lubin talk

Information about lubin talk

Published on January 3, 2008

Author: Barbara

Source: authorstream.com

Content

Assessing the Ecological Impact of the Antarctic Ozone Hole Using Multi-sensor Satellite Data:  Assessing the Ecological Impact of the Antarctic Ozone Hole Using Multi-sensor Satellite Data Dan Lubin, Scripps Institution of Oceanography Kevin Arrigo, Dept. of Geophysics, Stanford University Osmund Holm-Hansen, Scripps Institution of Oceanography Enhancement of UV Flux at Antarctic Surface:  Enhancement of UV Flux at Antarctic Surface Measured since 1988 NSF UV Monitoring Program Palmer Station McMurdo Station Ushuaia, Argentina Barrow, AK San Diego, CA http://www.biospherical.com The Antarctic Marine Food Web:  The Antarctic Marine Food Web Primary Production Grazing by Krill (Euphausia superba) Higher Predators (leopard seals, orcas) Field Work on Ecological Effects:  Field Work on Ecological Effects Began in late 1980s, primarily at Palmer Station, west of Antarctic Peninsula Smith et al. (Science, 1990) ICECOLORS: 2-4% reduction in primary production in marginal ice zone (MIZ) Holm-Hansen et al. (Photochem. Photobiol., 1993), reduction < 1% integrated over entire Southern Ocean Need for Satellite-Based Assessment:  Need for Satellite-Based Assessment Comprehensive field work is expensive, limited in time and place. Previous estimates of total impact on Southern Ocean primary production are rough extrapolations from point measurements to larger areas. Satellite data now offer complete coverage of the Southern Ocean for evaluating key forcing factors. Surface UVR Algorithm Development co-locating TOMS, AVHRR, SSM/I in 3 regions:  Surface UVR Algorithm Development co-locating TOMS, AVHRR, SSM/I in 3 regions Sea ice more influential than clouds on TOA UV radiance. Parameterization of UV sea ice albedo as function of sea ice concentration. Method developed to use TOMS and SSM/I alone. see Lubin and Morrow, JGRd (2001). Slide7:  AVHRR cloud ID using near-IR (3.5 mm) channel Seasonal variability in sea ice concentration:  Seasonal variability in sea ice concentration Total Column Ozone from TOMS:  Total Column Ozone from TOMS Sea Ice Concentration from SSM/I:  Sea Ice Concentration from SSM/I Cloud Effective Optical Depth from TOMS Reflectivity:  Cloud Effective Optical Depth from TOMS Reflectivity UV-A (315-400 nm) Flux from d-Eddington model:  UV-A (315-400 nm) Flux from d-Eddington model UV-B (280-315 nm) Flux from d-Eddington model:  UV-B (280-315 nm) Flux from d-Eddington model Biologically Weighted Flux (photoinhibition in phytoplankton):  Biologically Weighted Flux (photoinhibition in phytoplankton) Comparison with Palmer Station UV Monitor Data:  Comparison with Palmer Station UV Monitor Data Geographic Assessment of Enhanced UV Fluxes:  Geographic Assessment of Enhanced UV Fluxes Spectral flux weighted by action spectrum for photoinhibition in Antarctic phytoplankton Define climatological UVR: in terms of mean cloud attenuation, sea ice, 1979 total ozone evaluate 20-year standard deviation s Enhancement: where photoinhibition flux exceeds climatological mean by 2s or more Geographically significant enhancement: where the enhanced fluxes intersect biomass as determined by SeaWiFS Lubin et al., GRL 2004 UVR Enhancement at Palmer Station, Spring 1992:  UVR Enhancement at Palmer Station, Spring 1992 Use of SeaWiFS to Locate Phytoplankton Biomass:  Use of SeaWiFS to Locate Phytoplankton Biomass UVR Enhancements by Southern Ocean Sector Lubin et al., GRL 2004:  UVR Enhancements by Southern Ocean Sector Lubin et al., GRL 2004 Spectral Flux at the Sea Surface:  Spectral Flux at the Sea Surface Edd and Edi are direct and diffuse components surface reflection divided into direct and diffuse components, both of which are sum of specular reflection and reflectance from sea foam sea foam reflectance a function of wind stress Fresnel’s law for specular reflection In-Water Optics:  In-Water Optics Beer’s law for spectral flux penetration Diffuse attenuation coefficient Kd(z) partitioned into components describing attenuation by pure water, phytoplankton, detritus, and chromophoric dissolved organic matter. In-Water Optics - Components:  In-Water Optics - Components Pure Water: coefficents from Smith & Baker (1981) Plankton (chlorophyll) from Sathyendranath et al. (1989) Detritus from work by Arrigo et al. (1998) CDOM from work by Mitchell and Holm-Hansen (1991); Arrigo et al. (1998) Phytoplankton Production:  Phytoplankton Production G is phytoplankton growth rate (d-1) calculated from temperature and light availability C/Chl a is the phytoplankton C:Chl a mass ratio (50) Beff is effective phytoplankton concentration G is modeled in terms of a temperature-dependent maximum rate and a light limitation term Cumulative Exposure to UVR:  Cumulative Exposure to UVR Throughout the day, the physiological inactivation of algal biomass (effective biomass Beff) is expressed by reducing Beff with increasing UVR exposure. At dawn, Beff(z,t) is set = Chl a (z,t) Vertical mixing: simulated by averaging Beff over MLD, then applying this average to each layer within MLD Comparison with Field Observations: % decrease in C-fixation relative to no UVR:  Comparison with Field Observations: % decrease in C-fixation relative to no UVR Station A 59.19 S, 56.89 E 04 October:  Station A 59.19 S, 56.89 E 04 October Photoinhibition dose Hinh varies with time and depth, 30% greater in exp. run than control at surface Assess individual contributions of UV-B and UV-A Substantial UV-A contribution to Hinh and Beff Panel B: 1979 (control) Panel C: 1992 (exp.) Total Change in Primary Production:  Total Change in Primary Production Temporal Variation in Primary Production Loss over Southern Ocean:  Temporal Variation in Primary Production Loss over Southern Ocean Major Conclusion of Small Impact:  Major Conclusion of Small Impact Surface UVR-induced losses of primary production can be several percent, with large UV-B component When integrated to 0.1% light depth, loss of primary production throughout Southern Ocean, due to enhanced UV-B, is < 0.25% Major reasons: strong UV-B attenuation with depth, location of most ozone depletion over Antarctic continent, temporal mismatch between maximum ozone loss and maximum phytoplankton abundance Several sensitivity analyses did not alter this conclusion: changing MLD and mixing time temperature dependence of primary production Photoacclimation parameter Ek, specifying saturation of photosynthesis detrital and CDOM absorption phytoplankton absorption variability in Action Spectrum Instantaneous versus cumulative exposure to UVR Necessary Future Work:  Necessary Future Work Improve parameterizations throughout model in-water radiative transfer, processes very near sea ice Repeat experiments for even deeper and longer-lasting ozone holes of late 1990s Consider regional ecosystem effects

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