Comparing Two Models of Large-Scale White Sea Hydrodynamics and Thermal Dynamics

To calculate the water temperature of the White Sea we used two models of large-scale hydro-and thermal dynamics, maintained by the authors. Comparing two models, we show that the first one describes summer hydrophysical conditions better, while the second model is better for winter conditions. Now we are trying to improve and combine two models in order to describe the state of the Sea more accurately

Sensitivity of the coupled model of the White Sea dynamics and biochemistry

The JASMINE model based on the prof. N.G. Iakovlev's model of the Arctic Ocean (FEMAO) is the software complex for simulating hydrodynamics and thermal dynamics of a sea; we use the White Sea as an example and also have tried to model other seas. JASMINE allows coupling with special purpose blocks, such as data assimilation or simulation of the sea ecosystem. For that we chose the mature BFM model of pelagic sea biochemistry. An important question is sensitivity of the model with respect to the outer forcing, such as synoptic data (air temperature and pressure, cloud cover, precipitation, wind), boundary values on liquid boundaries, river run-off, initial distributions of the tracers. The White Sea is a convenient model region for such investigation because of dominating tides; thus boundary values become important, while initial distribution is expected not to influence on the results in the long run, at least. The biochemical system also depends on the boundary conditions strongly, and also reacts on the forcing variations. We describe the response of the sea subsystems to different variations of forcing, show what values are crucial and what is not important

The White Sea: Available Data and Numerical Models

The White Sea is a small shallow semi-closed sea in the North-West of Russia. It is strongly affected by induced tides, so the tidal motion dominates in the sea. Sea ice is seasonal and the water salinity is less than in the neighbouring Barents sea due to strong river discharge. We review the sources of in-situ and satellite data that are available for the sea, and describe those few numerical models, together with the challenges that are faced. We focus on the large-scale circulation and thermohaline fields, but also cover sea ice, river runoff, and pelagic biogeochemical data

Simulating Dynamics and Ecology of the Sea Ice of the White Sea by the Coupled Ice–Ocean Numerical Model

In this paper, a numerical model of the White Sea is presented. The White Sea is a small shallow sea with strong tidal currents and complex ice behavior. The model is the only comprehensive numerical model for the White Sea. It consists of several coupled submodels (for water, ice, pelagic, and sympagic ecology). In this work, the focus is on the dynamics of sea ice and its ecosystem. The model is described and its results are compared to available sea–ice data, mostly satellite data. The spatial resolution of the model is 3 km. High current velocities require the time step of 3 min. The model is shown to reproduce sea–ice concentration well; in particular, timing of the sea ice is perfect. The dynamics of the sea–ice ecosystem also looks reasonable. Chlorophyll-a content agrees well with measurements, and the ratio of algal, bacterial, and faunal biomass is correct. Sympagic biomass is underestimated. Light is limiting at the early stage of sympagic bloom, nutrient limitation is for the second half. We show that sympagic component influences the spring bloom (in terms of timing and height of the peaks) but has little effect on the dynamics during the warm period of the year

Task Scheduling in Desktop Grids: Open Problems

We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, “needle in a haystack” paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

The White Sea is a small shallow sea covered by ice in winter. There are very few numerical models of this sea. For the ice-free sea, much data has been collected, but for winter only a small amount (satellite data only). We use our finite-element numerical model Jasmine and satellite data to trace the ice advection and exchange between parts of the White Sea. The aim of the investigation is to adjust the model to adequately reproduce the White Sea ice dynamics. By comparing satellite data on sea-ice concentration with the model prediction, we show that the model describes sea-ice dynamics well, and use it to estimate ice flow from bays to the middle part of the sea and ice exchange through the narrow strait. Ice exchange between neighbouring parts of the sea is shown to be intensive, with large dispersion compared to the time-mean, and bays are shown to be ice producers, while the Gorlo straight is shown to accept ice. We demonstrate that the model is a tool that can be used to better understand the winter regime of the sea

Determination of biogeochemical properties in sea waters using the inversion of the three-stream irradiance model

International audienceInversion models, in the context of oceanography, relate the observed ocean color to the concentrations of the different biogeochemical components present in the water of the ocean. However, building accurate inversion models can be quite complex due to the many factors that can influence the observed ocean color, such as variations in the composition or the optical properties of biogeochemical products. Here we assess the feasibility of the inversion approach, by implementing the three-stream light inversion model in a one-dimensional water column configuration, represented at the BOUSSOLE site in the northwestern Mediterranean Sea. Moreover, we provide a comprehensive sensitivity analysis of the model's skill by perturbing the parameters of the bio-optical properties and phytoplankton physiology. Analysis of the inversion indicates that the model is able to reconstruct the variability of the optical constituents. Results indicate that chlorophyll-a and coloured dissolved organic matter play a major role in light modulation. The sensitivity analysis shows that the parameterization of the ratio of chlorophyll-a to carbon is important for the performance of the inversion model. A coherent inversion model, as presented, can be used as an observational operator to assimilate remote sensing reflectance.Satellites sensors provide useful data at different temporal and spatial scales to reconstruct the variability of marine ecosystems. Ocean color sensors in Earth orbit allow the derivation of spectral water leaving radiance and inference of physical and biogeochemical properties of the water masses 1 . In simple terms, the color of the sea is related to dissolved and particulate matter present in the water that for most of the ocean are of biological origin. In recent years, suitable algorithms have been developed to estimate the biogeochemical state of the oceans from measured radiance 2 . In particular, the derivation of water biogeochemical properties can be formulated in terms of the inversion of a forward problem. Mathematically, the so-called forward description resolves light propagation according to the properties of the medium in which the light propagates; the corresponding mathematical framework is well established 3 . In parallel, the inversion algorithms use the available information about the light field to retrieve the Inherent Optical Properties (IOPs) of the medium in which the light propagates. The major optical constituents of seawater in open oceans are phytoplankton, chromophoric dissolved organic matter (CDOM), and non algal particles (NAP) such as organic and mineral particles, bacteria, viruses and air bubbles. These biogeochemical components are important indicators of the ecosystem trophic regime and carbon pool formation 4 and are among the most common products derived from inversion algorithms 2 . In addition, these indicators are extremely useful to validate surface dynamics of coupled hydrodynamic biogeochemical ocean models, by comparing the distribution of satellite-derived biogeochemical products with corresponding distributions derived from model simulations 5 .Traditionally, biogeochemical models used a simple Beer-Lambert formulation to describe photosynthetically available radiation (PAR) propagation along the water column, i.e. the downwelling irradiance integrated over visible wavelengths (from 400 to 700 nm) that decays exponentially due to attenuation. In recent years, a</div

CDOM Spatiotemporal Variability in the Mediterranean Sea: A Modelling Study

International audienceThis study investigates the spatial and temporal variability of chromophoric-dissolved organic matter (CDOM) in the Mediterranean Sea. The analysis is carried out using a state-of-the-art 3D biogeochemical model. The model describes the plankton dynamics, the cycles of the most important limiting nutrients, and the particulate and dissolved pools of carbon. The source of CDOM is directly correlated to the dynamics of dissolved organic carbon (DOC) by a fixed production quota. Then CDOM degrades by photobleaching and remineralization. The main innovation of the system is the inclusion of a bio-optical radiative transfer model that computes surface upwelling irradiance, and therefore simulates remotely sensed reflectance (Rrs). Simulation results of three model configurations are evaluated using satellite Rrs, particularly at 412 nm, 443 nm, and 490 nm. All simulations show a winter minimum in Rrs for the considered bands. However, different parameterizations of DOC-release induce a different accumulation of CDOM, especially in the eastern Mediterranean, and a different Rrs signature: a more active microbial loop during summer implies a decrease of Rrs at 412 nm. We demonstrate how the usage of a bio-optical model allows us to corroborate hypotheses on CDOM-cycling based on blue–violet Rrs data, supporting the importance of this complementary data stream with respect to satellite-derived chlorophyll

Influence of Compression Loading on Acoustic Emission and Light Polarization Features in TeO₂ Crystal

Monitoring the processes inside crystalline materials under their operating conditions is of great interest in optoelectronics and scientific instrumentation. Early defect detection ensures the proper functioning of multiple crystal-based devices. In this study, a combination of acoustic emission (AE) sensing and cross-polarization imaging is proposed for the fast characterization of the crystal’s structure. For the experiments, tellurium dioxide (TeO2) crystal was chosen due to its wide use in acousto-optics. Studies were performed under uniaxial compression loading with a simultaneous acquisition of AE signals and four polarized optical images. An analysis of the temporal dependencies of the AE data and two-dimensional maps of the light depolarization features was carried out in order to establish quantitative criteria for irreversible damage initiation and crack-like defect formation. The obtained results reveal the polarization image patterns and the AE pulse duration alteration specific to these processes, and they open up new possibilities for non-destructively monitoring in real-time the structure of optically transparent crystals under their operating conditions