Subsurface Temperature Observations Research Articles

Assessing the impact of subsurface temperature observations from fishing vessels on temperature and heat content estimates in shelf seas: a New Zealand case study using Observing System Simulation Experiments

We know that extremes in ocean temperature often extend below the surface, and when these extremes occur in shelf seas they can significantly impact ecosystems and fisheries. However, a key knowledge gap exists around the accuracy of model estimates of the ocean’s subsurface structure, particularly in continental shelf regions with complex circulation dynamics. It is well known that subsurface observations are crucial for the correct representation of the ocean’s subsurface structure in reanalyses and forecasts. While Argo floats sample the deep waters, subsurface observations of shelf seas are typically very sparse in time and space. A recent initiative to instrument fishing vessels and their equipment with temperature sensors has resulted in a step-change in the availability of in situ data in New Zealand’s shelf seas. In this study we use Observing System Simulation Experiments to quantify the impact of the recently implemented novel observing platform on the representation of temperature and ocean heat content around New Zealand. Using a Regional Ocean Modelling System configuration of the region with 4-Dimensional Variational Data Assimilation, we perform a series of data assimilating experiments to demonstrate the influence of subsurface temperature observations at two different densities and of different data assimilation configurations. The experiment period covers the 3 months during the onset of the 2017-2018 Tasman Sea Marine Heatwave. We show that assimilation of subsurface temperature observations in concert with surface observations results in improvements of 44% and 38% for bottom temperature and heat content in shelf regions (water depths< 400m), compared to improvements of 20% and 28% for surface-only observations. The improvement in ocean heat content estimates is sensitive to the choices of prior observation and background error covariances, highlighting the importance of the careful development of the assimilation system to optimize the way in which the observations inform the numerical model estimates.

Impact of assimilating repeated subsurface temperature transects on state estimates of a western boundary current

Western Boundary Currents and the eddies they shed are high priorities for numerical estimation and forecasting due to their economic, ecological and dynamical importance. However, the rapid evolution, complex dynamics and baroclinic structure that is typical of eddies and the relatively sparse sampling in western boundary currents leads to significant challenges in understanding the 3-dimensional structure of these boundary currents and mesoscale eddies. Here, we use Observing System Simulation Experiments (OSSEs) to explore the impact of assimilating synthetic subsurface temperature observations at a range of temporal resolutions, to emulate expendable bathythermograph transects with different repeat frequencies (weekly to quarterly). We explore the improvement in the representation of mesoscale eddies and subsurface conditions in a dynamic western boundary current system, the East Australian Current, with a data-assimilating regional ocean model. A characterisation of the spatial and temporal ocean variability spectrum demonstrates the potential for undersampling and aliasing by a lower sampling frequency. We find that assimilating subsurface temperature data with at least a weekly repeat time best improves subsurface representation of this dynamic, eddy-rich region. However, systemic biases introduced by the data assimilation system hinder the ability of the model to produce more accurate subsurface representation with fortnightly or monthly sampling. Removal of this bias may improve subsurface representation in eddy-rich regions with fortnightly or even less frequent observations. These results highlight the value of both increased subsurface observation density in regions of dynamic oceanography as well as continued development of data assimilation techniques in order to optimise the impact of existing observations.

Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current

Abstract. Western boundary currents (WBCs) form the narrow, fast-flowing poleward return flows of the great subtropical ocean gyres and are sources of rapidly varying mesoscale eddies. Accurate simulation of the vertical structure, separation latitude, and ocean heat content of WBCs is important for understanding the poleward transport of heat in the global ocean. However, state estimation and forecasting in WBC regions, such as the East Australian Current (EAC), the WBC of the South Pacific subtropical gyre, is challenging due to their dynamic nature and lack of observations at depth. Here we use observing system simulation experiments to show that subsurface temperature observations in a high eddy kinetic energy region yield large improvement in representation of key EAC circulation features, both downstream and ∼ 600 km upstream of the observing location. These subsurface temperature observations (in concert with sea surface temperature and height measurements) are also critical for correctly representing ocean heat content along the length of the EAC. Furthermore, we find that a more poleward separation latitude leads to an EAC and eddy field that is represented with far reduced error, compared to when the EAC separates closer to the Equator. Our results demonstrate the importance of subsurface observations for accurate state estimation of the EAC and ocean heat content that can lead to marine heatwaves. These results provide useful suggestions for observing system design under different oceanographic regimes, for example, adaptive sampling to target high energy states with more observations and low energy states with fewer observations.

Leveraging Uncertainty Quantification to Design Ocean Climate Observing Systems

AbstractOcean observations are expensive and difficult to collect. Designing effective ocean observing systems therefore warrants deliberate, quantitative strategies. We leverage adjoint modeling and Hessian uncertainty quantification (UQ) within the ECCO (Estimating the Circulation and Climate of the Ocean) framework to explore a new design strategy for ocean climate observing systems. Within this context, an observing system is optimal if it minimizes uncertainty in a set of investigator‐defined quantities of interest (QoIs), such as oceanic transports or other key climate indices. We show that Hessian UQ unifies three design concepts. (1) An observing system reduces uncertainty in a target QoI most effectively when it is sensitive to the same dynamical controls as the QoI. The dynamical controls are exposed by the Hessian eigenvector patterns of the model‐data misfit function. (2) Orthogonality of the Hessian eigenvectors rigorously accounts for redundancy between distinct members of the observing system. (3) The Hessian eigenvalues determine the overall effectiveness of the observing system, and are controlled by the sensitivity‐to‐noise ratio of the observational assets (analogous to the statistical signal‐to‐noise ratio). We illustrate Hessian UQ and its three underlying concepts in a North Atlantic case study. Sea surface temperature observations inform mainly local air‐sea fluxes. In contrast, subsurface temperature observations reduce uncertainty over basin‐wide scales, and can therefore inform transport QoIs at great distances. This research provides insight into the design of effective observing systems that maximally inform the target QoIs, while being complementary to the existing observational database.

Sea Turtles for Ocean Research and Monitoring: Overview and Initial Results of the STORM Project in the Southwest Indian Ocean

Surface and sub-surface ocean temperature observations collected by sea turtles (ST) during the first phase (Jan-2019 – April 2020) of the Sea Turtle for Ocean Research and Monitoring (STORM) program are compared against in-situ and satellite temperature measurements, and later relied upon to assess the performance of Glo12 ocean model forecasts over the west tropical Indian Ocean. The evaluation of ocean temperature profiles collected by STs against collocated ARGO drifter measurements show good agreement, with imperceptible discrepancies at all sample depths (0-250m). Comparisons against various operational satellite sea surface temperature (SST) products indicate a slight overestimation of ST-borne temperature observations of ~ 0.1° +/- 0.6° that is consistent with expected uncertainties on satellite derived SST data. Comparisons of ST-borne surface and subsurface temperature observations against Glo12 operational ocean model forecasts demonstrate the good performance of modelled surface and subsurface ( 50m), the model is however shown to significantly underestimate ocean temperatures as already noticed from global evaluation scores performed operationally at the basin scale. The distribution of model errors also shows significant spatial and temporal variability in the first 50 m of the ocean, which will be further investigated in the next phases of the STORM project.

Disturbances of Temperature-Depth Profiles by Surface Warming and Groundwater Flow Convection in Kumamoto Plain, Japan

Subsurface temperatures depend on climate and groundwater flow. A lack of observations of subsurface temperature collected over decades limits interpretation of the combined influences of surface warming and groundwater flow on subsurface thermal regimes. Subsurface temperature-depth profile data acquired for Kumamoto Plain, Japan, between 1987 and 2012 were collected and analyzed to elucidate regional groundwater and heat flows. The observed and simulated temperature-depth profiles showed the following: subsurface water flows from northeast to southwest in the study area; the combined influence of surface warming and water flow perturbation produces different temporal changes in thermal profiles in recharge, intermediate, and discharge areas; and aquifer thermal properties contribute more than hydraulic parameters to the perturbation of temperature-depth profiles. Spatial and temporal evolution features of subsurface thermal regimes may be utilized to investigate the influence of surface warming events on subsurface water and heat flows at the basin scale.

Slowdown of the Walker circulation driven by tropical Indo-Pacific warming

Global mean sea surface temperature (SST) has risen steadily over the past century, but the overall pattern contains extensive and often uncertain spatial variations, with potentially important effects on regional precipitation. Observations suggest a slowdown of the zonal atmospheric overturning circulation above the tropical Pacific Ocean (the Walker circulation) over the twentieth century. Although this change has been attributed to a muted hydrological cycle forced by global warming, the effect of SST warming patterns has not been explored and quantified. Here we perform experiments using an atmospheric model, and find that SST warming patterns are the main cause of the weakened Walker circulation over the past six decades (1950-2009). The SST trend reconstructed from bucket-sampled SST and night-time marine surface air temperature features a reduced zonal gradient in the tropical Indo-Pacific Ocean, a change consistent with subsurface temperature observations. Model experiments with this trend pattern robustly simulate the observed changes, including the Walker circulation slowdown and the eastward shift of atmospheric convection from the Indonesian maritime continent to the central tropical Pacific. Our results cannot establish whether the observed changes are due to natural variability or anthropogenic global warming, but they do show that the observed slowdown in the Walker circulation is presumably driven by oceanic rather than atmospheric processes.

Summer thermal structure and anticyclonic circulation of Lake Erie

In most thermally stratified lakes, the summer thermocline has the shape of a “dome”, with a shallower depth offshore than nearshore. This configuration is accompanied by a lake‐wide cyclonic circulation. Lake‐wide observations of subsurface temperature in central Lake Erie revealed an atypical “depressed” or “bowl‐shaped” thermocline in late summer, with a deeper thermocline in the middle of the lake and a shallower thermocline nearshore. Currents measured in the central basin when the bowl‐shaped thermocline was observed were anticyclonic, forming a single basin‐wide gyre. It is suggested that the unusual bowl‐shaped thermocline is the result of Ekman pumping driven by anticyclonic vorticity in surface winds. The bowl‐shaped thermocline can lead to greater hypoxia in bottom waters and negative effects on biota by reducing the hypolimnetic volume.

Decadal Shifts of the Kuroshio Extension Jet: Application of Thin-Jet Theory*

Abstract Meridional shifts of the Kuroshio Extension (KE) jet on decadal time scales are examined using a 1960–2004 hindcast simulation of an eddy-resolving ocean general circulation model for the Earth Simulator (OFES). The leading mode of the simulated KE represents the meridional shifts of the jet on decadal time scales with the largest southward shift in the early 1980s associated with the climate regime shift in 1976/77, a result confirmed with subsurface temperature observations. The meridional shifts originate east of the date line and propagate westward along the mean jet axis, a trajectory inconsistent with the traditionally used linear long Rossby waves linearized in Cartesian coordinates, although the phase speed is comparable to that in the traditional framework. The zonal scale of these westward propagation signals is about 4000 km and much larger than their meridional scale. To understand the mechanism for the westward propagation of the KE jet shifts, the authors consider the limit of a thin jet. This dynamic framework describes the temporal evolution of the location of a sharp potential vorticity front under the assumption that variations along the jet are small compared to variations normal to the jet in natural coordinates and is well suited to the strong jet and potential vorticity gradients of the KE. For scaling appropriate to the decadal adjustments in the KE, the thin-jet model successfully reproduces the westward propagations and decadal shifts of the jet latitude simulated in OFES. These results give a physical basis for the prediction of decadal variability in the KE.

Decadal Shifts of the Kuroshio Extension Jet: Application of Thin-Jet Theory*

AbstractMeridional shifts of the Kuroshio Extension (KE) jet on decadal time scales are examined using a 1960–2004 hindcast simulation of an eddy-resolving ocean general circulation model for the Earth Simulator (OFES). The leading mode of the simulated KE represents the meridional shifts of the jet on decadal time scales with the largest southward shift in the early 1980s associated with the climate regime shift in 1976/77, a result confirmed with subsurface temperature observations. The meridional shifts originate east of the date line and propagate westward along the mean jet axis, a trajectory inconsistent with the traditionally used linear long Rossby waves linearized in Cartesian coordinates, although the phase speed is comparable to that in the traditional framework. The zonal scale of these westward propagation signals is about 4000 km and much larger than their meridional scale. To understand the mechanism for the westward propagation of the KE jet shifts, the authors consider the limit of a thin...

Impact of glider data assimilation on the Monterey Bay model

Abstract Glider observations were essential components of the observational program in the Autonomous Ocean Sampling Network (AOSN-II) experiment in the Monterey Bay area during summer of 2003. This paper is focused on the impact of the assimilation of glider temperature and salinity observations on the Navy Coastal Ocean Model (NCOM) predictions of surface and subsurface properties. The modeling system consists of an implementation of the NCOM model using a curvilinear, orthogonal grid with 1–4 km resolution, with finest resolution around the bay. The model receives open boundary conditions from a regional (9 km resolution) NCOM implementation for the California Current System, and surface fluxes from the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model at 3 km resolution. The data assimilation component of the system is a version of the Navy Coupled Ocean Data Assimilation (NCODA) system, which is used for assimilation of the glider data into the NCOM model of the Monterey Bay area. The NCODA is a fully 3D multivariate optimum interpolation system that produces simultaneous analyses of temperature, salinity, geopotential, and vector velocity. Assimilation of glider data improves the surface temperature at the mooring locations for the NCOM model hindcast and nowcasts, and for the short-range (1–1.5 days) forecasts. It is shown that it is critical to have accurate atmospheric forcing for more extended forecasts. Assimilation of glider data provided better agreement with independent observations (for example, with aircraft measured SSTs) of the model-predicted and observed spatial distributions of surface temperature and salinity. Mooring observations of subsurface temperature and salinity show sharp changes in the thermocline and halocline depths during transitions from upwelling to relaxation and vice versa. The non-assimilative run also shows these transitions in subsurface temperature; but they are not as well defined. For salinity, the non-assimilative run significantly differs from the observations. However, the glider data assimilating run is able to show comparable results with observations of thermocline as well as halocline depths during upwelling and relaxation events in the Monterey Bay area. It is also shown that during the relaxation of wind, the data assimilative run has higher value of subsurface velocity complex correlation with observations than the non-assimilative run.

Daily, seasonal, and annual relationships between air and subsurface temperatures

Inversions of borehole temperature profiles that reconstruct past ground surface temperature (GST) changes have been used to estimate historical changes in surface air temperature (SAT). Paleoclimatic interpretations of GST reconstructions are based on the assumption that GST and SAT changes are closely coupled over decades, centuries, and longer. This assumption has been the subject of some debate because of known differences between GST and SAT at timescales of hours, days, seasons, and years. We investigate GST and SAT relationships on daily, seasonal, and annual timescales to identify and characterize the principal meteorological changes that lead to short‐term differences between GST and SAT and consider the effects of those differences on coupling between the two temperatures over much longer time periods. We use observational SAT and subsurface data from Fargo, North Dakota; Prague, Czech Republic; Cape Henlopen State Park, Delaware; and Cape Hatteras National Seashore, North Carolina. These records comprise intradaily observations that span parts of one or two decades. We compare subsurface temperature observations to calculations from a conductive subsurface model driven with daily SAT as the surface boundary condition and show that daily differences exist between observed and modeled subsurface temperatures. We also analyze year‐to‐year spectral decompositions of daily SAT and subsurface temperature time series and show that dissimilarities between mean annual GST and SAT are attributable to differences in annual amplitudes of the two temperature signals. The seasonal partitioning of these amplitude differences varies from year to year and from site to site, responding to variable evapotranspiration and cryogenic effects. Variable year‐to‐year differences between mean annual GST and SAT are closely estimated using results from a multivariate regression model that associates the partial influences of seasonal meteorological conditions with the attenuation of annual GST amplitudes.

Ensembles of global ocean analyses for seasonal climate prediction: impact of temperature assimilation

Two sets of ensembles of ocean initial conditions for seasonal climate prediction have been constructed following a strategy that preserves the dynamical balance of the ocean. One set has been constructed by perturbing the wind stress and sea surface temperature forcing of an ocean model. The other set is constructed by assimilating perturbed in situ temperature data using a fully multivariate three-dimensional variational system, in addition to using the perturbed forcing. Ensemble statistics are computed for the period 1990–1999.The ensemble mean temperature has a significant subsurface cold bias when no data are assimilated, indicating that some part of the DEMETER hindcast systematic error may be explained by the way the ensembles are generated. Constraining the temperature through data assimilation contributes to a reduction in this subsurface bias.The dispersion of the initial conditions is supposed to sample the uncertainty associated with the ocean initial state estimate. Therefore, a smaller spread in the assimilation case than in the forced-only case is consistent with the idea that ocean uncertainty has been reduced by constraining the ocean state through data assimilation. However, comparing ensemble spread and innovation statistics suggests that ocean uncertainty may be underestimated by the ensemble method in the assimilated case. It is also shown that wind stress perturbations mainly control the spread amplitude in the non-assimilated case, but that perturbed subsurface temperature observations have a stronger relative impact in the assimilation case.

Ocean Response and Feedback to the SST Dipole in the Tropical Atlantic*

Abstract The equatorial SST dipole represents a mode of climate variability in the tropical Atlantic Ocean that is closely tied to cross-equatorial flow in the atmosphere, from the cold to the warm hemisphere. It has been suggested that this mode is sustained by a positive feedback of the tropical winds on the cross-equatorial SST gradient. The role, if any, of the tropical ocean is the focus of this investigation, which shows that at the latitudes of the SST signal (centered on 10°N/S) there is a weak positive feedback suggested in data from the last half century, that the cross-equatorial wind stress is closely coupled to this SST gradient on monthly time scales with no discernable lag, and that the period from January to June is the most active period for coupling. Northward (southward) anomalies of cross-equatorial wind stress are associated with a substantial negative (positive) wind stress curl. This wind system can thus drive a cross-equatorial Sverdrup transport in the ocean from the warm to the cold side of the equator (opposite the winds) with a temporal lag of only a few months. The oceanic observations of subsurface temperature and a numerical model hindcast also indicate a clear relationship between this mode of wind-driven variability and changes in the zonal transport of the North Equatorial Countercurrent. It is estimated that the time-dependent oceanic flow is capable of providing a significant contribution to the damping of the SST dipole but that external forcing is essential to sustaining the coupled variability.

Historical Ocean Subsurface Temperature Analysis with Error Estimates

Abstract An objective analysis of monthly ocean subsurface temperatures from 1950 to 1998 is carried out. The analysis scheme and the results with estimated analysis errors are presented. The analysis domain is global with a horizontal grid of 1° × 1° and 14 vertical levels in the upper 500 m. Subsurface temperature observations used in the objective analysis are archived by the National Ocean Data Center of the National Oceanic and Atmospheric Administration, together with those collected through the global telecommunication system and domestic communication lines in Japan. All the observations are preprocessed by quality control and data selection procedures developed in this study. Together with these observations, three-dimensional fields of the upper-ocean temperature are optimally estimated using a variational technique. To ensure smooth and continuous vertical temperature profiles, a constraint term is introduced to the cost function that is minimized in the analysis. In addition, the analysis sche...

Toward the Use of Altimetry for Operational Seasonal Forecasting

The TOPEX/Poseidon and ERS-1/2 satellites have now been observing sea level anomalies for a continuous time span of more than 6 yr. These sea level observations are first compared with tide gauge data and then assimilated into an ocean model that is used to initialize coupled ocean–atmosphere forecasts with a lead time of 6 months. Ocean analyses in which altimeter data are assimilated are compared with those from a no-assimilation experiment and with analyses in which subsurface temperature observations are assimilated. Analyses with altimeter data show variations of upper-ocean heat content similar to analyses using subsurface observations, whereas the ocean model has large errors when no data are assimilated. However, obtaining good results from the assimilation of altimeter data is not straightforward: it is essential to add a good mean sea level to the observed anomalies, to filter the sea level observations appropriately, to start the analyses from realistic initial temperature and salinity fields, and to assign appropriate weights for the analyzed increments. To assess the impact of altimeter data assimilation on the coupled system, ensemble hindcasts are initialized from ocean analyses in which either no data, subsurface temperatures, or sea level observations were assimilated. For each kind of ocean analysis, a five-member ensemble is started every 3 months from January 1993 to October 1997, adding up to 100 forecasts for each type. The predicted SST anomalies for the equatorial Pacific are intercompared between the experiments and against observations. The predicted anomalies are on average closer to observed values when forecasts are initialized from the ocean analysis using altimeter data than when initialized from the no-assimilation ocean analysis, and forecast errors appear to be only slightly larger than for forecasts initialized from ocean analyses using subsurface temperatures. However, even based on 100 coupled forecasts, the distinction between the two experiments that benefit from data assimilation is barely statistically significant. The verification should still be considered preliminary, because the period covered by the forecasts is only 5 yr, which is too short properly to sample ENSO variability. It is, nonetheless, encouraging that altimeter assimilation can improve the forecast skill to a level comparable to that obtained from using Tropical Ocean Atmosphere–expendable bathythermograph data.

Impact of Sea Level Assimilation on Salinity Variability in the Western Equatorial Pacific

Abstract In the primitive equation model for the tropical Pacific at the National Centers for Environmental Prediction, subsurface temperature observations are assimilated. The addition of TOPEX/Poseidon sea level observations to the NCEP assimilation scheme has resulted in large differences in sea level during 1996. These differences are suggested to be related to salinity variability. A bivariate assimilation scheme is presented that corrects both temperature and salinity. The method is tested with synthetic data in an identical triplets experiment, in which a westerly wind burst is simulated. In this experiment, the correction of salinity improves the density simulation and attenuates errors in salinity. A four-year assimilation experiment with real data is performed to test the system’s performance for 1993–96. In this experiment, the assimilation of TOPEX/Poseidon observations improves dynamic height simulation without degrading the temperature field. This application of altimetry improves the mean s...

Assimilation of TOPEX/Poseidon data into a seasonal forecast system

This paper describes first steps towards the quasi-operational assimilation of sea level anomalies from the TOPEX/POSEIDON and ERS1/2 missions into a global ocean model that is used to initialize a coupled oceanatmosphere seasonal forecast system. We estimate the impact that assimilation of sea level might have on the ocean analysis compared to the assimilation of subsurface temperature observations. As a first step satellite-observed sea level anomalies are compared with simulated sea level anomalies from model experiments. To assess the quality of the ocean analysis and the altimeter data further, model results and satellite data are compared to independent sea level observations from tide gauges. Model results are from three experiments: no assimilation, assimilation of subsurface temperature data, and assimilation of sea level data, respectively. The comparison is focused on the equatorial Pacific where subsurface temperatures are frequently sampled and impact of subsurface oceanic conditions on forecast skill is assumed to be large . It is shown that altimeter data assimilation can match subsurface temperature assimilation in this area.

The Annual Cycle in the Tropical Pacific Ocean Based on Assimilated Ocean Data from 1983 to 1992

An analysis of the tropical Pacific Ocean from January 1983 to December 1992 is used to describe the annual cycle, with the main focus on subsurface temperature variations. Some analysis of ocean-current variations are also considered. Monthly mean fields are generated by assimilation of surface and subsurface temperature observations from ships and buoys. Comparisons with observations show that the analysis reasonably describes large-scale ocean thermal variations. Ocean currents are not assimilated and do not compare as well with observations. However, the ocean-current variations in the analysis are qualitatively similar to the known variations given by others. The authors use harmonic analysis to separate the mean annual cycle and estimate its contribution to total variance. The analysis shows that in most regions the annual cycle of subsurface thermal variations is larger than surface variations and that these variations are associated with changes in the depth of the thermocline. The annual cycle accounts for most of the total surface variance poleward of about 10{degrees} latitude but accounts for much less surface and subsurface total variance near the equator. Large subsurface annual cycles occur near 10{degrees}N associated with shifts of the intertropical convergence zone and along the equator associated with the annual cyclemore » of equatorial wind stress. The hemispherically asymmetric depths of the 20{degrees}C isotherms indicate that the large Southern Hemisphere warm pool, which extends to near the equator, may play an important role in thermal variations on the equator. 51 refs., 18 figs., 1 tab.« less

Temperature fluctuation in muddy intertidal sediments, Forth Estuary, Scotland

Temperatures in muddy intertidal sediments exhibit rapid changes which occur principally during tidal inundation. Observations of sub-surface temperature were made from an instrument tower in the Forth Estuary, Scotland. Observed rates of temperature change were compared with theoretical rates which would result from molecular diffusion of heat through the mud. The discrepancy between observation and theory was likely to be due to rapid non-diffusive heat transfers resulting from the movement of water through non-capillary pore spaces created by faunal activity.