Copernicus Ocean State Report, issue 6

The 6th issue of the Copernicus OSR incorporates a large range of topics for the blue, white and green ocean for all European regional seas, and the global ocean over 1993–2020 with a special focus on 2020

Statistical downscaling of island sea levels in the southwest Pacific : a multiple linear regression approach

L'élévation du niveau de la mer est une préoccupation croissante dans les îles du Pacifique. Au cours de l'ère altimétrique (depuis 1993), les taux d'élévation du niveau de la mer sur le Pacific tropical ouest ont été parmi les plus élevés du monde, atteignant jusqu'à 3-4 fois la moyenne globale. Alors que de plus en plus de communautés soumises aux risques associés à cette hausse du niveau de la mer se déplacent vers des terres plus élevées pour échapper à la montée des eaux, il est impératif de disposer de prédictions du niveau de la mer à l'échelle locale pour faciliter le processus d'adaptation et de planification. Ce processus n'est pas simple car le niveau de la mer varie d'une région à l'autre, notamment en fonction des redistributions de chaleur, sel et masses opérées aux échelles régionales par la circulation océanique, et des modes climatiques dominants (par exemple, ENSO, PDO/IPO). Même à l'échelle locale, d'importants changements du niveau de la mer relatif peuvent résulter de mouvements verticaux naturels ou anthropiques du sol terrestre. Motivée par ces préoccupations, cette thèse se concentre sur l'utilisation d'une technique de descente d'échelle statistique basée sur des régressions linéaires multiples (MLR) pour modéliser les variations interannuelles-à-interdécennales du niveau de la mer pour trois sites côtiers localisés sur des îles du Pacifique Sud-Ouest - Suva et Lautoka à Fidji, et Nouméa en Nouvelle-Calédonie. Le modèle MLR est basé sur la connaissance que les variations du niveau de la mer à ces échelles de temps dans le Pacifique tropical sont principalement de nature thermostérique (c.-à-d. provenant des changements de densité de l'eau de mer induits par des changements de température de l'océan) et que ces variations thermostériques sont principalement générées par les variations de forçage de vent et les ondes de Rossby se propageant vers l'ouest qui en résultent. Les expériences de MLR sont menées sur la période d'étude 1988-2014, l'accent étant mis sur la variabilité interannuelle à décennale et les tendances du niveau de la mer. Le niveau de la mer pour les trois sites côtiers insulaires est d'abord exprimé sous forme de somme des variations stériques et de masse. Dans un second temps, les modèles MLR développés se basent sur une approche plus orientée processus, en utilisant le rotationnel de tension de vent comme approximation de la composante thermostérique.[...]Sea level rise is a growing concern in the islands of the western Pacific. Over the altimetry era (1993-present), sea level rise rates in the western tropical Pacific were amongst the highest recorded across the world ocean, reaching up to 3-4 times the global mean. As more and more affected communities relocate to higher grounds to escape the rising seas, there is a compelling need for information on local scales to ease the adaptation and planning process. This is not a straightforward process as sea level varies regionally, driven by wind and ocean circulation patterns, and the prevailing climate modes (e.g. ENSO, PDO/IPO). On local scales, substantial sea level changes can result from natural or anthropogenic induced vertical ground motion. Motivated by such concerns, this thesis focuses on developing a statistical downscaling technique, namely a multiple linear regression (MLR) model, to simulate island sea levels at selected sites in the southwest Pacific - Suva and Lautoka in Fiji, and Nouméa in New Caledonia. The model is based on the knowledge that sea level variations in the tropical Pacific are mainly thermosteric in nature (temperature-related changes in ocean water density) and that these thermosteric variations are dominated by wind-forced, westward propagating Rossby waves. The MLR experiments are conducted over the 1988-2014 study period, with a focus on interannual-to-decadal sea level variability and trend. Island sea levels are first expressed a sum of steric and mass changes. Then, a more dynamical approach using wind stress curl as a proxy for the thermosteric component is undertaken to construct the MLR model. In the latter case, island sea levels are perceived as a composite of global, regional and local components, where the second is dominant. The MLR model takes wind stress curl as the dominant regional regressor (via a Rossby wave model), and the local halosteric component (salinity-related changes in ocean water density), local wind stress, and local sea surface temperature as minor regressors. A stepwise regression function is used to isolate statistically significant regressors before calibrating the MLR model. The modeled sea level shows high agreement with observations, capturing 80% of the variance on average. Stationarity tests on the MLR model indicate that it can be applied skillfully to projections of future sea level. The statistical downscaling approach overall provides insights on key drivers of sea level variability at the selected sites, showing that while local dynamics and the global signal modulate sea level to a given extent, most of the variance is driven by regional factors. [...

Descente d'échelle statistique du niveau de la mer pour les îles du Pacifique Sud-Ouest : une approche de régression linéaire multiple

Sea level rise is a growing concern in the islands of the western Pacific. Over the altimetry era (1993-present), sea level rise rates in the western tropical Pacific were amongst the highest recorded across the world ocean, reaching up to 3-4 times the global mean. As more and more affected communities relocate to higher grounds to escape the rising seas, there is a compelling need for information on local scales to ease the adaptation and planning process. This is not a straightforward process as sea level varies regionally, driven by wind and ocean circulation patterns, and the prevailing climate modes (e.g. ENSO, PDO/IPO). On local scales, substantial sea level changes can result from natural or anthropogenic induced vertical ground motion. Motivated by such concerns, this thesis focuses on developing a statistical downscaling technique, namely a multiple linear regression (MLR) model, to simulate island sea levels at selected sites in the southwest Pacific - Suva and Lautoka in Fiji, and Nouméa in New Caledonia. The model is based on the knowledge that sea level variations in the tropical Pacific are mainly thermosteric in nature (temperature-related changes in ocean water density) and that these thermosteric variations are dominated by wind-forced, westward propagating Rossby waves. The MLR experiments are conducted over the 1988-2014 study period, with a focus on interannual-to-decadal sea level variability and trend. Island sea levels are first expressed a sum of steric and mass changes. Then, a more dynamical approach using wind stress curl as a proxy for the thermosteric component is undertaken to construct the MLR model. In the latter case, island sea levels are perceived as a composite of global, regional and local components, where the second is dominant. The MLR model takes wind stress curl as the dominant regional regressor (via a Rossby wave model), and the local halosteric component (salinity-related changes in ocean water density), local wind stress, and local sea surface temperature as minor regressors. A stepwise regression function is used to isolate statistically significant regressors before calibrating the MLR model. The modeled sea level shows high agreement with observations, capturing 80% of the variance on average. Stationarity tests on the MLR model indicate that it can be applied skillfully to projections of future sea level. The statistical downscaling approach overall provides insights on key drivers of sea level variability at the selected sites, showing that while local dynamics and the global signal modulate sea level to a given extent, most of the variance is driven by regional factors. [...]L'élévation du niveau de la mer est une préoccupation croissante dans les îles du Pacifique. Au cours de l'ère altimétrique (depuis 1993), les taux d'élévation du niveau de la mer sur le Pacific tropical ouest ont été parmi les plus élevés du monde, atteignant jusqu'à 3-4 fois la moyenne globale. Alors que de plus en plus de communautés soumises aux risques associés à cette hausse du niveau de la mer se déplacent vers des terres plus élevées pour échapper à la montée des eaux, il est impératif de disposer de prédictions du niveau de la mer à l'échelle locale pour faciliter le processus d'adaptation et de planification. Ce processus n'est pas simple car le niveau de la mer varie d'une région à l'autre, notamment en fonction des redistributions de chaleur, sel et masses opérées aux échelles régionales par la circulation océanique, et des modes climatiques dominants (par exemple, ENSO, PDO/IPO). Même à l'échelle locale, d'importants changements du niveau de la mer relatif peuvent résulter de mouvements verticaux naturels ou anthropiques du sol terrestre. Motivée par ces préoccupations, cette thèse se concentre sur l'utilisation d'une technique de descente d'échelle statistique basée sur des régressions linéaires multiples (MLR) pour modéliser les variations interannuelles-à-interdécennales du niveau de la mer pour trois sites côtiers localisés sur des îles du Pacifique Sud-Ouest - Suva et Lautoka à Fidji, et Nouméa en Nouvelle-Calédonie. Le modèle MLR est basé sur la connaissance que les variations du niveau de la mer à ces échelles de temps dans le Pacifique tropical sont principalement de nature thermostérique (c.-à-d. provenant des changements de densité de l'eau de mer induits par des changements de température de l'océan) et que ces variations thermostériques sont principalement générées par les variations de forçage de vent et les ondes de Rossby se propageant vers l'ouest qui en résultent. Les expériences de MLR sont menées sur la période d'étude 1988-2014, l'accent étant mis sur la variabilité interannuelle à décennale et les tendances du niveau de la mer. Le niveau de la mer pour les trois sites côtiers insulaires est d'abord exprimé sous forme de somme des variations stériques et de masse. Dans un second temps, les modèles MLR développés se basent sur une approche plus orientée processus, en utilisant le rotationnel de tension de vent comme approximation de la composante thermostérique.[...

Copernicus Marine Sea Surface Temperature and chlorophyll-a indicators for two Pacific Islands: a co-construction monitoring framework for an integrated, transdisciplinary, multi-scale approach

International audienceOcean case studies with socio-economic relevance. Statement of main outcome: The ocean is an integral part for the three pillars of sustainable development: environment, society and economy. Pressures on the ocean from climate change, pollution, and over exploitation have increased over the past decades, posing unprecedented challenges, particularly for vulnerable communities such as the Large Ocean Island States, and these pressures need to be monitored. This study analyses the time series of Essential Ocean Variables sea surface temperature and chlorophyll-a in coastal reefs of two pilot regions in Fiji and New Caledonia. In situ measurements represent true local conditions, with a necessarily limited coverage in time and space. Remote sensing data have a broad coverage but are necessarily limited in terms of resolution and accuracy in the coastal zone. Our analysis points to the advantage in using these complementary data types for the same geographical areas at small spatial scales close to the coast, and in particular, for high frequencies and extreme events. We discuss the way forward for a co-coconstructed monitoring framework, drawing on ongoing initiatives in Oceania, and advocate a methodology for the use of ocean data to support society and economy. Co-construction with stakeholder involvement is paramount for this framework, including policy- and decision-makers, industry, scientists, local and indigenous, governmental and non-governmental organisations, all of whom need sound, multi-disciplinary science advice, targeted expertise, and reliable evidence-based information to make informed timely decisions for the right timescale. Such transdisciplinarity combines scientific, traditional, administrative, technical, and legal knowledge repertories

Copernicus Marine Sea Surface Temperature and chlorophyll-a indicators for two Pacific Islands: a co-construction monitoring framework for an integrated, transdisciplinary, multi-scale approach

International audienceOcean case studies with socio-economic relevance. Statement of main outcome: The ocean is an integral part for the three pillars of sustainable development: environment, society and economy. Pressures on the ocean from climate change, pollution, and over exploitation have increased over the past decades, posing unprecedented challenges, particularly for vulnerable communities such as the Large Ocean Island States, and these pressures need to be monitored. This study analyses the time series of Essential Ocean Variables sea surface temperature and chlorophyll-a in coastal reefs of two pilot regions in Fiji and New Caledonia. In situ measurements represent true local conditions, with a necessarily limited coverage in time and space. Remote sensing data have a broad coverage but are necessarily limited in terms of resolution and accuracy in the coastal zone. Our analysis points to the advantage in using these complementary data types for the same geographical areas at small spatial scales close to the coast, and in particular, for high frequencies and extreme events. We discuss the way forward for a co-coconstructed monitoring framework, drawing on ongoing initiatives in Oceania, and advocate a methodology for the use of ocean data to support society and economy. Co-construction with stakeholder involvement is paramount for this framework, including policy- and decision-makers, industry, scientists, local and indigenous, governmental and non-governmental organisations, all of whom need sound, multi-disciplinary science advice, targeted expertise, and reliable evidence-based information to make informed timely decisions for the right timescale. Such transdisciplinarity combines scientific, traditional, administrative, technical, and legal knowledge repertories

CMEMS SST and Chl-a indicators for two Pacific Islands: a co-construction monitoring framework for an integrated, transdisciplinary, multi-scale approach

The ocean is an integral part for the three pillars of sustainable development which are environment, society and economy. Pressures on the ocean from climate change, pollution, and over exploitation have increased over the past decades, posing unprecedented challenges, particularly for vulnerable communities such as the Large Ocean Island States, and these pressures need to be monitored. This study analyses time series of Essential Ocean Variables surface seawater water temperature and chlorophyll-a in coastal reefs of two pilot regions in Fiji and New Caledonia. In situ measurements represent true local conditions, with a necessarily limited coverage in time and space. Remote sensing data have a broad coverage but are necessarily limited in terms of resolution and accuracy in the coastal zone. Our analysis points to the advantage in using these complementary data types for the same geographical areas at small spatial scales close to the coast, and in particular, for high frequencies and extreme events. We discuss the way forward for a co-constructed monitoring framework , drawing on a recently funded transdisciplinary project for Oceania (PACPATH) and advocate a methodology for the use of ocean data to support society and economy that goes well beyond the challenge of combining large-scale to local-scale ocean data . Stakeholder involvement is paramount for this framework, including local communities, policy- and decision-makers, industry, scientists, indigenous organisations, and governmental and non-governmental organisations, all of whom need sound, multi-disciplinary science advice, targeted expertise, and reliable evidence-based information to make informed timely decisions for the right timescale. We propose an approach based on transdisciplinary co construction, that includes scientific, traditional, administrative, technical, and legal knowledge repertories