Nansen International Environmental and Remote Sensing Center

Vasilievsky Island, Russia

Nansen International Environmental and Remote Sensing Center

Vasilievsky Island, Russia
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Hessen D.O.,University of Oslo | Carroll J.,Akvaplan Niva | Kjeldstad B.,Norwegian University of Science and Technology | Korosov A.A.,Nansen International Environmental and Remote Sensing Center | And 3 more authors.
Estuarine, Coastal and Shelf Science | Year: 2010

Spectral light attenuation profiles and concentrations of total and dissolved carbon (C), nutrients and chlorophyll a (Chla) were studied along transects running from the river mouth to the Kara Sea during late summer 2003 for the Yenisey and fall 2005 for the Ob estuaries. Earth Observation data were used to generate composite images of water color and Chla distribution over the estuaries and the Kara Sea to reveal the spatial impact of the river efflux in terms of optical properties. High levels of total nitrogen (N), total phosphorus (P), silicate (Si) and iron (Fe), but low levels of inorganic N and P and Chla were found in the estuaries. More than 90 % of total organic C was in dissolved form (DOC). The high concentrations of DOC, mostly terrigenous, humic compounds, gave extremely high attenuation coefficients for both visible and ultraviolet light. For UV-B, Z10% (the depth at which 10% of surface light remains) was <10 cm, while Z10% for visible light (PAR) generally ranged between 1 and 3 m for both transects. The light attenuation rapidly decreases when the freshwater is mixed with the coastal water outside off the coast. This leads to a strong light limitation and low productivity in the inner estuaries, while the high load of N and P associated with DOC eventually could promote primary production in the Kara Sea and further upstream the coastal current in the Arctic Ocean as the organic matter becomes diluted and photooxidized. On the other hand, the high inputs of colored dissolved organic matter (CDOM) provide an efficient screening of potential harmful UV-radiation over vast areas of the Arctic Ocean. A rising trend of riverine efflux to the Arctic seas is observed, and further increases in freshwater runoff as well as eventual permafrost thawing, will accentuate the freshwater impact in the estuaries and the Kara Sea. © 2010 Elsevier Ltd. All rights reserved.


Morozov E.,Russian State Hydrometeorological University | Pozdnyakov D.,Nansen International Environmental and Remote Sensing Center | Smyth T.,Plymouth Marine Laboratory | Sychev V.,Russian State Hydrometeorological University | Grassl H.,Max Planck Institute for Meteorology
International Journal of Remote Sensing | Year: 2013

Seasonal and inter-annual variations in phytoplankton community abundance in the Bay of Biscay are studied. Preliminarily processed by the National Aeronautics and Space Administration (NASA) to yield normalized water-leaving radiance and the top-of-the-atmosphere solar radiance, Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Coastal Zone Color Scanner (CZCS) data are further supplied to our dedicated retrieval algorithms to infer the sought for parameters. By applying the National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) data, the surface reflection coefficient in the only band in the visible spectrum is derived and employed for analysis. Decadal bridged time series of variations of diatom-dominated phytoplankton and green dinoflagellate Lepidodinium chlorophorum within the shelf zone and the coccolithophore Emiliania huxleyi in the pelagic area of the Bay are documented and analysed in terms of impacts of some biogeochemical and geophysical forcing factors.It is shown that in the shelf zone of the Bay, the diatom-dominated phytoplankton community variations are predominantly controlled by river discharge variations, by water column stratification conditions (forming in winter-early spring), and by wind action (resulting in such phenomena as up-wellings and sediment re-suspension).Satellite data indicate that while in river deltas and adjoining waters the L. chlorophorum blooming events occur annually, in the Iroise Sea and near the Bailiwick of Guernsey, they happen irregularly. It is thought that such an irregular pattern, possibly, arises from L. chlorophorum competing with other phytoplankton species for nutrients.E miliania huxleyi blooms are found to occur nearly every year in the northern part of the Bay, whereas in the central area, this phenomenon occurs very irregularly. Satellite data indicate that variations in the water chemistry (variations in the nitrogen: phosphorus ratio due to preceding blooms of diatoms), and the incident irradiance level (degree of cloudiness), are important factors controlling the occurrence of E. huxleyi blooming in the central part of the Bay. Covering a 30 year period, the bridged data from CZCS, AVHRR, SeaWiFS, and MODIS imply that climate change might be responsible for the observed increase in E. huxleyi blooming events in the Bay since 1979. © 2013 Copyright Taylor and Francis Group, LLC.


Alexandrov V.,Nansen International Environmental and Remote Sensing Center | Sandven S.,Nansen Environmental and Remote Sensing Center | Sandven S.,University of Svalbard | Wahlin J.,Nansen Environmental and Remote Sensing Center | Johannessen O.M.,Nansen Environmental and Remote Sensing Center
Cryosphere | Year: 2010

Retrieval of Arctic sea ice thickness from CryoSat-2 radar altimeter freeboard data requires observational data to verify the relation between these two variables. In this study in-situ ice and snow data from 689 observation sites, obtained during the Sever expeditions in the 1980s, have been used to establish an empirical relation between thickness and freeboard of FY ice in late winter. Estimates of mean and variability of snow depth, snow density and ice density were produced on the basis of many field observations. These estimates have been used in the hydrostatic equilibrium equation to retrieve ice thickness as a function of ice freeboard, snow depth and snow/ice density. The accuracy of the ice thickness retrieval has been calculated from the estimated variability in ice and snow parameters and error of ice freeboard measurements. It is found that uncertainties of ice density and freeboard are the major sources of error in ice thickness calculation. For FY ice, retrieval of ≈ 1.0 m (2.0 m) thickness has an uncertainty of 46% (37%), and for MY ice, retrieval of 2.4 m (3.0 m) thickness has an uncertainty of 20% (18%), assuming that the freeboard error is ± 0.03 m for both ice types. For MY ice the main uncertainty is ice density error, since the freeboard error is relatively smaller than that for FY ice. If the freeboard error can be reduced to 0.01 m by averaging measurements from CryoSat-2, the error in thickness retrieval is reduced to about 32% for a 1.0 m thick FY floe and to about 18% for a 2.4 m thick MY floe. The remaining error is dominated by uncertainty in ice density. Provision of improved ice density data is therefore important for accurate retrieval of ice thickness from CryoSat-2 data. © 2010 Author(s).


Petrenko D.,Russian State Hydrometeorological University | Pozdnyakov D.,Nansen International Environmental and Remote Sensing Center | Johannessen J.,Nansen Environmental and Remote Sensing Center | Counillon F.,Nansen Environmental and Remote Sensing Center | Sychov V.,Russian State Hydrometeorological University
International Journal of Remote Sensing | Year: 2013

Spaceborne one month averaged data, predominantly from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and partly from the Moderate Resolution Imaging Spectroradiometer (MODIS), were used to investigate changes in primary production (PP) by phytoplankton in the Arctic Ocean from 1998 to 2010. Several PP retrieval algorithms were tested against the collected in situ data, and it was shown that the algorithm by Behrenfeld and Falkowski gave the best results (with the coefficient of correlation, r, equal to 0.8 and 0.75, respectively, for the pelagic and shelf zones). Based on the performed test, the Behrenfeld and Falkowski algorithm was further applied for determining both the annual PP in the Arctic and the PP trend over the above-mentioned time period. Results of our analysis indicate that PP in the Arctic has increased by ~15.9% over 13 years (1998-2010). This finding, as well as the absolute annual values of PP remotely quantified in the present study, is at odds with analogous numerical assessments by other workers. These disagreements are thought to be due to differences in the applied methodologies of satellite data processing such as cloud masking and determination of phytoplankton concentration within (1) overcast areas and (2) areas of massive growth of coccolithophores as well as (3) in the shelf zone prone to a significant influence of land and river run-off. © 2013 Copyright Taylor and Francis Group, LLC.


Zakhvatkina N.Yu.,Arctic and Antarctic Research Institute | Alexandrov V.Yu.,Nansen International Environmental and Remote Sensing Center | Johannessen O.M.,Nansen Environmental and Remote Sensing Center | Johannessen O.M.,University of Bergen | And 2 more authors.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013

In this paper, sea ice in the Central Arctic has been classified in synthetic aperture radar (SAR) images from ENVISAT using a neural network (NN)-based algorithm and a Bayesian algorithm. Since different sea ice types can have similar backscattering coefficients at C-band HH polarization, it is necessary to use textural features in addition to the backscattering coefficients. The analysis revealed that the most informative texture features for the classification of multiyear ice (MYI), deformed first-year ice (FYI) (DFYI), and level FYI (LFYI) and open water/nilas are correlation, inertia, cluster prominence, energy, homogeneity, and entropy, as well as third and fourth central statistical moments of image brightness. The optimal topology of the NN, trained for ENVISAT wide-swath SAR sea ice classification, consists of nine neurons in input layer, six neurons in hidden layer, and three neurons in output layer. The classification results for a series of 20 SAR images, acquired in the central part of the Arctic Ocean during winter months, were compared to expert analysis of the images and ice charts. The results of the NN classification show that the average correspondences with the expert analysis amount to 85%, 83%, and 80% for LFYI, DFYI, and MYI, respectively. The Bayesian pixel-based method can provide a higher resolution in the classified image and, therefore, better capability to identify leads compared to the NN method. Both methods may be effectively used in the Central Arctic where MYI is predominant. © 2012 IEEE.


Shuchman R.A.,Michigan Technological University | Leshkevich G.,National Oceanic and Atmospheric Administration | Sayers M.J.,Michigan Technological University | Johengen T.H.,University of Michigan | And 2 more authors.
Journal of Great Lakes Research | Year: 2013

An algorithm that utilizes individual lake hydro-optical (HO) models has been developed for the Great Lakes that uses SeaWiFS, MODIS, or MERIS satellite data to estimate concentrations of chlorophyll, dissolved organic carbon, and suspended minerals. The Color Producing Agent Algorithm (CPA-A) uses a specific HO model for each lake. The HO models provide absorption functions for the Color Producing Agents (CPAs) (chlorophyll (chl), colored dissolved organic matter (as dissolved organic carbon, doc), and suspended minerals (sm)) as well as backscatter for the chlorophyll, and suspended mineral parameters. These models were generated using simultaneous optical data collected with in situ measurements of CPAs collected during research cruises in the Great Lakes using regression analysis as well as using specific absorption and backscatter coefficients at specific chl, doc, and sm concentrations. A single average HO model for the Great Lakes was found to generate insufficiently accurate concentrations for Lakes Michigan, Erie, Superior and Huron. These new individual lake retrievals were evaluated with respect to EPA in situ field observations, as well as compared to the widely used OC3 MODIS retrieval. The new algorithm retrievals provided slightly more accurate chl values for Lakes Michigan, Superior, Huron, and Ontario than those obtained using the OC3 approach as well as providing additional concentration information on doc and sm. The CPA-A chl retrieval for Lake Erie is quite robust, producing reliable chl values in the reported EPA concentration ranges. Atmospheric correction approaches were also evaluated in this study. © 2013 Elsevier B.V.


Fujimura A.,Nova Southeastern University | Soloviev A.,Nova Southeastern University | Kudryavtsev V.,Nansen Environmental and Remote Sensing Center | Kudryavtsev V.,Nansen International Environmental and Remote Sensing Center
IEEE Geoscience and Remote Sensing Letters | Year: 2010

Centerline wakes of ships in synthetic aperture radar (SAR) images were modeled in 2-D with the computational fluid dynamics (CFD) software Fluent and a radar-imaging algorithm. We initialized the model with a pair of vortices generated by a ship hull and applied wind stress perpendicular to the ship wake. Results of the CFD simulation using a nonhydrostatic model have demonstrated ship-wake asymmetry with respect to the wind-stress direction relative to the ship course. Due to the wind stress, flow convergence increased on the upwind side of the centerline wake and reduced on the downwind side of the wake. The radar-imaging algorithm processed with the surface velocity field produced by the CFD model revealed ship-wake asymmetry relative to the wind direction. These results are qualitatively consistent with SAR images from the TerraSAR-X satellite and representative statistics of photographic images of the ship wake collected from a volunteer observing ship. © 2006 IEEE.


Volkov V.A.,Nansen International Environmental and Remote Sensing Center | Ivanov N.E.,Arctic and Antarctic Research Institute | Demchev D.M.,Arctic and Antarctic Research Institute
Journal of Operational Oceanography | Year: 2012

This paper considers the theoretical bases of the vectorial-algebraic method developed and applied in Russia for the time-series analysis of vector values - wind, currents and ice drift - and presents examples of the analysis of measurement data. The vectorial-algebraic approach allows the initial information to be significantly compressed and adequately describe the vector time-series of full-scale and model data restricted by a set of statistical characteristics in the invariant form. The methodology was used in the MyOcean Project (FP7).


Kantzas E.P.,University of Sheffield | Kantzas E.P.,Nansen International Environmental and Remote Sensing Center | Quegan S.,University of Sheffield | Lomas M.,University of Sheffield
Geoscientific Model Development | Year: 2015

Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to net ecosystem exchange in many biomes, even the most complex dynamic vegetation models (DVMs) embedded in general circulation models contain poor representations of fire behaviour and dynamics, such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected-component labelling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the obtained fire size probability distributions are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its fire return interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model; the fire regime is described by large-scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals) are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the modelled evolution of land cover, biomass and net ecosystem exchange after a fire. © Author(s) 2015.


Pozdnyakov D.,Nansen International Environmental and Remote Sensing Center | Petrenko D.,Nansen International Environmental and Remote Sensing Center
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2015

Spaceborne one month averaged data, predominantly from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and partly from the Moderate Resolution Imaging Spectroradiometer (MODIS), were used to investigate changes in primary production (PP) by phytoplankton in the Arctic Ocean from 1998 till 2010. Several PP retrieval algorithms were tested against the collected in situ data, and it was shown that the algorithm by Behrenfeld and Falkowski gave the best results (with the coefficient of correlation, r equal to 0.8 and 0.75, respectively, for the pelagic and shelf zones. Based on the performed test, the Behrenfeld and Falkowski algorithm was further applied for determining both the annual PP in the Arctic and the PP trend over the aforementioned time period. The results of our analysis indicate that PP in the Arctic has increased by ∼ 15.9% over 13 years. This finding, as well as the absolute annual values of PP remotely quantified in the present study, is at odds with analogous numerical assessments by other workers. These disagreements are thought to be due to differences in the applied methodologies of satellite data processing, such as cloud masking and determination of phytoplankton concentration within (i) overcast areas, and (ii) areas of massive growth of coccolithophore algae, as well as (iii) in the shelf zone prone to a significant influence of land and river runoff. Hindcast (a decadal long) and forecast projections of PP variations are performed.

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