Upper-ocean Heat Research Articles

Multi-year La Niña frequency tied to southward tropical Pacific wind shift

AbstractMulti-year La Niña events cause prolonged climate disruptions worldwide, but a systematic understanding of the underlying mechanisms is not yet established. Here we show using observations and models from the sixth phase of Coupled Model Intercomparison Project that a greater frequency of consecutive La Niña events is tied to the upper equatorial Pacific Ocean when it favors more rapid heat discharge. The propensity for heat discharge is underscored by negative skewness in upper-ocean heat content, underpinned by southward tropical Pacific wind shift during austral summer. Models with stronger westerly anomalies south of the equator simulate steeper east-to-west upward tilt of the thermocline that is favorable for a greater discharge rate. This highlights the crucial role of the southward wind shift in the nonlinear system of the El Niño-Southern Oscillation. The large inter-model spread in multi-year La Niña processes underscores the need in constraining models for reliable climate prediction and projection.

Salinity and Stratification at the Sea Ice Edge (SASSIE): an oceanographic field campaign in the Beaufort Sea

Abstract. As our planet warms, Arctic sea ice coverage continues to decline, resulting in complex feedbacks with the climate system. The core objective of NASA's Salinity and Stratification at the Sea Ice Edge (SASSIE) mission is to understand how ocean salinity and near-surface stratification affect upper-ocean heat content and thus sea ice freeze and melt. SASSIE specifically focuses on the formation of Arctic Sea ice in autumn. The SASSIE field campaign in 2022 collected detailed observations of upper-ocean properties and meteorology near the sea ice edge in the Beaufort Sea using ship-based and piloted and drifting assets. The observations collected during SASSIE include vertical profiles of stratification up to the sea surface, air–sea fluxes, and ancillary measurements that are being used to better understand the role of salinity in coupled Arctic air–sea–ice processes. This publication provides a detailed overview of the activities during the 2022 SASSIE campaign and presents the publicly available datasets generated by this mission (available at https://podaac.jpl.nasa.gov/SASSIE, last access: 29 May 2024; DOIs for individual datasets in the “Data availability” section), introducing an accompanying repository that highlights the numerical routines used to generate the figures shown in this work.

Mean‐State and Seasonal Variability in Temperature Structure and Heat Transport in the East Australian Current System From a Multi‐Decadal Regional Ocean Model

AbstractWestern Boundary Currents (WBCs) such as the East Australian Current (EAC) are vital for moving heat from low to high latitudes, controlling regional weather and global climate. Previous EAC System studies have provided a general overview of temperature variability and heat transport, but they lacked spatial and seasonal detail. Using a high‐resolution, 26‐year‐long ocean model simulation, we systematically characterize the seasonal variability and structure in key temperature metrics and heat transport in the EAC System. Our findings reveal a clear seasonal cycle with a poleward expansion of key variables in summer (mean and eddy kinetic energy, upper ocean heat content, heat transport) and contraction equatorward with reductions in winter. We show that the dynamical regime transition, from jet to eddy‐dominated at the EAC separation zone (S), modifies the net meridional heat transport. Upstream of separation, transport is poleward, with some zonal input of heat. Downstream of EAC separation, there is an increase in heat recirculation by mesoscale eddies combined with a smaller zonal export of heat. This study highlights the significance of resolving spatio‐temporal variability in WBC systems driven by mesoscale dynamics, which will have implications for the representation of critical dynamics in future climate models.

The role of upper-ocean heat content in the regional variability of Arctic sea ice at sub-seasonal timescales

Abstract. In recent decades, the Arctic Ocean has undergone changes associated with enhanced poleward inflow of Atlantic and Pacific waters and increased heat flux exchange with the atmosphere in seasonally ice-free regions. The associated changes in upper-ocean heat content can alter the exchange of energy at the ocean–ice interface. Yet, the role of ocean heat content in modulating Arctic sea ice variability at sub-seasonal timescales is still poorly documented. We analyze ocean heat transports and surface heat fluxes between 1980–2021 using two eddy-permitting global ocean reanalyses, C-GLORSv5 and ORAS5, to assess the surface energy budget of the Arctic Ocean and its regional seas. We then assess the role of upper-ocean heat content, computed in the surface mixed layer (Qml) and in the 0–300 m layer (Q300), as a sub-seasonal precursor of sea ice variability by means of lag correlations. Our results reveal that in the Pacific Arctic regions, sea ice variability in autumn is linked with Qml anomalies leading by 1 to 3 months, and this relationship has strengthened in the Laptev and East Siberian seas during 2001–2021 relative to 1980–2000, primarily due to reduced surface heat loss since the mid-2000s. Q300 anomalies act as a precursor for wintertime sea ice variability in the Barents and Kara seas, with considerable strengthening and expansion of this link from 1980–2000 and 2001–2021 in both reanalyses. Our results highlight the role played by upper-ocean heat content in modulating the interannual variability of Arctic sea ice at sub-seasonal timescales. Heat stored in the ocean has important implications for the predictability of sea ice, calling for improvements in forecast initialization and a focus upon regional predictions in the Arctic region.

Escalation of tropical cyclone impacts on the northwestern Bay of Bengal over the past decade

Tropical cyclones have resulted in casualties and economic losses in the areas surrounding the Bay of Bengal (BoB). Thus, a comprehensive investigation of these tropical cyclones holds vital implications for disaster preparedness and mitigation. This paper compares the occurrence of storms in the last two decades, i.e., 2002–2011 and 2012–2021, and results reveal that such storms exhibited predominantly a northwesterly track towards the northwestern BoB, with a severer intensity but equal total storm frequencies. Over the past decade, a southeast-northwest pathway (SNP) was identified, demonstrating a higher incidence of severe tropical cyclones (STC, with lifetime maximum intensity ≥ 64 knots) over the BoB. Further analysis of the changes in the environmental conditions between these two decades indicates that a southeasterly anomaly in the steering flow contributed to the formation of the SNP. During the same period, the more favorable oceanic conditions during the last decade, including higher sea surface temperatures, a greater upper ocean heat content, a thicker warm water layer, and a thicker barrier layer beneath the SNP, favored the development of these storms by providing more heat energy to the storms. The atmospheric conditions, including increased air-sea heat fluxes, moisture, and instability within the lower troposphere, as well as reduced vertical wind shear, facilitated the development of convection within these storm systems. These favorable conditions improved the potential for storm development into STCs and elevated the risk of the northwestern BoB being impacted by more destructive storms.

Variations in the Upper Ocean Heat Content of the Southern Canadian Basin

Variations in the Upper Ocean Heat Content of the Southern Canadian Basin

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.

Definition of springtime easterly wind bursts in the Indian Ocean and their roles in triggering positive IOD events

Using wind reanalysis dataset, we propose a definition for easterly wind bursts (EWBs) occurring in the Indian Ocean and analyze their effects on positive Indian Ocean Dipole (pIOD) events. It was found that there were eight pIOD events during the period from 1980–2020, all of which were accompanied by EWBs occurrence in spring except 2015. The significant impact of EWBs on pIOD events is through the Bjerkness feedback process, strengthening upwelling in the Eastern Indian Ocean (EIO) and triggering a westward zonal current in the equatorial Indian Ocean, both cooling the EIO and in turn strengthening the easterly wind anomalies. Further analysis reveals that the negative upper ocean heat content (OHC) anomalies in EIO, acting as a trigger of Bjerkness feedback process, also plays a critical role in the development of pIOD. Thus, the simultaneous occurrence of EWBs and negative OHC anomalies in spring is an important precursor to pIOD occurrence, although there are possible other triggers.

COVID Impacts Cause Critical Gaps in the Indian Ocean Observing System

Abstract Observing and understanding the state of the Indian Ocean and its influence on climate and maritime resources is of critical importance to the populous nations that rim its border. Acute gaps have occurred in the Indian Ocean Observing System, which underpins monitoring and forecasting of regional climate, since the start of the COVID pandemic. The pandemic disrupted the deployment and maintenance cruises for the observational array and also resulted in supply chain issues for procurement and refurbishment of equipment. In particular, the observational platforms that provide key measurements of upper ocean heat variability have experienced serious multiyear declines. There is now record-low data reporting and the platforms that are successfully reporting are old and quickly surpassing their expected period of reliable operation. The overall impact on the observing system will take a few years to fully comprehend. In the meantime, there is a critical need to document the gaps that have appeared over the past few years and how this will impact our ability to improve understanding and model representations of the real world that support regional weather and climate forecasts. The article outlines the expected slow road to recovery for the Indian Ocean Observing System, documents case studies of successful international collaborative efforts that will revive the observing system and provides guidelines for resilience from unexpected external factors in the future.

A new tool for studying seasonality and spatio-temporal structure of ENSO cycles in data and ESM simulations

Abstract In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality.

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.

Impacts of North Atlantic Model Biases on Natural Decadal Climate Variability

AbstractIncreasing the horizontal resolution of an ocean model is frequently seen as a way to reduce the model biases in the North Atlantic, but we are often limited by computational resources. Here, a two‐way nested ocean model configuration (VIKING10) that consists of a high‐resolution (1/10°) component and covers the northern North Atlantic, is embedded in a 1/2° ocean grid as part of the global chemistry‐climate model, FOCI (called FOCI‐VIKING10). This configuration yields a significantly improved path of the North Atlantic current (NAC), which here reduces the North Atlantic cold bias by ∼50%. Compared with the coarse‐resolution, non‐eddying model, the improved thermal state of upper ocean layers and surface heat fluxes in a historical simulation based on FOCI‐VIKING10 are beneficial for simulating the subdecadal North Atlantic Oscillation (NAO) variability (i.e., a period of 8 years). A northward drift of the NAO‐forced ocean thermal anomalies as seen in observations and the eddying FOCI‐VIKING10, provide a lagged ocean feedback to the NAO via changes in the net surface heat flux, leading to the NAO periodicity of 8 years. This lagged feedback and the 8 years variability of the NAO cannot be captured by the non‐eddying standard FOCI historical simulation. Furthermore, the argumentative responses of the North Atlantic to the 11‐year solar cycle are re‐examined in this study. The reported solar‐induced NAO‐like responses are confirmed in the 9‐member ensemble mean based on FOCI but with low robustness among individual members. A lagged NAO‐like response is only found in the nested eddying simulation but absent from the non‐eddying reference simulation, suggesting North Atlantic biases importantly limit climate model capability to realistically solar imprints in North Atlantic climate.

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.

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Atmosphere–Ocean Coupled Energy Budgets of Tropical Convective Discharge–Recharge Cycles

Abstract An energy budget combining atmospheric moist static energy (MSE) and upper ocean heat content (OHC) is used to examine the processes impacting day-to-day convective variability in the tropical Indian and western Pacific Oceans. Feedbacks arising from atmospheric and oceanic transport processes, surface fluxes, and radiation drive the cyclical amplification and decay of convection around suppressed and enhanced convective equilibrium states, referred to as shallow and deep convective discharge–recharge (D–R) cycles, respectively. The shallow convective D–R cycle is characterized by alternating enhancements of shallow cumulus and stratocumulus, often in the presence of extensive cirrus clouds. The deep convective D–R cycle is characterized by sequential increases in shallow cumulus, congestus, narrow deep precipitation, wide deep precipitation, a mix of detached anvil and altostratus and altocumulus, and once again shallow cumulus cloud types. Transitions from the shallow to deep D–R cycle are favored by a positive “column process” feedback, while discharge of convective instability and OHC by mesoscale convective systems (MCSs) contributes to transitions from the deep to shallow D–R cycle. Variability in the processes impacting MSE is comparable in magnitude to, but considerably more balanced than, variability in the processes impacting OHC. Variations in the quantity of atmosphere–ocean coupled static energy (MSE + OHC) result primarily from atmospheric and oceanic transport processes, but are mainly realized as changes in OHC. MCSs are unique in their ability to rapidly discharge both lower-tropospheric convective instability and OHC.

How Well Do CMIP6 Models Simulate Salinity Barrier Layers in the North Indian Ocean?

Abstract Previous studies have hypothesized that climatologically thick salinity-stratified barrier layers (BLs) in the north Indian Ocean (NIO) influence the upper ocean heat budget, sea surface temperature (SST), and monsoons. Here, we investigate how state-of-the-art Coupled Model Intercomparison Project phase 6 (CMIP6) climate models simulate the NIO barrier layer thickness (BLT). CMIP6 models generally reproduce the BLT seasonal cycle and spatial distribution, but with shallow November–February (NDJF) biases in regions with thick observed BLT: the eastern equatorial Indian Ocean (EEIO), Bay of Bengal (BoB), and southeastern Arabian Sea (SEAS). We show that the intensity of the CMIP6 equatorial easterly wind bias controls the EEIO shallow isothermal layer depth (ILD) and BLT biases. It also controls the BoB shallow BLT bias, both through the propagation of the EEIO shallow ILD bias into the NIO coastal waveguide and because it is linked to the BoB dry and cold bias through the Bjerknes feedback, hence also controlling the mixed layer depth (MLD) deep bias there. Finally, the SEAS shallow BLT bias is due to a too-deep MLD, in response to subdued monsoonal currents around India, which do not bring enough BoB low-salinity water. The BL insulating effect mentioned in literature does not seem to dominate in CMIP6. Rather, the CMIP6 salinity-related deep MLD biases diminish the BoB cooling rate by winter upward surface heat fluxes, reducing cold SST biases. This suggests that salinity effects alleviate the easterly equatorial wind, cold, and dry BoB biases that develop through the positive Bjerknes feedback loop in CMIP6.

Can ocean heat content regulate Indian summer monsoon rainfall?

Abstract Modern studies suggest that the upper ocean heat content (OHC) in the tropical Indian Ocean (TIO) is a better qualitative predictor of the Indian summer monsoon rainfall (ISMR). But it is still unknown how the OHC is mechanically linked to ISMR and whether it can be applied to long-term climate changes. By analyzing reanalysis datasets across the 20th century, we illustrate that in contrast to those anomalies associated with stronger ISM westerlies, higher ISMR is accompanied with summer surface high pressure and east wind anomalies from the South China Sea to the Bay of Bengal (BOB), and is loosely related to increased western TIO OHC during decayed phases of positive Indian Ocean dipole (IOD) and of El Niño. Except for 1944–1968 AD, this interannually lagged ISMR response to winter OHC is insignificant, probably suppressed by those simultaneous effects of positive IOD and El Niño on ISMR. In our paleoclimatic simulations, this modern observed lagged response is interrupted by seasonally reversed insolation anomalies at the 23,000-year precessional band. Our sensitivity experiments further prove that, the ISMR can be simultaneously reduced by positive IOD-like summer OHC anomalies both for modern and precessional situations. This damping effect is mainly contributed by the warmer western TIO that triggers anomalous surface high pressure, easterly winds, and drastically reduced rainfall from BOB to Arabian Peninsula, but with slightly increased rainfall in the northern ISM region. And the cooler southeastern TIO will only moderately increase rainfall in the southern ISM region.

Subtropical Mode Water south of Japan impacts typhoon intensity.

Subtropical Mode Water (STMW), characterized by vertically uniform temperature of ~17°C, is distributed horizontally over 5000 kilometers at the 100- to 500-meter depths in the subtropical North Pacific Ocean. Its formation and spreading fluctuate in relation to the Pacific Decadal Oscillation and the Kuroshio path variation, but the feedback from STMW on the sea surface temperature (SST) and the overlying atmosphere remains unclear. Using Argo profiling float data, we show that STMW south of Japan, whose thickness varies decadally, modulates the overlying thermal structure throughout the year by increasing isotherm uplift with increasing thickness. The STMW-induced decadal temperature change has a magnitude of up to ~1°C and is large in the warm season in the presence of the seasonal thermocline. Furthermore, 50-year observations, together with numerical simulation, show that SST, upper ocean heat content, and typhoon intensification rate have been significantly lower in years with thicker STMW and higher in years with thinner STMW.

Evaluation of multi-level upper ocean heat content and its relationship with intensity and translation speed of tropical cyclones in the North Indian Ocean

Evaluation of multi-level upper ocean heat content and its relationship with intensity and translation speed of tropical cyclones in the North Indian Ocean

An Improved Coupled Data Assimilation System with a CGCM Using Multi-Time-Scale High-Efficiency EnOI-Like Filtering

Abstract Coupled data assimilation (CDA), which combines coupled models and observations from multiple Earth system domains, plays a critical role in climate studies by producing a four-dimensional estimation of Earth system states. Traditional ensemble Kalman filter (EnKF) CDA algorithms, while convenient to implement in multiple DA components in a coupled system, are, however, expensive and lack sufficient representativeness for low-frequency background flows. Here, a multi-time-scale high-efficiency approximate filter with ensemble optimal interpolation (MSHea-EnOI) scheme has been implemented with a global fully coupled model. It consists of stationary, low-frequency, and high-frequency filters constructed from the time series of a single-model solution with improved representativeness for low-frequency background error statistics and enhanced computational efficiency. The MSHea-EnOI is evaluated in a biased twin experiment framework with synthetic “observations” produced by another coupled model, and a three-decade coupled reanalysis experiment with real observations. Results show that with increased representativeness on multiscale background flows, while computationally costing only a small fraction of ensemble-based CDA, the MSHea-EnOI shows the potential to improve CDA quality with synthetic observations. The coupled reanalysis experiment with real observations also shows reasonable fittings to observations and comparable results to other reanalysis products using different DA schemes. While reconstructing a close-to-rapid Atlantic meridional overturning circulation, the coupled reanalysis reproduces most of the atmosphere and ocean reanalysis signals such as the Hadley circulation and upper ocean heat content. The MSHea-EnOI could have good application potential in ensemble-based DA systems in terms of its multiscale property and computational efficiency.