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Multiple Stressors in ESM2M: Time of Emergence Jonathan Lin 1, Keith Rodgers 1, Thomas Froelicher 2 1 Princeton University 2 ETH Zurich August 2014.

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Presentation on theme: "Multiple Stressors in ESM2M: Time of Emergence Jonathan Lin 1, Keith Rodgers 1, Thomas Froelicher 2 1 Princeton University 2 ETH Zurich August 2014."— Presentation transcript:

1 Multiple Stressors in ESM2M: Time of Emergence Jonathan Lin 1, Keith Rodgers 1, Thomas Froelicher 2 1 Princeton University 2 ETH Zurich August 2014

2 Organizations and Host Princeton Environmental Institute – “The Internship Program offers Princeton undergraduates a unique opportunity to complement their academic interests with hands- on, engaging, independent research and project experiences through the summer months.” Atmospheric and Ocean Sciences (AOS) Program

3 Background Information What is the ESM2M? – Models physical climate (land, atmosphere, ocean and sea ice) – Incorporates interactive biogeochemistry (e.g. carbon cycle) – Internal variability (ENSO and other climatic modes) – Fully coupled model 30 member ensemble (1950 – 2100) – Each ensemble member initialized with slightly different atmospheric state (i.e. January 1, January 2, etc.) – Each ensemble member is just one realization of all the possible paths of progression – Does NOT represent all possibilities, but rather just a range

4 Guiding Question What are the time scales of detectable trends in four major stressors that control ocean ocean ecosystem and marine organisms? – Omega Aragonite (saturation state) Ω arag = [Ca 2+ ] [CO 3 2- ] / K’ sp – Sea Surface Temperature – Oxygen (integral over 100m – 600m depth) – Primary Productivity

5 Time of Emergence: Method Signal to Noise Ratios – Averaged linear trend (signal) divided by the standard deviation (noise) among the 30 ensemble members – Used a 30 year moving window for linear trends to create signal to noise ratio over time (1965 – 2085) Mechanism – Time of emergence when the signal to noise ratio finally crosses a threshold – Define the threshold as a signal to noise ratio of 2 (95% confidence of a detectable trend, a rather conservative value)

6 Confidence Intervals % confidence of Trend from 2005 – 2014. From top left, Ω arag, SST, Oxygen Inventories, and Primary Productivity.

7 Confidence Intervals We can also look at the combined effect of the stressors. Average of the % confidence of all four major stressors, averaged from 2005-2014 (top), and 2075- 2084 (top).

8 Time of Emergence Time of Emergence (95% confidence). From top left, Ω arag, SST, Oxygen Inventories, and Primary Productivity.

9 Acknowledgments PEI for allowing me the opportunity to participate in this internship Keith Rodgers, Thomas Froelicher, and Brendan Carter for their initiation of this project as well as their valuable mentorship and involvement in my work


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