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Developing Daily Biomass Burning Inventories from Satellite Observations and MOPITT Observations of CO during TRACE P. Colette Heald Advisor: Daniel Jacob. IDS Meeting: Duke University April 26, 2002. Satellite Observation of Fires and Biomass Burning Emission Inventories. MOTIVATION - PowerPoint PPT Presentation
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Developing Daily Biomass Burning Inventories from Satellite Observations
andMOPITT Observations of CO
during TRACE P
Colette HealdAdvisor: Daniel Jacob
IDS Meeting: Duke UniversityApril 26, 2002
Satellite Observation of Firesand Biomass Burning Emission Inventories
MOTIVATION
Specific: Improve the forward and inverse GEOS-CHEM
simulation of CO
General: Improve Temporal Resolution of BB Emissions Use satellite observations to constrain emission features
Concept
Annual BB CO Emission Budget (Logan & Yevich)
Monthly BB CO Emission Budget
(Martin & Duncan)
Observed Daily Satellite
FireCounts
Daily FireCounts (after correct for
coverage)
Daily BB CO Emission Budget
Constrain Total Emissions Add Temporal Variability
AVHRR Fire Data
Why AVHRR? Need: global, daily
coverage during Spring 2001 ATSR, MODIS and TRMM
not suitable
AVHRR Observations: 13:40 local cross-over time 1 km resolution at nadir World Fire Web: 22 ground
stations Gridded product: 0.5°x0.5°
• #pixels on fire, #cloudy pixels, total #pixels observed
WFW:10 day
composite
AVHRR Coverage Limitations
Coverage limited by:1. Polar Orbit2. Ground Station
Data Submission 3. Clouds
WFW:1 day
coverage
Percentage of days observed in Spring 2001
Accounting for Clouds
ii
ii ct
fF
Threshold Box > 90% cloudy pixels = No Information
Defining the Fraction on Fire (FOF)
fi = # pixels on fireci = # cloudy pixelsti = # total pixels
Average Cloud Cover during Spring 2001
Correlation Scales
Local temporal correlation = persistence of fire patterns
Local spatial correlation = cohesion of fires
Application of Correlation Scales to Daily Fire Data
Correlation analysis supplements daily measurements with weighted information from neighbouring gridboxes, in either space or time.
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Application of Fire Data to CO Emissions
Magnitude of FOF used to partition monthly BB CO budget
Implementing in GEOS-CHEM
Boundary Layer:Difference strongestover source regions
Mid-troposphere:Difference strongestIn outflow (W. Pacific)
CO: Standard Simulation Standard Simulation - Daily Emissions Simulation
CO Sources: Integrating MOPITT and Aircraft
MOPITT Data EvaluationComparing to aircraft CO, GEOS-CHEM CO and fire activity
Forward Model Evaluation of Aircraft ObservationsComparing flight data with GEOS-CHEM fields
Inverse Modeling of CO Sources using MOPITT and aircraft observations
Characterize regional (Asian) emission sources viainversion of combined observational set
Background: TRACE-P and GEOS-CHEM
TRACE-P Feb-Apr. 2001 Characterize evolution and
composition of outflow from Asia
100 E 130 E 160 E 190 E 220 E 250 E 280 E
Longitude
0 N
10 N
20 N
30 N
40 N
50 N
60 N
La
titu
de
DC-8 FlightsP-3B Flights
GEOS-CHEM tagged CO “tag” CO by emission type
(biomass burning, fossil fuel, etc.) and source region using linear OH chemistry
GEOS-CHEM during TRACE-P
GEOS-CHEM UNDERESTIMATES THE OBSERVED CO BY 5-10%
Attributing Source Type to Observations
Multivariable fit to aircraft CO: PCE (C2Cl4) = fossil fuel HCN = biomass burning, biofuel Background term = chemical production
BLACK=OBSERVATIONSRED=FIT
cHCNbPCEaCO ][][][
Observation and Model Location of Source Influenced CO
PCE=FFHCN=BB/BFTOTAL CO MODEL
MISSING A BB/BF SOURCE?
Observation and Model Location of Source Influenced CO
PCE=FF
HCN=BB/BF
MISSING A BB/BF SOURCE?
TOTALCO
MODEL
Use of MOPITT
Integrated Analysis of global troposphere:
MOPITT COGEOS-CHEM
Aircraft COObservations
CMDL CO
Understanding Tropospheric
Processes (CO)
Emission Inventories
MOPITT Averaging Kernels
Gε)xA(xxx atruea ˆRetrieved CO:
Comparing MOPITT and GEOS-CHEM20010324
MOPITT adjusted for bias
…the Next Day (20010325)
MOPITT adjusted for bias
…and the Next (20010326)
MOPITT adjusted for bias
TRACE-P Validation Profiles
Courtesy: Louisa Emmons (NCAR)
BLACK=AIRCRAFT RED=AIRCRAFTxAVG KERNELSBLUE=MOPITT
V2 Retrieval:~20% bias
PreliminaryV3 Retrieval:
Better agreement
EMBARGO’ED!PRELIMINARY FIGURESPROVIDED BY LOUISA EMMONS
CO Source Inversion: Aircraft + Satellite
a1ε
T11aε
Ta KxySKSKSKxx ˆ
1a
1ε
T1 SKSKS ˆ
A posteriori CO emissions:
CO Inversion from aircraft and satellite observations: Goal: Refine regional (Asian) sources Collaborate with those working on global inversions = a priori Initially: exploit TRACE-P aircraft data and MOPITT
Associated error covariance:
Future Observations of CO: SCIAMACHY
Interests: Compare and evaluate MOPITT and SCIAMACHY observations of CO Exploit SCIAMACHY observations in future CO source inversion