Quantifying natural and anthropogenic variation in California Current upwelling

Ee6a8505884e516c5abfb7df54a8b14d?s=47 Riley Brady
September 24, 2015

Quantifying natural and anthropogenic variation in California Current upwelling

Ee6a8505884e516c5abfb7df54a8b14d?s=128

Riley Brady

September 24, 2015
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  1. 1.

    Quantifying Natural and Anthropogenic Variation in California Upwelling Evaluating human

    impacts in the presence of internal climate variability Riley X. Brady University of South Carolina Acknowledgements: Ryan Rykaczewski (U. South Carolina) Michael Alexander (NOAA ESRL) Jamie Scott (NOAA ESRL) Giuliana Turi (NOAA ESRL)
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ A mechanism exists whereby global greenhouse warming could . . . lead to acceleration of coastal upwelling. (Bakun, 1990) Source: Rykaczewski & Checkley 2008
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Emissions Scenario: How will we emit greenhouse gases in the future? Model Response: How does each model simulate change in response to an identical scenario? Internal (Natural) Variability: How does the climate behave void of human intervention? Source: Hawkins & Sutton 2010 Could this be an underappreciated source of uncertainty?
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ By holding the model and emissions scenario constant, we can attribute disparities entirely to internally-generated climate variability. Modified from Kay et al. 2015 1850 Control Member 1 Observations Members 2-35 Generated ensemble with 10-14K air temperature differences Forced with RCP8.5 emissions scenario
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Peak upwelling season is represented in the model from April through September. Southern Region Central Region Northern Region Vertical Velocity (cm/s x 10-4) Vertical Velocity (cm/s x 10-6) - -
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Change in Vertical Velocity (cm/s x 10-4) June Total Change in Upwelling (2041-2100) – (1941-2000) June Natural Change in Upwelling (2041-2100) – (1941-2000) Total Natural Forced Change in Vertical Velocity (cm/s x 10-4)
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Upwelling trends vary by season and location. Signal-to-Noise Ratio 95% Confidence 99.7% Confidence More Upwelling Less Upwelling
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    Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling

    Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Inter-annual change is complex. Fractional Change in Vertical Velocity Relative to Hist. Mean AMJ Central JAS Central AMJ North AMJ South JAS North JAS South 100% of Runs 80% of Runs 50% of Runs Historical Mean Ensemble Mean
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    Summary Natural variability can largely impact the magnitude of change

    in an upwelling system. Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ The sign of change in upwelling may vary meridionally and seasonally. Decadal changes are not necessarily indicative of long-term trends.
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    Further Questions Could the forced response be indicative of a

    poleward shift in the North Pacific High? Ÿ Upwelling Ÿ Uncertainty Ÿ Large Ensemble Ÿ Historical Upwelling Ÿ Natural Var. Ÿ SNR Ÿ Inter-Seasonal Ÿ Summary Ÿ Are differences between individual runs attributable to known natural climate oscillations?