• Energy Research

AbstractIllness caused by pathogenic strains of Vibrio bacteria incurs significant economic and health care costs in many areas around the world. In the Chesapeake Bay, the two most problematic species are V. vulnificus and V. parahaemolyticus, which cause infection both from exposure to contaminated water and consumption of contaminated seafood. We used existing Vibrio habitat models, four global climate models, and a recently developed statistical downscaling framework to project the spatiotemporal probability of occurrence of V. vulnificus and V. cholerae in the estuarine environment, and the mean concentration of V. parahaemolyticus in oysters in the Chesapeake Bay by the end of the 21st century. Results showed substantial future increases in season length and spatial habitat for V. vulnificus and V. parahaemolyticus, while projected increase in V. cholerae habitat was less marked and more spatially heterogeneous. Our findings underscore the need for spatially variable inputs into models of climate impacts on Vibrios in estuarine environments. Overall, economic costs associated with Vibrios in the Chesapeake Bay, such as incidence of illness and management measures on the shellfish industry, may increase under climate change, with implications for recreational and commercial uses of the ecosystem.

AbstractPopulations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment‐driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this “fishery relevant” scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast‐informed harvest controls with additional harvest restrictions at low biomass.

Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El Niño Southern Oscillation (ENSO). Drier and warmer conditions associated with El Niño increased egg and hatchling mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly decline in the region over the next 100 years by ∼50-60%, due to warming and drying in northwestern Costa Rica, threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in other areas affected by similar climate changes.

This repository contains annual 3D sea water age since surface contact files from the ScenarioMIP ssp585 simulation conducted with GFDL's ESM4.1 climate model (Dunne et al., 2020) that was contributed to the 6th Coupled Model Intercomparison Project (CMIP6). Both the ocean model native grid and the regridded output can be found in this repository. For the regridded output, the files have been regridded from MOM6 native grid to standard World Ocean Atlas 1x1 horizontal grid, and they have been remapped from the lagrangian vertical coordinate used by GFDL's MOM6 ocean model (Adcroft et al., 2019) to standard World Ocean Atlas depths. Files have undergone QA/QC. All data files are NetCDF. Enquiries should be directed to Jasmin.John (Jasmin.John@noaa.gov) or John Dunne (John.Dunne@noaa.gov) Anyone using these data should cite Dunne et al. (2020) and Adcroft et al. (2019). See references below. Other variables associated with these simulations, along with assigned DOI's, are available through the ESGF CMIP6 portal: https://esgf-node.llnl.gov/projects/cmip6/ ______________________________________________________________________ The organization of this repository is as follows: Experiments: The tar files in the repository follow this naming convention: <model>_<activity>_<MIP>_<experiment>_<component_and_grid>_<variable>.tar.gz E.g. GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_1x1deg_agessc.tar.gz (regridded) GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_agessc.tar.gz (native grid) The organization of above repository is as follows: Experiment: ssp585 NOAA-GFDL/CMIP6/ScenarioMIP/GFDL-ESM4/ESM4_ssp585_D1/ For each experiment, 3D annual sea water age data can be found in the sub-directory: /ocean_annual_z_1x1deg (for regridded output) /ocean_annual_z (for native grid output) _________________________________________________________________________ NOTES: Provenance: The data provided here do not have metadata that can be used for provenance and traceability back to NOAA/GFDL. The data DOI assigned should be used when sharing and citing these data. _________________________________________________________________________ {"references": ["Dunne, John P., Larry W Horowitz, Alistair Adcroft, Paul Ginoux, Isaac M Held, Jasmin G John, John P Krasting, Sergey Malyshev, Vaishali Naik, Fabien Paulot, Elena Shevliakova, Charles A Stock, Niki Zadeh, V Balaji, Chris Blanton, Krista A Dunne, Christopher Dupuis, Jeffrey W Durachta, Raphael Dussin, Paul P G Gauthier, Stephen M Griffies, Huan Guo, Robert Hallberg, Matthew J Harrison, Jian He, William J Hurlin, Colleen McHugh, Raymond Menzel, P C D Milly, Sergei Nikonov, David J Paynter, Jeff J Ploshay, Aparna Radhakrishnan, Kristopher Rand, Brandon G Reichl, Thomas E Robinson, M Daniel Schwarzkopf, Lori T Sentman, Seth D Underwood, Hans Vahlenkamp, Michael Winton, Andrew T Wittenberg, Bruce Wyman, Yujin Zeng, and Ming Zhao, November 2020: The GFDL Earth System Model version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation characteristics. Journal of Advances in Modeling Earth Systems, 12(11), DOI:10.1029/2019MS002015.", "Adcroft, Alistair, Whit G Anderson, V Balaji, Chris Blanton, Mitchell Bushuk, C O Dufour, John P Dunne, Stephen M Griffies, Robert Hallberg, Matthew J Harrison, Isaac M Held, Malte Jansen, Jasmin G John, John P Krasting, Amy R Langenhorst, Sonya Legg, Zhi Liang, Colleen McHugh, Aparna Radhakrishnan, Brandon G Reichl, Anthony Rosati, Bonita L Samuels, Andrew Shao, Ronald J Stouffer, Michael Winton, Andrew T Wittenberg, Baoqiang Xiang, Niki Zadeh, and Rong Zhang, October 2019: The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features. Journal of Advances in Modeling Earth Systems, 11(10), DOI:10.1029/2019MS001726vers"]}

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-ESM4.ssp585' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

AbstractClimate change is an environmental emergency threatening species and ecosystems globally. Oceans have absorbed about 90% of anthropogenic heat and 20%–30% of the carbon emissions, resulting in ocean warming, acidification, deoxygenation, changes in ocean stratification and nutrient availability, and more severe extreme events. Given predictions of further changes, there is a critical need to understand how marine species will be affected. Here, we used an integrated risk assessment framework to evaluate the vulnerability of 132 chondrichthyans in the Eastern Tropical Pacific (ETP) to the impacts of climate change. Taking a precautionary view, we found that almost a quarter (23%) of the ETP chondrichthyan species evaluated were highly vulnerable to climate change, and much of the rest (76%) were moderately vulnerable. Most of the highly vulnerable species are batoids (77%), and a large proportion (90%) are coastal or pelagic species that use coastal habitats as nurseries. Six species of batoids were highly vulnerable in all three components of the assessment (exposure, sensitivity and adaptive capacity). This assessment indicates that coastal species, particularly those relying on inshore nursery areas are the most vulnerable to climate change. Ocean warming, in combination with acidification and potential deoxygenation, will likely have widespread effects on ETP chondrichthyan species, but coastal species may also contend with changes in freshwater inputs, salinity, and sea level rise. This climate‐related vulnerability is compounded by other anthropogenic factors, such as overfishing and habitat degradation already occurring in the region. Mitigating the impacts of climate change on ETP chondrichthyans involves a range of approaches that include addressing habitat degradation, sustainability of exploitation, and species‐specific actions may be required for species at higher risk. The assessment also highlighted the need to further understand climate change's impacts on key ETP habitats and processes and identified knowledge gaps on ETP chondrichthyan species.

Abstract The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish (Anoplopoma fimbria) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions.