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On the use of directional wave spectra to identify distant swells approaching a Pacific atoll
Laura Cagigal a, b, Ana Rueda b, Alba Ricondo b, Giovanni Coco a, Fernando Méndez b
a. University of Auckland, b. Universidad de Cantabria
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MOTIVATION
STUDY SITE
METHODOLOGY
RESULTS
CONCLUSIONS
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
MOTIVATION: Inundation in the Pacific Islands
Atoll Islands are low-lying, with much of the land area < 3 m above
mean sea level
Source: Hoeke et al 2013
Atoll Islands are vulnerable to a range of inundation hazards generated by atmospheric and oceanographic
processes, including typhoons and tropical storms and far-field generated
swell
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
MAJURO ATOLL: Marshall Islands
64 ISLANDSArea: 9.7 km2
Mean elevation: 3mPopulation: 28000
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
FLOODING EVENTS
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IMPORTANCE DIRECTIONAL SPECTRUM
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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MOTIVATION: Probabilistic assessment of coastal flooding
ATMOSPHERIC
CIRCULATION(SLP)
MULTIVARIATE
WAVE CLIMATE
(H, T, Dir)
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
OBJECTIVE
Time
Hs
duration
Objective Point
Time
Tp
duration
durationduration
duration
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STEPS
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
1. CREATE A SUPER SPECTRA WITH ALL THE ENERGY APPROACHING THE ATOLL
2. OBTAIN THE SPECTRAL PARTITINONS
3. DEVELOP AN ALGORITHM TO AGREGATE SWELLS
4. PARAMETERIZE SWELLS
5. LINK SWELLS WITH WEATHER CONDITIONS
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
1) SUPER-POINT
STATION2913
STATION2914
STATION2915
STATION2858
STATION2857
STATION2856
2914
2915
2858
2857
2856
2913
CSIRO – SPECTRAL INFORMATION
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IMPORTANCE DIRECTIONAL SPECTRUM
AIRPORT
26 June 2013
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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IMPORTANCE SUPER POINT
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
2) SPECTRAL PARTITIONING
WAVESPECTRA
https://github.com/metocean/wavespectra/
OPEN SOURCE LIBRARY FOR PROCESSING OCEAN WAVE SPECTRA ON PYTHON FROM METOCEAN SOLUTIONS (NZ)
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2) SPECTRAL PARTITIONING
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
WW3 Watershed Algorithm, Hanson and Philips 2009
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2) SPECTRAL PARTITIONING: Sea + Swells
HS
TP
DIR
DSPR
GAMMA
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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2) SPECTRAL PARTITIONING: Swells
HS
TP
DIR
DSPR
GAMMA
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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3) SWELL IDENTIFICATION
D = 𝑎 ∗ 𝐻𝑡 − 𝐻𝑡−12 + 𝑏 ∗ 𝑇𝑝𝑡 − 𝑇𝑝𝑡−1
2 + 𝑐 ∗ 𝐷𝑖𝑟𝑡 − 𝐷𝑖𝑟𝑡−12 + 𝑑 ∗ 𝛿𝑡 − 𝛿𝑠𝑝𝑟𝑡−1
2 + 𝑒 ∗ 𝛾𝑡 − 𝛾𝑡−12
𝑫𝑰𝑺𝑻𝑨𝑵𝑪𝑬 = 𝒇(∆𝑯𝒔, ∆𝑻𝒑, ∆𝑫𝒊𝒓, ∆𝑫𝒔𝒑𝒓, ∆𝑮𝒂𝒎𝒎𝒂)
𝑺𝒏𝒂𝒌𝒆𝒔 𝒔𝒆𝒂𝒓𝒄𝒉 𝒂𝒍𝒈𝒐𝒓𝒊𝒕𝒉𝒎
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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3) SNAKES
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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3) SNAKES
HS
TP
DIR
HS
TP
DIR
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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4) SNAKES PARAMETERIZATION
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
𝜏𝐷𝑢𝑟
𝐷𝑢𝑟
𝐻𝑠∗, 𝑠𝐻𝑠
𝑇𝑝∗, 𝑠𝑇𝑝
𝐷𝑖𝑟∗, 𝑠𝐷𝑖𝑟
𝜎∗, 𝑠𝜎
𝛾∗, 𝑠𝛾
𝜏
𝑃𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑠
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4) SNAKES PARAMETERIZATION
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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5) LINK TO WEATHER CONDITIONS
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
FINDING THE LINK BETWEEN PRESSURE CONDITIONS AND THE SWELL PARAMETERS FOR EACH WAVE FAMILY
Algorithm from Portilla 2012
Storm-Source-Locating Algorithm Based on the Dispersive Nature of Ocean Swells
PCs 12 Swell Parameters
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CONCLUSIONS
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
• IMPORTANCE OF AGGREGATING SPECTRAL INFORMATION AROUND THE STUDY ATOLL TO INCLUDE ALL SOURCES OF WAVE ENERGY
• NECESSITY TO CORRECTLY SIMULATE THE TIME EVOLUTION OF EVERY SWELL
• NEED OF EMULATE THE SWELL CHARACTERISTICS BASED ON THE ATMOSPHERIC SYSTEM THAT GENERATES THEM
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ThanksLaura Cagigal, Ana Rueda, Alba Ricondo, Giovanni Coco, Fernando Mendez