2004-09-12 Data and Tools for Web-Based Monitoring and Analysis
120612 geia closure_ofeo_ms_soa_subm
1. Tools for
Closure of Emissions, Observations and Models
using
Service Oriented Architecture
Rudolf B. Husar, rhusar@wustl.edu, Washington University, USA
Stefan R. Falke, stefan.falke@ngc.com, NGC, USA
Gregory J. Frost, gregory.j.frost@noaa.gov, NOAA & U. Colorado, USA
Terry J. Keating, keating.terry@epa.gov, US EPA/OAR, USA
GEIA Conference, Toulouse, FR, June 11-13, 2012
2. Guiding Principles by
Global Observing System of Systems (GEOSS)
Any Single Data Set Can
Serve Many Applications
Any Single Problem
Requires Many Data Sets
Interoperability
is Required!
3. AQ Networking Requires:
Interoperability of People and Machines
People & Machines
People People
People & People
AQ Community of Practice
Machines & Machines
AQ Community Server
4. AQ Data Network:
Core Datastes; AQ Community Catalog Exits
Many Interop. Issues Unresolved (e.g. Sept. Dublin Metadata Mtg.)
20+ Datasets, 12+ Originators
5. GEO Air Quality Community of Practice
AQ Data Network Architecture
Based on Service Oriented Architecture:
Loosely Coupled Components
6. GEO Air Quality Community of Practice
AQ Data Network Architecture
Atmospheric Model
Evaluation Network
7. The Atmospheric Model Evaluation Network (AMEN)
Terry Keating, U.S. EPA, keating.terry@epa.gov
Air Quality Air Quality Air Quality
Obs. Data Obs. Data Obs. Data
Air Quality
Model Output Air Model Stat Tests & Views
Model-Obs; Model-Model
Evaluation Model-Emiss; Emiss-Obs
Network Portal Obs-Obs
Air Quality
Model Output
Emissions
Air Quality
Model Output
Database
Tools for statistical & interactive model evaluation
Built on the federated data infrastructure
8. Still High Variability of Aerosol Model Performance
Example: Huneeus et al, 2011: Global dust model intercomparison in AeroCom I
10000
Max Median Min
1000
100
10
NorthAfrica AsiaSouth MiddleEast WorldRest
• Transport simulations are are consistent but
emissions and transformation/removal
processes diverge among models
• Dust emissions varied my an order of
magnitude, causing similar divergence of the
simulated dust surface concentrations
9. Simple Goal: Utopia
Best Available Atmospheric Composition
Best Available
Atm. Composition
Public Health
Chem. Climate
Ecology, Esthetics
By Integrating Best
Observations, Emiss
ions, Models
10. Approach to Obs. Model Closure:
Tool to Iteratively Reduce the Bias
Actual closure to be worked out by the AQ community
DJF MAM JJA SON
Nitrate Organics Fine Dust Bio. Organics
Low in DJF Low in DJF Low in MAM High MAM & JJA
Add nitrate source Improved smoke by Add Sahara, local dust Reduce biogenic OC
Inverse modeling of combined Dust and smoke BC for Adjust source trem
VIEWS Nitrate chemical, satellite, spa CMAQ – e.g. NAAPS
ce-time
VIEWS NO3 DJF
CMAQ
NAAPS Dust, July
11. Fine Particle Mass, PM 2.5
Obs.: USEPA; Model: Regional-Summer
PM2.5 BIAS
OBSERVATION MODEL
12. Fine Particle Mass, PM 2.5
Obs.: USEPA; Model: Regional-Winter
PM2.5 BIAS
OBSERVATION MODEL
15. Summary:
Current State: Future Possibilities:
Tools for Emission Obs. Community-based EOM
Model Closure convergence & closure
Best Available
Atm. Composition
Public Health
Chem. Climate
Ecology, Esthetics
By Integrating Best
Observations, Emiss
ions, Models
Notas del editor
Loosely coupled data network for Observations, Models and Emissions (OME)AMEN portal that facilitates standards-based access to the distributed OMEsTools for statistical test and analyses through interactive graphic interface