Consulta: creatorFacets:"Lengaigne, Matthieu"
Registros recuperados: 10
Data/hora: 02/06/2024 00:52:37

Ocean Climate Observing Requirements in Support of Climate Research and Climate Information
Provedor de dados: 5
Autores: Stammer, Detlef; Bracco, Annalisa; Achutarao, Krishna; Beal, Lisa; Bindoff, Nathaniel L.; Braconnot, Pascale; Cai, Wenju; Chen, Dake; Collins, Matthew; Danabasoglu, Gokhan; Dewitte, Boris; Farneti, Riccardo; Fox-kemper, Baylor; Fyfe, John; Griffies, Stephen M.; Jayne, Steven R.; Lazar, Alban; Lengaigne, Matthieu; Lin, Xiaopei; Marsland, Simon; Minobe, Shoshiro; Monteiro, Pedro M. S.; Robinson, Walter; Roxy, Mathew Koll; Rykaczewski, Ryan R.; Speich, Sabrina; Smith, Inga J.; Solomon, Amy; Storto, Andrea; Takahashi, Ken; Toniazzo, Thomas; Vialard, Jerome.
Natural variability and change of the Earth's climate have significant global societal impacts. With its large heat and carbon capacity and relatively slow dynamics, the ocean plays an integral role in climate, and provides an important source of predictability at seasonal and longer timescales. In addition, the ocean provides the slowly evolving lower boundary to the atmosphere, driving, and modifying atmospheric weather. Understanding and monitoring ocean climate variability and change, to constrain and initialize models as well as identify model biases for improved climate hindcasting and prediction, requires a scale-sensitive, and long-term observing system. A climate observing system has requirements that significantly differ from, and sometimes are...
Tipo: Text
Palavras-chave: Ocean observing system; Ocean climate; Earth observations; In situ measurements; Satellite observations; Ocean modeling; Climate information.
Ano: 2019
URL: https://archimer.ifremer.fr/doc/00675/78724/80996.pdf

Assessment of seasonal and year-to-year surface salinity signals retrieved from SMOS and Aquarius missions in the Bay of Bengal
Provedor de dados: 5
Autores: Akhil, V. P.; Lengaigne, Matthieu; Durand, Fabien; Vialard, Jerome; Chaitanya, A. V. S.; Keerthi, M. G.; Gopalakrishna, V. V.; Boutin, Jacqueline; De Boyer Montegut, Clement.
The Bay of Bengal (BoB) exhibits a wide range of sea surface salinity (SSS), with very fresh water induced by heavy monsoonal precipitation and river run-offs to the north, and saltier water to the south. This is a particularly challenging region for the application of satellite-derived SSS measurements because of the potential pollution of the SSS signal by radio frequency interference (RFI) and land-induced contamination in this semi-enclosed basin. The present study validates recent level-3 monthly gridded (1° × 1°) SSS products from Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions to an exhaustive in situ SSS product for the BoB. Current SMOS SSS retrievals do not perform better than existing climatologies. This is in stark contrast to...
Tipo: Text
Ano: 2016
URL: http://archimer.ifremer.fr/doc/00319/42986/45003.pdf

Global impact of tropical cyclones on primary production
Provedor de dados: 5
Autores: Menkes, Christophe E.; Lengaigne, Matthieu; Levy, Marina; Ethe, Christian; Bopp, Laurent; Aumont, Olivier; Vincent, Emmanuel; Vialard, Jerome; Jullien, Swen.
In this paper, we explore the global responses of surface temperature, chlorophyll and primary production to tropical cyclones (TCs). Those ocean responses are first characterized from the statistical analysis of satellite data under ~1000 TCs over the 1998-2007 period. Besides the cold wake, the vast majority of TCs induce a weak chlorophyll response, with only ~10% of induced blooms exceeding 0.1 mg.m-3. The largest chlorophyll responses mostly occur within coastal regions, in contrast to the strongest cold wakes that generally occur farther offshore. To understand this decoupling, we analyze a coupled dynamical-biogeochemical oceanic simulation forced by realistic wind vortices applied along observed TC tracks. The simulation displays a realistic...
Tipo: Text
Ano: 2016
URL: http://archimer.ifremer.fr/doc/00333/44449/44121.pdf

A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal
Provedor de dados: 5
Autores: Akhil, V. P.; Durand, Fabien; Lengaigne, Matthieu; Vialard, Jerome; Keerthi, M. G.; Gopalakrishna, V. V.; Deltel, Charles; Papa, Fabrice; De Boyer Montegut, Clement.
In response to the Indian Monsoon freshwater forcing, the Bay of Bengal exhibits a very strong seasonal cycle in sea surface salinity (SSS), especially near the mouths of the Ganges-Brahmaputra and along the east coast of India. In this paper, we use an eddy-permitting (∼25 km resolution) regional ocean general circulation model simulation to quantify the processes responsible for this SSS seasonal cycle. Despite the absence of relaxation toward observations, the model reproduces the main features of the observed SSS seasonal cycle, with freshest water in the northeastern Bay, particularly during and after the monsoon. The model also displays an intense and shallow freshening signal in a narrow (∼100 km wide) strip that hugs the east coast of India, from...
Tipo: Text
Ano: 2014
URL: http://archimer.ifremer.fr/doc/00197/30819/29189.pdf

Influence of the state of the Indian Ocean Dipole on the following year's El Nino
Provedor de dados: 5
Autores: Izumo, Takeshi; Vialard, Jerome; Lengaigne, Matthieu; De Boyer Montegut, Clement; Behera, Swadhin K.; Luo, Jing-jia; Cravatte, Sophie; Masson, Sebastien; Yamagata, Toshio.
El Nino-Southern Oscillation (ENSO) consists of irregular episodes of warm El Nino and cold La Nina conditions in the tropical Pacific Ocean(1), with significant global socio-economic and environmental impacts(1). Nevertheless, forecasting ENSO at lead times longer than a few months remains a challenge(2,3). Like the Pacific Ocean, the Indian Ocean also shows interannual climate fluctuations, which are known as the Indian Ocean Dipole(4,5). Positive phases of the Indian Ocean Dipole tend to co-occur with El Nino, and negative phases with La Nina(6-9). Here we show using a simple forecast model that in addition to this link, a negative phase of the Indian Ocean Dipole anomaly is an efficient predictor of El Nino 14 months before its peak, and similarly, a...
Tipo: Text
Ano: 2010
URL: http://archimer.ifremer.fr/doc/00002/11304/7831.pdf

Impact of projected sea surface temperature biases on tropical cyclones projections in the South Pacific
Provedor de dados: 5
Autores: Dutheil, C.; Lengaigne, Matthieu; Bador, M.; Vialard, J.; Lefèvre, J.; Jourdain, N. C.; Jullien, Swen; Peltier, A.; Sultan, B.; Menkès, C.
Climate model projections generally indicate fewer but more intense tropical cyclones (TCs) in response to increasing anthropogenic emissions. However these simulations suffer from long-standing biases in their Sea Surface Temperature (SST). While most studies investigating future changes in TC activity using high-resolution atmospheric models correct for the present-day SST bias, they do not consider the reliability of the projected SST changes from global climate models. The present study illustrates that future South Pacific TC activity changes are strongly sensitive to correcting the projected SST changes using an emergent constraint method. This additional correction indeed leads to a strong reduction of the cyclogenesis (−55%) over the South Pacific...
Tipo: Text
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00614/72648/71651.pdf

Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach
Provedor de dados: 5
Autores: Martinez, Elodie; Gorgues, Thomas; Lengaigne, Matthieu; Fontana, Clement; Sauzède, Raphaëlle; Menkes, Christophe; Uitz, Julia; Di Lorenzo, Emanuele; Fablet, Ronan.
Monitoring the spatio-temporal variations of surface chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) greatly benefited from the availability of continuous and global ocean color satellite measurements from 1997 onward. These two decades of satellite observations are however still too short to provide a comprehensive description of Chl variations at decadal to multi-decadal timescales. This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. With a limited training period (13 years), we first demonstrate that Chl variability...
Tipo: Text
Palavras-chave: Machine learning; Phytoplankton variability; Satellite ocean color; Decadel variability; Global scale.
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00641/75314/75810.pdf

Physical control of interannual variations of the winter chlorophyll bloom in the northern Arabian Sea
Provedor de dados: 5
Autores: Keerthi, Madhavan Girijakumari; Lengaigne, Matthieu; Levy, Marina; Vialard, Jerome; Parvathi, Vallivattathillam; De Boyer Montegut, Clement; Ethe, Christian; Aumont, Olivier; Suresh, Iyyappan; Akhil, Valiya Parambil; Muraleedharan, Pillathu Moolayil.
The northern Arabian Sea hosts a winter chlorophyll bloom, triggered by convective overturning in response to cold and dry northeasterly monsoon winds. Previous studies of interannual variations of this bloom only relied on a couple of years of data and reached no consensus on the associated processes. The current study aims at identifying these processes using both similar to 10 years of observations (including remotely sensed chlorophyll data and physical parameters derived from Argo data) and a 20-year-long coupled biophysical ocean model simulation. Despite discrepancies in the estimated bloom amplitude, the six different remotely sensed chlorophyll products analysed in this study display a good phase agreement at seasonal and interannual timescales....
Tipo: Text
Ano: 2017
URL: http://archimer.ifremer.fr/doc/00395/50625/51332.pdf

Contrasted contribution of intraseasonal timescales to Surface Chlorophyll variations in a bloom and an oligotrophic regime
Provedor de dados: 5
Autores: Keerthi, M. G.; Levy, M.; Aumont, Olivier; Lengaigne, Matthieu; Antoine, D.
Understanding long‐term variations of ocean ecosystems requires untangling the time scales involved in their natural fluctuations. We applied a temporal decomposition procedure to two decades of satellite ocean color observations to characterize the time variability of surface Chlorophyll‐a (SChl) in the Mediterranean Sea. In order to assess the reliability of the satellite data at capturing intraseasonal, seasonal and interannual variability, we first show that satellite SChl data compare well with field data of phytoplankton fluorescence from the long‐term BOUSSOLE time series, at all three timescales. The decomposition procedure is then applied to satellite SChl and to mixing‐layer depth (MxLD) data from an ocean reanalysis, both at the scale of the...
Tipo: Text
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00624/73654/73098.pdf

A Road Map to IndOOS-2: Better observations of the rapidly-warming Indian Ocean
Provedor de dados: 5
Autores: Beal, L. M.; Vialard, J.; Roxy, M.k.; Li, J.; Andres, M.; Annamalai, H.; Feng, M.; Han, W.; Hood, R.; Lee, T.; Lengaigne, Matthieu; Lumpkin, R.; Masumoto, Y.; Mcphaden, M.j.; Ravichandran, M.; Shinoda, T.; Sloyan, B.m.; Strutton, P.g.; Subramanian, A.c.; Tozuka, T.; Ummenhofer, C.c.; Unnikrishnan, A.s.; Wiggert, J.; Yu, L.; Cheng, L.; Desbruyères, Damien; Parvathi, V.
The Indian Ocean Observing System (IndOOS), established in 2006, is a multi-national network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity indeed lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific...
Tipo: Text
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00644/75658/76530.pdf