Ocean Heat Content Variability Research Articles

Skill assessment of seasonal forecasts of ocean variables

There is growing demand for seasonal forecast products for marine applications. The availability of consistent and sufficiently long observational records of ocean variables permits the assessment of the spatial distribution of the skill of ocean variables from seasonal forecasts. Here we use state-of-the-art temporal records of sea surface temperature (SST), sea surface height (SSH) and upper 300m ocean heat content (OHC) to quantify the distribution of skill, up to 2 seasons ahead, of two operational seasonal forecasting systems contributing to the seasonal multi-model of the Copernicus Climate Change Services (C3S). This study presents the spatial distribution of the skill of the seasonal forecast ensemble mean in terms of anomaly correlation and root mean square error and compares it to the persistence and climatological benchmarks. The comparative assessment of the skill among variables sheds light on sources/limits of predictability at seasonal time scales, as well as the nature of model errors. Beyond these standard verification metrics, we also evaluate the ability of the models to represent the observed long-term trends. Results show that long-term trends contribute to the skill of seasonal forecasts. Although the forecasts capture the long-term trends in general, some regional aspects remain challenging. Part of these errors can be attributed to specific aspects of the ocean initialization, but others, such as the overestimation of the warming in the Eastern Pacific are also influenced by model error. Skill gains can be obtained by improving the trend representation in future forecasting systems. In the meantime, a forecast calibration procedure that corrects the linear trends can produce substantial skill gains. The results show that calibrated seasonal forecasts beat both the climatological and persistence benchmark almost at every location for all initial dates and lead times. Results demonstrate the value of the seasonal forecasts for marine applications and highlight the importance of representing the decadal variability and trends in ocean heat content and sea level.

An Assessment of Convergence of Climate Reanalyses from Two Coupled Data Assimilation Systems with Identical High-Efficiently Filtering

Abstract Coupled data assimilation (CDA) uses coupled model dynamics and physics to extract observational information from measured data in multiple Earth system domains to reconstruct historical states of the Earth system, forming a reanalysis of climate variability. Due to imperfect numerical schemes in modeling dynamics and physics, models are usually biased from the real world. Such model bias is a critical obstacle in the reconstruction of historical variability by combining model and observations, and, to some degree, causes divergence of CDA results because of individual model behavior in each system. Here, based on a multitimescale high-efficiency filtering algorithm which includes a deep ocean bias relaxing scheme, we first develop a high-efficiency online CDA system with the Community Earth System Model (CESM-MSHea-CDA). Then, together with the other previously-established CDA system (CM2-MSHea-CDA) within the Coupled Model version 2.1 model that is developed by Geophysical Fluid Dynamics Laboratory, we conduct climate reanalysis for the past four decades (1978–2018). Evaluations show that due to improved representation for multiscale background statistics and effective deep ocean model bias relaxing, both CDA systems produce convergent estimation of variability for major climate signals such as variability of basin-scale ocean heat content, ENSO, PDO, etc. Particularly, both CDA systems generate similar time-mean of global and Atlantic meridional overturning circulations that converge to the geostrophic velocity estimate from climatological temperature and salinity data. The CDA-estimated mass transport at typical measurement sections is mostly consistent with the observations.

A Dynamics-Weighted Principal Components Analysis of Dominant Atmospheric Drivers of Ocean Variability with an Application to the North Atlantic Subpolar Gyre

Abstract This paper describes a framework for identifying dominant atmospheric drivers of ocean variability. The method combines statistics of atmosphere–ocean fluxes with physics from an ocean general circulation model to derive atmospheric patterns optimized to excite variability in a specified ocean quantity of interest. We first derive the method as a weighted principal components analysis and illustrate its capabilities in a toy problem. Next, we apply our analysis to the problem of interannual upper ocean heat content (HC) variability in the North Atlantic Subpolar Gyre (SPG) using the adjoint of the MITgcm and atmosphere–ocean fluxes from the ECCOv4-r4 state estimate. An unweighted principal components analysis reveals that North Atlantic heat and momentum fluxes in ECCOv4-r4 have a range of spatiotemporal patterns. By contrast, dynamics-weighted principal components analysis collapses the space of these patterns onto a small subset—principally associated with the North Atlantic Oscillation—that dominates interannual SPG HC variance. By perturbing the ECCOv4-r4 state estimate, we illustrate the pathways along which variability propagates from the atmosphere to the ocean in a nonlinear ocean model. This technique is applicable across a range of problems across Earth system components, including in the absence of a model adjoint. Significance Statement While the oceans have absorbed 90% of the excess heat associated with human-forced climate change, the change in the ocean’s heat content is not steady, with peaks and troughs superimposed upon a general increase. These fluctuations come from chaotic changes in the atmosphere and ocean and can be hard to disentangle. We use this case of ocean heat content variability to introduce a new method for determining the patterns of weather and climate in the atmosphere that are most effective at generating fluctuations in the ocean. To do this, we combine the statistics of recent atmospheric activity with output from a state-of-the-art numerical ocean model that reveals physical processes driving changes in ocean quantities including ocean heat content. This approach suggests that the atmospheric patterns that stimulate the most energetic changes in ocean heat content in the northern North Atlantic are not necessarily the most energetic patterns present in the atmosphere. We test our findings by preventing these patterns from affecting the ocean in our numerical model and measure a strong reduction in ocean heat content fluctuations.

ENSO phase locking, asymmetry and predictability in the INMCM Earth system model

Abstract Advanced numerical climate models are known to exhibit biases in simulating some features of El Niño–Southern Oscillation (ENSO), which is a key mode of interannual climate variability. In this study we analyze how two fundamental features of observed ENSO – asymmetry between hot and cold states and phase-locking to the annual cycle – are reflected in two different versions of the INMCM Earth system model (state-of-the-art Earth system model participating in the Coupled Model Intercomparison Project). We identify the above ENSO features using the conventional empirical orthogonal functions (EOF) analysis, which is applied to both observed and simulated upper ocean heat content (OHC) data in the tropical Pacific. We obtain that the observed tropical Pacific OHC variability is described well by two leading EOF-modes, which roughly reflect the fundamental recharge-discharge mechanism of ENSO. These modes exhibit strong seasonal cycles associated with ENSO phase locking while the revealed nonlinear dependencies between amplitudes of these cycles reflect ENSO asymmetry.We also assess and compare the predictability of observed and simulated ENSO based on linear inverse modelling. We find that the improved INMCM6 model has significant benefits in simulating described features of observed ENSO as compared with the previous INMCM5 model. The improvements of the INMCM6 model providing such benefits are discussed. We argue that proper cloud parameterization scheme is crucial for accurate simulation of ENSO dynamics with numerical climate models.

Processes Driving Subseasonal Variations of Upper Ocean Heat Content in the Equatorial Indian Ocean

AbstractIn the equatorial Indian Ocean, the largest subseasonal temperature variations in the upper ocean are observed below the mixed layer. Subsurface processes can influence mixed layer temperature and consequently air‐sea coupling. However, the physical processes driving temperature variability at these depths are not well quantified. During the boreal winter, the Madden–Julian Oscillation (MJO) partly drives upper ocean heat content (OHC) variations. Therefore, to understand processes driving subseasonal OHC variability in the equatorial Indian Ocean, we use an observationally constrained, physically consistent ocean state estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) Consortium. Using a heat budget analysis, we show that the main driver of subseasonal OHC variability in the ECCO ocean state estimate is horizontal advection. Along the equator, OHC variations are driven by zonal advection while the role of meridional advection becomes more important away from the equator. During the active phase of the MJO, net air‐sea heat fluxes damp OHC variability along the equator, while away from the equator net air‐sea heat fluxes partly drive OHC variability. Equatorial OHC variations are found to be associated with processes driven by Kelvin and Rossby waves consistent with previous studies. By quantifying the physical processes, we highlight the important role of ocean dynamics in contributing to the observed variations of subseasonal OHC in the equatorial Indian Ocean.

Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses.

Long-term changes in ocean heat content (OHC) represent a fundamental global warming indicator and are mostly caused by anthropogenic climate-altering gas emissions. OHC increases heavily threaten the marine environment, therefore, reconstructing OHC before the well-instrumented period (i.e., before the Argo floats deployment in the mid-2000s) is crucial to understanding the multi-decadal climate change in the ocean. Here, we shed light on ocean warming and its uncertainty for the 1961-2022 period through a large ensemble reanalysis system that spans the major sources of uncertainties. Results indicate a 62-year warming of 0.43 ± 0.08 W m-2, and a statistically significant acceleration rate equal to 0.15 ± 0.04 W m-2 dec-1, locally peaking at high latitudes. The 11.6% of the global ocean area reaches the maximum yearly OHC in 2022, almost doubling any previous year. At the regional scale, major OHC uncertainty is found in the Tropics; at the global scale, the uncertainty represents about 40% and 15% of the OHC variability, respectively before and after the mid-2000s. The uncertainty of regional trends is mostly affected by observation calibration (especially at high latitudes), and sea surface temperature data uncertainty (especially at low latitudes).

A meridional dipole mode in the Indian Ocean subsurface ocean heat content and its multidecadal variability

The dominant mode of the Indian Ocean variability can be impacted by changes in the background state (multidecadal timescale) of the subsurface heat content. The multidecadal variability of subsurface ocean heat content (sub-OHC) in the Indian Ocean is examined using four reanalysis products from 1958 to 2017. The analysis reveals a meridional basin-wide dipole mode in the subsurface OHC until the late 1980s, followed by the mode embedded in the uniform basin-wide patterns. These patterns are also observed in the trends of thermocline and sea surface height. The observed patterns in the Indian Ocean are explained by two distinct mechanisms. Firstly, the multidecadal variability of dipole patterns over the Indian Ocean is influenced by local wind forcing. Wind stress trends and Ekman pumping velocity trends favor downwelling (upwelling) in the off-equatorial southern Indian Ocean region, leading to thermocline depth deepening (shallowing) during 1958–1975 and 1976–1987, respectively. Secondly, the combined effect of heat transport from the western Pacific through Indonesian Through Flow and local wind forcing accounts for the basin-wide cooling and warming trends observed during 1988–2000, and 2001–2014, respectively.

Long-term trend and variability of ocean heat content in the Indonesian Maritime Continent

The evolution of 64 years of the ocean heat content for the upper 300 meters (OHC300) in the Indonesian Maritime Continent, viz the Banda Sea, the Sulu Sea, the Java Sea, and the Karimata Strait, was investigated using the combination of ocean and atmosphere reanalysis data. The study aims to understand its long-term trend variability and association with El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The result showed a positive trend in all basins except the Banda Sea. The most significant rise was the Sulu Sea. The IOD fluctuation was more pronounced in the Western part of Indonesia. In contrast, the ENSO variation was more apparent in the Eastern part of Indonesia. The coincided La Nina events and the negative IOD significantly increased OHC—conversely, the coinciding of the El Niño events and the positive IOD caused a decrease in OHC magnitude. The significant factor increasing OHC in the maritime continent is the ENSO fluctuation, followed by the IOD fluctuation.

Ocean Heat Content Responses to Changing Anthropogenic Aerosol Forcing Strength: Regional and Multi‐Decadal Variability

AbstractThe causes of decadal variations in global warming are poorly understood, however it is widely understood that variations in ocean heat content (OHC) are linked with variations in surface warming. To investigate the forced response of OHC to anthropogenic aerosols (AA), we use an ensemble of historical simulations, which were carried out using a range of anthropogenic aerosol forcing magnitudes in a CMIP6‐era global circulation model. We find that the centennial scale linear trends in historical OHC are significantly sensitive to AA forcing magnitude (−3.0 ± 0.1 × 105 (J m−3 century−1)/(W m−2), R2 = 0.99), but interannual to multi‐decadal variability in global OHC appear largely independent of AA forcing magnitude. Comparison with observations find consistencies in different depth ranges and at different time scales with all but the strongest aerosol forcing magnitude, at least partly due to limited observational accuracy. We find that OHC is sensitive to aerosol forcing magnitude across much of the tropics and sub‐tropics, and stronger negative forcing induces more ocean cooling. The polar regions and North Atlantic show the strongest heat content trends, and also show the strongest dependence on aerosol forcing magnitude. However, the OHC response to increasing aerosol forcing magnitude in the North Atlantic and Southern Ocean is either dominated by internal variability, or strongly state dependent, showing different behavior in different time periods. Our results suggest the response to aerosols in these regions is a complex combination of influences from ocean transport, atmospheric forcings, and sea ice.

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Characterizing the Variability of Boundary Currents and Ocean Heat Content Around New Zealand Using a Multi‐Decadal High‐Resolution Regional Ocean Model

AbstractNew Zealand is located in the southwest Pacific Ocean and is surrounded by a complex system of boundary currents that vary on a variety of time scales, with important impacts on weather, primary productivity, and fisheries. While various observational and modeling studies have shed light on many of the characteristics of New Zealand's ocean circulation, this study provides a comprehensive, quantitative, seamless, 3‐dimensional characterization of the region's boundary current circulation and ocean heat content. We use a 28 yr long hydrodynamic model simulation that accurately represents the mean and variability of the ocean circulation to characterize and quantify the temporal and spatial variability across the region. We show that low‐frequency variability in boundary current transport and upper ocean heat content are correlated over the entire New Zealand oceanic region. Oceanic eddies dominate heat content variability at intra‐annual scales in the northeast of the region, while on the west and southeast coasts heat content varies predominantly at interannual scales controlled by large‐scale changes in the subtropical and sub‐Antarctic fronts. The model shows a significant downstream strengthening and deepening of the boundary currents off northeast New Zealand which, if confirmed by observations, could suggest a significant new understanding of this Western Boundary Current system. This study presents a region‐wide characterization of the temporal and spatial variability of ocean currents and heat content, and their interconnections, providing a vital basis for understanding climate change impacts and the increasing occurrence of marine heatwaves.

Seasonal Variability in Ocean Heat Content and Heat Flux in the Arabian Gulf

This study aimed to evaluate the seasonal variability in surface heat content in the Arabian Gulf (AG) based on hydrographic data. The ocean heat content (OHC) was initially estimated from surface to maximum depth (75 m) to show the seasonal variability, where the seasonal temperature reaches to that depth. Then OHC was re-estimated from the surface to a depth of 35 m, which represents the average depth of AG, to obtain accurate horizontal distributions. Results showed that during winter, the northern part of AG experiences the lowest OHC compared to the southeastern part. The monthly spatial average implies that the highest OHC of AG water was in September and October, while the lowest heat content was found in February and March. However, the OHC horizontal distributions were almost the same for the entire gulf during summer. In general, there was increasing in the OHC in the southeast region of the gulf. OHC anomalies are concentrated in the northern region of the AG, while the southeastern part near the Strait of Hormuz has the lowest values. Regarding heat flux, the highest heat gains were during spring, while the highest loss was in autumn. The water exchange between the AG and the Indian Ocean through the Strait of Hormuz may play a major role in the seasonal variability in OHC.

Recent Warming Trends in the Arabian Sea: Causative Factors and Physical Mechanisms

In recent years, and particularly from 2000 onwards, the North Indian Ocean (NIO) has been acting as a major sink of ocean heat that is clearly visible in the sub-surface warming trend. Interestingly, a part of the NIO—the Arabian Sea (AS) sector—witnessed dramatic variations in recent sub-surface warming that has direct repercussion on intense Tropical Cyclone (TC) activity. This study investigated the possible causative factors and physical mechanisms towards the multi-decadal warming trends in surface and sub-surface waters over the AS region. Responsible factors towards warming are examined using altimetric observations and reanalysis products. This study used ORAS5 OHC (Ocean Heat Content), derived meridional and zonal heat transport, currents, temperature, salinity, Outgoing Longwave Radiation (OLR), and air-sea fluxes to quantify the OHC build-up and its variability at water depths of 700 m (D700) and 300 m (D300) during the past four decades. The highest variability in deeper and upper OHC is noticed for the western and southern regions of the Indian Ocean. The warming trend is significantly higher in the deeper regions of AS compared to the upper waters, and relatively higher compared to the Bay of Bengal (BoB). Increased OHC in AS show good correlation with decreased OLR in the past 20 years. An analysis of altimetric observations revealed strengthening of downwelling Kelvin wave propagation leading to warming in eastern AS, mainly attributed due to intrusion of low saline water from BoB leading to stratification. Rossby wave associated with deepening of thermocline warmed the southern AS during its propagation. Heat budget analysis reveals that surface heat fluxes play a dominant role in warming AS during the pre-monsoon season. Increasing (decreasing) trend of surface heat fluxes (vertical entrainment) during 2000–2018 played a significant role in warming the southeastern sector of AS.

Unabated Global Ocean Warming Revealed by Ocean Heat Content from Remote Sensing Reconstruction

As the most relevant indicator of global warming, the ocean heat content (OHC) change is tightly linked to the Earth’s energy imbalance. Therefore, it is vital to study the OHC and heat absorption and redistribution. Here we analyzed the characteristics of global OHC variations based on a previously reconstructed OHC dataset (named OPEN) with four other gridded OHC datasets from 1993 to 2021. Different from the other four datasets, the OPEN dataset directly obtains OHC through remote sensing, which is reliable and superior in OHC reconstruction, further verified by the Clouds and the Earth’s Radiant Energy System (CERES) radiation flux data. We quantitatively analyzed the changes in the upper 2000 m OHC of the oceans over the past three decades from a multisource and multilayer perspective. Meanwhile, we calculated the global ocean heat uptake to quantify and track the global ocean warming rate and combined it with the Oceanic Niño Index to analyze the global evolution of OHC associated with El Niño–Southern Oscillation variability. The results show that different datasets reveal a continuously increasing and non-decaying global ocean warming from multiple perspectives, with more heat being absorbed by the subsurface and deeper ocean over the past 29 years. The global OHC heating trend from 1993 to 2021 is 7.48 ± 0.17, 7.89 ± 0.1, 10.11 ± 0.16, 7.78 ± 0.17, and 12.8 ± 0.26 × 1022 J/decade according to OPEN, IAP, EN4, Ishii, and ORAS5, respectively, which shows that the trends of the OPEN, IAP, and Ishii datasets are generally consistent, while those of EN4 and ORAS5 datasets are much higher. In addition, the ocean warming characteristics revealed by different datasets are somewhat different. The OPEN OHC dataset from remote sensing reconstruction shows a unique remote sensing mapping advantage, presenting a distinctive warming pattern in the East Indian Ocean. Meanwhile, the OPEN dataset had the largest statistically significant area, with 85.6% of the ocean covered by significant positive trends. The significant and continuous increase in global ocean warming over the past three decades, revealed from remote sensing reconstruction, can provide an important reference for projecting ocean warming in the context of global climate change toward the United Nations Sustainable Development Goals.

The interannual variability of shallow meridional overturning circulation and its association with the south-west Indian Ocean heat content variability

The present study examines the interannual variability of the Indian Ocean Shallow Meridional Overturning Circulation (SMOC) using century-long reanalysis data. The strength of the transport associated with SMOC is calculated using meridional overturning stream function. The highest SMOC variability is found between the latitudes 5° S and 15° S, which displayed enhancement in amplitude after 1940s. Strong and weak SMOC years are identified using standard deviation threshold. Strong SMOC years composite displayed excess southward transport (~ 2.5 Sv) and subduction over the South Indian Ocean. The associated southward heat transport (~ 0.25 PW) reduced the sea level and upper 200 m ocean heat content (OHC) over the Southwest Indian Ocean (SWIO). On the other hand, weaker SMOC years composite displayed weak heat transport, increased sea level and OHC over the SWIO. Tide gauge and satellite observations also displayed similar variation in sea level for respective phases of SMOC. Further analysis reveals that the SMOC variability is primarily driven by changes in the zonal wind stress south of the equator and displays close association with the Southern Oscillation Index. The Ocean model-based sensitivity experiments confirm that the OHC variability over SWIO is closely associated with the SMOC variability and is primarily driven by local wind forcing as a response to El Niño Southern Oscillation. However, the role of remote forcing from Pacific through oceanic pathway over SWIO is not evident. The present study provides a comprehensive understanding of the interannual variability of SMOC and its linkage to sea level and OHC variability over SWIO during the last century.

Oceanic Electrical Conductivity Variability From Observations and Its Budget From an Ocean State Estimate

AbstractBecause spatio‐temporal variations in ocean heat content (OHC) are strongly predicted by ocean conductivity content (OCC) over most of the global ocean, we analyze the dynamical budget and behavior of the electrical conductivity of seawater. To perform these analyses, we use an ocean‐model state estimate designed to accurately represent long‐term variations in ocean properties in a dynamically and kinematically consistent way. We show that this model accurately reproduces the spatio‐temporal variations in electrical conductivity seen in satellite‐derived data and in a seasonal climatology product derived from in‐situ data, justifying use of the model data to perform further analyses. An empirical orthogonal function analysis suggests that the vast majority of the variance in OHC and OCC can be explained by similar mechanisms. The electrical conductivity budget's most important term is the temperature forcing tendency term, suggesting that ocean heat uptake is the mechanism responsible for the strong relationship between OCC and OHC.

The redistribution of anthropogenic excess heat is a key driver of warming in the North Atlantic

Understanding ocean excess heat uptake is crucial for assessing climate warming, yet uncertainties remain about its history and redistribution. Here, we reconstruct ocean heat content change along the 25°N Atlantic hydrographic section and assess its spatiotemporal origin and fate. We show that the delayed response of the ocean below 700 m to sea surface temperature change contribute to 62% of full depth warming at this latitude for 1850–2018, falling to 35% for 1975–2018 when anthropogenic warming in the upper ocean accelerated. The regional climate fluctuations shape ocean heat content variability at 25°N with contributions from the Labrador Sea producing most of the decadal variability and the Nordic Seas bound to become the main contributor to deep ocean warming in the coming decades. Chiefly, the net excess heat transport across 25°N has increased recently, warming the domain north of 25°N at a rate of 0.89 ± 0.19 W m−2 during 2012–2018, revealing that excess heat redistribution is a key driver of North Atlantic heat gain.

Spatiotemporal propagating decadal signal of ocean heat content and thermocline depth identified in the tropical Pacific

Tropical Pacific decadal variability (TPDV) and its mechanisms are essential for understanding long-term variations in global climate. The spatiotemporal pattern of this decadal variation has yet to be clarified. Here, on the basis of observational data with the help of the adaptive data analysis method, we extracted and investigated the spatiotemporal evolution of the tropical Pacific decadal variability in upper ocean heat content (UOHC) and thermocline depth. The tropical decadal signal propagated eastward along the equator from the western Pacific to the eastern Pacific after the 1970s, with a speed of 4–5 cm s−1 yielding a decadal oscillation of approximately 11–13 years. This decadal variability of the thermocline fluctuations (UOHC) was proven to be closely correlated with western wind anomalies since the 1970s and may have been induced by the regime shift of the Pacific decadal oscillation. These peaks of decadal signals corresponded well with the strong El Niño–Southern Oscillation (ENSO) events, reflecting nonlinear rectification of ENSOs on TPDV. Moreover, the TPDV showed a modulating signal on moderate and weak ENSO events.

Improving statistical prediction and revealing nonlinearity of ENSO using observations of ocean heat content in the tropical Pacific

It is well-known that the upper ocean heat content (OHC) variability in the tropical Pacific contains valuable information about dynamics of El Niño–Southern Oscillation (ENSO). Here we combine sea surface temperature (SST) and OHC indices derived from the gridded datasets to construct a phase space for data-driven ENSO models. Using a Bayesian optimization method, we construct linear as well as nonlinear models for these indices. We find that the joint SST-OHC optimal models yield significant benefits in predicting both the SST and OHC as compared with the separate SST or OHC models. It is shown that these models substantially reduce seasonal predictability barriers in each variable—the spring barrier in the SST index and the winter barrier in the OHC index. We also reveal the significant nonlinear relationships between the ENSO variables manifesting on interannual scales, which opens prospects for improving yearly ENSO forecasting.

Predictability of the low-frequency modes of the Arctic Ocean heat content variability: a perfect model approach

Abstract The problem of potential predictability of the temperature of the upper layer of the Arctic Ocean for the data of pre-industrial climate modelling run by the INM-CM5 Earth system model developed at the INM RAS is considered. The main attention is paid to the analysis of predictability of the phases of the dominant modes of low-frequency variability of the Arctic Ocean circulation. The initial estimate of its predictability is made by using the method of analogues and calculating the resonances of the invariant measure. Then this estimate is verified by direct ensemble calculations with the model. The results obtained indicate that the maximum predictability time interval reaches ten years for 15-year average values of heat content and corresponds to the states with maximum positive anomalies along the leading low-frequency variability modes.