Future wind and wave climate projections in the Indian Ocean based on a super-high-resolution MRI-AGCM3.2S model projection

Kamranzad, Bahareh; Mori, Nobuhito

doi:10.1007/s00382-019-04861-7

Cited by 33 publications

(16 citation statements)

References 53 publications

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“…Wind drag estimations have limitations especially for higher wind speeds, where they are known to under-estimate and even limit wave growth, therefore, for every different configuration, the C D should be adjusted. Kamranzad et al [33] indicated that even though wind drag parametrisations in models are good at generating waves, they are limited in their performance especially at higher wind values, where wave growth reduces, see Figure 2. To alleviate this limitation, a modified formulation was used and since 41.20, a similar approach to that of Rogers et al [34] can be activated.…”

Section: Calibration Parametrisationmentioning

confidence: 99%

North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments

Lavidas

Polinder

2019

Atmosphere

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The study presents a newly generated hindcast database of metocean conditions for the region of the North Sea by parametrising the newly introduced ST6 physics in a nearshore wave model. Exploring and assessing the intricacies in wave generation are vital to produce a reliable hindcast. The new parametrisations perform better, though they have a higher number of tuneable options. Parametrisation of the white capping coefficient within the ST6 package improved performance with significant differences ≈±20-30 cm. The configuration which was selected to build the database shows a good correlation ≈95% for H m0 , has an overall minimal bias with the majority of locations being slightly over-estimated ±0.5-1 cm. The calibrated model was subsequently used to produce a database for 38 years, analysing and discussing the metocean condition. In terms of wave energy resource, the North Sea has not received attention due to its perceived "lower" resource. However, from analysing the long-term climatic data, it is evident that the level of metocean conditions, and subsequently wave power, can prove beneficial for development. The 95 th percentile indicates that the majority of the time H m0 should be expected at 3.4-5 m, and the wave energy period T e at 5-7 s. Wave power resource exceeds 15 kW/m at locations very close to the coast, and it is uniformly reduced as we move to the Southern parts, near the English Channel, with values there being ≈5 kW/m, with most energetic seas originating from the North East. Results by the analysis show that in the North Sea, conditions are moderate to high, and the wave energy resource, which has been previously overlooked, is high and easily accessible due to the low distance from coasts. The study developed a regional high-fidelity model, analysed metocean parameters and properly assessed the energy content. Although, the database and its results can have multiple usages and benefit other sectors that want to operate in the harsh waters of the North Sea.wave height (H m0 ) and period(s) display differences since their 1948 levels, and will tend to alter in the years to come. However, this is not universally distributed along the globe; further exploration regional analysis must be undertaken to determine the metocean characteristics accurately. Long-term high fidelity spatio-temporal data are very important for analysis on wave conditions [5], wave power resource [6], extreme value analysis [1,7], and climate characteristics [3,8], etc.To obtain necessary information, for climate analysis on any type of renewable resource, a minimum duration of 10 years is required [9][10][11][12][13]. Furthermore, to have a good understanding of climate conditions and their persistence, additional considerations on Climatological Standard Normals (CSN) are required. CSN suggest a minimum period that allows long-term extrapolation and proper estimation of averages for climatological parameters, computed for consecutive periods of ≥30 years [14]. Without long-term data, any estimation on coastal infrastru...

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Section: Calibration Parametrisationmentioning

confidence: 99%

North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments

Lavidas

Polinder

2019

Atmosphere

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“…However, as well as short-term variations, long-term changes should also be taken into account. For this purpose, Kamranzad and Mori [1] proposed a Climate Stability Index (CSI) that comprises Monthly Variability Index (MVI) in both historical and future projections and the relative change of the intended parameter in the future. Lower change in both short and long-term conveys higher stability of the parameter.…”

Section: Wave Energy Calculationmentioning

confidence: 99%

“…The model has been calibrated against the gridded Satellite multi-mission wave products from Aviso (http://www.aviso.oceanobs.com/) and the results have shown that the model is reliable to produce the wave characteristics in the Western Indian Ocean. A detailed discussion on the wave modeling and the validation procedure, qualitatively and quantitatively, can be found in [1].…”

Section: Wave Energy Calculationmentioning

confidence: 99%

“…Considering the global tendency to the usage of renewable energies and especially the ocean resources in the areas adjacent to water bodies, the Indian Ocean can be considered as a potential source of energy for the population living in surrounding areas. The previous studies have shown that parts of the Indian Ocean wave climate are swell dominated (e.g., [1]), which considering the advantages of utilizing the wave energy, such as predictability, higher density and lower visual and environmental impacts [2], provides a more stable supply of energy. However, due mainly to the lack of vast information about the climate regime, the Indian Ocean has been less studied for that purpose.…”

Section: Introductionmentioning

confidence: 99%

“…Lavidas and Venugopal [15] used 18-years of the simulated wave using SWAN to estimate the wave energy potential and its variability in South Africa and represented promising conditions for offshore wave applications regarding the low easily accessible depths and short coast distances. Kamranzad and Mori [1] assessed the impact of climate change on the sustainability of wave energy in southeast Africa and indicated higher values and stability in Reunion, Mauritius, and southern Madagascar.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Assessment of Climate Change Impact on Wave Energy Resources Using Various Time Dependent Criteria

2020

Self Cite

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The wave energy resources in the Indian Ocean can be considered as a potential alternative to fossil fuels. However, the wave energy resources are subject to short-term fluctuations and long-term changes due to climate change. Hence, considering sustainable development goals, it is necessary to assess both short-term (intra-annual) variation and long-term change. For this purpose, the simulated wave characteristics were utilized, and the wave power and its variation and change were analyzed in the whole domain and nearshore areas. The short-term fluctuation was investigated in terms of monthly and seasonal variations and the future change was discussed based on absolute and relative changes. Both analyses show that the Southern Indian Ocean, despite experiencing extreme events and having higher wave energy potential, is more stable in terms of both short and long-term variation and change. The assessment of the total and exploitable storages of wave energy and their future change revealed the higher potential and higher stability of the nearshores of the Southern Indian Ocean. It can be concluded that based on various factors, the south of Sri Lanka, Horn of Africa, southeast Africa, south of Madagascar and Reunion and Mauritius islands are the most suitable areas for wave energy extraction.

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Skill assessment of global climate model wind speed from CMIP5 and CMIP6 and evaluation of projections for the Bay of Bengal

Krishnan

Bhaskaran

2020

Clim Dyn

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Future wind and wave climate projections in the Indian Ocean based on a super-high-resolution MRI-AGCM3.2S model projection

Cited by 33 publications

References 53 publications

North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments

North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments

Spatio-Temporal Assessment of Climate Change Impact on Wave Energy Resources Using Various Time Dependent Criteria

Skill assessment of global climate model wind speed from CMIP5 and CMIP6 and evaluation of projections for the Bay of Bengal

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