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Abstract
The simulated impact of the Atlantic meridional overturning circulation (AMOC) on the low-frequency variability of the Arctic surface air temperature (SAT) and sea ice extent is studied with a 1000-year-long segment of a control simulation of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1. The simulated AMOC variations in the control simulation are found to be significantly anticorrelated with the Arctic sea ice extent anomalies and significantly correlated with the Arctic SAT anomalies on decadal time scales in the Atlantic sector of the Arctic. The maximum anticorrelation with the Arctic sea ice extent and the maximum correlation with the Arctic SAT occur when the AMOC index leads by one year. An intensification of the AMOC is associated with a sea ice decline in the Labrador, Greenland, and Barents Seas in the control simulation, with the largest change occurring in winter. The recent declining trend in the satellite-observed sea ice extent also shows a similar pattern in the Atlantic sector of the Arctic in the winter, suggesting the possibility of a role of the AMOC in the recent Arctic sea ice decline in addition to anthropogenic greenhouse-gas-induced warming. However, in the summer, the simulated sea ice response to the AMOC in the Pacific sector of the Arctic is much weaker than the observed declining trend, indicating a stronger role for other climate forcings or variability in the recently observed summer sea ice decline in the Chukchi, Beaufort, East Siberian, and Laptev Seas.
Abstract
The simulated impact of the Atlantic meridional overturning circulation (AMOC) on the low-frequency variability of the Arctic surface air temperature (SAT) and sea ice extent is studied with a 1000-year-long segment of a control simulation of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1. The simulated AMOC variations in the control simulation are found to be significantly anticorrelated with the Arctic sea ice extent anomalies and significantly correlated with the Arctic SAT anomalies on decadal time scales in the Atlantic sector of the Arctic. The maximum anticorrelation with the Arctic sea ice extent and the maximum correlation with the Arctic SAT occur when the AMOC index leads by one year. An intensification of the AMOC is associated with a sea ice decline in the Labrador, Greenland, and Barents Seas in the control simulation, with the largest change occurring in winter. The recent declining trend in the satellite-observed sea ice extent also shows a similar pattern in the Atlantic sector of the Arctic in the winter, suggesting the possibility of a role of the AMOC in the recent Arctic sea ice decline in addition to anthropogenic greenhouse-gas-induced warming. However, in the summer, the simulated sea ice response to the AMOC in the Pacific sector of the Arctic is much weaker than the observed declining trend, indicating a stronger role for other climate forcings or variability in the recently observed summer sea ice decline in the Chukchi, Beaufort, East Siberian, and Laptev Seas.
Abstract
Satellite-based ocean color measurements indicate clear evidence for bioclimate interactions in the tropical Pacific associated with El Niño–Southern Oscillation (ENSO). Recent modeling studies have demonstrated that ocean biology can potentially affect the climate through the penetration depth of solar radiation in the upper ocean (Hp ), a primary parameter in coupling biology to physics in the ocean. At present, interannual variability in Hp and its related bioclimate feedback effects have not been adequately represented in coupled ocean–atmosphere models. In this work, chlorophyll (Chl) concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), available since 1997, are used to characterize interannual Hp variability in the tropical Pacific and to quantify its relationships with physical fields, including sea surface temperature (SST) and sea level (SL). It is found that interannual Hp variability is dominated by ENSO signals, with the largest variability located in the central basin near the date line and a coherent relationship with SST. A singular value decomposition (SVD) analysis is adopted to extract interannual covariability patterns between Hp and SST during the period 1997–2007. Their close relationships are then utilized to construct an empirical anomaly model for Hp , allowing for its prognostic estimate in terms of SST anomalies without explicit involvement of a marine ecosystem model. Validation and sensitivity experiments indicate that the empirical model can reasonably well capture interannual Hp responses to SST anomalies in association with ENSO. The derived empirical Hp model offers a simple and an effective way to parameterize and represent the effects of Chl containing biomass on penetrative solar radiation in the tropical Pacific, demonstrating the dynamical implication of remotely sensed Chl data for bioclimate coupling studies. Further improvements and applications of the empirical Hp model to climate modeling are discussed.
Abstract
Satellite-based ocean color measurements indicate clear evidence for bioclimate interactions in the tropical Pacific associated with El Niño–Southern Oscillation (ENSO). Recent modeling studies have demonstrated that ocean biology can potentially affect the climate through the penetration depth of solar radiation in the upper ocean (Hp ), a primary parameter in coupling biology to physics in the ocean. At present, interannual variability in Hp and its related bioclimate feedback effects have not been adequately represented in coupled ocean–atmosphere models. In this work, chlorophyll (Chl) concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), available since 1997, are used to characterize interannual Hp variability in the tropical Pacific and to quantify its relationships with physical fields, including sea surface temperature (SST) and sea level (SL). It is found that interannual Hp variability is dominated by ENSO signals, with the largest variability located in the central basin near the date line and a coherent relationship with SST. A singular value decomposition (SVD) analysis is adopted to extract interannual covariability patterns between Hp and SST during the period 1997–2007. Their close relationships are then utilized to construct an empirical anomaly model for Hp , allowing for its prognostic estimate in terms of SST anomalies without explicit involvement of a marine ecosystem model. Validation and sensitivity experiments indicate that the empirical model can reasonably well capture interannual Hp responses to SST anomalies in association with ENSO. The derived empirical Hp model offers a simple and an effective way to parameterize and represent the effects of Chl containing biomass on penetrative solar radiation in the tropical Pacific, demonstrating the dynamical implication of remotely sensed Chl data for bioclimate coupling studies. Further improvements and applications of the empirical Hp model to climate modeling are discussed.
Abstract
A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te ), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period.
Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system.
Abstract
A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te ), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period.
Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system.
Abstract
This study investigates spatiotemporal features of multidecadal climate variability using observations and climate model simulation. Aside from a long-term warming trend, observational SST and atmospheric circulation records are dominated by an almost 65-yr variability component. Although its center of action is over the North Atlantic, it manifests also over the Pacific and Indian Oceans, suggesting a tropical interbasin teleconnection maintained through an atmospheric bridge. An analysis shows that simulated internal climate variability in a coupled climate model (CSIRO Mk3.6.0) reproduces the main spatiotemporal features of the observed component. Model-based multidecadal variability includes a coupled ocean–atmosphere teleconnection, established through a zonally oriented atmospheric overturning circulation between the tropical North Atlantic and eastern tropical Pacific. During the warm SST phase in the North Atlantic, increasing SSTs over the tropical North Atlantic strengthen locally ascending air motion and intensify subsidence and low-level divergence in the eastern tropical Pacific. This corresponds with a strengthening of trade winds and cooling in the tropical central Pacific. The model’s derived component substantially shapes its global climate variability and is tightly linked to multidecadal variability of the Atlantic meridional overturning circulation (AMOC). This suggests potential predictive utility and underscores the importance of correctly representing North Atlantic variability in simulations of global and regional climate. If the observations-based component of variability originates from internal climate processes, as found in the model, the recently observed (1970s–2000s) North Atlantic warming and eastern tropical Pacific cooling might presage an ongoing transition to a cold North Atlantic phase with possible implications for near-term global temperature evolution.
Abstract
This study investigates spatiotemporal features of multidecadal climate variability using observations and climate model simulation. Aside from a long-term warming trend, observational SST and atmospheric circulation records are dominated by an almost 65-yr variability component. Although its center of action is over the North Atlantic, it manifests also over the Pacific and Indian Oceans, suggesting a tropical interbasin teleconnection maintained through an atmospheric bridge. An analysis shows that simulated internal climate variability in a coupled climate model (CSIRO Mk3.6.0) reproduces the main spatiotemporal features of the observed component. Model-based multidecadal variability includes a coupled ocean–atmosphere teleconnection, established through a zonally oriented atmospheric overturning circulation between the tropical North Atlantic and eastern tropical Pacific. During the warm SST phase in the North Atlantic, increasing SSTs over the tropical North Atlantic strengthen locally ascending air motion and intensify subsidence and low-level divergence in the eastern tropical Pacific. This corresponds with a strengthening of trade winds and cooling in the tropical central Pacific. The model’s derived component substantially shapes its global climate variability and is tightly linked to multidecadal variability of the Atlantic meridional overturning circulation (AMOC). This suggests potential predictive utility and underscores the importance of correctly representing North Atlantic variability in simulations of global and regional climate. If the observations-based component of variability originates from internal climate processes, as found in the model, the recently observed (1970s–2000s) North Atlantic warming and eastern tropical Pacific cooling might presage an ongoing transition to a cold North Atlantic phase with possible implications for near-term global temperature evolution.
Abstract
The El Niño–Southern Oscillation (ENSO) has been observed to exhibit decadal changes in its properties; the cause and implication of such changes are strongly debated. Here the authors examine the influences of two particular attributors of the ocean–atmospheric system. The roles of stochastic forcing (SF) in the atmosphere and decadal changes in the temperature of subsurface water entrained into the mixed layer (Te ) in modulating ENSO are compared to one another using coupled ocean–atmosphere models of the tropical Pacific climate system. Two types of coupled models are used. One is an intermediate coupled model (ICM) and another is a hybrid coupled model (HCM), both of which consist of the same intermediate ocean model (IOM) with an empirical parameterization for Te , constructed via singular value decomposition (SVD) analysis of the IOM simulated historical data. The differences in the ICM and HCM are in the atmospheric component: the one in the ICM is an empirical feedback model for wind stress (τ), and that in the HCM is an atmospheric general circulation model (AGCM; ECHAM4.5). The deterministic component of atmospheric τ variability, representing its signal response (τ Sig) to an external SST forcing, is constructed statistically by an SVD analysis from a 24-member ensemble mean of the ECHAM4.5 AGCM simulations forced by observed SST; the SF component (τ SF) is explicitly estimated from the ECHAM4.5 AGCM ensemble and HCM simulations. Different SF representations are specified in the atmosphere: the SF effect can be either absent or present explicitly in the ICM, or implicitly in the HCM where the ECHAM4.5 AGCM is used as a source for SF. Decadal changes in the ocean thermal structure observed in the late 1970s are incorporated into the coupled systems through the Te parameterizations for the two subperiods before (1963–79) and after (1980–96) the climate shift (T 63–79 e and T 80–96 e ), respectively.
The ICM and HCM simulations well reproduce interannual variability associated with El Niño in the tropical Pacific. Model sensitivity experiments are performed using these two types of coupled models with different realizations of SF in the atmosphere and specifications of decadal Te changes in the ocean. It is demonstrated that the properties of ENSO are modulated differently by these two factors. The decadal Te changes in the ocean can be responsible for a systematic shift in the phase propagation of ENSO, while the SF in the atmosphere can contribute to the amplitude and period modulation in a random way. The relevance to the observed decadal ENSO variability in the late 1970s is discussed.
Abstract
The El Niño–Southern Oscillation (ENSO) has been observed to exhibit decadal changes in its properties; the cause and implication of such changes are strongly debated. Here the authors examine the influences of two particular attributors of the ocean–atmospheric system. The roles of stochastic forcing (SF) in the atmosphere and decadal changes in the temperature of subsurface water entrained into the mixed layer (Te ) in modulating ENSO are compared to one another using coupled ocean–atmosphere models of the tropical Pacific climate system. Two types of coupled models are used. One is an intermediate coupled model (ICM) and another is a hybrid coupled model (HCM), both of which consist of the same intermediate ocean model (IOM) with an empirical parameterization for Te , constructed via singular value decomposition (SVD) analysis of the IOM simulated historical data. The differences in the ICM and HCM are in the atmospheric component: the one in the ICM is an empirical feedback model for wind stress (τ), and that in the HCM is an atmospheric general circulation model (AGCM; ECHAM4.5). The deterministic component of atmospheric τ variability, representing its signal response (τ Sig) to an external SST forcing, is constructed statistically by an SVD analysis from a 24-member ensemble mean of the ECHAM4.5 AGCM simulations forced by observed SST; the SF component (τ SF) is explicitly estimated from the ECHAM4.5 AGCM ensemble and HCM simulations. Different SF representations are specified in the atmosphere: the SF effect can be either absent or present explicitly in the ICM, or implicitly in the HCM where the ECHAM4.5 AGCM is used as a source for SF. Decadal changes in the ocean thermal structure observed in the late 1970s are incorporated into the coupled systems through the Te parameterizations for the two subperiods before (1963–79) and after (1980–96) the climate shift (T 63–79 e and T 80–96 e ), respectively.
The ICM and HCM simulations well reproduce interannual variability associated with El Niño in the tropical Pacific. Model sensitivity experiments are performed using these two types of coupled models with different realizations of SF in the atmosphere and specifications of decadal Te changes in the ocean. It is demonstrated that the properties of ENSO are modulated differently by these two factors. The decadal Te changes in the ocean can be responsible for a systematic shift in the phase propagation of ENSO, while the SF in the atmosphere can contribute to the amplitude and period modulation in a random way. The relevance to the observed decadal ENSO variability in the late 1970s is discussed.
Abstract
Various forcing and feedback processes coexist in the tropical Pacific, which can modulate El Niño–Southern Oscillation (ENSO). In particular, large covariabilities in chlorophyll (Chl) and freshwater flux (FWF) at the sea surface are observed during ENSO cycles, acting to execute feedbacks on ENSO through the related ocean-biology-induced heating (OBH) and FWF forcing, respectively. At present, the related effects and underlying mechanism are strongly model dependent and are still not well understood. Here, a new hybrid coupled model (HCM), developed to represent interactions between the atmosphere and ocean physics–biology (AOPB) in the tropical Pacific, is used to examine the extent to which ENSO can be modulated by interannually covarying anomalies of FWF and Chl. HCM AOPB–based sensitivity experiments indicate that individually the FWF forcing tends to amplify ENSO via its influence on the stratification and vertical mixing in the upper ocean, whereas the OBH feedback tends to damp it. While the FWF- and OBH-related individual effects tend to counteract each other, their combined effects give rise to unexpected situations. For example, an increase in the FWF forcing intensity actually acts to decrease the ENSO amplitude when the OBH feedback effects coexist at a certain intensity. The nonlinear modulation of the ENSO amplitude can happen when the FWF-related amplifying effects on ENSO are compensated for by OBH-related damping effects. The results offer insight into modulating effects on ENSO, which are evident in nature and different climate models.
Abstract
Various forcing and feedback processes coexist in the tropical Pacific, which can modulate El Niño–Southern Oscillation (ENSO). In particular, large covariabilities in chlorophyll (Chl) and freshwater flux (FWF) at the sea surface are observed during ENSO cycles, acting to execute feedbacks on ENSO through the related ocean-biology-induced heating (OBH) and FWF forcing, respectively. At present, the related effects and underlying mechanism are strongly model dependent and are still not well understood. Here, a new hybrid coupled model (HCM), developed to represent interactions between the atmosphere and ocean physics–biology (AOPB) in the tropical Pacific, is used to examine the extent to which ENSO can be modulated by interannually covarying anomalies of FWF and Chl. HCM AOPB–based sensitivity experiments indicate that individually the FWF forcing tends to amplify ENSO via its influence on the stratification and vertical mixing in the upper ocean, whereas the OBH feedback tends to damp it. While the FWF- and OBH-related individual effects tend to counteract each other, their combined effects give rise to unexpected situations. For example, an increase in the FWF forcing intensity actually acts to decrease the ENSO amplitude when the OBH feedback effects coexist at a certain intensity. The nonlinear modulation of the ENSO amplitude can happen when the FWF-related amplifying effects on ENSO are compensated for by OBH-related damping effects. The results offer insight into modulating effects on ENSO, which are evident in nature and different climate models.
Abstract
The tropical thermocline plays an important role in regulating equatorial sea surface temperature (SST); at present, it is still poorly simulated in the state-of-the-art climate models. In this paper, thermocline biases in the tropical North Pacific are investigated using the newly released CMIP6 historical simulations. It is found that CMIP6 models tend to produce an overly shallow thermocline in the northwestern tropics, accompanied by a deep thermocline in the northeastern tropics. A pronounced thermocline strength bias arises in the tropical northeastern Pacific, demonstrating a dipole structure with a sign change at about 8°N. These thermocline biases are accompanied with biases in the simulations of oceanic circulations, including a too weak North Equatorial Countercurrent (NECC), a reduction in water exchanges between the subtropics and the equatorial regions, and an eastward extension of the equatorward interior water transport. The causes of these thermocline biases are further analyzed. The thermocline bias is primarily caused by the model deficiency in simulating the surface wind stress curl, which can be further attributed to the longstanding double-ITCZ bias in the tropical North Pacific. Besides, thermocline strength bias can be partly attributed to the poor prescription of oceanic background diffusivity. By constraining the diffusivity to match observations, the thermocline strength in the tropical northeastern Pacific is greatly increased.
Abstract
The tropical thermocline plays an important role in regulating equatorial sea surface temperature (SST); at present, it is still poorly simulated in the state-of-the-art climate models. In this paper, thermocline biases in the tropical North Pacific are investigated using the newly released CMIP6 historical simulations. It is found that CMIP6 models tend to produce an overly shallow thermocline in the northwestern tropics, accompanied by a deep thermocline in the northeastern tropics. A pronounced thermocline strength bias arises in the tropical northeastern Pacific, demonstrating a dipole structure with a sign change at about 8°N. These thermocline biases are accompanied with biases in the simulations of oceanic circulations, including a too weak North Equatorial Countercurrent (NECC), a reduction in water exchanges between the subtropics and the equatorial regions, and an eastward extension of the equatorward interior water transport. The causes of these thermocline biases are further analyzed. The thermocline bias is primarily caused by the model deficiency in simulating the surface wind stress curl, which can be further attributed to the longstanding double-ITCZ bias in the tropical North Pacific. Besides, thermocline strength bias can be partly attributed to the poor prescription of oceanic background diffusivity. By constraining the diffusivity to match observations, the thermocline strength in the tropical northeastern Pacific is greatly increased.
Abstract
A variety of observational and modeling studies show that changes in the Atlantic meridional overturning circulation (AMOC) can induce rapid global-scale climate change. In particular, a substantially weakened AMOC leads to a southward shift of the intertropical convergence zone (ITCZ) in both the Atlantic and the Pacific Oceans. However, the simulated amplitudes of the AMOC-induced tropical climate change differ substantially among different models. In this paper, the sensitivity to cloud feedback of the climate response to a change in the AMOC is studied using a coupled ocean–atmosphere model [the GFDL Coupled Model, version 2.1 (CM2.1)]. Without cloud feedback, the simulated AMOC-induced climate change in this model is weakened substantially. Low-cloud feedback has a strong amplifying impact on the tropical ITCZ shift in this model, whereas the effects of high-cloud feedback are weaker. It is concluded that cloud feedback is an important contributor to the uncertainty in the global response to AMOC changes.
Abstract
A variety of observational and modeling studies show that changes in the Atlantic meridional overturning circulation (AMOC) can induce rapid global-scale climate change. In particular, a substantially weakened AMOC leads to a southward shift of the intertropical convergence zone (ITCZ) in both the Atlantic and the Pacific Oceans. However, the simulated amplitudes of the AMOC-induced tropical climate change differ substantially among different models. In this paper, the sensitivity to cloud feedback of the climate response to a change in the AMOC is studied using a coupled ocean–atmosphere model [the GFDL Coupled Model, version 2.1 (CM2.1)]. Without cloud feedback, the simulated AMOC-induced climate change in this model is weakened substantially. Low-cloud feedback has a strong amplifying impact on the tropical ITCZ shift in this model, whereas the effects of high-cloud feedback are weaker. It is concluded that cloud feedback is an important contributor to the uncertainty in the global response to AMOC changes.
Abstract
In this study, an improved sea surface temperature (SST) anomaly (SSTA) solution for the tropical Pacific is presented by explicitly embedding into a layer ocean general circulation model (OGCM) a separate SSTA submodel with an empirical parameterization for the temperature of subsurface water entrained into the ocean mixed layer (Te ). Instead of using subsurface temperature directly from the OGCM, Te anomalies for the embedded SSTA submodel are calculated from a historical data-based empirical procedure in terms of sea level (SL) anomalies simulated from the OGCM. An inverse modeling approach is first adopted to estimate Te anomalies from the SSTA equation using observed SST and simulated upper-ocean currents from the OGCM. A relationship between Te and SL anomalies is then obtained by utilizing an empirical orthogonal function (EOF) analysis technique. The empirical Te parameterization optimally leads to a better balanced depiction of the subsurface effect on SST variability by the mean upwelling of anomalous subsurface temperature and vertical mixing in the equatorial Pacific. As compared with a standard OGCM simulation, SSTA simulations from the embedded submodel exhibit more realistic variability, with significantly increased correlation and reduced SSTA errors due to the optimized empirical Te parameterization. In the Niño-3 region (5°S–5°N, 150°–90°W), the anomaly correlation and root-mean-square (RMS) error of the simulated SST anomalies for the period 1963–96 from the standard OGCM are 0.74° and 0.58°C, while from the embedded SSTA submodel they are 0.94° and 0.29°C in the Te -dependent experiment, and 0.86° and 0.41°C in the experiment with one-dependent-year data excluded, respectively. Cross validation and sensitivity experiments to training periods for building the Te parameterization are made to illustrate the robustness and effectiveness of the approach. Moreover, the impact on simulations of SST anomalies and El Niño are examined in hybrid coupled atmosphere–ocean models (HCMs) consisting of the OGCM and a statistical atmospheric wind stress anomaly model that is constructed from a singular value decomposition (SVD) analysis. Results from coupled runs with and without embedding the SSTA submodel are compared. It is demonstrated that incorporating the embedded SSTA submodel in the context of an OGCM has a significant impact on performance of the HCMs and the behavior of the coupled system, with more realistic simulations of interannual SST anomalies (e.g., the amplitude and structure) in the tropical Pacific.
Abstract
In this study, an improved sea surface temperature (SST) anomaly (SSTA) solution for the tropical Pacific is presented by explicitly embedding into a layer ocean general circulation model (OGCM) a separate SSTA submodel with an empirical parameterization for the temperature of subsurface water entrained into the ocean mixed layer (Te ). Instead of using subsurface temperature directly from the OGCM, Te anomalies for the embedded SSTA submodel are calculated from a historical data-based empirical procedure in terms of sea level (SL) anomalies simulated from the OGCM. An inverse modeling approach is first adopted to estimate Te anomalies from the SSTA equation using observed SST and simulated upper-ocean currents from the OGCM. A relationship between Te and SL anomalies is then obtained by utilizing an empirical orthogonal function (EOF) analysis technique. The empirical Te parameterization optimally leads to a better balanced depiction of the subsurface effect on SST variability by the mean upwelling of anomalous subsurface temperature and vertical mixing in the equatorial Pacific. As compared with a standard OGCM simulation, SSTA simulations from the embedded submodel exhibit more realistic variability, with significantly increased correlation and reduced SSTA errors due to the optimized empirical Te parameterization. In the Niño-3 region (5°S–5°N, 150°–90°W), the anomaly correlation and root-mean-square (RMS) error of the simulated SST anomalies for the period 1963–96 from the standard OGCM are 0.74° and 0.58°C, while from the embedded SSTA submodel they are 0.94° and 0.29°C in the Te -dependent experiment, and 0.86° and 0.41°C in the experiment with one-dependent-year data excluded, respectively. Cross validation and sensitivity experiments to training periods for building the Te parameterization are made to illustrate the robustness and effectiveness of the approach. Moreover, the impact on simulations of SST anomalies and El Niño are examined in hybrid coupled atmosphere–ocean models (HCMs) consisting of the OGCM and a statistical atmospheric wind stress anomaly model that is constructed from a singular value decomposition (SVD) analysis. Results from coupled runs with and without embedding the SSTA submodel are compared. It is demonstrated that incorporating the embedded SSTA submodel in the context of an OGCM has a significant impact on performance of the HCMs and the behavior of the coupled system, with more realistic simulations of interannual SST anomalies (e.g., the amplitude and structure) in the tropical Pacific.
Abstract
The relationship between the North Atlantic Oscillation (NAO) and Atlantic sea surface temperature (SST) variability is investigated using models and observations. Coupled climate models are used in which the ocean component is either a fully dynamic ocean or a slab ocean with no resolved ocean heat transport. On time scales less than 10 yr, NAO variations drive a tripole pattern of SST anomalies in both observations and models. This SST pattern is a direct response of the ocean mixed layer to turbulent surface heat flux anomalies associated with the NAO. On time scales longer than 10 yr, a similar relationship exists between the NAO and the tripole pattern of SST anomalies in models with a slab ocean. A different relationship exists both for the observations and for models with a dynamic ocean. In these models, a positive (negative) NAO anomaly leads, after a decadal-scale lag, to a monopole pattern of warming (cooling) that resembles the Atlantic multidecadal oscillation (AMO), although with smaller-than-observed amplitudes of tropical SST anomalies. Ocean dynamics are critical to this decadal-scale response in the models. The simulated Atlantic meridional overturning circulation (AMOC) strengthens (weakens) in response to a prolonged positive (negative) phase of the NAO, thereby enhancing (decreasing) poleward heat transport, leading to broad-scale warming (cooling). Additional simulations are used in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. It is shown that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the Subpolar Gyre.
Abstract
The relationship between the North Atlantic Oscillation (NAO) and Atlantic sea surface temperature (SST) variability is investigated using models and observations. Coupled climate models are used in which the ocean component is either a fully dynamic ocean or a slab ocean with no resolved ocean heat transport. On time scales less than 10 yr, NAO variations drive a tripole pattern of SST anomalies in both observations and models. This SST pattern is a direct response of the ocean mixed layer to turbulent surface heat flux anomalies associated with the NAO. On time scales longer than 10 yr, a similar relationship exists between the NAO and the tripole pattern of SST anomalies in models with a slab ocean. A different relationship exists both for the observations and for models with a dynamic ocean. In these models, a positive (negative) NAO anomaly leads, after a decadal-scale lag, to a monopole pattern of warming (cooling) that resembles the Atlantic multidecadal oscillation (AMO), although with smaller-than-observed amplitudes of tropical SST anomalies. Ocean dynamics are critical to this decadal-scale response in the models. The simulated Atlantic meridional overturning circulation (AMOC) strengthens (weakens) in response to a prolonged positive (negative) phase of the NAO, thereby enhancing (decreasing) poleward heat transport, leading to broad-scale warming (cooling). Additional simulations are used in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. It is shown that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the Subpolar Gyre.
