Iestyn Barr

Dr. Iestyn Barr

Manchester Metropolitan University, UK
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2018 in Earth-Science Reviews
Verified
Journal Article
Open access
BCBenjamin M.P. Chandler
Benjamin M.P. Chandler
HLHarold Lovell
Harold Lovell
CBClare M. Boston
Clare M. Boston
SLSven Lukas
Sven Lukas
IBIestyn Barr
Iestyn Barr
ASArjen Stroeven
Arjen Stroeven

21 October 2019 in Nature Geoscience
Verified
Journal Article
Closed access
PDF file
GSGraeme T. Swindles
Graeme T. Swindles
PMPaul J. Morris
Paul J. Morris
DMDonal J. Mullan
Donal J. Mullan
RPRichard J. Payne
Richard J. Payne
TRThomas P. Roland
Thomas P. Roland
BWBarry Warner
Barry Warner

29 August 2017 in Boreas
Verified
Journal Article
Open access
PDF file
CCChris D. Clark
Chris D. Clark
JEJeremy C. Ely
Jeremy C. Ely
SGSarah L. Greenwood
Sarah L. Greenwood
AHAnna L. C. Hughes
Anna L. C. Hughes
RMRobert Meehan
Robert Meehan
MSMichael Sheehy
Michael Sheehy
During the last glaciation, most of the British Isles and the surrounding continental shelf were covered by the British–Irish Ice Sheet (BIIS). An earlier compilation from the existing literature (BRITICE version 1) assembled the relevant glacial geomorphological evidence into a freely available GIS geodatabase and map (Clark et al. 2004: Boreas 33, 359). New high‐resolution digital elevation models, of the land and seabed, have become available casting the glacial landform record of the British Isles in a new light and highlighting the shortcomings of the V.1 BRITICE compilation. Here we present a wholesale revision of the evidence, onshore and offshore, to produce BRITICE version 2, which now also includes Ireland. All published geomorphological evidence pertinent to the behaviour of the ice sheet is included, up to the census date of December 2015. The revised GIS database contains over 170 000 geospatially referenced and attributed elements – an eightfold increase in information from the previous version. The compiled data include: drumlins, ribbed moraine, crag‐and‐tails, mega‐scale glacial lineations, glacially streamlined bedrock (grooves, roches moutonnées, whalebacks), glacial erratics, eskers, meltwater channels (subglacial, lateral, proglacial and tunnel valleys), moraines, trimlines, cirques, trough‐mouth fans and evidence defining ice‐dammed lakes. The increased volume of features necessitates different map/database products with varying levels of data generalization, namely: (i) an unfiltered GIS database containing all mapping; (ii) a filtered GIS database, resolving data conflicts and with edits to improve geo‐locational accuracy (available as GIS data and PDF maps); and (iii) a cartographically generalized map to provide an overview of the distribution and types of features at the ice‐sheet scale that can be printed at A0 paper size at a 1:1 250 000 scale. All GIS data, the maps (as PDFs) and a bibliography of all published sources are available for download from: https://www.sheffield.ac.uk/geography/staff/clark_chris/britice.

1 December 2015 in Earth-Science Reviews
Verified
Journal Article
Open access
IBIestyn Barr
Iestyn Barr
MSMatteo Spagnolo
Matteo Spagnolo

1 December 2014 in Geomorphology
Verified
Journal Article
Closed access
IBIestyn Barr
Iestyn Barr
HLHarold Lovell
Harold Lovell

21 September 2021 in Journal of Glaciology
Verified
Journal Article
Open access
PDF file
RORachel P. Oien
Rachel P. Oien
BRBrice R. Rea
Brice R. Rea
MSMatteo Spagnolo
Matteo Spagnolo
IBIestyn Barr
Iestyn Barr
RBRobert G. Bingham
Robert G. Bingham
In this study, we compare equilibrium-line altitudes (ELAs) calculated using the area–altitude balance ratio (AABR) and the accumulation–area ratio (AAR) methods, with measured ELAs derived from direct field observations. We utilise a GIS toolbox to calculate the ELA for 64 extant glaciers by applying the AABR and AAR methods to DEMs and polygons of their geometry. The calculated ELAs (c-ELAs) are then compared to measured zero-net balance ELAs (znb-ELAs) obtained from mass-balance time series held by the WGMS for the same glaciers. The correlation between znb-ELAs and AABR (1.56)/AAR (0.58) c-ELAs is very strong, with an r2 = 0.99. The smallest median difference between znb-ELAs and c-ELAs (i.e. 65.5 m) is obtained when a globally representative AABR of 1.56 is used. When applied to palaeoglacier-climate applications, this difference translates to ~0.42°C, well within the uncertainty of palaeotemperature proxies used to determine mean summer temperature at the ELA. The more widely used mean AABR of 1.75 is shown to be statistically invalid due to the skewness of the dataset. On this basis, when calculating glacier ELAs, we recommend the use of a global AABR value of 1.56.