tropospheric ozone as a climate gas, and satellite observations of its precursors
DESCRIPTION
TROPOSPHERIC OZONE AS A CLIMATE GAS, AND SATELLITE OBSERVATIONS OF ITS PRECURSORS. Daniel J. Jacob. CHEMISTRY, AEROSOLS, AND CLIMATE: TROPOSPHERIC UNIFIED SIMULATION (CACTUS). A NASA Interdisciplinary Science (IDS) investigation: - PowerPoint PPT PresentationTRANSCRIPT
TROPOSPHERIC OZONE AS A CLIMATE GAS, TROPOSPHERIC OZONE AS A CLIMATE GAS, AND SATELLITE OBSERVATIONS OF ITS PRECURSORSAND SATELLITE OBSERVATIONS OF ITS PRECURSORS
Daniel J. Jacob
GISS GCM
Atmosphericchemistry
Aerosolmicrophysics
emissions land use climate forcing
CACTUS model
climate chemistry
CHEMISTRY, AEROSOLS, AND CLIMATE:CHEMISTRY, AEROSOLS, AND CLIMATE:TROPOSPHERIC UNIFIED SIMULATION (CACTUS)TROPOSPHERIC UNIFIED SIMULATION (CACTUS)
A NASA Interdisciplinary Science (IDS) investigation:Harvard (Jacob, P.I.), Caltech (Seinfeld), NASA/GISS (Rind), UC Irvine (Prather)
“…Kyoto also failed to address two major pollutants that have an impact on warming: black soot and tropospheric ozone. Both are proven health hazards. Reducing both would not only address climate change, but also dramatically improve people's health.” (George W. Bush, June 11 2001 Rose Garden speech)
GLOBAL BUDGET OF TROPOSPHERIC OZONEGLOBAL BUDGET OF TROPOSPHERIC OZONE
O3
O2 h
O3
OH HO2
h, H2O
Deposition
NO
H2O2
CO, CH4, VOC
NO2
h
STRATOSPHERE
TROPOSPHERE
8-18 km
Chem prod in troposphere
4900 Chem loss in troposphere
4200
Transport from stratosphere
500 Deposition 1200
Global sources and sinks, Tg O3 yr-1 (GEOS-CHEM model)
Climatology of observed ozone at 400 hPa in July from ozonesondes and MOZAIC aircraft (circles) and corresponding GEOS-CHEM model results for 1997 (contours).
GEOS-CHEM tropospheric ozone columns for July 1997
GLOBAL DISTRIBUTION OF TROPOSPHERIC OZONEGLOBAL DISTRIBUTION OF TROPOSPHERIC OZONE
Li et al. [2001]
Lifetime is ~ weeks
FOSSIL FUEL 23.1AIRCRAFT
0.5BIOFUEL 2.2
BIOMASSBURNING 5.2
SOILS 5.1
LIGHTNING 5.8
STRATOSPHERE 0.2 ANIMALS
90
LANDFILLS50
GAS60
COAL40TERMITES
25
RICE85
WETLANDS180
BIOMASSBURNING20
NOx (Tg N yr-1) METHANE (Tg C yr-1)
ANTHROPOGENIC INCREASE IN TROPOSPHERIC OZONE ANTHROPOGENIC INCREASE IN TROPOSPHERIC OZONE DRIVEN BY NODRIVEN BY NOxx AND METHANE EMISSIONS AND METHANE EMISSIONS
PRESENT-DAY EMISSIONS
RISE IN TROPOSPHERIC OZONE OVER 20RISE IN TROPOSPHERIC OZONE OVER 20thth CENTURY CENTURY
Preindustrialozone models
}Observations at mountain sites in Europe [Marenco et al., 1994]
RADIATIVE FORCING FROM TROPOSPHERIC OZONERADIATIVE FORCING FROM TROPOSPHERIC OZONE
But how good is radiative forcing as an indicator of climate change, when this forcing is so heterogeneous?
Annual mean values (0.49 W m-2 globally)
(9.6 m)
Mickley et al. [1999] 0.46
IPCC [2001] range 0.3-0.5
From 19th century obs
[Mickley et al., 2001]
0.80
Global radiative forcing F (W m-2)
GISS GCM ANALYSIS OF CLIMATE RESPONSE TO GISS GCM ANALYSIS OF CLIMATE RESPONSE TO TROPOSPHERIC OZONE CHANGE OVER 20TROPOSPHERIC OZONE CHANGE OVER 20thth CENTURY CENTURY
GCM equilibrium simulation for present-day climate with present vs. preindustrial tropospheric ozone; includes “Q-flux” ocean
equilibriumclimate
T = 0.3oC
F = 0.49 W m-2
L.J. Mickley, Harvard
present-day ozone
Preindustrial ozone
Also sensitivity simulations with O3 = 18 ppb, CO2 = 25 ppm, giving same F
INHOMOGENEITY OF CLIMATE RESPONSE INHOMOGENEITY OF CLIMATE RESPONSE TO OZONE CHANGE OVER 20TO OZONE CHANGE OVER 20thth CENTURY CENTURY
• Greater warming in northern hemisphere
•Strong cooling in stratosphere:
Surface
Troposphericozone
9.6 m
Stratosphericozone
L.J. Mickley, Harvard
LOWER STRATOSPHERIC COOLING FROM TROPOSPHERIC LOWER STRATOSPHERIC COOLING FROM TROPOSPHERIC OZONE IS STRONGEST IN ARCTIC WINTER OZONE IS STRONGEST IN ARCTIC WINTER
GCM temperature change in lower stratosphere in DJF (oC) from increasing tropospheric ozone over 20th century
particularly sensitive region for recovery of ozone layer!
L.J. Mickley, Harvard
CLIMATE RESPONSE EXPERIMENTS WITH IDENTICAL CLIMATE RESPONSE EXPERIMENTS WITH IDENTICAL GLOBAL RADIATIVE FORCINGS (0.49 W mGLOBAL RADIATIVE FORCINGS (0.49 W m-2-2) FROM:) FROM:
1. tropospheric ozone2. uniform tropospheric ozone (18 ppv)3. carbon dioxide (25 ppmv)
• CO2 is a more effective warming agent at surface
• In lower stratosphere, CO2 causes warming while tropospheric ozone causes cooling
L.J. Mickley, Harvard
WHY IS COWHY IS CO22 MORE EFFECTIVE THAN OZONE MORE EFFECTIVE THAN OZONE
FOR SURFACE WARMING AT SAME RADIATIVE FORCING?FOR SURFACE WARMING AT SAME RADIATIVE FORCING?Correlation of forcing with 500 hPa humidity in tropics (25N-25S)
Overlap of CO2 and H2O bands causes CO2 forcing to shift poleward where ice feedback enhances warming
FCO2 – FO3
L.J. Mickley, Harvard
Ozone CO2
GCM SURFACE WARMING PATTERNS (GCM SURFACE WARMING PATTERNS (ooC) FROM INCREASING C) FROM INCREASING TROPOSPHERIC OZONE OVER 20TROPOSPHERIC OZONE OVER 20thth CENTURY – JJA SURFACE CENTURY – JJA SURFACE
Difference
Tropospheric ozone Equivalent uniform CO2
(white = insignificant or high altitude)
Largest warmings downwind of ozone source regions – ozone there is more effective than CO2
L.J. Mickley, Harvard
USING SATELLITE MEASUREMENTS OF NOUSING SATELLITE MEASUREMENTS OF NO22 AND HCHO AND HCHO
COLUMNS (SOLAR BACKSCATTER) TO MAP NOCOLUMNS (SOLAR BACKSCATTER) TO MAP NOx x AND AND
VOC EMISSIONSVOC EMISSIONS
Emission
NOh (420 nm)
O3, RO2
NO2
HNO3
1 day
NITROGEN OXIDES (NOx) VOLATILE ORGANIC CARBON (VOC)
Emission
VOC
OHHCHOh (340 nm)
hoursCO
hours
BOUNDARYLAYER
~ 2 km
Tropospheric NO2 column ~ ENOx
Tropospheric HCHO column ~ EVOC
Deposition
GOME satellite instrument
Instrumentsensitivity w()(“scattering weight”)
Vertical shapefactor S()(normalized mixing ratio)
what GOMEsees
AMFG = 2.08actual AMF = 0.71
IN SCATTERING ATMOSPHERE, THE AIR MASS FACTOR IN SCATTERING ATMOSPHERE, THE AIR MASS FACTOR (AMF) OF A SOLAR BACKSCATTER MEASUREMENT (AMF) OF A SOLAR BACKSCATTER MEASUREMENT DEPENDS ON VERTICAL DISTRIBUTION OF THE GASDEPENDS ON VERTICAL DISTRIBUTION OF THE GAS
1
0
( ) ( )GAMF AMF w S d
Illustrative retrieval of HCHO column at 340 nm
Palmer et al. [2001]
geometric
USE GLOBAL 3-D MODEL DRIVEN BY ASSIMILATED USE GLOBAL 3-D MODEL DRIVEN BY ASSIMILATED METEOROLOGICAL DATA TO PROVIDE AMFsMETEOROLOGICAL DATA TO PROVIDE AMFs
FOR EVERY SATELLITE VIEWING SCENE FOR EVERY SATELLITE VIEWING SCENE
SATELLITE DATA
SLANTCOLUMN
GEOS-CHEM GLOBAL 3-D MODEL OF TROPOSPHERIC CHEMISTRY:
provides S(
AMF
VERTICALCOLUMN
VERTICALCOLUMN
• Best information applied to each scene• Consistency in comparing model and observed columns• Apply with any 3-D model (recalculate AMFs using tabulated scattering weights)
ADVANTAGES OF 3-D MODEL APPROACHFOR COMPUTING AMFs
spectralfit
LIDORT RAD.TRANSFER MODEL:
provides w()
HCHO COLUMNS FROM GOME OVER U.S.:HCHO COLUMNS FROM GOME OVER U.S.:July 1996 meansJuly 1996 means
BIOGENIC ISOPRENE IS THE MAIN SOURCE OF HCHO IN U.S. IN SUMMER
Palmer et al. [2001]
GEIAisopreneemissions
R = 0.83Bias 14%
Precision:4x1015 cm-2
GOMEGOMEslantslant
GOMEGOMEverticalvertical
GEOS-CHEMGEOS-CHEMverticalvertical
DifferenceDifference
MAPPING OF ISOPRENE MAPPING OF ISOPRENE EMISSIONS FOR JULY 1996 EMISSIONS FOR JULY 1996 BY SCALING OF GOME BY SCALING OF GOME FORMALDEHYDE COLUMNS FORMALDEHYDE COLUMNS [Palmer et al., 2002][Palmer et al., 2002]
GEIA (IGAC inventory)
BEIS2(official EPA inventory)
GOME
COMPARE TO…
SEASONAL VARIABILITY OF HCHO COLUMNS (9/96-8/97)SEASONAL VARIABILITY OF HCHO COLUMNS (9/96-8/97)- proxy for isoprene emissions -- proxy for isoprene emissions -
SEP
AUG
JUL
OCT
MAR
JUN
MAY
APR
Dorian Abbott (Harvard)
GOME GEOS-CHEM GOME GEOS-CHEM
GOME Tropospheric NO2 GEOS-CHEM Tropospheric NO2
1015 molecules cm-2
DJF 96-97
MAM 1997
JJA 1997
SON 1996
r = 0.75 bias=5%
R.V. Martin
with a priori emissions (scaled GEIA)
OPTIMIZED NOOPTIMIZED NOxx EMISSION INVENTORY FROM GOME EMISSION INVENTORY FROM GOME
A POSTERIORI A PRIORIR.V. Martin, Harvard
TRACE-P AIRCRAFT MISSION (March-April 2001):TRACE-P AIRCRAFT MISSION (March-April 2001):top-down constraints on Asian emissionstop-down constraints on Asian emissions
CO fossil and biofuel bottom-up emissions (D.R. Streets, ANL)
Daily CO biomass burning emissions from AVHRR (C.L. Heald, Harvard)
Chemical forecastsCTMs
MOPITT COObservations(IR emission)
CO aircraft observations(G.W. Sachse)
Jacob et al. [2002]
MOPITT VALIDATION PROFILES DURING TRACE-PMOPITT VALIDATION PROFILES DURING TRACE-P
aircraftAircraft w/MOPITT av kernels
MOPITT
Averagingkernels
MEAN MOPITT MEAN MOPITT CO COLUMN DATA CO COLUMN DATA DURING TRACE-P DURING TRACE-P (Mar-Apr 2001)(Mar-Apr 2001)
MOPITT
GEOS-CHEMmodel w/av kernels
DifferenceC.L. Heald, Harvard
• FTIR spectrometer (3.3 - 15.4 m) to be launched on Aura satellite in 2004 (P.I. Reinhard Beer, JPL)
• Field of view: 0.5x8 km2
Std. products Nadir Limb
Temperature X X
Surface temp. X
Land surf. emissivity
X
O3 X X
CO X X
H2O X X
CH4 X X
NO X
HNO3 X
TROPOSPHERIC EMISSION SPECTROMETER (TES)TROPOSPHERIC EMISSION SPECTROMETER (TES)
Averaging kernels
“True” profile(GEOS-CHEM)
CO retrieval
a priori
retrieved
D.B. Jones, Harvard
About 3 pieces of information on vertical profile: ~ 1 more than MOPITT
TES NADIR RETRIEVAL OF COTES NADIR RETRIEVAL OF CO
WILLTES NADIR CO OBSERVATIONS IMPROVEWILLTES NADIR CO OBSERVATIONS IMPROVEOUR ABILITY TO QUANTIFY REGIONAL CO EMISSIONS?OUR ABILITY TO QUANTIFY REGIONAL CO EMISSIONS?
Assume that we know the true sources of CO
From these sources of CO.Use GEOS-CHEM model to simulate “true” CO concentration field
Sample model along TES orbit tracks, apply TES averaging kernels and noise to simulate retrieval of this CO field
Make a priori (deliberately wrong)
estimate of CO sourcesby applying errors
to the “true” source
Apply optimal estimation
inverse method
Obtain a posteriori sources and errors;
How successful are we at finding the true
source and reducing the error?
1 day GEOS-CHEM CO data (March 10, 2001) along TES orbit at 500 hPa
CONSTRUCTING THE MODEL ERROR COVARIANCE MATRIXCONSTRUCTING THE MODEL ERROR COVARIANCE MATRIXUSING TRACE-P OBSERVATIONS AND FORECASTSUSING TRACE-P OBSERVATIONS AND FORECASTS
• Assume that difference between successive GEOS-CHEM CO forecasts during TRACE-P (to+48h and to + 24 h) describes the covariant error structure (“NMC method”)
• Assume that mean bias in GEOS-CHEM model simulation of CO in TRACE-P is due to emission errors, and that residual relative error (RRE) is due to transport; use RRE to scale covariant error structure.
• Add representativeness error of 5% (small) based on subgrid variablity in TRACE-P aircraft data
D.B. Jones and P. I. Palmer, Harvard
CO TRACE-P dataGEOS-CHEM error,TRACE-P simulation
Forecast error (blue) and scaled model transport error (red)
MODEL TRANSPORT ERRORSMODEL TRANSPORT ERRORS(DIAGONALS OF ERROR COVARIANCE MATRIX)(DIAGONALS OF ERROR COVARIANCE MATRIX)
RELATIVE ERROR850 hPa,
March-April 2001
D.B. Jones, Harvard
CHEM
NAFF
RWFF RWBB
AFBB
EUFF
SABB
ASFFASBB
NAFF: 121.3 SABB: 96.5EUFF: 131.1 RWBB: 98.0ASFF: 258.3 RWFF: 149.8ASBB: 96.0 CHEM: 1125.0AFBB: 193.9
“True” Emissions (Tg/yr)
Total = 2270 Tg/yr
• FF = Fossil Fuel + Biofuel• All sources include contributions from oxidation of VOCs; assume 50% error• OH is specified• Use a “tagged CO” method to estimate contribution from each source (Jacobian matrix)• Use linear inverse method to solve for annually-averaged emissions
D. B. Jones, Harvard
REGIONAL CO SOURCES TO BE RETRIEVED REGIONAL CO SOURCES TO BE RETRIEVED IN TES SIMULATION EXERCISEIN TES SIMULATION EXERCISE
INVERSION RESULTS (5 days of TES data, Mar 10-15 2001)INVERSION RESULTS (5 days of TES data, Mar 10-15 2001)
a priori a posteriori true
• With Gaussian unbiased error statistics, TES is extremely powerful for constraining global sources of CO (because it provides lots of data!)• Still very powerful when using only data above 500 hPa• Realization of this potential rests on quantification of error statistics, particularly for the model transport error – a very difficult problem!
D. B. Jones, Harvard