In-situ measured primary productivity of ice algae in Arctic sea ice floes using a new incubation method

2016 ◽  
Vol 51 (3) ◽  
pp. 387-396 ◽  
Author(s):  
Ho Jung Song ◽  
Jae Hyung Lee ◽  
Gawn Woo Kim ◽  
So Hyun Ahn ◽  
Houng-Min Joo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Primary Productivity ◽  
Arctic Sea Ice ◽  
Ice Algae ◽  
Arctic Sea ◽  
Ice Floes ◽  
Incubation Method

An in situ Method for Measuring Primary Productivity of Arctic Sea Ice Algae

1973 ◽  
Vol 30 (6) ◽  
pp. 835-838 ◽  
Author(s):  
R. C. Clasby ◽  
Rita Horner ◽  
Vera Alexander
Keyword(s):  
Sea Ice ◽  
Primary Productivity ◽  
Carbon Fixation ◽  
Arctic Sea Ice ◽  
Algal Community ◽  
Sea Ice Algae ◽  
In Situ Method ◽  
Arctic Sea ◽  
Thaw Period

With the use of SCUBA diving and a new 14C incubation chamber, the rates of carbon fixation by the algal community that lives within the undersurface of sea ice have been measured. Rates of primary productivity ranged from 7.67-mg C/m2∙hr near the peak of the bloom to a low of 0.30-mg C/m2∙hr just prior to the thaw period.

scholarly journals Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

2017 ◽  
Vol 11 (5) ◽  
pp. 2059-2073 ◽  
Author(s):  
Kevin Guerreiro ◽  
Sara Fleury ◽  
Elena Zakharova ◽  
Alexei Kouraev ◽  
Frédérique Rémy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Flight Period ◽  
Data Sets ◽  
Data Set ◽  
Arctic Sea ◽  
The Common ◽  
Ice Floes ◽  
Along Track

Abstract. Over the past decade, sea-ice freeboard has been monitored with various satellite altimetric missions with the aim of producing long-term time series of ice thickness. While recent studies have demonstrated the capacity of the CryoSat-2 mission (2010–present) to provide accurate freeboard measurements, the current estimates obtained with the Envisat mission (2002–2012) still require some large improvements. In this study, we first estimate Envisat and CryoSat-2 radar freeboard by using the exact same processing algorithms. We then analyse the freeboard difference between the two estimates over the common winter periods (November 2010–April 2011 and November 2011–March 2012). The analysis of along-track data and gridded radar freeboard in conjunction with Envisat pulse-peakiness (PP) maps suggests that the discrepancy between the two sensors is related to the surface properties of sea-ice floes and to the use of a threshold retracker. Based on the relation between the Envisat pulse peakiness and the radar freeboard difference between Envisat and CryoSat-2, we produce a monthly CryoSat-2-like version of Envisat freeboard. The improved Envisat data set freeboard displays a similar spatial distribution to CryoSat-2 (RMSD  =  1.5 cm) during the two ice growth seasons and for all months of the period of study. The comparison of the altimetric data sets with in situ ice draught measurements during the common flight period shows that the improved Envisat data set (RMSE  =  12–28 cm) is as accurate as CryoSat-2 (RMSE  =  15–21 cm) and much more accurate than the uncorrected Envisat data set (RMSE  =  178–179 cm). The comparison of the improved Envisat radar freeboard data set is then extended to the rest of the Envisat mission to demonstrate the validity of PP correction from the calibration period. The good agreement between the improved Envisat data set and the in situ ice draught data set (RMSE  =  13–32 cm) demonstrates the potential of the PP correction to produce accurate freeboard estimates over the entire Envisat mission lifetime.

scholarly journals Windows in Arctic sea ice: Light transmission and ice algae in a refrozen lead

2017 ◽  
Vol 122 (6) ◽  
pp. 1486-1505 ◽  
Author(s):  
Hanna M. Kauko ◽  
Torbjørn Taskjelle ◽  
Philipp Assmy ◽  
Alexey K. Pavlov ◽  
C. J. Mundy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Light Transmission ◽  
Arctic Sea Ice ◽  
Ice Algae ◽  
Arctic Sea

Dissolved Neodymium Isotopes Trace Origin and Spatiotemporal Evolution of Modern Arctic Sea Ice

2020 ◽  
Author(s):  
Georgi Laukert ◽  
Dorothea Bauch ◽  
Ilka Peeken ◽  
Thomas Krumpen ◽  
Kirstin Werner ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Surface Waters ◽  
Ice Cores ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Spatiotemporal Evolution ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Ice Floes

<p>The lifetime and thickness of Arctic sea ice have markedly decreased in the recent past. This affects Arctic marine ecosystems and the biological pump, given that sea ice acts as platform and transport medium of marine and atmospheric nutrients. At the same time sea ice reduces light penetration to the Arctic Ocean and restricts ocean/atmosphere exchange. In order to understand the ongoing changes and their implications, reconstructions of source regions and drift trajectories of Arctic sea ice are imperative. Automated ice tracking approaches based on satellite-derived sea-ice motion products (e.g. ICETrack) currently perform well in dense ice fields, but provide limited information at the ice edge or in poorly ice-covered areas. Radiogenic neodymium (Nd) isotopes (ε<sub>Nd</sub>) have the potential to serve as a chemical tracer of sea-ice provenance and thus may provide information beyond what can be expected from satellite-based assessments. This potential results from pronounced ε<sub>Nd</sub> differences between the distinct marine and riverine sources, which feed the surface waters of the different sea-ice formation regions. We present the first dissolved (< 0.45 µm) Nd isotope and concentration data obtained from optically clean Arctic first- and multi-year sea ice (ice cores) collected from different ice floes across the Fram Strait during the RV POLARSTERN cruise PS85 in 2014. Our data confirm the preservation of the seawater ε<sub>Nd</sub>signatures in sea ice despite low Nd concentrations (on average ~ 6 pmol/kg) resulting from efficient brine rejection. The large range in ε<sub>Nd</sub> signatures (~ -10 to -30) mirrors that of surface waters in various parts of the Arctic Ocean, indicating that differences between ice floes but also between various sections in an individual ice core reflect the origin and evolution of the sea ice over time. Most ice cores have ε<sub>Nd</sub> signatures of around -10, suggesting that the sea ice was formed in well-mixed waters in the central Arctic Ocean and transported directly to the Fram Strait via the Transpolar Drift. Some ice cores, however, also revealed highly unradiogenic signatures (ε<sub>Nd</sub> < ~ -15) in their youngest (bottom) sections, which we attribute to incorporation of meltwater from Greenland into newly grown sea ice layers. Our new approach facilitates the reconstruction of the origin and spatiotemporal evolution of isolated sea-ice floes in the future Arctic.</p>

scholarly journals A linear model to derive melt pond depth from hyperspectral data

2019 ◽  
Author(s):  
Marcel König ◽  
Natascha Oppelt
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Large Scale ◽  
Hyperspectral Data ◽  
Arctic Sea Ice ◽  
Optical Data ◽  
Melt Pond ◽  
Arctic Sea ◽  
Melt Water

Abstract. Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring vertical melt pond evolution in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of melt water on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way melt water changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm. We validated the model using 49 in situ melt pond spectra and corresponding depths from ponds on dark and bright ice. Retrieved pond depths are precise (RMSE = 2.81 cm) and highly correlated with in situ measurements (r = 0.89; p = 4.34e−17). The model further explains a large portion of the variation in pond depth (R2 = 0.74). Our results indicate that pond depth is retrievable from optical data under clear sky conditions. This technique is potentially transferrable to hyperspectral remote sensors on UAVs, aircraft and satellites.

scholarly journals The melt pond fraction and spectral sea ice albedo retrieval from MERIS data: validation and trends of sea ice albedo and melt pond fraction in the Arctic for years 2002–2011

2014 ◽  
Vol 8 (5) ◽  
pp. 5227-5292 ◽  
Author(s):  
L. Istomina ◽  
G. Heygster ◽  
M. Huntemann ◽  
P. Schwarz ◽  
G. Birnbaum ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Imaging Spectrometer ◽  
Melt Pond ◽  
Result Show ◽  
Area North ◽  
Ice Floes ◽  
Multiyear Ice

Abstract. The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences on the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo (Zege et al., 2014) from the MEdium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, ship borne and in situ campaign data. The result show the best correlation for landfast and multiyear ice of high ice concentrations (albedo: R = 0.92, RMS = 0.068, melt pond fraction: R = 0.6, RMS = 0.065). The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to complicated surface conditions and ice drift. Combining all aerial observations gives a mean albedo RMS equal to 0.089 and a mean melt pond fraction RMS equal to 0.22. The in situ melt pond fraction correlation is R = 0.72 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the ASPeCT protocol, which is the reason for discrepancy between the satellite value and observed value: mean R = 0.21, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data. The case studies and trend analysis for the whole MERIS period (2002–2011) show pronounced and reasonable spatial features of melt pond fractions and sea ice albedo. The most prominent feature is the melt onset shifting towards spring (starting already in weeks 3 and 4 of June) within the multiyear ice area, north to the Queen Elizabeth Islands and North Greenland.

scholarly journals Production of Chromophoric Dissolved Organic Matter (CDOM) in Laboratory Cultures of Arctic Sea Ice Algae

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 926
Author(s):  
Guiju Li ◽  
Huixiang Xie ◽  
Guisheng Song ◽  
Michel Gosselin
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Sea Ice ◽  
Chlorophyll A ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Chromophoric Dissolved Organic Matter ◽  
Ice Algae ◽  
Production Rates ◽  
Arctic Sea

Chromophoric dissolved organic matter (CDOM) is highly enriched in bottom sea ice in the Arctic during ice algal blooms, giving rise to multifaceted ecological implications in both the sea ice and the underlying seawater. We conducted laboratory culture incubations to assess the potential role of ice algae in the accumulation of CDOM in Arctic sea ice. Non-axenic monocultures of Attheya septentrionalis and Nitzschia frigida and a natural ice algal assemblage (NIAA) were grown at 4 °C in an f/2 medium under cool white fluorescent light. Culture samples were collected several days apart throughout the exponential, stationary, and senescent phases, and analyzed for CDOM absorbance, chlorophyll a, and bacterial cell abundance. The cultures displayed apparent specific growth rates of algal and bacterial cells comparable to those in the field. Accumulations of CDOM were observed in all cultures during the time-course incubations, with the senescent phase showing the largest accumulations and the highest production rates. The senescent-phase production rate for NIAA was ~40% higher than that for A. septentrionalis. The chlorophyll a-normalized CDOM production rates in the cultures are comparable to those reported for Arctic first-year sea ice. The absorption spectra of CDOM in the cultures exhibited characteristic short-ultraviolet shoulders similar to those previously identified in sea ice. This study demonstrates that ice algal-derived CDOM can account for the springtime accumulation of CDOM in Arctic sea ice.

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