Download 040715CATTReporttmp

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Microsoft SQL Server wikipedia , lookup

Clusterpoint wikipedia , lookup

Object-relational impedance mismatch wikipedia , lookup

Functional Database Model wikipedia , lookup

Database model wikipedia , lookup

Transcript
Combined Aerosol Trajectory Tool
CATT
Indicates the origin of air masses for specific aerosol condition
MANE-VU & MRPO
Tools in support of Inter-RPO Data Analysis Workgroup
CAPITA
Trajectory Aggregator – User Defined Filter
Kitty – Simple Combined Aggregator
• Back trajectory coming from one site
CATT – Combined Aerosol Trajectory Aggregator
Differing TrajPoint weight combinations
• These were all created using the CATT Aerosol Trajectory Aggregator
Fine Particle (PM 2.5) – Decreasing concentration limit
Combined Aerosol Trajectory Tool
(CATT)
Example: Airmass origin for high (2.5*average) nitrate
Boundary Waters
Doly Sods
Lye Brook
Smoky Mtn.
Triangulation indicates nitrate source in the corn belt
CATT Tool User Interface
CATT:
Single web page
Map View:
Superimposed GIS
layers
Rendering
Zoom, Pan, Point
Color, Size, Visibility
Layer Controls:
Location selector
Parameter selector
Filter conditions
Direction of Dust Origin at 5 IMPROVE Sites
High ‘dust’ concentration at 5 sites
indicate the same airmass pathway from
the tropical Atlantic
NOAA ARL
ATAD
Weather Serv.
Ad hoc Data Processing Value Chain
ATAD Traject
Gebhart (2002)
Upper Air Data
PMF Tool
Pareto (2001)
PMF “Sources”
NPS-CIRA
Coutant (2002)
IMPROVEData
CATT Tool
Aggregation
Husar (2003)
Poirot (2003)
SQL Queries
SELECT Lat as lat,
Lon as lon,
Loc_Code as loc_code,
SUM(ResTime) AS [VALUE]
FROM
dTrajResTime
WHERE ([Date] IN
(SELECT datetime
FROM dSourceApp
WHERE (Loc_Code = 'loc_code')
sql_filter_clause))
GROUP BY GridCode, Lat, Lon, Loc_Code
ORDER BY Lon ASC
Settings that are unique to a specific
query are designated by red text
Query (filter) result: List of dates the satisfy the chemical filter conditions
Trajectory and Residence Time Grid
Residence time and ATAD trajectory
data superimposed for June 1, 2000.
Residence time aggregate (sum) for a
range of dates
Airmass Source Regions by Season
e.g. Sum Residence Time for Loc=LYBR, Date between June-Sept
Lye Brook, DJF
Gr Smoky Mtn, JJA
Lye Brook, JJA
Gr Smoky Mtn, JJA
Seasonal Incremental Probability
Year
DJF
MAM
JJA
SON
Secular Changes: 1988-94; 1995-2000
1988-2000
1994-2000
1988-1994
Transport Probability Metrics
• The transport metric is calculated from two residence time grids, one
for all trajectories and another for trajectories on selected (filtered
days). Both residence time grids are normalized by the sum of all
resdence times in all grid cells:
pijf=rij/SS rij
pija=rij/SS rij
• pijf, is the filtered and pija is the unfiltered residence time probabilitiy
that an airmasses passes through a specific grid. There is a choice of
transport probaility metrics:
• The Incremental Residence Time Probability (IRTP) proposed by
Poirot et al., 2001 is obtained by subtracting the chemically filtered
grid from the unfiltered residence time grid, IRTP = pijf - pija
• The other metric is the Potential Source Contribution Function (PSCF)
proposed by Hopke et al., 19xx which is the ratio of the filtered and
unfiltered residence time probabilities, PSCF = pijf / pija
Transport Metric Selection
• Currently, there is a choice of two different transport probability metrics:
• Incremental Residence Time Probability (IRTP) proposed by Poirot et
al., 2001 is the difference between the chemically filtered and unfiltered
residence time probalbilities. Positive values of IRTP in a grid indicates
more than average liekihood of transport; (red); negative IRTP values
(blue) represent less than average likeihood of transport.
• Potential Source Contribution Function (PSCF) proposed by Hopke et
al., 19?? is computed as the ratio of the filtered and unfiltered residence
time probabilities. Higher values of PSCF is indicative of inreased source
contribution.
• Greens Metric, Clustering….etc
• The desired metric is selected through a dialog box invoked by clicking
on the right-most button in the TRAJ_CHEM layer.
Incremental Transport Probability
Results
Combined Aerosol Trajectory Tool
(CATT)
CATT Presentation and Workgroup Discussions
Project Status/Summary
Phase II Completed
1. Relational Database of PMF/UNMIX and trajectory data: Complete
2. Develop specific SQL filtering and aggregation queries
• Chemical filtering/aggregation: Developed
• Trajectory filtering/aggregation: Developed
• Paired Chemical/Trajectory data: Developed, needs user input, testing,
feedback
3. Graphic interface for user input (query) and for data output: Developed,
needs user input, testing, more feedback
Not There!
Further
Analysis
When?
Where?
The new CATT: A Community Tool!
GIS
Part of an Analysis Value Chain
Grid Processing
Emission
Why?
There!
Comparison
How?
AEROSOL
Collection
IMP. EPA
Aerosol
Sensors
Integration
VIEWS
Aerosol
Data
CATT-In
CAPITA
Integrated
AerData
AerData
Cube
Aggreg.
Aerosol
Next
Process
CATT
Weather
Data
Gridded
Meteor.
Assimilate
NWS
TRANSPORT
Traject.
Data
Trajectory
ARL
TrajData
Cube
CATT-In
CAPITA
Aggreg.
Traject.
Next
Process
New CATT Components:
Chemical filter
CATT-In
CAPITA
Accomplished through queries to chemical data sets.
AerData
Cube
Aggreg.
Aerosol
The output a list of “qualified” dates for a specific location (s).
CATT
TrajData
Cube
CATT-In
CAPITA
Aggreg.
Traject.
Trajectory aggregator
Receives the list of dates for a specific location
Performs the trajectory/restime aggregation
Yield transport pattern for specific receptor location and
chemical filter conditions.
Trajectory Aggregator Tool Inputs:
–
–
–
–
–
Receptor location. Single location; multiple receptors; weighed multi-site
Receptor times. Time range for each site
Temporal filter/weight conditions. Date range; specific dates; weights for each date
Trajectory input files. Pre-computed or on the fly calculated (e.g. HYSPLIT, ATAD etc)
Trajectory aggregation metrics. Endpoint counts, residence time, incr. probability
TAT Output:
–
–
XMLGrid, GIS layers, ASCII point
Rendered contour images of transport metric
Project Extension Proposal to MANE_VU:
Extensions to the CATT Analysis Tool
1.
Flexible connectivity to chemical datasets, especially to VIEWS
2.
Flexible import of pre-calculated back-trajectory data
3.
Additional chemical filtering and trajectory aggregation algorithms
4.
Spatial interpolation and rendering (contouring) of point data
5.
CATT server hardware and software installation and maintenance
CATT Extension 1: VIEWS and other Aerosol Datasets
Background:
A combined aerosol trajectory aggregation tool, CATT, has been developed for easy aggregation and browsing
of airmass histories associated with specific aerosol conditions. The CATT tool, is now supported
(MANEVU/MRPO) for 16 stations and for pre-calculated residence times.
Proposal:
We propose to extend the CATT tool by allowing the use of the entire VIEWS chemical database and other
remotely accessible datasets to set the aerosol filter conditions.
Implementation and Status:
The technologies or remotely accessing the VIEWS and other databases and performing chemical filtering
queries to VIEWS has been tested for feasibility. This extension to CATT has was option on the Phase II
contract but funds were not available. Husar will lead this effort in close cooperation with B. Schichtel of
CIRA/VIEWS.
Deliverables:
The main deliverable of this sub-project is a fully functioning CATT aerosol transport analysis tool applicable
to the entire VIEWS database as well as to other chemical/trajectory data pairs.
Extending CATT to VIEWS
Current MANEVU/MRPO Project
Prepared by
Battelle and Sonoma Tech. Inc.
Proposed Extension to VIEWS
‘On the fly trajectory aggregation for 150+
VIEWS sites (supported by EPA- CATTTAT)
16 sites
180+ VIEWS sites over the
entire US; 100+ ‘species’
Typical Source Profiles
15 ‘species’
CATT Tool Implementation
•
Further information about CATT is
available , including tesing.
•
The tool displays the incremental
transport probability for specified
query conditions
Query Conditions
Combined Aerosol Trajectory Tool - CATT
CATT Extension 2: Trajectory Data Connectivity
Background:
The extended CATT tool should be applicable to an evolving list of datasets. Each new dataset consists of an
aerosol monitoring dataset and a companion trajectory dataset. Thus, for each new CATT dataset, the
trajectory data will be submitted to the CATT system separately.
Proposal:
We propose the development of a procedure for easy import of pre-computed trajectory data into the CATT
trajectory database. At a minimum, the trajectory import facility will include ATAD and HYSPLIT
trajectory formats.
Implementation and Status:
The trajectory import facility does not exists. In the past, trajectory import to CATT was executed through
special one-of-a kind program. The new, semi-automated import facility will facilitate data transfer through
FTP and subsequent import to CATT. The task will be executed by the CAPITA database/network
manager.
Deliverables:
The main deliverable of this sub-project is a functioning import facility for ATAD and HYSPLIT and possibly
other data formats.
CATT Extension 3: Filtering and Aggregation Algorithms
Background:
CATT is an exploratory tool to examine the relationship between aerosol pattern and the associated transport
conditions. An n evolving set of algorithms that evaluates that relationship.
Proposal:
We propose to develop a flexible framework for adding new aerosol filtering and trajectory aggregation
algorithms. The initial algorithms will include, incremental probability, residence time ratio, aerosolweighed residence time, trajectory clustering, followed by emerging new algorithms. Some schemes will be
implemented in multi-receptor mode.
Implementation and Status:
Currently, the incremental probability and residence time ratio algorithms are implanted in the CATT tool.
Deliverables:
Extension 3 of the CATT tool will implement the aerosol-weighed residence time, trajectory clustering
algorithms. At least two additional new filtering/aggregation schemes will be added to the tool.
CATT Extension 4: Spatial Interpolation and Rendering
Background:
A tool for transforming point measurement data to a continuous surface would aid the analysis of CATT
transport as well as VIEWS chemical data. In particular, gridding/contouring will allow comparison
with other data from monitoring, emissions, satellite as well as with model results/
Proposal:
We propose to incorporate spatial interpolation and rendering facilities into the CATT tool. The
Gridder/Contourer tool will be applicable to the spatial datasets from CATT, VIEWS as well as other
spatial point data.
Implementation and Status:
The gridder/contourer technology has been developed at CAPITA over the past 15 years. Stefan Falke,
who did his PhD dissertation on spatial interpolation will lead the effort.
Deliverables:
The deliverable of this sub-task is is a web-based Gridder/Contourer incorporated in CATT. The outputs
from the Gridder/Contour will be suitable for import into GIS and other processing/rendering
software.
Spatial Interpolation and Rendering
Site Code
1534
1538
1535
1540
108
107
1142
1135
1137
1143
102
1144
1138
1140
88
89
2388
2380
2396
2392
2393
2397
83
2410
2394
Lat
Lon
21.3291
21.3966
21.3102
20.7808
20.8086
19.4309
61.533
61.2066
61.1822
61.5341
63.7233
63.7258
64.8411
58.3592
41.56
42.5519
42.4319
44.5883
44.6156
44.0263
43.8338
44.9432
48.0065
45.5182
44.0538
-158.093
-157.972
-157.858
-156.446
-156.282
-155.258
-150.25
-149.821
-149.814
-149.032
-148.968
-148.963
-147.72
-134.509
-124.086
-124.059
-123.346
-123.274
-123.092
-123.084
-123.035
-123.006
-122.973
-122.967
-122.938
VALUE
Spatial Interpolation Settings
4.60
4.10
4.00
6.50
4.09
2.78
4.90
5.10
5.90
5.40
4.56
5.80
7.40
5.20
Point Rendering
PM25 Conc.
6.75
8.70
6.10
7.20
9.00
8.80
7.80
5.70
9.30
The spatial interpolation operator transforms a data
table to a gridded map using nearby measurement data.
The gridding and contouring of the selected data is
done ‘on the fly’ by the user
Contour Rendering
Grid PM25
PM25 Conc.
Interpolate
Gridding: Accounting for Data Density
The advanced spatial interpolation algorithm accounts for the variations in
point data density inherent in air quality monitoring networks.
The resulting interpolated estimates are more representative of the urban
and rural differences in air pollutant concentrations.
Low Point Data Density
High Point Data Density
Rendering: Rectangular, Contour, Lines
A flexible display rendering of gridded data will be implemented to accommodate
different applications.
The flexibility enables clearer presentation and easier comparison with other data.
Rectangular Grid Cells
Contoured Grid Cells
Contoured Grid Lines
CATT Extension 5: CATT Server Maintenance
Background:
The web-based CATT tool needs to reside on a web server, consisting of three parts: (1) SQL server that
manages the relational database for chemical and trajectory data (MS SQL Server); (2) General-purpose
web server to respond to HTTP queries (MS IIS); (3) CATT analysis server for the computation and
presentation of CATT analysis.
Proposal:
This task covers the installation and maintenance of the CATT web-delivery delivery system (SQL Server,
Web Server, CATT Server) for one year.
Implementation and Status:
The server hardware and software used in Phase II CATT project is currently operational. For this CATTextension, all 3 servers will be upgraded to some extent, including the hardware. The CATT system will
be maintained by Kari Hojarvi at CAPITA..
Deliverables:
A web-based CATT tool will be upgraded, installed and maintained for one year by CAPITA staff.
CATT Server Hardware and VIEWS Connectivity
Auxiliary Data
VOYGER Browser
CAPITA Server
Data Replication
CATT server
connected to CIRA and
CAPITA
VIEWS &
Auxiliary
Data
CATT
Data Replication
Software
Replication
Analysis & Aux. Data Viewer
Analysis
Tools &
Delivery
Analysis Server
VIEWS Viewer
CIRA Server
VIEWS
Data
VIEWS
Business Logic