Cluster Models

2013 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger
Keyword(s):  
East Coast ◽  
Gulf Coast ◽  
Southern Oscillation ◽  
Time Correlation ◽  
Additional Time ◽  
Feature Clustering ◽  
The North ◽  
Time Space ◽  
Hurricane Activity ◽  
The North Atlantic Oscillation

A cluster is a group of the same or similar events close together. Clusters arise in hurricane origin locations, tracks, and landfalls. In this chapter, we look at how to analyze and model clusters. We divide the chapter into methods for time, space, and feature clustering. Of the three feature clustering is best known to climatologists. We begin by showing you how to detect and model time clusters. Consecutive hurricanes originating in the same area often take similar paths. This grouping, or clustering, increases the potential for multiple landfalls above what you expect from random events. A statistical model for landfall probability captures clustering through covariates like the North Atlantic Oscillation (NAO), which relates a steering mechanism (position and strength of the subtropical high pressure) to coastal hurricane activity. But there could be additional time correlation not related to the covariates. A model that does not account for this extra variation will underestimate the potential for multiple hits in a season. Following Jagger and Elsner (2006), you consider three coastal regions including the Gulf Coast, Florida, and the East Coast (Fig. 6.2). Regions are large enough to capture enough hurricanes, but not too large as to include many non-coastal strikes. Here you use hourly position and intensity data described in Chapter 6. For each hurricane, you note its wind speed maximum within each region. If the maximum wind exceeds 33 m s−1, then you count it as a hurricane for the region. A tropical cyclone that affects more than one region at hurricane intensity is counted in each region. Because of this, the sum of the regional counts is larger than the total count. Begin by loading annual.RData. These data were assembled in Chapter 6. Subset the data for years starting with 1866. . . . > load("annual.RData") > dat = subset(annual, Year >= 1866) . . . The covariate Southern Oscillation Index (SOI) data begins in 1866 . Next, extract all hurricane counts for the Gulf coast, Florida, and East coast regions. . . . > cts = dat[, c("G.1", "F.1", "E.1")] . . .

scholarly journals Observed Changes in Cyclone Activity in Canada and Their Relationships to Major Circulation Regimes

2006 ◽  
Vol 19 (6) ◽  
pp. 896-915 ◽  
Author(s):  
Xiaolan L. Wang ◽  
H. Wan ◽  
Val R. Swail
Keyword(s):  
Regression Analysis ◽  
Great Lakes ◽  
East Coast ◽  
Southern Oscillation ◽  
Linear Regression Analysis ◽  
Cyclone Activity ◽  
The North ◽  
The Pacific ◽  
Central Canada ◽  
The North Atlantic Oscillation

Abstract This study assessed the climate and trend of cyclone activity in Canada using mainly the occurrence frequency of cyclone deepening events and deepening rates, which were derived from hourly mean sea level pressure data observed at 83 Canadian stations for up to 50 years (1953–2002). Trends in the frequency of cyclone activity were estimated by logistic regression analysis, and trends of seasonal extreme cyclone intensity, by linear regression analysis. The results of trend analysis show that, among the four seasons, winter cyclone activity has shown the most significant trends. It has become significantly more frequent, more durable, and stronger in the lower Canadian Arctic, but less frequent and weaker in the south, especially along the southeast and southwest coasts. Winter cyclone deepening rates have increased in the zone around 60°N but decreased in the Great Lakes area and southern Prairies–British Columbia. However, extreme winter cyclone activity seems to have experienced a weaker increase in northwest-central Canada but a stronger decline in the Great Lakes area and in southern Prairies. The results also show more frequent summer cyclone activity with slower deepening rates on the east coast, as well as less frequent cyclone activity with faster deepening rates in the Great Lakes area in autumn. Cyclone activity in Canada was found to be closely related to the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and El Niño–Southern Oscillation (ENSO). Overall, cyclone activity in Canada is most closely related to the NAO. The simultaneous NAO index explains about 44% (41%) of the winter (autumn) cyclone activity variance in the east coast, 31% of winter cyclone activity variance in the 60°–70°N zone, and 17% of autumn cyclone activity variance in the Great Lakes area. Also, in several regions (e.g., the east coast, the southwest, and the 60°–70°N zone) up to 15% of the seasonal cyclone activity variance can be explained by the NAO/PDO/ENSO index one–three seasons earlier, which is useful for seasonal forecasting.

scholarly journals ENSO’s Impact on Regional U.S. Hurricane Activity

2007 ◽  
Vol 20 (7) ◽  
pp. 1404-1414 ◽  
Author(s):  
Shawn R. Smith ◽  
Justin Brolley ◽  
James J. O’Brien ◽  
Carissa A. Tartaglione
Keyword(s):  
North Atlantic ◽  
East Coast ◽  
Southern Oscillation ◽  
Regional Analysis ◽  
The North ◽  
Hurricane Season ◽  
Hurricane Activity ◽  
National Hurricane Center ◽  
Observational Record ◽  
The U.S

Abstract Regional variations in North Atlantic hurricane landfall frequency along the U.S. coastline are examined in relation to the phase of El Niño–Southern Oscillation (ENSO). ENSO warm (cold) phases are known to reduce (increase) hurricane activity in the North Atlantic basin as a whole. Using best-track data from the U.S. National Hurricane Center, regional analysis reveals that ENSO cold-phase landfall frequencies are only slightly larger than neutral-phase landfall frequencies along the Florida and Gulf coasts. However, for the East Coast, from Georgia to Maine, a significant decrease in landfall frequency occurs during the neutral ENSO phase as compared to the cold phase. Along the East Coast, two or more major (category 3 or above) hurricanes never made landfall in the observational record (1900–2004) during a single hurricane season classified as an ENSO neutral or warm phase.

Hurricane Clusters in the Vicinity of Florida

2012 ◽  
Vol 51 (5) ◽  
pp. 869-877 ◽  
Author(s):  
Thomas H. Jagger ◽  
James B. Elsner
Keyword(s):  
Poisson Distribution ◽  
North Atlantic ◽  
Cluster Model ◽  
Negative Binomial ◽  
Southern Oscillation ◽  
Inverse Gaussian ◽  
Gaussian Models ◽  
The North ◽  
Hurricane Activity ◽  
The North Atlantic Oscillation

AbstractModels that predict annual U.S. hurricane activity assume a Poisson distribution for the counts. Here the authors show that this assumption applied to Florida hurricanes leads to a forecast that underpredicts both the number of years without hurricanes and the number of years with three or more hurricanes. The underdispersion in forecast counts arises from a tendency for hurricanes to arrive in groups along this part of the coastline. The authors then develop an extension to their earlier statistical model that assumes that the rate of hurricane clusters follows a Poisson distribution with cluster size capped at two hurricanes. Hindcasts from the cluster model better fit the distribution of Florida hurricanes conditional on the climate covariates including the North Atlantic Oscillation and Southern Oscillation index. Results are similar to models that parameterize the extra-Poisson variation in the observed counts, including the negative binomial and the Poisson inverse Gaussian models. The authors argue, however, that the cluster model is physically consistent with the way Florida hurricanes tend to arrive in groups.

scholarly journals Prediction Models for Annual U.S. Hurricane Counts

2006 ◽  
Vol 19 (12) ◽  
pp. 2935-2952 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger
Keyword(s):  
Prediction Models ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Skill Levels ◽  
The North ◽  
Out Of Sample ◽  
Squared Prediction Error ◽  
Hurricane Activity ◽  
Modeling Strategy ◽  
The North Atlantic Oscillation

Abstract The authors build on their efforts to understand and predict coastal hurricane activity by developing statistical seasonal forecast models that can be used operationally. The modeling strategy uses May–June averaged values representing the North Atlantic Oscillation (NAO), the Southern Oscillation index (SOI), and the Atlantic multidecadal oscillation to predict the probabilities of observing U.S. hurricanes in the months ahead (July–November). The models are developed using a Bayesian approach and make use of data that extend back to 1851 with the earlier hurricane counts (prior to 1899) treated as less certain relative to the later counts. Out-of-sample hindcast skill is assessed using the mean-squared prediction error within a hold-one-out cross-validation exercise. Skill levels are compared to climatology. Predictions show skill above climatology, especially using the NAO + SOI and the NAO-only models. When the springtime NAO values are below normal, there is a heightened risk of U.S. hurricane activity relative to climatology. The preliminary NAO value for 2005 is −0.565 standard deviations so the NAO-only model predicts a 13% increase over climatology of observing three or more U.S. hurricanes.

scholarly journals Impacts of large-scale atmospheric circulation changes due to winter sea-ice retreat on Black Carbon transport and deposition to the Arctic

2016 ◽  
Author(s):  
Luca Pozzoli ◽  
Srdan Dobricic ◽  
Simone Russo ◽  
Elisabetta Vignati
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
The Arctic ◽  
The North ◽  
Ice Retreat ◽  
The North Atlantic Oscillation ◽  
Sea Ice Retreat

Abstract. Winter warming and sea ice retreat observed in the Arctic in the last decades determine changes of large scale atmospheric circulation pattern that may impact as well the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a new statistical algorithm, based on the Maximum Likelihood Estimate approach, to determine how the changes of three large scale weather patterns (the North Atlantic Oscillation, the Scandinavian Blocking, and the El Nino-Southern Oscillation), associated with winter increasing temperatures and sea ice retreat in the Arctic, impact the transport of BC to the Arctic and its deposition. We found that the three atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the Eastern Arctic while they increase BC deposition in the Western Arctic. The increasing trend is mainly due to the more frequent occurrences of stable high pressure systems (atmospheric blocking) near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. The North Atlantic Oscillation has a smaller impact on BC deposition in the Arctic, but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The El Nino-Southern Oscillation does not influence significantly the transport and deposition of BC to the Arctic. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.

scholarly journals Intraseasonal and Interannual Variability in North American Storm Tracks and Its Relationship to Equatorial Pacific Variability

2013 ◽  
Vol 141 (10) ◽  
pp. 3610-3625 ◽  
Author(s):  
Kevin M. Grise ◽  
Seok-Woo Son ◽  
John R. Gyakum
Keyword(s):  
North America ◽  
Interannual Variability ◽  
North American ◽  
Southern Oscillation ◽  
Extratropical Cyclones ◽  
The North ◽  
The Pacific ◽  
Cyclone Tracks ◽  
Lagrangian Tracking ◽  
The North Atlantic Oscillation

Abstract Extratropical cyclones play a principal role in wintertime precipitation and severe weather over North America. On average, the greatest number of cyclones track 1) from the lee of the Rocky Mountains eastward across the Great Lakes and 2) over the Gulf Stream along the eastern coastline of North America. However, the cyclone tracks are highly variable within individual winters and between winter seasons. In this study, the authors apply a Lagrangian tracking algorithm to examine variability in extratropical cyclone tracks over North America during winter. A series of methodological criteria is used to isolate cyclone development and decay regions and to account for the elevated topography over western North America. The results confirm the signatures of four climate phenomena in the intraseasonal and interannual variability in North American cyclone tracks: the North Atlantic Oscillation (NAO), the El Niño–Southern Oscillation (ENSO), the Pacific–North American pattern (PNA), and the Madden–Julian oscillation (MJO). Similar signatures are found using Eulerian bandpass-filtered eddy variances. Variability in the number of extratropical cyclones at most locations in North America is linked to fluctuations in Rossby wave trains extending from the central tropical Pacific Ocean. Only over the far northeastern United States and northeastern Canada is cyclone variability strongly linked to the NAO. The results suggest that Pacific sector variability (ENSO, PNA, and MJO) is a key contributor to intraseasonal and interannual variability in the frequency of extratropical cyclones at most locations across North America.

Dynamics of the ENSO Teleconnection and NAO Variability in the North Atlantic–European Late Winter

2020 ◽  
Vol 33 (3) ◽  
pp. 907-923 ◽  
Author(s):  
Bianca Mezzina ◽  
Javier García-Serrano ◽  
Ileana Bladé ◽  
Fred Kucharski
Keyword(s):  
North Atlantic ◽  
Southern Oscillation ◽  
Reanalysis Data ◽  
Late Winter ◽  
Sea Level Pressure ◽  
The North ◽  
Nao Index ◽  
Eddy Heat Flux ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe winter extratropical teleconnection of El Niño–Southern Oscillation (ENSO) in the North Atlantic–European (NAE) sector remains controversial, concerning both the amplitude of its impacts and the underlying dynamics. However, a well-established response is a late-winter (January–March) signal in sea level pressure (SLP) consisting of a dipolar pattern that resembles the North Atlantic Oscillation (NAO). Clarifying the relationship between this “NAO-like” ENSO signal and the actual NAO is the focus of this study. The ENSO–NAE teleconnection and NAO signature are diagnosed by means of linear regression onto the sea surface temperature (SST) Niño-3.4 index and an EOF-based NAO index, respectively, using long-term reanalysis data (NOAA-20CR, ERA-20CR). While the similarity in SLP is evident, the analysis of anomalous upper-tropospheric geopotential height, zonal wind, and transient-eddy momentum flux, as well as precipitation and meridional eddy heat flux, suggests that there is no dynamical link between the phenomena. The observational results are further confirmed by analyzing two 10-member ensembles of atmosphere-only simulations (using an intermediate-complexity and a state-of-the-art model) with prescribed SSTs over the twentieth century. The SST-forced variability in the Northern Hemisphere is dominated by the extratropical ENSO teleconnection, which provides modest but significant SLP skill in the NAE midlatitudes. The regional internally generated variability, estimated from residuals around the ensemble mean, corresponds to the NAO pattern. It is concluded that distinct dynamics are at play in the ENSO–NAE teleconnection and NAO variability, and caution is advised when interpreting the former in terms of the latter.

Rainfall Variability and Trend Analysis of Multiannual Rainfall in Romanian Plain

2017 ◽  
Vol 17 (2) ◽  
pp. 124-144 ◽  
Author(s):  
Zeineddine Nouaceur ◽  
Ovidiu Murărescu ◽  
George Murătoreanu
Keyword(s):  
North Atlantic Oscillation ◽  
Central Europe ◽  
North Atlantic ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
El Nino Southern Oscillation ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe IPCC climate models predict, for the Central Europe, are for climate changes, being seen variability of temperature, with a growing trend of 1-2,5° C (with 1° C for alpine zone – Carpathians and 2-2,5° C for plains). Current observations in the Romanian plain are not consistent, with an existence of a multiannual variability of temperature and precipitations depending on cyclonal and anti-ciclonal activity. The research is based on calculation of reduced centered index, also the graphical chronological method in information processing (MGCTI) of „Bertin Matrix” type, to show current trends of the spatio-temporal variability of precipitation in the context of global climate change. These are in line with the movement of air masses in Europe in general, and implicitly in Romania, with particular regard to the southern region of the country where the Romanian Plain. The variability of short-term global climate is generally associated with coupling phases of oceanic and atmospheric phenomena including El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). While El Niño Southern Oscillation (ENSO) affects climate variability in the world, the North Atlantic Oscillation (NAO) is the climate model dominant in the North Atlantic region. The latter cyclic oscillation whose role is still under debate could explain the variability of rainfall in much of the, central Europe area, and support the hypothesis of a return of the rains marking the end of years of drought in Romanian plain. Faced with such great changes that today affect the central Europe region and given the complexity of spatial and temporal dimensions of the climatic signal, a more thorough research of causes and retroactions would allow for a better understanding of the mechanisms behind this new trend.

scholarly journals Sub-decadal- to decadal-scale climate cyclicity during the Holsteinian interglacial (MIS 11) evidenced in annually laminated sediments

2011 ◽  
Vol 7 (3) ◽  
pp. 987-999 ◽  
Author(s):  
A. Koutsodendris ◽  
A. Brauer ◽  
H. Pälike ◽  
U. C. Müller ◽  
P. Dulski ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Laminated Sediments ◽  
Solar Cycles ◽  
The North ◽  
Decadal Scale ◽  
Time Series Analyses ◽  
Diatom Blooms ◽  
Winter Time ◽  
The North Atlantic Oscillation

Abstract. To unravel the short-term climate variability during Marine Isotope Stage (MIS) 11, which represents a close analogue to the Holocene with regard to orbital boundary conditions, we performed microfacies and time series analyses on a ~3200-yr-long record of annually laminated Holsteinian lake sediments from Dethlingen, northern Germany. These biogenic varves comprise two sub-layers: a light sub-layer, which is controlled by spring/summer diatom blooms, and a dark sub-layer consisting mainly of amorphous organic matter and fragmented diatom frustules deposited during autumn/winter. Time series analyses were performed on the thickness of the light and dark sub-layers. Signals exceeding the 95% and 99% confidence levels occur at periods that are near-identical to those known from modern instrumental data and Holocene palaeoclimatic records. Spectral peaks at periods of 90, 25, and 10.5 yr are likely associated with the 88-, 22- and 11-yr solar cycles, respectively. This variability is mainly expressed in the light sub-layer spectra, suggesting solar influence on the palaeoproductivity of the lake. Significant signals at periods between 3 and 5 yr and at ∼6 yr are strongest expressed in the dark sub-layer spectra and may reflect an influence of the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) during autumn/winter. Our results suggest that solar forcing and ENSO/NAO-like variability influenced central European climate during MIS 11 similarly to the present interglacial, thus demonstrating the comparability of the two interglacial periods at sub-decadal to decadal timescales.

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