1
|
Clemens-Sewall D, Polashenski C, Raphael IA, Parno M, Perovich D, Itkin P, Jaggi M, Jutila A, Macfarlane AR, Matero ISO, Oggier M, Visser RJW, Wagner DN. High-resolution repeat topography of drifting ice floes in the Arctic Ocean from terrestrial laser scanning. Sci Data 2024; 11:70. [PMID: 38218968 PMCID: PMC10787767 DOI: 10.1038/s41597-023-02882-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 12/27/2023] [Indexed: 01/15/2024] Open
Abstract
Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km2 drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Using in-situ measurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements.
Collapse
Affiliation(s)
- David Clemens-Sewall
- Thayer School of Engineering at Dartmouth College, Hanover, NH, USA.
- NSF National Center for Atmospheric Research, Boulder, CO, USA.
| | - Chris Polashenski
- Thayer School of Engineering at Dartmouth College, Hanover, NH, USA
- USACE-CRREL Fort Wainwright, Fairbanks, AK, USA
| | - Ian A Raphael
- Thayer School of Engineering at Dartmouth College, Hanover, NH, USA
| | | | - Don Perovich
- Thayer School of Engineering at Dartmouth College, Hanover, NH, USA
| | - Polona Itkin
- UiT The Arctic University of Norway, Tromso, Norway
| | - Matthias Jaggi
- WSL Snow and Avalanche Research Institute SLF, Davos, Switzerland
| | - Arttu Jutila
- Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, 27570, Germany
- Finnish Meteorological Institute, Helsinki, Finland
| | - Amy R Macfarlane
- WSL Snow and Avalanche Research Institute SLF, Davos, Switzerland
| | - Ilkka S O Matero
- Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, 27570, Germany
- Svalbard Integrated Arctic Earth Observing System Knowledge Centre, Longyearbyen, Norway
| | - Marc Oggier
- International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK, USA
| | | | - David N Wagner
- WSL Snow and Avalanche Research Institute SLF, Davos, Switzerland
- CRYOS, School of Architecture, Civil and Environmental Engineering, EPFL, Lausanne, Switzerland
| |
Collapse
|
2
|
Jin Z, Ottaviani M, Sikand M. Modeling sea ice albedo and transmittance measurements with a fully-coupled radiative transfer model. OPTICS EXPRESS 2023; 31:21128-21152. [PMID: 37381220 DOI: 10.1364/oe.491306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/23/2023] [Indexed: 06/30/2023]
Abstract
A rigorous treatment of the sea ice medium has been incorporated in the advanced Coupled Ocean-Atmosphere Radiative Transfer (COART) model. The inherent optical properties (IOPs) of brine pockets and air bubbles over the 0.25-4.0 µm spectral region are parameterized as a function of the sea ice physical properties (temperature, salinity and density). We then test the performance of the upgraded COART model using three physically-based modeling approaches to simulate the spectral albedo and transmittance of sea ice, and compare them with measurements collected during the Impacts of Climate on the Ecosystems and Chemistry of the Arctic Pacific Environment (ICESCAPE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaigns. The observations are adequately simulated when at least three layers are used to represent bare ice, including a thin surface scattering layer (SSL), and two layers to represent ponded ice. Treating the SSL as a low-density ice layer yields better model-observation agreement than treating it as a snow-like layer. Sensitivity results indicate that air volume (which determines the ice density) has the largest impact on the simulated fluxes. The vertical profile of density drives the optical properties but available measurements are scarce. The approach where the scattering coefficient for the bubbles is inferred in lieu of density leads to essentially equivalent modeling results. For ponded ice, the albedo and transmittance in the visible are mainly determined by the optical properties of the ice underlying the water layer. Possible contamination from light-absorbing impurities, such as black carbon or ice algae, is also implemented in the model and is able to effectively reduce the albedo and transmittance in the visible spectrum to further improve the model-observation agreement.
Collapse
|
3
|
Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice. REMOTE SENSING 2022. [DOI: 10.3390/rs14122831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In order to satisfy the demand of key sea ice parameters, including melt pond depth Hp and underlying ice thickness Hi, in studies of Arctic sea ice change in summer, four algorithms of retrieving Hp and Hi were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of Hp. For the retrieval of Hi, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more accurate. The retrieval results of Hi for Lu18 agreed better with field measurements for thin ice (Hi < 1 m) than that for thick ice, but those results of Hp were not satisfactory. The König20 algorithm was only suitable for clear sky conditions, and underestimated Hp, while showing a good agreement with Hp < 0.15 m. For Arctic applications, Malinka18 and Zhang21 algorithms provided a basis and reference for the satellite optical data such as WoeldView2 to retrieve Hp and Hi. Malimka18 also showed the ability to retrieve Hi, except for the Lu18 algorithm if pond color captured by helicopters and unmanned aerial vehicles were available. This study identifies the optimal algorithm for retrieval of Hp and Hi under different conditions, which have the potential to provide necessary data for numerical simulations of Arctic sea ice changes in summer.
Collapse
|
4
|
Garnett J, Halsall C, Vader A, Joerss H, Ebinghaus R, Leeson A, Wynn PM. High Concentrations of Perfluoroalkyl Acids in Arctic Seawater Driven by Early Thawing Sea Ice. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:11049-11059. [PMID: 34308632 PMCID: PMC8383270 DOI: 10.1021/acs.est.1c01676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/02/2021] [Accepted: 07/02/2021] [Indexed: 05/12/2023]
Abstract
Poly- and perfluoroalkyl substances are synthetic chemicals that are widely present in the global environment including the Arctic. However, little is known about how these chemicals (particularly perfluoroalkyl acids, PFAA) enter the Arctic marine system and cycle between seawater and sea ice compartments. To evaluate this, we analyzed sea ice, snow, melt ponds, and near-surface seawater at two ice-covered stations located north of the Barents Sea (81 °N) with the aim of investigating PFAA dynamics in the late-season ice pack. Sea ice showed high concentrations of PFAA particularly at the surface with snow-ice (the uppermost sea ice layer strongly influenced by snow) comprising 26-62% of the total PFAA burden. Low salinities (<2.5 ppt) and low δ18OH20 values (<1‰ in snow and upper ice layers) in sea ice revealed the strong influence of meteoric water on sea ice, thus indicating a significant atmospheric source of PFAA with subsequent transfer down the sea ice column in meltwater. Importantly, the under-ice seawater (0.5 m depth) displayed some of the highest concentrations notably for the long-chain PFAA (e.g., PFOA 928 ± 617 pg L-1), which were ≈3-fold higher than those of deeper water (5 m depth) and ≈2-fold higher than those recently measured in surface waters of the North Sea infuenced by industrial inputs of PFAAs. The evidence provided here suggests that meltwater arising early in the melt season from snow and other surface ice floe components drives the higher PFAA concentrations observed in under-ice seawater, which could in turn influence the timing and extent of PFAA exposure for organisms at the base of the marine food web.
Collapse
Affiliation(s)
- Jack Garnett
- Lancaster
Environment Centre, Lancaster University, Lancaster LA1 4YQ, U.K.
| | - Crispin Halsall
- Lancaster
Environment Centre, Lancaster University, Lancaster LA1 4YQ, U.K.
| | - Anna Vader
- Department
of Arctic Biology, The University Centre
in Svalbard (UNIS), Longyearbyen N-9170, Norway
| | - Hanna Joerss
- Helmholtz-Zentrum
Hereon, Max-Planck-Straße
1, Geesthacht 21502, Germany
| | - Ralf Ebinghaus
- Helmholtz-Zentrum
Hereon, Max-Planck-Straße
1, Geesthacht 21502, Germany
| | - Amber Leeson
- Lancaster
Environment Centre, Lancaster University, Lancaster LA1 4YQ, U.K.
| | - Peter M. Wynn
- Lancaster
Environment Centre, Lancaster University, Lancaster LA1 4YQ, U.K.
| |
Collapse
|
5
|
Liston GE, Itkin P, Stroeve J, Tschudi M, Stewart JS, Pedersen SH, Reinking AK, Elder K. A Lagrangian Snow-Evolution System for Sea-Ice Applications (SnowModel-LG): Part I-Model Description. JOURNAL OF GEOPHYSICAL RESEARCH. OCEANS 2020; 125:e2019JC015913. [PMID: 33133995 PMCID: PMC7583384 DOI: 10.1029/2019jc015913] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 07/31/2020] [Accepted: 08/05/2020] [Indexed: 06/11/2023]
Abstract
A Lagrangian snow-evolution model (SnowModel-LG) was used to produce daily, pan-Arctic, snow-on-sea-ice, snow property distributions on a 25 × 25-km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective-Analysis for Research and Applications-Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis-5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14-km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static-surfaces and blowing-snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing-snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt-season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA-2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first-order control on snow property evolution.
Collapse
Affiliation(s)
- Glen E. Liston
- Cooperative Institute for Research in the Atmosphere (CIRA)Colorado State UniversityFort CollinsCOUSA
| | - Polona Itkin
- Department of Physics and TechnologyUiT The Arctic University of NorwayTromsøNORWAY
| | - Julienne Stroeve
- Earth SciencesUniversity College LondonLondonUK
- National Snow and Ice Data Center (NSIDC)University of Colorado BoulderBoulderCOUSA
| | - Mark Tschudi
- Colorado Center for Astrodynamics Research (CCAR)University of Colorado BoulderBoulderCOUSA
| | - J. Scott Stewart
- Colorado Center for Astrodynamics Research (CCAR)University of Colorado BoulderBoulderCOUSA
| | - Stine H. Pedersen
- Cooperative Institute for Research in the Atmosphere (CIRA)Colorado State UniversityFort CollinsCOUSA
- Department of Biological SciencesUniversity of Alaska AnchorageAnchorageAKUSA
| | - Adele K. Reinking
- Cooperative Institute for Research in the Atmosphere (CIRA)Colorado State UniversityFort CollinsCOUSA
| | - Kelly Elder
- Rocky Mountain Research StationUSDA Forest ServiceFort CollinsCOUSA
| |
Collapse
|
6
|
Retrieval of Melt Pond Fraction over Arctic Sea Ice during 2000–2019 Using an Ensemble-Based Deep Neural Network. REMOTE SENSING 2020. [DOI: 10.3390/rs12172746] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The accurate knowledge of variations of melt ponds is important for understanding the Arctic energy budget due to its albedo–transmittance–melt feedback. In this study, we develop and validate a new method for retrieving melt pond fraction (MPF) over Arctic sea ice using all seven spectral bands of MODIS surface reflectance. We construct a robust ensemble-based deep neural network and use in-situ MPF observations collected from multiple sources as the target data to train the network. We examine the potential influence of using sea ice concentration (SIC) from different sources as additional target data (besides MPF) on the MPF retrieval. The results suggest that the inclusion of SIC has a minor impact on MPF retrieval. Based on this, we create a new MPF data from 2000 to 2019 (the longest data in our knowledge). The validation shows that our new MPF data is in good agreement with the observations. We further compare the new MPF dataset with the previously published MPF datasets. It is found that the evolution of the new MPF is similar to previous MPF data throughout the melting season, but the new MPF data is in relatively better agreement with the observations in terms of correlations and root mean squared errors (RMSE), and also has the smallest value in the first half of the melting season.
Collapse
|
7
|
Xu D, Kong H, Yang EJ, Li X, Jiao N, Warren A, Wang Y, Lee Y, Jung J, Kang SH. Contrasting Community Composition of Active Microbial Eukaryotes in Melt Ponds and Sea Water of the Arctic Ocean Revealed by High Throughput Sequencing. Front Microbiol 2020; 11:1170. [PMID: 32582106 PMCID: PMC7291953 DOI: 10.3389/fmicb.2020.01170] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 05/07/2020] [Indexed: 01/03/2023] Open
Abstract
Melt ponds (MPs), form as the result of thawing of snow and sea ice in the summer, have lower albedo than the sea ice and are thus partly responsible for the polar amplification of global warming. Knowing the community composition of MP organisms is key to understanding their roles in the biogeochemical cycles of nutrients and elements. However, the community composition of MP microbial eukaryotes has rarely been studied. In the present study, we assessed the microbial eukaryote biodiversity, community composition, and assembly processes in MPs and surface sea water (SW) using high throughput sequencing of 18S rRNA of size-fractionated samples. Alpha diversity estimates were lower in the MPs than SW across all size fractions. The community composition of MPs was significantly different from that of SW. The MP communities were dominated by members from Chrysophyceae, the ciliate classes Litostomatea and Spirotrichea, and the cercozoan groups Filosa-Thecofilosea. One open MP community was similar to SW communities, which was probably due to the advanced stage of development of the MP enabling the exchange of species between it and adjacent SW. High portions of shared species between MPs and SW may indicate the vigorous exchange of species between these two major types of environments in the Arctic Ocean. SW microbial eukaryote communities are mainly controlled by dispersal limitation whereas those of MP are mainly controlled by ecological drift.
Collapse
Affiliation(s)
- Dapeng Xu
- State Key Laboratory of Marine Environmental Science, Institute of Marine Microbes and Ecospheres, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen, China
| | - Hejun Kong
- State Key Laboratory of Marine Environmental Science, Institute of Marine Microbes and Ecospheres, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen, China
| | - Eun-Jin Yang
- Division of Polar Ocean Science, Korea Polar Research Institute, Incheon, South Korea
| | - Xinran Li
- State Key Laboratory of Marine Environmental Science, Institute of Marine Microbes and Ecospheres, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen, China
| | - Nianzhi Jiao
- State Key Laboratory of Marine Environmental Science, Institute of Marine Microbes and Ecospheres, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Fujian Key Laboratory of Marine Carbon Sequestration, Xiamen University, Xiamen, China
| | - Alan Warren
- Department of Life Sciences, Natural History Museum, London, United Kingdom
| | - Ying Wang
- State Key Laboratory of Marine Environmental Science, Institute of Marine Microbes and Ecospheres, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Youngju Lee
- Division of Polar Ocean Science, Korea Polar Research Institute, Incheon, South Korea
| | - Jinyoung Jung
- Division of Polar Ocean Science, Korea Polar Research Institute, Incheon, South Korea
| | - Sung-Ho Kang
- Division of Polar Ocean Science, Korea Polar Research Institute, Incheon, South Korea
| |
Collapse
|
8
|
Hu Y, Yao X, Wu Y, Han W, Zhou Y, Tang X, Shao K, Gao G. Contrasting Patterns of the Bacterial Communities in Melting Ponds and Periglacial Rivers of the Zhuxi glacier in the Tibet Plateau. Microorganisms 2020; 8:microorganisms8040509. [PMID: 32252494 PMCID: PMC7232332 DOI: 10.3390/microorganisms8040509] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/26/2020] [Accepted: 03/30/2020] [Indexed: 12/04/2022] Open
Abstract
Since the early 21st century, global climate change has been inducing rapid glacier retreat at an unprecedented rate. In this context, the melt ponds impart increasing unique footprints on the periglacial rivers due to their hydrodynamic connection. Given that bacterial communities control numerous ecosystem processes in the glacial ecosystem, exploring the fate of bacterial communities from melt ponds to periglacial rivers yields key knowledge of the biodiversity and biogeochemistry of glacial ecosystems. Here, we analyzed the bacterial community structure, diversity, and co-occurrence network to reveal the community organization in the Zhuxi glacier in the Tibet Plateau. The results showed that the bacterial communities in melt ponds were significantly lower in alpha-diversity but were significantly higher in beta-diversity than those in periglacial rivers. The rare sub-communities significantly contributed to the stability of the bacterial communities in both habitats. The co-occurrence network inferred that the mutually beneficial relationships predominated in the two networks. Nevertheless, the lower ratio of positive to negative edges in melt ponds than periglacial rivers implicated fiercer competition in the former habitat. Based on the significantly higher value of degree, betweenness, and modules, as well as shorter average path length in melt ponds, we speculated that their bacterial communities are less resilient than those of periglacial rivers.
Collapse
Affiliation(s)
- Yang Hu
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
| | - Xin Yao
- School of Environment and Planning, Liaocheng University, Liaocheng 25200, China
| | - Yuanyuan Wu
- Sino-Japan Friendship Center for Environmental Protection, Beijing 100029, China
| | - Wei Han
- Sino-Japan Friendship Center for Environmental Protection, Beijing 100029, China
| | - Yongqiang Zhou
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
| | - Xiangming Tang
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
| | - Keqiang Shao
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
| | - Guang Gao
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
- Correspondence: ; Tel.: (+86) 25 86882187; Fax: (+86) 25 86882187
| |
Collapse
|
9
|
Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data. REMOTE SENSING 2020. [DOI: 10.3390/rs12061033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Meltwater drainage onset (DO) timing and drainage duration (DD) related to snowmelt-water redistribution are both important for understanding not only the Arctic energy and heat budgets but also the salt/heat balance of the mixed layer in the ocean and sea-ice ecosystem. We present DO and DD as determined from the time series of Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) melt pond fraction (MPF) estimates in an area with Canadian landfast ice. To address the lack of evaluation on a day-by-day basis for the AMSR-E MPF estimate, we first compared AMSR-E MPF with the daily Medium Resolution Imaging Spectrometer (MERIS) MPF. The AMSR-E MPF estimate correlates significantly with the MERIS MPF (r = 0.73–0.83). The estimate has a product quality similar to the MERIS MPF only when the albedo is around 0.5–0.7 and a positive bias of up to 10% in areas with an albedo of 0.7–0.9, including melting snow. The DO/DD estimates are determined by using a polynomial regression curve fitted on the time series of the AMSR-E MPF. The DOs/DDs from time series of the AMSR-E and MERIS MPFs are compared, revealing consistency in both DD and DO. The DO timing from 2006 to 2011 is correlated with melt onset timing. To the best of our knowledge, our study provides the first large-scale information on both DO timing and DD.
Collapse
|
10
|
An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice. REMOTE SENSING 2019. [DOI: 10.3390/rs11232860] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Sea-ice biophysical properties are characterized by high spatio-temporal variability ranging from the meso- to the millimeter scale. Ice coring is a common yet coarse point sampling technique that struggles to capture such variability in a non-invasive manner. This hinders quantification and understanding of ice algae biomass patchiness and its complex interaction with some of its sea ice physical drivers. In response to these limitations, a novel under-ice sled system was designed to capture proxies of biomass together with 3D models of bottom topography of land-fast sea-ice. This system couples a pushbroom hyperspectral imaging (HI) sensor with a standard digital RGB camera and was trialed at Cape Evans, Antarctica. HI aims to quantify per-pixel chlorophyll-a content and other ice algae biological properties at the ice-water interface based on light transmitted through the ice. RGB imagery processed with digital photogrammetry aims to capture under-ice structure and topography. Results from a 20 m transect capturing a 0.61 m wide swath at sub-mm spatial resolution are presented. We outline the technical and logistical approach taken and provide recommendations for future deployments and developments of similar systems. A preliminary transect subsample was processed using both established and novel under-ice bio-optical indices (e.g., normalized difference indexes and the area normalized by the maximal band depth) and explorative analyses (e.g., principal component analyses) to establish proxies of algal biomass. This first deployment of HI and digital photogrammetry under-ice provides a proof-of-concept of a novel methodology capable of delivering non-invasive and highly resolved estimates of ice algal biomass in-situ, together with some of its environmental drivers. Nonetheless, various challenges and limitations remain before our method can be adopted across a range of sea-ice conditions. Our work concludes with suggested solutions to these challenges and proposes further method and system developments for future research.
Collapse
|
11
|
Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data. REMOTE SENSING 2019. [DOI: 10.3390/rs11212481] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The paper presents a comparison of sea ice concentration (SIC) derived from satellite microwave radiometry data and dedicated ship observations. For the purpose, the NASA Team (NT), Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI), and Variation Arctic/Antarctic Sea Ice Algorithm 2 (VASIA2) algorithms were used as well as the database of visual ice observations accumulated in the course of 15 Arctic expeditions. The comparison was performed in line with the SIC gradation (in tenths) into very open (1–3), open (4–6), close (7–8), very close and compact (9–10,10) ice, separately for summer and winter seasons. On average, in summer NT underestimates SIC by 0.4 tenth as compared to ship observations, while ASI and VASIA2 by 0.3 tenth. All three algorithms overestimate total SIC in regions of very open ice and underestimate it in regions of close, very close, and compact ice. The maximum average errors are typical of open ice regions that are most common in marginal ice zones. In winter, NT and ASI also underestimate SIC on average by 0.4 and 0.8 tenths, respectively, while VASIA2, on the contrary, overestimates by 0.2 tenth against the ship data, however, for open and close ice the average errors are significantly higher than in summer. In the paper, we also estimate the impact of ice melt stage and presence of new ice and nilas on SIC derived from NT, ASI, and VASIA2.
Collapse
|
12
|
Hyun CU, Kim JH, Han H, Kim HC. Mosaicking Opportunistically Acquired Very High-Resolution Helicopter-Borne Images over Drifting Sea Ice Using COTS Sensors. SENSORS 2019; 19:s19051251. [PMID: 30871071 PMCID: PMC6427715 DOI: 10.3390/s19051251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Revised: 03/08/2019] [Accepted: 03/08/2019] [Indexed: 11/17/2022]
Abstract
Observing sea ice by very high-resolution (VHR) images not only improves the quality of lower-resolution remote sensing products (e.g., sea ice concentration, distribution of melt ponds and pressure ridges, sea ice surface roughness, etc.) by providing details on the ground truth of sea ice, but also assists sea ice fieldwork. In this study, two fieldwork-based methods are proposed, one for the practical acquisition of VHR images over drifting Arctic sea ice using low-cost commercial off-the-shelf (COTS) sensors equipped on a helicopter, and the other for quantifying the compensating effect from continuously drifting sea ice that reduces geolocation uncertainty in the image mosaicking procedure. The drifting trajectory of the target ice was yielded from that recorded by an icebreaker that was tightly anchored to the floe and was then used to reversely compensate the locations of acquired VHR images. After applying the compensation, three-dimensional geolocation errors of the VHR images were decreased by 79.3% and 24.2% for two pre-defined image groups, respectively. The enhanced accuracy of the imaging locations was affected by imaging duration causing variable drifting distances of individual images. Further applicability of the mosaicked VHR image was discussed by comparing it with a TerraSAR-X synthetic aperture radar image containing the target ice, suggesting that the proposed methods can be used for precise comparison with satellite remote sensing products.
Collapse
Affiliation(s)
- Chang-Uk Hyun
- Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute, KIOST, Incheon 21990, Korea.
| | - Joo-Hong Kim
- Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute, KIOST, Incheon 21990, Korea.
| | - Hyangsun Han
- Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute, KIOST, Incheon 21990, Korea.
| | - Hyun-Cheol Kim
- Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute, KIOST, Incheon 21990, Korea.
| |
Collapse
|
13
|
Mann EA, Ziegler SE, Steffen A, O'Driscoll NJ. Increasing chloride concentration causes retention of mercury in melted Arctic snow due to changes in photoreduction kinetics. J Environ Sci (China) 2018; 68:122-129. [PMID: 29908731 DOI: 10.1016/j.jes.2018.01.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Revised: 12/19/2017] [Accepted: 01/08/2018] [Indexed: 06/08/2023]
Abstract
Mercury (Hg) in the Arctic is a significant concern due to its bioaccumulative and neurotoxic properties, and the sensitivity of Arctic environments. Previous research has found high levels of Hg in snowpacks with high chloride (Cl-) concentrations. We hypothesised that Cl- would increase Hg retention by decreasing Hg photoreduction to Hg(0) in melted Arctic snow. To test this, changes in Hg photoreduction kinetics in melted Alert, NU snow were quantified with changing Cl- concentration and UV intensity. Snow was collected and melted in Teflon bottles in May 2014, spiked with 0-10μg/g Cl-, and irradiated with 3.52-5.78W·m-2 UV (280-400nm) radiation in a LuzChem photoreactor. Photoreduction rate constants (k) (0.14-0.59hr-1) had positive linear relationships with [Cl-], while photoreduced Hg amounts (Hg(II)red) had negative linear relationships with [Cl-] (1287-64pg in 200g melted snow). Varying UV and [Cl-] both altered Hg(II)red amounts, with more efficient Hg stabilisation by Cl- at higher UV intensity, while k can be predicted by Cl- concentration and/or UV intensity, depending on experimental parameters. Overall, with future projections for greater snowpack Cl- loading, our experimental results suggest that more Hg could be delivered to Arctic aquatic ecosystems by melted snow (smaller Hg(II)red expected), but the Hg in the melted snow that is photoreduced may do so more quickly (larger k expected).
Collapse
Affiliation(s)
- E A Mann
- Department of Environmental Science, Acadia University, Wolfville, NS, Canada; Environmental Science Programme, Memorial University of Newfoundland, St. John's, NL, Canada.
| | - S E Ziegler
- Environmental Science Programme, Memorial University of Newfoundland, St. John's, NL, Canada
| | - A Steffen
- Environment and Climate Change Canada, Science and Technology Branch, Air Quality Research Division, Toronto, ON, Canada
| | - N J O'Driscoll
- Department of Environmental Science, Acadia University, Wolfville, NS, Canada
| |
Collapse
|
14
|
Popović P, Cael BB, Silber M, Abbot DS. Simple Rules Govern the Patterns of Arctic Sea Ice Melt Ponds. PHYSICAL REVIEW LETTERS 2018; 120:148701. [PMID: 29694130 DOI: 10.1103/physrevlett.120.148701] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Indexed: 06/08/2023]
Abstract
Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming.
Collapse
Affiliation(s)
- Predrag Popović
- Department of the Geophysical Sciences, The University of Chicago, Chicago, Illinois 60637, USA
| | - B B Cael
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Mary Silber
- Department of Statistics and Committee on Computational and Applied Mathematics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Dorian S Abbot
- Department of the Geophysical Sciences, The University of Chicago, Chicago, Illinois 60637, USA
| |
Collapse
|
15
|
Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice. REMOTE SENSING 2017. [DOI: 10.3390/rs10010037] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
16
|
Sørensen HL, Thamdrup B, Jeppesen E, Rysgaard S, Glud RN. Nutrient availability limits biological production in Arctic sea ice melt ponds. Polar Biol 2017; 40:1593-1606. [PMID: 32025085 PMCID: PMC6979518 DOI: 10.1007/s00300-017-2082-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 08/26/2016] [Accepted: 01/10/2017] [Indexed: 11/29/2022]
Abstract
Every spring and summer melt ponds form at the surface of polar sea ice and become habitats where biological production may take place. Previous studies report a large variability in the productivity, but the causes are unknown. We investigated if nutrients limit the productivity in these first-year ice melt ponds by adding nutrients to three enclosures ([1] PO43−, [2] NO3−, and [3] PO43− and NO3−) and one natural melt pond (PO43− and NO3−), while one enclosure and one natural melt pond acted as controls. After 7–13 days, Chl a concentrations and cumulative primary production were between two- and tenfold higher in the enclosures and natural melt ponds with nutrient addition compared with their respective controls, with the largest increase occurring in the enclosures. Separate additions of PO43− and NO3− in the enclosures led to intermediate increases in productivity, suggesting co-limitation of nutrients. Bacterial production and the biovolume of ciliates, which were the dominant grazers, were positively correlated with primary production, showing a tight coupling between primary production and both microbial activity and ciliate grazing. To our knowledge, this study is the first to ascertain nutrient limitation in melt ponds. We also document that the addition of nutrients, although at relative high concentrations, can stimulate biological productivity at several trophic levels. Given the projected increase in first-year ice, increased melt pond coverage during the Arctic spring and potential additional nutrient supply from, e.g. terrestrial sources imply that biological activity of melt ponds may become increasingly important for the sympagic carbon cycling in the future Arctic.
Collapse
Affiliation(s)
- Heidi Louise Sørensen
- Department of Biology, Nordic Centre for Earth Evolution (NordCEE), University of Southern Denmark (SDU), Campusvej 55, 5230 Odense, Denmark
- Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, 3900 Nuuk, Greenland
| | - Bo Thamdrup
- Department of Biology, Nordic Centre for Earth Evolution (NordCEE), University of Southern Denmark (SDU), Campusvej 55, 5230 Odense, Denmark
| | - Erik Jeppesen
- Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, 3900 Nuuk, Greenland
- Department of Bioscience, Aarhus University, Vejlsøvej, 25, 8600 Silkeborg, Denmark
- Sino-Danish Centre for Education and Research (SDC), The University of the Chinese Academy of Sciences (UCAS), Beijing, 100190 China
- Arctic Research Centre, Aarhus University, 8000 Aarhus, Denmark
| | - Søren Rysgaard
- Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, 3900 Nuuk, Greenland
- Department of Environment and Geography, Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 2N2 Canada
- Department of Geological Sciences, University of Manitoba, Winnipeg, MB R3T 2N2 Canada
- Arctic Research Centre, Aarhus University, 8000 Aarhus, Denmark
| | - Ronnie Nøhr Glud
- Department of Biology, Nordic Centre for Earth Evolution (NordCEE), University of Southern Denmark (SDU), Campusvej 55, 5230 Odense, Denmark
- Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, 3900 Nuuk, Greenland
- Arctic Research Centre, Aarhus University, 8000 Aarhus, Denmark
- Scottish Association for Marine Science, Scottish Marine Institute, Oban, PA37 1QA UK
| |
Collapse
|
17
|
Biopolymers form a gelatinous microlayer at the air-sea interface when Arctic sea ice melts. Sci Rep 2016; 6:29465. [PMID: 27435531 PMCID: PMC4951643 DOI: 10.1038/srep29465] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 06/20/2016] [Indexed: 11/08/2022] Open
Abstract
The interface layer between ocean and atmosphere is only a couple of micrometers thick but plays a critical role in climate relevant processes, including the air-sea exchange of gas and heat and the emission of primary organic aerosols (POA). Recent findings suggest that low-level cloud formation above the Arctic Ocean may be linked to organic polymers produced by marine microorganisms. Sea ice harbors high amounts of polymeric substances that are produced by cells growing within the sea-ice brine. Here, we report from a research cruise to the central Arctic Ocean in 2012. Our study shows that microbial polymers accumulate at the air-sea interface when the sea ice melts. Proteinaceous compounds represented the major fraction of polymers supporting the formation of a gelatinous interface microlayer and providing a hitherto unrecognized potential source of marine POA. Our study indicates a novel link between sea ice-ocean and atmosphere that may be sensitive to climate change.
Collapse
|
18
|
Petty A, Tsamados M, Kurtz N, Farrell S, Newman T, Harbeck J, Feltham D, Richter-Menge J. Characterizing Arctic sea ice topography using high-resolution IceBridge data. THE CRYOSPHERE 2016; 10:1161-1179. [PMID: 32818051 PMCID: PMC7430516 DOI: 10.5194/tc-10-1161-2016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
We present an analysis of Arctic sea ice topography using high resolution, three-dimensional, surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009-2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by ice type to estimate the topographic variability across first-year and multi-year ice regimes. The results demonstrate that Arctic sea ice topography exhibits significant spatial variability, mainly driven by the increased surface feature height and volume (per unit area) of the multi-year ice that dominates the Central Arctic region. The multi-year ice topography exhibits greater interannual variability compared to the first-year ice regimes, which dominates the total ice topography variability across both regions. The ice topography also shows a clear coastal dependency, with the feature height and volume increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. A strong correlation between ice topography and ice thickness (from the IceBridge sea ice product) is found, using a square-root relationship. The results allude to the importance of ice deformation variability in the total sea ice mass balance, and provide crucial information regarding the tail of the ice thickness distribution across the western Arctic. Future research priorities associated with this new dataset are presented and discussed, especially in relation to calculations of atmospheric form drag.
Collapse
Affiliation(s)
- Alek Petty
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
- Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Michel Tsamados
- Centre for Polar Observation and Modelling, Department of Earth Sciences, University College London, London, UK
| | - Nathan Kurtz
- Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Sinead Farrell
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
- Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- NOAA Center for Weather and Climate Prediction, College Park, Maryland, USA
| | - Thomas Newman
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
- NOAA Center for Weather and Climate Prediction, College Park, Maryland, USA
| | - Jeremy Harbeck
- Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Daniel Feltham
- Centre for Polar Observation and Modelling, Department of Meteorology, University of Reading, Reading, UK
| | | |
Collapse
|
19
|
Pućko M, Stern GA, Barber DG, Macdonald RW, Warner KA, Fuchs C. Mechanisms and implications of α-HCH enrichment in melt pond water on Arctic sea ice. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2012; 46:11862-9. [PMID: 23039929 DOI: 10.1021/es303039f] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
During the summer of 2009, we sampled 14 partially refrozen melt ponds and the top 1 m of old ice in the pond vicinity for α-hexachlorocyclohexane (α-HCH) concentrations and enantiomer fractions (EFs) in the Beaufort Sea. α-HCH concentrations were 3 - 9 times higher in melt ponds than in the old ice. We identify two routes of α-HCH enrichment in the ice over the summer. First, atmospheric gas deposition results in an increase of α-HCH concentration from 0.07 ± 0.02 ng/L (old ice) to 0.34 ± 0.08 ng/L, or ~20% less than the atmosphere-water equilibrium partitioning concentration (0.43 ng/L). Second, late-season ice permeability and/or complete ice thawing at the bottom of ponds permit α-HCH rich seawater (~0.88 ng/L) to replenish pond water, bringing concentrations up to 0.75 ± 0.06 ng/L. α-HCH pond enrichment may lead to substantial concentration patchiness in old ice floes, and changed exposures to biota as the surface meltwater eventually reaches the ocean through various drainage mechanisms. Melt pond concentrations of α-HCH were relatively high prior to the late 1980-s, with a Melt pond Enrichment Factor >1 (MEF; a ratio of concentration in surface meltwater to surface seawater), providing for the potential of increased biological exposures.
Collapse
Affiliation(s)
- M Pućko
- Centre for Earth Observation Science, University of Manitoba, 460 Wallace Building, 125 Dysart Road, Winnipeg, R3T 2N2, Canada.
| | | | | | | | | | | |
Collapse
|
20
|
Flocco D, Schroeder D, Feltham DL, Hunke EC. Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2012jc008195] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|