1. Lagrangian-based studies in the coastal Gulf of Maine Overall goal: estimation of community production rates by tracking satellite-derived inventories over time and space Problem: LEO-derived productivity estimates presently rely on single images of stocks and state variables to infer rates of change Solution: Multiple views/day from GeoCAPE will enable monitoring of biogeochemical inventories within a water parcel as they evolve over time.

2. Lagrangian-based Studies in the coastal Gulf of Maine (supplements to NASA-Carbon NNX08AL80G). Part 1: A Lagrangian field experiment to determine net community productivity in the Gulf of Maine Olivia DeMeo (MS Candidate, UNH), Joe Salisbury (UNH) Part 2: Preliminary results of tracking particle inventories with a high resolution circulation model and MODIS 250m data Bror Jonsson (Princeton), Joe Salisbury (UNH), Amala Mahadevan, (Boston University)

3. Part 1 The Lagrangian Experiment Approach:1. Tracked a drogue at 12m (7 cruises over 16 days) 2. Kept track of oxygen and particle inventories These are equivalent (Within the context of a homogenous water mass) With GeoCAPE, we can probably track dPOC : dt

4. Cruise data examples: Time-depth f-chlorophyll (mg/m 3 )

5. Time-depth biological Oxygen Anomaly (μmol/m 3 )

6. Raw oxygen and f-chl profiles were corrected with bottle data bbp and c-660 derived particle inventories estimated using a regression with bottle POC Integration to euphotic depth Oxygen corrected for thermodynamic variability, air-sea flux and diffusion, then converted to carbon using the Redfield ratio Data Processing

7. y = 0.1882x – 0.2243 r 2 = 0.45 Results:  optically-derived particle inventories versus NCP

8. r 2 = 0.85 y = 0.1432x + 0.0124 Results:  optically-derived particle inventories versus NCP

9. r 2 = 0.76 y = 0.1058x – 0.2125 Results:  optically-derived particle inventories versus NCP

10. The Good: Highly significant relationships between  optically derived particle inventories and NCP The Bad: The relationships (in carbon units) should be 1:1, but are off by a factor 3 - 5 The Ugly: We don’t know why (yet!) Conclusions for part 1

11. Part 2: Preliminary results of tracking particle inventories with a high resolution circulation model and MODIS 500m data Based on recent work: Estimating community productivity by tracking particle inventories in a Lagrangian context Jonsson, Salisbury, Mahadevan, Campbell (2009) Jonsson, Salisbury, Mahadevan (2011) POC t1 POC t2 Premise: (POC t2 - POC t1 ) (t2 - t1)  NCP

15.  POC inventory gives an estimate of NCP

16. Still to do on the GEO-CAPE Grant: Use a 300m, hourly model and daily cloud free 250 and 500m MODIS data to: 1.Simulate differences in “net radiance production” between Eularian versus Lagrangian determinations over the course of a day. 2.Run the same simulation using increasingly large pixel resolutions.

17. The first run using high res circulation and 500m MODIS (12:27 AM last night) The high res domain, Casco Bay Maine (about 120x120 km)

18. Model output from Huijie Xue (UMO) 300m GOM-POM model (Salinity)

19. How do our results help inform the GEO-CAPE SWG? 1.Results from part 1 suggest that sub daily changes in particle inventories can be use to to track daytime NCP rates 2.3-5 determinations per day may be enough for daily NCP estimates provided the advective component is adequately resolved 3.For part 2: Preliminary work shows promise towards estimating rates from satellite tracking of particle inventories in a Lagrangian context. 4.In work still to be done, we anticipate considerable differences between the Lagrangian and Eularian approach (using high resolution data)

21. mg C m -2 d -1 Net community productivity (gC m 2 d -1 )

22. Interpolation of a MODIS chl row over 5 days Linear Time (5days) Longitude Lagrangian

24. Many assumptions but the biggest are: 1.Within the euphotic zone, along a Largrangian trajectory  POC =  pCO 2 (bio) 2. Phytoplankton POC : Chl = 53 3. Sinking, vertical mixing and DOC production by phytoplankton “excess production” are minimal, over short (2-7 day) time scales