A practical indicator for surface ocean heat and freshwater buoyancy fluxes and its application to the NCEP reanalysis data

The buoyancy flux at the air/sea interface plays a key role in water mass transformation and mixing as it modifies surface water density and in turn drives overturning and enhances stratification. It is the interplay of these two independent heat and freshwater buoyancy flux components that is of central importance when analysing mechanisms of the ocean/atmosphere interaction. Here, a diagnostic quantity (ΘB) is presented that allows to capture the relative contribution of both components on the buoyancy flux in one single quantity. Using NCEP reanalysis of heat and freshwater fluxes (1948–2009) demonstrates that ΘB is a convenient tool to analyse both the temporal and spatial variability of their corresponding buoyancy fluxes. For the global ocean the areal extent of buoyancy gain and loss regions changed by 10%, with the largest extent of buoyancy gain during the 1970–1990 period. In the subpolar North Atlantic, and likewise in the South Pacific, decadal variability in freshwater flux is pronounced and, for the latter region, takes control over the total buoyancy flux since the 1980s. Some of the areal extent time series show a significant correlation with large-scale climate indices

Historical greenhouse gas concentrations for climate modelling (CMIP6)

Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at https://esgfnode.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality)

Ocean mixedlayer depth: A subsurface proxy for ocean-atmosphere variability

A new criterion, based on the shallowest extreme curvature of near surface layer density or temperature profiles, is established for demarking the mixed layer depth, h mix. Using historical global hydrographic profile data, including conductivity-temperature-depth and expendable bathythermograph data obtained during World Ocean Circulation Experiment, its seasonal variability and monthly to interannual anomalies are computed. Unlike the more commonly used Δ criterion, the new criterion is able to deal with both different vertical resolutions of the data set and a large variety of observed stratification profiles. For about two thirds of the profiles our algorithm produces an h mix/c that is more reliable than the one of the Δ criterion. The uncertainty for h mix/c is ±5 m for high- (<5 m) and ±8 m for low- (<20 m) resolution profiles. A quality index, QImix, which compares the variance of a profile above h mix to the variance to a depth of 1.5 × h mix, shows that for the 70% of the profile data for which a clearly recognizable well-mixed zone exists near the surface, our criterion identifies the depth of the well-mixed zone in all cases. The standard deviation of anomalous monthly h mix/c is typically 20–70% of the long-term mean h mix/c . In the tropical Pacific the monthly mean anomalies of h mix/c are not well correlated with anomalies of sea surface temperature, which indicate that a variety of turbulent processes, other than surface heat fluxes, are important in the upper ocean there. Comparisons between observed h mix/c and Massachusetts Institute of Techonology/ocean general circulation model/Estimating the Circulation and Climate of the Ocean model simulated mixed layer depth indicate that the KPP algorithm captures in general a 30% smaller mixed layer depth than observed

Regional Patterns of Sea Level Change Related to Interannual Variability and Multidecadal Trends in the Atlantic Meridional Overturning Circulation

Some studies of ocean climate model experiments suggest that regional changes in dynamic sea level could provide a valuable indicator of trends in the strength of the Atlantic meridional overturning circulation (MOC). This paper describes the use of a sequence of global ocean–ice model experiments to show that the diagnosed patterns of sea surface height (SSH) anomalies associated with changes in the MOC in the North Atlantic (NA) depend critically on the time scales of interest. Model hindcast simulations for 1958–2004 reproduce the observed pattern of SSH variability with extrema occurring along the Gulf Stream (GS) and in the subpolar gyre (SPG), but they also show that the pattern is primarily related to the wind-driven variability of MOC and gyre circulation on interannual time scales; it is reflected also in the leading EOF of SSH variability over the NA Ocean, as described in previous studies. The pattern, however, is not useful as a “fingerprint” of longer-term changes in the MOC: as shown with a companion experiment, a multidecadal, gradual decline in the MOC [of 5 Sv (1 Sv ≡ 106 m3 s−1) over 5 decades] induces a much broader, basin-scale SSH rise over the mid-to-high-latitude NA, with amplitudes of 20 cm. The detectability of such a trend is low along the GS since low-frequency SSH changes are effectively masked here by strong variability on shorter time scales. More favorable signal-to-noise ratios are found in the SPG and the eastern NA, where a MOC trend of 0.1 Sv yr−1 would leave a significant imprint in SSH already after about 20 years

Winter mixed layer development in the central Irminger Sea : the effect of strong, intermittent wind events

Author Posting. © American Meteorological Society, 2008. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 38 (2008): 541-565, doi:10.1175/2007JPO3678.1.The impact of the Greenland tip jet on the wintertime mixed layer of the southwest Irminger Sea is investigated using in situ moored profiler data and a variety of atmospheric datasets. The mixed layer was observed to reach 400 m in the spring of 2003 and 300 m in the spring of 2004. Both of these winters were mild and characterized by a low North Atlantic Oscillation (NAO) index. A typical tip jet event is associated with a low pressure system that is advected by upper-level steering currents into the region east of Cape Farewell and interacts with the high topography of southern Greenland. Heat flux time series for the mooring site were constructed that include the enhancing influence of the tip jet events. This was used to force a one-dimensional mixed layer model, which was able to reproduce the observed envelope of mixed layer deepening in both winters. The deeper mixed layer of the first winter was largely due to a higher number of robust tip jet events, which in turn was caused by the steering currents focusing more storms adjacent to southern Greenland. Application of the mixed layer model to the winter of 1994–95, a period characterized by a high-NAO index, resulted in convection exceeding 1700 m. This prediction is consistent with hydrographic data collected in summer 1995, supporting the notion that deep convection can occur in the Irminger Sea during strong winters.KV and RP were supported by National Science Foundation Grant OCE-0450658. GWKM was supported by the Canadian Foundation for Climate and Atmospheric Sciences. MHR was supported by the Nordic Council of Ministers (West-Nordic Ocean Climate)

Uncertainties in steric sea level change estimation during the satellite altimeter era: concepts and practices

This article presents a review of current practice in estimating steric sea level change, focussed on the treatment of uncertainty. Steric sea level change is the contribution to the change in sea level arising from the dependence of density on temperature and salinity. It is a significant component of sea level rise and a reflection of changing ocean heat content. However tracking these steric changes remains still a significant challenge for the scientific community. We review the importance of understanding the uncertainty in estimates of steric sea level change. Relevant concepts of uncertainty are discussed and illustrated with the example of observational uncertainty propagation from a single profile of temperature and salinity measurements to steric height. We summarise and discuss the recent literature on methodologies and techniques used to estimate steric sea level in the context of the treatment of uncertainty. Our conclusions are that progress in quantifying steric sea level uncertainty will benefit from: greater clarity and transparency in published discussions of uncertainty, including exploitation of international standards for quantifying and expressing uncertainty in measurement; and the development of community ‘recipes’ for quantifying the error covariances in observations and from sparse sampling, and for estimating and propagating uncertainty across spatio-temporal scales

Complementing thermosteric sea level rise estimates

Thermal expansion of seawater has been one of the most important contributors to global sea level rise (SLR) over the past 100 years. Yet, observational estimates of this volumetric response of the world's oceans to temperature changes are sparse and mostly limited to the ocean's upper 700 m. Furthermore, only a part of the available climate model data is sufficiently diagnosed to complete our quantitative understanding of thermosteric SLR (thSLR). Here, we extend the available set of thSLR diagnostics from the Coupled Model Intercomparison Project Phase 5 (CMIP5), analyze those model results in order to complement upper-ocean observations and enable the development of surrogate techniques to project thSLR using vertical temperature profile and ocean heat uptake time series. Specifically, based on CMIP5 temperature and salinity data, we provide a compilation of thermal expansion time series that comprise 30 % more simulations than currently published within CMIP5. We find that 21st century thSLR estimates derived solely based on observational estimates from the upper 700 m (2000 m) would have to be multiplied by a factor of 1.39 (1.17) with 90 % uncertainty ranges of 1.24 to 1.58 (1.05 to 1.31) in order to account for thSLR contributions from deeper levels. Half (50 %) of the multi-model total expansion originates from depths below 490 ± 90 m, with the range indicating scenario-to-scenario variations. To support the development of surrogate methods to project thermal expansion, we calibrate two simplified parameterizations against CMIP5 estimates of thSLR: one parameterization is suitable for scenarios where hemispheric ocean temperature profiles are available, the other, where only the total ocean heat uptake is known (goodness of fit: ±5 and ±9 %, respectively)

Complementing thermosteric sea level rise estimates

Thermal expansion of seawater has been one of the most important contributors to global sea level rise (SLR) over the past 100 years. Yet, observational estimates of this volumetric response of the world's oceans to temperature changes are sparse and mostly limited to the ocean's upper 700 m. Furthermore, only a part of the available climate model data is sufficiently diagnosed to complete our quantitative understanding of thermosteric SLR (thSLR). Here, we extend the available set of thSLR diagnostics from the Coupled Model Intercomparison Project Phase 5 (CMIP5), analyze those model results in order to complement upper-ocean observations and enable the development of surrogate techniques to project thSLR using vertical temperature profile and ocean heat uptake time series. Specifically, based on CMIP5 temperature and salinity data, we provide a compilation of thermal expansion time series that comprise 30 % more simulations than currently published within CMIP5. We find that 21st century thSLR estimates derived solely based on observational estimates from the upper 700 m (2000 m) would have to be multiplied by a factor of 1.39 (1.17) with 90 % uncertainty ranges of 1.24 to 1.58 (1.05 to 1.31) in order to account for thSLR contributions from deeper levels. Half (50 %) of the multi-model total expansion originates from depths below 490 ± 90 m, with the range indicating scenario-to-scenario variations. To support the development of surrogate methods to project thermal expansion, we calibrate two simplified parameterizations against CMIP5 estimates of thSLR: one parameterization is suitable for scenarios where hemispheric ocean temperature profiles are available, the other, where only the total ocean heat uptake is known (goodness of fit: ±5 and ±9 %, respectively)

Complementing thermosteric sea level rise estimates

Thermal expansion of seawater has been one of the most important contributors to global sea level rise (SLR) over the past 100 years. Yet, observational estimates of this volumetric response of the world's oceans to temperature changes are sparse and mostly limited to the ocean's upper 700 m. Furthermore, only a part of the available climate model data is sufficiently diagnosed to complete our quantitative understanding of thermosteric SLR (thSLR). Here, we extend the available set of thSLR diagnostics from the Coupled Model Intercomparison Project Phase 5 (CMIP5), analyze those model results in order to complement upper-ocean observations and enable the development of surrogate techniques to project thSLR using vertical temperature profile and ocean heat uptake time series. Specifically, based on CMIP5 temperature and salinity data, we provide a compilation of thermal expansion time series that comprise 30 % more simulations than currently published within CMIP5. We find that 21st century thSLR estimates derived solely based on observational estimates from the upper 700 m (2000 m) would have to be multiplied by a factor of 1.39 (1.17) with 90 % uncertainty ranges of 1.24 to 1.58 (1.05 to 1.31) in order to account for thSLR contributions from deeper levels. Half (50 %) of the multi-model total expansion originates from depths below 490 ± 90 m, with the range indicating scenario-to-scenario variations. To support the development of surrogate methods to project thermal expansion, we calibrate two simplified parameterizations against CMIP5 estimates of thSLR: one parameterization is suitable for scenarios where hemispheric ocean temperature profiles are available, the other, where only the total ocean heat uptake is known (goodness of fit: ±5 and ±9 %, respectively)