scholarly journals Uncovering marine connectivity through sea surface temperature

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ljuba Novi ◽  
Annalisa Bracco ◽  
Fabrizio Falasca
Keyword(s):  
Large Scale ◽  
World Ocean ◽  
Marine Ecology ◽  
Ocean Currents ◽  
Data Availability ◽  
Sea Surface ◽  
Biological Communities ◽  
Data Sparseness ◽  
Water Characteristics ◽  
Marine Connectivity

AbstractA foundational paradigm in marine ecology is that Oceans are divided into distinct ecoregions demarking unique assemblages of species where the characteristics of water masses, and quantity and quality of environmental resources are generally similar. In most of the world Ocean, defining these ecoregions is complicated by data sparseness away of coastal areas and by the large-scale dispersal potential of ocean currents. Furthermore, ocean currents and water characteristics change in space and time on scales pertinent to the transitions of biological communities, and predictions of community susceptibility to these changes remain elusive. Given recent advances in data availability from satellite observations that are indirectly related to ocean currents, we are now poised to define ecoregions that meaningfully delimit marine biological communities based on their connectivity and to follow their evolution over time. Through a time-dependent complex network framework applied to a thirty-year long dataset of sea surface temperatures over the Mediterranean Sea, we provide compelling evidence that ocean ecoregionalization based on connectivity can be achieved at spatial and time scales relevant to conservation management and planning.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Subseasonal Forecasts of the Northern Queensland Floods of February 2019: Causes and Forecast Evaluation

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 758
Author(s):  
Wayne Yuan-Huai Tsai ◽  
Mong-Ming Lu ◽  
Chung-Hsiung Sui ◽  
Yin-Min Cho
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Austral Summer ◽  
Rainfall Event ◽  
Monsoon Depression ◽  
Forecast Skill ◽  
Sea Surface ◽  
Central Pacific ◽  
Percentile Rank ◽  
Extended Range

During the austral summer 2018/19, devastating floods occurred over northeast Australia that killed approximately 625,000 head of cattle and inundated over 3000 homes in Townsville. In this paper, the disastrous event was identified as a record-breaking subseasonal peak rainfall event (SPRE). The SPRE was mainly induced by an anomalously strong monsoon depression that was modulated by the convective phases of an MJO and an equatorial Rossby (ER) wave. The ER wave originated from an active equatorial deep convection associated with the El Niño warm sea surface temperatures near the dateline over the central Pacific. Based on the S2S Project Database, we analyzed the extended-range forecast skill of the SPRE from two different perspectives, the monsoon depression represented by an 850-hPa wind shear index and the 15-day accumulated precipitation characterized by the percentile rank (PR) and the ratio to the three-month seasonal (DJF) totals. The results of four S2S models of this study suggest that the monsoon depression can maintain the same level of skill as the short-range (3 days) forecast up to 8–10 days. For precipitation parameters, the conclusions are similar to the monsoon depression. For the 2019 northern Queensland SPRE, the model forecast was, in general, worse than the expectation derived from the hindcast analysis. The clear modulation of the ER wave that enhanced the SPRE monsoon depression circulation and precipitation is suspected as the main cause for the lower forecast skill. The analysis procedure proposed in this study can be applied to analyze the SPREs and their associated large-scale drivers in other regions.

scholarly journals Quantitative Recognition and Characteristic Analysis of Production-Living-Ecological Space Evolution for Five Resource-Based Cities: Zululand, Xuzhou, Lota, Surf Coast and Ruhr

2021 ◽  
Vol 13 (8) ◽  
pp. 1563
Author(s):  
Yuanyuan Tao ◽  
Qianxin Wang
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Large Scale ◽  
Remote Sensing Image ◽  
Data Availability ◽  
Function Evaluation ◽  
Characteristic Analysis ◽  
Accurate Identification ◽  
Living Space ◽  
Evolution Characteristics

The accurate identification of PLES changes and the discovery of their evolution characteristics is a key issue to improve the ability of the sustainable development for resource-based urban areas. However, the current methods are unsuitable for the long-term and large-scale PLES investigation. In this study, a modified method of PLES recognition is proposed based on the remote sensing image classification and land function evaluation technology. A multi-dimensional index system is constructed, which can provide a comprehensive evaluation for PLES evolution characteristics. For validation of the proposed methods, the remote sensing image, geographic information, and socio-economic data of five resource-based urbans (Zululand in South Africa, Xuzhou in China, Lota in Chile, Surf Coast in Australia, and Ruhr in Germany) from 1975 to 2020 are collected and tested. The results show that the data availability and calculation efficiency are significantly improved by the proposed method, and the recognition precision is better than 87% (Kappa coefficient). Furthermore, the PLES evolution characteristics show obvious differences at the different urban development stages. The expansions of production, living, and ecological space are fastest at the mining, the initial, and the middle ecological restoration stages, respectively. However, the expansion of living space is always increasing at any stage, and the disorder expansion of living space has led to the decrease of integration of production and ecological spaces. Therefore, the active polices should be formulated to guide the transformation of the living space expansion from jumping-type and spreading-type to filling-type, and the renovation of abandoned industrial and mining lands should be encouraged.

scholarly journals Can We Infer Diapycnal Mixing Rates from the World Ocean Temperature–Salinity Distribution?

2016 ◽  
Vol 46 (12) ◽  
pp. 3751-3775 ◽  
Author(s):  
Olivier Arzel ◽  
Alain Colin de Verdière
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Water Mass ◽  
World Ocean ◽  
Eddy Diffusivity ◽  
Regional Variability ◽  
Diapycnal Mixing ◽  
Inverse Models ◽  
The World ◽  
The Difference

AbstractThe turbulent diapycnal mixing in the ocean is currently obtained from microstructure and finestructure measurements, dye experiments, and inverse models. This study presents a new method that infers the diapycnal mixing from low-resolution numerical calculations of the World Ocean whose temperatures and salinities are restored to the climatology. At the difference of robust general circulation ocean models, diapycnal diffusion is not prescribed but inferred. At steady state the buoyancy equation shows an equilibrium between the large-scale diapycnal advection and the restoring terms that take the place of the divergence of eddy buoyancy fluxes. The geography of the diapycnal flow reveals a strong regional variability of water mass transformations. Positive values of the diapycnal flow indicate an erosion of a deep-water mass and negative values indicate a creation. When the diapycnal flow is upward, a diffusion law can be fitted in the vertical and the diapycnal eddy diffusivity is obtained throughout the water column. The basin averages of diapycnal diffusivities are small in the first 1500 m [O(10−5) m2 s−1] and increase downward with bottom values of about 2.5 × 10−4 m2 s−1 in all ocean basins, with the exception of the Southern Ocean (50°–30°S), where they reach 12 × 10−4 m2 s−1. This study confirms the small diffusivity in the thermocline and the robustness of the higher canonical Munk’s value in the abyssal ocean. It indicates that the upward dianeutral transport in the Atlantic mostly takes place in the abyss and the upper ocean, supporting the quasi-adiabatic character of the middepth overturning.

Contributions of Wind Forcing and Surface Heating to Interannual Sea Level Variations in the Atlantic Ocean

2006 ◽  
Vol 36 (9) ◽  
pp. 1739-1750 ◽  
Author(s):  
Cécile Cabanes ◽  
Thierry Huck ◽  
Alain Colin de Verdière
Keyword(s):  
Atlantic Ocean ◽  
Sea Level ◽  
Wind Stress ◽  
Large Scale ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Altimeter Data ◽  
Local Response ◽  
Sea Level Variability ◽  
Sea Level Variations

Abstract Interannual sea surface height variations in the Atlantic Ocean are examined from 10 years of high-precision altimeter data in light of simple mechanisms that describe the ocean response to atmospheric forcing: 1) local steric changes due to surface buoyancy forcing and a local response to wind stress via Ekman pumping and 2) baroclinic and barotropic oceanic adjustment via propagating Rossby waves and quasi-steady Sverdrup balance, respectively. The relevance of these simple mechanisms in explaining interannual sea level variability in the whole Atlantic Ocean is investigated. It is shown that, in various regions, a large part of the interannual sea level variability is related to local response to heat flux changes (more than 50% in the eastern North Atlantic). Except in a few places, a local response to wind stress forcing is less successful in explaining sea surface height observations. In this case, it is necessary to consider large-scale oceanic adjustments: the first baroclinic mode forced by wind stress explains about 70% of interannual sea level variations in the latitude band 18°–20°N. A quasi-steady barotropic Sverdrup response is observed between 40° and 50°N.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

SHIRSHOV INSTITUTE OF OCEANOLOGY 75 YEARS OLD

2021 ◽  
Vol 49 (3) ◽  
pp. 3-11
Author(s):  
A. V. Sokov
Keyword(s):  
Large Scale ◽  
World Ocean ◽  
Research Center ◽  
Shirshov Institute ◽  
The Past ◽  
The World ◽  
International Projects

This year in 2021, Shirshov Institute of Oceanology celebrated 75 years old. Shirshov Institute is the largest and oldest research center of seas and oceans in Russia. In the past and present of the Institute, there are many significant discoveries and developments for world oceanology, the most complex expeditions and large-scale international projects. I am sure that our future as a Center for the Study of the World Ocean will be no less rich and bright.

Oligocene sea-surface temperature gradients in the Southern Ocean related to Tasmanian Gateway widening: New TEX86 paleothermometry, dinoflagellate cyst data and climate model comparisons

2021 ◽  
Author(s):  
Frida Hoem ◽  
Suning Hou ◽  
Matthew Huber ◽  
Francesca Sangiorgi ◽  
Henk Brinkhuis ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Model ◽  
Temperature Gradients ◽  
Ocean Currents ◽  
Sea Surface ◽  
Dinoflagellate Cyst ◽  
Frontal Systems ◽  
Dsdp Site

<p>The opening of the Tasmanian Gateway during the Eocene and further deepening in the Oligocene is hypothesized to have reorganized ocean currents, preconditioning the Antarctic Circumpolar Current (ACC) to evolve into place. However, fundamental questions still remain on the past Southern Ocean structure. We here present reconstructions of latitudinal temperature gradients and the position of ocean frontal systems in the Australian sector of the Southern Ocean during the Oligocene. We generated new sea surface temperature (SST) and dinoflagellate cyst data from the West Tasman margin, ODP Site 1168. We compare these with other records around the Tasmanian Gateway, and with climate model simulations to analyze the paleoceanographic evolution during the Oligocene. The novel organic biomarker TEX<sub>86</sub>- SSTs from ODP Site 1168, range between 19.6 – 27.9°C (± 5.2°C, using the linear calibration by Kim et al., 2010), supported by temperate and open ocean dinoflagellate cyst assemblages. The data compilation, including existing TEX<sub>86</sub>-based SSTs from ODP Site 1172 in the Southwest Pacific Ocean, DSDP Site 274 offshore Cape Adare, DSDP Site 269 and IODP Site U1356 offshore the Wilkes Land Margin and terrestrial temperature proxy records from the Cape Roberts Project (CRP) on the Ross Sea continental shelf, show synchronous variability in temperature evolution between Antarctic and Australian sectors of the Southern Ocean. The SST gradients are around 10°C latitudinally across the Tasmanian Gateway throughout the early Oligocene, and increasing in the Late Oligocene. This increase can be explained by polar amplification/cooling, tectonic drift, strengthening of atmospheric currents and ocean currents. We suggest that the progressive cooling of Antarctica and the absence of mid-latitude cooling strengthened the westerly winds, which in turn could drive an intensification of the ACC and strengthening of Southern Ocean frontal systems.</p>

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