Dynamics and predictability of a low-order wind-driven ocean–atmosphere coupled model

The dynamics of a low-order coupled wind-driven ocean–atmosphere system is investigated with emphasis on its predictability properties. The low-order coupled deterministic system is composed of a baroclinic atmosphere for which 12 dominant dynamical modes are only retained (Charney and Straus in J Atmos Sci 37:1157–1176, 1980) and a wind-driven, quasi-geostrophic and reduced-gravity shallow ocean whose field is truncated to four dominant modes able to reproduce the large scale oceanic gyres (Pierini in J Phys Oceanogr 41:1585–1604, 2011). The two models are coupled through mechanical forcings only. The analysis of its dynamics reveals first that under aperiodic atmospheric forcings only dominant single gyres (clockwise or counterclockwise) appear, while for periodic atmospheric solutions the double gyres emerge. In the present model domain setting context, this feature is related to the level of truncation of the atmospheric fields, as indicated by a preliminary analysis of the impact of higher wavenumber (“synoptic” scale) modes on the development of oceanic gyres. In the latter case, double gyres appear in the presence of a chaotic atmosphere. Second the dynamical quantities characterizing the short-term predictability (Lyapunov exponents, Lyapunov dimension, Kolmogorov–Sinaï (KS) entropy) displays a complex dependence as a function of the key parameters of the system, namely the coupling strength and the external thermal forcing. In particular, the KS-entropy is increasing as a function of the coupling in most of the experiments, implying an increase of the rate of loss of information about the localization of the system on its attractor. Finally the dynamics of the error is explored and indicates, in particular, a rich variety of short term behaviors of the error in the atmosphere depending on the (relative) amplitude of the initial error affecting the ocean, from polynomial (at ² + bt ³ + ct ⁴) up to exponential-like evolutions. These features are explained and analyzed in the light of the recent findings on error growth (Nicolis et al. in J Atmos Sci 66:766–778, 2009).     

Predictability of the subtropical dipole modes in a coupled ocean–atmosphere model

Predictability of the subtropical dipole modes is assessed using the SINTEX-F coupled model. Despite the known difficulty in predicting subtropical climate due to large internal variability of the atmosphere and weak ocean–atmosphere coupling, it is shown for the first time that the coupled model can successfully predict the South Atlantic Subtropical Dipole (SASD) 1 season ahead, and the prediction skill is better than the persistence in all the 1–12 month lead hindcast experiments. There is a prediction barrier in austral winter due to the seasonal phase locking of the SASD to austral summer. The prediction skill is lower for the Indian Ocean Subtropical Dipole (IOSD) than for the SASD, and only slightly better than the persistence till 6-month lead because of the low predictability of the sea surface temperature anomaly in its southwestern pole. However, for some strong IOSD events in the last three decades, the model can predict them 1 season ahead. The co-occurrence of the negative SASD and IOSD in 1997/1998 austral summer can be predicted from July 1st of 1997. This is because the negative sea level pressure anomalies over the South Atlantic and the southern Indian Ocean in September–October (November–December) that trigger the occurrence of the negative SASD and IOSD are related to the well predicted tropical Indian Ocean Dipole (El Niño/Southern Oscillation). Owing to the overall good performances of the SINTEX-F model in predicting the SASD, some strong IOSD, and El Niño/Southern Oscillation, the prediction skill of the southern African summer precipitation is high in the SINTEX-F model.     

Coupled atmosphere�Cmixed layer ocean response to ocean heat flux convergence along the Kuroshio Current Extension

The winter response of the coupled atmosphere?Cocean mixed layer system to anomalous geostrophic ocean heat flux convergence in the Kuroshio Extension is investigated by means of experiments with an atmospheric general circulation model coupled to an entraining ocean mixed layer model in the extra-tropics. The direct response consists of positive SST anomalies along the Kuroshio Extension and a baroclinic (low-level trough and upper-level ridge) circulation anomaly over the North Pacific. The low-level component of this atmospheric circulation response is weaker in the case without coupling to an extratropical ocean mixed layer, especially in late winter. The inclusion of an interactive mixed layer in the tropics modifies the direct coupled atmospheric response due to a northward displacement of the Pacific Inter-Tropical Convergence Zone which drives an equivalent barotropic anomalous ridge over the North Pacific. Although the tropically driven component of the North Pacific atmospheric circulation response is comparable to the direct response in terms of sea level pressure amplitude, it is less important in terms of wind stress curl amplitude due to the mitigating effect of the relatively broad spatial scale of the tropically forced atmospheric teleconnection.     

Coupling ocean–atmosphere intensity determines ocean chlorophyll-induced SST change in the tropical Pacific

Phytoplankton pigments (e.g., chlorophyll-a) absorb solar radiation in the upper ocean and induce a pronounced radiant heating effect (chlorophyll effect) on the climate. However, the ocean chlorophyll-induced heating effect on the mean climate state in the tropical Pacific has not been understood well. Here, a hybrid coupled model (HCM) of the atmosphere, ocean physics and biogeochemistry is used to investigate the chlorophyll effect on sea surface temperature (SST) in the eastern equatorial Pacific; a tunable coefficient, α, is introduced to represent the coupling intensity between the atmosphere and ocean in the HCM. The modeling results show that the chlorophyll effect on the mean-state SST is sensitively dependent on α (the coupling intensity). At weakly represented coupling intensity (0 ≤ α < 1.01), the chlorophyll effect tends to induce an SST cooling in the eastern equatorial Pacific, whereas an SST warming emerges at the strongly represented coupling intensity (α ≥ 1.01). Thus, a threshold exists for the coupling intensity (about α = 1.01) at which the sign of SST responses can change. Mechanisms and processes are illustrated to understand the different SST responses. In the weak coupling cases, indirect dynamical cooling processes (the adjustment of ocean circulation, enhanced vertical mixing, and upwelling) tend to dominate the SST cooling. In the strong coupling cases, the persistent warming induced by chlorophyll in the southern subtropical Pacific tends to induce cross-equatorial northerly winds, which shifts to anomalous westerly winds in the eastern equatorial Pacific, consequently reducing the evaporative cooling and weakening indirect dynamical cooling; eventually, SST warming maintains in the eastern equatorial Pacific. These results provide new insights into the biogeochemical feedback on the climate and bio-physical interactions in the tropical Pacific.

     

Bi-decadal variability excited in the coupled ocean–atmosphere system by strong tropical volcanic eruptions

Decadal and bi-decadal climate responses to tropical strong volcanic eruptions (SVEs) are inspected in an ensemble simulation covering the last millennium based on the Max Planck Institute—Earth system model. An unprecedentedly large collection of pre-industrial SVEs (up to 45) producing a peak annual-average top-of-atmosphere radiative perturbation larger than ?1.5 Wm^?2 is investigated by composite analysis. Post-eruption oceanic and atmospheric anomalies coherently describe a fluctuation in the coupled ocean–atmosphere system with an average length of 20–25 years. The study provides a new physically consistent theoretical framework to interpret decadal Northern Hemisphere (NH) regional winter climates variability during the last millennium. The fluctuation particularly involves interactions between the Atlantic meridional overturning circulation and the North Atlantic gyre circulation closely linked to the state of the winter North Atlantic Oscillation. It is characterized by major distinctive details. Among them, the most prominent are: (a) a strong signal amplification in the Arctic region which allows for a sustained strengthened teleconnection between the North Pacific and the North Atlantic during the first post-eruption decade and which entails important implications from oceanic heat transport and from post-eruption sea ice dynamics, and (b) an anomalous surface winter warming emerging over the Scandinavian/Western Russian region around 10–12 years after a major eruption. The simulated long-term climate response to SVEs depends, to some extent, on background conditions. Consequently, ensemble simulations spanning different phases of background multidecadal and longer climate variability are necessary to constrain the range of possible post-eruption decadal evolution of NH regional winter climates.     

Projected climate change scenario over California by a regional ocean–atmosphere coupled model system

This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.     

Bimodality and regime behavior in atmosphere–ocean interactions during the recent climate change

Maximum covariance analysis (MCA) and isometric feature mapping (Isomap) are applied to investigate the spatio-temporal atmosphere–ocean interactions otherwise hidden in observational data for the period of 1979–2010. Despite an established long-term surface warming trend for the whole northern hemisphere, sea surface temperatures (SST) in the East Pacific have remained relatively constant for the period of 2001–2010. Our analysis reveals that SST anomaly probability density function of the leading two Isomap components is bimodal. We conclude that Isomap shows the existence of two distinct regimes in surface ocean temperature, resembling the break and active phases of rainfall over equatorial land areas. These regimes occurred within two separated time windows during the past three decades. Strengthening of trade winds over Pacific was coincident with the cold phase of east equatorial Pacific. This pattern was reversed during the warm phase of east equatorial Pacific. The El Niño event of 1997/1998 happened within the transition mode between these two regimes and may be a trigger for the SST changes in the Pacific. Furthermore, we suggest that Isomap, compared with MCA, provides more information about the behavior and predictability of the inter-seasonal atmosphere–ocean interactions.     

Impact of initialization procedures on the predictive skill of a coupled ocean–atmosphere model

The sensitivity of the predictive skill of a decadal climate prediction system is investigated with respect to details of the initialization procedure. For this purpose, the coupled ocean–atmosphere UCLA/MITgcm climate model is initialized using the following three different initialization approaches: full state initialization (FSI), anomaly initialization (AI) and FSI employing heat flux and freshwater flux corrections (FC). The ocean initial conditions are provided by the German contribution to Estimating the Circulation and Climate of the Ocean state estimate (GECCO project), from which ensembles of decadal hindcasts are initialized every 5 years from 1961 to 2001. The predictive skill for sea surface temperature (SST), sea surface height (SSH) and the Atlantic meridional overturning circulation (AMOC) is assessed against the GECCO synthesis. In regions with a deep mixed layer the predictive skill for SST anomalies remains significant for up to a decade in the FC experiment. By contrast, FSI shows less persistent skill in the North Atlantic and AI does not show high skill in the extratropical Southern Hemisphere, but appears to be more skillful in the tropics. In the extratropics, the improved skill is related to the ability of the FC initialization method to better represent the mixed layer depth, and the highest skill occurs during wintertime. The correlation skill for the spatially averaged North Atlantic SSH hindcasts remains significant up to a decade only for FC. The North Atlantic MOC initialized hindcasts show high correlation values in the first pentad while correlation remains significant in the following pentad too for FSI and FC. Overall, for the current setup, the FC approach appears to lead to the best results, followed by the FSI and AI procedures.     

Interannual variations of the boreal summer intraseasonal variability predicted by ten atmosphere–ocean coupled models

The reproducibility of boreal summer intraseasonal variability (ISV) and its interannual variation by dynamical models are assessed through diagnosing 21-year retrospective forecasts from ten state-of-the-art ocean–atmosphere coupled prediction models. To facilitate the assessment, we have defined the strength of ISV activity by the standard deviation of 20–90 days filtered precipitation during the boreal summer of each year. The observed climatological ISV activity exhibits its largest values over the western North Pacific and Indian monsoon regions. The notable interannual variation of ISV activity is found primarily over the western North Pacific in observation while most models have the largest variability over the central tropical Pacific and exhibit a wide range of variability in spatial patterns that are different from observation. Although the models have large systematic biases in spatial pattern of dominant variability, the leading EOF modes of the ISV activity in the models are closely linked to the models’ El Nino-Southern Oscillation (ENSO), which is a feature that resembles the observed ISV and ENSO relationship. The ENSO-induced easterly vertical shear anomalies in the western and central tropical Pacific, where the summer mean vertical wind shear is weak, result in ENSO-related changes of ISV activity in both observation and models. It is found that the principal components of the predicted dominant modes of ISV activity fluctuate in a very similar way with observed ones. The model biases in the dominant modes are systematic and related to the external SST forcing. Thus the statistical correction method of this study based on singular value decomposition is capable of removing a large portion of the systematic errors in the predicted spatial patterns. The 21-year-averaged pattern correlation skill increases from 0.25 to 0.65 over the entire Asian monsoon region after applying the bias correction method to the multi-model ensemble mean prediction.     

An efficient climate model with a 3D ocean and statistical–dynamical atmosphere*

We describe a coupled climate model of intermediate complexity designed for use in global warming experiments. The atmospheric component is a two-dimensional (zonally averaged) statistical-dynamical model based on the Goddard Institute for Space Study's atmospheric general circulation model (GCM). In contrast with energy-balance models used in some climate models of intermediate complexity, this model includes full representation of the hydrological and momentum cycles. It also has parameterizations of the main physical processes, including a sophisticated radiation code. The ocean component is a coarse resolution ocean GCM with simplified global geometry based on the Geophysical Fluid Dynamics Laboratory modular ocean model. Because of the simplified geometry the resolution in the western boundary layers can be readily increased compared to conventional coarse resolution models, without increasing the model's computational requirements in a significant way. The ocean model's efficiency is also greatly increased by using a moderate degree of asynchronous coupling between the oceanic momentum and tracer fields. We demonstrate that this still allows an accurate simulation of transient behavior, including the seasonal cycle. A 100 years simulation with the model requires less than 8 hours on a state-of the art workstation. The main novelty of the model is therefore a combination of computational efficiency, statistical-dynamical atmosphere and 3D ocean. Long-term present-day climate simulations are carried out using the coupled model with and without flux adjustments, and with either the Gent-McWilliams (GM) parametrization scheme or horizontal diffusion (HD) in the ocean. Deep ocean temperatures systematically decrease in the runs without flux adjustment. We demonstrate that the mismatch between heat transports in the uncoupled states of two models is the main cause for the systematic drift. In addition, changes in the circulation and sea-ice formation also contribute to the drift. Flux adjustments in the freshwater fluxes are shown to have a stabilizing effect on the thermohaline circulation in the model, whereas the adjustments in the heat fluxes tend to weaken the global "conveyor". To evaluate the model's response to transient external forcing global warming simulations are also carried out with the flux-adjusted version of the coupled model. The coupled model reproduces reasonably well the behavior of more sophisticated coupled GCMs for both current climate and for the global warming scenarios.     

Coupled atmosphere–ocean data assimilation experiments with a low-order climate model

A simple idealized atmosphere–ocean climate model and an ensemble Kalman filter are used to explore different coupled ensemble data assimilation strategies. The model is a low-dimensional analogue of the North Atlantic climate system, involving interactions between large-scale atmospheric circulation and ocean states driven by the variability of the Atlantic meridional overturning circulation (MOC). Initialization of the MOC is assessed in a range of experiments, from the simplest configuration consisting of forcing the ocean with a known atmosphere to performing fully coupled ensemble data assimilation. “Daily” assimilation (that is, at the temporal frequency of the atmospheric observations) is contrasted with less frequent assimilation of time-averaged observations. Performance is also evaluated under scenarios in which ocean observations are limited to the upper ocean or are non-existent. Results show that forcing the idealized ocean model with atmospheric analyses is inefficient at recovering the slowly evolving MOC. On the other hand, daily assimilation rapidly leads to accurate MOC analyses, provided a comprehensive set of oceanic observations is available for assimilation. In the absence of sufficient observations in the ocean, the assimilation of time-averaged atmospheric observations proves to be more effective for MOC initialization, including the case where only atmospheric observations are available.     

Isolating mesoscale coupled ocean–atmosphere interactions in the Kuroshio Extension region

The Kuroshio Extension region is characterized by energetic oceanic mesoscale and frontal variability that alters the air–sea fluxes that can influence large-scale climate variability in the North Pacific. We investigate this mesoscale air-sea coupling using a regional eddy-resolving coupled ocean–atmosphere (OA) model that downscales the observed large-scale climate variability from 2001 to 2007. The model simulates many aspects of the observed seasonal cycle of OA coupling strength for both momentum and turbulent heat fluxes. We introduce a new modeling approach to study the scale-dependence of two well-known mechanisms for the surface wind response to mesoscale sea surface temperatures (SSTs), namely, the ‘vertical mixing mechanism’ (VMM) and the ‘pressure adjustment mechanism’ (PAM). We compare the fully coupled model to the same model with an online, 2-D spatial smoother applied to remove the mesoscale SST field felt by the atmosphere. Both VMM and PAM are found to be active during the strong wintertime peak seen in the coupling strength in both the model and observations. For VMM, large-scale SST gradients surprisingly generate coupling between downwind SST gradient and wind stress divergence that is often stronger than the coupling on the mesoscale, indicating their joint importance in OA interaction in this region. In contrast, VMM coupling between crosswind SST gradient and wind stress curl occurs only on the mesoscale, and not over large-scale SST gradients, indicating the essential role of the ocean mesocale. For PAM, the model results indicate that coupling between the Laplacian of sea level pressure and surface wind convergence occurs for both mesoscale and large-scale processes, but inclusion of the mesoscale roughly doubles the coupling strength. Coupling between latent heat flux and SST is found to be significant throughout the entire seasonal cycle in both fully coupled mode and large-scale coupled mode, with peak coupling during winter months. The atmospheric response to the oceanic mesoscale SST is also studied by comparing the fully coupled run to an uncoupled atmospheric model forced with smoothed SST prescribed from the coupled run. Precipitation anomalies are found to be forced by surface wind convergence patterns that are driven by mesoscale SST gradients, indicating the importance of the ocean forcing the atmosphere at this scale.     

Coupled atmosphere–ocean data assimilation experiments with a low-order model and CMIP5 model data

Climate Dynamics - Coupled atmosphere–ocean data assimilation (DA) experiments are performed for estimating the Atlantic meridional overturning circulation (AMOC). Recovery of the AMOC with...     

Uncertainty in the ocean–atmosphere feedbacks associated with ENSO in the reanalysis products

The evolution of El Ni?o-Southern Oscillation (ENSO) variability can be characterized by various ocean–atmosphere feedbacks, for example, the influence of ENSO related sea surface temperature (SST) variability on the low-level wind and surface heat fluxes in the equatorial tropical Pacific, which in turn affects the evolution of the SST. An analysis of these feedbacks requires physically consistent observational data sets. Availability of various reanalysis data sets produced during the last 15?years provides such an opportunity. A consolidated estimate of ocean surface fluxes based on multiple reanalyses also helps understand biases in ENSO predictions and simulations from climate models. In this paper, the intensity and the spatial structure of ocean–atmosphere feedback terms (precipitation, surface wind stress, and ocean surface heat flux) associated with ENSO are evaluated for six different reanalysis products. The analysis provides an estimate for the feedback terms that could be used for model validation studies. The analysis includes the robustness of the estimate across different reanalyses. Results show that one of the “coupled” reanalysis among the six investigated is closer to the ensemble mean of the results, suggesting that the coupled data assimilation may have the potential to better capture the overall atmosphere–ocean feedback processes associated with ENSO than the uncoupled ones.     

A multi-model study of atmosphere predictability in coupled ocean–atmosphere systems

Of great importance for guiding numerical weather and climate predictions, understanding predictability of the atmosphere in the ocean − atmosphere coupled system is the first and critical step to understand predictability of the Earth system. However, previous predictability studies based on prefect model assumption usually depend on a certain model. Here we apply the predictability study with the Nonlinear Local Lyapunov Exponent and Attractor Radius to the products of multiple re-analyses and forecast models in several operational centers to realize general predictability of the atmosphere in the Earth system. We first investigated the predictability characteristics of the atmosphere in NCEP, ECMWF and UKMO coupled systems and some of their uncoupled counterparts and other uncoupled systems. Although the ECMWF Integrated Forecast System shows higher skills in geopotential height over the tropics, there is no certain model providing the most precise forecast for all variables on all levels and the multi-model ensemble not always outperforms a single model. Improved low-frequency signals from the air − sea and stratosphere − troposphere interactions that extend predictability of the atmosphere in coupled system suggests the significance of air − sea coupling and stratosphere simulation in practical forecast development, although uncertainties exist in the model representation for physical processes in air − sea interactions and upper troposphere. These inspire further exploration on predictability of ocean and stratosphere as well as sea − ice and land processes to advance our understanding of interactions of Earth system components, thus enhancing weather − climate prediction skills.

     

Thirty-two-year ocean–atmosphere coupled downscaling of global reanalysis over the Intra-American Seas

This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean–Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean–atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well.     

Time-dependent response of a zonally averaged ocean–atmosphere–sea ice model to Milankovitch forcing

An ocean–atmosphere–sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5–3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (1) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (2) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45°N and 65°N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60°S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point.     

An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation

We present an atmosphere–ocean regional climate model for the Mediterranean basin, called the PROTHEUS system, composed by the regional climate model RegCM3 as the atmospheric component and by a regional configuration of the MITgcm model as the oceanic component. The model is applied to an area encompassing the Mediterranean Sea and compared to a stand-alone version of its atmospheric component. An assessment of the model performances is done by using available observational datasets. Despite a persistent bias, the PROTHEUS system is able to capture the inter-annual variability of seasonal sea surface temperature (SST) and also the fine scale spatio-temporal evolution of observed SST anomalies, with spatial correlation as high as 0.7 during summer. The close inspection of a 10-day strong wind event during the summer of 2000 proves the capability of the PROTHEUS system to correctly describe the daily evolution of SST under strong air–sea interaction conditions. As a consequence of the model’s skill in reproducing observed SST and wind fields, we expect a reliable estimation of air–sea fluxes. The model skill in reproducing climatological land surface fields is in line with that of state of the art regional climate models.     

Impact of a realistic river routing in coupled ocean–atmosphere simulations of the Last Glacial Maximum climate

The presence of large ice sheets over North America and North Europe at the Last Glacial Maximum (LGM) strongly impacted Northern hemisphere river pathways. Despite the fact that such changes may significantly alter the freshwater input to the ocean, modified surface hydrology has never been accounted for in coupled ocean–atmosphere general circulation model simulations of the LGM climate. To reconstruct the LGM river routing, we use the ICE-5G LGM topography. Because of the uncertainties in the extent of the Fennoscandian ice sheet in the Eastern part of the Kara Sea, we consider two more realistic river routing scenarios. The first scenario is characterised by the presence of an ice dammed lake south of the Fennoscandian ice sheet, and corresponds to the ICE-5G topography. This lake is fed by the Ob and Yenisei rivers. In the second scenario, both these rivers flow directly into the Arctic Ocean, which is more consistent with the latest QUEEN ice sheet margin reconstructions. We study the impact of these changes on the LGM climate as simulated by the IPSL_CM4 model and focus on the overturning thermohaline circulation. A comparison with a classical LGM simulation performed using the same model and modern river basins as designed in the PMIP2 exercise leads to the following conclusions: (1) The discharge into the North Atlantic Ocean is increased by 2,000 m³/s between 38° and 54°N in both simulations that contain LGM river routing, compared to the classical LGM experiment. (2) The ice dammed lake is shown to have a weak impact, relative to the classical simulation, both in terms of climate and ocean circulation. (3) In contrast, the North Atlantic deep convection and meridional overturning are weaker than during the classical LGM run if the Ob and Yenisei rivers flow directly into the Arctic Ocean. The total discharge into the Arctic Ocean is increased by 31,000 m³/s, relative to the classical LGM simulation. Consequentially, northward ocean heat transport is weaker, and sea ice more extensive, in better agreement with existing proxy data.