Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium

Abstract Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine-terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions

Climate variability and applications in the islands of the tropical Pacific

International audienc

Climate change in French Polynesia, observed changes detections and projection assessment

Les effets du changement climatique sur les îles du Pacifique constituent un enjeu majeur pour les populations insulaires. En particulier, les précipitations constituent un des paramètres sensibles car elles conditionnent la ressource en eau. Le but de cette thèse est mettre d'apporter les premiers éléments de réponse relatifs à l'évolution des précipitations au cours du 21ème siècle sur Tahiti. Dans un premier temps, les précipitations à Tahiti ont été caractérisées à partir des mesures issues du réseau d'observation de Météo France. La saison des pluies, de novembre à avril, constitue la saison d'intérêt, car c'est à cette période de l'année que les cumuls de pluie sont les plus élevés. En effet, la zone de convergence du Pacifique sud (SPCZ), siège de la convection profonde, est la principale source de précipitations à Tahiti en été austral (Décembre-Janvier-Février). A l'échelle interannuelle et interdécennale, les phénomènes El Niño Southern Oscillation (ENSO) et Interdecadal Pacific Oscillation (IPO) induisent des migrations nord/sud et est/ouest de cette zone de convergence qui l'éloignent ou l'approchent de Tahiti. L'IPO, implique un déplacement de la SPCZ vers le nord-est en phase positive, ce qui induit des cumuls plus élevés observés à Tahiti. Elle est déplacée vers le sud-ouest en phase négative de l'IPO, d'où une diminution des pluies à Tahiti. L'étude montre qu'en IPO positif, l'occurrence d'événements El Niño intenses est favorisée. Pour ces cas de figure, la SPCZ migre brutalement vers le nord-est et adopte une orientation zonale au-dessous de l'équateur. Cette configuration l'éloigne de Tahiti et perturbe le flux d'alizés de sud-est, il en résulte alors des pluies orographiques très abondantes sur les côtes sud-est de l'île. Suite à cet état des lieux des précipitations observées, une méthodologie originale, en l'absence de toute autre expérience internationale sur la région, a été mise en œuvre pour obtenir un modèle capable de distinguer l'île et capturer au mieux les effets orographiques. Deux descentes d'échelle successives ont été nécessaires pour passer du modèle couplé global CNRM-CM, à 150 km de résolution, au modèle à aire limitée ALADIN-Climat, de résolution 12 km, centré sur Tahiti. Les sorties du modèle régional obtenues ont été confrontées aux observations sur la partie historique. Un lien a été établi entre les précipitations observées et modélisées sur la période passée. Ce lien est construit entre stations d'observations et points de grille du modèle exhibant un comportement similaire relatif aux phases de l'ENSO. Il a été supposé encore pertinent au 21ième siècle pour déduire les précipitations futures les plus réalistes à Tahiti, à partir des précipitations simulées par le modèle à 12 km, suivant deux scénarios du GIEC (RCP4.5 et RCP8.5). La structure spatiale du réchauffement climatique de type El niño conforte la pertinence du lien établi. Les résultats obtenus concernent les côtes sud de Tahiti. Les précipitations vont augmenter progressivement tout au long du 21ème siècle, en réponse au réchauffement global. A Papara, il est tombé en moyenne sur la période 1961-2011 pendant l'été austral 695 mm de pluie. Il tombera en moyenne sur la période 2070-2100, 825 mm selon le scénario RCP4.5, 814 mm selon le scénario RCP8.5, soit une augmentation d'un peu moins de 20 %. Ajoutés à cet accroissement à long terme, les événements El Niño induiront un excédent de précipitations. Mais cet effet sera réduit en fin de période dans le RCP8.5. A l'inverse, les événements La Niña s'accompagneront toujours d'un déficit de précipitations mais sans arriver à contrecarrer l’accroissement à long terme.The effects of climate change on Pacific islands is a major concern for the local populations. The rainfall parameter, specifically, appears as one of the sensitive parameters, as it determines water resources. The goal of this thesis is to bring a first insight into the 21st century evolution of precipitation in Tahiti.The first step was to characterize rainfall in Tahiti using data records from the observation network of Meteo France. The “rainfall season”, lasting from November to April, is the season of interest, as rainfall amounts are the highest at this time of the year. Indeed, the South Pacific Convergence Zone (SPCZ), host of deep convection, remains the principal source of rainfall in Tahiti in austral summer (December-January-February). On interannual and interdecadal timescales, the El niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO) imply north/south and east/west migrations of the SPCZ, drawing it away, or closer to Tahiti. The positive phase of the IPO involves a north-eastward displacement of the SPCZ, which causes higher rainfall amounts in Tahiti. The SPCZ is displaced towards the south- west during negative IPO phase, leading to a decrease of rainfall in Tahiti. The study reveals that the IPO positive phase favor the occurrence of intense El niño events. In those cases, the SPCZ is critically displaced to the north-east and lies zonally just south of the equator. Accordingly, the SPCZ is drawn away from Tahiti and alters the south-east flow of trade winds. As a result, substantial orographic precipitation affect the south-east coasts of Tahiti.Following the assessment of observed precipitation for the period 1961-2011, an original method has been set up to obtain a model able to resolve the island and capture the orographic effects at best. Two successive downscaling steps have been necessary to get the limited area model ALADIN-Climat over Tahiti (at the resolution of 12 km), starting from the global coupled model CNRM-CM with a resolution of 150 km. The regional model outputs have been compared to the observed records over the historical period. A linkage between observed and modeled precipitation has been defined. This linkage has been built between meteorological stations and model grid cells exhibiting similar behaviour regarding the phases of ENSO. It has been assumed that this linkage is still relevant in the 21st century. In this way, future precipitation in Tahiti, as realistic as possible, are deduced from modeled precipitation (at 12 km of resolution), following two IPCC scenarios (RCP4.5 and RCP8.5). The El niño-like spatial structure of global warming further confirms the relevance of the linkage built previously. The results obtained concern the southern coasts of Tahiti. Rainfall would gradually increase along the 21st century, as a consequence of global warming. In Papara, the austral summer mean rainfall height is 695 mm over the period 1961-2011. The mean value, for the period 2070-2100, would be 825 mm for the scenario RCP4.5 and 814 mm for the scenario RCP8.5, let say an increase of a little less than 20%. Superimposed to this long-range raise, El niño events would induce an excess of rainfall. This effect would be reduced at the end of the 21st century in RCP8.5. Conversely, La niña events would always involve a decline of rainfall, but would not succeed in counteracting the long-range increase

Wind resource assessment for Tahiti, French Polynesia

International audienc

Changement climatique en Polynésie française détection des changements observés, évaluation des projections

The effects of climate change on Pacific islands is a major concern for the local populations. The rainfall parameter, specifically, appears as one of the sensitive parameters, as it determines water resources. The goal of this thesis is to bring a first insight into the 21st century evolution of precipitation in Tahiti.The first step was to characterize rainfall in Tahiti using data records from the observation network of Meteo France. The “rainfall season”, lasting from November to April, is the season of interest, as rainfall amounts are the highest at this time of the year. Indeed, the South Pacific Convergence Zone (SPCZ), host of deep convection, remains the principal source of rainfall in Tahiti in austral summer (December-January-February). On interannual and interdecadal timescales, the El niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO) imply north/south and east/west migrations of the SPCZ, drawing it away, or closer to Tahiti. The positive phase of the IPO involves a north-eastward displacement of the SPCZ, which causes higher rainfall amounts in Tahiti. The SPCZ is displaced towards the south- west during negative IPO phase, leading to a decrease of rainfall in Tahiti. The study reveals that the IPO positive phase favor the occurrence of intense El niño events. In those cases, the SPCZ is critically displaced to the north-east and lies zonally just south of the equator. Accordingly, the SPCZ is drawn away from Tahiti and alters the south-east flow of trade winds. As a result, substantial orographic precipitation affect the south-east coasts of Tahiti.Following the assessment of observed precipitation for the period 1961-2011, an original method has been set up to obtain a model able to resolve the island and capture the orographic effects at best. Two successive downscaling steps have been necessary to get the limited area model ALADIN-Climat over Tahiti (at the resolution of 12 km), starting from the global coupled model CNRM-CM with a resolution of 150 km. The regional model outputs have been compared to the observed records over the historical period. A linkage between observed and modeled precipitation has been defined. This linkage has been built between meteorological stations and model grid cells exhibiting similar behaviour regarding the phases of ENSO. It has been assumed that this linkage is still relevant in the 21st century. In this way, future precipitation in Tahiti, as realistic as possible, are deduced from modeled precipitation (at 12 km of resolution), following two IPCC scenarios (RCP4.5 and RCP8.5). The El niño-like spatial structure of global warming further confirms the relevance of the linkage built previously. The results obtained concern the southern coasts of Tahiti. Rainfall would gradually increase along the 21st century, as a consequence of global warming. In Papara, the austral summer mean rainfall height is 695 mm over the period 1961-2011. The mean value, for the period 2070-2100, would be 825 mm for the scenario RCP4.5 and 814 mm for the scenario RCP8.5, let say an increase of a little less than 20%. Superimposed to this long-range raise, El niño events would induce an excess of rainfall. This effect would be reduced at the end of the 21st century in RCP8.5. Conversely, La niña events would always involve a decline of rainfall, but would not succeed in counteracting the long-range increase.Les effets du changement climatique sur les îles du Pacifique constituent un enjeu majeur pour les populations insulaires. En particulier, les précipitations constituent un des paramètres sensibles car elles conditionnent la ressource en eau. Le but de cette thèse est mettre d'apporter les premiers éléments de réponse relatifs à l'évolution des précipitations au cours du 21ème siècle sur Tahiti. Dans un premier temps, les précipitations à Tahiti ont été caractérisées à partir des mesures issues du réseau d'observation de Météo France. La saison des pluies, de novembre à avril, constitue la saison d'intérêt, car c'est à cette période de l'année que les cumuls de pluie sont les plus élevés. En effet, la zone de convergence du Pacifique sud (SPCZ), siège de la convection profonde, est la principale source de précipitations à Tahiti en été austral (Décembre-Janvier-Février). A l'échelle interannuelle et interdécennale, les phénomènes El Niño Southern Oscillation (ENSO) et Interdecadal Pacific Oscillation (IPO) induisent des migrations nord/sud et est/ouest de cette zone de convergence qui l'éloignent ou l'approchent de Tahiti. L'IPO, implique un déplacement de la SPCZ vers le nord-est en phase positive, ce qui induit des cumuls plus élevés observés à Tahiti. Elle est déplacée vers le sud-ouest en phase négative de l'IPO, d'où une diminution des pluies à Tahiti. L'étude montre qu'en IPO positif, l'occurrence d'événements El Niño intenses est favorisée. Pour ces cas de figure, la SPCZ migre brutalement vers le nord-est et adopte une orientation zonale au-dessous de l'équateur. Cette configuration l'éloigne de Tahiti et perturbe le flux d'alizés de sud-est, il en résulte alors des pluies orographiques très abondantes sur les côtes sud-est de l'île. Suite à cet état des lieux des précipitations observées, une méthodologie originale, en l'absence de toute autre expérience internationale sur la région, a été mise en œuvre pour obtenir un modèle capable de distinguer l'île et capturer au mieux les effets orographiques. Deux descentes d'échelle successives ont été nécessaires pour passer du modèle couplé global CNRM-CM, à 150 km de résolution, au modèle à aire limitée ALADIN-Climat, de résolution 12 km, centré sur Tahiti. Les sorties du modèle régional obtenues ont été confrontées aux observations sur la partie historique. Un lien a été établi entre les précipitations observées et modélisées sur la période passée. Ce lien est construit entre stations d'observations et points de grille du modèle exhibant un comportement similaire relatif aux phases de l'ENSO. Il a été supposé encore pertinent au 21ième siècle pour déduire les précipitations futures les plus réalistes à Tahiti, à partir des précipitations simulées par le modèle à 12 km, suivant deux scénarios du GIEC (RCP4.5 et RCP8.5). La structure spatiale du réchauffement climatique de type El niño conforte la pertinence du lien établi. Les résultats obtenus concernent les côtes sud de Tahiti. Les précipitations vont augmenter progressivement tout au long du 21ème siècle, en réponse au réchauffement global. A Papara, il est tombé en moyenne sur la période 1961-2011 pendant l'été austral 695 mm de pluie. Il tombera en moyenne sur la période 2070-2100, 825 mm selon le scénario RCP4.5, 814 mm selon le scénario RCP8.5, soit une augmentation d'un peu moins de 20 %. Ajoutés à cet accroissement à long terme, les événements El Niño induiront un excédent de précipitations. Mais cet effet sera réduit en fin de période dans le RCP8.5. A l'inverse, les événements La Niña s'accompagneront toujours d'un déficit de précipitations mais sans arriver à contrecarrer l’accroissement à long terme

Interactions between intraseasonal and diurnal variability of precipitation in the South Central Pacific: The case of a small high island, Tahiti, French Polynesia

International audienceIntraseasonal and diurnal variability of precipitation over Tahiti, French Polynesia, are investigated with the use of wind regimes as intermediary tools. Four wind regimes have been determined over a large domain around Tahiti in the wet season. It has been shown that some phases of the Madden–Julian Oscillation (MJO) trigger some regimes and undermine some others. The diurnal cycle of precipitation in Tahiti is composed of two rainfall maxima. A frequent maximum at midnight but with a low value. An afternoon maximum, less frequent but with a higher value. We have noticed that the afternoon rainfall maximum, which is a reasonable consequence of the sea breeze circulation, is smoothen on the windward side when vigorous wind regimes obstruct the development of the sea breeze. We have also found that daily mean precipitation is significantly increased during MJO Phases 7 and 8, and reduced during Phases 2 and 3. Phase 8 is the wettest phase on Tahiti, suggesting the convective envelope is overlooking the island. Lastly, we have provided evidence that the diurnal cycle of rainfall is significantly affected by the MJO. Indeed, both the midnight and afternoon maxima increase during MJO Phase 7. The most quiescent wind regimes are triggered during Phase 7, as a result from the propagation of the westerly wind anomaly, which allow the development of the sea breeze circulation and the increase of the afternoon peak. For MJO Phase 8, however, the above relationships break down, as the diurnal cycle is not enhanced by the predominant quiescent wind regimes. We assume that the MJO convective envelope covers the island and stays several days, preventing the solar heating of the surface, hence the development of the land/sea breeze circulation, and foremost leads to higher amounts of rainfall as the Phase 8 is the wettest phase on Tahiti

Solar Irradiance Probabilistic Forecasting Using Machine Learning, Metaheuristic Models and Numerical Weather Predictions

Solar-power-generation forecasting tools are essential for microgrid stability, operation, and planning. The prediction of solar irradiance (SI) usually relies on the time series of SI and other meteorological data. In this study, the considered microgrid was a combined cold- and power-generation system, located in Tahiti. Point forecasts were obtained using a particle swarm optimization (PSO) algorithm combined with three stand-alone models: XGboost (PSO-XGboost), the long short-term memory neural network (PSO-LSTM), and the gradient boosting regression algorithm (PSO-GBRT). The implemented daily SI forecasts relied on an hourly time-step. The input data were composed of outputs from the numerical forecasting model AROME (Météo France) combined with historical meteorological data. Our three hybrid models were compared with other stand-alone models, namely, artificial neural network (ANN), convolutional neural network (CNN), random forest (RF), LSTM, GBRT, and XGboost. The probabilistic forecasts were obtained by mapping the quantiles of the hourly residuals, which enabled the computation of 38%, 68%, 95%, and 99% prediction intervals (PIs). The experimental results showed that PSO-LSTM had the best accuracy for day-ahead solar irradiance forecasting compared with the other benchmark models, through overall deterministic and probabilistic metrics

Investigating Wind Energy Potential in Tahiti, French Polynesia

In order to achieve France’s goal of carbon neutrality by 2050, the French Polynesian administration has set the objective of producing 100% of the local electricity requirements from renewable energy resources. To this end, we present the wind characteristics at six selected locations in Tahiti. Surface wind observations from 2008 to 2020 obtained from the Meteorological Service of French Polynesia are analysed in terms of wind speed, dominant wind direction and power density to identify the most suitable locations for the deployment of wind farms. The Weibull distribution is used to fit the wind speed data recorded at 10 m above ground level, as it is widely used by turbine manufacturers. Then, wind speed is extrapolated vertically up to the hub height with the power law, which is also commonly used in wind energy studies. The theoretical annual energy output and capacity factor of four selected commercial wind turbines are assessed for each site in order to provide stakeholders with the relevant information regarding wind energy harvesting in Tahiti. Power law indices lower than 0.2 were chosen. Our results show that all year round, two sites, Faaa and Tautira, are suitable to host wind turbines, even with a power law index as low as 0.1.ISSN:1996-107

Solar Irradiance Probabilistic Forecasting Using Machine Learning, Metaheuristic Models and Numerical Weather Predictions

International audienceSolar-power-generation forecasting tools are essential formicrogrid stability, operation, and planning. The prediction ofsolar irradiance (SI) usually relies on the time series of SI andother meteorological data. In this study, the considered microgridwas a combined cold- and power-generation system, located inTahiti. Point forecasts were obtained using a particle swarmoptimization (PSO) algorithm combined with three stand-alonemodels: XGboost (PSO-XGboost), the long short-term memory neuralnetwork (PSO-LSTM), and the gradient boosting regression algorithm(PSO-GBRT). The implemented daily SI forecasts relied on an hourlytime-step. The input data were composed of outputs from thenumerical forecasting model AROME (Météo France) combined withhistorical meteorological data. Our three hybrid models werecompared with other stand-alone models, namely, artificial neuralnetwork (ANN), convolutional neural network (CNN), random forest(RF), LSTM, GBRT, and XGboost. The probabilistic forecasts wereobtained by mapping the quantiles of the hourly residuals, whichenabled the computation of 38%, 68%, 95%, and 99% predictionintervals (PIs). The experimental results showed that PSO-LSTM hadthe best accuracy for day-ahead solar irradiance forecastingcompared with the other benchmark models, through overalldeterministic and probabilistic metrics

Assessing solar resource and photovoltaic production in Tahiti from ground-based measurements

This study focuses on the solar resource available at Faaa, Tahiti (17.5°S, 149.5°W) thanks to 10 year-long solar irradiance time series. Faaa’s global horizontal irradiance ranges from 14 MJ.m-2.day-1 (June) to 21 MJ.m-2.day-1 (November) in agreement with the sun’s annual path, while clearness index ranges from 0.5 (January) to 0.67 (July), in agreement with the wet and dry seasons. The Global Solar Atlas satellite-derived dataset shows acceptable relative error when compared to Faaa in situ measurements. This product could then be used for other coastal areas of Tahiti. The annual energy output of a single PV module is 256.7 kWh, which corresponds to 7 % of the annual consumption of a typical household in Tahiti. The capacity factor reaches 22.5 %, which makes Faaa a good site for harnessing solar resource