scholarly journals Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data

2017 ◽  
Vol 11 (4) ◽  
pp. 1553-1573 ◽  
Author(s):  
Gunnar Spreen ◽  
Ron Kwok ◽  
Dimitris Menemenlis ◽  
An T. Nguyen
Keyword(s):  
Sea Ice ◽  
Power Law ◽  
Large Scale ◽  
Remote Sensing Data ◽  
Satellite Observations ◽  
Small Scale ◽  
Grid Spacing ◽  
Model Solutions ◽  
Realistic Representation ◽  
The Right

Abstract. A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous–plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996–2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous–plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.

scholarly journals Sea Ice Deformation in a Coupled Ocean-Sea Ice Model and in Satellite Remote Sensing Data

2016 ◽  
Author(s):  
Gunnar Spreen ◽  
Ron Kwok ◽  
Dimitris Menemenlis ◽  
An T. Nguyen
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
Satellite Observations ◽  
The Arctic ◽  
Small Scale ◽  
Grid Spacing ◽  
Model Simulations ◽  
Ice Volume ◽  
Sensitivity Experiments ◽  
Ice Strength

Abstract. A realistic representation of sea ice deformation in models is important for accurate simulation of the sea ice mass balance. In this study, model ice strength sensitivity experiments show an increase in Arctic Basin sea ice volume of 7 % and 35 % for a decrease in ice strength of, respectively, 30 % and 70 %, after 8 years of model integration. This volume increase is caused by a combination of dynamic and thermodynamic processes. On the one hand, a weaker ice cover initially produces more ice due to increased deformation and new ice growth. The thickening of the ice, on the other hand, increases the ice strength and decreases the sea ice volume export out of the Arctic Basin. The balance of these processes leads to a new equilibrium Arctic Basin ice volume. Simulated sea ice deformation strain rates from model simulations with 4.5, 9, and 18-km horizontal grid spacing are compared with synthetic aperture radar satellite observations (RGPS). All three model simulations can reproduce the large-scale ice deformation patterns but they do not reproduce all aspects of the observed deformation rates. The overall sea ice deformation rate is about 50 % lower in all model solutions than in the satellite observations, especially in the seasonal sea ice zone. Small scale sea ice deformation and linear kinematic features are not adequately reproduced. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. Overall, the 4.5-km simulation produces the lowest misfits in divergence, vorticity, and shear when compared with RGPS data. Not addressed in this study is whether the differences between simulated and observed deformation rates are an intrinsic limitation of the viscous-plastic sea ice rheology that was used in the sensitivity experiments, or whether it indicates a lack of adjustment of existing model parameters to better represent these processes. Either way, this study provides new quantitative metrics for existing and new sea ice rheologies to strive for.

Atmospheric forcing of coastal polynyas in the south-western Weddell Sea

2015 ◽  
Vol 27 (4) ◽  
pp. 388-402 ◽  
Author(s):  
Verena Haid ◽  
Ralph Timmermann ◽  
Lars Ebner ◽  
Günther Heinemann
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Weddell Sea ◽  
Small Scale ◽  
Atmospheric Conditions ◽  
Atmospheric Forcing ◽  
The South ◽  
Ice Production

AbstractThe development of coastal polynyas, areas of enhanced heat flux and sea ice production strongly depend on atmospheric conditions. In Antarctica, measurements are scarce and models are essential for the investigation of polynyas. A robust quantification of polynya exchange processes in simulations relies on a realistic representation of atmospheric conditions in the forcing dataset. The sensitivity of simulated coastal polynyas in the south-western Weddell Sea to the atmospheric forcing is investigated with the Finite-Element Sea ice-Ocean Model (FESOM) using daily NCEP/NCAR reanalysis data (NCEP), 6 hourly Global Model Europe (GME) data and two different hourly datasets from the high-resolution Consortium for Small-Scale Modelling (COSMO) model. Results are compared for April to August in 2007–09. The two coarse-scale datasets often produce the extremes of the data range, while the finer-scale forcings yield results closer to the median. The GME experiment features the strongest winds and, therefore, the greatest polynya activity, especially over the eastern continental shelf. This results in higher volume and export of High Salinity Shelf Water than in the NCEP and COSMO runs. The largest discrepancies between simulations occur for 2008, probably due to differing representations of the ENSO pattern at high southern latitudes. The results suggest that the large-scale wind field is of primary importance for polynya development.

scholarly journals Size and frequency of natural forest disturbances and the Amazon forest carbon balance

2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Fernando D.B. Espírito-Santo ◽  
Manuel Gloor ◽  
Michael Keller ◽  
Yadvinder Malhi ◽  
Sassan Saatchi ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Large Scale ◽  
Carbon Sink ◽  
Remote Sensing Data ◽  
Biomass Accumulation ◽  
Airborne Lidar ◽  
Small Scale ◽  
Amazon Forest ◽  
Natural Forests ◽  
Landscape Scales

Abstract Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.28 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.01 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.003 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

scholarly journals Toward a method for downscaling sea ice pressure

2020 ◽  
Author(s):  
Jean-Francois Lemieux ◽  
Bruno Tremblay ◽  
Mathieu Plante
Keyword(s):  
High Pressure ◽  
Sea Ice ◽  
Numerical Experiments ◽  
Large Scale ◽  
High Stress ◽  
Small Scale ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
High Stress Concentration ◽  
Ice Pressure

Abstract. Sea ice pressure poses great risk for navigation; it can lead to ship besetting and damages. Contemporary large-scale sea ice forecasting systems can predict the evolution of sea ice pressure. There is, however, a mismatch between the spatial resolution of these systems (a few km) and the typical dimensions of ships (a few tens of m) navigating in ice-covered regions. In this paper, we investigate the downscaling of sea ice pressure from the km-scale to scales relevant for ships. Results show that sub-grid scale pressure values can be significantly larger than the large-scale pressure (up to $\\sim$ 4x larger in our numerical experiments). High pressure at the sub-grid scale is associated with the presence of defects (e.g. a lead). Numerical experiments show that a ship creates its own high stress concentration by forming a lead in its wake while navigating. These results also highlight the difficulty of forecasting the small-scale distribution of pressure and especially the largest values. Indeed, this distribution strongly depends on variables that are not well constrained: the rheology parameters and the small-scale structure of sea ice thickness (more importantly the length of the lead behind the ship).

Small-angle scattering behavior of thread-like and film-like systems

2016 ◽  
Vol 49 (1) ◽  
pp. 260-276 ◽  
Author(s):  
Salvino Ciccariello ◽  
Pietro Riello ◽  
Alvise Benedetti
Keyword(s):  
Small Angle ◽  
Large Scale ◽  
Probability Function ◽  
Structural Parameters ◽  
Small Angle Scattering ◽  
Constant Thickness ◽  
Small Scale ◽  
Linear Segment ◽  
Angle Scattering ◽  
The Right

Film-like and thread-like systems are, respectively, defined by the property that one of the constituting homogenous phases has a constant thickness (δ) or a constant normal cross section (of largest chord δ). The stick probability function of this phase, in the limit δ → 0, naturally leads to the definition of the correlation function (CF) of a surface or of a curve. This CF closely approximates the generating stick probability function in the range of distances larger than δ. The surface and the curve CFs, respectively, behave as 1/rand as 1/r2asrapproaches zero. This result implies that the relevant small-angle scattering intensities behave as {\cal P}_{{\cal S}}/q^2 or as {\cal P}_{{\cal C}}/q in the intermediate range of the scattering vector magnitude (q) and as {\cal P}/q^4 in the outermostqrange. Similarly to {\cal P}, pre-factors {\cal P}_{{\cal S}} and {\cal P}_{{\cal C}} simply depend on some structural parameters. Depending on the scale resolution it may happen that a given sample looks thread like at large scale, film like at small scale and particulate at a finer scale. An explicit example is reported. As a practical illustration of the above results, the surface and the curve CFs of some simple geometrical shapes have been explicitly evaluated. In particular, the CF of the right circular cylinder is evaluated. Its limits, as the height or the diameter the cylinder approaches zero, are shown to coincide with the CFs of a circle and of a linear segment, respectively.

Bridging the Nano-gap: From Scientific Discovery to Real World Products

2009 ◽  
Vol 1209 ◽  
Author(s):  
Partha Sarathi Dutta
Keyword(s):  
Large Scale ◽  
Scientific Discovery ◽  
High Volume ◽  
Small Scale ◽  
Global Business ◽  
Personal Learning ◽  
Start Up ◽  
Business Entities ◽  
Value Add ◽  
The Right

AbstractGoing from a small scale laboratory invention or discovery to a large scale application is not a trivial task and incorporating them into a product for a viable business is even more difficult. As technologies approach final products and applications, the number of criteria it must meet increases exponentially. Economics of the manufacturing process, environmental issues, intellectual property management, etc. needs to be assessed and monitored carefully. Bridging the gap from research to business not only needs multi-disciplinary understanding of the various aspects of the technology, but also how and what it could potentially enable or replace in current technologies and how to go about it through partnerships with global business entities. Especially with new materials, such as nano-scale materials, technology push needs to be rigorous and often the end results are uncertain. One needs to start from a large number of end user applications and narrow down to 1-2 high value-add or high volume opportunities. This process also requires constant development of the existing products to meet the exact needs for the high opportunity end markets. Timing for such efforts is crucial and the resources needed for such activities are often under-estimated by small start-up firms. Even for materials with well understood end products and established markets, significant market pull requires huge investments in product reliability demonstrations, cost of manufacturing, etc. Innovation, flexibility, change, educated risk, adaptability, focus and excellence are all key drivers and necessary ingredients for a successful and sustainable start-up venture. While scientific and engineering innovations are absolutely necessary, the metric for success for any business is revenue generation. Finding the right mechanisms for closing this gap (so-called the valley of death) is where the innovations of entrepreneurs lies. In this paper, I will share some of my personal learning experiences through the start-up company Applied Nanoworks Inc., (now Auterra Inc.).

scholarly journals Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data

2021 ◽  
Vol 13 (22) ◽  
pp. 4709
Author(s):  
Haiyang Shi ◽  
Qun Pan ◽  
Geping Luo ◽  
Olaf Hellwich ◽  
Chunbo Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Environmental Factors ◽  
Satellite Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Data ◽  
Small Scale ◽  
Driving Mechanism ◽  
Hole Density ◽  
Northern Slope ◽  
Sensing Data

Understanding the impacts of environmental factors on spatial–temporal and large-scale rodent distribution is important for rodent damage prevention. Investigating rat hole density (RHD) is one of the most effective methods to obtain the intensity of rodent damage. However, most of the previous field surveys or UAV-based remote sensing methods can only evaluate small-scale RHD and its influencing factors. However, these studies did not consider large-scale temporal and spatial heterogeneity. Therefore, we collected small-scale and in situ measurement records of RHD on the northern slope of the Tien Shan Mountains in Xinjiang (NTXJ), China, from 1982 to 2015, and then used correlation analysis and Bayesian network (BN) to analyze the environmental impacts on large-scale RHD with satellite remote sensing data such as the GIMMS NDVI product. The results show that the built BN can better quantify causality in the environmental mechanism modeling of RHD. The NDVI and LAI data from satellite remote sensing are important to the spatial–temporal RHD distribution and the mapping in the future. In regions with an elevation higher than 600 m (UPR) and lower than 600 m (LWR) of NTXJ, there are significant differences in the driving mechanism patterns of RHD, which are dependent on the elevation variation. In LWR, vegetation conditions have a weaker impact on RHD than UPR. It is possibly due to the Artemisia eaten by the dominant species Lagurus luteus (LL) in UPR being more sensitive to precipitation and temperature if compared with the Haloxylon ammodendron eaten by the Rhombomys opimus (RO) in LWR. In LWR, grazing intensity is more strongly and positively correlated to RHD than UPR, possibly due to both winter grazing and RO dependency on vegetation distribution; moreover, in UPR, sheep do not feed Artemisia as the main food, and the total vegetation is sufficient for sheep and LL to coexist. Under the different conditions of water availability of LWR and UPR, grazing may affect the ratio of aboveground and underground biomass by photosynthate allocation, thereby affecting the distribution of RHD. In extremely dry years, the RHD of LWR and UPR may have an indirect interactive relation due to changes in grazing systems.

scholarly journals Tierra, trabajo y reforma agraria en la Segunda República española (1931-1936): algunas consideraciones críticas

2017 ◽  
pp. 7-36 ◽  
Author(s):  
Ricardo Robledo ◽  
Ángel Luis González Esteban
Keyword(s):  
Twentieth Century ◽  
Land Reform ◽  
Large Scale ◽  
Small Scale ◽  
Farm Worker ◽  
Second Republic ◽  
Agricultural Reform ◽  
Social Unrest ◽  
Small Scale Farmers ◽  
The Right

The brief existence of the Second Republic and its violent end tend to favor the usual negative view of land reform. This article analyzes the perceptions of inefficiency and contradictory effects of the twentieth-century agr icultural reform, in contrast with the thesis of an active and extremely efficient market following the liberal refor ms of the nineteenth century. The second part of the paper focuses on recent historiographical research that considers the main cause of pre-Civil War social unrest to have been the labor polic y launched by the Socialists in 1931, which was also seen as a decisive factor in the swing towards the right of mid- and small-scale farmers. This article defends the viability of an agricultural reform that proved beneficial for the average farm worker. The initial costs of adaptation to the reform are explained, along with the hostility of Spain’s large-scale farmers to collective bargaining, an approach which had been institutionalized elsewhere through social policies.

scholarly journals The Use of Erts Photographs to Measure the Movement and Deformation of Sea Ice

1975 ◽  
Vol 15 (73) ◽  
pp. 429-436
Author(s):  
J. F. Nye
Keyword(s):  
Sea Ice ◽  
Continuum Model ◽  
Large Scale ◽  
Small Scale ◽  
Strain Rates ◽  
Pack Ice ◽  
Ice Velocity ◽  
Movement And Deformation ◽  
Preliminary Study ◽  
Displacement Measurements

AbstractIs it justified to adopt a two-dimensional continuum model for the movement and large-scale deformation of pack ice? A preliminary study oi’ ERTS-1 photography shows that the details of the ice movement are readily measurable; the problem is not in the accuracy of the remote sensing but in the inherent graininess of the sea ice. There is a spatial variation of ice velocity on a scale of several hundreds of kilometres; smaller-scale variations are superimposed on this, but their amplitude is not enough to obscure the large-scale trend. A continuum model is applicable, but, because of the small-scale variations in the velocity of the sea ice itself, it is not meaningful to specify continuum strain-rates on a scale of, say, 100 km to more than a certain accuracy, If ERTS pictures are available during the AIDJEX main experiment they could provide the necessary strain and displacement measurements for comparison with the predictions of the AIDJEX model.

scholarly journals Estimating Early-Winter Antarctic Sea Ice Thickness From Deformed Ice Morphology

2019 ◽  
Author(s):  
M. Jeffrey Mei ◽  
Ted Maksym ◽  
Hanumant Singh
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Relative Error ◽  
Snow Depth ◽  
Large Scale ◽  
Small Scale ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Mean Relative Error ◽  
Antarctic Sea Ice

Abstract. Satellites have documented variability in sea ice areal extent for decades, but there are significant challenges in obtaining analogous measurements for sea ice thickness data in the Antarctic, primarily due to difficulties in estimating snow cover on sea ice. Sea ice thickness can be estimated from surface elevation measurements, such as those from airborne/satellite LiDAR, by assuming some snow depth distribution or empirically fitting with limited data from drilled transects from various field studies. Current estimates for large-scale Antarctic sea ice thickness have errors as high as ~ 50 %, and simple statistical models of small-scale mean thickness have similarly high errors. Averaging measurements over hundreds of meters can improve the model fits to existing data, though these results do not necessarily generalize to other floes. At present, we do not have algorithms that accurately estimate sea ice thickness at high resolutions. We use a convolutional neural network with laser altimetry profiles of sea ice surfaces at 0.2 m resolution to show that it is possible to estimate sea ice thickness at 20 m resolution with better accuracy and generalization than current methods (mean relative errors ~ 15 %). Moreover, the neural network does not require specifying snow depth/density, which increases its potential applications to other LiDAR datasets. The learned features appear to correspond to basic morphological features, and these features appear to be common to other floes with the same climatology. This suggests that there is a relationship between the surface morphology and the ice thickness. The model has a mean relative error of 20 % when applied to a new floe from the region and season, which is much lower than the mean relative error for a linear fit (errors up to 47 %). This method may be extended to lower-resolution, larger-footprint data such as such as IceBridge, and suggests a possible avenue to reduce errors in satellite estimates of Antarctic sea ice thickness from ICESat-2 over current methods, especially at smaller scale.

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