scholarly journals Historical variation and trends in storminess along the Portuguese South Coast

2011 ◽  
Vol 11 (9) ◽  
pp. 2407-2417 ◽  
Author(s):  
L. P. Almeida ◽  
Ó. Ferreira ◽  
M. I. Vousdoukas ◽  
G. Dodet
Keyword(s):  
Wave Height ◽  
Linear Increase ◽  
Annual Number ◽  
The North ◽  
Storm Wave ◽  
Using Data ◽  
The North Atlantic Oscillation ◽  
Historical Variation ◽  
Storm Characteristics ◽  
South Portugal

Abstract. This work investigates historical variation and trends in storm climate for the South Portugal region, using data from wave buoy measurements and from modelling, for the period 1952 to 2009. Several storm parameters (annual number of storms; annual number of days with storms; annual maximum and mean individual storm duration and annual 99.8th percentile of significant wave height) were used to analyse: (1) historical storminess trends; (2) storm parameter variability and relationships; and (3) historical storminess and its relationship to the North Atlantic Oscillation (NAO). No statistically significant linear increase or decrease was found in any of the storm parameters over the period of interest. The main pattern of storm characteristics and extreme wave heights is an oscillatory variability with intensity peaks every 7–8 yr, and the magnitude of recent variations is comparable with that of variations observed in the earlier parts of the record. In addition, the results reveal that the NAO index is able to explain only a small percentage of the variation in storm wave height, suggesting that more local factors may be of importance in controlling storminess in this region.

scholarly journals The Interannual Variability of Tropical Cyclones

2007 ◽  
Vol 135 (10) ◽  
pp. 3587-3598 ◽  
Author(s):  
William M. Frank ◽  
George S. Young
Keyword(s):  
Tropical Cyclone ◽  
Interannual Variability ◽  
Tropical Cyclones ◽  
Large Scale ◽  
Storm Activity ◽  
Modes Of Variability ◽  
The North ◽  
Temporal And Spatial ◽  
Using Data ◽  
The North Atlantic Oscillation

Abstract This paper examines the interannual variability of tropical cyclones in each of the earth’s cyclone basins using data from 1985 to 2003. The data are first analyzed using a Monte Carlo technique to investigate the long-standing myth that the global number of tropical cyclones is less variable than would be expected from examination of the variability in each basin. This belief is found to be false. Variations in the global number of all tropical cyclones are indistinguishable from those that would be expected if each basin was examined independently of the others. Furthermore, the global number of the most intense storms (Saffir–Simpson categories 4–5) is actually more variable than would be expected because of an observed tendency for storm activity to be correlated between basins, and this raises important questions as to how and why these correlations arise. Interbasin correlations and factor analysis of patterns of tropical cyclone activity reveal that there are several significant modes of variability. The largest three factors together explain about 70% of the variance, and each of these factors shows significant correlation with ENSO, the North Atlantic Oscillation (NAO), or both, with ENSO producing the largest effects. The results suggest that patterns of tropical cyclone variability are strongly affected by large-scale modes of interannual variability. The temporal and spatial variations in storm activity are quite different for weaker tropical cyclones (tropical storm through category 2 strength) than for stronger storms (categories 3–5). The stronger storms tend to show stronger interbasin correlations and stronger relationships to ENSO and the NAO than do the weaker storms. This suggests that the factors that control tropical cyclone formation differ in important ways from those that ultimately determine storm intensity.

scholarly journals On the Changes in the Number and Intensity of North Atlantic Tropical Cyclones

2008 ◽  
Vol 21 (6) ◽  
pp. 1387-1402 ◽  
Author(s):  
William M. Briggs
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Power Dissipation ◽  
Storm Track ◽  
Atlantic Multidecadal Oscillation ◽  
Linear Increase ◽  
Track Length ◽  
Storm Intensity ◽  
The North ◽  
Using Data

Abstract Bayesian statistical models were developed for the number of tropical cyclones, the rate at which these cyclones became hurricanes, and the rate at which hurricanes became category 4+ storms in the North Atlantic using data from 1966 to 2006 and from 1975 to 2006. It is found that, controlling for the cold tongue index (CTI), North Atlantic Oscillation index (NAOI), and the Atlantic Multidecadal Oscillation (AMO), it is improbable that the number of tropical cyclones has linearly increased since 1966, but that the number has increased since 1975. The differences between these two results have to do with the numbers of storms at the start of these two periods: it was easier to say a linear increase was present starting from circa 1975 since the storms in that period were at a low point. The rate at which storms become hurricanes appears to have decreased, and the rate at which category 4+ storms evolved from hurricanes appears to have increased. Both of these results are also dependent on the starting year. Storm intensity was also investigated by measuring the distribution of individual storm lifetimes in days, storm track length, and Emanuel’s power dissipation index. Little evidence was found that mean individual storm intensity has changed through time, but it is noted that the variability of intensity has certainly increased. Any increase in cumulative yearly storm intensity and potential destructiveness is therefore due to the increasing number of storms and not due to any increase in the intensity of individual storms. CTI was not always significant, but lower CTIs were associated with more storms, higher rates of conversion, and higher intensities. NAOI was only weakly associated: the effect was negative for the number of storms, the rate of hurricanes evolving from storms, and intensity, but it was positive for the rate of category 4+ storms evolving from hurricanes. AMO was rarely significant except in explaining the number of storms using the 1966–2006 data. Its direction was always positive as expected; however, higher values of the AMO were associated with more storms, higher rates of conversion, and higher intensities.

scholarly journals Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

2016 ◽  
Vol 472 (2193) ◽  
pp. 20160376 ◽  
Author(s):  
H. Santo ◽  
P. H. Taylor ◽  
R. Gibson
Keyword(s):  
Wave Height ◽  
North Sea ◽  
North Atlantic ◽  
Decadal Variability ◽  
Climate Indices ◽  
Extreme Wave ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958–2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

IMPLEMENTASI ALGORITMA K-Modes UNTUK MENENTUKAN STRATEGI MARKETING STMIK BUDI DARMA

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Ewin Karman Nduru ◽  
Efori Buulolo ◽  
Pristiwanto Pristiwanto
Keyword(s):  
High School ◽  
Data Mining ◽  
High School Students ◽  
Marketing Strategy ◽  
Process Data ◽  
School Students ◽  
The North ◽  
The Government ◽  
Using Data ◽  
North Sumatra

Universities or institutions that operate in North Sumatra are very many, therefore, of course, competition in accepting new students is very tight, universities or institutions do certain ways or steps to be able to compete with other campuses in gaining interest from community or high school students who will continue their studies to a higher level. STMIK BUDI DARMA Medan (College of Information and Computer Management), is the first computer high school in Medan which was established on March 1, 1996 and received approval from the government through the Minister of Education and Culture, on July 23, 1996 with operating license number 48 / D / O / 1996, in promoting the campus, the team usually formed a promotion team to various regions in the North Sumatra Region to provide information to the community. Students who have learned in this campus are quite a lot who come from various regions in North Sumatra, from this point the need to process data from students who are active in college to be processed using data mining to achieve a target, one method that can be used in data mining, namely the ¬K-Modes clustering (grouping) algorithm. This method is a grouping of student data that will be a help to campus students in promoting, using the K-Modes algorithm is expected to help and become a reference for marketing in determining the marketing strategy STMIK Budi Darma MedanKeywords: STMIK Budi Darma, Marketing Strategy, K-Modes Algorithm.

scholarly journals Influence of the North Atlantic oscillation on the atmospheric levels of benzo[a]pyrene over Europe

2021 ◽  
Author(s):  
Pedro Jiménez-Guerrero ◽  
Nuno Ratola
Keyword(s):  
Spatial Pattern ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Transport Model ◽  
Regional Scale ◽  
The South ◽  
Climatic Fluctuations ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe atmospheric concentration of persistent organic pollutants (and of polycyclic aromatic hydrocarbons, PAHs, in particular) is closely related to climate change and climatic fluctuations, which are likely to influence contaminant’s transport pathways and transfer processes. Predicting how climate variability alters PAHs concentrations in the atmosphere still poses an exceptional challenge. In this sense, the main objective of this contribution is to assess the relationship between the North Atlantic Oscillation (NAO) index and the mean concentration of benzo[a]pyrene (BaP, the most studied PAH congener) in a domain covering Europe, with an emphasis on the effect of regional-scale processes. A numerical simulation for a present climate period of 30 years was performed using a regional chemistry transport model with a 25 km spatial resolution (horizontal), higher than those commonly applied. The results show an important seasonal behaviour, with a remarkable spatial pattern of difference between the north and the south of the domain. In winter, higher BaP ground levels are found during the NAO+ phase for the Mediterranean basin, while the spatial pattern of this feature (higher BaP levels during NAO+ phases) moves northwards in summer. These results show deviations up to and sometimes over 100% in the BaP mean concentrations, but statistically significant signals (p<0.1) of lower changes (20–40% variations in the signal) are found for the north of the domain in winter and for the south in summer.

scholarly journals Detecting Climate Driven Changes in Chlorophyll-a in Deep Subalpine Lakes Using Long Term Satellite Data

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 866
Author(s):  
Gary Free ◽  
Mariano Bresciani ◽  
Monica Pinardi ◽  
Nicola Ghirardi ◽  
Giulia Luciani ◽  
...  
Keyword(s):  
Climate Change ◽  
Chlorophyll A ◽  
Nutrient Dynamics ◽  
Cascading Effects ◽  
The North ◽  
Subalpine Lakes ◽  
Winter Temperatures ◽  
Decadal Climate ◽  
The North Atlantic Oscillation ◽  
Traditional Pattern

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the subalpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in Lakes Garda, Como, Iseo, and Maggiore. In all four deep subalpine lakes, there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a. Variables that were significant in NPMR included time, air temperature, total phosphorus, winter temperature, and winter values for the North Atlantic Oscillation. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause was probably cascading effects from increased winter temperatures, reduced winter mixing, and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

scholarly journals Time-Delay Identification Using Multiscale Ordinal Quantifiers

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 969
Author(s):  
Miguel C. Soriano ◽  
Luciano Zunino
Keyword(s):  
Time Series ◽  
Time Delay ◽  
Real World ◽  
Propagation Speed ◽  
Real World Data ◽  
External Observer ◽  
The North ◽  
Weather Phenomenon ◽  
The North Atlantic Oscillation ◽  
Finite Propagation Speed

Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from time series of observed data. We explore, in this work, the properties of several ordinal-based quantifiers for the identification of time-delays from time series. To that end, we generate artificial time series of stochastic and deterministic time-delay models. We find that the presence of a nonlinearity in the generating model has consequences for the distribution of ordinal patterns and, consequently, on the delay-identification qualities of the quantifiers. Here, we put forward a novel ordinal-based quantifier that is particularly sensitive to nonlinearities in the generating model and compare it with previously-defined quantifiers. We conclude from our analysis on artificially generated data that the proper identification of the presence of a time-delay and its precise value from time series benefits from the complementary use of ordinal-based quantifiers and the standard autocorrelation function. We further validate these tools with a practical example on real-world data originating from the North Atlantic Oscillation weather phenomenon.

scholarly journals Middle Holocene Climate Oscillations Recorded in the Western Dvina Lakeland

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1611
Author(s):  
Agnieszka Mroczkowska ◽  
Dominik Pawłowski ◽  
Emilie Gauthier ◽  
Andrey Mazurkevich ◽  
Tomi P. Luoto ◽  
...  
Keyword(s):  
River System ◽  
Summer Temperature ◽  
Human Occupation ◽  
Holocene Climate ◽  
Climate History ◽  
Remarkable Feature ◽  
Climate Oscillations ◽  
Climate Fluctuations ◽  
The North ◽  
The North Atlantic Oscillation

Although extensive archeological research works have been conducted in the Serteya region in recent years, the Holocene climate history in the Western Dvina Lakeland in Western Russia is still poorly understood. The Neolithic human occupation of the Serteyka lake–river system responded to climate oscillations, resulting in the development of a pile-dwelling settlement between 5.9 and 4.2 ka cal BP. In this paper, we present the quantitative paleoclimatic reconstructions of the Northgrippian stage (8.2–4.2 ka cal BP) from the Great Serteya Palaeolake Basin. The reconstructions were created based on a multiproxy (Chironomidae, pollen and Cladocera) approach. The mean July air temperature remained at 17–20 °C, which is similar to the present temperature in the Smolensk Upland. The summer temperature revealed only weak oscillations during 5.9 and 4.2 ka cal BP. A more remarkable feature during those events was an increase in continentality, manifested by a lower winter temperature and lower annual precipitation. During the third, intermediate oscillation in 5.0–4.7 ka cal BP, a rise in summer temperature and stronger shifts in continental air masses were recorded. It is still unclear if the above-described climate fluctuations are linked to the North Atlantic Oscillation and can be interpreted as an indication of Bond events because only a few high-resolution paleoclimatic reconstructions from the region have been presented and these reconstructions do not demonstrate explicit oscillations in the period of 5.9 and 4.2 ka cal BP.

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