https://biogeoscapes.net//wiki/api.php?action=feedcontributions&feedformat=atom&user=CamRichonOceanWiki - User contributions [en]2026-04-12T15:54:17ZUser contributionsMediaWiki 1.45.0https://biogeoscapes.net//wiki/index.php?title=CMIP&diff=598CMIP2026-03-24T10:35:06Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[User:CamRichon|Camille Richon]]<br />
* [[Responsible curator|Responsible curator]]: [[]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic<br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Spatial resolution:''' grid: 2°, 1° since CMIP6, domain: global<br />
|-<br />
| '''Temporal resolution:''' time step: model dependent, usually s to hours ; output: yearly to monthly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
The Coupled Model Intercomparison Project (CMIP) is a global effort from the international research community using Earth System Models (ESMs) to simulate the impacts of global greenhouse gases (GHGs) emissions on the planetary climate system. This effort gathers results from multiple models developped by different international research groups and compares simulation results in order to estimate the range of variability in the global climate system and its potential response to various natural and anthropogenic GHG forcings<ref>Meehl, G. A., G. J. Boer, C. Covey, M. Latif, and R. J. Stouffer (1997), Intercomparison makes for a better climate model, Eos Trans. AGU, 78(41), 445–451, doi:10.1029/97EO00276. </ref>. <br />
<br />
In order to allow an effective assessment of scientific results, common simulation setups are chosen for all models participating in CMIP exercises. All the ESMs contributing to CMIP simulate the global climate response to common GHG forcings and scenarios. Since the first phase of CMIP (CMIP1), various scenarios for GHG emissions have been developped and many models and research groups have joined the effort. From 18 global coupled models in CMIP1 simulating a single scenario of 1%/year increase in CO2 global emissions, there are now over 30 research groups involved, simulating multiple climate forcing parameter changes. <br />
<br />
== Scales of interest ==<br />
CMIP excercises typically simulate the Earth climate at the global scale. Regional analyses are also included. The temporal scales are typically interannual to decadal to centennial. <br />
<br />
== Data inputs ==<br />
Since CMIP6, the common datasets for forcing the models include: <br />
* Historical Short-Lived Climate Forcers (SLCF) and greenhouse gas (CO2 and CH4) Emissions<br />
* Biomass Burning Emissions<br />
* Global Gridded Land-use Forcing Datasets<br />
* Historical greenhouse gases concentrations: a full description is published via the CMIP6 Special Issue publication (https://gmd.copernicus.org/articles/special_issue590.html)<br />
* Ozone Concentrations and Nitrogen (N)-Deposition <ref> Checa-Garcia, R., Hegglin, M. I., Kinnison, D., Plummer, D. A., & Shine, K. P. (2018). Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264–3273. https://doi.org/10.1002/2017GL076770</ref><br />
* Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration <ref>Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017 </ref><br />
* Solar Forcing <ref> Matthes, K.; Funke, B.; Andersson, M. E.; Barnard, L.; Beer, J.; Charbonneau, P.; Clilverd, M. A.; Dudok de Wit, T.; Haberreiter, M. (2017-06-22). "Solar forcing for CMIP6 (v3.2)". Geosci. Model Dev. 10 (6): 2247–2302</ref><br />
* Stratospheric Aerosol Data Set<br />
* AMIP Sea Surface Temperature and Sea Ice Datasets<br />
* Shared Socioeconomic Pathways (SSPs) for simulating future trends in GHG emissions <ref>O'Neill, B. C.; Tebaldi, C.; van Vuuren, D. P.; Eyring, V.; Friedlingstein, P.; Hurtt, G.; Knutti, R.; Kriegler, E.; Lamarque, J.-F. (2016-09-28). "The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6". Geosci. Model Dev. 9 (9): 3461–3482 </ref><br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
Beyond CMIP, each component of ESMs (ocean, atmosphere, ice...) has had an intercomparison exercise (AeroMIP, OMIP....). <br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
The increased complexity of models associated with higher resolution and the number of simulations required for CMIP exercises leads to a significant increase in computing and data storage requirements. <br />
<br />
== References ==<br />
<br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PISCES&diff=597PISCES2026-03-24T10:34:37Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[User:CamRichon|Camille Richon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:CamRichon|Camille Richon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: daily to yearly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
Several versions of PISCES have been developped to address specific research questions. <br />
The verified versions (with public distribution of the codes) currently include: <br />
* PISCES-gas which models the cycle of additional compounds emitted to the atmosphere such as N2O, DMS and CO (Conte et al., 2019 ; Séférian et al., 2020 ; Conte et al., 2020, Berthet et al., 2023)<ref>Conte, L., Szopa, S., Séférian, R., and Bopp, L.: The oceanic cycle of carbon monoxide and its emissions to the atmosphere, Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, 2019</ref><ref> Conte, L., Szopa, S., Aumont, O., Gros, V., & Bopp, L. (2020). Sources and sinks of isoprene in the global open ocean: Simulated patterns and emissions to the atmosphere. Journal of Geophysical Research: Oceans, 125, e2019JC015946. https://doi.org/10.1029/2019JC015946</ref><ref> Séférian, Roland; Berthet, Sarah; Yool, Andrew; Palmiéri, Julien; Bopp, Laurent; Tagliabue, Alessandro; Kwiatkowski, Lester; Aumont, Olivier; Christian, James; Dunne, John; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Li, Hongmei; Long, Matthew C; Luo, Jessica Y; Nakano, Hideyuki; Romanou, Anastasia; Schwinger, Jörg; Stock, Charles; Santana-Falcón, Yeray; Takano, Yohei; Tjiputra, Jerry; Tsujino, Hiroyuki; Watanabe, Michio; Wu, Tongwen; Wu, Fanghua; Yamamoto, Akitomo <br />
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, vol. 6, no. 3, pp. 95-119, 2020, ISSN: 2198-6061 </ref><ref> Berthet, S.; Jouanno, J.; Séférian, R.; Gehlen, M.; Llovel, W.<br />
How does the phytoplankton–light feedback affect the marine N2O inventory? Earth System Dynamics, vol. 14, no. 2, pp. 399–412, 2023 </ref>.<br />
<br />
* PISCES-iso which represents 13C and 15N (Buchanan et al., 2021)<ref> Buchanan, Pearse J; Aumont, Olivier; Bopp, Laurent; Mahaffey, Claire; Tagliabue, Alessandro Impact of intensifying nitrogen limitation on ocean net primary production is fingerprinted by nitrogen isotopes, Nature Communications, vol. 12, no. 1, pp. 6214, 2021.</ref><br />
<br />
* PISCES-Byonic which in addition to Fe, describes the cycles of the trace metals Co, Zn Mn and Cu (Tagliabue et al., 2018 ; Weber et al., 2018 ; Richon and Tagliabue, 2019, 2021)<ref> Tagliabue, A., Hawco, N. J., Bundy, R. M., Landing, W. M., Milne, A., Morton, P. L., & Saito, M. A. (2018). The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: Insights from the first cobalt biogeochemical model. Global Biogeochemical Cycles, 32, 594–616. https://doi.org/10.1002/2017GB005830 </ref><ref> Richon, C., & Tagliabue, A. (2021). Biogeochemical feedbacks associated with the response of micronutrient recycling by zooplankton to climate change. Global Change Biology, 27, 4758–4770. https://doi.org/10.1111/gcb.15789</ref><ref> Richon, C., & Tagliabue, A. (2019). Insights into the major processes driving the global distribution of copper in the ocean from a global model. Global Biogeochemical Cycles, 33, 1594–1610. https://doi.org/10.1029/2019GB006280</ref>.<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Zooplankton&diff=596Zooplankton2026-03-24T10:33:51Z<p>CamRichon: Undo revision 595 by CamRichon (talk)</p>
<hr />
<div><br />
* [[Page authors|Page authors]]: [[User:CamRichon|Camille Richon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:CamRichon|Camille Richon]]<br />
<br />
== Conceptual definition ==<br />
Zooplankton are secondary producers and form the base of many ocean food webs. They are composed of thousands of species from different taxa, encompassing all animals unable to swim against currents. They span a large size range from invisible larvae and animals (a few µm) to macrozooplankton (e.g. Jellyfish). <br />
<br />
Zooplankton play a fundamental role for ocean's ecological and biogeochemical equilibrium. As primary consumers, they regulate phytoplankton biomass and play a major role in blooms phenology. Additionally, they are key players in nutrient cycling and carbon export. Thus, zooplankton can be seen as a key link between lower and higher trophics levels, as well as between the surface and the deep ocean. <br />
<br />
== Subfield notes ==<br />
=== Experimental ===<br />
<br />
=== Models ===<br />
In biogeochemical models, zooplankton is often represented using one or two size classes. Some models may represent up to a dozen size classes (Clerc et al., 2023, Ward et al., 2012)<ref> Clerc, C., Bopp, L., Benedetti, F., Knecht, N., Vogt, M., & Aumont, O. (2024). Effects of mesozooplankton growth and reproduction on plankton and organic carbon dynamics in a marine biogeochemical model. Global Biogeochemical Cycles, 38, e2024GB008153. https://doi.org/10.1029/2024GB008153 </ref><ref>Ward B. A. , Dutkiewicz S. , Jahn O. , Follows M. J. , (2012), A size-structured food-web model for the global ocean, Limnology and Oceanography, 57, doi: 10.4319/lo.2012.57.6.1877</ref>.<br />
<br />
Specific habitat models exist for some species or clades (Benedetti et al., 2021)<ref>Benedetti, F., Vogt, M., Elizondo, U.H. et al. Major restructuring of marine plankton assemblages under global warming. Nat Commun 12, 5226 (2021). https://doi.org/10.1038/s41467-021-25385-x</ref>.<br />
<br />
== References ==<br />
<references /><br />
<br />
[[Category:Lexicon]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Zooplankton&diff=595Zooplankton2026-03-24T10:32:47Z<p>CamRichon: </p>
<hr />
<div><br />
<br />
<br />
== Conceptual definition ==<br />
Zooplankton are secondary producers and form the base of many ocean food webs. They are composed of thousands of species from different taxa, encompassing all animals unable to swim against currents. They span a large size range from invisible larvae and animals (a few µm) to macrozooplankton (e.g. Jellyfish). <br />
<br />
Zooplankton play a fundamental role for ocean's ecological and biogeochemical equilibrium. As primary consumers, they regulate phytoplankton biomass and play a major role in blooms phenology. Additionally, they are key players in nutrient cycling and carbon export. Thus, zooplankton can be seen as a key link between lower and higher trophics levels, as well as between the surface and the deep ocean. <br />
<br />
== Subfield notes ==<br />
=== Experimental ===<br />
<br />
=== Models ===<br />
In biogeochemical models, zooplankton is often represented using one or two size classes. Some models may represent up to a dozen size classes (Clerc et al., 2023, Ward et al., 2012)<ref> Clerc, C., Bopp, L., Benedetti, F., Knecht, N., Vogt, M., & Aumont, O. (2024). Effects of mesozooplankton growth and reproduction on plankton and organic carbon dynamics in a marine biogeochemical model. Global Biogeochemical Cycles, 38, e2024GB008153. https://doi.org/10.1029/2024GB008153 </ref><ref>Ward B. A. , Dutkiewicz S. , Jahn O. , Follows M. J. , (2012), A size-structured food-web model for the global ocean, Limnology and Oceanography, 57, doi: 10.4319/lo.2012.57.6.1877</ref>.<br />
<br />
Specific habitat models exist for some species or clades (Benedetti et al., 2021)<ref>Benedetti, F., Vogt, M., Elizondo, U.H. et al. Major restructuring of marine plankton assemblages under global warming. Nat Commun 12, 5226 (2021). https://doi.org/10.1038/s41467-021-25385-x</ref>.<br />
<br />
== References ==<br />
<references /><br />
<br />
[[Category:Lexicon]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Mixotrophy&diff=558Mixotrophy2026-02-18T13:29:57Z<p>CamRichon: </p>
<hr />
<div><br />
[[Category:Lexicon]]<br />
<br />
See also<br />
*[[LysoTracker Green Incorporation]]<br />
*[[15N/13C-labelled DOM/cells]]<br />
*[[Bead consumption rates by cells with chloroplasts]]<br />
*[[BrdU-labeled prey incorporation into things with chloroplasts]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Zooplankton&diff=557Zooplankton2026-02-18T13:27:11Z<p>CamRichon: /* Models */</p>
<hr />
<div><br />
* [[Page authors|Page authors]]: [[User:CamRichon|Camille Richon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
<br />
== Conceptual definition ==<br />
Zooplankton are secondary producers and form the base of many ocean food webs. They are composed of thousands of species from different taxa, encompassing all animals unable to swim against currents. They span a large size range from invisible larvae and animals (a few µm) to macrozooplankton (e.g. Jellyfish). <br />
<br />
Zooplankton play a fundamental role for ocean's ecological and biogeochemical equilibrium. As primary consumers, they regulate phytoplankton biomass and play a major role in blooms phenology. Additionally, they are key players in nutrient cycling and carbon export. Thus, zooplankton can be seen as a key link between lower and higher trophics levels, as well as between the surface and the deep ocean. <br />
<br />
== Subfield notes ==<br />
=== Experimental ===<br />
<br />
=== Models ===<br />
In biogeochemical models, zooplankton is often represented using one or two size classes. Some models may represent up to a dozen size classes (Clerc et al., 2023, Ward et al., 2012)<ref> Clerc, C., Bopp, L., Benedetti, F., Knecht, N., Vogt, M., & Aumont, O. (2024). Effects of mesozooplankton growth and reproduction on plankton and organic carbon dynamics in a marine biogeochemical model. Global Biogeochemical Cycles, 38, e2024GB008153. https://doi.org/10.1029/2024GB008153 </ref><ref>Ward B. A. , Dutkiewicz S. , Jahn O. , Follows M. J. , (2012), A size-structured food-web model for the global ocean, Limnology and Oceanography, 57, doi: 10.4319/lo.2012.57.6.1877</ref>.<br />
<br />
Specific habitat models exist for some species or clades (Benedetti et al., 2021)<ref>Benedetti, F., Vogt, M., Elizondo, U.H. et al. Major restructuring of marine plankton assemblages under global warming. Nat Commun 12, 5226 (2021). https://doi.org/10.1038/s41467-021-25385-x</ref>.<br />
<br />
== References ==<br />
<references /><br />
<br />
[[Category:Lexicon]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Bacteria&diff=556Bacteria2026-02-18T13:18:19Z<p>CamRichon: Created page with "Important things to know Category:Lexicon"</p>
<hr />
<div>Important things to know<br />
<br />
<br />
[[Category:Lexicon]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=User:CamRichon&diff=555User:CamRichon2026-02-18T13:16:09Z<p>CamRichon: </p>
<hr />
<div>camille.richon@univ-brest.fr<br />
<br />
https://orcid.org/0000-0001-7097-7173<br />
<br />
https://crichon-lemar.github.io/camillerichon/</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=User:CamRichon&diff=554User:CamRichon2026-02-18T13:15:55Z<p>CamRichon: </p>
<hr />
<div>camille.richon@univ-brest.fr<br />
https://orcid.org/0000-0001-7097-7173<br />
https://crichon-lemar.github.io/camillerichon/</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=User:CamRichon&diff=553User:CamRichon2026-02-18T13:13:24Z<p>CamRichon: Created page with "camille.richon@univ-brest.fr"</p>
<hr />
<div>camille.richon@univ-brest.fr</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Zooplankton&diff=552Zooplankton2026-02-18T12:58:12Z<p>CamRichon: </p>
<hr />
<div><br />
* [[Page authors|Page authors]]: [[User:CamRichon|Camille Richon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
<br />
== Conceptual definition ==<br />
Zooplankton are secondary producers and form the base of many ocean food webs. They are composed of thousands of species from different taxa, encompassing all animals unable to swim against currents. They span a large size range from invisible larvae and animals (a few µm) to macrozooplankton (e.g. Jellyfish). <br />
<br />
Zooplankton play a fundamental role for ocean's ecological and biogeochemical equilibrium. As primary consumers, they regulate phytoplankton biomass and play a major role in blooms phenology. Additionally, they are key players in nutrient cycling and carbon export. Thus, zooplankton can be seen as a key link between lower and higher trophics levels, as well as between the surface and the deep ocean. <br />
<br />
== Subfield notes ==<br />
=== Experimental ===<br />
<br />
=== Models ===<br />
<br />
<br />
== References ==<br />
<references /><br />
<br />
[[Category:Lexicon]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PISCES&diff=551PISCES2026-02-18T12:30:26Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: daily to yearly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
Several versions of PISCES have been developped to address specific research questions. <br />
The verified versions (with public distribution of the codes) currently include: <br />
* PISCES-gas which models the cycle of additional compounds emitted to the atmosphere such as N2O, DMS and CO (Conte et al., 2019 ; Séférian et al., 2020 ; Conte et al., 2020, Berthet et al., 2023)<ref>Conte, L., Szopa, S., Séférian, R., and Bopp, L.: The oceanic cycle of carbon monoxide and its emissions to the atmosphere, Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, 2019</ref><ref> Conte, L., Szopa, S., Aumont, O., Gros, V., & Bopp, L. (2020). Sources and sinks of isoprene in the global open ocean: Simulated patterns and emissions to the atmosphere. Journal of Geophysical Research: Oceans, 125, e2019JC015946. https://doi.org/10.1029/2019JC015946</ref><ref> Séférian, Roland; Berthet, Sarah; Yool, Andrew; Palmiéri, Julien; Bopp, Laurent; Tagliabue, Alessandro; Kwiatkowski, Lester; Aumont, Olivier; Christian, James; Dunne, John; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Li, Hongmei; Long, Matthew C; Luo, Jessica Y; Nakano, Hideyuki; Romanou, Anastasia; Schwinger, Jörg; Stock, Charles; Santana-Falcón, Yeray; Takano, Yohei; Tjiputra, Jerry; Tsujino, Hiroyuki; Watanabe, Michio; Wu, Tongwen; Wu, Fanghua; Yamamoto, Akitomo <br />
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, vol. 6, no. 3, pp. 95-119, 2020, ISSN: 2198-6061 </ref><ref> Berthet, S.; Jouanno, J.; Séférian, R.; Gehlen, M.; Llovel, W.<br />
How does the phytoplankton–light feedback affect the marine N2O inventory? Earth System Dynamics, vol. 14, no. 2, pp. 399–412, 2023 </ref>.<br />
<br />
* PISCES-iso which represents 13C and 15N (Buchanan et al., 2021)<ref> Buchanan, Pearse J; Aumont, Olivier; Bopp, Laurent; Mahaffey, Claire; Tagliabue, Alessandro Impact of intensifying nitrogen limitation on ocean net primary production is fingerprinted by nitrogen isotopes, Nature Communications, vol. 12, no. 1, pp. 6214, 2021.</ref><br />
<br />
* PISCES-Byonic which in addition to Fe, describes the cycles of the trace metals Co, Zn Mn and Cu (Tagliabue et al., 2018 ; Weber et al., 2018 ; Richon and Tagliabue, 2019, 2021)<ref> Tagliabue, A., Hawco, N. J., Bundy, R. M., Landing, W. M., Milne, A., Morton, P. L., & Saito, M. A. (2018). The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: Insights from the first cobalt biogeochemical model. Global Biogeochemical Cycles, 32, 594–616. https://doi.org/10.1002/2017GB005830 </ref><ref> Richon, C., & Tagliabue, A. (2021). Biogeochemical feedbacks associated with the response of micronutrient recycling by zooplankton to climate change. Global Change Biology, 27, 4758–4770. https://doi.org/10.1111/gcb.15789</ref><ref> Richon, C., & Tagliabue, A. (2019). Insights into the major processes driving the global distribution of copper in the ocean from a global model. Global Biogeochemical Cycles, 33, 1594–1610. https://doi.org/10.1029/2019GB006280</ref>.<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=CMIP&diff=535CMIP2026-02-12T14:38:17Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic<br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Spatial resolution:''' grid: 2°, 1° since CMIP6, domain: global<br />
|-<br />
| '''Temporal resolution:''' time step: model dependent, usually s to hours ; output: yearly to monthly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
The Coupled Model Intercomparison Project (CMIP) is a global effort from the international research community using Earth System Models (ESMs) to simulate the impacts of global greenhouse gases (GHGs) emissions on the planetary climate system. This effort gathers results from multiple models developped by different international research groups and compares simulation results in order to estimate the range of variability in the global climate system and its potential response to various natural and anthropogenic GHG forcings<ref>Meehl, G. A., G. J. Boer, C. Covey, M. Latif, and R. J. Stouffer (1997), Intercomparison makes for a better climate model, Eos Trans. AGU, 78(41), 445–451, doi:10.1029/97EO00276. </ref>. <br />
<br />
In order to allow an effective assessment of scientific results, common simulation setups are chosen for all models participating in CMIP exercises. All the ESMs contributing to CMIP simulate the global climate response to common GHG forcings and scenarios. Since the first phase of CMIP (CMIP1), various scenarios for GHG emissions have been developped and many models and research groups have joined the effort. From 18 global coupled models in CMIP1 simulating a single scenario of 1%/year increase in CO2 global emissions, there are now over 30 research groups involved, simulating multiple climate forcing parameter changes. <br />
<br />
== Scales of interest ==<br />
CMIP excercises typically simulate the Earth climate at the global scale. Regional analyses are also included. The temporal scales are typically interannual to decadal to centennial. <br />
<br />
== Data inputs ==<br />
Since CMIP6, the common datasets for forcing the models include: <br />
* Historical Short-Lived Climate Forcers (SLCF) and greenhouse gas (CO2 and CH4) Emissions<br />
* Biomass Burning Emissions<br />
* Global Gridded Land-use Forcing Datasets<br />
* Historical greenhouse gases concentrations: a full description is published via the CMIP6 Special Issue publication (https://gmd.copernicus.org/articles/special_issue590.html)<br />
* Ozone Concentrations and Nitrogen (N)-Deposition <ref> Checa-Garcia, R., Hegglin, M. I., Kinnison, D., Plummer, D. A., & Shine, K. P. (2018). Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264–3273. https://doi.org/10.1002/2017GL076770</ref><br />
* Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration <ref>Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017 </ref><br />
* Solar Forcing <ref> Matthes, K.; Funke, B.; Andersson, M. E.; Barnard, L.; Beer, J.; Charbonneau, P.; Clilverd, M. A.; Dudok de Wit, T.; Haberreiter, M. (2017-06-22). "Solar forcing for CMIP6 (v3.2)". Geosci. Model Dev. 10 (6): 2247–2302</ref><br />
* Stratospheric Aerosol Data Set<br />
* AMIP Sea Surface Temperature and Sea Ice Datasets<br />
* Shared Socioeconomic Pathways (SSPs) for simulating future trends in GHG emissions <ref>O'Neill, B. C.; Tebaldi, C.; van Vuuren, D. P.; Eyring, V.; Friedlingstein, P.; Hurtt, G.; Knutti, R.; Kriegler, E.; Lamarque, J.-F. (2016-09-28). "The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6". Geosci. Model Dev. 9 (9): 3461–3482 </ref><br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
Beyond CMIP, each component of ESMs (ocean, atmosphere, ice...) has had an intercomparison exercise (AeroMIP, OMIP....). <br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
The increased complexity of models associated with higher resolution and the number of simulations required for CMIP exercises leads to a significant increase in computing and data storage requirements. <br />
<br />
== References ==<br />
<br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=CMIP&diff=534CMIP2026-02-12T14:35:58Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic<br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Spatial resolution:''' grid: 2°, 1° since CMIP6, domain: global<br />
|-<br />
| '''Temporal resolution:''' time step: model dependent, usually s to hours ; output: yearly to monthly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
The Coupled Model Intercomparison Project (CMIP) is a global effort from the international research community using Earth System Models (ESMs) to simulate the impacts of global greenhouse gases (GHGs) emissions on the planetary climate system. This effort gathers results from multiple models developped by different international research groups and compares simulation results in order to estimate the range of variability in the global climate system and its potential response to various natural and anthropogenic GHG forcings. <br />
<br />
In order to allow an effective assessment of scientific results, common simulation setups are chosen for all models participating in CMIP exercises. All the ESMs contributing to CMIP simulate the global climate response to common GHG forcings and scenarios. Since the first phase of CMIP (CMIP1), various scenarios for GHG emissions have been developped and many models and research groups have joined the effort. From 18 global coupled models in CMIP1 simulating a single scenario of 1%/year increase in CO2 global emissions, there are now over 30 research groups involved, simulating multiple climate forcing parameter changes. <br />
<br />
== Scales of interest ==<br />
CMIP excercises typically simulate the Earth climate at the global scale. Regional analyses are also included. The temporal scales are typically interannual to decadal to centennial. <br />
<br />
== Data inputs ==<br />
Since CMIP6, the common datasets for forcing the models include: <br />
* Historical Short-Lived Climate Forcers (SLCF) and greenhouse gas (CO2 and CH4) Emissions<br />
* Biomass Burning Emissions<br />
* Global Gridded Land-use Forcing Datasets<br />
* Historical greenhouse gases concentrations: a full description is published via the CMIP6 Special Issue publication (https://gmd.copernicus.org/articles/special_issue590.html)<br />
* Ozone Concentrations and Nitrogen (N)-Deposition <ref> Checa-Garcia, R., Hegglin, M. I., Kinnison, D., Plummer, D. A., & Shine, K. P. (2018). Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264–3273. https://doi.org/10.1002/2017GL076770</ref><br />
* Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration <ref>Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017 </ref><br />
* Solar Forcing <ref> Matthes, K.; Funke, B.; Andersson, M. E.; Barnard, L.; Beer, J.; Charbonneau, P.; Clilverd, M. A.; Dudok de Wit, T.; Haberreiter, M. (2017-06-22). "Solar forcing for CMIP6 (v3.2)". Geosci. Model Dev. 10 (6): 2247–2302</ref><br />
* Stratospheric Aerosol Data Set<br />
* AMIP Sea Surface Temperature and Sea Ice Datasets<br />
* Shared Socioeconomic Pathways (SSPs) for simulating future trends in GHG emissions <ref>O'Neill, B. C.; Tebaldi, C.; van Vuuren, D. P.; Eyring, V.; Friedlingstein, P.; Hurtt, G.; Knutti, R.; Kriegler, E.; Lamarque, J.-F. (2016-09-28). "The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6". Geosci. Model Dev. 9 (9): 3461–3482 </ref><br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
Beyond CMIP, each component of ESMs (ocean, atmosphere, ice...) has had an intercomparison exercise (AeroMIP, OMIP....). <br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
The increased complexity of models associated with higher resolution and the number of simulations required for CMIP exercises leads to a significant increase in computing and data storage requirements. <br />
<br />
== References ==<br />
<br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Talk:CMIP&diff=533Talk:CMIP2026-02-12T14:35:14Z<p>CamRichon: </p>
<hr />
<div>Some references missing<br />
Is it possible to add images? I think this schematics (https://wcrp-cmip.org/mips/cmip6-endorsed-mips/) is nice to explain all the "MIPs" that exist.</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Talk:CMIP&diff=532Talk:CMIP2026-02-12T14:32:04Z<p>CamRichon: Created page with "Some references missing"</p>
<hr />
<div>Some references missing</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=CMIP&diff=531CMIP2026-02-12T14:31:45Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic<br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Spatial resolution:''' grid: 2°, 1° since CMIP6, domain: global<br />
|-<br />
| '''Temporal resolution:''' time step: model dependent, usually s to hours ; output: yearly to monthly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
The Coupled Model Intercomparison Project (CMIP) is a global effort from the international research community using Earth System Models (ESMs) to simulate the impacts of global greenhouse gases (GHGs) emissions on the planetary climate system. This effort gathers results from multiple models developped by different international research groups and compares simulation results in order to estimate the range of variability in the global climate system and its potential response to various natural and anthropogenic GHG forcings. <br />
<br />
In order to allow an effective assessment of scientific results, common simulation setups are chosen for all models participating in CMIP exercises. All the ESMs contributing to CMIP simulate the global climate response to common GHG forcings and scenarios. Since the first phase of CMIP (CMIP1), various scenarios for GHG emissions have been developped and many models and research groups have joined the effort. From 18 global coupled models in CMIP1 simulating a single scenario of 1%/year increase in CO2 global emissions, there are now over 30 research groups involved, simulating multiple climate forcing parameter changes. <br />
<br />
== Scales of interest ==<br />
CMIP excercises typically simulate the Earth climate at the global scale. Regional analyses are also included. The temporal scales are typically interannual to decadal to centennial. <br />
<br />
== Data inputs ==<br />
Since CMIP6, the common datasets for forcing the models include: <br />
* Historical Short-Lived Climate Forcers (SLCF) and greenhouse gas (CO2 and CH4) Emissions<br />
* Biomass Burning Emissions<br />
* Global Gridded Land-use Forcing Datasets<br />
* Historical greenhouse gases concentrations: a full description is published via the CMIP6 Special Issue publication (https://gmd.copernicus.org/articles/special_issue590.html)<br />
* Ozone Concentrations and Nitrogen (N)-Deposition <ref> Checa-Garcia, R., Hegglin, M. I., Kinnison, D., Plummer, D. A., & Shine, K. P. (2018). Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264–3273. https://doi.org/10.1002/2017GL076770</ref><br />
* Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration <ref>Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017 </ref><br />
* Solar Forcing <ref> Matthes, K.; Funke, B.; Andersson, M. E.; Barnard, L.; Beer, J.; Charbonneau, P.; Clilverd, M. A.; Dudok de Wit, T.; Haberreiter, M. (2017-06-22). "Solar forcing for CMIP6 (v3.2)". Geosci. Model Dev. 10 (6): 2247–2302</ref><br />
* Stratospheric Aerosol Data Set<br />
* AMIP Sea Surface Temperature and Sea Ice Datasets<br />
* Shared Socioeconomic Pathways (SSPs) for simulating future trends in GHG emissions <ref>O'Neill, B. C.; Tebaldi, C.; van Vuuren, D. P.; Eyring, V.; Friedlingstein, P.; Hurtt, G.; Knutti, R.; Kriegler, E.; Lamarque, J.-F. (2016-09-28). "The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6". Geosci. Model Dev. 9 (9): 3461–3482 </ref><br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=CMIP&diff=530CMIP2026-02-12T14:30:56Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsGlobal}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]|Camille Richon]<br />
* [[Responsible curator|Responsible curator]]: [[User:]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic<br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Spatial resolution:''' grid: 2°, 1° since CMIP6, domain: global<br />
|-<br />
| '''Temporal resolution:''' time step: model dependent, usually s to hours ; output: yearly to monthly<br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
The Coupled Model Intercomparison Project (CMIP) is a global effort from the international research community using Earth System Models (ESMs) to simulate the impacts of global greenhouse gases (GHGs) emissions on the planetary climate system. This effort gathers results from multiple models developped by different international research groups and compares simulation results in order to estimate the range of variability in the global climate system and its potential response to various natural and anthropogenic GHG forcings. <br />
<br />
In order to allow an effective assessment of scientific results, common simulation setups are chosen for all models participating in CMIP exercises. All the ESMs contributing to CMIP simulate the global climate response to common GHG forcings and scenarios. Since the first phase of CMIP (CMIP1), various scenarios for GHG emissions have been developped and many models and research groups have joined the effort. From 18 global coupled models in CMIP1 simulating a single scenario of 1%/year increase in CO2 global emissions, there are now over 30 research groups involved, simulating multiple climate forcing parameter changes. <br />
<br />
== Scales of interest ==<br />
CMIP excercises typically simulate the Earth climate at the global scale. Regional analyses are also included. The temporal scales are typically interannual to decadal to centennial. <br />
<br />
== Data inputs ==<br />
Since CMIP6, the common datasets for forcing the models include: <br />
* Historical Short-Lived Climate Forcers (SLCF) and greenhouse gas (CO2 and CH4) Emissions<br />
* Biomass Burning Emissions<br />
* Global Gridded Land-use Forcing Datasets<br />
* Historical greenhouse gases concentrations: a full description is published via the CMIP6 Special Issue publication (https://gmd.copernicus.org/articles/special_issue590.html)<br />
* Ozone Concentrations and Nitrogen (N)-Deposition <ref> Checa-Garcia, R., Hegglin, M. I., Kinnison, D., Plummer, D. A., & Shine, K. P. (2018). Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database. Geophysical Research Letters, 45, 3264–3273. https://doi.org/10.1002/2017GL076770</ref><br />
* Aerosol Optical Properties and Relative Change in Cloud Droplet Number Concentration <ref>Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017 </ref><br />
* Solar Forcing <ref> Matthes, K.; Funke, B.; Andersson, M. E.; Barnard, L.; Beer, J.; Charbonneau, P.; Clilverd, M. A.; Dudok de Wit, T.; Haberreiter, M. (2017-06-22). "Solar forcing for CMIP6 (v3.2)". Geosci. Model Dev. 10 (6): 2247–2302</ref><br />
* Stratospheric Aerosol Data Set<br />
* AMIP Sea Surface Temperature and Sea Ice Datasets<br />
* Shared Socioeconomic Pathways (SSPs) for simulating future trends in GHG emissions <ref>O'Neill, B. C.; Tebaldi, C.; van Vuuren, D. P.; Eyring, V.; Friedlingstein, P.; Hurtt, G.; Knutti, R.; Kriegler, E.; Lamarque, J.-F. (2016-09-28). "The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6". Geosci. Model Dev. 9 (9): 3461–3482 </ref><br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PISCES&diff=529PISCES2026-02-12T14:08:29Z<p>CamRichon: Created page with "{{BreadcrumbsCellular}} * Page authors: CamRichon * Responsible curator: CamRichon ---- __TOC__ <div class="model-box"> {| class="model-ib" ! Model type |- | '''Approach:''' Mechanistic |- | '''Computational demand:''' HPC |- | '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° |- | '''Appropriate timescales:''' time step: typically around 1400-540..."</p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
Several versions of PISCES have been developped to address specific research questions. <br />
The verified versions (with public distribution of the codes) currently include: <br />
* PISCES-gas which models the cycle of additional compounds emitted to the atmosphere such as N2O, DMS and CO (Conte et al., 2019 ; Séférian et al., 2020 ; Conte et al., 2020, Berthet et al., 2023)<ref>Conte, L., Szopa, S., Séférian, R., and Bopp, L.: The oceanic cycle of carbon monoxide and its emissions to the atmosphere, Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, 2019</ref><ref> Conte, L., Szopa, S., Aumont, O., Gros, V., & Bopp, L. (2020). Sources and sinks of isoprene in the global open ocean: Simulated patterns and emissions to the atmosphere. Journal of Geophysical Research: Oceans, 125, e2019JC015946. https://doi.org/10.1029/2019JC015946</ref><ref> Séférian, Roland; Berthet, Sarah; Yool, Andrew; Palmiéri, Julien; Bopp, Laurent; Tagliabue, Alessandro; Kwiatkowski, Lester; Aumont, Olivier; Christian, James; Dunne, John; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Li, Hongmei; Long, Matthew C; Luo, Jessica Y; Nakano, Hideyuki; Romanou, Anastasia; Schwinger, Jörg; Stock, Charles; Santana-Falcón, Yeray; Takano, Yohei; Tjiputra, Jerry; Tsujino, Hiroyuki; Watanabe, Michio; Wu, Tongwen; Wu, Fanghua; Yamamoto, Akitomo <br />
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, vol. 6, no. 3, pp. 95-119, 2020, ISSN: 2198-6061 </ref><ref> Berthet, S.; Jouanno, J.; Séférian, R.; Gehlen, M.; Llovel, W.<br />
How does the phytoplankton–light feedback affect the marine N2O inventory? Earth System Dynamics, vol. 14, no. 2, pp. 399–412, 2023 </ref>.<br />
<br />
* PISCES-iso which represents 13C and 15N (Buchanan et al., 2021)<ref> Buchanan, Pearse J; Aumont, Olivier; Bopp, Laurent; Mahaffey, Claire; Tagliabue, Alessandro Impact of intensifying nitrogen limitation on ocean net primary production is fingerprinted by nitrogen isotopes, Nature Communications, vol. 12, no. 1, pp. 6214, 2021.</ref><br />
<br />
* PISCES-Byonic which in addition to Fe, describes the cycles of the trace metals Co, Zn Mn and Cu (Tagliabue et al., 2018 ; Weber et al., 2018 ; Richon and Tagliabue, 2019, 2021)<ref> Tagliabue, A., Hawco, N. J., Bundy, R. M., Landing, W. M., Milne, A., Morton, P. L., & Saito, M. A. (2018). The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: Insights from the first cobalt biogeochemical model. Global Biogeochemical Cycles, 32, 594–616. https://doi.org/10.1002/2017GB005830 </ref><ref> Richon, C., & Tagliabue, A. (2021). Biogeochemical feedbacks associated with the response of micronutrient recycling by zooplankton to climate change. Global Change Biology, 27, 4758–4770. https://doi.org/10.1111/gcb.15789</ref><ref> Richon, C., & Tagliabue, A. (2019). Insights into the major processes driving the global distribution of copper in the ocean from a global model. Global Biogeochemical Cycles, 33, 1594–1610. https://doi.org/10.1029/2019GB006280</ref>.<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Model_Types&diff=528Model Types2026-02-12T14:08:08Z<p>CamRichon: /* Global scale */</p>
<hr />
<div>Models integrate our understanding of ocean carbon cycling, proposing hypothesized mechanisms and trade-offs, and generating predictions. Biogeochemical models represent the conversion of elements, such as carbon, nitrogen, and phosphorus, from inorganic substrates to organic compounds through photosynthesis by phytoplankton and ultimately back into inorganic form through heterotrophic activity. For each of the model pools, a set of equations express how the pool changes over time, describing our best understanding of the dynamics at play in the physics, biogeochemistry, and ecology of the ocean. The ecosystem and biogeochemical components are derived from food web models, and are embedded into physical fluid dynamic models that represent the transport and conservation of water, salt, and heat, as well as carbon, nutrients, and plankton. Thus, ocean biogeochemical models inherently account for interactions between marine organisms and the dynamic fluid environment in which they live<ref name="Levine et al. 2025>Naomi M. Levine, Harriet Alexander, Erin M. Bertrand, Victoria J. Coles, Stephanie Dutkiewicz, Suzana G. Leles and Emily J. Zakem. 2025. Microbial Ecology to Ocean Carbon Cycling: From Genomes to Numerical Models.Annual Review of Earth and Planetary Science, Vol. 53:595-624, https://doi.org/10.1146/annurev-earth-040523-020630</ref>.<br><br />
Current state-of-the-art models represent a range of different microbial functional types including multiple phytoplankton groups, mixotrophs, grazers, viruses, detrital pools, and bacteria and archaea that consume the dead organic matter<ref>Follows MJ, Dutkiewicz S, Ward B, Follett CN. 2018. Theoretical interpretations of subtropical plankton biogeography. In Microbial Ecology of the Oceans, ed. JM Gasol, DL Kirchman , pp. 467–94. Hoboken, NJ:: Wiley & Sons, http://ndl.ethernet.edu.et/bitstream/123456789/33641/1/pdf.52#page=484</ref>.<br />
<br />
If you would like to add a model type page, please use the [[Model wiki template | Model wiki template]].<br />
<br />
=== Cellular scale ===<br />
<br />
*[[Flux Balance Analysis]] <span style="color: red;">- needs creation</span><br />
*[[Proteome Allocation Models]]<br />
*[[Particle Simulation]] <span style="color: red;">- needs creation</span><br />
*[[Bio Particle Simulation]] <span style="color: red;">- needs creation</span><br />
<br />
=== Biome scale ===<br />
<br />
*[[Community Flux Balance Analysis]] <span style="color: red;">- needs creation</span><br />
*[[GENOME]] <span style="color: red;">- needs creation</span><br />
<br />
=== Global scale ===<br />
<br />
*[[CMIP]] <span style="color: red;">- needs creation</span><br />
*[[MARBL]] <span style="color: red;">- needs creation</span><br />
*[[Darwin]] <span style="color: red;">- needs creation</span><br />
*[[AWESOME-OCIM]] <span style="color: red;">-needs creation</span><br />
*[[PISCES]]<br />
<br />
== References ==<br />
<references /></div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Model_Types&diff=527Model Types2026-02-12T14:04:24Z<p>CamRichon: /* Global scale */</p>
<hr />
<div>Models integrate our understanding of ocean carbon cycling, proposing hypothesized mechanisms and trade-offs, and generating predictions. Biogeochemical models represent the conversion of elements, such as carbon, nitrogen, and phosphorus, from inorganic substrates to organic compounds through photosynthesis by phytoplankton and ultimately back into inorganic form through heterotrophic activity. For each of the model pools, a set of equations express how the pool changes over time, describing our best understanding of the dynamics at play in the physics, biogeochemistry, and ecology of the ocean. The ecosystem and biogeochemical components are derived from food web models, and are embedded into physical fluid dynamic models that represent the transport and conservation of water, salt, and heat, as well as carbon, nutrients, and plankton. Thus, ocean biogeochemical models inherently account for interactions between marine organisms and the dynamic fluid environment in which they live<ref name="Levine et al. 2025>Naomi M. Levine, Harriet Alexander, Erin M. Bertrand, Victoria J. Coles, Stephanie Dutkiewicz, Suzana G. Leles and Emily J. Zakem. 2025. Microbial Ecology to Ocean Carbon Cycling: From Genomes to Numerical Models.Annual Review of Earth and Planetary Science, Vol. 53:595-624, https://doi.org/10.1146/annurev-earth-040523-020630</ref>.<br><br />
Current state-of-the-art models represent a range of different microbial functional types including multiple phytoplankton groups, mixotrophs, grazers, viruses, detrital pools, and bacteria and archaea that consume the dead organic matter<ref>Follows MJ, Dutkiewicz S, Ward B, Follett CN. 2018. Theoretical interpretations of subtropical plankton biogeography. In Microbial Ecology of the Oceans, ed. JM Gasol, DL Kirchman , pp. 467–94. Hoboken, NJ:: Wiley & Sons, http://ndl.ethernet.edu.et/bitstream/123456789/33641/1/pdf.52#page=484</ref>.<br />
<br />
If you would like to add a model type page, please use the [[Model wiki template | Model wiki template]].<br />
<br />
=== Cellular scale ===<br />
<br />
*[[Flux Balance Analysis]] <span style="color: red;">- needs creation</span><br />
*[[Proteome Allocation Models]]<br />
*[[Particle Simulation]] <span style="color: red;">- needs creation</span><br />
*[[Bio Particle Simulation]] <span style="color: red;">- needs creation</span><br />
<br />
=== Biome scale ===<br />
<br />
*[[Community Flux Balance Analysis]] <span style="color: red;">- needs creation</span><br />
*[[GENOME]] <span style="color: red;">- needs creation</span><br />
<br />
=== Global scale ===<br />
<br />
*[[CMIP]] <span style="color: red;">- needs creation</span><br />
*[[MARBL]] <span style="color: red;">- needs creation</span><br />
*[[Darwin]] <span style="color: red;">- needs creation</span><br />
*[[AWESOME-OCIM]] <span style="color: red;">-needs creation</span><br />
*[[PICES]]<br />
<br />
== References ==<br />
<references /></div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=526PICES2026-02-12T13:52:28Z<p>CamRichon: /* Classic examples */</p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
Several versions of PISCES have been developped to address specific research questions. <br />
The verified versions (with public distribution of the codes) currently include: <br />
* PISCES-gas which models the cycle of additional compounds emitted to the atmosphere such as N2O, DMS and CO (Conte et al., 2019 ; Séférian et al., 2020 ; Conte et al., 2020, Berthet et al., 2023)<ref>Conte, L., Szopa, S., Séférian, R., and Bopp, L.: The oceanic cycle of carbon monoxide and its emissions to the atmosphere, Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, 2019</ref><ref> Conte, L., Szopa, S., Aumont, O., Gros, V., & Bopp, L. (2020). Sources and sinks of isoprene in the global open ocean: Simulated patterns and emissions to the atmosphere. Journal of Geophysical Research: Oceans, 125, e2019JC015946. https://doi.org/10.1029/2019JC015946</ref><ref> Séférian, Roland; Berthet, Sarah; Yool, Andrew; Palmiéri, Julien; Bopp, Laurent; Tagliabue, Alessandro; Kwiatkowski, Lester; Aumont, Olivier; Christian, James; Dunne, John; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Li, Hongmei; Long, Matthew C; Luo, Jessica Y; Nakano, Hideyuki; Romanou, Anastasia; Schwinger, Jörg; Stock, Charles; Santana-Falcón, Yeray; Takano, Yohei; Tjiputra, Jerry; Tsujino, Hiroyuki; Watanabe, Michio; Wu, Tongwen; Wu, Fanghua; Yamamoto, Akitomo <br />
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, vol. 6, no. 3, pp. 95-119, 2020, ISSN: 2198-6061 </ref><ref> Berthet, S.; Jouanno, J.; Séférian, R.; Gehlen, M.; Llovel, W.<br />
How does the phytoplankton–light feedback affect the marine N2O inventory? Earth System Dynamics, vol. 14, no. 2, pp. 399–412, 2023 </ref>.<br />
<br />
* PISCES-iso which represents 13C and 15N (Buchanan et al., 2021)<ref> Buchanan, Pearse J; Aumont, Olivier; Bopp, Laurent; Mahaffey, Claire; Tagliabue, Alessandro Impact of intensifying nitrogen limitation on ocean net primary production is fingerprinted by nitrogen isotopes, Nature Communications, vol. 12, no. 1, pp. 6214, 2021.</ref><br />
<br />
* PISCES-Byonic which in addition to Fe, describes the cycles of the trace metals Co, Zn Mn and Cu (Tagliabue et al., 2018 ; Weber et al., 2018 ; Richon and Tagliabue, 2019, 2021)<ref> Tagliabue, A., Hawco, N. J., Bundy, R. M., Landing, W. M., Milne, A., Morton, P. L., & Saito, M. A. (2018). The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: Insights from the first cobalt biogeochemical model. Global Biogeochemical Cycles, 32, 594–616. https://doi.org/10.1002/2017GB005830 </ref><ref> Richon, C., & Tagliabue, A. (2021). Biogeochemical feedbacks associated with the response of micronutrient recycling by zooplankton to climate change. Global Change Biology, 27, 4758–4770. https://doi.org/10.1111/gcb.15789</ref><ref> Richon, C., & Tagliabue, A. (2019). Insights into the major processes driving the global distribution of copper in the ocean from a global model. Global Biogeochemical Cycles, 33, 1594–1610. https://doi.org/10.1029/2019GB006280</ref>.<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=525PICES2026-02-12T13:49:46Z<p>CamRichon: /* Recent applications */</p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
Several versions of PISCES have been developped to address specific research questions. <br />
The verified versions (with public distribution of the codes) currently include: <br />
* PISCES-gas which models the cycle of additional compounds emitted to the atmosphere such as N2O, DMS and CO (Conte et al., 2019 ; Séférian et al., 2020 ; Conte et al., 2020, Berthet et al., 2023)<ref>Conte, L., Szopa, S., Séférian, R., and Bopp, L.: The oceanic cycle of carbon monoxide and its emissions to the atmosphere, Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, 2019</ref><ref> Conte, L., Szopa, S., Aumont, O., Gros, V., & Bopp, L. (2020). Sources and sinks of isoprene in the global open ocean: Simulated patterns and emissions to the atmosphere. Journal of Geophysical Research: Oceans, 125, e2019JC015946. https://doi.org/10.1029/2019JC015946</ref><ref> Séférian, Roland; Berthet, Sarah; Yool, Andrew; Palmiéri, Julien; Bopp, Laurent; Tagliabue, Alessandro; Kwiatkowski, Lester; Aumont, Olivier; Christian, James; Dunne, John; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Li, Hongmei; Long, Matthew C; Luo, Jessica Y; Nakano, Hideyuki; Romanou, Anastasia; Schwinger, Jörg; Stock, Charles; Santana-Falcón, Yeray; Takano, Yohei; Tjiputra, Jerry; Tsujino, Hiroyuki; Watanabe, Michio; Wu, Tongwen; Wu, Fanghua; Yamamoto, Akitomo <br />
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, vol. 6, no. 3, pp. 95-119, 2020, ISSN: 2198-6061 </ref><ref> Berthet, S.; Jouanno, J.; Séférian, R.; Gehlen, M.; Llovel, W.<br />
How does the phytoplankton–light feedback affect the marine N2O inventory? Earth System Dynamics, vol. 14, no. 2, pp. 399–412, 2023 </ref>.<br />
<br />
* PISCES-iso which represents 13C and 15N (Buchanan et al., 2021)<ref> Buchanan, Pearse J; Aumont, Olivier; Bopp, Laurent; Mahaffey, Claire; Tagliabue, Alessandro Impact of intensifying nitrogen limitation on ocean net primary production is fingerprinted by nitrogen isotopes, Nature Communications, vol. 12, no. 1, pp. 6214, 2021.</ref><br />
<br />
* PISCES-Byonic which in addition to Fe, describes the cycles of the trace metals Co, Zn Mn and Cu (Tagliabue et al., 2018 ; Weber et al., 2018 ; Richon and Tagliabue, 2019, 2021)<ref> Tagliabue, A., Hawco, N. J., Bundy, R. M., Landing, W. M., Milne, A., Morton, P. L., & Saito, M. A. (2018). The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: Insights from the first cobalt biogeochemical model. Global Biogeochemical Cycles, 32, 594–616. https://doi.org/10.1002/2017GB005830 </ref><ref> Richon, C., & Tagliabue, A. (2021). Biogeochemical feedbacks associated with the response of micronutrient recycling by zooplankton to climate change. Global Change Biology, 27, 4758–4770. https://doi.org/10.1111/gcb.15789</ref><ref> Richon, C., & Tagliabue, A. (2019). Insights into the major processes driving the global distribution of copper in the ocean from a global model. Global Biogeochemical Cycles, 33, 1594–1610. https://doi.org/10.1029/2019GB006280</ref>.<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=524PICES2026-02-12T13:32:45Z<p>CamRichon: /* Classic examples */</p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
The reference article describing the main features and parameters of the model is: Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015<br />
All informations on the latest developpements (including access to code) can be found at: https://www.pisces-community.org/<br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=523PICES2026-02-12T13:30:21Z<p>CamRichon: /* Scales of interest */</p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...)<ref> Santana-Falcón, Yeray; Mason, Evan; Arístegui, Javier <br />
Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Progress in Oceanography, vol. 186, pp. 102322, 2020, ISSN: 00796611.</ref><ref> Richon, Camille; Dutay, Jean-Claude; Dulac, François; Wang, Rong; Balkanski, Yves; Nabat, Pierre; Aumont, Olivier; Desboeufs, Karine; Laurent, Benoît; Guieu, Cécile; Raimbault, Patrick; Beuvier, Jonathan Modeling the Impacts of Atmospheric Deposition of Nitrogen and Desert Dust-Derived Phosphorus on Nutrients and Biological Budgets of the Mediterranean Sea, Progress in Oceanography, vol. 163, pp. 21–39, 2018. </ref>.<br />
<br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. distant past and futures)<ref> Sarr, A-C; Donnadieu, Yannick; Laugié, Marie; Ladant, J-B; Suchéras-Marx, Baptiste; Raisson, François Ventilation Changes Drive Orbital-Scale Deoxygenation Trends in the Late Cretaceous Ocean In: Geophysical Research Letters, vol. 49, no. 19, pp. e2022GL099830, 2022.</ref><ref> Kwiatkowski, Lester; Torres, Olivier; Bopp, Laurent; Aumont, Olivier; Chamberlain, Matthew; Christian, James R; Dunne, John P; Gehlen, Marion; Ilyina, Tatiana; John, Jasmin G; Lenton, Andrew; Li, Hongmei; Lovenduski, Nicole S; Orr, James C; Palmieri, Julien; Santana-Falcón, Yeray; Schwinger, Jörg; Séférian, Roland; Stock, Charles A; Tagliabue, Alessandro; Takano, Yohei; Tjiputra, Jerry; Toyama, Katsuya; Tsujino, Hiroyuki; Watanabe, Michio; Yamamoto, Akitomo; Yool, Andrew; Ziehn, Tilo <br />
Twenty-First Century Ocean Warming, Acidification, Deoxygenation, and Upper-Ocean Nutrient and Primary Production Decline from CMIP6 Model Projections, Biogeosciences, vol. 17, no. 13, pp. 3439-3470, 2020, ISSN: 1726-4170. </ref><br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=Talk:PICES&diff=518Talk:PICES2026-02-12T13:21:10Z<p>CamRichon: Created page with "I don't know how to modify the title of the page, but the model name is PISCES. Can someone change it?"</p>
<hr />
<div>I don't know how to modify the title of the page, but the model name is PISCES. Can someone change it?</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=517PICES2026-02-12T13:19:06Z<p>CamRichon: </p>
<hr />
<div>{{BreadcrumbsCellular}}<br />
<br />
* [[Page authors|Page authors]]: [[CamRichon]]<br />
* [[Responsible curator|Responsible curator]]: [[CamRichon]]<br />
----<br />
<br />
__TOC__<br />
<div class="model-box"><br />
{| class="model-ib"<br />
! Model type<br />
|-<br />
| '''Approach:''' Mechanistic <br />
|-<br />
| '''Computational demand:''' HPC<br />
|-<br />
| '''Typical physical scales:''' grid: C-type grid. Global resolution : 1 or 2°, regional resolution from 1/12° to 1/36° <br />
|-<br />
| '''Appropriate timescales:''' time step: typically around 1400-5400s<br />
<br />
output: <br />
|}<br />
</div><br />
<div style="clear:both"></div><br />
<br />
== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015)<ref>Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. </ref>. It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean). See https://www.pisces-community.org/.<br />
<br />
== Scales of interest ==<br />
PISCES has been developped and used for studying a variety of biogeochemical questions at the global and regional scale (Mediterranean, Indian Ocean, North Atlantic...). <br />
Temporal scales include seasonnal to interannual variability. PISCES is also regularly used to study past and future climates (incl. Distant past and futures). <br />
<br />
== Data inputs ==<br />
<br />
== Example Studies & Code ==<br />
<br />
=== Classic examples ===<br />
<br />
=== Recent applications ===<br />
<br />
== Limitations ==<br />
<br />
== References ==<br />
<references/><br />
[[Category:Main Pages|Model types]]</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=516PICES2026-02-12T13:10:00Z<p>CamRichon: </p>
<hr />
<div>== Model overview ==<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015). It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean).See https://www.pisces-community.org/.</div>CamRichonhttps://biogeoscapes.net//wiki/index.php?title=PICES&diff=515PICES2026-02-12T13:06:07Z<p>CamRichon: Created page with "Model overview PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015). It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean).See https://www.pisces-community.org/."</p>
<hr />
<div>Model overview<br />
PISCES is a biogeochemical model that simulates marine biological productivity and describes the biogeochemical cycles of carbon, oxygen and the main nutrients (P, N, Si, Fe) (Aumont et al., 2015). It is the marine biogeochemistry component of two ocean modeling platforms (NEMO and CROCO), three Earth System models (IPSL-CM, CNRM-CM and EC-Earth) and one operational oceanographic system (MERCATOR-Ocean).See https://www.pisces-community.org/.</div>CamRichon