flight planning
DESCRIPTION
Forecasting Analysis. Flight Planning. Quick-look. Post-Mission. Air Quality. Thoughts on the Summer 2004 Experiments UI/CGRER Focus : Improving Forecasting and Analysis through Closer Integration of Observations and Models. Test: - PowerPoint PPT PresentationTRANSCRIPT
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Thoughts on the Summer 2004 Experiments
UI/CGRER Focus: Improving Forecasting and Analysis through Closer Integration of
Observations and ModelsFlight Planning
Air Quality Quick-look
Post-Mission
Test:
•Our ability to forecast 4-dimensional distributions of ozone and PM
•The utility of forecasts of ozone, fine particles in flight planning and quick-look analysis
•The utility of why-cast products (e.g., O3-production, VOC vs NOx limited regions, influence functions, hydrocarbon reactivity….) in flight planning and analysis and air quality forecasting
•Our ability to assimilate surface chemical observations into the forecasts; the impact of assimilation on the forecasts (for a sub-region; e.g., the NE)
•Targeted measurements that explore the concept of aircraft as “mobile super-sites”
Forecasting Analysis
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Fine Chloride
Fine Sulfate
Total Extinction
Fine Nitrate
We Plan to Forecast Size + Chemically Resolved Aerosol Products STEM simulations with on-line SCAPE compared to measurements of ACE-ASIA C-130 Flight 6
Observations from PILS (Weber)
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2 2.4 2.8 3.2 3.6 4TIME (GMT)
5 2
5 6
6 0
6 4
6 8
O3
(pp
bv
)
0
400
800
1200
1600
2000
Alt
itu
de
(m)
ObservedNORMALNOAODCLEARSKYFlight Altitude
Impact of aerosols on photochemistry
[Clarke]
[Avery]
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A Scenario during TRACE-P Is value-added by forecasts of additional species?
CO
NOx
O3
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STEM Forecast for ITCT2K2
The locations with maximumO3 and CO may not be the same
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Predicted sensitivity of O3 to VOCs and NOx
VOC-limited
NOx-limited
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Influence functions (over Cheju for O3 concentrations at 0:0:00 UT, 3/07/01) wrt O3, NO2, HCHO at -48, -24, -12 hr
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Combining Back Trajectory and CMB Analysis to Estimate Contributions to Fossil, Biofuel and Open
Biomass Burning to Airmasses
2-D and 3-D analysis features for DC8 flight8 (March 9th)
Left: same as previous figure, but (light blue: 3.4GMT, purple: 3.3GMT, red: 2.5GMT); Right: same as uppermost figure.
Fly by animation
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MOZART in ITCT 2K2• Forecast mode
– Driven by NCEP AVN analysis + forecast– Run at NCAR once daily, output every 6 hours– Full gas-phase O3 chemistry, “regional tracers”
• Analysis mode– Run after campaign, AVN analysis, higher res.– O3 chemistry + tagged regional CO– Output every 3 hours
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Lessons from ITCT 2K2
• Importance of using timely met. forecasts
• Comparison of chemical transport model forecasts
• Identification of met. features associated with pollution / long-range transport
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Examples from ITCT 2K2
• May 05 Flight– Large long-range transport (LRT) event (CO)
• May 10 Flight– Stratospheric intrusion (O3)
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May 05 Flight, CO (ppbv)
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May 05 Flight, CO (ppbv)
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May 10 Flight, Ozone (ppbv)
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May 10 Flight, Ozone (ppbv)
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MOZART for ITCT 2K4• Aerosol simulation
– Sulfate, nitrate, ammonium, black carbon, organic carbon now included– Mineral dust, sea salt being added
• Full O3 photochemistry plus tagged CO species
• Run at ~2 deg resolution [driven by NCEP GFS ~ 0.5 deg]
• Run forecasts 4 times per day out to 84 hours
• Output every 3 hours
• Automated plots of forecast results posted to web site
• Couple with regional model (STEM)
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Issues for ITCT 2K4 (vs. 2K2)• Long-range transport (LRT) less important
– Should be “easier” for models
– But, less lead time
• Emission inventories should be more reliable• More emphasis on aerosols
– Washout parameterization
– Test understanding of organic aerosols
• Nighttime chemistry
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Science Questions for ITCT 2K4• Transport
– What other U.S. source regions impact pollutant levels in New England?
– What are the major export pathways during summer?– Are these pathways well-simulated in models?
• Chemical transformations– Can we simulate the chemical evolution of air masses from source
regions to the North Atlantic? (e.g., O3 production, NOy partitioning)
• Aerosols– What is the composition of aerosols transported from North America
to the North Atlantic?– Are aerosol aging and removal processes well-simulated in models?– What are the main sources of organic aerosols?
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Development of a General Computational Framework for the Optimal Integration
of Atmospheric Chemical Transport Models and Measurements Using Adjoints
(NSF ITR/AP&IM 0205198 – Started Fall 2002)
A collaboration between:
Greg Carmichael (Dept. of Chem. Eng., U. Iowa)
Adrian Sandu (Dept. of Comp. Sci., Mich. Inst. Tech.)
John Seinfeld (Dept. Chem. Eng., Cal. Tech.)
Tad Anderson (Dept. Atmos. Sci., U. Washington)
Peter Hess (Atmos. Chem., NCAR)
Dacian Daescu (Inst. of Appl. Math., U. Minn.)
Goal:
To develop general computational tools, and associated software, for assimilation of atmospheric chemical and optical measurements into chemical transport models (CTMs). These tools are to be developed so that users need not be experts in adjoint modeling and optimization theory.
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Approach: •Develop efficient algorithms for 4D-Var data assimilation in CTMs;
•Develop software support tools for the construction of CTM adjoints;
•Apply these techniques to: (a) analysis of emission control strategies; (b) integration of measurements and models to produce optimalanalysis data sets for field experiments; (c) inverse analyses to produce a better estimate of emissions;(d) design observation strategies to improve chemical forecasting
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Iowa/GFDL/Argonne STEM Model Deployment
MesoscaleMeteorological Model
(RAMS or MM5)
MOZART Global Chemical Transport Model
STEM Prediction Model with on-line
TUV & SCAPE
Anthropogenic & biomass burning Emissions
TOMS O3
Chemistry & TransportAnalysis
Meteorological Dependent Emissions
(biogenic, dust, sea salt)
STEM Tracer Model (classified tracers for
regional and emission types)
STEM Data-Assimilation
Model
Observations
Airmasses andtheir age & intensity
Analysis
Influence FunctionsEmission Biases
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Through a NSF ITR Grant we are developing data assimilation tools – we have a 3-d version ready for application
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Thoughts on the Summer 2004 Experiments
UI/CGRER Focus: Improving Forecasting and Analysis through Closer Integration of
Observations and ModelsFlight Planning
Air Quality Quick-look
Post-Mission
Test:
•Our ability to forecast 4-dimensional distributions of ozone and PM
•The utility of forecasts of ozone, fine particles in flight planning and quick-look analysis
•The utility of why-cast products (e.g., O3-production, VOC vs NOx limited regions, influence functions, hydrocarbon reactivity….) in flight planning and analysis and air quality forecasting
•Our ability to assimilate surface chemical observations into the forecasts; the impact of assimilation on the forecasts (for a sub-region; e.g., the NE)
•Targeted measurements that explore the concept of aircraft as “mobile super-sites”
Forecasting Analysis
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O f t e n ,
[ G l o b a l , I n d i a , C h i n a , … ]
B I O M A S S B U R N I N G
E N E R G Y U S E
B C E M I S S I O N F A C T O R S
S O U R C E T E S T I N G
B C E M I S S I O N S
B C A N A L Y S I S M E T H O D S
A T M O S P H E R I C M O D E L I N G
M O N I T O R I N G C A M P A I G N S
C A L C U L A T E DB C
C O N C E N T R A T I O N S
O B S E R V E DB C
C O N C E N T R A T I O N S
( )( )
( )C A L C
O B S
2 4
T h e B C p r o b l e m
We Plan to Look for Ways to Improve the Quality of the Emission Inventories by Close Integration with Modeling
Activities
Anticipated Activities:
Refine PM Inventories
Refine/Add species to aid in analysis (e.g., OCS, halocarbons, ethanol…). We look for input on species of interest.
Possible other activities: trends, consistent N-Hemisphere inventory, forecasts of emissions,…
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Surface reflection
Ice cloud
Water cloud
EP/TOMS Ozone (Dobson)
SCAPE AerosolEquilibriumModuleAerosols
absorption by gas-phase species O3, SO2 and NO2
Inputs from STEM 3-D field
STEM TOP
O3 (Dobson) below STEM top
TUV TOP80km
Overtop O3 =
Heterogeneous reactions on BC for NO2, O3, SO2, HNO3
Outputs:
Aerosol composition (size-resolved),
Aerosol heterogeneous influences, J-values
STEM schematics for on-line TUV and on-line SCAPE
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ITCT2K2 Post-Run with MOZART Boundary Conditions
Top and Lateral Top and Lateral Boundary Conditions Boundary Conditions from MOZART II from MOZART II every 3 hoursevery 3 hours
STEM 80x70 domain
13.4km
mapped species: O3, CO, ethane, ethene, propane, propene, ethyne, HCHO, CH3CHO, H2O2, PAN, MPAN, isoprene, NO, NO2, HNO3, HNO4, NO3, and MVK
Lateral boundary conditions of other species, included SO2 and sulfate still come from the large-scale CFORS tracer model
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May 05 Flight
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May 10 Flight