Kathrin Naegeli

Mrs. Kathrin Naegeli


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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2 November 2021 in Earth System Dynamics
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MLMickaël Lalande
Mickaël Lalande
MMMartin Ménégoz
Martin Ménégoz
GKGerhard Krinner
Gerhard Krinner
KNKathrin Naegeli
Kathrin Naegeli
SWStefan Wunderle
Stefan Wunderle
Climate change over High Mountain Asia (HMA, including the Tibetan Plateau) is investigated over the period 1979–2014 and in future projections following the four Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. The skill of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models is estimated for near-surface air temperature, snow cover extent and total precipitation, and 10 of them are used to describe their projections until 2100. Similarly to previous CMIP models, this new generation of general circulation models (GCMs) shows a mean cold bias over this area reaching −1.9 [−8.2 to 2.9] ∘C (90 % confidence interval) in comparison with the Climate Research Unit (CRU) observational dataset, associated with a snow cover mean overestimation of 12 % [−13 % to 43 %], corresponding to a relative bias of 52 % [−53 % to 183 %] in comparison with the NOAA Climate Data Record (CDR) satellite dataset. The temperature and snow cover model biases are more pronounced in winter. Simulated precipitation rates are overestimated by 1.5 [0.3 to 2.9] mm d−1, corresponding to a relative bias of 143 % [31 % to 281 %], but this might be an apparent bias caused by the undercatch of solid precipitation in the APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) observational reference. For most models, the cold surface bias is associated with an overestimation of snow cover extent, but this relationship does not hold for all models, suggesting that the processes of the origin of the biases can differ from one model to another. A significant correlation between snow cover bias and surface elevation is found, and to a lesser extent between temperature bias and surface elevation, highlighting the model weaknesses at high elevation. The models with the best performance for temperature are not necessarily the most skillful for the other variables, and there is no clear relationship between model resolution and model skill. This highlights the need for a better understanding of the physical processes driving the climate in this complex topographic area, as well as for further parameterization developments adapted to such areas. A dependency of the simulated past trends on the model biases is found for some variables and seasons; however, some highly biased models fall within the range of observed trends, suggesting that model bias is not a robust criterion to discard models in trend analysis. The HMA median warming simulated over 2081–2100 with respect to 1995–2014 ranges from 1.9 [1.2 to 2.7] ∘C for SSP1-2.6 to 6.5 [4.9 to 9.0] ∘C for SSP5-8.5. This general warming is associated with a relative median snow cover extent decrease from −9.4 % [−16.4 % to −5.0 %] to −32.2 % [−49.1 % to −25.0 %] and a relative median precipitation increase from 8.5 % [4.8 % to 18.2 %] to 24.9 % [14.4 % to 48.1 %] by the end of the century in these respective scenarios. The warming is 11 % higher over HMA than over the other Northern Hemisphere continental surfaces, excluding the Arctic area. Seasonal temperature, snow cover and precipitation changes over HMA show a linear relationship with the global surface air temperature (GSAT), except for summer snow cover which shows a slower decrease at strong levels of GSAT.

27 January 2017 in Remote Sensing
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KNKathrin Naegeli
Kathrin Naegeli
ADAlexander Damm
Alexander Damm
MHMatthias Huss
Matthias Huss
HWHendrik Wulf
Hendrik Wulf
XXXxx Xxx
Xxx Xxx
MHMartin Hoelzle
Martin Hoelzle
Surface albedo partitions the amount of energy received by glacier surfaces from shortwave fluxes and modulates the energy available for melt processes. The ice-albedo feedback, influenced by the contamination of bare-ice surfaces with light-absorbing impurities, plays a major role in the melting of mountain glaciers in a warming climate. However, little is known about the spatial and temporal distribution and variability of bare-ice glacier surface albedo under changing conditions. In this study, we focus on two mountain glaciers located in the western Swiss Alps and perform a cross-comparison of different albedo products. We take advantage of high spectral and spatial resolution (284 bands, 2 m) imaging spectrometer data from the Airborne Prism Experiment (APEX) and investigate the applicability and potential of Sentinel-2 and Landsat 8 data to derive broadband albedo products. The performance of shortwave broadband albedo retrievals is tested and we assess the reliability of published narrow-to-broadband conversion algorithms. The resulting albedo products from the three sensors and different algorithms are further cross-compared. Moreover, the impact of the anisotropy correction is analysed depending on different surface types. While degradation of the spectral resolution impacted glacier-wide mean albedo by about 5%, reducing the spatial resolution resulted in changes of less than 1%. However, in any case, coarser spatial resolution was no longer able to represent small-scale variability of albedo on glacier surfaces. We discuss the implications when using Sentinel-2 and Landsat 8 to map dynamic glaciological processes and to monitor glacier surface albedo on larger spatial and more frequent temporal scales.

24 November 2020 in Earth System Science Data
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EWEthan Welty
Ethan Welty
MZMichael Zemp
Michael Zemp
FNFrancisco Navarro
Francisco Navarro
MHMatthias Huss
Matthias Huss
JFJohannes J. Fürst
Johannes J. Fürst
GCGlaThiDa Contributors
GlaThiDa Contributors
Although worldwide inventories of glacier area have been coordinated internationally for several decades, a similar effort for glacier ice thicknesses was only initiated in 2013. Here, we present the third version of the Glacier Thickness Database (GlaThiDa v3), which includes 3 854 279 thickness measurements distributed over roughly 3000 glaciers worldwide. Overall, 14 % of global glacier area is now within 1 km of a thickness measurement (located on the same glacier) – a significant improvement over GlaThiDa v2, which covered only 6 % of global glacier area and only 1100 glaciers. Improvements in measurement coverage increase the robustness of numerical interpolations and model extrapolations, resulting in better estimates of regional to global glacier volumes and their potential contributions to sea-level rise. In this paper, we summarize the sources and compilation of glacier thickness data and the spatial and temporal coverage of the resulting database. In addition, we detail our use of open-source metadata formats and software tools to describe the data, validate the data format and content against this metadata description, and track changes to the data following modern data management best practices. Archived versions of GlaThiDa are available from the World Glacier Monitoring Service (e.g., v3.1.0, from which this paper was generated: https://doi.org/10.5904/wgms-glathida-2020-10; GlaThiDa Consortium, 2020), while the development version is available on GitLab (https://gitlab.com/wgms/glathida, last access: 9 November 2020).

9 June 2021 in Geophysical Research Letters
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Martina BarandunMartina Barandun
Martina Barandun
EPEric Pohl
Eric Pohl
KNKathrin Naegeli
Kathrin Naegeli
RMRobert McNabb
Robert McNabb
MHMatthias Huss
Matthias Huss
MHMartin Hoelzle
Martin Hoelzle
The Tien Shan and Pamir mountains host over 28,000 glaciers providing essential water resources for increasing water demand in Central Asia. A disequilibrium between glaciers and climate affects meltwater release to Central Asian rivers, challenging the region's water availability. Previous research has neglected temporal variability. We present glacier mass balance estimates based on transient snowline and geodetic surveys with unprecedented spatiotemporal resolution from 1999/00 to 2017/18. Our results reveal spatiotemporal heterogeneity characterized by two mass balance clusters: (a) positive, low variability, and (b) negative, high variability. This translates into variable glacial meltwater release (≈1–16%) of annual river runoff for two watersheds. Our study reveals more complex climate forcing‐runoff responses and importance of glacial meltwater variability for the region than suggested previously.

1 November 2014 in Global and Planetary Change
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Journal Article
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IGI. Gärtner-Roer
I. Gärtner-Roer
KNKathrin Naegeli
Kathrin Naegeli
MHMatthias Huss
Matthias Huss
TKT. Knecht
T. Knecht
HMH. Machguth
H. Machguth
MZM. Zemp
M. Zemp
One of the grand challenges in glacier research is to assess the total ice volume and its global distribution. Over the past few decades the compilation of a world glacier inventory has been well-advanced both in institutional set-up and in spatial coverage. The inventory is restricted to glacier surface observations. However, although thickness has been observed on many glaciers and ice caps around the globe, it has not yet been published in the shape of a readily available database. Here, we present a standardized database of glacier thickness observations compiled by an extensive literature review and from airborne data extracted from NASA's Operation IceBridge. This database contains ice thickness observations from roughly 1100 glaciers and ice caps including 550 glacier-wide estimates and 750,000 point observations. A comparison of these observational ice thicknesses with results from area- and slope-dependent approaches reveals large deviations both from the observations and between different estimation approaches. For glaciers and ice caps all estimation approaches show a tendency to overestimation. For glaciers the median relative absolute deviation lies around 30% when analyzing the different estimation approaches. This initial database of glacier and ice caps thickness will hopefully be further enlarged and intensively used for a better understanding of the global glacier ice volume and its distribution

1 February 2019 in The Cryosphere
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KNKathrin Naegeli
Kathrin Naegeli
MHMatthias Huss
Matthias Huss
MHMartin Hoelzle
Martin Hoelzle
Albedo feedback is an important driver of glacier melt over bare-ice surfaces. Light-absorbing impurities strongly enhance glacier melt rates but their abundance, composition and variations in space and time are subject to considerable uncertainties and ongoing scientific debates. In this study, we assess the temporal evolution of shortwave broadband albedo derived from 15 end-of-summer Landsat scenes for the bare-ice areas of 39 large glaciers in the western and southern Swiss Alps. Trends in bare-ice albedo crucially depend on the spatial scale considered. No significant negative temporal trend in bare-ice albedo was found on a regional to glacier-wide scale. However, at higher spatial scales, certain areas of bare ice, including the lowermost elevations and margins of the ablation zones, revealed significant darkening over the study period 1999 to 2016. A total glacier area of 13.5 km2 (equivalent to about 12 % of the average end-of-summer bare-ice area in the study area) exhibited albedo trends significant at the 95 % confidence level or higher. Most of this area was affected by a negative albedo trend of about −0.05 decade−1. Generally, bare-ice albedo exhibits a strong interannual variability, caused by a complex interplay of meteorological conditions prior to the acquisition of the data, local glacier characteristics and the date of the investigated satellite imagery. Although a darkening of glacier ice was found to be present over only a limited region, we emphasize that due to the recent and projected growth of bare-ice areas and prolongation of the ablation season in the region, the albedo feedback will considerably enhance the rate of glacier mass loss in the Swiss Alps in the near future.