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
MOTIVATION
STUDY SITE
METHODOLOGY
RESULTS
CONCLUSIONS
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
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
MAJURO ATOLL: Marshall Islands
64 ISLANDSArea: 9.7 km2
Mean elevation: 3mPopulation: 28000
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
FLOODING EVENTS
IMPORTANCE DIRECTIONAL SPECTRUM
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
MOTIVATION: Probabilistic assessment of coastal flooding
ATMOSPHERIC
CIRCULATION(SLP)
MULTIVARIATE
WAVE CLIMATE
(H, T, Dir)
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
OBJECTIVE
Time
Hs
duration
Objective Point
Time
Tp
duration
durationduration
duration
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
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
1) SUPER-POINT
STATION2913
STATION2914
STATION2915
STATION2858
STATION2857
STATION2856
2914
2915
2858
2857
2856
2913
CSIRO – SPECTRAL INFORMATION
IMPORTANCE DIRECTIONAL SPECTRUM
AIRPORT
26 June 2013
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
IMPORTANCE SUPER POINT
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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)
2) SPECTRAL PARTITIONING
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
WW3 Watershed Algorithm, Hanson and Philips 2009
2) SPECTRAL PARTITIONING: Sea + Swells
HS
TP
DIR
DSPR
GAMMA
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
2) SPECTRAL PARTITIONING: Swells
HS
TP
DIR
DSPR
GAMMA
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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
3) SNAKES
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
3) SNAKES
HS
TP
DIR
HS
TP
DIR
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
4) SNAKES PARAMETERIZATION
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
𝜏𝐷𝑢𝑟
𝐷𝑢𝑟
𝐻𝑠∗, 𝑠𝐻𝑠
𝑇𝑝∗, 𝑠𝑇𝑝
𝐷𝑖𝑟∗, 𝑠𝐷𝑖𝑟
𝜎∗, 𝑠𝜎
𝛾∗, 𝑠𝛾
𝜏
𝑃𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑠
4) SNAKES PARAMETERIZATION
MOTIVATION STUDY SITE METHODOLOGY RESULTS CONCLUSIONS
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
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
ThanksLaura Cagigal, Ana Rueda, Alba Ricondo, Giovanni Coco, Fernando Mendez