Research over the past decade has demonstrated that dynamical forecast systems can skillfully predict Pan-Arctic sea ice extent (SIE) on the seasonal timescale; however, there have been fewer assessments of prediction skill on user-relevant spatial scales. In this work, we evaluate regional Arctic SIE predictions made with the FLOR and SPEAR_MED dynamical seasonal forecast systems developed at the NOAA Geophysical Fluid Dynamics Laboratory. Compared to FLOR, we find that the recently-developed SPEAR_MED system displays improved skill in predicting regional detrended SIE anomalies, partially owing to improvements in sea ice concentration (SIC) and thickness (SIT) initial conditions. In both systems, winter SIE is skillfully predicted up to 11 months in advance, whereas summer minimum SIE predictions are limited by the Arctic spring predictability barrier, with typical skill horizons of roughly four months. We construct a parsimonious set of simple statistical prediction models to investigate the mechanisms of sea ice predictability in these systems. Three distinct predictability regimes are identified: a summer regime dominated by SIE and SIT anomaly persistence; a winter regime dominated by SIE and upper ocean heat content (uOHC) anomaly persistence; and a combined regime in the Chukchi Sea, characterized by a trade-off between uOHC-based and SIT-based predictability that occurs as the sea ice edge position evolves seasonally. The combination of regional SIE, SIT, and uOHC predictors is able to reproduce the SIE skill of the dynamical models in nearly all regions, suggesting that these statistical predictors provide a stringent skill benchmark for assessing seasonal sea ice prediction systems.
This study shows that the frequency of North American summertime (June-August) heat extremes is skillfully predicted several months in advance in the newly-developed GFDL (Geophysical Fluid Dynamics Laboratory) SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Using a statistical optimization method, the Average Predictability Time, we identify three large-scale components of the frequency of North American summer heat extremes that are predictable with significant correlation skill. One component, which is related to a secular warming trend, shows a continent-wide increase in the frequency of summer heat extremes and is highly predictable at least 9 months in advance. This trend component is likely a response to external radiative forcing. The second component is largely driven by the sea surface temperatures in the North Pacific and North Atlantic and is significantly correlated with the central U.S. soil moisture. The second component shows largest loadings over the central U.S. and is significantly predictable 9 months in advance. The third component, which is related to the central Pacific El Niño, displays a dipole structure over North America and is predictable up to 4 months. Potential implications for advancing seasonal predictions of North American summertime heat extremes are discussed.
The Kuroshio Extension (KE), an eastward-flowing jet located in the Pacific western boundary current system, exhibits prominent seasonal-to-decadal variability, which is crucial for understanding climate variations in the northern midlatitudes. We explore the representation and prediction skill for the KE in the GFDL SPEAR (Seamless System for Prediction and Earth System Research) coupled model. Two different approaches are used to generate coupled reanalyses and forecasts: 1) restoring the coupled model’s SST and atmospheric variables toward existing reanalyses, or 2) assimilating SST and subsurface observations into the coupled model without atmospheric assimilation. Both systems use an ocean model with 1° resolution and capture the largest sea surface height (SSH) variability over the KE region. Assimilating subsurface observations appears to be essential to reproduce the narrow front and related oceanic variability of the KE jet in the coupled reanalysis. We demonstrate skillful retrospective predictions of KE SSH variability in monthly (up to 1 year) and annual-mean (up to 5 years) KE forecasts in the seasonal and decadal prediction systems, respectively. The prediction skill varies seasonally, peaking for forecasts initialized in January and verifying in September due to the winter intensification of North Pacific atmospheric forcing. We show that strong large-scale atmospheric anomalies generate deterministic oceanic forcing (i.e., Rossby waves), leading to skillful long-lead KE forecasts. These atmospheric anomalies also drive Ekman convergence and divergence, which forms ocean memory, by sequestering thermal anomalies deep into the winter mixed layer that re-emerge in the subsequent autumn. The SPEAR forecasts capture the recent negative-to-positive transition of the KE phase in 2017, projecting a continued positive phase through 2022.
Quantifying the response of atmospheric rivers (ARs) to radiative forcing is challenging due to uncertainties caused by internal climate variability, differences in shared socioeconomic pathways (SSPs), and methods used in AR detection algorithms. In addition, the requirement of medium-to-high model resolution and ensemble sizes to explicitly simulate ARs and their statistics can be computationally expensive. In this study, we leverage the unique 50-km large ensembles generated by a Geophysical Fluid Dynamics Laboratory next-generation global climate model, Seamless system for Prediction and EArth system Research, to explore the warming response in ARs. Under both moderate and high emissions scenarios, increases in AR-day frequency emerge from the noise of internal variability by 2060. This signal is robust across different SSPs and time-independent detection criteria. We further examine an alternative approach proposed by Thompson et al. (2015), showing that unforced AR variability can be approximated by a first-order autoregressive process. The confidence intervals of the projected response can be analytically derived with a single ensemble member.
One of the most puzzling observed features of recent climate has been a multidecadal surface cooling trend over the subpolar Southern Ocean (SO). In this study we use large ensembles of simulations with multiple climate models to study the role of the SO meridional overturning circulation (MOC) in these sea surface temperature (SST) trends. We find that multiple competing processes play prominent roles, consistent with multiple mechanisms proposed in the literature for the observed cooling. Early in the simulations (twentieth century and early twenty-first century) internal variability of the MOC can have a large impact, in part due to substantial simulated multidecadal variability of the MOC. Ensemble members with initially strong convection (and related surface warming due to convective mixing of subsurface warmth to the surface) tend to subsequently cool at the surface as convection associated with internal variability weakens. A second process occurs in the late-twentieth and twenty-first centuries, as weakening of oceanic convection associated with global warming and high-latitude freshening can contribute to the surface cooling trend by suppressing convection and associated vertical mixing of subsurface heat. As the simulations progress, the multidecadal SO variability is suppressed due to forced changes in the mean state and increased oceanic stratification. As a third process, the shallower mixed layers can then rapidly warm due to increasing forcing from greenhouse gas warming. Also, during this period the ensemble spread of SO SST trend partly arises from the spread of the wind-driven Deacon cell strength. Thus, different processes could conceivably have led to the observed cooling trend, consistent with the range of possibilities presented in the literature. To better understand the causes of the observed trend, it is important to better understand the characteristics of internal low-frequency variability in the SO and the response of that variability to global warming.
Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_LO, and SPEAR_MED dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/Bellingshausen, Indian, and west Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper-ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal time scales.
Goosse, Hugues, Quentin Dalaiden, Marie G P Cavitte, and Liping Zhang, January 2021: Can we reconstruct the formation of large open-ocean polynyas in the Southern Ocean using ice core records?Climate of the Past, 17(1), DOI:10.5194/cp-17-111-2021111-131. Abstract
Large open-ocean polynyas, defined as ice-free areas within the sea ice pack, have only rarely been observed in the Southern Ocean over the past decades. In addition to smaller recent events, an impressive sequence occurred in the Weddell Sea in 1974, 1975 and 1976 with openings of more than 300 000 km2 that lasted the full winter. These big events have a huge impact on the sea ice cover, deep-water formation, and, more generally, on the Southern Ocean and the Antarctic climate. However, we have no estimate of the frequency of the occurrence of such large open-ocean polynyas before the 1970s. Our goal here is to test if polynya activity could be reconstructed using continental records and, specifically, observations derived from ice cores. The fingerprint of big open-ocean polynyas is first described in reconstructions based on data from weather stations, in ice cores for the 1970s and in climate models. It shows a signal characterized by a surface air warming and increased precipitation in coastal regions adjacent to the eastern part of the Weddell Sea, where several high-resolution ice cores have been collected. The signal of the isotopic composition of precipitation is more ambiguous; thus, we base our reconstructions on surface mass balance records alone. A first reconstruction is obtained by performing a simple average of standardized records. Given the similarity between the observed signal and the one simulated in models, we also use data assimilation to reconstruct past polynya activity. The impact of open-ocean polynyas on the continent is not large enough, compared with the changes due to factors such as atmospheric variability, to detect the polynya signal without ambiguity, and additional observations would be required to clearly discriminate the years with and without open-ocean polynya. Thus, it is reasonable to consider that, in these preliminary reconstructions, some high snow accumulation events may be wrongly interpreted as the consequence of polynya formation and some years with polynya formation may be missed. Nevertheless, our reconstructions suggest that big open-ocean polynyas, such as those observed in the 1970s, are rare events, occurring at most a few times per century. Century-scale changes in polynya activity are also likely, but our reconstructions are unable to precisely assess this aspect at this stage.
Mao, Rui, Seong-Joong Kim, Dao-Yi Gong, Xiaohong Liu, Xinyu Wen, and Liping Zhang, et al., August 2021: Increasing difference in interannual summertime surface air temperature between interior East Antarctica and the Antarctic Peninsula under future climate scenarios. Geophysical Research Letters, 48(16), DOI:10.1029/2020GL092031. Abstract
In this study, using the Climate Model Intercomparison Project 5 (CMIP5) simulations and by empirical orthogonal function (EOF) analysis, the first mode of variability in interannual surface air temperature (SAT) in Antarctica (EOF1) was examined for the period between 1979–2004 and 2051–2099 during the austral summer. The ensemble mean of EOF1 of the CMIP5 models shows a positive SAT anomaly over the northern Antarctic Peninsula (AP) and a negative SAT anomaly over Eastern Antarctica (EA) in both periods. A poleward expansion of the AP positive anomaly and an increase in the negative anomaly over interior EA are expected in 2051–2099, resulting in a larger difference of interannual SAT between interior EA and the AP in 2051–2099 than in 1979–2004. The increasing difference in the interannual SAT is consistent with a larger magnitude of the SAM-related circulation anomalies in the future.
Atmospheric rivers (ARs) exert significant socioeconomic impacts in western North America, where 30% of the annual precipitation is determined by ARs that occur in less than 15% of wintertime. ARs are thus beneficial to water supply but can produce extreme precipitation hazards when making landfall. While most prevailing research has focused on the subseasonal (<5 weeks) prediction of ARs, only limited efforts have been made for AR forecasts on multiseasonal timescales (>3 months) that are crucial for water resource management and disaster preparedness. Through the analysis of reanalysis data and retrospective predictions from a new seasonal-to-decadal forecast system, this research shows the existing potential of multiseasonal AR frequency forecasts with predictive skills 9 months in advance. Additional analysis explores the dominant predictability sources and challenges for multiseasonal AR prediction.
Using GFDL's new coupled model SPEAR, we have developed a decadal coupled reanalysis/initialization system (DCIS) that does not use subsurface ocean observations. In DCIS, the winds and temperature in the atmosphere, along with sea surface temperature (SST), are restored to observations. Under this approach the ocean component of the coupled model experiences a sequence of surface heat and momentum fluxes that are similar to observations. DCIS offers two initialization approaches, called A1 and A2, which differ only in the atmospheric forcing from observations. In A1, the atmospheric winds/temperature are restored toward the JRA reanalysis; in A2, surface pressure observations are assimilated in the model. Two sets of coupled reanalyses have been completed during 1961–2019 using A1 and A2, and they show very similar multi-decadal variations of the Atlantic Meridional Overturning Circulation (AMOC). Two sets of retrospective decadal forecasts were then conducted using initial conditions from the A1 and A2 reanalyses. In comparison with previous prediction system CM2.1, SPEAR-A1/A2 shows comparable skill of predicting the North Atlantic subpolar gyre SST, which is highly correlated with initial values of AMOC at all lead years. SPEAR-A1 significantly outperforms CM2.1 in predicting multi-decadal SST trends in the Southern Ocean (SO). Both A1 and A2 have skillful prediction of Sahel precipitation and the associated ITCZ shift. The prediction skill of SST is generally lower in A2 than A1 especially over SO presumably due to the sparse surface pressure observations.
Previous studies have shown the existence of internal multidecadal variability in the Southern Ocean using multiple climate models. This variability, associated with deep ocean convection, can have significant climate impacts. In this work, we use sensitivity studies based on Geophysical Fluid Dynamics Laboratory (GFDL) models to investigate the linkage of this internal variability with the background ocean mean state. We find that mean ocean stratification in the subpolar region that is dominated by mean salinity influences whether this variability occurs, as well as its time scale. The weakening of background stratification favors the occurrence of deep convection. For background stratification states in which the low-frequency variability occurs, weaker ocean stratification corresponds to shorter periods of variability and vice versa. The amplitude of convection variability is largely determined by the amount of heat that can accumulate in the subsurface ocean during periods of the oscillation without deep convection. A larger accumulation of heat in the subsurface reservoir corresponds to a larger amplitude of variability. The subsurface heat buildup is a balance between advection that supplies heat to the reservoir and vertical mixing/convection that depletes it. Subsurface heat accumulation can be intensified both by an enhanced horizontal temperature advection by the Weddell Gyre and by an enhanced ocean stratification leading to reduced vertical mixing and surface heat loss. The paleoclimate records over Antarctica indicate that this multidecadal variability has very likely happened in past climates and that the period of this variability may shift with different climate background mean state.
Midlatitude baroclinic waves drive extratropical weather and climate variations, but their predictability beyond 2 weeks has been deemed low. Here we analyze a large ensemble of climate simulations forced by observed sea surface temperatures (SSTs) and demonstrate that seasonal variations of baroclinic wave activity (BWA) are potentially predictable. This potential seasonal predictability is denoted by robust BWA responses to SST forcings. To probe regional sources of the potential predictability, a regression analysis is applied to the SST-forced large ensemble simulations. By filtering out variability internal to the atmosphere and land, this analysis identifies both well-known and unfamiliar BWA responses to SST forcings across latitudes. Finally, we confirm the model-indicated predictability by showing that an operational seasonal prediction system can leverage some of the identified SST-BWA relationships to achieve skillful predictions of BWA. Our findings help to extend long-range predictions of the statistics of extratropical weather events and their impacts.
We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL ‐ the AM4 atmosphere model, MOM6 ocean code, LM4 land model and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0o (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1o to 0.25o. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM 4 models, but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time‐mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM 4 models.
Smith, D M., A A Scaife, R Eade, P Athanasiadis, A Bellucci, I Bethke, R Bilbao, L F Borchert, L-P Caron, F Counillon, Gokhan Danabasoglu, Thomas L Delworth, Francisco J Doblas-Reyes, Nick Dunstone, V Estella-Perez, S Flavoni, L Hermanson, N Keenlyside, V Kharin, M Kimoto, William J Merryfield, J Mignot, T Mochizuki, K Modali, P-A Moneri, W A Muller, D Nicolí, P Ortega, K Pankatz, H Pohlmann, J Robson, P Ruggieri, R Sospedra-Alfonso, D Swingedouw, Y Wang, S Wild, Stephen G Yeager, Xiaosong Yang, and Liping Zhang, July 2020: North Atlantic climate far more predictable than models imply. Nature, 583, DOI:10.1038/s41586-020-2525-0796-800. Abstract
Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain. This leads to low confidence in regional projections, especially for precipitation, over the coming decades. The chaotic nature of the climate system may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade.
In this paper, we have evaluated the Southern Ocean (SO) heat flux feedback in a fully coupled model and for the first time examined how this feedback evolves in response to global warming. The model broadly captures the observed characteristics of heat flux feedback over the SO. The heat flux tends to damp SST anomalies over the SO and thus the feedback is negative. In a warmer climate, the negative heat flux feedback in the SO, contributed mainly from turbulent component, becomes stronger. The turbulent feedback in the present day is primarily balanced by the upper boundary that strongly depends on background SST and wind and the thermal adjustment of boundary layer to SST anomalies. It is found that this balance shifts a little bit under global warming scenario. The upper limit increases in a warmer climate due to warm SST responses. The thermal adjustment of boundary layer becomes weaker in a warmer climate because of decreased atmospheric background heat convergence. The mean Deacon Cell transports anomalous heat caused by the greenhouse gas effect northward, leading to a heat convergence along the northern flank of the Antarctic Circumpolar Current. Constrained by the energy, the atmospheric northward heat transport has a corresponding divergence north of 55°S. This anomalous heat transport divergence favors air heat leaving away from 55°S–35°S regions to the polar region, leads to smaller air temperature tendencies in the local compared to the present day and therefore leads to a weakened thermal adjustment of boundary layer. Therefore, both changes in the upper limit and thermal adjustment of boundary layer contribute positively to the enhanced turbulent feedback in a warmer climate. The dynamic component due to changes in wind tends to compensate these two positive contributors, but its magnitude is too small to become a dominant factor.
Observed Southern Ocean surface cooling and sea-ice expansion over the past several decades are inconsistent with many historical simulations from climate models. Here we show that natural multidecadal variability involving Southern Ocean convection may have contributed strongly to the observed temperature and sea-ice trends. These observed trends are consistent with a particular phase of natural variability of the Southern Ocean as derived from climate model simulations. Ensembles of simulations are conducted starting from differing phases of this variability. The observed spatial pattern of trends is reproduced in simulations that start from an active phase of Southern Ocean convection. Simulations starting from a neutral phase do not reproduce the observed changes, similarly to the multimodel mean results of CMIP5 models. The long timescales associated with this natural variability show potential for skilful decadal prediction.
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 ten years 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 ten years 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).
We use additional simulations in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. We show that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the subpolar gyre.
Li, Shujun, Liping Zhang, and Lixin Wu, November 2017: Decadal potential predictability of upper ocean heat content over the twentieth century. Climate Dynamics, 49(9-10), DOI:10.1007/s00382-016-3513-9. Abstract
The statistical method, Average Predictability Time (APT) decomposition, is used in the present paper to estimate the decadal predictability of upper ocean heat content over the global ocean, North Pacific and North Atlantic, respectively. The twentieth century simulations from CMIP5 outputs are the main data sources in this study. On global scale, the leading predictable component is characterized by a warming trend over the majority of oceans, which is related to the anthropogenic forced response. The second predictable component has significant loadings in the North Atlantic, especially in the subtropical region, which originates from the Atlantic Multidecadal Oscillation (AMO) predictability. To separate interactions among different ocean basins, we further maximize APT in individual North Pacific and North Atlantic oceans. It is found that the second and the third predictable component in North Pacific are significantly correlated with the well-known North Pacific Gyre Oscillation mode and the Pacific Decadal Oscillation respectively. Upper limit prediction skill of these two components are on the order of 6 years. In contrast, the most predictable component derived from the North Atlantic features an AMO-like spatial structure with its prediction skill up to 18 years, while the basin mode due to global warming only exists as the third component. This indicates the interdecadal variability in the North Atlantic is strong enough to mask the anthropogenic climate signals. Furthermore, predictability in the real world is also investigated and compared with model results by using observation-based data.
The impact of multidecadal variations of the Atlantic meridional overturning circulation (AMOC) on the Southern Ocean (SO) is investigated in the current paper using a coupled ocean–atmosphere model. We find that the AMOC can influence the SO via fast atmosphere teleconnections and subsequent ocean adjustments. A stronger than normal AMOC induces an anomalous warm SST over the North Atlantic, which leads to a warming of the Northern Hemisphere troposphere extending into the tropics. This induces an increased equator-to-pole temperature gradient in the Southern Hemisphere (SH) upper troposphere and lower stratosphere due to an amplified tropical upper tropospheric warming as a result of increased latent heat release. This altered gradients leads to a poleward displacement of the SH westerly jet. The wind change over the SO then cools the SST at high latitudes by anomalous northward Ekman transports. The wind change also weakens the Antarctic bottom water (AABW) cell through changes in surface heat flux forcing. The poleward shifted westerly wind decreases the long term mean easterly winds over the Weddell Sea, thereby reducing the turbulent heat flux loss, decreasing surface density and therefore leading to a weakening of the AABW cell. The weakened AABW cell produces a temperature dipole in the SO, with a warm anomaly in the subsurface and a cold anomaly in the surface that corresponds to an increase of Antarctic sea ice. Opposite conditions occur for a weaker than normal AMOC. Our study here suggests that efforts to attribute the recent observed SO variability to various factors should take into consideration not only local process but also remote forcing from the North Atlantic.
This study explores the potential predictability of the Southern Ocean (SO) climate on decadal timescales as represented in the GFDL CM2.1 model using prognostic methods. We conduct perfect model predictability experiments starting from ten different initial states, and show potentially predictable variations of Antarctic bottom water formation (AABW) rates on time scales as long as twenty years. The associated Weddell Sea (WS) subsurface temperatures and Antarctic sea ice have comparable potential predictability as the AABW cell. The predictability of sea surface temperature (SST) variations over the WS and the SO is somewhat smaller, with predictable scales out to a decade. This reduced predictability is likely associated with stronger damping from air-sea interaction. As a complement to our perfect predictability study, we also make hindcasts of SO decadal variability using the GFDL CM2.1 decadal prediction system. Significant predictive skill for SO SST on multi-year time scales is found in the hindcast system. The success of the hindcasts, especially in reproducing observed surface cooling trends, is largely due to initializing the state of the AABW cell. A weak state of the AABW cell leads to cooler surface conditions and more extensive sea ice. Although there are considerable uncertainties regarding the observational data used to initialize the hindcasts, the consistency between the perfect model experiments and the decadal hindcasts at least gives us some indication as to where and to what extent skillful decadal SO forecasts might be possible.
The average predictability time (APT) method is used to identify the most predictable components of decadal sea surface temperature (SST) variations over the Southern Ocean (SO) in a 4000 year unforced control run of the GFDL CM2.1 model. The most predictable component shows significant predictive skill for periods as long as 20 years. The physical pattern of this variability has a uniform sign of SST anomalies over the SO, with maximum values over the Amundsen-Bellingshausen-Weddell Seas. Spectral analysis of the associated APT time series shows a broad peak on time scales of 70-120 years. This most predictable pattern is closely related to the mature phase of a mode of internal variability in the SO that is associated with fluctuations of deep ocean convection. The second most predictable component of SO SST is characterized by a dipole structure, with SST anomalies of one sign over the Weddell Sea and SST anomalies of the opposite sign over the Amundsen-Bellingshausen Seas. This component has significant predictive skill for periods as long as 6 years. This dipole mode is associated with a transition between phases of the dominant pattern of SO internal variability. The long time scales associated with variations in SO deep convection provide the source of the predictive skill of SO SST on decadal scales. These analyses suggest that if we could adequately initialize the SO deep convection in a numerical forecast model, the future evolution of SO SST and its associated climate impacts is potentially predictable.
Pronounced climate changes have occurred since the 1970s, including rapid loss of Arctic sea ice1, large-scale warming2 and increased tropical storm activity3 in the Atlantic. Anthropogenic radiative forcing is likely to have played a major role in these changes4, but the relative influence of anthropogenic forcing and natural variability is not well established. The above changes have also occurred during a period in which the North Atlantic Oscillation has shown marked multidecadal variations5. Here we investigate the role of the North Atlantic Oscillation in these rapid changes through its influence on the Atlantic meridional overturning circulation and ocean heat transport. We use climate models to show that observed multidecadal variations of the North Atlantic Oscillation can induce multidecadal variations in the Atlantic meridional overturning circulation and poleward ocean heat transport in the Atlantic, extending to the Arctic. Our results suggest that these variations have contributed to the rapid loss of Arctic sea ice, Northern Hemisphere warming, and changing Atlantic tropical storm activity, especially in the late 1990s and early 2000s. These multidecadal variations are superimposed on long-term anthropogenic forcing trends that are the dominant factor in long-term Arctic sea ice loss and hemispheric warming.
The impact of climate change on the Pacific Decadal Oscillation (PDO) is studied using a fully coupled climate model. The model results show that the PDO has a similar spatial pattern in altered climates, but its amplitude and time scale of variability change in response to global warming or cooling. In response to global warming the PDO amplitude is significantly reduced, with a maximum decrease over the Kuroshio-Oyashio-Extension (KOE) region. This reduction appears to be associated with a weakened meridional temperature gradient in the KOE region. In addition, reduced variability of North Pacific wind stress, partially due to reduced air-sea feedback, also helps to weaken the PDO amplitude by reducing the meridional displacements of the subtropical and subpolar gyre boundaries. In contrast, the PDO amplitude increases in response to global cooling.
In our control simulations the model PDO has an approximately bi-decadal peak. In a warmer climate the PDO timescale becomes shorter, changing from approximately 20 years to approximately 12 years. In a colder climate the timescale of the PDO increases to approximately 34 years. Physically, global warming (cooling) enhances (weakens) ocean stratification. The increased (decreased) ocean stratification acts to increase (reduce) the phase speed of internal Rossby waves, thereby altering the timescale of the simulated PDO.
Zhang, Liping, and Thomas L Delworth, August 2016: Impact of the Antarctic bottom water formation on the Weddell Gyre and its northward propagation characteristics in GFDL model. Journal of Geophysical Research: Oceans, 121(8), DOI:10.1002/2016JC011790. Abstract
The impact of Antarctic bottom water (AABW) formation on the Weddell Gyre and its northward propagation characteristics are studied using a 4000-yr long control run of the GFDL CM2.1 model as well as sensitivity experiments. In the control run, the AABW cell and Weddell Gyre are highly correlated when the AABW cell leads the Weddell Gyre by several years, with an enhanced AABW cell corresponding to a strengthened Weddell Gyre and vice versa. An additional sensitivity experiment shows that the response of the Weddell Gyre to AABW cell changes is primarily attributed to interactions between the AABW outflow and ocean topography, instead of the surface wind stress curl and freshwater anomalies. As the AABW flows northward, it encounters topography with steep slopes that induce strong downwelling and negative bottom vortex stretching. The anomalous negative bottom vortex stretching induces a cyclonic barotropic streamfunction over the Weddell Sea, thus leading to an enhanced Weddell Gyre. The AABW cell variations in the control run have significant meridional coherence in density space. Using passive dye tracers, it is found that the slow propagation of AABW cell anomalies south of 35oS corresponds to the slow tracer advection time scale. The dye tracers escape the Weddell Sea through the western limb of the Weddell Gyre and then go northwestward to the Argentine Basin through South Sandwich Trench and Georgia Basin. This slow advection by deep ocean currents determines the AABW cell propagation speed south of 35oS. North of 35oS the propagation speed is determined both by advection in the deep western boundary current and through Kelvin waves.
Yi, Daling L., Liping Zhang, and L Wu, September 2015: On the mechanisms of decadal variability of the North Pacific gyre oscillation over the twentieth century. Journal of Geophysical Research: Oceans, 120(9), DOI:10.1002/2014JC010660. Abstract
The decadal variability of the North Pacific gyre oscillation (NPGO) over the 20th century is examined from a long term integration of the Simple Ocean Data Assimilation (SODA) reanalysis. The NPGO is reflected by the second dominant pattern of sea surface height (SSH) variability in SODA, with a north-south dipole structure over the northeast Pacific. SSH anomalies in this region exhibit distinct decadal variability with a significant spectrum peak at approximately 18-yr. The upper-ocean heat budget reveals that this dipole structure associated with the NPGO is predominantly due to the anomalous Ekman pumping and Ekman advection induced by the surface wind. The NPGO mode in SODA reanalysis originates from atmosphere stochastic noise (North Pacific Oscillation) which has a meridional dipole pattern but no preferred timescale. The oceanic planetary wave, particularly the advective baroclinic mode, integration of atmospheric stochastic noise leads to a spatial resonance with preferred decadal time scale. The limitation of current study is also discussed.
Zhang, Liping, and Chuanhu Zhao, June 2015: Processes and mechanisms for the model SST biases in the North Atlantic and North Pacific: A link with the Atlantic meridional overturning circulation. Journal of Advances in Modeling Earth Systems, 7(2), DOI:10.1002/2014MS000415. Abstract
Almost all of CMIP5 climate models show cold SST biases in the extratropical North Atlantic (ENA) and tropical North Atlantic (TNA) as well as in the North Pacific which are commonly linked with the weak simulated Atlantic meridional overturning circulation (AMOC). A weak AMOC and its associated reduced northward oceanic heat transport are associated with a cooling of the ENA Ocean, whereas the TNA cooling is attributable to both the weak AMOC and surface heat flux. The cold biases in the ENA and TNA have remote impacts on the SST bias in the North Pacific. Here we use coupled ocean-atmosphere model experiments to show the mechanisms and pathways by which the ENA and TNA affect the North Pacific. The model simulations demonstrate that the cooling SST bias in the North Pacific is largely due to the remote effect of the cooling SST bias in the ENA, while the remote impact of the TNA cooling SST bias is of secondary importance. The ENA cooling bias triggers the circum-global teleconnection via the Northern Hemisphere annular mode, producing a strengthening of the Aleutian low, an enhancement of the southward Ekman and Oyashio cold advection, and thus a cooling SST in the North Pacific. In contrast, the TNA cooling produces a surface high extending to the eastern tropical North Pacific, inducing the northeasterly wind anomalies north, northerly cross-equatorial wind anomalies, and northwesterly wind anomalies south of the equator. This C-shape wind anomaly pattern generates an SST warming in the tropical southeastern Pacific, which eventually leads to an SST warming in the tropical central and western Pacific by the wind-evaporation-SST feedback. The tropical Pacific warming in turn leads to an SST cooling in the North Pacific by the Pacific North American teleconnection pattern. This article is protected by copyright. All rights reserved.
Zhang, Liping, and Thomas L Delworth, October 2015: Analysis of the Characteristics and Mechanisms of the Pacific Decadal Oscillation in a Suite of Coupled Models from the Geophysical Fluid Dynamics Laboratory. Journal of Climate, 28(19), DOI:10.1175/JCLI-D-14-00647.1. Abstract
North Pacific decadal oceanic and atmospheric variability is examined in a suite of coupled climate models developed at the Geophysical Fluid Dynamics Laboratory (GFDL). The models have ocean horizontal resolutions ranging from 1° to 0.1°, and atmospheric horizontal resolutions ranging from 200km to 50km. In all simulations the dominant pattern of decadal-scale sea surface temperature (SST) variability over the North Pacific is similar to the observed Pacific Decadal Oscillation (PDO). Simulated SST anomalies in the Kuroshio Oyashio Extension (KOE) region exhibit a significant spectral peak at approximately 20 years.
We use sensitivity experiments to show that: (i) the simulated PDO mechanism involves extratropical air-sea interaction and oceanic Rossby wave propagation, (ii) the oscillation can exist independent of interactions with the Tropics, but that such interactions can enhance the PDO, and (iii) ocean to atmosphere feedback in the extratropics is critical for establishing the approximately 20-year timescale of the PDO. The spatial pattern of the PDO can be generated from atmospheric variability that occurs independently of ocean-atmosphere feedback, but the existence of a spectral peak depends on active air-sea coupling. The specific interdecadal timescale is strongly influenced by the propagation speed of oceanic Rossby waves in the subtropical and subpolar gyres, as they provide a delayed feedback to the atmosphere.
The simulated PDO has a realistic association with precipitation variations over North America, with a warm phase of the PDO generally associated with positive precipitation anomalies over regions of the western United States. The seasonal dependence of this relationship is also reproduced by the model.
Hong, L, and Liping Zhang, et al., June 2014: Linkage between the Pacific Decadal Oscillation and the low frequency variability of the Pacific Subtropical Cell. Journal of Geophysical Research: Oceans, 119(6), DOI:10.1002/2013JC009650. Abstract
The decadal variability of Pacific Subtropical Cell (STC) and its linkages with the Pacific Decadal Oscillation (PDO) are investigated in the present study based on a Simple Ocean Data Assimilation (SODA 2.2.4). It is found that, on decadal time scales, the western boundary and interior pycnocline transports are anticorrelated and the variation of the interior component is more significant, which is consistent with previous studies. The decadal variability of STC in the Northern Hemisphere is found to be strongly associated with PDO. Associated with a positive (negative) phase of PDO, the relaxation (acceleration) of the northeast trades slows down (spins up) the STC within a few years through baroclinic adjustment in conjunction with the subduction of the cold (warm) mixed-layer anomalies in the extratropics. The cold (warm) water is then injected into the thermocline and advected further southwestward to the tropics along the isopycnal surfaces, leading to the slowdown (spin-up) of STC due to zonal pressure gradient change at low latitude. Along with the STC weakening (strengthening), a significant warming (cold) anomaly appears in the tropics and it is advected to the midlatitude by the Kuroshio and North Pacific currents, thus feeding back to the atmosphere over the North Pacific. In contrast to the Northern Hemisphere, it is found the STC in the south only passively responds to the PDO. The mechanism found here highlights the role of the STC advection of extratropical anomalies to the tropics and horizontal gyre advection of the tropical anomalies to the extratropics in decadal variability of the STC and PDO.
Zhang, Liping, et al., December 2014: Remote effect of the model cold bias in the tropical North Atlantic on the warm bias in the tropical southeastern Pacific. Journal of Advances in Modeling Earth Systems, 6(4), DOI:10.1002/2014MS000338. Abstract
Most state-of-the-art climate models show significant systematic biases in the tropical southeastern Pacific (SEP) and tropical North Atlantic (TNA). These biases manifest themselves as the sea surface temperature (SST) in the SEP being too warm and the SST in the TNA being too cold. That is, as the cold SST biases appear in the TNA, the warm SST biases also occur in the SEP. This indicates that if climate models cannot succeed in simulating the TNA variability, they will also fail at least partially in the SEP. Our coupled model experiments show that the cold SST bias in the TNA results in a weakening of the Hadley-type circulation from the TNA to the SEP. This meridional circulation reduces the South Pacific subtropical anticyclone and the associated subsidence, which in turn leads to a reduction of low clouds, a weakening of the easterly trade wind, and thus an increase of the warm SST bias in the SEP.
