Improving Marine Ecosystem Models Use of Data Assimilation
![Improving Marine Ecosystem Models: Use of Data Assimilation and Mesocosm Experiments Joseph Vallino ASLO Improving Marine Ecosystem Models: Use of Data Assimilation and Mesocosm Experiments Joseph Vallino ASLO](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-1.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-2.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-3.jpg)
![Mesocosm Experiment · Additions: – NO 3 (5 m. M), PO 4 (0. 5 Mesocosm Experiment · Additions: – NO 3 (5 m. M), PO 4 (0. 5](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-4.jpg)
![Mesocosm Food Web Model · Aggregated, coupled C and N model · Emphasis on Mesocosm Food Web Model · Aggregated, coupled C and N model · Emphasis on](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-5.jpg)
![Data Assimilation Problem · State Model: · Mapping to Observations: e. g. , POC(t) Data Assimilation Problem · State Model: · Mapping to Observations: e. g. , POC(t)](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-6.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-7.jpg)
![Optimization Routines Tested Optimization Routines Tested](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-8.jpg)
![Optimization Results Optimization Results](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-9.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-10.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-11.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-12.jpg)
![Local and Global Optima Raw Data Model y(x) L L a x Local Optima Local and Global Optima Raw Data Model y(x) L L a x Local Optima](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-13.jpg)
![Model Errors · Aggregation Error Concentration True Model P 1 P 2 True parameter Model Errors · Aggregation Error Concentration True Model P 1 P 2 True parameter](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-14.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-15.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-16.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-17.jpg)
![Conclusions · Mesocosms useful for process based modeling – However, should separately model bag Conclusions · Mesocosms useful for process based modeling – However, should separately model bag](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-18.jpg)
![Acknowledgements Chuck Hopkinson Hap Garritt Linda Deegan Ishi Buffam Anne Giblin Michele Bahr John Acknowledgements Chuck Hopkinson Hap Garritt Linda Deegan Ishi Buffam Anne Giblin Michele Bahr John](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-19.jpg)
- Slides: 19
![Improving Marine Ecosystem Models Use of Data Assimilation and Mesocosm Experiments Joseph Vallino ASLO Improving Marine Ecosystem Models: Use of Data Assimilation and Mesocosm Experiments Joseph Vallino ASLO](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-1.jpg)
Improving Marine Ecosystem Models: Use of Data Assimilation and Mesocosm Experiments Joseph Vallino ASLO Meeting Santa Fe NM, Feb. 1999 Ecosystems Center Marine Biological Laboratory, Woods Hole MA
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-2.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-3.jpg)
![Mesocosm Experiment Additions NO 3 5 m M PO 4 0 5 Mesocosm Experiment · Additions: – NO 3 (5 m. M), PO 4 (0. 5](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-4.jpg)
Mesocosm Experiment · Additions: – NO 3 (5 m. M), PO 4 (0. 5 m. M), Si (7 m. M) – Leaf litter leachate (300 m. M DOC) · Treatments: – Control: – Organic Matter: Bag B – Daily Nutrients: Bag C – DOM + Nutrients: · Samples Taken: – NO 3, NH 4, PO 4, Si, O 2 DIC – PAR – POC, PON, DOC, DON – Chl a – PP (14 C and O 2 incubations) – Bacterial No. and productivity – Phyto- and zooplankton counts – DI 13 C, DO 15 N – Size fractionated d 13 C and d 15 N D C B A Bag D
![Mesocosm Food Web Model Aggregated coupled C and N model Emphasis on Mesocosm Food Web Model · Aggregated, coupled C and N model · Emphasis on](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-5.jpg)
Mesocosm Food Web Model · Aggregated, coupled C and N model · Emphasis on OM processing · Holling type II and III growth kinetics · State Eqns: 10 – Auto. – Osomo. – Hetero. – Detritus – DIN – DOM-L – DOM-R C, N C N C N · Parameters – 29 Kinetic – 10 Initial cond.
![Data Assimilation Problem State Model Mapping to Observations e g POCt Data Assimilation Problem · State Model: · Mapping to Observations: e. g. , POC(t)](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-6.jpg)
Data Assimilation Problem · State Model: · Mapping to Observations: e. g. , POC(t) = A(t) + H(t) + B(t) + DC (t) · Objective Function: Measurement error
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-7.jpg)
![Optimization Routines Tested Optimization Routines Tested](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-8.jpg)
Optimization Routines Tested
![Optimization Results Optimization Results](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-9.jpg)
Optimization Results
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-10.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-11.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-12.jpg)
![Local and Global Optima Raw Data Model yx L L a x Local Optima Local and Global Optima Raw Data Model y(x) L L a x Local Optima](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-13.jpg)
Local and Global Optima Raw Data Model y(x) L L a x Local Optima Solution y(x) G b Global Optima Solution y(x) x x
![Model Errors Aggregation Error Concentration True Model P 1 P 2 True parameter Model Errors · Aggregation Error Concentration True Model P 1 P 2 True parameter](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-14.jpg)
Model Errors · Aggregation Error Concentration True Model P 1 P 2 True parameter values Z Time P 1+2 = P 1 + P 2 · Process Errors Concentration Approx. Model P 1+2 Z Estimated aggregated parameter values N Time – Organic matter production and consumption. – Constant parameter values, such as C: N ratio of phytoplankton. – Mortality closure scheme. – Etc.
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-15.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-16.jpg)
![](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-17.jpg)
![Conclusions Mesocosms useful for process based modeling However should separately model bag Conclusions · Mesocosms useful for process based modeling – However, should separately model bag](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-18.jpg)
Conclusions · Mesocosms useful for process based modeling – However, should separately model bag walls, etc. · Optimization Routines – Simulated annealing, if computation limits permits – PRAXIS (no Grad. ) or Levenberg-Marquardt (w/ Grad. ) routines – Adjoint useful for computationally intense problems · Integrate model development with experimental observations · Improve model robustness based on aggregation techniques – Holistic versus reductionist approach · Establish modeling benchmarks
![Acknowledgements Chuck Hopkinson Hap Garritt Linda Deegan Ishi Buffam Anne Giblin Michele Bahr John Acknowledgements Chuck Hopkinson Hap Garritt Linda Deegan Ishi Buffam Anne Giblin Michele Bahr John](https://slidetodoc.com/presentation_image/1fe7d9b3b438670de075890467134a36/image-19.jpg)
Acknowledgements Chuck Hopkinson Hap Garritt Linda Deegan Ishi Buffam Anne Giblin Michele Bahr John Hobbie Jane Tucker · Funding: - National Science Foundation, LMER and LTER programs - Lakian Foundation · Manuscript submitted: JMR – Available at: http: //eco 25. mbl. edu/
Biotic and abiotic components of marine ecosystem
Magnesium cycle in marine ecosystem
Marine ecosystem dominated by marsh grasses
Characteristics of marine ecosystem
Chapter 4 lesson 2 energy flow in ecosystems answer key
What are the two main types of aquatic ecosystems
Caribbean large marine ecosystem
Jedi data assimilation
Data assimilation
Data assimilation tutorial
Data assimilation
Data assimilation
Data assimilation
Data assimilation
Data assimilation
Ahrq safety program for improving antibiotic use
Using assessment data for improving teaching practice
Modals and semi-modals
Assimilation ap psychology definition
Regressive assimilation examples