A cross-calibration of chlorine isotopic measurements and suitability of seawater as the international reference material

A collection of 24 seawaters from various worldwide locations and differing depth was culled to measure their chlorine isotopic composition (delta(37)Cl). These samples cover all the oceans and large seas: Atlantic, Pacific, Indian and Antarctic oceans, Mediterranean and Red seas. This collection includes nine seawaters from three depth profiles down to 4560 mbsl. The standard deviation (2sigma) of the delta(37)Cl of this collection is +/-0.08 parts per thousand, which is in fact as large as our precision of measurement ( +/- 0.10 parts per thousand). Thus, within error, oceanic waters seem to be an homogeneous reservoir. According to our results, any seawater could be representative of Standard Mean Ocean Chloride (SMOC) and could be used as a reference standard. An extended international cross-calibration over a large range of delta(37)Cl has been completed. For this purpose, geological fluid samples of various chemical compositions and a manufactured CH3Cl gas sample, with delta(37)Cl from about -6 parts per thousand to +6 parts per thousand have been compared. Data were collected by gas source isotope ratio mass spectrometry (IRMS) at the Paris, Reading and Utrecht laboratories and by thermal ionization mass spectrometry (TIMS) at the Leeds laboratory. Comparison of IRMS values over the range -5.3 parts per thousand to +1.4 parts per thousand plots on the Y=X line, showing a very good agreement between the three laboratories. On 11 samples, the trend line between Paris and Reading Universities is: delta(37)Cl(Reading)= (1.007 +/- 0.009)delta(37)Cl(Paris) - (0.040 +/- 0.025), with a correlation coefficient: R-2 = 0.999. TIMS values from Leeds University have been compared to IRMS values from Paris University over the range -3.0 parts per thousand to +6.0 parts per thousand. On six samples, the agreement between these two laboratories, using different techniques is good: delta(37)Cl(Leeds)=(1.052 +/- 0.038)delta(37)Cl(Paris) + (0.058 +/- 0.099), with a correlation coefficient: R-2 = 0.995. The present study completes a previous cross-calibration between the Leeds and Reading laboratories to compare TIMS and IRMS results (Anal. Chem. 72 (2000) 2261). Both studies allow a comparison of IRMS and TIMS techniques between delta(37)Cl values from -4.4 parts per thousand to +6.0 parts per thousand and show a good agreement: delta(37)Cl(TIMS)=(1.039 +/- 0.023)delta(37)Cl(IRMS)+(0.059 +/- 0.056), with a correlation coefficient: R-2 = 0.996. Our study shows that, for fluid samples, if chlorine isotopic compositions are near 0 parts per thousand, their measurements either by IRMS or TIMS will give comparable results within less than +/- 0.10 parts per thousand, while for delta(37)Cl values as far as 10 parts per thousand (either positive or negative) from SMOC, both techniques will agree within less than +/- 0.30 parts per thousand. (C) 2004 Elsevier B.V. All rights reserved.

Very large inverse problems in atmosphere and ocean modelling

For the very large nonlinear dynamical systems that arise in a wide range of physical, biological and environmental problems, the data needed to initialize a numerical forecasting model are seldom available. To generate accurate estimates of the expected states of the system, both current and future, the technique of ‘data assimilation’ is used to combine the numerical model predictions with observations of the system measured over time. Assimilation of data is an inverse problem that for very large-scale systems is generally ill-posed. In four-dimensional variational assimilation schemes, the dynamical model equations provide constraints that act to spread information into data sparse regions, enabling the state of the system to be reconstructed accurately. The mechanism for this is not well understood. Singular value decomposition techniques are applied here to the observability matrix of the system in order to analyse the critical features in this process. Simplified models are used to demonstrate how information is propagated from observed regions into unobserved areas. The impact of the size of the observational noise and the temporal position of the observations is examined. The best signal-to-noise ratio needed to extract the most information from the observations is estimated using Tikhonov regularization theory. Copyright © 2005 John Wiley & Sons, Ltd.

Sustained monitoring of the Southern Ocean at Drake Passage: past achievements and future priorities

Drake Passage is the narrowest constriction of the Antarctic Circumpolar Current (ACC) in the Southern Ocean, with implications for global ocean circulation and climate. We review the long-term sustained monitoring programmes that have been conducted at Drake Passage, dating back to the early part of the twentieth century. Attention is drawn to numerous breakthroughs that have been made from these programmes, including (a) the first determinations of the complex ACC structure and early quantifications of its transport; (b) realization that the ACC transport is remarkably steady over interannual and longer periods, and a growing understanding of the processes responsible for this; (c) recognition of the role of coupled climate modes in dictating the horizontal transport, and the role of anthropogenic processes in this; (d) understanding of mechanisms driving changes in both the upper and lower limbs of the Southern Ocean overturning circulation, and their impacts. It is argued that monitoring of this passage remains a high priority for oceanographic and climate research, but that strategic improvements could be made concerning how this is conducted. In particular, long-term programmes should concentrate on delivering quantifications of key variables of direct relevance to large-scale environmental issues: in this context, the time-varying overturning circulation is, if anything, even more compelling a target than the ACC flow. Further, there is a need for better international resource-sharing, and improved spatio-temporal coordination of the measurements. If achieved, the improvements in understanding of important climatic issues deriving from Drake Passage monitoring can be sustained into the future.

Estimation of systematic error in an equatorial ocean model using data assimilation

Assimilation of temperature observations into an ocean model near the equator often results in a dynamically unbalanced state with unrealistic overturning circulations. The way in which these circulations arise from systematic errors in the model or its forcing is discussed. A scheme is proposed, based on the theory of state augmentation, which uses the departures of the model state from the observations to update slowly evolving bias fields. Results are summarized from an experiment applying this bias correction scheme to an ocean general circulation model. They show that the method produces more balanced analyses and a better fit to the temperature observations.

Foreword: International Space Science Institute (ISSI) workshop on the Earth’s cryosphere and sea level change

Rising sea level is perhaps the most severe consequence of climate warming, as much of the world’s population and infrastructure is located near current sea level (Lemke et al. 2007). A major rise of a metre or more would cause serious problems. Such possibilities have been suggested by Hansen and Sato (2011) who pointed out that sea level was several metres higher than now during the Holsteinian and Eemian interglacials (about 250,000 and 120,000 years ago, respectively), even though the global temperature was then only slightly higher than it is nowadays. It is consequently of the utmost importance to determine whether such a sea level rise could occur and, if so, how fast it might happen. Sea level undergoes considerable changes due to natural processes such as the wind, ocean currents and tidal motions. On longer time scales, the sea level is influenced by steric effects (sea water expansion caused by temperature and salinity changes of the ocean) and by eustatic effects caused by changes in ocean mass. Changes in the Earth’s cryosphere, such as the retreat or expansion of glaciers and land ice areas, have been the dominant cause of sea level change during the Earth’s recent history. During the glacial cycles of the last million years, the sea level varied by a large amount, of the order of 100 m. If the Earth’s cryosphere were to disappear completely, the sea level would rise by some 65 m. The scientific papers in the present volume address the different aspects of the Earth’s cryosphere and how the different changes in the cryosphere affect sea level change. It represents the outcome of the first workshop held within the new ISSI Earth Science Programme. The workshop took place from 22 to 26 March, 2010, in Bern, Switzerland, with the objective of providing an in-depth insight into the future of mountain glaciers and the large land ice areas of Antarctica and Greenland, which are exposed to natural and anthropogenic climate influences, and their effects on sea level change. The participants of the workshop are experts in different fields including meteorology, climatology, oceanography, glaciology and geodesy; they use advanced space-based observational studies and state-of-the-art numerical modelling.

Thermobaric control of gravitational potential energy generation by diapycnal mixing in the deep ocean

Sources and sinks of gravitational potential energy (GPE) play a rate-limiting role in the large scale ocean circulation. A key source is turbulent diapycnal mixing, whereby irre- versible mixing across isoneutral surfaces is enhanced by turbulent straining of these surfaces. This has motivated international observational efforts to map diapycnal mixing in the global ocean. However, in order to accurately relate the GPE supplied to the large scale circulation by diapycnal mixing to the mixing energy source, it is first necessary to determine the ratio, ξ , of the GPE generation rate to the available potential energy dissipation rate associated with turbulent mixing. Here, the link between GPE and hydro- static pressure is used to derive the GPE budget for a com- pressible ocean with a nonlinear equation of state. The role of diapycnal mixing is isolated and from this a global cli- matological distribution of ξ is calculated. It is shown that, for a given source of mixing energy, typically three times as much GPE is generated if the mixing takes place in bottom waters rather than in the pycnocline. This is due to GPE destruction by cabbelling in the pycnocline, as opposed to thermobaric enhancement of GPE generation by diapycnal mixing in the deep ocean.

Comparison of the radiative properties and direct radiative effect of aerosols from a global aerosol model and remote sensing data over ocean

A global aerosol transport model (Oslo CTM2) with main aerosol components included is compared to five satellite retrievals of aerosol optical depth (AOD) and one data set of the satellite-derived radiative effect of aerosols. The model is driven with meteorological data for the period November 1996 to June 1997 which is the time period investigated in this study. The modelled AOD is within the range of the AOD from the various satellite retrievals over oceanic regions. The direct radiative effect of the aerosols as well as the atmospheric absorption by aerosols are in both cases found to be of the order of 20 Wm−2 in certain regions in both the satellite-derived and the modelled estimates as a mean over the period studied. Satellite and model data exhibit similar patterns of aerosol optical depth, radiative effect of aerosols, and atmospheric absorption of the aerosols. Recently published results show that global aerosol models have a tendency to underestimate the magnitude of the clear-sky direct radiative effect of aerosols over ocean compared to satellite-derived estimates. However, this is only to a small extent the case with the Oslo CTM2. The global mean direct radiative effect of aerosols over ocean is modelled with the Oslo CTM2 to be –5.5 Wm−2 and the atmospheric aerosol absorption 1.5 Wm−2.

Application of data assimilation to ocean and climate prediction

Ocean prediction systems are now able to analyse and predict temperature, salinity and velocity structures within the ocean by assimilating measurements of the ocean’s temperature and salinity into physically based ocean models. Data assimilation combines current estimates of state variables, such as temperature and salinity, from a computational model with measurements of the ocean and atmosphere in order to improve forecasts and reduce uncertainty in the forecast accuracy. Data assimilation generally works well with ocean models away from the equator but has been found to induce vigorous and unrealistic overturning circulations near the equator. A pressure correction method was developed at the University of Reading and the Met Office to control these circulations using ideas from control theory and an understanding of equatorial dynamics. The method has been used for the last 10 years in seasonal forecasting and ocean prediction systems at the Met Office and European Center for Medium-range Weather Forecasting (ECMWF). It has been an important element in recent re-analyses of the ocean heat uptake that mitigates climate change.