Subsurface Temperature Data Research Articles

How much does heat content of the western tropical Pacific Ocean modulate the South China Sea summer monsoon onset in the last four decades?

AbstractThe role of the western tropical Pacific Ocean heat content in the South China Sea summer monsoon (SCSSM) onset is investigated in the present paper, by using atmospheric data from NCEP and ocean subsurface temperature data from Japan Meteorology Agency. It is showed from the result that the heat content (HC) of the upper 400 m layer in the western tropical Pacific (WTP), especially in the region of (130°E–150°E, 0°N–14°N) in the last four decades, is a good predictive indicator for the SCSSM onset. Positive (negative) HC anomalies can induce a strong (weak) convection over the WTP, leading to stronger (weaker) Walker circulation and weaker (stronger) western North Pacific subtropical high (WNPSH) in the boreal spring. Consequently, the anomalous westerly (easterly) in the tropical Indian Ocean is favorable (unfavorable) for the airflow into the SCS and for an early (late) WNPSH retreat from the SCS and hence for an early (late) SCSSM onset. It is elucidated that the long‐term trend of SCSSM onset changes its sign around 1993/94 from decline to rise, which is responding and attributed to the WTP HC trend. During the period of 1971–1993, the WTP HC shows a significant decrease trend. In particular, a significant decline trend is observed in the HC difference between the WTP and western tropical Indian Ocean, which causes an easterly trend in the SCS and strengthened WNPSH trend, leading to a late onset trend of SCSSM. The situation is reverse after 1993/94.

The vertical variability of hyporheic fluxes inferred from riverbed temperature data

We present detailed profiles of vertical water flux from the surface to 1.2 m beneath the Haughton River in the tropical northeast of Australia. A 1-D numerical model is used to estimate vertical flux based on raw temperature time series observations from within downwelling, upwelling, neutral, and convergent sections of the hyporheic zone. A Monte Carlo analysis is used to derive error bounds for the fluxes based on temperature measurement error and uncertainty in effective thermal diffusivity. Vertical fluxes ranged from 5.7 m d−1 (downward) to −0.2 m d−1 (upward) with the lowest relative errors for values between 0.3 and 6 m d−1. Our 1-D approach provides a useful alternative to 1-D analytical and other solutions because it does not incorporate errors associated with simplified boundary conditions or assumptions of purely vertical flow, hydraulic parameter values, or hydraulic conditions. To validate the ability of this 1-D approach to represent the vertical fluxes of 2-D flow fields, we compare our model with two simple 2-D flow fields using a commercial numerical model. These comparisons showed that: (1) the 1-D vertical flux was equivalent to the mean vertical component of flux irrespective of a changing horizontal flux; and (2) the subsurface temperature data inherently has a “spatial footprint” when the vertical flux profiles vary spatially. Thus, the mean vertical flux within a 2-D flow field can be estimated accurately without requiring the flow to be purely vertical. The temperature-derived 1-D vertical flux represents the integrated vertical component of flux along the flow path intersecting the observation point.

An Ensemble Adjustment Kalman Filter for the CCSM4 Ocean Component

Abstract The authors report on the implementation and evaluation of a 48-member ensemble adjustment Kalman filter (EAKF) for the ocean component of the Community Climate System Model, version 4 (CCSM4). The ocean assimilation system described was developed to support the eventual generation of historical ocean-state estimates and ocean-initialized climate predictions with the CCSM4 and its next generation, the Community Earth System Model (CESM). In this initial configuration of the system, daily subsurface temperature and salinity data from the 2009 World Ocean Database are assimilated into the ocean model from 1 January 1998 to 31 December 2005. Each ensemble member of the ocean is forced by a member of an independently generated CCSM4 atmospheric EAKF analysis, making this a loosely coupled framework. Over most of the globe, the time-mean temperature and salinity fields are improved relative to an identically forced ocean model simulation without assimilation. This improvement is especially notable in strong frontal regions such as the western and eastern boundary currents. The assimilation system is most effective in the upper 1000 m of the ocean, where the vast majority of in situ observations are located. Because of the shortness of this experiment, ocean variability is not discussed. Challenges that arise from using an ocean model with strong regional biases, coarse resolution, and low internal variability to assimilate real observations are discussed, and areas of ongoing improvement for the assimilation system are outlined.

Six years of ground–air temperature tracking at Malence (Slovenia): thermal diffusivity from subsurface temperature data

To understand the processes which govern the downward propagation of the surface temperature signal and to quantify the relationship between ground and air temperatures, a borehole climate observatory was established at Malence (Slovenia). A substantial (climate?) warming has been observed; surface air temperature from 2003 to 2009 has been increasing by a rate of more than 0.5 K/year. Temperature difference between ground and air temperatures revealed a typical annual course; during the winter months the ground is warmer than the air, in the summer the ground gets slightly colder, the mean yearly offset value amounting to 1.6 K. Here we report on the thermal diffusivity distribution which was determined for a near-surface 10 m deep section using a number of six-year-long temperature–time data series. The series of daily averaged temperatures were processed by spectral analysis. Thermal diffusivity was calculated from the amplitude and phase angle of annual waves corresponding to different subsurface layers using conduction theory as well as the conduction–convection approach. Both methods lead to the generally similar results and revealed a definite heterogeneity of the subsurface medium. The results proved that the annual scale convective heat transfer did not contribute significantly to the temperature–time variations monitored in the uppermost 10 m depth interval.

Role of Western Pacific Oceanic variability in the onset of the Bay of Bengal summer monsoon

The influence of the tropical Indo-Pacific Ocean heat content on the onset of the Bay of Bengal summer monsoon (BOBSM) onset was investigated using atmospheric data from the NCEP and ocean subsurface temperature data from the Japan Metorology Agency (JMA). Results showed that the onset time of the BOBSM is highly related to the tropical Pacific upper ocean heat content (HC), especially in the key region of the western Pacific warm pool (WPWP), during the preceding winter and spring. When the HC anomalies in the WPWP are positive (negative), the onset of the BOBSM is usually early (late). Accompanied by the variation of the convection activity over the WPWP, mainly induced by the underlying ocean temperature anomalies, the Walker circulation becomes stronger or weaker. This enhances or weakens the westerly over the tropical Indian Ocean flowing into the BOB in the boreal spring, which is essential to BOBSM onset. The possible mechanism of influence of cyclonic/anti-cyclonic circulation over the northwestern tropical Pacific on BOBSM onset is also discussed.

Investigation of the geothermal state of sedimentary basins using oil industry thermal data: case study from Northern Alberta exhibiting the need to systematically remove biased data

Subsurface temperature data from industrial sources may contain significant biases that greatly reduce their overall quality. However, if these biases can be identified and removed, the data can provide a good preliminary source of information for further studies. In this paper, industrial thermal data from three sources: bottom hole temperatures, annual pool pressure tests and drill stem tests are evaluated to provide an updated view of the subsurface temperatures below the oil sand regions of Northern Alberta. The study highlights some of the potentially large systematic biases inherent in industrial temperature data which affect estimates of geothermal gradient and regional mapping of the geothermal field.

Decadal variability of the Arctic Ocean thermal structure

Long-term variability of heat content (HC) in the upper 1,000 m of the Arctic Ocean is investigated using surface and subsurface temperature and current data during 1958–2005 compiled by Simple Ocean Data Assimilation. Annual cycle of the Arctic Ocean HC is controlled primarily by the negative and positive excursions in net upper ocean heat flux, while the inter-annual variability is mainly associated with meridional thermal advection from the North Atlantic Ocean. Variability in HC is experienced as a basin-wide cooling/warming in association with the Arctic Oscillation on a decadal time scale. In the first three dominant modes of Empirical Orthogonal Function, the maximum amplitude of HC variability occurs in the Greenland–Norwegian Sea and Eurasian Basin. In general, HC showed increasing trend during 1958–2005 indicating continuous warming with regional variations in magnitude.

Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

Predicting Atlantic meridional overturning circulation (AMOC) variations using subsurface and surface fingerprints

Recent studies have suggested that the leading modes of North Atlantic subsurface temperature ( T sub ) and sea surface height (SSH) anomalies are induced by Atlantic meridional overturning circulation (AMOC) variations and can be used as fingerprints of AMOC variability. Based on these fingerprints of the AMOC in the GFDL CM2.1 coupled climate model, a linear statistical predictive model of observed fingerprints of AMOC variability is developed in this study. The statistical model predicts a weakening of AMOC strength in a few years after its peak around 2005. Here, we show that in the GFDL coupled climate model assimilated with observed subsurface temperature data, including recent Argo network data (2003–2008), the leading mode of the North Atlantic T sub anomalies is similar to that found with the objectively analyzed T sub data and highly correlated with the leading mode of altimetry SSH anomalies for the period 1993–2008. A statistical auto-regressive (AR) model is fit to the time-series of the leading mode of objectively analyzed detrended North Atlantic T sub anomalies (1955–2003) and is applied to assimilated T sub and altimetry SSH anomalies to make predictions. A similar statistical AR model, fit to the time-series of the leading mode of modeled T sub anomalies from the 1000-year GFDL CM2.1 control simulation, is applied to predict modeled T sub , SSH, and AMOC anomalies. The two AR models show comparable skills in predicting observed T sub and modeled T sub , SSH and AMOC variations.

Propagation of linear surface air temperature trends into the terrestrial subsurface

Previous studies have tested the long‐term coupling between air and terrestrial subsurface temperatures working under the assumption that linear trends in surface air temperature should be equal to those measured at depth within the subsurface. A one‐dimensional model of heat conduction is used to show that surface trends are attenuated as a function of depth within conductive media on time scales of decades to centuries, therefore invalidating the above assumption given practical observational constraints. The model is forced with synthetic linear temperature trends as the time‐varying upper boundary condition; synthetic trends are either noise free or include additions of Gaussian noise at the annual time scale. It is shown that over a 1000 year period, propagating surface trends are progressively damped with depth in both noise‐free and noise‐added scenarios. Over shorter intervals, the relationship between surface and subsurface trends is more variable and is strongly impacted by annual variability (i.e., noise). Using output from the FOR1 millennial simulation of the GKSS ECHO‐G General Circulation Model as a more realistic surface forcing function for the conductive model, it is again demonstrated that surface trends are damped as a function of depth within the subsurface. Observational air and subsurface temperature data collected over 100 years in Armagh, Ireland, and 29 years in Fargo, North Dakota, are also analyzed and shown to have subsurface temperature trends that are not equal to the surface trend. While these conductive effects are correctly accounted for in inversions of borehole temperature profiles in paleoclimatic studies, they have not been considered in studies seeking to evaluate the long‐term coupling between air and subsurface temperatures by comparing trends in their measured time series. The presented results suggest that these effects must be considered and that a demonstrated trend equivalency in air and subsurface temperatures is inconclusive regarding their long‐term tracking.

Long term sea level change and water mass balance in the South China Sea

Sea level anomalies observed by altimeter during the 1993–2006 period, thermosteric sea level anomalies estimated by using subsurface temperature data produced by Ishii and SODA reanalysis data, tide gauge records and HOAPS freshwater flux data were analyzed to investigate the long term sea level change and the water mass balance in the South China Sea. The altimeter-observed sea level showed a rising rate of (3.5±0.9) mm yr−1 during the period 1993–2006, but this figure was considered to have been highly distorted by the relatively short time interval and the large inter-decadal variability, which apparently exists in both the thermosteric sea level and the observed sea level. Long term thermosteric sea level from 1945 to 2004 gave a rising rate of 0.15±0.06 mm yr−1. Tide gauge data revealed this discrepancy and the regional distributions of the sea-level trends. Both the ‘real’ and the thermosteric sea level showed a good correspondence to ENSO: decreasing during El Nino years and increasing during La Nina years. Amplitude and phase differences between the ‘real’ sea level and the thermosteic sea level were substantially revealed on both seasonal and interannual time scales. As one of the possible factors, the freshwater flux might play an important role in balancing the water mass.

Coherent surface‐subsurface fingerprint of the Atlantic meridional overturning circulation

Satellite altimeter data shows a weakening of the North Atlantic subpolar gyre during the 1990s, which is thought as an indicator of a slowdown of the Atlantic meridional overturning circulation (AMOC). However, whether the recent slowing subpolar gyre is a decadal variation or a long‐term trend remains unclear. Here I show that altimeter data is highly correlated with instrumental subsurface ocean temperature data in the North Atlantic, and both show opposite signs between the subpolar gyre and the Gulf Stream path. Such a dipole pattern is a distinctive fingerprint of AMOC variability, as shown for the first time by a 1000‐year coupled ocean‐atmosphere model simulation. The results suggest that, contrary to previous interpretations, the recent slowdown of the subpolar gyre is a part of a multidecadal variation and suggests a strengthening of the AMOC. The ongoing satellite and subsurface temperature measurements could be used to monitor future AMOC variations sensitively.

Change in the Indonesian Throughflow with the climatic shift of 1976/77

A climate shift occurred in 1976 with Pacific equatorial temperatures experiencing a sharp rise and was first identified as a change in the background state of the El Niño Southern Oscillation. The associated weakening of easterly trade winds across the Pacific led to our hypothesis that the Indonesian Throughflow (ITF) had also weakened. The change in volume transport of ITF before and after December 1975 was estimated using all the available subsurface temperature data on the IX1 expendable bathythermograph (XBT) line between Australia and Indonesia. Sea surface temperature (SST) rose by 1–2°C, which could be due to increased air‐sea heat flux and/or a change in regional circulation. A subsurface cooling in the main thermocline was attributed to a weakening of the Pacific trade winds. The South Equatorial Current (SEC) diminished in size and weakened in strength. The net westward volume transport between Australia and Indonesia showed a decrease of ∼2.5 Sverdrups, or 23%.

Combined Effects of Urbanization and Global Warming on Subsurface Temperature in Four Asian Cities

Subsurface temperature profiles measured in boreholes can be analyzed to infer depths of thermal disturbance and associated surface warming due to combined global warming and urbanization (heat island effects). Asian cities are extremely vulnerable because of rapid increases in population. Average subsurface temperature profiles in four Asian cities (Tokyo, Osaka, Seoul, and Bangkok) were compared and analyzed to evaluate the effects of surface warming. The magnitude of surface warming is largest in Tokyo (2.8°C), followed by Seoul (2.5°C), Osaka (2.2°C), and Bangkok (1.8°C). Comparisons between analytical solutions and observations show that the mean depth of deviation from the regional geothermal gradient in each urban area may be one of the indicators of the history of urbanization in each city. The mean depth of deviation from the steady thermal gradient, which is approximately 140 m in Tokyo, 80 m in Osaka, and 50 m in Seoul and Bangkok, indicates the time from the start of the additional heat from urbanization. These results agree qualitatively with air temperature records in the cities during the last 100 yr. The heat island effect on subsurface temperature is an important global groundwater quality issue because it may alter the groundwater systems chemically and microbiologically. Measurement of subsurface temperature data provides important information for understanding the joint effects of urbanization and global warming on groundwater systems.

地下温度に関する研究の現状と水文学的知見の貢献

Subsurface thermal regime is affected not only by thermal conduction but also by advection owing to groundwater flow. The effect of thermal advection is especially large in shallow sedimentary layer with active groundwater flow. Subsurface temperature distributions in some basins and plains in Japan are affected by regional groundwater flow systems. Both field observation and simulation results in the study area show that thermal transport conducted by regional groundwater flow system, driven by topographic effect, distorts subsurface temperature distributions. Moreover, subsurface temperature distributions in the Yonezawa Basin and Nagaoka Plain show effect of groundwater pumping. Subsurface temperatures in shallow layers in these areas have seasonal change due to groundwater pumping for snow melting in winter season.In recent years, subsurface temperature data have been used for reconstruction of ground surface temperature (GST) history as well. The effects of temperature change at the ground surface in the past have conducted into subsurface and have been recorded as transient temperature perturbations onto the background thermal field. Many studies on GST history in North America and Europe are inferred from inversion of borehole temperature profiles in log data.On the other hand, direct utilization of low-temperature geothermal resources, such as geothermal heat pump system, is important from the viewpoint of reduction of CO2 that causes global warming. Such systems are gradually increasing in Japan. To evaluate the influence of direct utilization onto subsurface temperature, an areal simulation, which numerical model was cut out from regional 3D groundwater flow and heat transport model of the Sendai plains, was conducted.Subsurface temperature observed with comparative ease includes important clues to understand global environment problems and/or hints for development of new energy to preserve global environment.It is hoped that hydrological knowledge contributes to understand many problems in various studies with subsurface temperature.

Evaluation of The Existing State of Geothermal Exploration and Development in Nigeria

Relatively little expenditure for hydroelectricity and fossil fuels have had a restraining influence on levels of exploration and development for geothermal energy resources in Nigeria for the past several years. The focus of development has been in the areas of low temperature geothermal energy involving the exploration and assessment of hot spring resources primarily for recreational applications – although possibly for other direct uses depending on local infrastructure and access to appropriate energy markets. The geological structure of Nigeria influences geothermal exploration extent within each geological province. Sedimentary basins in Nigeria have been explored for hydrocarbons for several decades, thus the oil companies collected large subsurface temperature data basis. But not much is known about geothermal conditions within Nigerian Precambrian crystalline province. On the basis of BHT data from oil wells it has been found that geothermal gradient in Niger Delta ranges from 1.5 to 4.9°C/100m and in Anambra Basin (directly to the north) it can reach 5.7°C/100m. Exploration for geothermal energy in northern Nigeria based on shallow water wells (down to 600 m deep) was carried out over 20 years ago. The other aspect of geothermal exploration in Nigeria is investigating of the thermal springs and seepages, which occur mainly within sediments of the Middle and Upper Benue Trough. The water of the warmest springs in that area: Akiri and Ruwan Zafi have the temperature about 56°C and it suggests the occurrence of some geothermal anomalies. So far, there are probably only three (direct) geothermal energy utilisation sites in Nigeria. The Ikogosi warm spring (37°C) located in south-western part of the country, in Ekiti state, the Wikki warm spring (39°C) located in Bauchi (North-eastern) part of Nigeria and the Rafin Rewa spring (42°C) located in Plateau (North-central) state of Nigeria. Hence this paper reviews the current status of the geothermal industry (both high and low temperature) in Nigeria.

Estimating Transient Surface Heating using a Cellular Automaton Energy-transport Model

The use of subsurface temperature data to estimate an unknown transient surface-heating event is a classic, and practical, inverse problem in engineering. This paper describes a new inverse heat-transfer estimation procedure that is formulated using a cellular automaton model of energy transport into the medium. The quantitative heat-flux estimates generated by this new scheme appear to have accuracies comparable to conventional inverse procedures; consequently, this new method may prove a useful alternative and/or confirmational strategy in measurement situations where the data is noise-ridden or the heating event is sporadic.

Possible Ambiguities in Subsurface Temperature Logs: Consideration of Ground-water Flow and Ground Surface Temperature Change

Subsurface temperature regimes can commonly be influenced by both ground-water flow in the saturated zone and ground surface temperature change. Both phenomena are widespread and one or the other may be unnoticed and/or unanticipated in various temperature logs. As a consequence, it is often difficult to determine the relative impact of the two phenomena on the temperature-depth data at a site. A number of models for ground-water flow, ground surface temperature change, and a combination of the two processes, are fitted to two example temperature logs showing characteristic nonlinearity. Examples of the possible impact of one phenomenon on the parameters calculated for the other phenomenon demonstrate the potential interactive influence. The analysis can be used to estimate potential uncertainties in calculations of ground-water flow and ground surface temperature change from subsurface temperature data, and therefore how interpretations of ground-water flow and ground surface warming might be affected. From the analysis presented the relative importance of the two phenomena may be further considered at different locations.

Climate Variability over the Tropical Indian Ocean Sector in the NSIPP Seasonal Forecast System

Abstract Prospects for forecasting Indian dipole mode (IDM) events with lead times of a season or more are examined using the NASA Seasonal-to-Interannual Prediction Project (NSIPP) coupled-model forecast system. The mean climatology of the system over the sector is reasonable, as determined from an almost-century-long run without data assimilation. However, the system presents biases, for example, too cool sea surface temperatures (SSTs), too shallow thermocline, and too strong southeasterlies along the Sumatra–Java coast in the east, and too warm SSTs, too deep thermocline, and too weak extension of the southeast trades into the Findlater jet in the west. These suggest coupling between the ocean and atmosphere is stronger, and the SST–clouds–shortwave radiation negative feedback less effective, than observed in the east with the opposite holding true in the west. Also, the negative zonal gradient in SST in the eastern equatorial basin, in contrast with the positive observed, suggests that equatorial Kelvin and Rossby coupled modes may have a different character from observed. Biases identified in the seasonal cycle, which may affect the strength and timing of IDM events, include a delayed onset of the boreal summer monsoon in the west, and a prolonged boreal summer monsoon in the east. Eight major positive IDM events occur during the almost-century-long run over a range of El Niño–Southern Oscillation phases with a tendency to occur post–El Niño/pre–La Niña. Consistent with the identified air–sea interaction biases, the cold (warm) anomaly at the east (west) pole tends to be stronger (weaker) than observed. Also, the cold anomaly extends much farther westward and is more equatorially trapped than observed; its slow westward propagation and the structure of the associated fields is reminiscent of an unstable, coupled Rossby mode with SST governed by lateral advection due to the westward displacement of the convective anomaly from the heat source. Otherwise, the life cycle of the eight-event composite is similar in seasonal phase locking and mechanisms of evolution and decay to the canonical event. For the decade from 1993 to the present, there were major positive IDM events in 1994 and 1997/98. Monthly mean SST anomalies over the western pole are well hindcast by the ocean component of the NSIPP system forced by observed surface fluxes with SST damped to observed values, and in which subsurface temperature data available in real time are assimilated; these data are very sparse over the Indian Ocean. Over the eastern pole, the SST anomalies are well hindcast except for the 1997/98 event, when it is too cool. The ensemble mean hindcast of the zonal surface wind anomaly of the central basin by the atmosphere component of the NSIPP system forced by observed SST is too weak during both events. These hindcasts provide initial conditions for the coupled system forecasts. Forecast ensembles for the decade 1993 onward, generated by the coupled system, give monthly mean SST anomalies averaged over the east and west poles of the IDM in agreement with observations at lead times of three months. The cool anomaly at the eastern pole is slightly too large in 1997/98, and the onset of the warm anomaly in 1997 is delayed by a month or so; its peak and decay are correctly timed. At lead times of six months, there is a significant deterioration in the forecast at the eastern pole with either false positive or negative alarms generated annually in boreal fall; that at the western pole remains good. These results are very encouraging and suggest that major IDM events have the potential to be forecast a season or more in advance.

Interannual-to-decadal variability of the North Atlantic from an ocean data assimilation system

An ocean analysis, assimilating both surface and subsurface hydrographic temperature data into a global ocean model, has been produced for the period 1958–2000, and used to study the time and space variations of North Atlantic upper ocean heat content (HC). Observational evidence is presented for interannual-to-decadal variability of upper ocean thermal fluctuations in the North Atlantic related to the North Atlantic Oscillation (NAO) variability over the last 40 years. The assimilation scheme used in the ocean analysis is a univariate, variational optimum interpolation of temperature. The first guess is produced by an eddy permitting global ocean general circulation forced by atmospheric reanalysis from the National Center for Environmental Prediction (NCEP). The validation of the ocean analysis has been done through the comparison with objectively analyzed observations and independent data sets. The method is able to compensate for the model systematic error to reproduce a realistic vertical thermal structure of the region and to improve consistently the model estimation of the time variability of the upper ocean temperature. Empirical orthogonal function (EOF) analysis shows that an important mode of variability of the wintertime upper ocean climate over the North Atlantic during the period of study is characterized by a tripole pattern both for SST and upper ocean HC. A similar mode is found for summer HC anomalies but not for summer SST. Over the whole period, HC variations in the subtropics show a general warming trend while the tropical and north eastern part of the basin have an opposite cooling tendency. Superimposed on this linear trend, the HC variability explained by the first EOF both in winter and summer conditions reveals quasi-decadal oscillations correlated with changes in the NAO index. On the other hand, there is no evidence of correlation in time between the NAO index and the upper ocean HC averaged over the whole North Atlantic which exhibits a substantial and monotonic warming trend during the last two decades of the analysis period. The maximum correlation is found between the leading principal component of winter HC anomalies and NAO index at 1 year lag with NAO leading. For SST anomalies significant correlation is found only for winter conditions. In contrast, for HC anomalies high correlations are found also in the summer suggesting that the summer HC keeps a memory of winter conditions.