Archive for prediction

Multiyear predictions of ocean acidification in the California Current System

Posted by mmaheigan 
· Thursday, August 20th, 2020 

The California Current System is a highly productive coastal upwelling region that supports commercial fisheries valued at $6 billion/year. These fisheries are supported by upwelled waters, which are rich in nutrients and serve as a natural fertilizer for phytoplankton. Due to remineralization of organic matter at depth, these upwelled waters also contain large amounts of dissolved inorganic carbon, causing local conditions to be more acidic than the open ocean. This natural acidity, compounded by the dissolution of anthropogenic CO2 into coastal waters, creates corrosive conditions for shell-forming organisms, including commercial fishery species.

A recent study in Nature Communications showcases the potential for climate models to skillfully predict variations in surface pH—thus ocean acidification—in the California Current System. The authors evaluate retrospective predictions of ocean acidity made by a global Earth System Model set up similarly to a weather forecasting system. The forecasting system can already predict variations in observed surface pH fourteen months in advance, but has the potential to predict surface pH up to five years in advance with better initializations of dissolved inorganic carbon (Figure 1). Skillful predictions are mostly driven by the model’s initialization and subsequent transport of dissolved inorganic carbon throughout the North Pacific basin.

Figure 1. Forecast of annual surface pH anomalies in the California Current Large Marine Ecosystem for 2020. Red colors denote anomalously basic conditions for the given location and blue colors indicate anomalously acidic conditions.

These results demonstrate, for the first time, the feasibility of using climate models to make multiyear predictions of surface pH in the California Current. Output from this global prediction system could serve as boundary conditions for high-resolution models of the California Current to improve prediction time scale and ultimately help inform management decisions for vulnerable and valuable shellfisheries.

 

Authors:
Riley X. Brady (University of Colorado Boulder)
Nicole S. Lovenduski (University of Colorado Boulder)
Stephen G. Yeager (National Center for Atmospheric Research)
Matthew C. Long (National Center for Atmospheric Research)
Keith Lindsay (National Center for Atmospheric Research)

Predicting marine ecosystem futures

Posted by mmaheigan 
· Wednesday, September 4th, 2019 

Earth System Models (ESMs) are powerful and effective tools for exploring and predicting marine ecosystem response to environmental change, including biogeochemical processes that underlie threats to ocean health such as ocean acidification, deoxygenation, and changes in productivity. Seasonal to interannual marine biogeochemical predictions with ESMs hold great promise for exploring links between climate and marine resources such as fisheries but have thus far been challenged by limitations associated with observational initialization, model structure, and computational availability. In a recent study published in Science, authors integrated the Geophysical Fluid Dynamics Laboratory’s (GFDL) COBALT (Carbon, Ocean Biogeochemistry and Lower Trophics) marine biogeochemical model with seasonal to multi-annual climate predictions from GFDL’s CM2.1 climate model to examine marine ecosystem futures on these shorter time scales. The global biogeochemical forecasts were initialized on the first of each month between 1991 and 2017 with 12 ensemble members in each prediction, creating a database of nearly 4000 forecasts and 8000 simulation years. The model skillfully predicted seasonal to multi-annual chlorophyll fluctuations in many ocean regions (Figure 1).

 

Figure 1: Prediction skill in reproducing observed variations of monthly chlorophyll anomaly. (Top) Correlation coefficient between predicted and observed chlorophyll at 1-3 month lead time during the period 1997-2017. Stippled areas indicate that the correlation is significantly greater than 0 with 95% confidence. Areas with less than 80% satellite chlorophyll coverage are masked in grey. (Lower panels) Correlation coefficient between predicted and observed chlorophyll as a function of forecast initialization month (x-axis) and lead time (y-axis) in tropical Pacific, Indian, North Atlantic, North Pacific, and South Pacific oceans. In all panels, the darker the red, the higher the correlation up to a perfect correlation of 1.0. White indicates no correlation, while blue indicates negative correlation.

These results suggest that annual fish catches in selected large marine ecosystems can be predicted from chlorophyll and sea surface temperature anomalies up to 2-3 years in advance. Given that fisheries predictions sometimes failed to the point of commercial stock collapse in the past, this prediction capacity could be vital for fisheries managers. Biogeochemical prediction systems can extend beyond sea surface temperature and chlorophyll to include other potential drivers (e.g., oxygen, acidity, net primary production, zooplankton, etc.) as highly valuable tools for marine resource managers of dynamic and changing ecosystems.

Authors:
Jong-Yeon Park (Princeton Univ, NOAA GDFL, Chonbuk National Univ., Korea)
Charles A. Stock, John P. Dunne, Xiaosong Yang, and Anthony Rosati (NOAA GFDL)

Filter by Keyword

abundance acidification africa air-sea interactions alkalinity allometry ammonium AMOC anoxia anoxic Antarctic anthropogenic carbon aragonite saturation arctic arsenic Atlantic Atlantic modeling atmospheric CO2 atmospheric nitrogen deposition authigenic carbonates autonomous platforms bacteria BATS benthic bgc argo bioavailability biogeochemical cycles biogeochemical models biogeochemistry biological pump biological uptake biophysics bloom blooms blue carbon bottom water boundary layer buffer capacity CaCO3 calcification calcite carbon-climate feedback carbon-sulfur coupling carbon cycle carbon dioxide carbon sequestration Caribbean CCA CCS changing marine ecosystems changing ocean chemistry chemoautotroph chesapeake bay chl a chlorophyll circulation climate change CO2 coastal darkening coastal ocean cobalt Coccolithophores community composition conservation cooling effect copepod coral reefs currents cyclone DCM decomposers decomposition deep convection deep ocean deep sea coral deoxygenation depth diagenesis diatoms DIC diel migration dimethylsulfide dinoflagellate dissolved inorganic carbon dissolved organic carbon DOC DOM domoic acid dust DVM earth system models ecosystem state eddy Education Ekman transport emissions ENSO enzyme equatorial regions error ESM estuarine and coastal carbon fluxes estuary euphotic zone eutrophication evolution export EXPORTS extreme events extreme weather events faecal pellets filter feeders filtration rates fire fish Fish carbon fisheries floats fluid dynamics fluorescence food webs forams freshening freshwater frontal zone functional role future oceans geochemistry geoengineering GEOTRACES glaciers gliders global carbon budget global warming go-ship grazing greenhouse gas Greenland groundwater Gulf of Maine Gulf of Mexico Gulf Stream gyre harmful algal bloom high latitude human food human impact hurricane hydrothermal hypoxia ice age ice cores ice cover industrial onset inverse circulation iron iron fertilization isotopes jellies katabatic winds kelvin waves krill kuroshio land-ocean continuum larvaceans lateral transport LGM lidar ligands light light attenuation mangroves marine heatwave marine snowfall marshes Mediterranean meltwater mesopelagic mesoscale metagenome metals methane microbes microlayer microorganisms microscale microzooplankton midwater mixed layer mixed layers mixotrophy modeling mode water molecular diffusion MPT multi-decade NASA NCP net community production new technology nitrate nitrogen nitrogen fixation nitrous oxide north atlantic north pacific nutricline nutrient budget nutrient cycling nutrient limitation nutrients OA ocean-atmosphere ocean acidification ocean carbon uptake and storage ocean color ocean observatories ODZ oligotrophic omics OMZ open ocean optics organic particles overturning circulation oxygen pacific paleoceanography particle flux pCO2 PDO peat pelagic pH phenology phosphorus photosynthesis physical processes physiology phytoplankton plankton POC polar regions pollutants prediction primary productivity Prochlorococcus proteins pteropods pycnocline radioisotopes remineralization remote sensing residence time resource management respiration resuspension rivers rocky shore Rossby waves Ross Sea ROV salinity salt marsh satell satellite scale seafloor seagrass sea ice sea level rise seasonal patterns sea spray seaweed sediments sensors shelf system shells ship-based observations shorelines silicate sinking particles size SOCCOM soil carbon southern ocean south pacific spatial covariations speciation SST subduction submesoscale subpolar subtropical sulfate surface surface ocean Synechococcus teleconnections temperate temperature temporal covariations thermocline thermohaline thorium tidal time-series time of emergence top predators total alkalinity trace elements trace metals trait-based transfer efficiency transient features trophic transfer tropical turbulence twilight zone upper ocean upper water column upwelling US CLIVAR validation velocity gradient ventilation vertical flux vertical migration vertical transport volcano water clarity water quality western boundary currents wetlands winter mixing zooplankton

Copyright © 2021 - OCB Project Office, Woods Hole Oceanographic Institution, 266 Woods Hole Rd, MS #25, Woods Hole, MA 02543 USA Phone: 508-289-2838  •  Fax: 508-457-2193  •  Email: ocb_news@us-ocb.org

link to nsflink to noaalink to WHOI

Funding for the Ocean Carbon & Biogeochemistry Project Office is provided by the National Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA). The OCB Project Office is housed at the Woods Hole Oceanographic Institution.