Kirsty Langley

Dr. Kirsty Langley

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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18 May 2020 in Ecosystems
Verified
Journal Article
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TCT. R. Christensen
T. R. Christensen
MLM. Lund
M. Lund
KSK. Skov
K. Skov
JAJakob Abermann
Jakob Abermann
ELE. López-Blanco
E. López-Blanco
MMM. Mastepanov
M. Mastepanov
The Arctic is getting warmer and wetter. Here, we document two independent examples of how associated extreme precipitation patterns have severe implications for high Arctic ecosystems. The events stand out in a 23-year record of continuous observations of a wide range of ecosystem parameters and act as an early indication of conditions projected to increase in the future. In NE Greenland, August 2015, one-quarter of the average annual precipitation fell during a 9-day intensive rain event. This ranked number one for daily sums during the 1996–2018 period and caused a strong and prolonged reduction in solar radiation decreasing CO2uptake in the order of 18–23 g C m−2, a reduction comparable to typical annual C budgets in Arctic tundra. In a different type of event, but also due to changed weather patterns, an extreme snow melt season in 2018 triggered a dramatic gully thermokarst causing rapid transformation in ecosystem functioning from consistent annual ecosystem CO2uptake and low methane exchange to highly elevated methane release, net source of CO2, and substantial export of organic carbon downstream as riverine and coastal input. In addition to climate warming alone, more frequent occurrence of extreme weather patterns will have large implications for otherwise undisturbed tundra ecosystems including their element transport and carbon interactions with the atmosphere and ocean.

25 August 2018 in Remote Sensing
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Journal Article
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LSLouise Sandberg Sørensen
Louise Sandberg Sørensen
Sebastian Bjerregaard SimonsenSebastian Bjerregaard Simonsen
Sebastian Bjerregaard Simonsen
KLKirsty Langley
Kirsty Langley
LGLaurence Gray
Laurence Gray
VHVeit Helm
Veit Helm
MDMalcolm W.J. Davidson
Malcolm W.J. Davidson
The study presented here is focused on the assessment of surface elevations derived from CryoSat-2 SARIn level 1b data over the Austfonna ice cap, Svalbard, in 2016. The processing chain that must be applied to the CryoSat-2 waveforms to derive heights is non-trivial, and consists of multiple steps, all requiring subjective choices of methods such as the choice of retracker, geo-relocation, and outlier rejection. Here, we compare six CryoSat-2 level-2 type data sets of surface elevations derived using different SARIn processing chains. These data sets are validated against surface elevation data collected from an airborne laser scanner, during a dedicated CryoSat validation experiment field campaign carried out in April 2016. The flight pattern of the airborne campaign was designed so that elevations were measured in a grid pattern rather than along single lines, as has previously been the standard procedure. The flight grid pattern was chosen to optimize the comparison with the CryoSat-2 SARIn elevation data, the location of which can deviate from nadir by several kilometers due to topography within the satellite footprint. The processing chains behind the six data sets include different outlier/error rejection approaches, and do not produce the same number of data points in our region of interest. To make a consistent analysis, we provide statistics from the validation of both the full data sets from each processing chain, and on only those data that all the six data sets provide a geo-located elevation estimate for. We find that the CryoSat-2 data sets that agree best with the validation data are those derived from dedicated land ice processing schemes. This study may serve as a benchmark for future CryoSat-2 retracker developments, and the evaluation software and data set are made publicly available.

24 August 2020 in Environment: Science and Policy for Sustainable Development
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Journal Article
Open access
TMTwila Moon
Twila Moon
TSTed Scambos
Ted Scambos
WAWaleed Abdalati
Waleed Abdalati
AAAndreas P. Ahlstrøm
Andreas P. Ahlstrøm
RBRobert Bindschadler
Robert Bindschadler
MTMartin Truffer
Martin Truffer
(2020). Ending a Sea of Confusion: Insights and Opportunities in Sea-Level Change Communication. Environment: Science and Policy for Sustainable Development: Vol. 62, No. 5, pp. 4-15.

7 July 2023 in Geosciences
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Journal Article
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MKMarko Kaasik
Marko Kaasik
OMOuti Meinander
Outi Meinander
Leena LeppänenLeena Leppänen
Leena Leppänen
KAKati Anttila
Kati Anttila
PWPavla Dagsson Waldhauserova
Pavla Dagsson Waldhauserova
Ali Nadir ArslanAli Nadir Arslan
Ali Nadir Arslan
Snow sampling, either by inserting a tube through the entire snowpack or by taking samples from the vertical profile, is widely applied to measure the snow depth, density, and snow water equivalent (SWE). A comparative study of snow-sampling methods was carried out on 24 March 2022 in Sodankylä, Finland. Six groups from five countries (Estonia, Finland, Greenland, Iceland, and Sweden) participated, using 12 different snow samplers, including 9 bulk tube samplers and 3 density cutters. The cross-sectional area of the SWE samplers varied from 11 to 100 cm2, while tube length varied from 30 cm to 100 cm. The cross-sectional area of the density profile cutters varied from 100 cm2 to 200 cm2 and the vertical sampling step varied from 5 cm to 10 cm. The samples were taken from snow pits in 55–65-centimeter-deep snow cover in a flat area with sparse pine trees, with the pits at a maximum distance of 10 m from each other. Each tube sampling series consisted of 3–10 vertical columns to ensure statistical validation. The snowpack was relatively soft, with two moderately hard crust layers. The density recorded in the tube sample measurements varied from 218 to 265 kgm−3. The measurement results of SWE, however, varied depending on the sampling equipment used, ranging from 148 to 180 kgm−2, with two outliers of 77 and 106 kgm−2, both with 11 cm2 samplers.

1 January 2013 in Journal of Glaciology
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Journal Article
Open access
RHRobert L. Hawley
Robert L. Hawley
OBOla Brandt
Ola Brandt
TDThorben Dunse
Thorben Dunse
JHJon Ove Hagen
Jon Ove Hagen
VHVeit Helm
Veit Helm
KHKjell-Arild Høgda
Kjell-Arild Høgda
Winter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received altimeter waveforms over Austfonna ice cap, Svalbard. Additionally, we attempt to distinguish the long-term firn area from other glacier facies. We validate our results using snow depth and glacier facies characterizations determined from ground-based radar profiles, snow pits and a multi-look satellite synthetic aperture radar image. We show that the depth of the winter snowpack can be extracted from the altimeter data over most of the accumulation zone, comprising wet snow zone and a superimposed ice zone. The method struggles at lower elevations where internal reflections within the winter snowpack are strong and the winter snow depth is less than ∼1 m. We use the abruptness of the reflection from the last summer surface (LSS) to attempt to distinguish glacier facies. While there is a general correlation between LSS abruptness and glacier facies, we do not find a relationship that warrants a distinct classification based on ASIRAS waveforms alone.

7 March 2022 in Permafrost and Periglacial Processes
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Journal Article
Open access
JAJakob Abermann
Jakob Abermann
KLKirsty Langley
Kirsty Langley
Rock glaciers (RGs) are landscape features impacting the composition and magnitude of runoff and, given their ice content, they are used as indicators for past and present climate conditions. While our knowledge of RG coverage has improved over recent years in many mountainous regions, there is very little information available for RGs in Greenland. Here, we provide evidence for an active RG in West Greenland, about 230 km south of what previously has been identified as the southern limit of active RGs. We present field evidence such as bottom temperature of the snow pack and surface displacements and indicate how these results could be utilized in further studies to better assess RG distribution or their ice content.