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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.

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.

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.

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.

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