lagrangian-based studies in the coastal gulf of maine
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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.
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)
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
Cruise data examples: Time-depth f-chlorophyll (mg/m3)
Time-depth biological Oxygen Anomaly (μmol/m3)
• 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 ProcessingData Processing
y = 0.1882x – 0.2243
r2 = 0.45
Results: optically-derived particle inventories versus NCP
r2 = 0.85y = 0.1432x + 0.0124
Results: optically-derived particle inventories versus NCP
r2 = 0.76
y = 0.1058x – 0.2125
Results: optically-derived particle inventories versus NCP
• 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 1Conclusions for part 1
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)
POCt1
POCt2
Premise:
(POCt2 - POCt1)
(t2 - t1)NCP
POC inventory gives an estimate of NCP
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.
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)
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 rates2.3-5 determinations per day may be enough for daily NCP estimates provided the advective component is adequately resolved3.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)
mg
C m
-2 d
-1
Net community productivity (gC m2 d-1)
Interpolation of a MODIS chl row over 5 days
Linear
Tim
e (5
days
)
Longitude
Lagrangian
Many assumptions but the biggest are:1. Within the euphotic zone, along a Largrangian trajectory
POC = pCO2(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