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.

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 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.

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 The Tropospheric Pathway of the ENSO–North Atlantic Teleconnection

2018 ◽  
Vol 31 (11) ◽  
pp. 4563-4584 ◽  
Author(s):  
Bernat Jiménez-Esteve ◽  
Daniela I. V. Domeisen
Keyword(s):  
North Atlantic ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
Stationary Waves ◽  
The North ◽  
La Nina ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract El Niño–Southern Oscillation (ENSO) exerts an influence on the North Atlantic–European (NAE) region. However, this teleconnection is nonlinear and nonstationary owing to the superposition and interaction of a multitude of influences on this region. The stratosphere is one of the major players in terms of the influence of the ENSO signal on this sector. Nevertheless, there are tropospheric dynamical links between the North Pacific and the North Atlantic that are clearly influenced by ENSO. This tropospheric pathway of ENSO to the NAE has received less attention. In view of this, the present study revisits the tropospheric pathway of ENSO to the North Atlantic using ECMWF reanalysis products. Anomalous propagation of transient and quasi-stationary waves across North America is analyzed with respect to their sensitivity to ENSO. Transient (quasi-stationary zonal waves 1–3) wave activity flux (WAF) from the Pacific to the Atlantic increases during El Niño (La Niña) conditions leading to a negative (positive) phase of the North Atlantic Oscillation (NAO). This response is observed from January to March for El Niño and only visible during February for La Niña events. However, the stratosphere strongly modulates this response. For El Niño (La Niña) conditions a weaker (stronger) stratospheric vortex tends to reinforce the negative (positive) NAO with the stratosphere and troposphere working in tandem, contributing to a stronger and more persistent tropospheric circulation response. These findings may have consequences for the prediction of the NAO during times with an inactive stratosphere.

scholarly journals The influence of the North Atlantic Oscillation and El Niño–Southern Oscillation on mean and extreme values of column ozone over the United States

2014 ◽  
Vol 14 (14) ◽  
pp. 21065-21099
Author(s):  
I. Petropavlovskikh ◽  
R. Evans ◽  
G. McConville ◽  
G. L. Manney ◽  
H. E. Rieder
Keyword(s):  
United States ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Total Ozone ◽  
Southern Oscillation ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
Column Ozone

Abstract. Continuous measurements of total ozone (by Dobson spectrophotometers) across the contiguous United States (US) began in the early 1960s. Here, we analyze temporal and spatial variability and trends in total ozone from the five US sites with long-term records. While similar long-term ozone changes are detected at all five sites, we find differences in the patterns of ozone variability on shorter time scales. In addition to standard evaluation techniques, STL-decomposition methods (Seasonal Trend decomposition of time series based on LOcally wEighted Scatterplot Smoothing, LOESS) are used to address temporal variability and trends in the Dobson data. The LOESS-smoothed trend components show a decline of total ozone between the 1970s and 2000s and a "stabilization" at lower levels in recent years, which is also confirmed by linear trend analysis. Methods from statistical extreme value theory (EVT) are used to characterize days with high and low total ozone (termed EHOs and ELOs, respectively) at each station and to analyze temporal changes in the frequency of ozone extremes and their relationship to dynamical features such as the North Atlantic Oscillation and El Niño Southern Oscillation. A comparison of the "fingerprints" detected in the frequency distribution of the extremes with those for standard metrics (i.e., the mean) shows that more "fingerprints" are found for the extremes, particularly for the positive phase of the NAO, at all five US monitoring sites. Results from the STL-decomposition support the findings of the EVT analysis. Finally, we analyze the relative influence of low and high ozone events on seasonal mean column ozone at each station. The results show that the influence of ELOs and EHOs on seasonal mean column ozone can be as much as ±5%, or about twice as large as the overall long-term decadal ozone trends.

scholarly journals Letter to the editor: Are the North Atlantic Oscillation and the Southern Oscillation related in any time-scale?

2000 ◽  
Vol 18 (2) ◽  
pp. 247-251 ◽  
Author(s):  
R. García ◽  
P. Ribera ◽  
L. Gimenoo ◽  
E. Hernández
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Singular Spectrum Analysis ◽  
Atmospheric Dynamics ◽  
Meteorology And Atmospheric Dynamics ◽  
The North ◽  
Ocean Atmosphere ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract. The North Atlantic Oscillation (NAO) and the Southern Oscillation (SO) are compared from the standpoint of a possible common temporal scale of oscillation. To do this a cross-spectrum of the temporal series of NAO and SO indices was determined, finding a significant common oscillation of 6-8 years. To assure this finding, both series were decomposed in their main oscillations using singular spectrum analysis (SSA). Resulting reconstructed series of 6-8 years oscillation were then cross-correlated without and with pre-whitened, the latter being significant. The main conclusion is a possible relationship between a common oscillation of 6-8 years' that represents about 20% of the SO variance and about 25% of the NAO variance.Key words: Meteorology and atmospheric dynamics (climatology; ocean-atmosphere interactions)

Sign in / Sign up

Export Citation Format

Share Document