Natural processes behind the CO2 sink variability in the Southern Ocean during the last three decades

Anthropogenic activities during the past two centuries have caused an increase in atmospheric CO2 which has driven a linear increase in oceanic CO2 uptake. The Southern Ocean (SO, < 35¿S) is one of the major uptake areas for anthropogenic CO2, responsible for ~40% of ocean CO2 sink. Apart from the linear increase in the CO2 sinking trend, in the SO pronounced variations have been observed in recent decades, driven by natural processes, but the exact mechanisms behind them are still debated. Aiming to fill this knowledge gap, we investigated the natural drivers of CO2 flux variations in the SO using existing observation-based datasets between the years 1982-2019. We removed the long-term linear trend in the time series of CO2 flux and other indexes to focus on decadal variations. We found that two mechanisms explain the interannual to decadal variations in the SO: Ekman upwelling and eddy kinetic energy, by their controls on different components of surface pCO2 variations. The pattern of variability in Ekman upwelling during the time period studied was markedly circumpolar, and the time series of its 1st principal component was strongly correlated with the detrended SAM Index (r=0.81, p<0.05). Similarly, leading EOF maps of CO2 flux anomalies and the components of surface pCO2 changes (i.e., nonthermal and thermal) show that their variations were dominantly symmetric. As previously shown, weakening of SO CO2 sink in the 1990s coincides with intense positive SAM episodes. Following the late 1990s, the intensity of SAM decreased, which strengthened the CO2 sink in the early 2000s. At the same time, the relative contribution of the thermal component grew south of the Polar Front, indicating positive temperature anomalies during this period. Such warming events, following intense and recursive SAM episodes were reported before and were attributed to the increased mesoscale eddy activity in the region. In agreement with these studies, our results show that eddy kinetic energy increased after intense SAM periods with a lagged response of ~2 years, and a positive temperature anomaly in low frequency was observed following these peaks. This warming prevented the CO2 uptake rate from reaching immediately to its potential strength in the absence of strong westerlies, and explains the growing effect of the thermal pCO2 component.Postprint (published version

Modelling the Pelagic Ecosystem Dynamics: The NW Mediterranean

26 páginas. 11 figuras,1 tabla.Peer reviewe

Impact of Weddell Sea deep convection on natural and anthropogenic carbon in a climate model

A climate model is used to investigate the influence of Weddell Sea open ocean deep convection on anthropogenic and natural carbon uptake for the period 1860-2100. In a three-member ensemble climate change simulation, convection ceases on average by year 1981, weakening the net oceanic cumulative uptake of atmospheric CO2 by year 2100 (-4.3 Pg C) relative to an ocean that has continued convection. This net weakening results from a decrease in anthropogenic carbon uptake (-10.1 Pg C), partly offset by an increase in natural carbon storage (+5.8 Pg C). Despite representing only 4% of its area, the Weddell Sea is responsible for 22% of the Southern Ocean decrease in total climate-driven carbon uptake and 52% of the decrease in the anthropogenic component of oceanic uptake. Although this is a model-specific result, it illustrates the potential of deep convection to produce an inter-model spread in future projections of ocean carbon uptake

The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.The development of EC-Earth3 was supported by the European Union's Horizon 2020 research and innovation program under project IS-ENES3, the third phase of the distributed e-infrastructure of the European Network for Earth System Modelling (ENES) (grant agreement no. 824084, PRIMAVERA grant no. 641727, and CRESCENDO grant no. 641816). Etienne Tourigny and Raffaele Bernardello have received funding from the European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement nos. 748750 (SPFireSD project) and 708063 (NeTNPPAO project). Ivana Cvijanovic was supported by Generalitat de Catalunya (Secretaria d'Universitats i Recerca del Departament d’Empresa i Coneixement) through the Beatriu de Pinós program. Yohan Ruprich-Robert was funded by the European Union's Horizon 2020 research and innovation program in the framework of Marie Skłodowska-Curie grant INADEC (grant agreement 800154). Paul A. Miller, Lars Nieradzik, David Wårlind, Roland Schrödner, and Benjamin Smith acknowledge financial support from the strategic research area “Modeling the Regional and Global Earth System” (MERGE) and the Lund University Centre for Studies of Carbon Cycle and Climate Interactions (LUCCI). Paul A. Miller, David Wårlind, and Benjamin Smith acknowledge financial support from the Swedish national strategic e-science research program eSSENCE. Paul A. Miller further acknowledges financial support from the Swedish Research Council (Vetenskapsrådet) under project no. 621-2013-5487. Shuting Yang acknowledges financial support from a Synergy Grant from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC (grant agreement 610055) as part of the ice2ice project and the NordForsk-funded Nordic Centre of Excellence project (award 76654) ARCPATH. Marianne Sloth Madsen acknowledges financial support from the Danish National Center for Climate Research (NCKF). Andrea Alessandri and Peter Anthoni acknowledge funding from the Helmholtz Association in its ATMO program. Thomas Arsouze, Arthur Ramos, and Valentina Sicardi received funding from the Ministerio de Ciencia, Innovación y Universidades as part of the DeCUSO project (CGL2017-84493-R).​​​​​​​Peer Reviewed"Article signat per 61 autors/es: Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho11, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang"Postprint (author's final draft

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean- sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean-sea-ice models (JRA55-do).We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean-ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean-sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80% of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP- 2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP- 2. For example, the sea surface temperatures of the OMIP- 2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating processlevel responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean-sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123).Peer ReviewedPostprint (published version

A comparison of remote-sensing SST and in situ seawater temperature in near-shore habitats in the western Mediterranean Sea

Remote sensing of sea surface temperature (SST) is widely used in climate science because it provides a quasi-synoptic coverage of the ocean. However, the use of these data for near-shore habitats is hindered by the proximity of the coast, therefore further investigation is needed. We compared remote-sensing SST from the MODIS sensor (aboard the Aqua satellite) to near-shore seawater temperature (ST) recorded in situ with data loggers at 5 locations in the western Mediterranean Sea. In situ ST data were collected at 5 m depth over a ~6 yr period and at depths below 5 m at 3 of the locations. We evaluated the suitability of MODIS to represent the temperature at shallow subtidal depths relative to different modes of variability. MODIS reproduced seasonal variability with high correlations (r &gt; 0.98) and biases (0.59 ± 0.03°C) only slightly higher than the accuracy of the loggers (0.50°C). MODIS also captured interannual variability with no systematic biases. When evaluated for intra-seasonal temperature variability, MODIS showed limited biases (up to 0.79°C) with a tendency to overestimate the variability (between 4 and 64%) in both cold and warm seasons. Finally, MODIS over-/underestimated only the most extreme unseasonably cold/warm events (by 1.51 and -0.79°C, respectively). The observed limited differences between the 2 methods can be explained by the particular hydrodynamics of the area and by methodological constraints. Overall, MODIS SST data proved to be a reliable proxy for near-shore ST in the western Mediterranean Sea, and are thus considered suitable for studies requiring temperature reconstruction in shallow near-shore environments

The CEAB´s Marine Observatory in the Catalan Sea: Consolidating long time series observations?

Trabajo presentado en el MARTECH 2011 Fourth International Workshop on Marine Technology, celbrado en Cádiz el 22 y 23 de septiembre de 2011.The Operational Observatory of the Catalan Sea (OOCS), created in 2009 at CEAB-CSIC may be considered as a reference marine observatory because of its effectiveness and relatively low-cost functioning and maintenance. The number of time series obtained at the observation station of the meteorological conditions above the sea surface, along with physical and biogeochemical properties of the water layer over the continental shelf, supports its success. The strong fluctuations of atmospheric conditions registered in the last years altering the marine conditions make the simultaneous records of meteorological and marine observations essential for understanding present environmental fluctuations and for improving marine environmental predictions. Updated information regarding the observatory can be found at http://www.ceab.csic.es/~oceans/.The marine observatory is supported by the Spanish Ministry of Science and Innovation project CTM2008-03983.Peer Reviewe

Bridging the gaps between particulate backscattering measurements and modeled particulate organic carbon in the ocean

International audienceOceanic particulate organic carbon (POC) is a small but dynamic component of the global carbon cycle. Biogeochemical models historically focused on reproducing the sinking flux of POC driven by large fast-sinking particles (LPOC). However, suspended and slow-sinking particles (SPOC, here Recent developments in the parameterization of POC reactivity in PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies model; PISCESv2_RC) have improved its ability to capture POC dynamics. Here we evaluated this model by matching a global 3D simulation and 1D simulations at 50 different locations with observations made from biogeochemical (BGC-) Argo floats and satellites. Our evaluation covers globally representative biomes between 0 and 1000 m depth and relies on (1) a refined scheme for converting particulate backscattering at 700 nm (bbp700) to POC, based on biome-dependent POC / bbp700 ratios in the surface layer that decrease to an asymptotic value at depth; (2) a novel approach for matching annual time series of BGC-Argo vertical profiles to PISCES 1D simulations forced by pre-computed vertical mixing fields; and (3) a critical evaluation of the correspondence between in situ measurements of POC fractions, PISCES model tracers, and SPOC and LPOC estimated from high vertical resolution bbp700 profiles through a separation of the baseline and spike signals. We show that PISCES captures the major features of SPOC and LPOC across a range of spatiotemporal scales, from highly resolved profile time series to biome-aggregated climatological profiles. Model-observation agreement is usually better in the epipelagic (0-200 m) than in the mesopelagic (200-1000 m), with SPOC showing overall higher spatiotemporal correlation and smaller deviation (typically within a factor of 1.5). Still, annual mean LPOC stocks estimated from PISCES and BGC-Argo are highly correlated across biomes, especially in the epipelagic (r=0.78; n=50). Estimates of the SPOC / TPOC fraction converge around a median of 85 % (range 66 %-92 %) globally. Distinct patterns of model-observations misfits are found in subpolar and subtropical gyres, pointing to the need to better resolve the interplay between sinking, remineralization, and SPOC-LPOC interconversion in PISCES. Our analysis also indicates that a widely used satellite algorithm overestimates POC severalfold at high latitudes during the winter. The approaches proposed here can help constrain the stocks, and ultimately budgets, of oceanic POC

Seven years of marine environmental changes monitoring at coastal OOCS stations (Catalan Sea, NW Mediterranean)

7th International Workshop on Marine Technology – Martech Workshop 2016, 26-28 October 2016, Barcelona.-- 2 pages, 3 figuresSince March 2009 up to the present (more than 7 years now), the Operational Observatory of the Catalan Sea (OOCS; http://www2.ceab.csic.es/ oceans/) remains a witness of persistent marine environmental changes. The OOCS has two fixed observation stations at the head of the Blanes Canyon (200 m depth, 41.66°N; 2.91°E) and at the Blanes bay (20 m depth, 41.67°N; 2.80°E) in the Catalan Sea, NW Mediterranean. At the canyon station, a multi-parametric buoy presently installed delivers high frequency (by 30 min) and multi-parametric oceanographic (i.e. salinity, temperature, chlorophyll, turbidity, as well as light intensity in the PAR range for the upper 50 m depth) and atmospheric (air temperature, relative humidity, wind speed and direction and PAR) data. Subsurface photos and videos by an IP high resolution fisheye camera attached to the buoy are also delivered at 4-hour basis. Data and multimedia are transmitted in near real time for public access, via combined GSM/GPRS and 3G connections. At both stations, CTD profiles and water samples (collected for nutrients and picoplankton analyses) are carried out on board a research vessel at fortnightly basis. Numerical simulations along with the time series of in-situ observations show inter-annual seasonality anomalies possibly linked to global environmental changes. The lower-atmosphere and upper-sea environmental time series data collected prove the occurrence of shifting patterns of heat and matter fluxes impacting pelagic and benthic organismsPeer Reviewe