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The Federated Data System
DataFed-Non-intrusive data integration infrastructure-Based on standards-based web services-Processing tools created from reusable components
Local, Regional, Global Pollution
Before 1950s:
LocalSmoke, Fly ash
Post- 2000s:
Global, HTAPOzone, PM,Global Change
1970s-1990s:
Regional, LRTPAcid Rain, Haze
• The LRTP/HTAP flow of air pollutants is likely to increase as overseas economies grow.• Pollutant influx leads to significant exceedances of O3 PM NAAQS in some regions• Even after domestic controls, some US areas will be no-compliant because of LRTP
Terrestrial
Airborne
Near-Space
LEO/MEO Commercial Satellites and Manned Spacecraft
Far-Space
L1/HEO/GEO TDRSS & CommercialSatellites
Dep
loya
ble
P
erm
anen
t Coordinating Earth Observing Systems
Forecasts & Predictions
Aircraft/Balloon Event Tracking and Campaigns
User Community
Vantage Points Capabilities
`
Products
Products
State & Local
Canadian Providences
NOAANWS
HHSCDC-EPHTN
Aerosol Optical Depth(GASP)
TERRA MODISTERRA MODISAQUA MODISAQUA MODIS
ProductsCMAQ Forecast Data
US EPAAQS
ProductsSLAMS/NAMS SURACE PM2.5 Data
Air Quality/Public Health NTO Integrated Observed-Modeled Air Quality FieldsAir Quality/Public Health NTO Integrated Observed-Modeled Air Quality Fields
ProductsSpatial surface Predictions Satellite/Model/Surface Data Fusion
State Public Health
Departments
~10:30 local overpass~1:30 local overpass
Algorithms/QA
NASAGFSC
Science Team
NASAGFSCDACC
*Note: Regional East Atmospheric Lidar Mesonet (REALM) is university led federated network by UMBC and is identified as a NTO in the implementation plan.
Products Aerosol Optical Depth(MOD04_L2)
NOAANESDIS
NOAANESDIS/ORA &
CREST Institutes
?UMBC
CREST Institute
GEOS-12GEOS-12CONUS every 30 minutes
REALMREALMContinuous VerticalResolution Data
ProductsAlgorithms/QA
EPAOAR & ORD
ProductsCMAQ Assessment Data
ProductsStudies and Impacts to human health
US EPA OAQPS/ORD/OEI
RSI Gateway
P. Dickerson, EPA
http://www.igospartners.org/http://www.fz-juelich.de/icg/icg-ii/iagos/
http://www.fz-juelich.de/icg/icg-ii/mozaic/home
http://earthobservations.org/
http://www.epa.gov/ttn/amtic/monstratdoc.html
National Ambient Air Monitoring StrategyOffice of Air Quality Planning and StandardsResearch Triangle Park, NCDecember 2005
http://www.al.noaa.gov/AQRS/reports/monitoring.html
http://www.empa.ch/gaw/gawsis/
http://www.nesdis.noaa.gov/
http://www.cmdl.noaa.gov/
Barrow
Mauna Loa
Trinidad Head
A. Samoa
S. Pole
L2
NCORE L3
L1
http://www.emep.int/
GAW
CENR/AQRSGEOSS
NO
AA
CM
DL
NOAA NESDIS
EMEP
R. Scheffe
GEOSS
Eco-informatics
Accountability/indicatorsSIPs, nat.rules
designations
PHASE
PM research
Risk/exposureassessments
AQ forecastingPrograms
NAAQS setting
EPANOAA
NASA
NPS
USDA
DOE
PrivateSector
States/TribesRPO’s/Interstate
Academia
NARSTO
NAS, CAAACCASAC, OMB
Enviros
Organizations
CDC
Supersites
IMPROVE, NCorePM monit, PAMS
CASTNET
Lidarsystems
NADP Satellite data
Intensive studies
PM centers
Other networks:SEARCH, IADN..
Data sources
CMAQGEOS-CHEM
EmissionsMeteorology
Health/mort.records
The Scheffe Challenge: Organizations - Programs – Data: A Mess
Info System Challenges:
What’s the overall dependency
Information Flow
Forces and Controls on Data Flow
Cooperation, Competition, Co-Opetition
Relationship Between
Organizations - Programs – DataVersion 0.1
Goals $$Info needs, $$
Data need, $$
Judge, Decide, ActAnalyze, Report
Actionable Knowledge
Decision, Action
Public
Measure, Organize
Organized Data
Flow of InformationData systems organize the measurements and models and provide them to programs.
Programs analyze the data and provide actionable knowledge to organizations.
Organizations evaluate multiple information sources, make decisions and act.
Flow of ControlPublic and special interest groups set up organizations and provides them with funding
Organizations develop programs, define their scope, governance and funding
Programs satisfy their information needs by monitoring or by using other’s data
Data sources acquire the data for their parent programs and also expose them for reuse
System of SystemsGlobal Earth Observing System of Systems - GEOSS
Characteristics of System of Systems (SoS)
• Autonomous constituents managed/operated independently
• Independent evolution of each constituent
• SoS displays emergent behavior
Must recognize, manage, exploit the characteristics:
• No stakeholder has complete SoS insight
• Central control is limited; distributed control is essential
• Users, must be involved throughout the life of a SoS
GEOSS Architecture and Interoperability
Screencast: Information Landscape
Screencast: Info System Screencast
Screencast: DataFed Technologies
Screencast: DataFed Tools
KMZ: Google Earth-DataFed Mashup
GA Smoke Global Chem
The Transformational Effect of Networking
“Networking has led to an unprecedented surge of productivity” Time Magazine, Person of the Year 2006, YOU
• These are opportunities to enable Earth Science through more networking
• But many resistances to networking exist that need to be overcome
• Information has become the main driver of progress• Time and place are no longer barriers to participation and interaction • The Web has become a medium participation - ‘Web 2.0’ phenomenon
Networking Multiplies Value Creation
ApplicationData
1 User Stovepipe Value = 1 1 Data x 1 Program = 1
Enclosed Value-Creating Process - ‘Stovepipe’
ApplicationData
Application
Application
Application
Application
Stovepipe
1 User Stovepipe Value = 1 1 Data x 1 Program = 1
5 Uses of Data Value = 5 1 Data x 5 Program = 5
Networking Multiplies Value Creation
Merging data may creates new, unexpected opportunities
Not all data are equally valuable to all programs
1 User Stovepipe Value = 1 1 Data x 1 Program = 1
5 Uses of Data Value = 5 1 Data x 5 Program = 5
Open Network Value = 25 5 Data x 5 Program = 25
Data
Data
Data
Data
Data
StovepipeApplication
Application
Application
Application
Application
Networking Multiplies Value Creation
The Future
• AQ Science, Management – Pollutant Characterization (Obs-Model-Emission Integration)– Agile monitoring and assessment
• GEOSS, Collaboration, Informatics – The future is bright, too bright?– So many new things, so little time
• DataFed– Continue promoting standards-based networking– Enabling IS users create new, actionable knowledge faster – Move data flow maintenance from R/D to operational
Integrated observation-modeling complex – R. Scheffe
Land AQ Monitors
Total column depth(through Satellites)
AQ model results
Vertical Profiles
Integrated Observation- Modeling
Optimized PM2.5, O3
Characterizations
Health
Air management
ecosystems
Pollutant Characterization, Understanding
• Characterization – creating the best available pollutant pattern as distributed in space-time-parameter• Characterization - achievable by Reanalysis with the ‘best available’ model and assimilated observations• Understanding gained from the model processes and applying previous/tacit knowledge
Goal: Pollutant Characterization and Understanding
Models
Observations
Emissions
Reanalysis
Forward model with assimilated observations
Data Interpretation
Use of previous & tacit knowledge to explain data
GOAL:
Knowledge Creation
Characterization of pattern; understating of processes
Characterization
NAAMS: National Ambient Air Monitoring Strategy and NCore
…coordinated multi-pollutant real-time monitoring network
Public Public InformationInformation
Health/Exp. Assessment
Emissions Planning
AQ Trends and Accountability
Science Support
NAAQS
National Air Quality Information Integration
AQ Data Pool
National Air Quality Info Network
Re-examination of Data Access and processing Systems
Pooling of data/info resources for re-use in multiple applications; a la GEOSS
Sensing Revolution
Web 2.0
Summary
There is a slow ‘aligning of stars’ for integrating heterogeneous data
• System of Systems architecture is suitable for integrating data– Standard data access is a key interoperability protocol
– Heterogeneous data can be non-intrusively standardized by mediators
– Service-based software architecture delivers tailored products to diverse uses
• Federated data and shared web-based tools are in use– DataFed already includes over 100 datasets (emissions, ground, satellite)
– The system has been applied to EPA policy, regulatory and science development
• However, – DataFed is just one of the many mediator nodes, but these need to be connected
– Much more data would need to be federated
– HTAP model-data comparison would be an attractive use case
DataFed Applications (2002-2007)
ScienceMystery (Nitrate?) EventsData Integration (PM-Bext; NO2 Sat-Surf; AQ Event Detection Algorithms
AQ ManagementExceptional Event Analysis (EPA – N. Frank)Network Assessment (EPA – R. Scheffe)Fire-Smoke, Global Emissions (EPA – T. Keating)FASTNET, CATT Tools, S/R Analysis (RPO – R. Poirot)
IS Networking Infrastructure
NASA/ESIP Web Services, SAO (NASA – L. Friedl, K. Moe) GEOSS Interoperability Demos (Wash. U)HTAP Network, Integration (EPA – Keating)
FASTNET Report: 0409FebMystHaze (RPO – R. Poirot)
Mystery Winter Haze:
Natural? Nitrate/Sulfate? Stagnation?
Contributed by the FASNET Community, Sep. 2004
Correspondence to R Husar , R Poirot
Coordination Support by
Inter-RPO WG Fast Aerosol Sensing Tools for Natural Event Tracking, FASTNETNSF Collaboration Support for Aerosol Event Analysis
NASA REASON CoopEPA -OAQPS
AIRNOW PM25 - February
Sulfate-driven Jul-Aug peak
Feb-Mar peak, of unknown
origin
Data Fusion: AIRNOW PM25 - ASOS Bext
2004 July 20 14:00
July 21, 2004 July 22, 2004 July 23, 2004
ARINOW PM25 ARINOW PM25ARINOW PM25
ASOS RHBext
ASOS RHBext
ASOS RHBext
PM Event Detection from Time Series
Contributed by the FASNET Community, Sep. 2004Correspondence to R Husar , R Poirot
Coordination Support by
Inter-RPO WG Fast Aerosol Sensing Tools for Natural Event Tracking, FASTNETNSF Collaboration Support for Aerosol Event Analysis
NASA REASON CoopEPA -OAQPS
Event : Deviation > x*percentile
Speciated PM Network Assessment (EPA – R. Scheffe)
CIRA/ VIEWS
Database
CAPITA/ DataFed Database
Network Assessment
PPT
IMPROVE
EPA SPEC
CIRA Tools and Processes
DataFed Tools and Processes
Analysis Tools and Processes
Speciated Data Flow and Processing
EPA NCore Process
Evaluation, Feedback
Distributed Fire Data Sources (S. Falke, EPA, NASA)
Numerous state, regional, and national fire related databases and online access applications exist. The challenge is to bring them together, on-the-fly, without requiring substantial changes to the underlying systems.
Also need to access data sources that are not “Web-ready”.
BlueSkyRAINS
GeoMACWFAS
USGS
NOAAUMaryland
Next Process
Next Process
Aerosol Data
Collection IMP. EPA
Aerosol Sensors
Integration VIEWS
Integrated AerData
AEROSOL
Weather Data
Assimilate NWS
Gridded Meteor.
Trajectory ARL
Traject.Data
TRANSPORT
TrajData Cube
Aggreg. Traject.
AerData Cube
CATT
Aggreg.Aerosol
CATT-In CAPITA
CATT-In CAPITA
Combined Aerosol Trajectory Tool, CATT (RPO – R. Poirot)
Trajectory Browser
Kitty: Simple CATT
CATT Transport Analyzer
HTAP Data Network (EPA – T. Keating)
TF HTAP Workshop Forshungszentrum Juelich, Oct 17-19, 2007, Juelich, Germay
Application Examples for NOx Analysis
Collaborators:
Rudolf Husar, Washington U. St. Louis
Stefan Falke, Northrop, Wash U.
Greg Leptoukh, NASA, Goddard
Martin Schultz, FZJ, Juelich
GEOSS Interoperability Demos (Washington Univ.)
Beijing
BarcelonaDenver
Origin of Fine Dust Events over the US
Sulfate is local, no major spikes
Gobi dust transport in springSahara dust import in summer
Fine dust spikes over the entire US are mainly from intercontinental transport
Air Quality Management System: Components and Functions
Public
Analyzing
Interpreting Evaluating Separating Synthesizing
Organizing
Quality controlFormattingDocumentingDisplaying
Deciding
Evaluate optionsMatching goals CompromisingChoosing
Data Manager, Organizer
Technical Analysts, Program Manager
Policy Analysts, Decision Maker
Valu
e A
dd
ing
P
rocesses
Human Agents
Decision Support System (DSS)
The primary purpose of data systems is to mediate between data providers and programs/projects
Programs perform analysis for Orgs., the DSS is within programs
The big decisions of societal importance are done by Organizations
(This needs more wisdom from the practioners)
Flow of Data and Usage Control
Data
Control
Requesting Information
Providing Information
Sensors Acquisition processing
User Agencie
s
User Progra
ms
NAAQS SIPs Forecast GEOSS …
Info SystemNegotiating Space
Domain ProcessingData Sharing
Std
. In
terf
ace
Gen. ProcessingS
td.
Inte
rface
Data
Control
Reports
Reporting
Obs. & Models Decision Support System
DataFed Tools - Subset
Consoles: Data from diverse sources are displayed to create a rich context for exploration and analysis
CATT: Combined Aerosol Trajectory Tool for the browsing backtrajectories for specified chemical conditions
Viewer: General purpose spatio-temporal data browser and view editor applicable for all DataFed datasets
Summary
• Global Monitoring - Modeling Revolution – ‘May you live in interesting times’– We are in the midst of an observational revolution (satellites, monitoring networks).– The global distribution and transport of some pollutants can be monitored daily– Global models are maturing into effective analytical and predictive tools
• Results to Date: – Compelling evidence for global-scale transport of PM and Ozone– Qualitative evidence of ‘extra-jurisdictional’ impact on the US air quality– Potential for quantification of natural and non-US impact
• Such massive job will require:– International, interagency, interdisciplinary collaboration.– Open flow of data/knowledge– Scientific ‘value-adding chains’
FASTNET and DataFedFASTNET (Fast Aerosol Sensing Tools for Natural Event Tracking) an open communal information sharing facility to study aerosol events, including detection, tracking and impact on PM and haze.
The main asset of FASTNET is the community of data analysts, modelers, managers participating in the production of actionable knowledge from data and models
The community is supported by a non-intrusive data integration infrastructure based on Internet standards (web services) and a set of web-tools evolving under the federated data system, DataFed
DataFed is supported by its community and is under the umbrella of the interagency Earth Science Information Partners, ESIP (NASA, NOAA and EPA)
OGC WCS Data Access Protocol
GEOSS Provides SOA for Coupling for Autonomous Nodes Facilitates Publishing, Finding and Accessing Data
Emerging Air Quality Data Flow Network
Application of OGC WCS Data Access Protocol
Regardless of the data location, data type and format,
• the parameter-space-time query is the same
• the return is in user selectable format from the offerings
Coverage=THEEDDS.T& BBOX=-126,24,-65,52,0,0 &TIME=2002-07-07/2002-07-07 &FORMAT=NetCDFCoverage=SEAW.Refl& BBOX=-126,24,-65,52,0,0 &TIME=2002-07-07/2002-07-07 &FORMAT=GeoTIFFCoverage=SURF.Bext& BBOX=-126,24,-65,52,0,0 &TIME=2002-07-07/2002-07-07 &FORMAT=NetCDF-table
Grid Image Station Data
Parameter Bounding Box Time Range Out Format
Web 1.0 -> Web 2.0 Transformation
• The Web is being transformed: It is becoming more participatory
• Its content is increasingly generated and distributed by individuals
• See the explosive growth of wikies, picture-sharing, blogs, Facebook
• This architectural, technological and cultural change is Web 2.0
• Web 2.O is good for AtmosphericScience community since it allows
– Better harvesting of current knowledge– Collaborative creation new knowledge.
Distribution of ResponsibilityDistribution of Responsibility
Distributed Responsibility DataFedDistributed Responsibility DataFed
The data lies with the data providersThe wrappers and mediators with DataFed communityApplication programs with end user Data discovery with data & service registries
The Information Interoperability Stack
Imagine…More Shared Obs & Models…. On Your Fingertips or Google Earth..
2007++More Global Data & Models
2007Global Data & Models
Regional Haze Rule: Natural Aerosol
Looking ahead to reach natural conditions … in 60+ years!!!
Asian Dust Cloud over N. America
On April 27, 1998 the dust cloud arrived in North America.
Regional average PM10 concentrations increased to 65 mg/m3
In Washington State, PM10 concentrations exceeded 100 mg/m3
Asian Dust 100 g/m3
Hourly PM10
Aircraft Detection of Siberian Forrest Smoke near Seattle, WA
Jaffe et. al., 2003