2010
DOI: 10.1175/2010jcli3362.1
|View full text |Cite
|
Sign up to set email alerts
|

Interannual Variability of Northwest Australian Tropical Cyclones

Abstract: Tropical cyclone (TC) activity over the southeast Indian Ocean has been studied far less than other TC basins, such as the North Atlantic and northwest Pacific. The authors examine the interannual TC variability of the northwest Australian (NWAUS) subbasin (08-358S, 1058-1358E), using an Australian TC dataset for the 39-yr period of . Thirteen TC metrics are assessed, with emphasis on annual TC frequencies and total TC days.Major findings are that for the NWAUS subbasin, there are annual means of 5.6 TCs and 4… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
18
0

Year Published

2010
2010
2024
2024

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 36 publications
(20 citation statements)
references
References 51 publications
2
18
0
Order By: Relevance
“…These predictors might reflect the atmospheric conditions associated with ENSO as well as other climatic oscillations and therefore are the good predictors for the TC activity in the Australian region. Other than ENSO‐related predictors, Goebbert et al (2010) found a set of NCEP‐NCAR reanalysis fields for the seasonal prediction of the northwest Australian (0°–35°S, 105°–135°E) TC frequency and obtained a fairly high skill over climatology. The predictors used in this study included the May–Jul 850‐hPa geopotential heights over the south Indian Ocean, the Apr–Jun 700‐hPa geopotential heights over Central North American, the May‐Jul 850‐hPa air temperatures over the central North Pacific and the Jun–Aug 925‐hPa geopotential heights over the southern Atlantic Ocean and the eastern Pacific Ocean.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…These predictors might reflect the atmospheric conditions associated with ENSO as well as other climatic oscillations and therefore are the good predictors for the TC activity in the Australian region. Other than ENSO‐related predictors, Goebbert et al (2010) found a set of NCEP‐NCAR reanalysis fields for the seasonal prediction of the northwest Australian (0°–35°S, 105°–135°E) TC frequency and obtained a fairly high skill over climatology. The predictors used in this study included the May–Jul 850‐hPa geopotential heights over the south Indian Ocean, the Apr–Jun 700‐hPa geopotential heights over Central North American, the May‐Jul 850‐hPa air temperatures over the central North Pacific and the Jun–Aug 925‐hPa geopotential heights over the southern Atlantic Ocean and the eastern Pacific Ocean.…”
Section: Discussionmentioning
confidence: 99%
“…Flay and Nott (2007) also developed a statistical model for the prediction of TC landfalls in Queensland using the SOI. More recently, Goebbert et al (2010) proposed a prediction scheme for the northwest Australian TC frequency based on a set of NCEP‐NCAR reanalysis fields (geopotential height, air temperature, and components of wind) which are highly correlated with TC frequency.…”
Section: Introductionmentioning
confidence: 99%
“…For the northwest Australian region (0°-35°S, 105°-135°E), the annual mean tropical cyclone occurrence is 5.6 (standard deviation of 2.3; Goebbert and Leslie 2010). The mean number of tropical cyclone landfalls in the same region is 1.5 (out of 4.9 for all Australian coastlines; Dare and Davidson 2004).…”
Section: Data and Model Configurationmentioning
confidence: 99%
“…However, strong interannual variability in TC activity occurs around this trend, and Nicholls et al (1996) showed evidence of a strong statistical link between these interannual fluctuations of TC numbers in the Australian region and the Southern Oscillation, as well as the sea surface temperature (SST) in the northern Australian region. Goebbert and Leslie (2010) investigated the influence of ENSO on TC activity in the eastern region of the south Indian Ocean with a view toward developing seasonal prediction schemes.…”
Section: Introductionmentioning
confidence: 99%