Characterization of south central Pacific Ocean wind regimes in present and future climate for pearl farming application

Dutheil, Cyril; Andréfouët, Serge; Jullien, Swen; Gendre, Romain Le; Aucan, Jérôme; Menkès, Christophe E.

doi:10.1016/j.marpolbul.2020.111584

Cited by 19 publications

(9 citation statements)

References 45 publications

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“…These methods have been widely used to define recurrent spatial patterns over time (e.g. Cassou et al 2004;Dutheil et al 2020;Grams et al 2017), but are not yet widely used to spatially separate temporal trends.…”

Section: Introductionmentioning

confidence: 99%

Understanding past and future sea surface temperature trends in the Baltic Sea

et al. 2021

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The Baltic Sea is one of the fastest-warming semi-enclosed seas in the world over the last decades, yielding critical consequences on physical and biogeochemical conditions and on marine ecosystems. Although long-term trends in sea surface temperature (SST) have long been attributed to trends in air temperature, there are however, strong seasonal and sub-basin scale heterogeneities of similar magnitude than the average trend which are not fully explained. Here, using reconstructed atmospheric forcing fields for the period 1850–2008, oceanic climate simulations were performed and analyzed to identify areas of homogenous SST trends using spatial clustering. Our results show that the Baltic Sea can be divided into five different areas of homogeneous SST trends: the Bothnian Bay, the Bothnian Sea, the eastern and western Baltic proper, and the southwestern Baltic Sea. A classification tree and sensitivity experiments were carried out to analyze the main drivers behind the trends. While ice cover explains the seasonal north/south warming contrast, the changes in surface winds and air-sea temperature anomalies (along with changes in upwelling frequencies and heat fluxes) explain the SST trends differences between the sub-basins of the southern part of the Baltic Sea. To investigate future warming trends climate simulations were performed for the period 1976–2099 using two RCP scenarios. It was found that the seasonal north/south gradient of SST trends should be reduced in the future due to the vanishing of sea ice, while changes in the frequency of upwelling and heat fluxes explained the lower future east/west gradient of SST trend in fall. Finally, an ensemble of 48 climate change simulations has revealed that for a given RCP scenario the atmospheric forcing is the main source of uncertainty. Our results are useful to better understand the historical and future changes of SST in the Baltic Sea, but also in terms of marine ecosystem and public management, and could thus be used for planning sustainable coastal development.

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Section: Introductionmentioning

confidence: 99%

Understanding past and future sea surface temperature trends in the Baltic Sea

et al. 2021

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“…The large-scale origin, the frequency of occurrence and the seasonal variability of regional wave regimes are computed. Along with wind regimes depicted by Dutheil et al (2020), these results bring a new understanding of the environment of pearl farming atolls.…”

Section: Introductionmentioning

confidence: 77%

“…While a better characterization of the South Pacific wind conditions is presented in Dutheil et al (2020), the present study aims at better describing the wave conditions for the atolls of this region, specifically including pearl farming atolls. To describe the wave climate for the whole SCP region, as well as for atolls and for their rim sections, we used a WW3 simulation over the 2000-2017 period, with a nesting strategy to increase the horizontal resolution up to 0.05° around atolls, and then performed a statistical clustering of wave conditions at different scales (region, atoll, rim sections).…”

Section: Discussionmentioning

confidence: 99%

“…To describe the wave climate for the whole SCP region, as well as for atolls and for their rim sections, we used a WW3 simulation over the 2000-2017 period, with a nesting strategy to increase the horizontal resolution up to 0.05° around atolls, and then performed a statistical clustering of wave conditions at different scales (region, atoll, rim sections). Unlike winds which have a regional pattern not particularly affected by low-lying atoll orographic effects (Dutheil et al 2020), waves are strongly modified when crossing the archipelagos to the point that each different atoll rim section can be exposed to specific wave conditions.…”

Section: Discussionmentioning

confidence: 99%

“…These waves appear in R2 and have a seasonal distribution corresponding to the trade wind regime (see Dutheil et al 2020). They are characterized by a shorter period associated to their more local origin.…”

Section: Large Scale Wave Originsmentioning

confidence: 99%

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