ORCID Profile
0000-0001-8541-3573
Current Organisations
University of California, San Diego
,
CSIRO
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Publisher: Australian Ocean Data Network
Date: 2022
DOI: 10.26198/5R16-XF23
Publisher: American Meteorological Society
Date: 16-06-2016
Abstract: Ocean warming accounts for the majority of the earth’s recent energy imbalance. Historic ocean heat content (OHC) changes are important for understanding changing climate. Calculations of OHC anomalies (OHCA) from in situ measurements provide estimates of these changes. Uncertainties in OHCA estimates arise from calculating global fields from temporally and spatially irregular data (mapping method), instrument bias corrections, and the definitions of a baseline climatology from which anomalies are calculated. To investigate sensitivity of OHCA estimates for the upper 700 m to these different factors, the same quality-controlled dataset is used by seven groups and comparisons are made. Two time periods (1970–2008 and 1993–2008) are examined. Uncertainty due to the mapping method is 16.5 ZJ for 1970–2008 and 17.1 ZJ for 1993–2008 (1 ZJ = 1 × 1021 J). Uncertainty due to instrument bias correction varied from 8.0 to 17.9 ZJ for 1970–2008 and from 10.9 to 22.4 ZJ for 1993–2008, depending on mapping method. Uncertainty due to baseline mean varied from 3.5 to 14.5 ZJ for 1970–2008 and from 2.7 to 9.8 ZJ for 1993–2008, depending on mapping method and offsets. On average mapping method is the largest source of uncertainty. The linear trend varied from 1.3 to 5.0 ZJ yr−1 (0.08–0.31 W m−2) for 1970–2008 and from 1.5 to 9.4 ZJ yr−1 (0.09–0.58 W m−2) for 1993–2008, depending on method, instrument bias correction, and baseline mean. Despite these complications, a statistically robust upper-ocean warming was found in all cases for the full time period.
Publisher: Frontiers Media SA
Date: 16-02-2023
DOI: 10.3389/FMARS.2022.1075510
Abstract: Millions of in situ ocean temperature profiles have been collected historically using various instrument types with varying sensor accuracy and then assembled into global databases. These are essential to our current understanding of the changing state of the oceans, sea level, Earth’s climate, marine ecosystems and fisheries, and for constraining model projections of future change that underpin mitigation and adaptation solutions. Profiles distributed shortly after collection are also widely used in operational applications such as real-time monitoring and forecasting of the ocean state and weather prediction. Before use in scientific or societal service applications, quality control (QC) procedures need to be applied to flag and ultimately remove erroneous data. Automatic QC (AQC) checks are vital to the timeliness of operational applications and for reducing the volume of dubious data which later require QC processing by a human for delayed mode applications. Despite the large suite of evolving AQC checks developed by institutions worldwide, the most effective set of AQC checks was not known. We have developed a framework to assess the performance of AQC checks, under the auspices of the International Quality Controlled Ocean Database (IQuOD) project. The IQuOD-AQC framework is an open-source collaborative software infrastructure built in Python (available from github.com/IQuOD ). Sixty AQC checks have been implemented in this framework. Their performance was benchmarked against three reference datasets which contained a spectrum of instrument types and error modes flagged in their profiles. One of these (a subset of the Quality-controlled Ocean Temperature Archive (QuOTA) dataset that had been manually inspected for quality issues by its creators) was also used to identify optimal sets of AQC checks. Results suggest that the AQC checks are effective for most historical data, but less so in the case of data from Mechanical Bathythermographs (MBTs), and much less effective for Argo data. The optimal AQC sets will be applied to generate quality flags for the next release of the IQuOD dataset. This will further elevate the quality and historical value of millions of temperature profile data which have already been improved by IQuOD intelligent metadata and observational uncertainty information ( 0.7289/v51r6nsf ).
Publisher: Frontiers Media SA
Date: 13-09-2022
DOI: 10.3389/FMARS.2022.991760
Abstract: Since the 1970s, eXpendable BathyThermographs (XBTs) have provided the simplest and most cost-efficient solution for rapid s ling of temperature vs. depth profiles of the upper part of the ocean along ship transects. This manual, compiled by the Ship of Opportunity Program Implementation Panel (SOOPIP) a subgroup of the Global Ocean Observing System (GOOS) Observations Coordination Group (OCG) Ship Observations Team (SOT) together with members of the XBT Science Team, aims to improve the quality assurance of XBT data by establishing best practices for field measurements and promoting their adoption by the global operational and scientific community. The measurement system components include commercially available expendable temperature probes, the launcher, the data acquisition (DAQ) hardware, a Global Navigation Satellite System (GNSS) receiver, an optional satellite transmitter, and a computer with software controls. The measurement platform can be any sea-going vessel with available space for the equipment and operator, and capable of oceanic voyages across the regions of interest. Adoption of a standard methodology in the installation and deployment of the measurement system will lead to data quality improvements with subsequent impact on the computation and understanding of changes in the near surface ocean properties (e.g., heat content), ocean circulation dynamics, and their relationship to climate variability.
Publisher: American Meteorological Society
Date: 03-2018
DOI: 10.1175/JTECH-D-17-0129.1
Abstract: Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty in estimates of historical ocean heat content variability and change. One of the challenges in the development of XBT bias corrections is the lack of metadata in ocean profile databases. Approximately 50% of XBT profiles in the World Ocean database (WOD) have no information about manufacturer or probe type. Building on previous research efforts, this paper presents a deterministic algorithm for assigning missing XBT manufacturer and probe type for in idual temperature profiles based on 1) the reporting country, 2) the maximum reported depth, and 3) the record date. The criteria used are based on bulk analysis of known XBT profiles in the WOD for the period 1966–2015. A basic skill assessment demonstrates a 77% success rate at correctly assigning manufacturer and probe type for profiles where this information is available. The skill rate is lowest during the early 1990s, which is also a period when metadata information is particularly poor. The results suggest that substantive improvements could be made through further data analysis and that future algorithms may benefit from including a larger number of predictor variables.
Publisher: American Meteorological Society
Date: 02-2023
Abstract: The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean’s role in Earth’s climate system. In idual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements.
Publisher: American Meteorological Society
Date: 06-2013
DOI: 10.1175/JTECH-D-12-00127.1
Abstract: Because they make up 56% of ocean temperature profile data between 1967 and 2001, quantifying the biases in expendable bathythermograph (XBT) data is fundamental to understanding the evolution of the planetary energy and sea level budgets over recent decades. The nature and time history of these biases remain in dispute and dominate differences in analyses of the history of ocean warming. A database of over 4100 side-by-side deployments of XBTs and conductivity–temperature–depth (CTD) data has been assembled, and this unique resource is used to characterize and separate out the pure temperature bias from depth error in a way that was not previously possible. Two independent methods of bias extraction confirm that the results are robust to bias model and fitting method. It was found that there is a pure temperature bias in Sippican probes of ~0.05°C, independent of depth. The temperature bias has a time dependency, being larger (~0.1°C) in the earlier analog acquisition era and being likely due to changes in recorder type. Large depth errors are found in the 1970s–80s in shallower-measuring Sippican T4/T6 probe types, but the deeper-measuring Sippican T7/Deep Blue (DB) types have no error during this time. The Sippican T7/DB fall rate slows from ~1990 onward. It is found that year-to-year variations in fall rate have a bigger effect on corrections to the global XBT database than do any small effects of ocean temperature on fall rate. This study has large implications for the future development of better schemes to correct the global historical XBT archive.
Publisher: American Meteorological Society
Date: 03-2022
DOI: 10.1175/JTECH-D-21-0183.1
Abstract: In situ observations are vital to improving our understanding of the variability and dynamics of the ocean. A critical component of the ocean circulation is the strong, narrow, and highly variable western boundary currents. Ocean moorings that extend from the seafloor to the surface remain the most effective and efficient method to fully observe these currents. For various reasons, mooring instruments may not provide continuous records. Here we assess the application of the Iterative Completion Self-Organizing Maps (ITCOMPSOM) machine learning technique to fill observational data gaps in a 7.5 yr time series of the East Australian Current. The method was validated by withholding parts of fully known profiles, and reconstructing them. For 20% random withholding of known velocity data, validation statistics of the u - and υ -velocity components are R 2 coefficients of 0.70 and 0.88 and root-mean-square errors of 0.038 and 0.064 m s −1 , respectively. Withholding 100 days of known velocity profiles over a depth range between 60 and 700 m has mean profile residual differences between true and predicted u and υ velocity of 0.009 and 0.02 m s −1 , respectively. The ITCOMPSOM also reproduces the known velocity variability. For 20% withholding of salinity and temperature data, root-mean-square errors of 0.04 and 0.38°C, respectively, are obtained. The ITCOMPSOM validation statistics are significantly better than those obtained when standard data filling methods are used. We suggest that machine learning techniques can be an appropriate method to fill missing data and enable production of observational-derived data products. Moored observational time series of ocean boundary currents monitor the full-depth variability and change of these dynamic currents and are used to understand their influence on large-scale ocean climate, regional shelf–coastal processes, extreme weather, and seasonal climate. In this study we apply a machine learning technique, Iterative Completion Self-Organizing Maps (ITCOMPSOM), to fill data gaps in a boundary current moored observational data record. The ITCOMPSOM provides an improved method to fill data gaps in the mooring record and if applied to other observational data records may improve the reconstruction of missing data. The derived gridded data product should improve the accessibility and potentially increase the use of these data.
Publisher: Australian Ocean Data Network
Date: 2022
Publisher: American Meteorological Society
Date: 05-2018
DOI: 10.1175/JTECH-D-17-0122.1
Abstract: Biases have been identified in historical expendable bathythermograph (XBT) datasets, which are one of the major sources of uncertainty in the ocean subsurface database. More than 10 correction schemes were proposed however, their performance has not been collectively evaluated and compared. This study quantifies how well 10 different available schemes can correct the historical XBT data by comparing the corrected XBT data with collocated reference data in both the World Ocean Database (WOD) 2013 and the EN4 dataset. Four different metrics are proposed to quantify their performances. The results indicate CH14 is the best among the currently available methods, and L09/G12/GR10 can be used with some caveats. To test the robustness of the schemes, we further train the CH14 and L09 by using 50% of the XBT–reference data and the schemes are tested by using the remaining data. The results indicate that the two schemes are robust. Moreover, the EN4 and WOD comparison datasets show a systematic difference of XBT error (~0.01°C on a global scale and 0–700 m on average). influences of quality control and data processing have been investigated. Additionally, the side-by-side XBT–CTD comparison experiment is used to examine the correction schemes and provides independent high-quality data for the assessment. The schemes that best correct the global datasets do not always perform as well at correcting the side-by-side dataset, and further examination of the discrepancy in performance is still required. Finally, CH14 and L09 result in very similar ocean heat content (OHC) change estimates in the upper 700 m since 1966, suggesting the potential of reducing XBT-induced error in OHC estimates.
Publisher: American Meteorological Society
Date: 06-2016
DOI: 10.1175/JTECH-D-15-0216.1
Abstract: A very large portion of the historical information on ocean temperatures has been measured using expendable bathythermograph (XBT) devices. For decades, these devices provided the majority of global information. It is, therefore, important to quantify their accuracy and identify biases in this important historical dataset. Here, calculations are made of the influence of water temperature on the rate of descent of the XBT devices into the ocean waters. In colder regions, the larger viscosity of the water is expected to cause a greater drag force on the device, which would slow the descent. It was found through computational fluid dynamic models that the impact of temperature and viscosity on the probe descent is approximately 2.2% for water temperatures that range from 0° to 27°C. Probe-specific temperature-dependent fall rate equations were applied to 269 collocated XBT/conductivity–temperature–depth (CTD) measurements from two different research cruises. It was found that the probe-specific descent equations were an improvement over the uncorrected method. Next, in an effort to automate the process, the fall rate coefficients were related to the topmost measured temperature in the water column. With this relationship, comparisons were made between the probe-specific descent calculations and 2937 high-resolution XBT–CTD pairs. It was found that again, the new methodology outperformed the standard fall rate equation. The new method was also compared with an independent correction method that was previously published. It was found that both new methods were improvements upon the industry-standard fall rate calculation. Subsequent calculations using the top-100-m water temperature were performed and were found to be statistically insignificant compared to the proposed simplified method.
Publisher: No publisher found
Date: 2014
Publisher: American Meteorological Society
Date: 15-01-2022
Abstract: The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with ∼60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970–2008—with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups—to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30°N–30°S. In both mapping and XBT cases, spread is higher for 1990–2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.
Publisher: Hobart, Tas., CSIRO Div. of Marine Research
Date: 1999
Publisher: Australian Ocean Data Network
Date: 2021
DOI: 10.26198/N3XJ-SY16
Publisher: Springer Science and Business Media LLC
Date: 17-03-2021
DOI: 10.1038/S41467-021-22318-6
Abstract: A Correction to this paper has been published: 0.1038/s41467-021-22318-6
Publisher: Springer Science and Business Media LLC
Date: 21-01-2021
DOI: 10.1038/S41467-020-20781-1
Abstract: Despite playing a major role in global ocean heat storage, the Southern Ocean remains the most sparsely measured region of the global ocean. Here, a unique 25-year temperature time-series of the upper 800 m, repeated several times a year across the Southern Ocean, allows us to document the long-term change within water-masses and how it compares to the interannual variability. Three regions stand out as having strong trends that dominate over interannual variability: warming of the subantarctic waters (0.29 ± 0.09 °C per decade) cooling of the near-surface subpolar waters (−0.07 ± 0.04 °C per decade) and warming of the subsurface subpolar deep waters (0.04 ± 0.01 °C per decade). Although this subsurface warming of subpolar deep waters is small, it is the most robust long-term trend of our section, being in a region with weak interannual variability. This robust warming is associated with a large shoaling of the maximum temperature core in the subpolar deep water (39 ± 09 m per decade), which has been significantly underestimated by a factor of 3 to 10 in past studies. We find temperature changes of comparable magnitude to those reported in Amundsen–Bellingshausen Seas, which calls for a reconsideration of current ocean changes with important consequences for our understanding of future Antarctic ice-sheet mass loss.
Publisher: American Meteorological Society
Date: 03-2016
Abstract: The East Australian Current (EAC) is the complex and highly energetic poleward western boundary current of the South Pacific Ocean. A full-depth current meter and property (temperature and salinity) mooring array was deployed from the continental shelf to the abyssal waters off Brisbane Australia (27°S) for 18 months from April 2012 to August 2013. The EAC mooring array is an essential component of the Australian Integrated Marine Observing System (IMOS). During this period the EAC was coherent with an eddy kinetic to mean kinetic energy ratio of less than 1. The 18-month, mean, poleward-only mass transport above 2000 m is 22.1 ± 7.5 Sverdrups (Sv 1 Sv ≡ 10 6 m 3 s −1 ). The mean, poleward-only heat transport and flow-weighted temperature above 2000 m are −1.35 ± 0.42 PW and 15.33°C, respectively. A difference in the poleward-only and net poleward mass and heat transports above 2000 m of 6.3 Sv and 0.24 PW reflects the presence of an equatorward EAC retroflection at the eastern (offshore) end of the mooring array. A complex empirical orthogonal function (EOF) analysis of the along-slope velocity anomalies finds that the first two modes explain 72.1% of the velocity variance. Mode 1 is dominant at periods of approximately 60 days, and mode 2 is dominant at periods of 120 days. These dominant periods agree with previous studies in the Tasman Sea south of 27°S and suggest that variability of the EAC in the Tasman Sea may be linked to variability north of 27°S.
Publisher: Springer Science and Business Media LLC
Date: 25-03-2022
DOI: 10.1038/S41597-022-01212-W
Abstract: Despite technological advances over the last several decades, ship-based hydrography remains the only method for obtaining high-quality, high spatial and vertical resolution measurements of physical, chemical, and biological parameters over the full water column essential for physical, chemical, and biological oceanography and climate science. The Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP) coordinates a network of globally sustained hydrographic sections. These data provide a unique data set that spans four decades, comprised of more than 40 cross-ocean transects. The section data are, however, difficult to use owing to inhomogeneous format. The purpose of this new temperature, salinity, and dissolved oxygen data product is to combine, reformat and grid these data measured by Conductivity-Temperature-Depth-Oxygen (CTDO) profilers in order to facilitate their use by a wider audience. The product is machine readable and readily accessible by many existing visualisation and analysis software packages. The data processing can be repeated with modifications to suit various applications such as analysis of deep ocean, validation of numerical simulation, and calibration of autonomous platforms.
Publisher: CLIVAR
Date: 10-12-2019
Publisher: American Meteorological Society
Date: 04-2021
DOI: 10.1175/JTECH-D-20-0136.1
Abstract: Expendable bathythermographs (XBTs) have been widely deployed for ocean monitoring since the late 1960s. Improving the quality of XBT data is a vital task in climatology. Many factors (e.g., temperature, probe type, and manufacturing time) have been identified as major influences of XBT systematic bias. In addition, the recording system (RS) has long been suspected as another factor. However, this factor has not been taken into account in any global XBT correction schemes, partly because its impact is poorly understood. Here, based on analysis of an XBT–CTD side-by-side dataset and a global collocated reference dataset, the influence of RSs on the pure temperature error (PTE) is examined. Results show a clear time dependency of PTE on the RS, with maximum values occurring in the 1970s. In addition, the method used to convert thermistor resistance into temperature in the RS (using a resistance–temperature equation) has changed over time. These changes, together with the decadal changes in RSs, might contribute a small error (10% on average) to the RS dependency. Here, an improvement of global XBT bias correction that accounts for the RS dependency is proposed. However, more than 70% of historical global XBT data are missing RS-type information. We investigate several assumptions about the temporal distribution of RS types, and all scenarios lead to at least a ~50% reduction in the time variation of PTE compared with the uncorrected data. Therefore, the RS dependency should be taken into account in updated XBT correction schemes, which would have further implications for climatology studies.
Publisher: Australian Ocean Data Network
Date: 2022
DOI: 10.26198/RGNS-V363
Publisher: Frontiers Media SA
Date: 15-09-2020
Publisher: No publisher found
Date: 2014
Publisher: American Meteorological Society
Date: 06-2016
DOI: 10.1175/BAMS-D-15-00031.1
Abstract: Expendable bathythermograph (XBT) data were the major component of the ocean temperature profile observations from the late 1960s through the early 2000s, and XBTs still continue to provide critical data to monitor surface and subsurface currents, meridional heat transport, and ocean heat content. Systematic errors have been identified in the XBT data, some of which originate from computing the depth in the profile using a theoretically and experimentally derived fall-rate equation (FRE). After in-depth studies of these biases and discussions held in several workshops dedicated to discussing XBT biases, the XBT science community met at the Fourth XBT Science Workshop and concluded that XBT biases consist of 1) errors in depth values due to the inadequacy of the probe motion description done by standard FRE and 2) independent pure temperature biases. The depth error and temperature bias are temperature dependent and may depend on the data acquisition and recording system. In addition, the depth bias also includes an offset term. Some biases affecting the XBT-derived temperature profiles vary with manufacturer robe type and have been shown to be time dependent. Best practices for historical XBT data corrections, recommendations for future collection of metadata to accompany XBT data, impact of XBT biases on scientific applications, and challenges encountered are presented in this manuscript. Analysis of XBT data shows that, despite the existence of these biases, historical XBT data without bias corrections are still suitable for many scientific applications, and that bias-corrected data can be used for climate research.
Publisher: American Meteorological Society
Date: 08-2014
DOI: 10.1175/JTECH-D-13-00197.1
Abstract: Systematic biases in historical expendable bathythermograph (XBT) data are examined using two datasets: 4151 XBT–CTD side-by-side pairs from 1967 to 2011 and 218 653 global-scale XBT–CTD pairs (within one month and 1°) extracted from the World Ocean Database 2009 (WOD09) from 1966 to 2010. Using the side-by-side dataset, it was found that both the pure thermal bias and the XBT fall rate (from which the depth of observation is calculated) increase with water temperature. Correlations between the terminal velocity A and deceleration B terms of the fall-rate equation (FRE) and between A and the offset from the surface terms are obtained, with A as the dominant term in XBT fall-rate behavior. To quantify the time variation of the XBT fall-rate and pure temperature biases, global-scale XBT–CTD pairs are used. Based on the results from the two datasets, a new correction scheme for historical XBT data is proposed for nine independent probe-type groups. The scheme includes corrections for both temperature and depth records, which are all variable with calendar year, water temperature, and probe type. The results confirm those found in previous studies: a slowing in fall rate during the 1970s and 2000s and the large pure thermal biases during 1970–85. The performance of nine different correction schemes is compared. After the proposed corrections are applied to the XBT data in the WOD09 dataset, global ocean heat content from 1967 to 2010 is reestimated.
Publisher: Informa UK Limited
Date: 02-2011
Publisher: Frontiers Media SA
Date: 11-06-2021
DOI: 10.3389/FMARS.2021.689695
Abstract: Ocean temperature observations are crucial for a host of climate research and forecasting activities, such as climate monitoring, ocean reanalysis and state estimation, seasonal-to-decadal forecasts, and ocean forecasting. For all of these applications, it is crucial to understand the uncertainty attached to each of the observations, accounting for changes in instrument technology and observing practices over time. Here, we describe the rationale behind the uncertainty specification provided for all in situ ocean temperature observations in the International Quality-controlled Ocean Database (IQuOD) v0.1, a value-added data product served alongside the World Ocean Database (WOD). We collected information from manufacturer specifications and other publications, providing the end user with uncertainty estimates based mainly on instrument type, along with extant auxiliary information such as calibration and collection method. The provision of a consistent set of observation uncertainties will provide a more complete understanding of historical ocean observations used to examine the changing environment. Moving forward, IQuOD will continue to work with the ocean observation, data assimilation and ocean climate communities to further refine uncertainty quantification. We encourage submissions of metadata and information about historical practices to the IQuOD project and WOD.
Publisher: CSIRO
Date: 2022
DOI: 10.25919/3TM5-ZN80
Publisher: Australian Ocean Data Network
Date: 2022
Publisher: No publisher found
Date: 2017
Location: United States of America
Location: Australia
No related grants have been discovered for Rebecca Cowley.