Quantifying natural and anthropogenic variation in California Current upwelling

Transcript

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)

2. 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

3. 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?

4. 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

5. 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) - -

6. 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)

7. 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

8. 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

9. 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.

10. 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?