Pacific.
They found good forecasting skill for ENSO variability prediction, and HCMs have
been extensively used for ENSO forecasting since then (Latif et al., 1998). Singular
value decomposition of observational data has been used in Syu et al. (1995), to
implement an anomaly model of wind–stress for the equatorial Pacific. The HCM
including this model has been used to investigate the role of ENSO–like feedbacks
in seasonal variability. In Burgers and van Oldenborgh (2003), linear regressions on
Ni˜ no–3 and Ni˜ no–4 indexes are used in combination with a red noise term to study
the importance of local wind feedbacks in the Tropical Pacific. Singular value decom-
position in combination with a stochastic term has been used also in von Storch et al.
(2005). In these studies, only the wind–stress–SST interaction has been considered,
but other feedbacks are also active in the ocean–atmosphere system. Changes in
wind speed affect evaporation and, as a consequence, surface temperature (Neelin
et al., 1987). Also the freshwater flux is correlated to SST, through the triggering
of convective events in the atmosphere (Graham and Barnett, 1987; Zhang et al.,
1995).
Our aim here is to develop a global HCM that includes all the main atmosphere–
ocean feedbacks relevant for the stability of the AMOC, in an approach that focuses
on the quasi–steady state behaviour rather than on variability. As we want to fol-
low an approach as general as possible, we regress all the surface fluxes pointwise on
SST. Since the SST variability has a typical extent ranging from regional to basin
scale, the atmosphere–ocean interaction is roughly captured by this local approach.
In the HCM, two linear perturbation terms dependent on SST are added to the
climatology of the forcing fields of the ocean model. A term depending on the local
SST anomaly represents the atmosphere–ocean feedbacks that are acting in a statis-
tical steady state. The large–scale changes in the surface fluxes due to the collapse
of the AMOC can not be described by these local regressions alone, but are included
through a second linear term that depends on the anomalous strength of the over-
turning circulation itself, measured through the NH annual average SST anomaly.
Taken together, the local– and large–scale terms give a simple representation of the
atmospheric feedbacks which play a role in the stability of the AMOC.
As a demonstration of concept, our regressions are based on the output of an
EMIC (described in section 2). The linear atmospheric feedback representations
are presented in section 3 with results in section 4. The performance of the HCM
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is compared to the one of the original EMIC in section 5. With both local and
large–scale regression terms, the HCM captures the changes in atmospheric fluxes
in response to AMOC changes. The advantages of the HCM over the EMIC are that
(i) a more than ten fold decrease in computation time is achieved and (ii) it gives
the possibility to selectively investigate the effect of different physical processes on
the stability of the AMOC separately.
2 The EMIC SPEEDO
The HCM is constructed from data of the EMIC SPEEDO (Severijns and Hazeleger,
2009), an intermediate complexity coupled atmosphere/land/ocean/sea–ice general
circulation model. The choice for an EMIC is motivated by the fact that multi–
thousand year runs are needed to construct the HCM, which is at the moment not
feasible with a GCM.
The atmospheric component of SPEEDO is a modified version of Speedy (Molteni,
2003; Kucharski and Molteni, 2003; Bracco et al., 2004; Hazeleger and Haarsma,
2005; Breugem et al., 2007), an atmospheric GCM, having a horizontal spectral
resolution of T30 with a horizontal Gaussian latitude–longitude grid (approximately
3◦resolution) and 8 vertical density levels. Simple parameterisation are included
for large–scale condensation, convection, radiation, clouds and vertical diffusion. A
simple land model is included, with three soil layers and up to two snow layers. The
hydrological cycle is represented with the collection of precipitation in the main river
basins and outflow in the ocean at specific positions. Freezing and melting of soil
moisture is included.
The ocean model component of SPEEDO is the CLIO model (Goosse and Fichefet,
1999). It has approximately a 3◦× 3◦resolution in the horizontal, with 20 vertical
layers ranging in resolution from 10 m to 750 m from the surface to the bottom.
The horizontal grid of the ocean model is curvilinear, and deviates from a latitude–
longitude one in the north Atlantic and Arctic basins to avoid the singularity of the
north pole. A convective adjustment scheme, increasing vertical diffusivity when
the water column is unstably stratified, is used in the model. LIM sea–ice model is
included in CLIO (Graham and Barnett, 1987). A coupler provides the boundary
conditions to the components, and performs the interpolations between the different
ocean and atmosphere model grids in a conservative way.
Studies conducted both with an EMIC (de Vries and Weber, 2005) and with a
fully implicit ocean model (Huisman et al., 2010) showed the fundamental role of the
salinity budget at the southern boundary of the Atlantic ocean in determining the
response of the AMOC to freshwater anomalies (Rahmstorf, 1996). The value of the
net freshwater transport by the overturning circulation at 35◦S, shorthanded Mov,
is likely a control parameter that signals the coexistence of two stable equilibria of
the AMOC. If Movis positive, the AMOC is importing freshwater into the Atlantic
basin and only the present–day “ON” state of the overturning is stable. If Movis
negative, freshwater is exported out of the basin by the AMOC, and a second stable
“OFF” state of the AMOC exists, with reversed or no overturning in the Atlantic
ocean.
In the equilibrium solution of SPEEDO, the Atlantic basin integrated net evap-
oration is overestimated both with respect to most other models and to the few
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available observations (Rahmstorf, 1996). Furthermore, the zonal gradient of salin-
ity in the south Atlantic is reversed too, with a maximum on the eastern side. The
high evaporation over the basin, combined with the low freshwater import by the
gyre due to the reversed zonal salinity profile, force the overturning circulation to
import freshwater (Mov= 0.29 Sv) in order to close the budget. For these reasons,
a small freshwater flux correction is needed in the model for the purpose of our
study, since we are interested in the feedbacks connected with a permanent collapse
of the AMOC. Following the example of de Vries and Weber (2005), a freshwater
increase is applied over the eastern Atlantic, from the southern boundary to the lat-
itude of the Gibraltar strait, summing up to 0.2 Sv. A dipole correction is applied
over the southern gyre to reverse the zonal salinity profile, with a rate of 0.25 Sv1.
All the corrections are performed as a virtual salt flux, keeping the global budget
closed with an increased evaporation in the tropical Pacific and Indian oceans. As
a consequence of these corrections, the net freshwater transport of the AMOC at
the southern boundary of the Atlantic basin becomes negative (Mov= −0.069 Sv).
As proposed in de Vries and Weber (2005) and Huisman et al. (2010), this situation
may allow the coexistence of multiple equilibria of AMOC under the same boundary
conditions. Even if the data necessary for the definition of the HCM comes from 300
years of simulations alone, in the testing phase of different freshwater corrections
applied to reach the regime where the MOC can permanently collapse, several tens
of thousand years of integrations have been simulated by the EMIC (i.e., chang-
ing fresh-water correction and going to equilibrium, testing flux diagnostics, testing
whether the collapse of the AMOC is permanent), motivating the use of a fast EMIC.
The surface boundary conditions for the ocean are computed from the atmospheric
model as follows. Since the atmospheric boundary layer is represented by only one
model layer, near surface values of temperature (Tsa), wind (?Usa, the bold font indi-
cating a vector quantity) and specific humidity (Qsa) are extrapolated from the val-
ues of the model lowest full layers. Furthermore, an effective wind velocity is defined
to include the effect of unresolved wind variability as |V0| =
where Vgustis a model parameter. The ocean model provides through the coupler the
values of SST, from which also the saturation specific humidity at the surface (Qsat
is computed through the Clausius–Clapeyron equation. With these quantities, the
surface boundary conditions for the ocean are computed. The sensible (ΦSQ) and
latent heat (ΦLQ) fluxes into the ocean are obtained from the bulk formulas:
??Usa·?Usa+ V2
gust
?1
sa)
2,
ΦSQ= ρsacpCH|V0|(Tsa− SST),
ΦLQ= ρsaLHCH|V0|min??Qsa− Qsat
sa
?,0?,
(1)
where ρsa is the surface air density, cp and LH are the specific heat of air and
the latent heat of evaporation, respectively, and CHis a heat exchange coefficient,
a model parameter depending on the stability properties of the boundary layer.
The parameterisation of the radiative fluxes are more complex.
wave (ΦSW) and long–wave components (ΦLW), two and four frequency bands are
used, respectively. Transmittance is computed for each band separately, taking into
For the short–
1The model used in de Vries and Weber (2005) shares the same ocean model component as SPEEDO, but uses
ECBilt as the atmospheric model instead of Speedy. In their setup, the basin integrated net evaporation of the
Atlantic ocean is underestimated, while the zonal salinity contrast in the southern Atlantic is overestimated.
Therefore, their correction has a sign opposite to that here.
5