
26 March 2025 | 16:00 - 18:00 (MDT)
Open Session - HYBRID
Room: UMC Third Floor - 384
Organisers: Rohit Srivastava (National Centre for Polar and Ocean Research, India); Archana Singh (National Centre for Polar and Ocean Research, India); Dariusz Ignatiuk (University of Silesia in Katowice, Poland)
Zoom link to the Session (password-protected)
The password needed to connect to the session will be distributed the day prior to the start of the sessions to all registered conference participants. Further guidelines on how to participate virtually in the ASSW 2025 can be found on the ASSW 2025 website.
Session Description:
Scientific Observation Networks are essential for advancing our understanding of Arctic environmental dynamics and their impact on global climate change. By monitoring key indicators and collecting long-term data, these networks enable scientists to assess the state of the Arctic ecosystem, identify emerging trends, and inform policymakers and society about the need for effective strategies to mitigate and adapt to ongoing environmental changes.
Arctic Scientific Observation Networks typically combine ground-based observatories, remote sensing platforms, autonomous instruments, and satellite technologies. Their primary goal is to gather data on key indicators such as sea ice extent and thickness, ocean currents, biodiversity, meteorological parameters, atmospheric composition, glacier and snow dynamics, and changes in the state of permafrost.
Creating Scientific Observation Networks involves many challenges, including the long-term financing system, national or international structure, and the use of solutions limiting carbon footprint. Standardization and harmonization of observations, together with data sharing in accordance with FAIR standards, are among the most important challenges facing networks. Maintaining Arctic Scientific Observation Networks is crucial to the development of research, calibration, and validation of Earth System Models and remote-sensing products.
The session invites Abstracts from small and big-scale observation networks in the Arctic presenting their execution, scientific outcomes, and the logistical and technological challenges in setup, deployment, monitoring, data acquisition, data sharing, etc.
Instructions for Speakers: Oral presentations in this session should be at most 10-minutes in length, with an additional 2-3 minutes for questions (unless more detailed instructions are provided by session conveners). See more detailed presenter instructions here.
Oral Presentations:
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unfold_moreArctic Beaver Observation Network and the future of lowland tundra ecosystems — Ken Tape
Ken Tape 1; Helen Wheeler 2; Benjamin Jones 3; Mikhaela Neelin 4
1 University of Alaska Fairbanks; 2 Anglia Ruskin University; 3 University of Alaska; 4 Nunanvik Hunters & Trappers AssociationFormat: Oral in-person
Abstract:
The Arctic Beaver Observation Network is a group of research scientists, Indigenous observers, and land managers from the U.S., Canada, and Europe, who are working to understand the scale and implications of beaver colonization of the Arctic. Collaboration across disciplines, and indeed across cultures, has enriched our understanding of this relatively new phenomenon. Remote sensing and modeling indicate that beavers have constructed over 10,000 ponds in the Alaska Arctic, and are predicted to expand their range to the entire North Slope of Alaska by 2090 under moderate climate change scenarios (RCP 6.0). Similar trends have been observed and are expected in northern Canada. Field measurements indicate that beavers are targeting tundra streams with groundwater inputs, and that their ponds are increasing unfrozen water in winter, which thaws permafrost and initially releases methane surrounding these streams. Biological studies are underway to examine the impact of beaver engineering on riparian plant diversity, aquatic communities, and avian communities. We anticipate that the effects of these oases will be to increase local terrestrial and aquatic biodiversity as the physical constraints of wintertime conditions are relaxed. Current and developing studies will focus research on local subsistence resources such as clean water and fish. Our growing understanding of this issue is shared among members of the Arctic Beaver Observation Network at biennial meetings and more regularly through community visits and collaborations.
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unfold_moreDecadal Glacier Dynamics in Nunavut's Sirmilik and Auyuittuq National Parks: A Photogrammetric Analysis of Historical Aerial Photographs (1958 - 2023) — Wilson (Wai Yin) Cheung
Wilson (Wai Yin) Cheung 1
1 Queen's UniversityFormat: Oral in-person
Abstract:
Understanding Arctic glacier dynamics is essential for predicting future sea-level rise and assessing the regional climate's impact on Arctic societies, including communities such as Pond Inlet and Pangnirtung. This study examines six decades of glacier changes in Auyuittuq and Sirmilik National Parks on Baffin and Bylot Islands, Nunavut, Canada. Using photogrammetry of historical aerial photographs from 1958-2023, alongside modern satellite imagery and high-resolution DEMs, we document significant glacier retreat and thinning. In Auyuittuq, glaciers like Nakarpog and Nerutusoq experienced notable reductions in length (up to 15.82%) and area (up to 19.94%), reflecting the effects of climate warming. In Sirmilik, Fountain Glacier showed pronounced thinning (elevation loss of -24.90 ± 1.77 m water equivalent), with minimal areal change, indicating the complexity of polythermal glacier behavior.
Methodological advancements, such as ArcticDEM and hypsometric interpolation, helped address challenges like data voids and photogrammetric errors, increasing the accuracy of our findings. These results have important implications for predicting future glacier contributions to sea-level rise and for understanding the broader impacts on Arctic hydrology and ecosystems. For local communities, glacier changes affect freshwater availability, hunting routes, and traditional livelihoods. This research enhances understanding of glacier mass balance trends in the Arctic and contributes to improved models for predicting glacier behavior under ongoing climate change, offering crucial insights for future environmental and societal adaptation strategies.
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unfold_moreBuilding a regional international and multidisciplinary observing network - the SIOS story — Heikki Lihavainen
Heikki Lihavainen 1; Eleanor Jones 1; Rudolf Denkmann 1; Daan Kivits 1; Ashley Morris 1; Christiane Hübner 1; Ilkka Matero 1
1 SIOS-KCFormat: Oral in-person
Abstract:
Svalbard Integrated Arctic Earth Observing System (SIOS) is an international consortium of 28 research institutions from 10 countries with research interests and infrastructure in and around the Norwegian Arctic archipelago of Svalbard. Within SIOS, researchers collaborate by sharing data and research infrastructure to build an efficient observing system. SIOS focuses on long-term monitoring of parameters that are important to understand the Arctic in the context of global environmental change. SIOS has its own data management system where Earth System Science data in and around Svalbard can be found. SIOS provides also help and tools to publish data following FAIR principles. SIOS also provides joint activities and services to its members. Some of these, such as the Data Access Portal and the Access Programme, are open to all, regardless of membership. SIOS is one node amongst the other Arctic observing systems.
The idea of SIOS was first introduced in 2007 and it entered its operational phase in 2018. Our vision is to be the leading comprehensive long-term observing system in the Arctic to serve Earth system Science. SIOS activities are based on three three pillars: Joint activities, Services and Sustainability. These pillars are supported by five active working groups and several task forces. SIOS Knowledge Centre is the central hub, coordinating and facilitating SIOS activities.
In this presentation we will share our experiences on building SIOS, international and multidisciplinary research infrastructure, success stories, challenges and lessons learned.
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unfold_moreKeeping curiosity alive: Maintaining early career participation in long-term Arctic ecosystem monitoring — Christina Goethel
Christina Goethel 1; Clare Gaffey 2; Jacqueline Grebmeier 1; Lee Cooper 1; Karen Frey 2
1 University of Maryland Center for Environmental Science; 2 Clark UniversityFormat: Oral in-person
Abstract:
Long-term observational networks require both trained researchers and transitional pathways for researchers at all career stages. However, because of funding cycles and the length of degree programs, many early career researchers (ECRs) do not stay within long-term observational programs, losing continuity of valuable skills and training in leadership and management. We present two successful case studies that enabled ECRs to participate in observation networks: the Distributed Biological Observatory and the Synoptic Arctic Survey. As measurements and observations associated with these change detection arrays mature, the reliance on a network of cooperating scientists across multiple countries becomes essential for success. The involvement of ECRs in network-based observations enables a scientific workforce motivated to increasing national and international collaborations and strengthening Arctic and Subarctic marine observations. For these two networks, we will highlight the mechanisms that have enabled success for ECRs involvement in data collection and synthesis activities. Specific observations of ongoing ecosystem changes led by ECRs are demonstrated in a time series study of benthic communities and their phytoplankton food sources in the Pacific Arctic. Recent shifts in phytoplankton phenology owing to decreased spring sea ice cover appear to be one of the controlling factors in observed declines in bivalve biomass. Potential future outcomes for ecosystem structure will be discussed in the context of continued warming of seawater and decreased sea ice cover. We will also discuss the need for deliberate design features that provide opportunities for ECRs to effectively build upon current capabilities, including furthering long-term national and international collaborations.
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unfold_moreThe Distributed Biological Observatory (DBO): A Change Detection Array in the Pacific Arctic and Model for the UN Decade endorsed Pan-Arctic DBO Network — Lee Cooper
Lee Cooper 1; Jacqueline Grebmeier 1; Karen Frey 2; Christina Goethel 1; Sue Moore 3
1 University of Maryland Center for Environmental Science; 2 Clark University; 3 Center for Ecosystem Sentinels, University of WashingtonFormat: Oral in-person
Abstract:
The DBO, a component of the US Arctic Observing Network, resulted in part from national science planning. However, international coordination has always been a key goal of the DBO, and has been provided through the International Arctic Science Committee. International investment has also increased after the observational network was endorsed by the Pacific Arctic Group (PAG), a consortium of 6 core countries conducting research in the Pacific Arctic (Canada, China, Japan, Republic of Korea, Russia, USA). US funding to support the DBO continues, but success is also predicated upon separate national funding by countries of the PAG to their own scientific institutions. The DBO was formally implemented in 2010 to document ecosystem responses to ongoing environmental changes observed in the Arctic. It has developed into a change detection array to track interconnections of declining seasonal sea ice, warming water temperatures, stratification changes, and other processes that impact the marine ecosystem. Shipboard sampling of physical, chemical and biological features are undertaken as well as bird and marine mammal observations. Autonomous sensors on moorings, gliders, and satellite platforms are also used. The DBO concept has expanded into a nascent pan-Arctic DBO network, with parallel sites identified across the Arctic. This on-going construction of a pan-Arctic DBO Network has received endorsement from the UN Decade of Ocean Science for Sustainable Development. This presentation outlines the history of the DBO, and discusses its strengths and limitations, lessons learned from national and international coordination, and ongoing efforts to incorporate Indigenous community needs and knowledge.
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unfold_moreArena for the gap analysis of the existing Arctic Science Co-Operations (AASCO) — Hanna Lappalainen
Hanna Lappalainen 1; Tuukka Petäjä 1
1 University of HelsinkiFormat: Oral virtual
Abstract:
The "Arena for the gap analysis of the existing Arctic Science Co-Operations" AASCO project is coordinated by the University of Helsinki. Scientific partners are SAON-ROADS, University of Arctic, SIOS, WMO-GAW, CBAS and UNESCO-UNITAR. The project is funded by the Foundation Prince Albert II de Monaco for 2020-2025. The AASCO project is dedicated to understanding the feedback and interactions between land, ocean, and atmosphere in the Arctic-boreal context under changing climate. To effectively address these challenges, we recognize the need for a coordinated framework that considers the various perspectives from different disciplines. This involves better integration, improved information and data flows, and the ability to derive science-based synthesis and predictions from existing information through platforms and data services. The goal of the AASCO is to strengthen connections among existing research communities interested in feedback research. Additionally, the aim is to formulate a science-based message directed at Arctic research policymakers and funding agencies. This will help consolidate efforts and contribute to a more effective and coordinated approach in addressing environmental challenges in the Arctic. What are the Essential Research questions and Variables for land-atmosphere-ocean feedback & interactions research in the Arctic context? or are the EV already well coved by the current approach? Which are the relevant networks and communities whom could contribute to the identification of these EVs? In what ways can AI be helpful in combining different sets of data (data fusion)? We will report the outcomes of AASCO workshop held on February 2025 in Monaco.
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unfold_moreGround Observations of Sky Indicators: Leveraging Citizen Science to Monitor Polar Region Upper Atmospheric Characteristics of Climate Changes and Inform Adaptive Strategies — Yvette Gonzalez
Yvette Gonzalez 1; Adrien Mauduit 2; Shayla Redmond 3
1 University of Plymouth; 2 Night Lights Films; 3 Native Sky Inc.Format: Oral virtual
Abstract:
The Intergovernmental Panel on Climate Change report attempts to improve the understanding of a range of characteristics causing climate change. These characteristics are limited, and any future predictive climate models will have to be based on proven causal pathways. Noctilucent Clouds (NLCs) might be one such pathway. These upper atmospheric “ice” clouds may be our only current visual window into changes in the atmosphere, informing how increased carbon dioxide and methane in NLCs might demonstrate one cause of global temperature increase. While typically NLCs were observed by NASA’s Aeronomy of Ice in the Mesosphere (AIM) program, it stopped collecting data in March 2023 following failure of the spacecraft's battery. Since NLC observations take place at upper latitudes, there are communities across the planet that have access to viewing them with the naked eye and continue collecting ground observations. Our NLC observation community is 10k strong, using Facebook to collect novel data using a camera or smartphone. The team is now coordinating with the NASA GLOBE team to integrate NLC observations into their dataset, pairing data with remote sensing, arctic researchers, and polar platforms to further analyze the collective information. This puts the power of participation in the hands of citizens, offers a higher quantity of data, and increases our ability to support the UN Global Goals, notably Goal 13 “Climate Action”. This open science effort has the potential to inform polar environmental policies and adaptive strategies for Arctic and other higher latitude communities facing rapid climate deterioration.
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unfold_morePOLar AERosol NETwork (POLAERNET) — Rohit Srivastava
Rohit Srivastava 1; Ritesh Kumar 1
1 National Centre for Polar and Ocean Research (NCPOR)Format: Oral in-person
Abstract:
Arctic aerosols play a crucial yet often underappreciated role in the region’s climate system. These aerosols originate from natural sources, such as sea spray, as well as human activities and forest fires. They influence the Arctic’s energy balance by either scattering sunlight, which cools the atmosphere, or absorbing radiation, which contributes to warming. When aerosols settle on snow and ice, they darken the surface, reducing its reflectivity (albedo) and accelerating melting. This contributes to Arctic amplification, where warming in the region occurs nearly four times faster than the global average. Aerosols also interact with clouds, altering their properties and lifespans, further complicating the region’s climate dynamics.
However, the role of aerosols in Arctic climate change remains poorly understood, creating significant uncertainty in future predictions. Continuous long-term observations are essential for addressing this knowledge gap. Monitoring aerosols in the Arctic using satellite remote sensing is challenging due to the high reflectivity of snow and ice, as well as the long polar nights.
The National Centre for Polar and Ocean Research (NCPOR) in India is developing the POLar AERosol NETwork (POLAERNET) to monitor aerosols in the Arctic, Antarctic, and Himalayan regions. Aerosol parameters such as black carbon mass concentration and aerosol absorption and scattering coefficients are being measured. This comprehensive dataset will quantify black carbon and aerosol properties in the Arctic, enabling the validation of climate models and satellite data. These improvements will enhance the accuracy of climate predictions, particularly in understanding anthropogenic impacts on the Arctic climate.
Poster Presentations (during Poster Exhibit and Session on Wednesday 26 March):
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unfold_moreEvaluating Snow Cover Dynamics Using Satellite Imagery in Utqiaġvik, Alaska — Valentina Ekimova
Valentina Ekimova 1; Howard Epstein 1; Matthew Jull 1; Leena Cho 1; Mirella Shaban 1; MacKenzie Nelson 1
1 The University of VirginiaFormat: Poster in-person
Poster number: 469
Abstract:
Alaska, with 80-85% of its land underlain by permafrost, is highly vulnerable to climate warming. Rising temperatures accelerate permafrost thaw, leading to infrastructure damage and environmental impacts. Snow cover, which insulates the frozen ground, is a key factor in permafrost stability. With ongoing climate change, main snow cover parameters —such as area, thickness, density, albedo —are changing, impacting the thermal regime of permafrost.
Traditionally, snow studies relied on field data collection, constrained by harsh conditions and remoteness. To overcome these limitations, we analyzed snow parameters using satellite imagery from 2017 to 2024 in Utqiaġvik, Alaska. We used PlanetScope and Sentinel-2 multispectral data, supplemented with passive microwave data (MODIS and AMSR-E/AMSR2) from NASA’s Earthdata Portal. Key parameters, including the Normalized Difference Snow Index (NDSI), snow density, and snow depth, were calculated.
Our analysis revealed spatial and temporal variability in snow cover, with a focus on differences between open tundra and urban areas affected by snow management. For example, between January and February 2024, we observed a slight decrease in snow cover in urban areas, likely due to snow removal practices. NDSI values in April ranged from 0 to 1 in urban areas but remained stable around 0.4 in the tundra, reflecting less disturbance. Additionally, snow density in urban areas increased significantly from January to April, from 200 kg/m³ to 479 kg/m³.
This research offers valuable insights for modeling snow cover, ground temperature, and permafrost behavior, enhancing our understanding of the changing Arctic landscape.
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unfold_moreExploring Permafrost and Subsurface Features in Arctic Urban and Tundra Areas through GPR and ERT — Valentina Ekimova
Valentina Ekimova 1; MacKenzie Nelson 1; Taylor Sullivan 2; Thomas A. Douglas 2; Howard Epstein 1; Matthew Jull 1; Mirella Shaban 1
1 The University of Virginia; 2 CRRELFormat: Poster in-person
Poster number: 482
Abstract:
In the context of ongoing climate warming, Arctic regions require detailed research, particularly concerning permafrost degradation and the dynamics of subsurface features. Geophysical surveying is a key method in permafrost research. During the 2021–2023 field seasons, we employed ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) to investigate active layer depth and subsurface features around various infrastructure elements in Utqiaġvik, Alaska. GPR and ERT effectively monitor active layer variations; however, analyzing subsurface features (e.g., ice wedges, high-ice-content zones, ice lenses, and cryopegs) presents challenges due to technical constraints. Noise can result from dry surface materials, such as air-filled gravel, or from interference caused by subsurface metal objects.
To validate and enhance the geophysical data, we combined it with ground temperature and moisture measurements down to 90 cm depth and high-resolution satellite imagery from Planet SkySat for landscape feature detection. We identified ice wedges in open tundra near a road and at the Barrow Environmental Observatory (BEO) site, while at urban infrastructure sites (e.g., a Taġiuġmiullu Nunamiullu Housing Authority apartment building and the Samuel Simmonds Memorial Hospital), we observed a mix of thawed zones, high-ice-content areas, and highly saline cryopegs.This research demonstrates that integrating GPR, ERT, and supplementary data sources improves the precision of permafrost studies, particularly in detecting active layer dynamics and subsurface features. While the analysis is ongoing, initial observations indicate significant variability in permafrost structure beneath urban infrastructure compared to open tundra areas.
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unfold_moreA new all-year round CO2 fluxes multi-instrumental observatory in the High Arctic Tundra — Mariasilvia Giamberini
Mariasilvia Giamberini 1; Ilaria Baneschi 1; Letizia Costanza 1; Simona Gennaro 1; Matteo Lelli 1; Jasmine Natalini 1; Brunella Raco 1; Gianna Vivaldo 1; Antonello Provenzale 1
1 Institute of Geoscience and Earth Resources - National Research Council of ItalyFormat: Poster in-person
Poster number: 58
Abstract:
Arctic amplification is causing rapid changes in the tundra carbon cycle, which may lead to transforming the tundra from a carbon sink into a carbon source. The all-year-long CO2 cycle monitoring is challenging due to remoteness, winter weather conditions and lack of infrastructures. Nevertheless, all-year data are extremely precious, as winter emissions are the "great unknown" of the Arctic carbon cycle (Natali S, Nature, 2019). Most studies focus on the short summer season, making it difficult to provide an accurate tundra carbon budget. To address this, we have fully exploited the facilities offered by the permanent Ny Ålesund research station in the Svalbard Archipelago (NO) and we established a comprehensive observatory to measure CO2 fluxes at different scales and all-year-round, using various instruments such as portable flux chambers, Eddy Covariance and an array of below and above ground sensors to measure winter CO2 fluxes from the snowpack; this latter is particularly aimed at intercepting wind-burst emissions, when the Eddy Covariance fails due to the absence of vertical turbulence. Additionally, all set ups are complemented by meteorological stations. All data are made available following the FAIR principles through the Italian Arctic Data Centre, the Svalbard Integrated Observing System SIOS and a CNR Virtual Research Environment, also hosting a modelling environment. Our challenging goal is to develop an integrated open virtual laboratory for modeling Arctic CO2 fluxes at multiple scales and serving as seed for a pan-Arctic network of similar observatories, possibly including other observation platforms as airborne remote-sensing.
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unfold_moreRole of snowfall rate on the recent decadal loss of sea ice in the Arctic during summer seasons — Arnab Mukherjee
Arnab Mukherjee 1
1 National Centre for Polar and Ocean Research (NCPOR), Ministry of Earth Sciences (MoES), GOvernment of IndiaFormat: Poster in-person
Poster number: 173
Abstract:
In this study, the role of snowfall rate on the decadal decrease of sea-ice concentration (SIC) and increase of Sea Surface Temperature (SST) during the summer seasons of Arctic (June–September) has been performed using a global sea-ice coupled model and satellite observations. The model successfully simulates decadal weakening of SIC and the increase of SST between the decades of 2011–2020 and 2001–2010 in the Arctic during summer seasons.
A sensitivity experiment was performed after removing the snowfall atmospheric forcing in the model to understand the role of snowfall rate on the long-term variability of SIC and SST in the Arctic. It has been observed that after removing the snowfall rate in the model as a forcing, Arctic warming (loss of sea ice) is increased by the order of 5 - 10 %. Also, after removing snowfall forces in the model, sea ice thickness (SIT) in the Arctic significantly reduced. This implies that snowfall is a barrier between the atmosphere and ocean interaction processes. The strong decrease in the snowfall rate in the recent decade in the Arctic strengthens Arctic warming. Also, the maximum impact of snowfall rate on sea ice has been observed in the western Arctic compared to the eastern, which includes the Chukchi and Beaufort Sea regions. This study implies that continuous observations of snowfall rate and SIT using ground-based satellite observations are necessary to study long term trends of Arctic warming and sea ice loss.
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unfold_moreExploring ICESat-2 derived coastal elevation data for erosion quantification in the Arctic — Rafael Bendo Paulino
Rafael Bendo Paulino 1; Andre De Lima 1; Celso Ferreira 1; Tyler Miesse 1; Thomas Ravens 2; Paul Houser 1; William Najjar 2; Ries Tviet 2
1 George Mason University; 2 University of Alaska AnchorageFormat: Poster in-person
Poster number: 214
Abstract:
High-latitude regions are highly susceptible to the impacts of climate change, where the increases in temperature at twice the global average result in decreasing sea ice, sea-level rise, and permafrost thawing. Consequently, the frequency and intensity of extreme weather conditions can potentially cause unprecedented flooding and erosion on the coast, significantly impacting coastal communities. The NASA Ice, Cloud, and land Elevation Satellite (ICESat-2) provides a great opportunity to assist in monitoring and assessing natural disasters over space and time in remote polar coastal regions. However, the utilization of ICESAT-2 for monitoring and quantifying coastal erosion and landscape changes in the Arctic is still scarce in the literature. In this context, this research seeks to validate ICESat-2 elevation data for tracking coastal erosion and shoreline retreat in the Arctic. A framework that integrates ICESat-2 data, and available Arctic elevation datasets provided by federal and state agencies was developed to better quantify and understand the inherent uncertainties in utilizing the satellite data for shoreline monitoring. Thus, supporting a greater understanding of fundamental processes impacting Arctic coastal erosion, and investigating potential impacts of climate change on coastal erosion in the Arctic. These findings enhance the capacity to quantify and monitor changes in Arctic coastal erosion, including coastal bluff retreat, barrier island erosion, and permafrost collapse.
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unfold_moreLeveraging Data Assimilation for Accurate Sea Ice State Prediction-Sea Ice Albedo as an Alternative Observational Framework — Joseph Rotondo
Joseph Rotondo 1; Molly Weiringa 1; Cecilia Bitz 1; Robin Clancy 2; Steven Cavallo 2
1 University of Washington; 2 University of OklahomaFormat: Poster in-person
Poster number: 268
Abstract:
The Arctic is warming four times faster than the global average (Rantanen et al., 2022). This accelerated warming is evident in the rapid decline of sea ice, which not only serves as a critical indicator of climate change but also drives further warming through the ice albedo feedback loop. The decline in Arctic sea ice has far-reaching implications, including impacts on geopolitics, industrial development, and biodiversity. Accurately predicting future Arctic sea ice states is therefore a critical objective within the sea ice modeling community.
A perfect model experiment within Icepack, a one-dimensional single-column ice model, has been conducted to explore the potential of data assimilation in improving predictions of mean sea ice state by incorporating sea ice albedo. In this study, one ensemble member is designated as truth, and the sea ice characteristics from this truth member is assimilated into all other ensemble members. Data assimilation was performed using the Data Assimilation Research Testbed, which employs the Ensemble Adjustment Kalman Filter to directly solve the forward problem.
This approach was used to evaluate the significance of remote sensing for future ice albedo observations. The study found that albedo critically enhances predictions of future sea ice states when compared to commonly assimilated variables such as sea ice concentration and thickness. As a result, increasing the frequency and spatial distribution of albedo observations in the Arctic is essential. Enhanced observation networks will provide more accurate data, leading to better forecasting and a deeper understanding of sea ice dynamics in a changing climate.
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unfold_moreArctic Snowpack study using SAR data and in-situ observation in Alaska — Sreelekshmi S
Sreelekshmi S 1; Gulab Singh 1
1 Indian Institute of Technology BombayFormat: Poster in-person
Poster number: 295
Abstract:
This study explores the sensitivity of SAR (Synthetic Aperture Radar) backscatter to snow properties, emphasizing its utility in regions with complex terrain and variable weather conditions. Temporal analysis of SAR data reveals its ability to characterize snow properties where conventional co- and cross-polarization-based snow mapping methods often fail, particularly in areas with snow densities below 200 kg/m3. By integrating snow depth data of Alaska from NOAA, the study correlates temporal variations in SAR backscatter with snow characteristics such as depth and wetness, highlighting the significance of selecting optimal time periods for snow cover mapping. The study emphasizes the importance of multi-sensor data integration, particularly in challenging conditions where cloud cover hinders optical sensors' ability to accurately map snow. SAR, with its cloud-penetrating capabilities, provides reliable snow information even during adverse weather conditions, making it a valuable tool for snow studies. Furthermore, SAR's sensitivity to the dynamic nature of the snowpack, snowmelt and freeze, allows for more detailed monitoring of snow evolution over time. With changing climatic conditions, continuous snowpack monitoring during spring melt becomes critical for freshwater resource management. The study suggests that frequent SAR observations are essential for tracking snowpack changes, offering valuable insights for decision-making in water resource management. Combining SAR with optical data and climate records enhances the understanding of snow dynamics, ensuring more accurate and timely snow mapping in critical regions.
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unfold_moreArctic snow observations in Alaska, U.S. — Svetlana Stuefer
Svetlana Stuefer 1
1 Univesity of Alaska FairbanksFormat: Poster in-person
Poster number: 488
Abstract:
Snow depth and snow water equivalent (SWE) data are widely used in Arctic science and climate change studies. This presentation provides an overview of two projects with extensive in situ snow measurements in the Arctic: 1) NASA’s SnowEx 2023 campaigns in Alaska (https://snow.nasa.gov/campaigns/snowex), and 2) long-term (1985–2024) SWE measurements in remote Arctic watersheds collected by the Water and Environmental Research Center (WERC) at University of Alaska Fairbanks (UAF) (https://ine.uaf.edu/werc/imnavait). NASA's SnowEx project produced multiple snow data sets to advance the snow remote sensing, modelling, and measurements in different climates and ecosystems. In Alaska, SnowEx tested the state-of-the-art snow measurement techniques in boreal forest and Arctic tundra in 2022–2023. The second project offers 40 years of spatially distributed snow depth and SWE measurements collected in the small Imnavait Creek watershed located north of the Brooks Range, Alaska. These two projects contribute to Arctic science planning and research in different ways. The first project features very large spatially distributed snow data collection with concurrent airborne and ground-based snow measurements for testing specific instruments and methods. The second project maintains consistent long-term snow measurement practices allowing us to study changes in SWE and snow depth over decades. Both projects offer snow measurements in data-sparse regions of the Arctic, highlight the collaborative nature of Arctic research, and provide valuable resources for hydrological and climate studies.
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unfold_moreExploring novel technologies to assess spotted seal terrestrial ecology in the Alaska Chukchi and Beaufort Seas — Maeghan Connor
Maeghan Connor 1; Donna Hauser 1; Todd Brinkman 2; Andrew Von Duyke 3
1 University of Alaska Fairbanks, International Arctic Research Center, Alaska Arctic Observatory and Knowledge Hub; 2 University of Alaska Fairbanks, Institute of Arctic Biology; 3 North Slope Borough Department of Wildlife BiologyFormat: Poster in-person
Poster number: 547
Abstract:
Climate-induced environmental change poses a significant threat to ice-associated marine mammal species. In recent years, Indigenous Knowledge (IK) holders in Arctic Alaska have observed shifts in foraging behavior, seasonal movement, and abundance of harvested Arctic marine mammals. To assess the potential impacts of ecosystem change on marine mammals, it is necessary to document trends in animal ecology, abundance, behavior, and health. However, baseline data are severely lacking for many Arctic species, including the spotted seal (Phoca largha). Challenging weather conditions, financial and logistical constraints, inaccessible habitats, and the highly sensitive nature of this species pose a significant challenge to effective data collection via traditional survey methods including manned aircraft and boats.
To address this knowledge gap, we utilized two non-invasive technologies, namely camera traps and small drones, to assess spotted seal ecology at coastal haulouts in the Chukchi and Beaufort Seas during the open-water season. From 2020 - 2022, camera traps were placed at known seal haulout sites. Images and local weather data were analyzed to assess the impact of environmental conditions on terrestrial haulout behavior. To deepen our understanding of haulout behavior, results were woven with local environmental observations from IK holders from the nearby community of Utqiaġvik. We also tested the feasibility of using drones to assess spotted seal relative abundance, body condition, and age distribution by flying over haulouts throughout the 2024 open-water season. We found that these technologies have the potential to significantly improve data collection for spotted seals as well as other ice seal species.