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