CPClimate of the PastCPClim. Past1814-9332Copernicus PublicationsGöttingen, Germany10.5194/cp-12-911-2016Palaeo-sea-level and palaeo-ice-sheet databases: problems, strategies, and perspectivesDüsterhusAndréandre.duesterhus@uni-hamburg.dehttps://orcid.org/0000-0003-2192-175XRovereAlessiohttps://orcid.org/0000-0001-5575-1168CarlsonAnders E.HortonBenjamin P.https://orcid.org/0000-0001-9245-3768KlemannVolkerhttps://orcid.org/0000-0002-8342-8947TarasovLevBarlowNatasha L. M.BradwellTomClarkJorieDuttonAndreaGehrelsW. RolandHibbertFiona D.HijmaMarc P.KhanNicoleKoppRobert E.https://orcid.org/0000-0003-4016-9428SivanDoritTörnqvistTorbjörn E.https://orcid.org/0000-0002-1563-1716National Oceanography Centre, Liverpool, L3 5DA, UKInstitute of Oceanography, Center for Earth System Research and
Sustainability (CEN), University of Hamburg, Bundesstraße 53, 20146
Hamburg, GermanyMARUM, University of Bremen, & ZMT, Leibniz
Center for Tropical Marine Ecology, Leobener Str., Bremen, GermanyLamont-Doherty Earth Observatory, Columbia University, P.O. Box
1000, 61 Route 9W, Palisades, New York, USACollege of Earth,
Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR
97331 USASea Level Research, Department of Marine and Coastal
Science and Institute of Earth, Ocean and Atmospheric Sciences, Rutgers
University, New Brunswick, NJ 08901, USAEarth Observatory of
Singapore and Asian School of the Environment, Nanyang Technological
University, 639798, Nanyang, SingaporeDep. Geodesy
and Remote Sensing, German Research Centre for Geosciences GFZ, Potsdam,
GermanyMemorial University of Newfoundland, St. John's, NL,
CanadaDepartment of Geography, Durham University, South Road,
Durham, DH1 3LE, UKBiological & Environmental Sciences,
University of Stirling, Stirling, FK9 4LA, Scotland, UKDepartment of Geological Sciences, University of Florida, Gainesville, Florida, USAEnvironment Department, University of York, Heslington, York,
YO10 5NG, UKOcean and Earth Science, National Oceanography
Centre, University of Southampton, Southampton, SO14 3ZH, UKDepartment of Applied Geology and Geophysics, Deltares, Utrecht,
the NetherlandsDepartment of Earth & Planetary Sciences,
Rutgers Energy Institute, and Institute of Earth, Ocean, and Atmospheric
Sciences, Rutgers University, New Brunswick, NJ, USADepartment
of Maritime Civilizations, Leon Charney School of Marine Sciences and
Recanati Institute of Maritime Studies (RIMS), University of Haifa, Haifa,
IsraelDepartment of Earth and Environmental Sciences, Tulane
University, 6823 St. Charles Avenue, New Orleans, Louisiana 70118-5698, USAAndré Düsterhus (andre.duesterhus@uni-hamburg.de)11April201612491192122May201525June201516February20167March2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://cp.copernicus.org/articles/12/911/2016/cp-12-911-2016.htmlThe full text article is available as a PDF file from https://cp.copernicus.org/articles/12/911/2016/cp-12-911-2016.pdf
Sea-level and ice-sheet databases have driven numerous advances in
understanding the Earth system. We describe the challenges and offer best
strategies that can be adopted to build self-consistent and standardised
databases of geological and geochemical information used to archive palaeo-sea-levels
and palaeo-ice-sheets. There are three phases in the development of a
database: (i) measurement, (ii) interpretation, and (iii) database creation.
Measurement should include the objective description of the position and age
of a sample, description of associated geological features, and
quantification of uncertainties. Interpretation of the sample may have a
subjective component, but it should always include uncertainties and
alternative or contrasting interpretations, with any exclusion of existing
interpretations requiring a full justification. During the creation of a
database, an approach based on accessibility, transparency, trust,
availability, continuity, completeness, and communication of content
(ATTAC3) must be adopted. It is essential to consider the community that
creates and benefits from a database. We conclude that funding agencies
should not only consider the creation of original data in specific
research-question-oriented projects, but also include the possibility of
using part of the funding for IT-related and database creation tasks, which
are essential to guarantee accessibility and maintenance of the collected
data.
Introduction
The rapid acquisition of palaeoclimate data and the development of strategies
to assimilate these data into models has resulted in a growing need for
open-access and user-friendly databases with the goal of machine readability
. Within the palaeo-sea-level and palaeo-ice-sheet
communities, there is the further requirement of standardisation
. These communities use field data to reconstruct
the elevation of past sea levels and the dimensions and extent of former ice
sheets. As an example of assimilation of data into models, databases of
sea-level index points have constrained model estimates of the rates of
glacial isostatic adjustment (GIA) during and following the last deglaciation
e.g.. The results from
these studies have contributed, in turn, to estimating current rates of
ice-sheet mass loss and sea-level rise from geodetic observations
. Other databases have been used to assess the
magnitude of the sea-level highstand during the last interglacial period
and improve our understanding of
global ocean volume and earth dynamic topography during the Pliocene
. Likewise, the
worldwide timing of the Last Glacial Maximum e.g.
and global deglaciation of valley glaciers e.g.
has been determined from ice-sheet databases.
The generation of
databases of past sea-level changes began with and
, with early examples of reconstructing temporal changes in
former ice-sheet margins by and
. The need for standardisation among studies as new
sea-level data emerged was recognised and implemented by International Geoscience Programme (IGCP) projects,
starting with IGCP Project 61 in 1974 . Subsequent IGCP
projects produced Holocene databases in the United Kingdom
, the US Atlantic coast , South
America , and elsewhere . Several
recent studies have constructed deglacial databases of ice-sheet retreat, but
they have used different criteria and approaches to data assimilation
e.g..
The process of setting up a sea-level or ice-sheet database can be divided
into three phases: (i) measurement, (ii) interpretation, and (iii) database
creation. In this paper, we build on the results of PALSEA (PALeo constraints
on SEA level rise; ) workshops over the last 8
years to report the main challenges identified for each phase and the
possible solutions that can be adopted.
Measurements
A common denominator of palaeo-sea-level and palaeo-ice-sheet data is that they
originate from two types of direct measurements. Field measurements are taken
to determine the position, location, and elevation of a particular feature
(e.g. a fossil coral or a glacial deposit). Meta data, such as cross
sections and photographs, may also be used to illustrate the local geological
and geomorphological context. Laboratory measurements include establishing
the age of a feature (e.g. a 14C or cosmogenic surface exposure age)
which was sampled in the field. Sample information on location, elevation, and
shielding for cosmogenic surface exposure ages is critical for recalculation
of ages as inferred production rates change .
Any measurement of palaeo-sea-level and palaeo-ice-sheet data needs clearly
specified measures of uncertainties. The scientific value of the data is
maximised if uncertainties are reduced, but missing information often
exacerbates difficulties in
quantifying uncertainties. For example, uncertainties related to the
elevation of a sea-level index point are potentially large if the original
study did not indicate the tidal or geodetic data to which the elevation is
referenced . Elevation errors, which greatly affect
palaeo-relative-sea-level (RSL) calculations, can be avoided by employing
state-of-the-art GPS and levelling
techniques e.g.. Despite this,
high-accuracy GPS systems are to date seldom applied to measure Quaternary
and Pliocene sea-level proxies. Although the laboratory error is often
indicated as part of laboratory procedures, this is not always the case with
instrumental errors in a field measurement.
(a) The effect of different measurement and
documentation of time and space of the same sea-level indicator in two
different studies. (b) Different interpretations for the sea-level
indicator: a deposit containing fossil corals. (c) ATTAC3
approach to database creation. See text for details.
Ideally, multiple studies measuring and interpreting the same proxy should have overlapping
uncertainty ellipses (cases 1 and 2 in Fig. a). Unfortunately,
there are many examples where measurements do not overlap (3 in Fig. a)
or cannot be realistically compared due to the lack of
details on measurement techniques or details on interpretation (4 in Fig. a).
In the worst case, some studies may fail to report the error
and cannot be compared. Incomplete data limit the longevity of some data,
requiring new studies to remeasure the same proxies.
Measurement of palaeo-sea-level and palaeo-ice-sheet data can either be obtained by
direct field or laboratory activities, or derived from a previous publication
and inserted in the database. In all cases, the transfer of information
should be objective and complete, reporting only what can be read in the
original publication and/or what is measured in the field, with no further
interpretation. An important goal for the future is for different communities
to agree on standardised measurements and data reporting norms
e.g.. Precision of terminology is vital to
avoid misinterpretations of field and laboratory measurements
. This will facilitate seamless interfacing with
database systems for archiving and further analysis. Palaeo-sea-level and
palaeo-ice-sheet databases need to include standardised documentation of fundamental
data fields:Position
(i.e. geographical location and elevation or depth),
referred to a specific sea-level datum and, if available, the positioning techniques applied;
Age
including laboratory identification number, details on the dating technique used, and
ideally the raw data;
Description of the feature
including metadata
and images to complement the quantitative information;
Quantification
of measurement uncertainties.
Interpretation
Once measured, field and laboratory data are interpreted to reconstruct the
palaeo-sea-level and the spatial and temporal extent of the palaeo-ice-sheet.
Commonly it is the interpretation that will be most interesting for the final
users, who may not be experts but need to compare the reconstructions with
independent estimates, such as model predictions.
There is often a subjective component to the interpretation of field data. In
Fig. b, we show fossil corals, a typical example of a sea-level
indicator. An objective assessment of the coral age can be determined using
U-series techniques e.g. applying the template used
in. The position of the deposit relative to a tidal or
geodetic datum can be measured with appropriate accuracy. The taxonomy of the
sample can be reported, which should include information on the benthic
assemblage and its relation to sea level and geological and sedimentological
properties. The subjectivity relates to the interpretation of the palaeowater
depth (i.e. relation to sea level) of the coral. One possible interpretation
following investigation of the depth distribution of corals in the deposit is
that the corals are in situ (e.g. in living position) and sea level at the
time of deposition was somewhere above the measured elevation (i.e. it is a
lower limiting data point, Int. 1 in Fig. b). Another
interpretation could be that the corals are allochthonous, and instead
represent a storm deposit. In this case, it is only possible to infer that
the deposit represents the top of a marine sequence and that the palaeo-sea-level
was located below the measured elevation of the deposit (i.e. its upper
limiting data point, Int. 2 in Fig. b). A final interpretation
may instead recognise elements (e.g. microatolls, intertidal geological
facies within the deposit) that tie the deposit to the palaeo-sea-level
around the measured elevation within an uncertainty (i.e. identifying
reference water level and indicative range
, Int. 3 in
Fig. b). Whenever controversial interpretations such as those
summarised above exist, a database should document all of them. If one
interpretation is more likely than the others, or is supported by independent
studies, this information should be inserted in the database within the
metadata. Issues may emerge in the interpretation of laboratory data,
such as the use of different calibration curves to establish the age of an
indicator. The interpretation of data can be subject to changes with
scientific advances. As an example, old 14C ages or cosmogenic surface
exposure ages can be recalibrated following the availability of new
calibration curves or calibration schemes or new production rates and scaling
models, respectively. But the possibility of recalibrating these measurements
depends on the presence of primary data, such as δ13C measurements,
description of the dated material, sample thickness, etc.
. In principle, if measurement data
are present in a database, obtaining secondary data from new interpretations
can be streamlined relatively easily.
Uncertainties of sea-level and ice-sheet indicators are usually treated as
Gaussian distributions, with the exception of limiting data that only provide
information on maximum or minimum sea level (Int. 1 and Int. 2 in
Fig. b). In the case of Gaussian uncertainties, the uncertainty
of the interpretation can be combined with the uncertainty of the measurement
(dashed line in Fig. b) using the root mean square error formula
assuming the uncertainties are independent; more complicated uncertainties
may require Monte Carlo sampling. As understanding of habitat distribution
for marine species or coastal facies increases, and more consideration is
given to the physical processes that perturb sample elevation over time, an
increasing amount of data will use more accurate uncertainty distributions
that extend beyond the Gaussian approximation. We recommend recording
multiple percentiles of these non-Gaussian distributions to reflect not only
the width of the uncertainty but also the shape of its probability
distribution.
Palaeo-sea-level and palaeo-ice-sheet databases that incorporate interpretations
must therefore beFlexible
to take into account the fact that, although the measurement must
be unequivocal, interpretation of the data can be multiple and vary or evolve over time;
Consistent
in the reporting of interpretations and uncertainties of data.
Published regional sea-level databases that follow (where
appropriate) IGCP guidelines: (A) Pacific
, (B) Gulf
, and (C) Atlantic
coasts of North America; (D) Caribbean and South America
; (E) Greenland ; (F) Ireland
; (G) the UK ; (H) northwest
Europe ; (I) the Mediterranean
; (J) China ,
(K) Malay Peninsula ; (L) New Zealand
; and (M) Antarctica .
Database creation
A database is primarily a collection of data records and secondarily a
platform for exchange of data and information. The process of creating a
database must necessarily start from the identification of the agents that
will interact with it. Data creators provide the original data sets and
should carry out their work with databases in mind. In palaeoclimate
sciences, these are usually geologists and geochemists, who carry out the
main part of the measurement and interpretation process. Data compilers
collect data from different sources and, if necessary, reinterpret it.
Measurement and interpretation constitute the backbone of every palaeo-sea-level
and palaeo-ice-sheet database, but there are other key elements to be
considered, which we summarise under the ATTAC3 acronym
(Fig. c): accessibility, transparency,
trust, availability, continuity,
completeness, and communication of content.
Accessibility
is a challenge due to the heterogeneity of the user communities.
A majority of published databases today use a spreadsheet format, which is easy
to access for most users. However, some information (e.g. images or non-Gaussian
uncertainty estimates) is more simply presented in relational databases. Furthermore,
relational databases enable different presentation formats for different end-user communities.
Transparency
is critical in interdisciplinary research fields. Scientists
must trust each other on the applied methodology, but at the same time they have
to be able to understand the applied procedures. As a database creator and
compiler cannot know all future users of the data and the fields in which
they are applied, the database description must be as detailed as possible.
The description should include appropriate metadata and use standardised
language and comments in data fields. Indicating the quality of each data
field in understandable formats will help the end user to make appropriate
use of the data .
Trust
is built by database compilers sharing credit with the scientists
delivering the data . Data creators and
compilers are confronted with the risk that their original publications are
no longer cited when their data are included in a larger citable database
and thus will not gain credit under current performance metrics, such as the
H-index . To ensure the availability of high-quality
data sets in the future, data creators need to be given appropriate credit.
Trust of a database requires consistent data quality and transparently
applied procedures, and a consistent and trustworthy host. It also requires
effective software design for the database and within the data processing.
Ideally, the code should be openly available and well documented.
Availability
of a database for the long term requires long-term funding
(see below). Today, most databases are attached to journal articles as a
spreadsheet in the supplement. This ensures persistence, but no database
maintenance and/or upgrade is possible for most journals.
Continuity
of updating is important to stay relevant and reflect the
changing interpretations of the data. To allow cite-ability of the database
e.g. with digital object identifiers
(DOIs);, version control is essential.
Furthermore, the use of unique and persistent identifiers, such as the
International Geo Sample Number (IGSN) that is currently used for geological
samples, should be encouraged to ensure that over different update cycles a
data point can be uniquely referenced by scientists.
Completeness
of the database is important, especially in the context of
uncertainties . Even when the basic elements (like
position, age, and elevation) are complete, for many applications they are of
limited use when associated uncertainties are not clearly indicated or
defined.
Communication
of the content, for example through interfaces for
visualisation software, helps to open the database for new audiences.
Advanced visualisation approaches e.g. require standardised protocols for data extraction and
consistent data types. These properties have to be determined in the design
phase of the database; thus it is important to consider its applications
right from the beginning.
The community structure
Any database should be aimed at serving a community of end users, who extract
content for further analysis, and give feedback on specific needs regarding
data sets or analyses. Databases should be centralised and interconnected via
the Internet in order to reach the maximum possible number of end users, with
the widest possible geographic distribution. The data are more likely to be
used if the end users have a unique access point for the data sets, such as a
WebGIS portal. In the geological domain, there are large initiatives to build
data repositories, which are already well established and used by scientists
worldwide. Two examples are the NOAA World Data Center for Paleoclimatology
and PANGAEA
(http://www.pangaea.de/). Some journals link PANGAEA databases to
online versions of associated papers.
Example of a data management plan (DMP) for a project on Pleistocene
sea-level markers obtained with the IEDA (Interdisciplinary Earth Data
Alliance, http://www.iedadata.org/) DMP toolbox. Note that, to
correctly store sea-level data, at least four independent repositories are
needed.
Most funding agencies require that data collected in the framework of a
project be archived and made available through data repositories. This is
achieved through a “data management plan” (National Science Foundation of
the United States) or the “open data policy” (European Union), which
requests that the project leaders state where they plan to store the data
collected within their project. Currently, a researcher working on sea-level
and/or ice-sheet databases only has the choice to store the new data sets in
different repositories, which might have the effect of dispersing the data
across several repositories, decentralising data storage (see example in
Fig. ).
List of published global sea-level databases that follow (where
appropriate) the IGCP format. Formats in which the data are provided:
spreadsheets (R) and interactive interfaces that allow the visualisation,
extraction, or download of data (I).
DescriptionAccessibilityCompilation of last interglacial coral U–Th age data, elevation data, and associated sample information. The first worksheet of the Excel file contains the data and calculated ages and elevations that have been normalised to common decay constants and elevation benchmarks, respectively; the second worksheet contains definitions of column headings and data units; the third worksheet contains a lookup table for data sources listed by number in the first worksheet. Some entries in the database are annotated by comment fields to denote supplemental information for data or calculations not included in the original publications.Annexed to publ. (R) Storage of different accessible compilations in relational database system PostgreSQL. Contains the regional databases A, B, C, and D shown in Fig. and further data mainly from published compilations or grey literature. Access via visualisation and analysis software SLIVISU (beta version) or direct access (password protected).Online (I), on request Compilation of global Holocene relative sea-level data. Each database entry includes location, sea level, sea-level error, age, and age error, as well as the original source of publication.Annexed to publ. (R) Multi-proxy database of last interglacial index and limiting relative sea-level index points. A legend worksheet defines column headings and data units.Annexed to publ. (R)https://www.ncdc.noaa.gov/paleo/study/19823Database of Common Era (last 3000 years) relative sea-level data. Each database entry includes location, sea level, sea-level error, age, and age error, as well as the original source publication. There is a front page of definitions of column headings and data units.Online (R) Spreadsheets containing information on shoreline analysis from Holocene to Miocene highstands. Regarding ages, only stratigraphic units are given.Annexed to publ. (R)http://pliomax.org/pliowiki/index.php/RSLmap
RSLmap is a visualisation tool for RSL markers, which allows the display and querying of a database of published or user-submitted relative sea-level data points.Online (I)
In the framework of a single research project, the data creator is also a
data compiler, and often the first end user. It is, therefore, necessary to
ensure that the data sets collected in the framework of a single project have
a standardised structure and are available to other end users.
Description of regional databases presented in Fig. .
For details see Table .
RegionDescriptionAccessibilityA (http://sealevel.marine.rutgers.edu/).Deglacial sea-level database for the Pacific coast of central North America.Online (R)Bhttps://www.ncdc.noaa.gov/paleo/study/16361.Pilot database intended as an initial release of Holocene geological relative sea-level data that have been compiled according to a recently developed protocol . The database is provided in two versions: a complete version that consists of 77 variables and that includes all the underlying data, as well as a processed version with only the 11 most critical variables. It is anticipated that this latter version will be adequate for most users, while the former provides a full documentation for those who wish to carry out more detailed analyses.Online (R)Chttp://sealevel.marine.rutgers.edu/.Holocene sea-level database for the Atlantic coast of the United States.Online (R)D.Deglacial sea-level compilation for the Caribbean and South American Atlantic coast that was compiled for a regional GIA study.Appendix to publ.E. Compilation and own investigations mainly of Holocene isolation basins for southern Greenland.Table in publ.Fhttp://www.naturalscience.tcd.ie/SL_Database.php.Compilation of sea-level data of Ireland, which contains detailed spreadsheet and additional information on webpage.Online (R)G. The database covers Great Britain (England, Scotland, and Wales) and has around 2250 entries. It exists as an Access database; interfaces to convert the information to Excel spreadsheets for regional compilations are available.From authorH. Compilation of available data of Belgium, the Netherlands, and Germany of the Channel and southern North Sea of about 380 SLIs which are listed in an appendix to the publication.Appendix to publ.Ihttp://www.medflood.org/results-2/webgis/.Published Pleistocene and Holocene sea-level data in the Mediterranean Sea collected by the INQUA MEDFLOOD project.Online (I)J. Compilation of SLIs covering SE coast of China. There are only a few attributes listed.Appendix to publ.Khttp://sealevel.marine.rutgers.edu/.Holocene sea-levels database of Malay–Thai Peninsula, Southeast Asia.Online (R)L. Compilation of Holocene sea-level data of New Zealand.Table in publ.M. Compilation of late-glacial and Holocene sea-level data of Antarctica.Table in publ.
A significant concern regarding the maintenance of a healthy research
community is appropriate crediting of authorship. How does an end user using
thousands of data points from dozens of source publications provide
appropriate credit? Journals often allow for only a limited number of
citations, and often the citation credit goes to the data compiler, who
created the review database, and not to the data creator. If the question
above is not addressed, the long-term result will be that data creators will
have no incentive to support the inclusion of their work in a centralised
database. This issue must be addressed by journal editors. In some cases,
editors have made exceptions to standard journal length rules in order to
include all the original papers in the reference list
e.g.. Alternatively, some journals allow longer,
online-only papers with space for a full reference list
e.g.. A number of sea-level databases have been
produced in the framework of single research projects (Table ).
In general, there are two formats in which the data are provided: data
repositories in the form of spreadsheets (R) and interactive interfaces that
allow the visualisation, extraction, or download of data (I). In
Fig. we show the geographic coverage for a number of databases
representing late-glacial and Holocene RSL data which were compiled from
different original studies following, where appropriate, the IGCP guidelines.
Each index point has a defined location, age, elevation relative to former
sea level, and appropriate accounting of errors (details to the databases in
Table ).
Concluding remarks
The discussions of the PALSEA community on sea-level and ice -heet databases
can be framed around the following points:
Any set-up of sea-level or ice-sheet databases must be divided into
measurement,
interpretation,
database creation.
Storage of measurements should include position, age, description of
geological features, and quantification of uncertainties. All must be described as objectively as possible with relevant metadata.
Interpretation of geological data will retain a subjective component,
but it should always include uncertainties and include all the possible interpretations.
When creating a database, all the aspects related to the ATTAC3
approach must be taken into account.
The community structure that creates and benefits from a database must
be considered, and the needs and concerns of each part of the community must be respected.
There remains the need for a centralised database structure for the sea-level
and ice-sheet communities. Despite this need, dedicated funding for “user-friendly”,
field-specific database creation is rarely available because
funding mostly prioritises projects that follow the classic hypothesis-driven
research approach. Data management is often restricted to archiving at a
general level. The tasks of database creation, maintenance, and guarantee of
accessibility are limited to single projects, and the possibility to hire ad
hoc personnel (e.g. experts in geoinformatics) to fulfil these requirements
is often disregarded by funding agencies. We favour interdisciplinary
research collaborations focusing on field-specific database development and
maintenance, including projects that amalgamate and reanalyse published
data sets into new databases. These new databases enhance the legacy of
monetary investments originally made to collect sea-level and ice-sheet data.
Many of the aspects discussed in this paper will also be valid for other
types of geological data and may be of interest to additional geoscientific
communities.
Acknowledgements
This paper has been written in the framework of PALSEA, the PALeo constraints
on SEA level rise project, sponsored by PAGES and INQUA. This publication was
planned at the PALSEA workshop in Lochinver, Scotland, organised by Antony
Long and Natasha Barlow (Durham University). Publication costs were covered
by Tulane's Vokes Geology Fund (Torbjörn E. Törnqvist). The authors
wish to thank the following funding sources: Natural Environmental Research
Council under the numbers NE/I008365/1 (André Düsterhus) and
NE/I008624/1 (W. Roland Gehrels); Institutional Strategy of the University of
Bremen (German Excellence Initiative, Alessio Rovere); the US National Science Foundation (NSF) grant OCE1458904 (Benjamin P. Horton, Robert E. Kopp), grant OCE-1502588 (Torbjörn Törnqvist) and award no. 1443037 (Andrea Dutton); Global Change Program (EAR 1304909, Jorie Clark); and the
German Climate Modeling Initiative (PALMOD, Volker Klemann). Edited by: D. Fleitmann
ReferencesBalco, G.: Contributions and unrealized potential contributions of
cosmogenic-nuclide exposure dating to glacier chronology, 1990–2010,
Quaternary Sci. Rev., 30, 3–27, 10.1016/j.quascirev.2010.11.003, 2011.Bradley, S. L., Milne, G. A., Shennan, I., and Edwards, R.: An improved
glacial isostatic adjustment model for the British Isles, J. Quat. Sci., 26,
541–552, 10.1002/jqs.1481, 2011.Briggs, R. D. and Tarasov, L.: How to evaluate model-derived deglaciation
chronologies: a case study using Antarctica, Quaternary Sci. Rev., 63,
109–127, 10.1016/j.quascirev.2012.11.021, 2013.Briggs, R. D., Pollard, D., and Tarasov, L.: A data-constrained large
ensemble analysis of Antarctic evolution since the Eemian, Quaternary Sci.
Rev., 103, 91–115, 10.1016/j.quascirev.2014.09.003, 2014.Brooks, A. and Edwards, R.: The Development of a Sea-Level Database for
Ireland, Irish J. Earth Sci., 24, 13–27, 10.3318/ijes.2006.24.1.13,
2006.Bryson, R. A., Wendland, W. M., Ives, J. D., and Andrews, J. T.: Radiocarbon
Isochrones on the Disintegration of the Laurentide Ice Sheet, Arctic Alpine
Res., 1, 1–14, 10.2307/1550356, 1969.Clark, P. U., Dyke, A.,
Shakun, J. D., Carlson, A. E., Clark, J., Wohlfarth, B., Hostetler, S.,
Mitrovica, J. X., and McCabe, A.: The Last Glacial Maximum, Science, 325,
710–714, 10.1126/science.1172873, 2009.Clement, A. J., Whitehouse, P. L., and Sloss, C. R.: An examination of
spatial variability in the timing and magnitude of Holocene relative
sea-level changes in the New Zealand archipelago, Quaternary Sci. Rev., 131,
73–101, 10.1016/j.quascirev.2015.09.025, 2016.Costello, M. J.: Motivating Online Publication of Data, BioScience, 59,
418–427, 10.1525/bio.2009.59.5.9, 2009.Daly, R. A.: The changing world of the ice age, Yale University Press, New
Haven, 10.1017/s001675680009422x, 1934.Düsterhus, A. and Hense, A.: Automated quality evaluation for a more
effective data peer review, Data Sci. J., 13, 67–78,
10.2481/dsj.14-009, 2014.Dutton, A. and Lambeck, K.: Ice Volume and Sea Level During the Last
Interglacial, Science, 337, 216–219, 10.1126/science.1205749, 2012.Dyke, A. S.: An outline of North American Deglaciation with emphasis on
central and northern Canada, in: Quaternary Glaciations – Extent and
Chronology: Part II: North America, edited by: Ehlers, J. and Gibbard, P. L.,
373–424, Elsevier, Amsterdam, 10.1016/S1571-0866(04)80209-4, 2004.Engelhart, S. and Horton, B. P.: Holocene sea level database for the Atlantic
coast of the United States, Quarternary Sci. Rev., 54, 12–25,
10.1016/j.quascirev.2011.09.013, 2012.Engelhart, S., Peltier, W. R., and Horton, B. P.: Holocene relative sea-level
changes and glacial isostatic adjustment of the U.S. Atlantic coast, Geology,
39, 751–754, 10.1130/G31857.1, 2011.Engelhart, S. E., Vacci, M., Horton, B. P., Nelson, A. R., and Kopp, R. E.: A
sea-level database for the Pacific coast of central North America, Quaternary
Sci. Rev., 113, 78–92, 10.1016/j.quascirev.2014.12.001, 2015.Godwin, H.: Studies in the post-glacial history of British vegetation. III:
Fenland pollen diagrams. IV: Post-glacial changes of relative land and sea
level in the English Fenland, Philos. T. R. Soc. B, 230, 239–303,
10.1098/rstb.1940.0001, 1940.Hijma, M., Engelhart, S., Horton, B. P., Törnqvist, T., Hu, P., and Hill,
D.: A Protocol for a Geological Sea-Level Database, in: Handbook of Sea-Level
Research, edited by: Shennan, I., Long, A. J., and Horton, B. P., Wiley
Blackwell, 536–553, 10.1002/9781118452547.ch34, 2015.Hirsch, J. E.: An index to quantify an individual's scientific research
output, P. Natl. Acad. Sci. USA, 102, 16569–16572,
10.1073/pnas.0507655102, 2005.Horton, B. P., Edwards, R. J., and Floyd, J. M.: Implications of a
microfossil-based transfer function in Holocene sea-level studies, Geol.
Soc. Sp., 166, 41–54, 10.1144/GSL.SP.2000.166.01.03, 2000.Horton, B. P., Gibbard, P. L., Mine, G. M., Morley, R. J., Purintavaragul,
C., and Stargardt, J. M.: Holocene sea levels and palaeoenvironments,
Malay-Thai Peninsula, southeast Asia, The Holocene, 15, 1199–1213,
10.1191/0959683605hl891rp, 2005.Hughes, A. L. C., Gyllencreutz, R., Lohne, Ø. S., Mangerud, J., and
Svendsen, J. I.: The last Eurasian ice sheets – a chronological database and
time-slice reconstruction, DATED-1, Boreas, 45, 1–45,
10.1111/bor.12142, 2016.Kattage, J., Diaz, S., and Wirth, C.: Of carrots and sticks, Nat. Geosci., 7,
778–779, 10.1038/ngeo2280, 2014.Khan, N. S., Ashe, E., Shaw, T. A., Vacchi, M., Walker, J., Peltier, W.,
Kopp, R. E., and Horton, B. P.: Holocene Relative Sea-Level Changes from
Near-, Intermediate-, and Far-Field Locations, Curr. Climate Change Reports,
1, 247–262, 10.1007/s40641-015-0029-z, 2015.
Klemann, V., Unger, A., Hibbert, F., and Dransch, D.: SLIVISU, a concept of
an interactive visualization framework for the analysis of geological data,
EGU General Assembly Conference Abstracts, 15, EGU2013–13953, 2013.Kopp, R. E., Simons, F. J., Mitrovica, J. X., Maloof, A. C., and
Oppenheimer, M.: Probabilistic assessment of sea level during the last
interglacial stage, Nature, 462, 863–867, 10.1038/nature08686, 2009.Kopp, R. E., Kemp, A. C., Bittermann, K., Horton, B. P., Donnelly, J. P.,
Gehrels, W. R., Hay, C. C., Mitrovica, J. X., Morrow, E. D., and Rahmstorf,
S.: Temperature-driven global sea-level variability in the Common Era, P.
Natl. Acad. Sci. USA, 113, E1434–E1441, 10.1073/pnas.1517056113, 2016.Long, A. J., Woodroffe, S. A., Roberts, D. H., and Dawson, S.: Isolation
basins, sea-level changes and the Holocene history of the Greenland Ice
Sheet, Quaternary Sci. Rev., 30, 3748–3768,
10.1016/j.quascirev.2011.10.013, 2011.Milne, G. A., Long, A. J., and Bassett, S. E.: Modelling Holocene Relative
Sea-Level Observations from the Caribbean and South America, Quaternary Sci.
Rev., 24, 1183–1202, 10.1016/j.quascirev.2004.10.005, 2005.Muhs, D. R., Simmons, K. R., Schumann, R. R., and Halley, R. B.: Sea-level
history of the past two interglacial periods: new evidence from U-series
dating of reef corals from south Florida, Quaternary Sci. Rev., 30, 570–590,
10.1016/j.quascirev.2010.12.019, 2011.Overpeck, J. T., Meehl, G. A., Bony, S., and Easterling, D. R.: Climate data
challenges in the 21st century, Science, 331, 700–702,
10.1126/science.1197869, 2011.Paskin, N.: Digital Object Identifiers for scientific data, Data Sci. J., 4,
12–20, 10.2481/dsj.4.12, 2005.Pedoja, K., Husson, L., Johnson, M. E., Melnick, D., Witt, C., Pochat, S.,
Nexer, M., Delcaillau, B., Pinegina, T., Poprawski, Y., Authemayou, C.,
Elliot, M., Regard, V., and Garestier, F.: Coastal staircase sequences
reflecting sea-level oscillations and tectonic uplift during the Quaternary
and Neogene, Earth-Sci. Rev., 132, 13–38,
10.1016/j.earscirev.2014.01.007, 2014.Peltier, W. R., Argus, D. F., and Drummond, R.: Space geodesy constrains ice
age terminal deglaciation: The global ICE-6G_C (VM5a) model, J. Geophys.
Res.-Sol. Ea., 120, 450–487, 10.1002/2014JB011176, 2015.Prest, V., Grant, D. R., and Rampton, V. N.: Gacial Map of Canada, Map 1532A,
Ottawa, 10.4095/108979, 1968.Quadt, F., Düsterhus, A., Höck, H., Lautenschlager, M., Hense, A. V.,
Hense, A. N., and Dames, M.: Atarrabi – A workflow system for the Publication
of Envrionmental Data, Data Sci. J., 11, 89–109, 10.2481/dsj.012-027,
2012.Reynolds, L. C. and Simms, A. R.: Late Quaternary relative sea level in
Southern California and Monterey Bay, Quaternary Sci. Rev., 126, 57–66,
10.1016/j.quascirev.2015.08.003, 2015.Rovere, A., Raymo, M. E., O'Leary, M. J., and Hearty, P. J.: Crowdsourcing in
the Quaternary sea level community: insights from the Pliocene, Quaternary
Sci. Rev., 56, 164–166, 10.1016/j.quascirev.2012.09.014, 2012.Rovere, A., Raymo, M. E., Mitrovica, J. X., Hearty, P. J., O'Leary, M. J.,
and Inglis, J. D.: The Mid-Pliocene sea-level conundrum: Glacial isostasy,
eustasy and dynamic topography, Earth Planet. Sc. Lett., 387, 27–33,
10.1016/j.epsl.2013.10.030, 2014.Rovere, A., Hearty, P. J., Austermann, J., Mitrovica, J. X., Gale, J.,
Moucha, R., Forte, A. M., and Raymo, M. E.: Mid-Pliocene shorelines of the US
Atlantic Coastal Plain – An improved elevation database with comparison to
Earth model predictions, Earth-Sci. Rev., 145, 117–131,
10.1016/j.earscirev.2015.02.007, 2015.Rowley, D. B., Forte, A. M., Moucha, R., Mitrovica, J. X., Simmons, N. A.,
and Grand, S. P.: Dynamic Topography Change of the Eastern United States
Since 3 Million Years Ago, Science, 340, 1560–1563,
10.1126/science.1229180, 2013.Roy, K. and Peltier, W. R.: Glacial isostatic adjustment, relative sea level
history and mantle viscosity: reconciling relative sea level model
predictions for the U.S. East coast with geological constraints, Geophys. J.
Int., 201, 1156–1181, 10.1093/gji/ggv066, 2015.Shakun, J. D., Clark, P. U., He, F., Lifton, N. A., Liu, Z., and
Otto-Bliesner, B. L.: Regional and global forcing of glacier retreat during
the last deglaciation, Nat. Comm., 6, 8059, 10.1038/ncomms9059, 2015.Shennan, I.: Flandrian sea-level changes in the Fenland. II: Tendencies of
sea-level movement, altitudinal changes, and local and regional factors, J.
Quaternary Sci., 1, 155–179, 10.1002/jqs.3390010205, 1986.Shennan, I. and Horton, B.: Holocene land- and sea-level changes in Great
Britain, J. Quaternary Sci., 17, 511–526, 10.1002/jqs.710, 2002.Shennan, I., Long, A. J., and Horton, B. P. (Eds.): Handbook of Sea-Level
Research, Wiley Blackwell, 10.1002/9781118452547, 2015.Siddall, M., Abe-Ouchi, A., Andersen, A., Antonioli, F., Bamber, J. L., Bard,
E., Clark, J., Clark, P. U., Deschamps, P., Dutton, A., Elliot, M., Gallup,
C., Gomez, N., Gregory, J. M., Huybers, P., Kawarnura, K., Kelly, M.,
Lambeck, K., Lowell, T., Mitrovica, J. X., Otto-Bliesner, B. L., Richards,
D., Stanford, J. R., Stirling, C., Stocker, T. F., Thomas, A. L., Thompson,
B., Törnquvist, T., Riveiros, N., Waelbroeck, C., Yokoyama, Y., and Yu,
S. U.: The sea-level conundrum: case studies from palaeo-archives, J.
Quarternary Sci., 25, 19–25, 10.1002/jqs.1270, 2010.Stokes, C. R., Tarasov, L., Blomdin, R., Cronin, T. M., Fisher, T. G.,
Gyllencreutz, R., Hättestrand, C., Heyman, J., Hindmarsh, R. C., Hughes,
A. L., Jakobsson, M., Kirchner, N., Livingstone, S. J., Margold, M., Murton,
J. B., Noormets, R., Peltier, W. R., Peteet, D. M., Piper, D. J., Preusser,
F., Renssen, H., Roberts, D. H., Roche, D. M., Saint-Ange, F., Stroevend,
A. P., and Tellert, J. T.: On the reconstruction of palaeo-ice sheets: Recent
advances and future challenges, Quarternary Sci. Rev., 125, 15–49,
10.1016/j.quascirev.2015.07.016, 2015.Stroeven, A. P., Hättestrand, C., Kleman, J., Heyman, J., Fabel, D.,
Fredin, O., Goodfellow, B. W., Harbor, J. M., Jansen, J. D., Olsen, L.,
Caffee, M. W., Fink, D., Lundqvist, J., Rosqvist, G. C., Strömberg, B.,
and Jansson, K. N.: Deglaciation of Fennoscandia, Quarternary Sci. Rev.,
10.1016/j.quascirev.2015.09.016, online first, 2015.Tarasov, L., Dyke, A., Neal, R. M., and Peltier, W. R.: A data-calibrated
distribution of deglacial chronologies for North American ice complex from
glaciological modelling, Earth Planet. Sc. Lett., 315–316,
10.1016/j.epsl.2011.09.010, 2012.Törnqvist, T. E., Rosenheim, B. E., Hu, P., and Fernandez, A. B.:
Radiocarbon dating and calibration, in: Handbook of Sea-Level Research,
edited by: Shennan, I., Long, A. J., and Horton, B. P., 349–360, Wiley
Blackwell, 10.1002/9781118452547.ch23, 2015.Unger, A., Schulte, S., Klemann, V., and Dransch, D.: Visual Analytics
Concept for the Validation of Geoscientific Simulation Models, IEEE Trans.
Vis. Comp. Graph, 18, 2216–2225, 10.1109/tvcg.2012.190, 2012.Vacchi, M., Rovere, A., Chatzipetros, A., Zouros, N., and Firpo, M.: An
updated database of Holocene relative sea level changes in NE Aegean Sea,
Quaternary Int., 328–329, 301–310, 10.1016/j.quaint.2013.08.036,
2014.Vacchi, M., Marriner, N., Morhange, C., Spada, G., Fontana, A., and Rovere,
A.: Multiproxy assessment of Holocene relative sea-level changes in the
western Mediterranean: Sea-level variability and improvements in the
definition of the isostatic signal., Earth-Sci. Rev., 155, 172–197,
10.1016/j.earscirev.2016.02.002, 2016.
van de Plassche, O.: Sea-level research: a manual for the collection and
evaluation of data, Springer Netherlands, 10.1007/978-94-009-4215-8,
1986.
Vaughan, D. G., Comiso, J., Allison, I., Carrasco, J., Kaser, G., Kwok, R.,
Mote, P., Murray, T., Paul, F., Ren, J., Rignot, E., Solomina, O., Steffen,
K., and Zhang, T.: Observations: Cryosphere, in: Climate Change 2013: The
Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.,
Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P., Cambridge
University Press, Cambridge, UK, and New York, NY, USA, 2013.Vink, A., Steffen, H., Reinhardt, L., and Kaufmann, G.: Holocene relative
sea-level change, isostatic subsidence and the radial viscosity structure of
the mantle of northwest Europe (Belgium, the Netherlands, Germany, southern
North Sea), Quaternary Sci. Rev., 26, 3249–3275,
10.1016/j.quascirev.2007.07.014, 2007.Wahl, E. R., Anderson, D. M., Bauer, B. A., Buckner, R., Gille, E. P., Gross,
W. S., Hartman, M., and Shah, A.: An archive of high-resolution temperature
reconstructions over the past 2+millennia, Geochem. Geophy. Geosy., 11,
10.1029/2009GC002817, 2010.Whitehouse, P. L., Bentley, M. J., and Le Brocq, A. M.: A deglacial model for
Antarctica: geological constraints and glaciological modelling as a basis for
a new model of Antarctic glacial isostatic adjustment, Quaternary Sci. Rev.,
32, 1–24, 10.1016/j.quascirev.2011.11.016, 2012.Zong, Y.: Mid-Holocene sea-level highstand along the Southeast Coast of
China, Quaternary Int., 117, 55–67, 10.1016/S1040-6182(03)00116-2,
2004.