PANGAEA - Data Publisher for Earth &amp; Environmental Science

Felden, Janine; Möller, Lars; Schindler, Uwe; Huber, Robert; Schumacher, Stefanie; Koppe, Roland; Diepenbroek, Michael; Glöckner, Frank Oliver

doi:10.1038/s41597-023-02269-x

Cited by 17 publications

(7 citation statements)

References 16 publications

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“…For the surface type classification, the sea ice concentration at the dropsonde launch location was obtained from satellite observations (Kern et al, 2020, for REFLEX andMelsheimer andSpreen, 2019, for STABLE andAFLUX). If the sea ice concentration was below 15 %, then the profile is considered to represent conditions over open ocean, while a sea ice concentration above 85 % corresponds to a sea-icecovered ocean.…”

Section: Temperature Profiles In the Fram Straitmentioning

confidence: 99%

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

Linke,

Quaas,

Baumer

et al. 2023

Atmos. Chem. Phys.

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Abstract. The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiaġvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

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Section: Temperature Profiles In the Fram Straitmentioning

confidence: 99%

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

Linke,

Quaas,

Baumer

et al. 2023

Atmos. Chem. Phys.

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“…Training datasets originating from academic outlets, such as CoreTrustSeal certified data‐publishers like PANGAEA or in peer‐reviewed data journals, undergo rigorous data collection, annotation, and quality control processes. These measures ensure the data meets scientific standards and complies with legal and ethical requirements (Chavan & Penev, 2011; Felden et al, 2023). Furthermore, they are distributed with clear licences, specifically curated for research, and are fully citable through Digital Object Identifiers (DOIs).…”

Section: The Ethics Of Utilizing Online Media For Ai Trainingmentioning

confidence: 99%

Conserve the open media ecosystem! Legal and ethical considerations when using online repositories for AI training in ecological research

Lilkendey

2023

Ecology Letters

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Ecological researchers who train Artificial Intelligence models using digital media have to be cognizant of legal and ethical implications when sourcing such content from online repositories. The way forward? Complying with Creative Commons licensing requirements, obtaining consent from media creators and adhering to FAIR data principles. Collective action from researchers, repositories, licence providers, and legislators is needed to conserve this complex open media ecosystem. This way, we can continue to develop innovative applications to address pressing ecological issues while maintaining the trust of content creators and respecting the legal and ethical framework of online media use.

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“…All data sets used in this work are open source. The “Physicochemical, particulate matter, temperature, and hydrological data sets collected from climate‐threatened glacial river headwaters on the eastern slopes of the Canadian Rocky Mountains (2019–2021)” that form the basis of this manuscript are available in the PANGAEA data repository (Felden et al., 2023) at https://doi.org/10.1594/PANGAEA.963863 (Serbu et al., 2023). Map base layers produced by Alberta Environment and Parks are from Alberta ArcHydro Phase 2 Data (https://open.alberta.ca/opendata/gda-d22f5906-358e-47b9-9259-02702932a7a0#summary; Alberta Environment and Parks, 2018).…”

Section: Data Availability Statementmentioning

confidence: 99%

A Comprehensive Biogeochemical Assessment of Climate‐Threatened Glacial River Headwaters on the Eastern Slopes of the Canadian Rocky Mountains

Serbu,

St. Louis,

Emmerton

et al. 2023

JGR Biogeosciences

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Climate change is driving the loss of alpine glaciers globally, yet investigations about the water quality of rivers stemming from them are few. Here we provide an overview assessment of a biogeochemical data set containing 200+ parameters that we collected between 2019 and 2021 from the headwaters of three such rivers (Sunwapta‐Athabasca, North Saskatchewan, and Bow) which originate from the glacierized eastern slopes of the Canadian Rocky Mountains. We used regional hydrometric data sets to accurately model discharge at our 14 sampling sites. We created a Local Meteoric Water Line (LMWL) using riverine water isotope signatures and compared it to collected regional rain, snow, and glacial ice signatures. Principal component analyses of river physicochemical measures revealed distance from glacier explained more data variability than other spatiotemporal factors (i.e., season, year, or river). Discharge, chemical concentrations, and watershed areas were then used to model site‐specific open water season yields for 25 parameters. Chemical yields followed what would generally be expected along river continuums from glacierized to montane altitudinal life zones, with landscape characteristics driving chemical sources and sinks. For instance, particulate chemical yields were generally highest near source glaciers with proglacial lakes acting as settling ponds, whereas most dissolved yields varied by parameter and site. As these headwaters continue to evolve with glacier mass loss, the data set and analyses presented here can be used as a contemporary baseline to mark future change against. Further, following this initial assessment of our data set, we encourage others to mine it for additional biogeochemical studies.

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PANGAEA - Data Publisher for Earth & Environmental Science

Cited by 17 publications

References 16 publications

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

Conserve the open media ecosystem! Legal and ethical considerations when using online repositories for AI training in ecological research

A Comprehensive Biogeochemical Assessment of Climate‐Threatened Glacial River Headwaters on the Eastern Slopes of the Canadian Rocky Mountains

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