Researcher: Clara Deal
Funding Source: JAMSTEC
Collaborators: Meibing Jin, Jingfeng Wu, Eiji Watanabe, David Atkinson, and Igor Semiletov (IARC/UAF); Rolf Gradinger (SFOS/UAF); Falk Huettmann and Grant Humphries (Biology/IARC/UAF); Scott Elliott, Elizabeth Hunke, Mat Maltrud, and Nicole Jefferey (LANL/DOE); Jacqueline Stefels (UGroningen/The Netherlands); John Dacey (WHOI); and Sei-Ichi Saitoh (UHokkaido/Japan)
Modeling of marine primary production and biogeochemical cycling in the Arctic will aid in the assessment of air-sea CO2 flux and improve our understanding of biogeochemical and ecological (e.g., food availability) changes in a warming climate. Development of a GIS-based statistical model for predicting surface seawater DMS concentrations and sea-to-air flux will complement our existing modeling work and allow us to add DMS as a new predictor variable for modeling ecological systems that include seabirds. The observational component will lead to year-round measurements of DMS mixing ratios in clean marine air from over the Arctic Ocean.
We will further develop our ice-ocean ecosystem models by utilizing observational results including those of IARC scientists (I. Semiletov and J. Wu) and collaborators (e.g., R. Gradinger). Our focus is on the Bering-Chukchi and East Siberian seas. From the Pacific Arctic, we are extending the model to the pan-Arctic scale. The DMS measurements involve instrument development, automation and testing in the lab at IARC, followed by installation of the automated DMS analytical system in NOAA CMDL at Barrow, Alaska.
We anticipate development of predictive models that will aid assessment of how diminishing sea ice will influence primary production and biogeochemical cycling on interannual and decadal scales. We expect to clarify the role of DMS as a key factor regulating the abundance and distribution of marine populations. We anticipate observing the seasonality of DMS and links between DMS, atmospheric constituent, and remotely sensed parameters (e.g., ice coverage).
These studies will improve our understanding of the influence of diminishing sea ice on marine primary production through integration of observations and modeling. Results from the GIS-based DMS model are a product of synthesis through linking multiple components of the Arctic system (e.g. sea ice, ocean productivity, marine ecology, climate variability). Year-round time series of DMS measurements in the Arctic will help fill the data gap hindering validation of DMS synthesis products and modeling studies.