comparing aircraft measurements of atmospheric compounds with a regional photochemical model
DESCRIPTION
Comparing Aircraft Measurements of Atmospheric Compounds with a Regional Photochemical Model. by Jennifer Schiffelbein CE 394K GISWR Fall 2003. Outline. Description of Model and Aircraft Data TexAQS 2000 (Southeast Texas) Completed Work Creating grids & polygons with ArcInfo - PowerPoint PPT PresentationTRANSCRIPT
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Comparing Aircraft Measurements of Atmospheric
Compounds with a Regional Photochemical Model
by Jennifer SchiffelbeinCE 394K GISWR
Fall 2003
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Outline Description of Model and Aircraft DataDescription of Model and Aircraft Data
– TexAQS 2000 (Southeast Texas)TexAQS 2000 (Southeast Texas)
Completed WorkCompleted Work– Creating grids & polygons with ArcInfoCreating grids & polygons with ArcInfo– CAMx ProjectionCAMx Projection
Future WorkFuture Work– Spatial & Temporal issuesSpatial & Temporal issues– InterpolationInterpolation
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Description of Data:Aircraft
Electra aircraft Electra aircraft – NOAANOAA
Data collectedData collected– Position (GPS x,y,z)Position (GPS x,y,z)
– Air analysis: CO, NOx, OAir analysis: CO, NOx, O33, PM, VOCs….., PM, VOCs…..
– MeteorologicalMeteorological Data frequency: 1 per secondData frequency: 1 per second Duration: 6-7 hours (~26,000 points!)Duration: 6-7 hours (~26,000 points!)
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Description of Data:Model
Predicts chemistry of atmosphere over Predicts chemistry of atmosphere over timetime
Inputs: emissions, temperature, Inputs: emissions, temperature, meteorology…meteorology…
Time scale: 1 hourTime scale: 1 hour Structure: 3-D gridStructure: 3-D grid
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Description of Data:Model
StructureStructure– Chosen domain: Houston/Galveston Chosen domain: Houston/Galveston
(HG)(HG)– Box = 1 km x 1 km x variable height Box = 1 km x 1 km x variable height
(m)(m)– Horizontal extent: 74 cells x 74 cellsHorizontal extent: 74 cells x 74 cells– Vertical extent: 21 layers from 0 Vertical extent: 21 layers from 0
(ground) to 4106 m(ground) to 4106 m
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Completed Work Generate grid (“fishnet”)Generate grid (“fishnet”)
Example: 2x3 gridExample: 2x3 grid– ArcGIS/ArcInfo Workstation/ArcArcGIS/ArcInfo Workstation/Arc
Arc:Arc: workspace mydirectory workspace mydirectory
Arc:Arc: generate generate stockingsstockings
Generate:Generate: fishnet fishnetFishnet Origin Coordinate (X,Y):Fishnet Origin Coordinate (X,Y): 0,0 0,0Y-Axis Coordinate (X,Y):Y-Axis Coordinate (X,Y): 0,2 0,2Cell Size (width, height):Cell Size (width, height): 1,1 1,1Number of Rows, Columns:Number of Rows, Columns: 2,3 2,3Generate:Generate: quit quit
**ItalicsItalics = prompts = prompts*mydirectory = z:\uteid, or c:\mystuff*mydirectory = z:\uteid, or c:\mystuff**red textred text = name of file you must specify = name of file you must specify
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Completed Work
Generate gridGenerate grid
– Make map displayableMake map displayableArc:Arc: clean clean stockings drawerstockings drawerArc:Arc: build build drawerdrawer poly polyArc: addxy Arc: addxy drawerdrawerArc: Arc: quitquit (to close Arc window)(to close Arc window)
-Directory “drawer” contains “polygon” grid shapefile-Directory “drawer” contains “polygon” grid shapefile
-“addxy” assigns x-y coordinate to center of each -“addxy” assigns x-y coordinate to center of each grid cellgrid cell**ItalicsItalics = prompts = prompts*mydirectory = z:\uteid, or c:\mystuff*mydirectory = z:\uteid, or c:\mystuff**red textred text = name of file you must specify = name of file you must specify
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Completed Work
Generate gridGenerate grid– Example: 2x3 grid resultExample: 2x3 grid result
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Completed Work
Generate polygonGenerate polygonExample: 1000x1000 boxExample: 1000x1000 box
Arc:Arc: generate generate bigboxbigboxGenerate:Generate: polygons polygons::ID, {AUTO | X,Y}:ID, {AUTO | X,Y}: 1, auto 1, autoX,Y:X,Y: -1000,0; -1000, 1000; 0,1000; 0,0 -1000,0; -1000, 1000; 0,1000; 0,0X,Y:X,Y: end endID, {AUTO | X,Y}:ID, {AUTO | X,Y}: end endGenerate:Generate: quit quit
*Clean “bigbox” & build as with grid*Clean “bigbox” & build as with grid
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Completed Work
Generate polygonGenerate polygon
Example resultsExample results
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Completed Work CAMx ProjectionCAMx Projection
– Projection type: Lambert Conformal ConicProjection type: Lambert Conformal Conic– First true latitude: 30°NFirst true latitude: 30°N– Second true latitude: 60°NSecond true latitude: 60°N– Latitude of origin: 40°NLatitude of origin: 40°N– Central meridian: 100°WCentral meridian: 100°W
*Earth datum: Perfect sphere, *Earth datum: Perfect sphere, radius = 6370kmradius = 6370km
*BUT ArcGIS only offers r ~6371 km*BUT ArcGIS only offers r ~6371 km-exact projection difficult to create-exact projection difficult to create
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Future Work
Spatial issues:Spatial issues:
*Filter aircraft data points by *Filter aircraft data points by
1.) Is aircraft within HG domain?1.) Is aircraft within HG domain?
2.) Which vertical layer is aircraft in?2.) Which vertical layer is aircraft in?
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Future Work Spatial issues:Spatial issues:
1.) Exclude all points outside domain1.) Exclude all points outside domain
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Future Work
Spatial issue: Spatial issue:
2.) Which vertical layer is aircraft in?2.) Which vertical layer is aircraft in?
-Horizontal slice-Horizontal slice -Vertical slice-Vertical slice
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Future Work Spatial issues:Spatial issues:
2.) Which vertical layer?2.) Which vertical layer?
Aircraft Altitude (sample)
0
1000
2000
3000
4000
5000
15.5 16 16.5 17
time (hours past midnight)
alti
tud
e (m
)
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Future Work
Spatial issues:Spatial issues: 2.) Which vertical layer?2.) Which vertical layer?
– Decisiion – Assign points +½(hDecisiion – Assign points +½(hi+1i+1-h-hii) & ) & -½(h-½(hii-h-hi-1i-1) to layer at h) to layer at hii
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Future Work
Temporal issue:Temporal issue:– Model hourly species concentrationModel hourly species concentration
Example: 1:00 pm, CO conc. = 50 ppbExample: 1:00 pm, CO conc. = 50 ppb
2:00 pm, CO conc. = 40 ppb2:00 pm, CO conc. = 40 ppb
Aircraft second by second concentrtionAircraft second by second concentrtionExample: 1:32:08 pm, CO conc. = 46 ppbExample: 1:32:08 pm, CO conc. = 46 ppb
How assign time intervals for comparison?How assign time intervals for comparison?- Aircraft points with time betweenAircraft points with time between
*1:31 to 2:30 with 2:00 model*1:31 to 2:30 with 2:00 model
*2:31 to 3:30 with 3:00 model*2:31 to 3:30 with 3:00 model
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Future Work
InterpolationInterpolation– Spatial Analyst – Interpolate to RasterSpatial Analyst – Interpolate to Raster
*Try & compare 2-3 methods*Try & compare 2-3 methods
*Consider ~small, spatially concentrated points for *Consider ~small, spatially concentrated points for each time interval and vertical layereach time interval and vertical layer
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Concluding Remarks
Complex problemComplex problem– 3 dimensions and time must be 3 dimensions and time must be
consideredconsidered Large volume of dataLarge volume of data
– 74x74 cells = 5476 grid cells per layer74x74 cells = 5476 grid cells per layer– ~26,000 aircraft data points~26,000 aircraft data points
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