Consulta: creatorFacets:"Monteiro, Pedro M. S."
Registros recuperados: 8
Data/hora: 09/06/2024 06:42:46

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

Global Carbon Budget 2016
Provedor de dados: 5
Autores: Le Quere, Corinne; Andrew, Robbie M.; Canadell, Josep G.; Sitch, Stephen; Korsbakken, Jan Ivar; Peters, Glen P.; Manning, Andrew C.; Boden, Thomas A.; Tans, Pieter P.; Houghton, Richard A.; Keeling, Ralph F.; Alin, Simone; Andrews, Oliver D.; Anthoni, Peter; Barbero, Leticia; Bopp, Laurent; Chevallier, Frederic; Chini, Louise P.; Ciais, Philippe; Currie, Kim; Delire, Christine; Doney, Scott C.; Friedlingstein, Pierre; Gkritzalis, Thanos; Harris, Ian; Hauck, Judith; Haverd, Vanessa; Hoppema, Mario; Goldewijk, Kees Klein; Jain, Atul K.; Kato, Etsushi; Koertzinger, Arne; Landschuetzer, Peter; Lefevre, Nathalie; Lenton, Andrew; Lienert, Sebastian; Lombardozzi, Danica; Melton, Joe R.; Metzl, Nicolas; Millero, Frank; Monteiro, Pedro M. S.; Munro, David R.; Nabel, Julia E. M. S.; Nakaoka, Shin-ichiro; O'Brien, Kevin; Olsen, Are; Omar, Abdirahman M.; Ono, Tsuneo; Pierrot, Denis; Poulter, Benjamin; Roedenbeck, Christian; Salisbury, Joe; Schuster, Ute; Schwinger, Joerg; Seferian, Roland; Skjelvan, Ingunn; Stocker, Benjamin D.; Sutton, Adrienne J.; Takahashi, Taro; Tian, Hanqin; Tilbrook, Bronte; Van Der Laan-luijkx, Ingrid T.; Van Der Werf, Guido R.; Viovy, Nicolas; Walker, Anthony P.; Wiltshire, Andrew J.; Zaehle, Soenke.
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere - the "global carbon budget" - is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil...
Tipo: Text
Ano: 2016
URL: https://archimer.ifremer.fr/doc/00383/49401/49899.pdf

Empirical methods for the estimation of Southern Ocean CO2: support vector and random forest regression
Provedor de dados: 5
Autores: Gregor, Luke; Kok, Schalk; Monteiro, Pedro M. S.
The Southern Ocean accounts for 40% of oceanic CO2 uptake, but the estimates are bound by large uncertainties due to a paucity in observations. Gap-filling empirical methods have been used to good effect to approximate pCO(2) from satellite observable variables in other parts of the ocean, but many of these methods are not in agreement in the Southern Ocean. In this study we propose two additional methods that perform well in the Southern Ocean: support vector regression (SVR) and random forest regression (RFR). The methods are used to estimate Delta pCO(2) in the Southern Ocean based on SOCAT v3, achieving similar trends to the SOM-FFN method by Landschitzer et al. (2014). Results show that the SOM-FFN and RFR approaches have RMSEs of similar magnitude...
Tipo: Text
Ano: 2017
URL: https://archimer.ifremer.fr/doc/00662/77388/79018.pdf

South African carbon observations: CO2 measurements for land, atmosphere and ocean
Provedor de dados: 5
Autores: Feig, Gregor T.; Joubert, Warren R.; Mudau, Azwitamisi E.; Monteiro, Pedro M. S.
Tipo: Text
Palavras-chave: PCO(2); Eddy covariance; Carbon reporting; Carbon flux.
Ano: 2017
URL: https://archimer.ifremer.fr/doc/00662/77391/79074.pdf

The seasonal cycle of pCO(2) and CO2 fluxes in the Southern Ocean: diagnosing anomalies in CMIP5 Earth system models
Provedor de dados: 5
Autores: Mongwe, N. Precious; Vichi, Marcello; Monteiro, Pedro M. S.
The Southern Ocean forms an important component of the Earth system as a major sink of CO2 and heat. Recent studies based on the Coupled Model Intercomparison Project version 5 (CMIP5) Earth system models (ESMs) show that CMIP5 models disagree on the phasing of the seasonal cycle of the CO2 flux (FCO2) and compare poorly with available observation products for the Southern Ocean. Because the seasonal cycle is the dominant mode of CO2 variability in the Southern Ocean, its simulation is a rigorous test for models and their long-term projections. Here we examine the competing roles of temperature and dissolved inorganic carbon (DIC) as drivers of the seasonal cycle of pCO(2) in the Southern Ocean to explain the mechanistic basis for the seasonal biases in...
Tipo: Text
Ano: 2018
URL: https://archimer.ifremer.fr/doc/00673/78489/80818.pdf

A multi-decade record of high-quality fCO(2) data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)
Provedor de dados: 5
Autores: Bakker, Dorothee C. E.; Pfeil, Benjamin; Landa, Camilla S.; Metzl, Nicolas; O'Brien, Kevin M.; Olsen, Are; Smith, Karl; Cosca, Cathy; Harasawa, Sumiko; Jones, Stephen D.; Nakaoka, Shin-ichiro; Nojiri, Yukihiro; Schuster, Ute; Steinhoff, Tobias; Sweeney, Colm; Takahashi, Taro; Tilbrook, Bronte; Wada, Chisato; Wanninkhof, Rik; Alin, Simone R.; Balestrini, Carlos F.; Barbero, Leticia; Bates, Nicholas R.; Bianchi, Alejandro A.; Bonou, Frederic; Boutin, Jacqueline; Bozec, Yann; Burger, Eugene F.; Cai, Wei-jun; Castle, Robert D.; Chen, Liqi; Chierici, Melissa; Currie, Kim; Evans, Wiley; Featherstone, Charles; Feely, Richard A.; Fransson, Agneta; Goyet, Catherine; Greenwood, Naomi; Gregor, Luke; Hankin, Steven; Hardman-mountford, Nick J.; Harlay, Jerome; Hauck, Judith; Hoppema, Mario; Humphreys, Matthew P.; Hunt, Christopherw.; Huss, Betty; Ibanhez, J. Severino P.; Johannessen, Truls; Keeling, Ralph; Kitidis, Vassilis; Koertzinger, Arne; Kozyr, Alex; Krasakopoulou, Evangelia; Kuwata, Akira; Landschuetzer, Peter; Lauvset, Siv K.; Lefevre, Nathalie; Lo Monaco, Claire; Manke, Ansley; Mathis, Jeremy T.; Merlivat, Liliane; Millero, Frank J.; Monteiro, Pedro M. S.; Munro, David R.; Murata, Akihiko; Newberger, Timothy; Omar, Abdirahman M.; Ono, Tsuneo; Paterson, Kristina; Pearce, David; Pierrot, Denis; Robbins, Lisa L.; Saito, Shu; Salisbury, Joe; Schlitzer, Reiner; Schneider, Bernd; Schweitzer, Roland; Sieger, Rainer; Skjelvan, Ingunn; Sullivan, Kevin F.; Sutherland, Stewart C.; Sutton, Adrienne J.; Tadokoro, Kazuaki; Telszewski, Maciej; Tuma, Matthias; Van Heuven, Steven M. A. C. .; Vandemark, Doug; Ward, Brian; Watson, Andrew J.; Xu, Suqing.
The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO(2) (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO(2) values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO(2) values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO(2) values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and...
Tipo: Text
Ano: 2016
URL: https://archimer.ifremer.fr/doc/00383/49405/49890.pdf

Global Carbon Budget 2017
Provedor de dados: 5
Autores: Le Quere, Corinne; Andrew, Robbie M.; Friedlingstein, Pierre; Sitch, Stephen; Pongratz, Julia; Manning, Andrew C.; Korsbakken, Jan Ivar; Peters, Glen P.; Canadell, Josep G.; Jackson, Robert B.; Boden, Thomas A.; Tans, Pieter P.; Andrews, Oliver D.; Arora, Vivek K.; Bakker, Dorothee C. E.; Barbero, Leticia; Becker, Meike; Betts, Richard A.; Bopp, Laurent; Chevallier, Frederic; Chini, Louise P.; Ciais, Philippe; Cosca, Catherine E.; Cross, Jessica; Currie, Kim; Gasser, Thomas; Harris, Ian; Hauck, Judith; Haverd, Vanessa; Houghton, Richard A.; Hunt, Christopher W.; Hurtt, George; Ilyina, Tatiana; Jain, Atul K.; Kato, Etsushi; Kautz, Markus; Keeling, Ralph F.; Goldewijk, Kees Klein; Koertzinger, Arne; Landschuetzer, Peter; Lefevre, Nathalie; Lenton, Andrew; Lienert, Sebastian; Lima, Ivan; Lombardozzi, Danica; Metzl, Nicolas; Millero, Frank; Monteiro, Pedro M. S.; Munro, David R.; Nabel, Julia E. M. S.; Nakaoka, Shin-ichiro; Nojiri, Yukihiro; Padin, X. Antonio; Peregon, Anna; Pfeil, Benjamin; Pierrot, Denis; Poulter, Benjamin; Rehder, Gregor; Reimer, Janet; Roedenbeck, Christian; Schwinger, Jorg; Seferian, Roland; Skjelvan, Ingunn; Stocker, Benjamin D.; Tian, Hanqin; Tilbrook, Bronte; Tubiello, Francesco N.; Van Der Laan-luijkx, Ingrid T.; Van Der Werf, Guido R.; Van Heuven, Steven; Viovy, Nicolas; Vuichard, Nicolas; Walker, Anthony P.; Watson, Andrew J.; Wiltshire, Andrew J.; Zaehle, Soenke; Zhu, Dan.
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and...
Tipo: Text
Ano: 2018
URL: https://archimer.ifremer.fr/doc/00433/54428/55948.pdf

Interannual drivers of the seasonal cycle of CO2 in the Southern Ocean
Provedor de dados: 5
Autores: Gregor, Luke; Kok, Schalk; Monteiro, Pedro M. S.
Resolving and understanding the drivers of variability of CO2 in the Southern Ocean and its potential climate feedback is one of the major scientific challenges of the ocean-climate community. Here we use a regional approach on empirical estimates of pCO(2) to understand the role that seasonal variability has in long-term CO2 changes in the Southern Ocean. Machine learning has become the preferred empirical modelling tool to interpolate time- and location-restricted ship measurements of pCO(2). In this study we use an ensemble of three machine-learning products: support vector regression (SVR) and random forest regression (RFR) from Gregor et al. (2017), and the self-organising-map feed-forward neural network (SOM-FFN) method from Land-schutzer et al....
Tipo: Text
Ano: 2018
URL: https://archimer.ifremer.fr/doc/00673/78492/80822.pdf