Extreme convection in the Lofoten Basin of the Norwegian Sea

2021 ◽  
Author(s):  
Aleksandr M. Fedorov ◽  
Roshin P. Raj ◽  
Tatyana V. Belonenko ◽  
Elena V. Novoselova ◽  
Igor L. Bashmachnikov ◽  
...  
Keyword(s):  
Heat Release ◽  
Global Climate ◽  
Mixed Layer Depth ◽  
Water Volume ◽  
Convection Current ◽  
Mixing Depth ◽  
Sea Level Pressure ◽  
Factors Affecting ◽  
Strong Convection ◽  
Composite Maps

<p>One of the factors affecting the variability of the global climate is strong oceanic convection. Current research declares the results of the investigation on the extreme convection in the Lofoten Basin (LB) using the Argo profilers data. The most common parameter reflecting the convection intensity is Mixed Layer Depth (MLD). In the frames of the understudied period, MLD exceeds 1000 m in March-April and December 2010 in the Lofoten Basin Eddy (LBE), whereas the average MLD is about 200 m and rarely exceeds 400 m in the basin. Water volume formed at mid-depth of the central LB, between 1000 m depth and the isosteric surface s07 is connected with the extreme convection events. We analytically assess the final mixing depth that corresponds well to measured values of the MLD. Such a correspondence indicates the variations in the buoyancy flux and stratification as the main reasons for MLD variability in the LB. We easily explain this variability due to heat release in the basin. Atmospheric patterns during the extreme convection are described. It occurs that northerly winds are as common as dominating south-westerly winds during the months with extreme convection. 32 cases of extreme convective events with MLD exceeding 350 m were analyzed and we reveal that correspondent composite maps of Sea Level Pressure (SLP) and surface heat flux match well NAO-/EAP- atmospheric pattern in the Northern Atlantic, while negative NAO pattern prevails in climate during winter-spring. We define the heat release as the major trigger of strong convection. Heat release associated with extreme convection events in the LB is twice stronger than usual.</p>

scholarly journals On the geophysical processes impacting palaeo-sea-level observations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yusuke Yokoyama ◽  
Anthony Purcell
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Global Climate ◽  
Sea Level Change ◽  
Sea Level Changes ◽  
Factors Affecting ◽  
Ice Volume ◽  
Level Change ◽  
Recent Developments ◽  
Geophysical Processes

AbstractPast sea-level change represents the large-scale state of global climate, reflecting the waxing and waning of global ice sheets and the corresponding effect on ocean volume. Recent developments in sampling and analytical methods enable us to more precisely reconstruct past sea-level changes using geological indicators dated by radiometric methods. However, ice-volume changes alone cannot wholly account for these observations of local, relative sea-level change because of various geophysical factors including glacio-hydro-isostatic adjustments (GIA). The mechanisms behind GIA cannot be ignored when reconstructing global ice volume, yet they remain poorly understood within the general sea-level community. In this paper, various geophysical factors affecting sea-level observations are discussed and the details and impacts of these processes on estimates of past ice volumes are introduced.

scholarly journals How Blue Carbon Ecosystems Are Perceived by Local Communities in the Coral Triangle: Comparative and Empirical Examinations in the Philippines and Indonesia

2020 ◽  
Vol 13 (1) ◽  
pp. 127
Author(s):  
Jay Mar D. Quevedo ◽  
Yuta Uchiyama ◽  
Kevin Muhamad Lukman ◽  
Ryo Kohsaka
Keyword(s):  
Global Climate ◽  
Anthropogenic Activities ◽  
Local Level ◽  
Management Strategies ◽  
The Philippines ◽  
Local Communities ◽  
Blue Carbon ◽  
Utilization Rate ◽  
Coral Triangle ◽  
Factors Affecting

Blue carbon ecosystem (BCE) initiatives in the Coral Triangle Region (CTR) are increasing due to their amplified recognition in mitigating global climate change. Although transdisciplinary approaches in the “blue carbon” discourse and collaborative actions are gaining momentum in the international and national arenas, more work is still needed at the local level. The study pursues how BCE initiatives permeate through the local communities in the Philippines and Indonesia, as part of CTR. Using perception surveys, the coastal residents from Busuanga, Philippines, and Karimunjawa, Indonesia were interviewed on their awareness, utilization, perceived threats, and management strategies for BCEs. Potential factors affecting residents’ perceptions were explored using multivariate regression and correlation analyses. Also, a comparative analysis was done to determine distinctions and commonalities in perceptions as influenced by site-specific scenarios. Results show that, despite respondents presenting relatively high awareness of BCE services, levels of utilization are low with 42.9–92.9% and 23.4–85.1% respondents in Busuanga and Karimunjawa, respectively, not directly utilizing BCE resources. Regression analysis showed that respondents’ occupation significantly influenced their utilization rate and observed opposite correlations in Busuanga (positive) and Karimunjawa (negative). Perceived threats are found to be driven by personal experiences—occurrence of natural disasters in Busuanga whereas discerned anthropogenic activities (i.e., land-use conversion) in Karimunjawa. Meanwhile, recognized management strategies are influenced by the strong presence of relevant agencies like non-government and people’s organizations in Busuanga and the local government in Karimunjawa. These results can be translated as useful metrics in contextualizing and/or enhancing BCE management plans specifically in strategizing advocacy campaigns and engagement of local stakeholders across the CTR.

scholarly journals Multivariate clustering of reindeer herding districts in Sweden according to range prerequisites for reindeer husbandry

Rangifer ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 107-119
Author(s):  
Henrik Lundqvist ◽  
Öje Danell
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Global Climate ◽  
Meteorological Data ◽  
Principal Component ◽  
Geographical Information ◽  
Reindeer Herding ◽  
Factors Affecting ◽  
Decision Tools ◽  
Forage Value

The 51 reindeer herding districts in Sweden vary in productivity and prerequisites for reindeer herding. In this study we characterize and group reindeer herding districts based on relevant factors affecting reindeer productivity, i.e. topography, vegetation, forage value, habitat fragmentation and reachability, as well as season lengths, snow fall, ice-crust probability, and insect harassment, totally quantified in 15 variables. The herding districts were grouped into seven main groups and three single outliers through cluster analyses. The largest group, consisting of 14 herding districts, was further divided into four subgroups. The range properties of herding districts and groups of districts were characterized through principal component analyses. By comparisons of the suggested grouping of herding districts with existing administrative divisions, these appeared not to coincide. A new division of herding districts into six administrative sets of districts was suggested in order to improve administrative planning and management of the reindeer herding industry. The results also give possibilities for projections of alterations caused by an upcoming global climate change. Large scale investigations using geographical information systems (GIS) and meteorological data would be helpful for administrative purposes, both nationally and internationally, as science-based decision tools in legislative, economical, ecological and structural assessments. Abstract in Swedish / Sammanfattning: Multivariat gruppering av svenska samebyar baserat på renbetesmarkernas grundförutsettningar Svenska renskötselområdet består av 51 samebyar som varierar i produktivitet och förutsättningar för renskötsel. Vi analyserade variationen mellan samebyar med avseende på 15 variabler som beskriver topografi, vegetation, betesvärde, fragmentering av betesmarker, klimat, skareförekomst och aktivitet av parasiterande insekter och vi föreslår en indelning av samebyar i tio grupper. Den största gruppen, som bestod av 14 samebyar, delades vidare in i 4 undergrupper. Klusteranalyser med 4 olika linkage-varianter användes till att gruppera samebyarna. Principalkomponentsanalys användes för att kartlägga undersökta variabler och de resulterande samebygruppernas karaktär. Samebygrupperna följde inte länsgränser och tre samebyar föll ut som enskilda grupper. Denna undersökning ger underlag för jämförelser mellan samebyar med beaktande av likheter och olikheter i fråga om produktivitet och funktionella särdrag istället för länsgränser och historik. Vi föreslår en ny administrativ indelning i sex områden som skulle kunna fungera som ett alternativt underlag för planering och beslut som rör produktionsaspekter i rennäringen. Resultaten ger också underlag för förutsägelser av förändringar i samebyars produktionsförutsättningar till följd av klimatförändringar.

Application of Machine Learning in Predicting Crude Oil Production Volume

2021 ◽  
Author(s):  
Okechukwu Prince Innocent
Keyword(s):  
Machine Learning ◽  
Crude Oil ◽  
Predictor Variable ◽  
Oil Production ◽  
Water Volume ◽  
Production Volume ◽  
Affecting Factors ◽  
Factors Affecting ◽  
Crude Oil Production ◽  
The Relationship

Abstract The production of oil is of great and immense significance as a source of energy worldwide. The major factors affecting the production volume of oil is classified into two groups namely the geological and the human factor. Each group comprises of factors affecting oilfield production volume. The challenge in this project is to find the variable for the crude oil production volume in an oilfield because there are numerous factors affecting the crude oil production volume in an oilfield. The objective of this paper is to provide a more accurate and efficient solution on how to predict the oil production volume. Furthermore, Machine Learning algorithm called Multiple Linear Regression was developed using Python programming Language to predict the production volume of oil in an oilfield. The model was developed and fitted to train and test the factors that affect and influence the oil production volume. After a several studies have been made, the affecting factors were provided from the oilfield which would be trained and tested in order to model the relationship between predictor variable and response variable which are the significant affecting factors and the oil production volume respectively. The predictor variables are the startup number of wells, the recovery percent of previous year, the injected water volume of previous year and the oil moisture content of previous year. The predictor variable is the oil production volume. Moreover, the model was found to possess greater utility in predicting the production volume of oil as it yielded an oil production volume output with an accuracy of 98 percent. The relationship between oil production volume and the affecting factors was observed and drawn to a perfect conclusion. This model can be of immense value in the oil and gas industry if implemented because of its ability to predict oilfield output more accurately. It is an invaluable and very efficient model for the oilfield manager and oil production manager.

Global Climate Model Performance over Alaska and Greenland

2008 ◽  
Vol 21 (23) ◽  
pp. 6156-6174 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman ◽  
Vladimir Romanovsky ◽  
Jens H. Christensen ◽  
Martin Stendel
Keyword(s):  
Sea Level ◽  
Root Mean Square ◽  
Global Climate ◽  
Systematic Errors ◽  
The Arctic ◽  
Future Climate Change ◽  
Mean Square ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Mean Square Errors

Abstract The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

scholarly journals The carbon cycle and carbon dioxide over Phanerozoic time: the role of land plants

1998 ◽  
Vol 353 (1365) ◽  
pp. 75-82 ◽  
Author(s):  
Robert A. Berner
Keyword(s):  
Organic Matter ◽  
Carbon Cycle ◽  
Vascular Plants ◽  
Global Climate ◽  
Carbon Isotopic Composition ◽  
Field Studies ◽  
Accelerated Weathering ◽  
Fossil Plants ◽  
Factors Affecting ◽  
Carbon Isotopic

A model (GEOCARB) of the long–term, or multimillion year, carbon cycle has been constructed which includes quantitative treatment of (1) uptake of atmospheric CO 2 by the weathering of silicate and carbonate rocks on the continents, and the deposition of carbonate minerals and organic matter in oceanic sediments; and (2) the release of CO 2 to the atmosphere via the weathering of kerogen in sedimentary rocks and degassing resulting from the volcanic–metamorphic–diagenetic breakdown of carbonates and organic matter at depth. Sensitivity analysis indicates that an important factor affecting CO 2 was the rise of vascular plants in the Palaeozoic. A large Devonian drop in CO 2 was brought about primarily by the acceleration of weathering of silicate rock by the development of deeply rooted plants in well–drained upland soils. The quantitative effect of this accelerated weathering has been crudely estimated by present–day field studies where all factors affecting weathering, other than the presence or absence of vascular plants, have been held relatively constant. An important additional factor, bringing about a further CO 2 drop into the Carboniferous and Permian, was enhanced burial of organic matter in sediments, due probably to the production of microbially resistant plant remains (e.g. lignin). Phanerozoic palaeolevels of atmospheric CO 2 calculated from the GEOCARB model generally agree with independent estimates based on measurements of the carbon isotopic composition of palaeosols and the stomatal index for fossil plants. Correlation of CO 2 levels with estimates of palaeoclimate suggests that the atmospheric greenhouse effect has been a major factor in controlling global climate over the past 600 million years.

The impact of a parameterisation of submesoscale mixed layer eddies on mixed layer depths in the NEMO ocean model

2020 ◽  
Author(s):  
Daley Calvert ◽  
George Nurser ◽  
Mike Bell ◽  
Baylor Fox-Kemper
Keyword(s):  
Mixed Layer ◽  
Global Climate ◽  
Mixed Layer Depth ◽  
Mixing Layer ◽  
Ocean Model ◽  
Alternative Form ◽  
Depth Scale ◽  
Hadley Centre ◽  
The Impact ◽  
Global Mean

<p><span><span><span>A parameterisation scheme for restratification of the mixed layer by submesoscale mixed layer eddies is implemented in the NEMO ocean model. Its impact on the mixed layer depth (MLD) is examined in 30-year integrations of "uncoupled" ocean-ice and "coupled" atmosphere-ocean-ice-land global climate configurations used by the Met Office Hadley Centre. The specification of the mixed-layer Rossby radius in the scheme is shown to affect its impact on the MLD in the 1/4 degree uncoupled configuration by up to a factor of 2 in subtropical and mid-latitudes. This factor has been limited in the extent to which small mixed-layer Rossby radii are utilised to guard against CFL-type instabilities in the scheme, but such a limit was not found to be necessary for this implementation. An alternative form of the scheme is described that approximates the mixed-layer Rossby radius as a function only of latitude. This form is shown to yield similar results to the original formulation for an appropriate choice of parameters. The global mean impact of the scheme on the MLD is found to be almost twice as large in the 1 degree and 2 degree uncoupled configurations as it is in the 1/4 degree configuration, although the parameterised vertical buoyancy fluxes have closer agreement. This is shown to be the result of the scheme overcompensating for the decay in strength of resolved mixed layer density fronts in this model with decreasing horizontal grid resolution. The MLD criterion defining the depth scale of the scheme is shown to affect its global mean impact on the MLD by nearly a factor of 3 in the 1/4 degree uncoupled and coupled configurations, depending on whether the criterion is chosen to capture the actively mixing layer or well-mixed layer. Climatological MLD biases are improved overall in both cases, substantively reducing deep winter biases whilst slightly increasing shallow summer biases.</span></span></span></p>

scholarly journals Effects of Different Vegetation Zones on CH4and N2O Emissions in Coastal Wetlands: A Model Case Study

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Yuhong Liu ◽  
Lixin Wang ◽  
Shumei Bao ◽  
Huamin Liu ◽  
Junbao Yu ◽  
...  
Keyword(s):  
Coastal Wetlands ◽  
Coastal Wetland ◽  
Global Climate ◽  
N2o Emissions ◽  
Organic Carbon Content ◽  
Dndc Model ◽  
Model Case ◽  
Wetland Ecosystems ◽  
Factors Affecting ◽  
Vegetation Zones

The coastal wetland ecosystems are important in the global carbon and nitrogen cycle and global climate change. For higher fragility of coastal wetlands induced by human activities, the roles of coastal wetland ecosystems in CH4and N2O emissions are becoming more important. This study used a DNDC model to simulate current and future CH4and N2O emissions of coastal wetlands in four sites along the latitude in China. The simulation results showed that different vegetation zones, including bare beach,Spartinabeach, andPhragmitesbeach, produced different emissions of CH4and N2O in the same latitude region. Correlation analysis indicated that vegetation types, water level, temperature, and soil organic carbon content are the main factors affecting emissions of CH4and N2O in coastal wetlands.

scholarly journals Why Is the Influence of Sunspot Peaks on the Ocean and Atmosphere in Northern Winter Seen Mainly in the Pacific Region?

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Harry van Loon
Keyword(s):  
Surface Waters ◽  
Temperature Data ◽  
Sea Surface ◽  
Pacific Region ◽  
Sea Level Pressure ◽  
The Pacific ◽  
Dry Zone ◽  
Northern Winter ◽  
Strong Convection ◽  
Solar Influence

The sun at sunspot peaks enhances the climatological means in the Pacific region from the stratosphere to the surface of the sea. The robust signal is physically consistent and statistically significant in the 14 sunspot peaks for which sea-level pressure and sea-surface temperature data are available. No other place shows such a strong influence of the sunspot peaks in the northern winter. Why in the Pacific and why a cooling of equatorial surface waters at sunspot peaks? I suggest that in the Indonesian region the strong convection, higher and colder tropopause, warmer water, and Indonesian topography are conducive to channel the solar influence mainly to this region, leading to an enhancement of the Walker and Hadley circulations, expansion and intensification of the dry zone, and cooler equatorial surface waters.

Sign in / Sign up

Export Citation Format

Share Document