The Arctic Ocean ecosystems are experiencing rapid changes. This could have possible implications for aerosol and cloud feedbacks that are not currently represented in CMIP6 models. One important proxy for plankton life is oceanic chlorophyll. This study investigates the representation of chlorophyll in two CMIP6 models; GFDL-ESM4 and MPI-ESM1-2-LR, and compares it with satellite observations. The chlorophyll concentration elvovement in time is investigated in Bering Strait and Fram Strait. The satellite observations show a positive trend of 0.1 mg myear (Fram Strait) and 0.06 mg myear (Bering Strait) in maximum chlorophyll values. The projected changes in SSP2-4.5 in GFDL-ESM4 is a negative trend of -0.018 mg myear in maximum values, while MPI-ESM1-2-LR shows a positive trend of 0.011 mg myear in maximum values. Chlorophyll is compared with the other biological proxies bacterial carbon concentration and dissolved organic carbon. Chlorophyll is found to have a moderate correlation of 0.53 with bacterical carbon in GFDL-ESM4. No correlation is found with dissolved organic carbon, 0.09 for GFDL-ESM4 and 0.05 for MPI-ESM1-2-LR. GFDL-ESM4 and MPI-ESM1-2-LR also show diverging relationship between sea ice concentration and chlorophyll, where chlorophyll decreases along with declining sea ice at the end of SSP2-4.5, while chlorophyll increases in MPI-ESM1-2-LR with declining sea ice. The computing resources used for this course have been kindly provided by Galaxy europe in the framework of the EOSC-Nordic and RELIANCE projects. The storage resources were provided by UNINETT Sigma2 - the Norwegian National Infrastructure for High Performance Computing and Data Storage in Norway as part of NS1000K project
Gjelsvik, Astrid Bragstad, and Gabriel Freitas. "A song of Ice and Phytoplankton." ROHub. Mar 18 ,2022. https://w3id.org/ro-id/183f2862-7509-4343-8ec9-74775b642c8d.
Department of Environmental Science, Stockholm university (Sweden)
Contains all the links and bibliographic documents used for this study
The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs).
Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6
Single-celled algae that rely on sunlight to survive form the basis of the food chain throughout the world’s oceans. In the Arctic, these algae can live in sea ice (ice algae) and in the water column (phytoplankton). Scientists use satellite-based observations of chlorophyll (the green pigment vital for photosynthesis) as a proxy for phytoplankton productivity. According to the 15th annual Arctic Report card, the productivity of these microscopic ocean plants has increased as summer sea ice has declined over the past two decades.
Sea ice withers while phytoplankton blooms in the Arctic
The future response of marine ecosystem diversity to continued anthropogenic forcing is poorly constrained. Phytoplankton are a diverse set of organisms that form the base of the marine ecosystem. Currently, ocean biogeochemistry and ecosystem models used for climate change projections typically include only 2−3 phytoplankton types and are, therefore, too simple to adequately assess the potential for changes in plankton community structure. Here, we analyse a complex ecosystem model with 35 phytoplankton types to evaluate the changes in phytoplankton community composition, turnover and size structure over the 21st century. We find that the rate of turnover in the phytoplankton community becomes faster during this century, that is, the community structure becomes increasingly unstable in response to climate change. Combined with alterations to phytoplankton diversity, our results imply a loss of ecological resilience with likely knock-on effects on the productivity and functioning of the marine environment.
Future phytoplankton diversity in a changing climate
Contributing roughly half of the biosphere's net primary production (NPP), photosynthesis by oceanic phytoplankton is a vital link in the cycling of carbon between living and inorganic stocks. Each day, more than a hundred million tons of carbon in the form of CO2 are fixed into organic material by these ubiquitous, microscopic plants of the upper ocean, and each day a similar amount of organic carbon is transferred into marine ecosystems by sinking and grazing. The distribution of phytoplankton biomass and NPP is defined by the availability of light and nutrients (nitrogen, phosphate, iron). These growth-limiting factors are in turn regulated by physical processes of ocean circulation, mixed-layer dynamics, upwelling, atmospheric dust deposition, and the solar cycle. Satellite measurements of ocean colour provide a means of quantifying ocean productivity on a global scale and linking its variability to environmental factors. Here we describe global ocean NPP changes detected from space over the past decade. The period is dominated by an initial increase in NPP of 1,930 teragrams of carbon a year (Tg C yr(-1)), followed by a prolonged decrease averaging 190 Tg C yr(-1). These trends are driven by changes occurring in the expansive stratified low-latitude oceans and are tightly coupled to coincident climate variability. This link between the physical environment and ocean biology functions through changes in upper-ocean temperature and stratification, which influence the availability of nutrients for phytoplankton growth. The observed reductions in ocean productivity during the recent post-1999 warming period provide insight on how future climate change can alter marine food webs.
Climate-driven trends in contemporary ocean productivity
The relationship between the spring bloom along the Primorye coast and the sea ice of the Tatarskiy Strait in the northern region of the East/Japan Sea, a semi-enclosed marginal sea in the North Pacific, was investigated using the ten-year SeaWiFS chlorophyll-a concentration data and DMSP/SSMI sea ice concentration data from 1998 to 2007. Year-to-year variations in the chlorophyll-a concentrations in the spring were positively correlated with those of the sea ice concentrations in the Tatarskiy Strait in the previous winter with a correlation coefficient of 0.77. Abrupt increases in nutrients, essential for the spring bloom in the upper ocean during spring, were supplied from sea ice-melted waters. Time series of vertical distributions of the nutrients indicated that phosphate concentrations were extremely elevated in the upper ocean (less than 100 m) without any connection to high concentrations in the deep waters below. The water mass from sea ice provided preferable conditions for the spring bloom through changes in the vertical stratification structure of the water columns. Along-coast ratios of stability parameters between two neighboring months clearly showed the rapid progression of the generation of a shallow pycnocline due to fresh water originating from sea ice. This study addressed the importance of the physical environment for biogeochemical processes in semi-enclosed marginal seas affected by local sea ice.
Role of sea ice on satellite-observed chlorophyll-a concentration variations during spring bloom in the East/Japan sea
Summer melting of sea ice leads to the formation of under-ice melt ponds in Arctic seas. The biological characteristics of such a pond were studied in summer 1993. The chlorophyte Pyramimonas sp. (Prasinophyceae) formed a unialgal bloom with cell densities of 19.1 x 103 cells ml-1 and a pigment concentration of 29.6 mg m-3. A comparison with ice core data revealed differences in algal biomass and community structure. Physical data indicate that under-ice ponds are a common feature in the Arctic Ocean. Thus, communities within under-ice ponds, which have not been included in production estimates, may significantly contribute to the Arctic marine food web.
Occurrence of an algal bloom under Arctic pack ice
Time evolution of chlorophyll concentrations in Bering Strait and Fram Straits. Blue dots mark satellite measured values (MODIS-Aqua). The trends in yearly mean and yearly maximum values for satellite data with significance level <= 0.05 are also plotted, as well as the GFDL-ESM4 and MPI-ESM1-2-LR chlorophyll values for the same periods.
CMIP6 versus MODIS Chlorophyll Concentration at two locations (Bering strait and Fram strait)
This is a Python script where all the functions used in the Jupyter Notebook were gathered. This Python script needs to be downloaded with the Jupyter Notebook and must be in the same folder than the Jupyter Notebook itself.
Python script containing all the functions used in the Jupyter Notebook
This is a tarball for the Docker climate-JupyterLab image - Version 2021-03-18 To use it: download the image file docker-climate-notebook-2021-03-18.tar load it with docker with the command: docker load --input docker-climate-notebook-2021-03-18.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-climate-notebook for more details
Docker climate-JupyterLab image - Version 2021-03-18
This jupyter notebook support the report written for the FORCeS eScience course 'Tools in Climate Science: Linking Observations with Modelling'
Jupyter Notebook for comparing model and observations of Chlorophyll concentrations over the Artic Ocean.
This Jupyter notebook has been used to generate the Research Object and also to update it e.g. add all the internal and external resources used and generated during the eScience course.
Jupyter Notebook for creating RO and aggregating all the resources used/generated
🐳 🔬 📚 Jupyter running in a docker container. The version used by this study is 2021-03-18 and it was used through the Galaxy Europe JupyterLab Climate Interactive Tool.
Docker Climate Analysis Jupyter Container (RO)
MODIS Chlorophyll-a Concentration Datasets from ADAM Platform DataCubes for 69618:MODh20chlMO_4km for JJA 2002 to 2018.
ADAM DataCube August 2005 MODIS Chlorophyll-a Concentration(monthly)
August 2005 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2007 MODIS Chlorophyll-a Concentration(monthly)
June 2007 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2015 MODIS Chlorophyll-a Concentration(monthly)
August 2015 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2012 MODIS Chlorophyll-a Concentration(monthly)
July 2012 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2011 MODIS Chlorophyll-a Concentration(monthly)
July 2011 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2006 MODIS Chlorophyll-a Concentration(monthly)
July 2006 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2002 MODIS Chlorophyll-a Concentration(monthly)
August 2002 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2010 MODIS Chlorophyll-a Concentration(monthly)
July 2010 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2017 MODIS Chlorophyll-a Concentration(monthly)
August 2017 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2016 MODIS Chlorophyll-a Concentration(monthly)
August 2016 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2009 MODIS Chlorophyll-a Concentration(monthly)
July 2009 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2007 MODIS Chlorophyll-a Concentration(monthly)
August 2007 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2008 MODIS Chlorophyll-a Concentration(monthly)
June 2008 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2018 MODIS Chlorophyll-a Concentration(monthly)
July 2018 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2003 MODIS Chlorophyll-a Concentration(monthly)
June 2003 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2017 MODIS Chlorophyll-a Concentration(monthly)
July 2017 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2013 MODIS Chlorophyll-a Concentration(monthly)
June 2013 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2006 MODIS Chlorophyll-a Concentration(monthly)
June 2006 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2013 MODIS Chlorophyll-a Concentration(monthly)
August 2013 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2005 MODIS Chlorophyll-a Concentration(monthly)
July 2005 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2009 MODIS Chlorophyll-a Concentration(monthly)
June 2009 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2006 MODIS Chlorophyll-a Concentration(monthly)
August 2006 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2008 MODIS Chlorophyll-a Concentration(monthly)
July 2008 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2007 MODIS Chlorophyll-a Concentration(monthly)
July 2007 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2018 MODIS Chlorophyll-a Concentration(monthly)
June 2018 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2004 MODIS Chlorophyll-a Concentration(monthly)
June 2004 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2016 MODIS Chlorophyll-a Concentration(monthly)
July 2016 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2004 MODIS Chlorophyll-a Concentration(monthly)
July 2004 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2014 MODIS Chlorophyll-a Concentration(monthly)
August 2014 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2014 MODIS Chlorophyll-a Concentration(monthly)
June 2014 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2008 MODIS Chlorophyll-a Concentration(monthly)
August 2008 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2017 MODIS Chlorophyll-a Concentration(monthly)
June 2017 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2012 MODIS Chlorophyll-a Concentration(monthly)
June 2012 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2011 MODIS Chlorophyll-a Concentration(monthly)
June 2011 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2003 MODIS Chlorophyll-a Concentration(monthly)
August 2003 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2011 MODIS Chlorophyll-a Concentration(monthly)
August 2011 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2015 MODIS Chlorophyll-a Concentration(monthly)
July 2015 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2002 MODIS Chlorophyll-a Concentration(monthly)
July 2002 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2013 MODIS Chlorophyll-a Concentration(monthly)
July 2013 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2010 MODIS Chlorophyll-a Concentration(monthly)
August 2010 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2010 MODIS Chlorophyll-a Concentration(monthly)
June 2010 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2018 MODIS Chlorophyll-a Concentration(monthly)
August 2018 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2009 MODIS Chlorophyll-a Concentration(monthly)
August 2009 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2004 MODIS Chlorophyll-a Concentration(monthly)
August 2004 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2016 MODIS Chlorophyll-a Concentration(monthly)
June 2016 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2003 MODIS Chlorophyll-a Concentration(monthly)
July 2003 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube August 2012 MODIS Chlorophyll-a Concentration(monthly)
August 2012 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube July 2014 MODIS Chlorophyll-a Concentration(monthly)
July 2014 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2005 MODIS Chlorophyll-a Concentration(monthly)
June 2005 MODIS Chlorophyll-a Concentration (monthly)
ADAM DataCube June 2015 MODIS Chlorophyll-a Concentration(monthly)
June 2015 MODIS Chlorophyll-a Concentration (monthly)
This is the final report written for the FORCeS eScience course 'Tools in Climate Science: Linking Observations with Modelling'. It has been built from the Jupyter Notebook and also contains the scientific discussion of the results as well as references.
Final Report on 'A song of Ice and Phytoplankton'
Ocean Color Data: Modis-aqua_chl-a (JJA, 2002-2018) downloaded from the ADAM Platform (https://reliance.adamplatform.eu/) used furing the FORCeS eScience course 'Tools in Climate Science: Linking Observations with Modelling'.
netCDF Ocean Color Data: Modis-aqua_chl-a (JJA, 2002-2018)
This GeoJSON file contains two areas e.g. Bering Strait and Fram Strait. Model and observations of Chlorophyll concentrations are compared over these two areas.