Marine climate variability based on weather patterns for a complicated island setting: The New Zealand case

Rueda, Ana; Cagigal, Laura; Antolínez, José A. Á.; Albuquerque, João; Castanedo, Sonia; Coco, Giovanni; Méndez, Fernando J.

doi:10.1002/joc.5912

Cited by 21 publications

(26 citation statements)

References 53 publications

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“…Finally, even though the hindcast database covers a period from 1871 to 2010, when analysing the reconstructed series (not shown), we observed a sharp change in the storm surge behaviour in the middle of the 20th century due to inhomogeneities that are present in the atmospheric reanalysis (Krueger et al ., ; Rueda et al ., ). Most likely, the inhomogeneities are caused by the limited number of observations assimilated into 20CR (Krueger et al ., ).…”

Section: Discussionmentioning

confidence: 97%

“…For this purpose we used high-resolution SLP fields from 1979 to 2011, with a spatial resolution of 0.5 and hourly temporal resolution, from the global climate forecast system reanalysis (CFSR; Saha et al, 2010Saha et al, , 2014. These SLP fields have been shown to be adequate when defining representative synoptic patterns for GCMs classification (Perez et al, 2015) and have been successfully applied for weather types (WTs) classification in the New Zealand area (Rueda et al, 2019).…”

Section: Atmospheric Datamentioning

confidence: 99%

See 1 more Smart Citation

Historical and future storm surge around New Zealand: From the 19th century to the end of the 21st century

Cagigal

Rueda

Castanedo

et al. 2019

Intl Journal of Climatology

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We developed a new hindcast for storm surge at a 0.25° spatial scale for the whole New Zealand area using a statistical downscaling technique that links the mean local atmospheric conditions with the maximum storm surge levels at a daily scale. After validating the hindcast against sea level instrumental records from 17 tidal gauges around New Zealand, the same technique has been applied to obtain storm surge projections until 2,100 using different global climate models. The global climate models have been previously classified according to their ability to reproduce the past climatology in the studied area and seven models have been selected in order to explore their effect on storm surge projections. For the two representative Concentration Pathways studied, the projections indicate that the storm surge associated with the 50 years return period will increase in magnitude in the Southern areas while it will decrease in the Northern region. Even where a decreasing linear trend over the annual maxima is observed in the future time series, sporadic events of higher magnitude than the historical peaks can be.

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Section: Discussionmentioning

confidence: 97%

Section: Atmospheric Datamentioning

confidence: 99%

Historical and future storm surge around New Zealand: From the 19th century to the end of the 21st century

Cagigal

Rueda

Castanedo

et al. 2019

Intl Journal of Climatology

Self Cite

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“…S2). Rueda et al (2019) used a method of weather typing to develop statistical predictors for storm surge and wave height in NZ based on statistical relationship with MSL pressure fields. The Kidson (2000) weather regimes are easily associated with the extreme storm-tide and skew-surge spatial clusters identified.…”

Section: Methodsmentioning

confidence: 99%

Spatial and temporal analysis of extreme storm-tide and skew-surge events around the coastline of New Zealand

Stephens

Bell

Haigh

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Coastal flooding is a major global hazard, yet few studies have examined the spatial and temporal characteristics of extreme sea level and associated coastal flooding. Here we analyse sea-level records around the coast of New Zealand (NZ) to quantify extreme storm-tide and skew-surge frequency and magnitude. We identify the relative magnitude of sea-level components contributing to 85 extreme sea level and 135 extreme skew-surge events recorded in NZ since 1900. We then examine the spatial and temporal clustering of these extreme storm-tide and skew-surge events and identify typical storm tracks and weather types associated with the spatial clusters of extreme events. We find that most extreme storm tides were driven by moderate skew surges combined with high perigean spring tides. The spring–neap tidal cycle, coupled with a moderate surge climatology, prevents successive extreme storm-tide events from happening within 4–10 d of each other, and generally there are at least 10 d between extreme storm-tide events. This is similar to findings from the UK (Haigh et al., 2016), despite NZ having smaller tides. Extreme events more commonly impacted the east coast of the North Island of NZ during blocking weather types, and the South Island and west coast of the North Island during trough weather types. The seasonal distribution of both extreme storm-tide and skew-surge events closely follows the seasonal pattern of mean sea-level anomaly (MSLA) – MSLA was positive in 92 % of all extreme storm-tide events and in 88 % of all extreme skew-surge events. The strong influence of low-amplitude (−0.06 to 0.28 m) MSLA on the timing of extreme events shows that mean sea-level rise (SLR) of similarly small height will drive rapid increases in the frequency of presently rare extreme sea levels. These findings have important implications for flood management, emergency response and the insurance sector, because impacts and losses may be correlated in space and time.

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“…Kidson (2000) defined three weather 'regimes', characterized by: (i) frequent low-pressure troughs crossing the country, (ii) high-pressure systems to the north with strong zonal flow to the south of the NZ, and (iii) blocking patterns with high-pressure 125 systems more prominent in the south ( Figure S1). Rueda et al (2019) used a method of weather typing to develop statistical predictors for storm surge and wave height in NZ based on statistical relationship with MSL pressure fields. The Kidson (2000) weather regimes are easily associated with the extreme sea-level and skew-surge spatial clusters identified.…”

Section: Methodsmentioning

confidence: 99%

“…Numerical models, properly calibrated, provide a means of extending the extreme sea-level analyses to develop probabilistic assessments of total water level along the entire coastline. These can include combinations of tidal (e.g., Walters et al 2001), storm-surge and wave models (e.g., Gorman et al 2003;Rueda et al 2019), which can include both hindcasts and climate-change future-casts (Cagigal et al submitted). However, numerical storm-surge models for climate change typically do not include MSLA, which 340 is an important component of extreme sea level (for tidally-dominant coasts) and hence flooding exposure (e.g., Stephens et al 2014;Sweet & Park 2014), and which we have shown to be an important influence on the timing of extreme events.…”

Section: (2017)mentioning

confidence: 99%

Spatial and temporal analysis of extreme sea level and skew surge events around the coastline of New Zealand

Stephens

Bell

Haigh

2019

Preprint

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Coastal flooding is a major global hazard, yet few studies have examined the spatial and temporal characteristics of extreme sea level and associated coastal flooding. Here we analyse sea-level records around the coast of New Zealand (NZ) to quantify extreme sea level and skew-surge frequency and magnitude. We identify the relative magnitude of sea level 10 components contributing to 85 extreme sea level and 135 extreme skew-surge events recorded in NZ since 1900. We then examine the spatial and temporal clustering of these extreme sea-level and skew-surge events and identify typical storm-tracks and weather types associated with the spatial clusters of extreme events. We find that most extreme sea levels were driven by moderate skew-surges combined with high perigean-spring tides. The spring-neap tidal cycle, coupled with a moderate surge climatology, prevents successive extreme sea-level events from happening within 4-10 days of each other and generally there 15 are at least 10 days between extreme sea-level events. This is similar to findings from the UK (Haigh et al. 2016), despite NZ having smaller tides. Extreme events more commonly impacted the east coast of the North Island of NZ during Blocking weather types, and the South Island and west coast of the North Island during Trough weather types. The seasonal distribution of both extreme sea-level and skew-surge events closely follows the seasonal pattern of mean sea-level anomaly (MSLA)-MSLA was positive in 92% of all extreme sea-level and in 88% of all extreme skew-surge events. The strong influence of low-20 amplitude (−0.06 to 0.28 m) MSLA on the timing of extreme events shows that mean sea-level rise (SLR) of similarly small height will drive rapid increases in the frequency of presently rare extreme sea levels. These findings have important implications for flood management, emergency response and the insurance sector, because impacts and losses may be correlated in space and time. 25

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Marine climate variability based on weather patterns for a complicated island setting: The New Zealand case

Cited by 21 publications

References 53 publications

Historical and future storm surge around New Zealand: From the 19th century to the end of the 21st century

Historical and future storm surge around New Zealand: From the 19th century to the end of the 21st century

Spatial and temporal analysis of extreme storm-tide and skew-surge events around the coastline of New Zealand

Spatial and temporal analysis of extreme sea level and skew surge events around the coastline of New Zealand

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