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

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)

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]

A Scenario during TRACE-P Is value-added by forecasts of additional species?

CO

NOx

O3

STEM Forecast for ITCT2K2

The locations with maximumO3 and CO may not be the same

Predicted sensitivity of O3 to VOCs and NOx

VOC-limited

NOx-limited

Influence functions (over Cheju for O3 concentrations at 0:0:00 UT, 3/07/01) wrt O3, NO2, HCHO at -48, -24, -12 hr

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

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

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

Examples from ITCT 2K2

• May 05 Flight– Large long-range transport (LRT) event (CO)

• May 10 Flight– Stratospheric intrusion (O3)

May 05 Flight, CO (ppbv)

May 05 Flight, CO (ppbv)

May 10 Flight, Ozone (ppbv)

May 10 Flight, Ozone (ppbv)

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)

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

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?

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.

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

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

Through a NSF ITR Grant we are developing data assimilation tools – we have a 3-d version ready for application

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

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,…

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

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

May 05 Flight

May 10 Flight