EvaluatingGas-phaseChemistryofaGlobalChemistry-ClimateModelUsingSatelliteData
1
1
2,3
XiaomengJin ([email protected]),TraceyHolloway ,MeiyunLin
1.NelsonInstituteCenterforSustainabilityandGlobalEnvironment(SAGE),UniversityofWisconsin-Madison,Madison,WI,USA
2.PrograminAtmosphericandOceanicSciences,PrincetonUniversity,Princeton,NJ,USA
3.NOAAGeophysicalFluidDynamicsLab,Princeton,NJ,USA
EvaluationofColumnDensity:TroposphericNO2
❖
Daily global coverage
❖
We used daily NO2 and HCHO Level-2
products available from NASA [Boersma
et al., 2011; Levelt et al., 2006].
❖
❖
❖
GFDL AM3 model reproduced the
seasonal and spatial variation of
tropospheric NO2 column. (R =
0.94)
❖
Application of averaging kernel
(AK) improved model-satellite
agreement.
EasternUS
❖
Emission data: HTAP2 anthropogenic
emissions, FINN daily wildfire emissions,
MEGAN v2.1 isoprene emissions
❖
We used daily 3-h average mixing ratio of
HCHO and NO2 in 2010.
❖
Resolution: 1° × 1.25°
Comparing with OMI data, GFDL
AM3 model underestimated the
NO2 column in eastern US, central
China, Europe and South Africa.
GFDL AM3 model overestimated
the NO2 column in eastern China,
South America and southeast
Asia.
Satellitedatahavefull
coveragewith
consistentrevisit
frequencybutlarger
uncertainty.
Modeldataarealways
available,butneed
validation
Forcing
Atmospheric
Dynamics and
Physics
Emission
Atmospheric
Chemistry
RESEARCH POSTER PRESENTATION DESIGN © 2012
www.PosterPresentations.com
Surface
Ozone
EvaluationofColumnDensity:HCHO
GFDLAM3Model
EasternChina
OMIHCHO
Europe
SouthAmerica
❖
FNR < 1 (A): VOC-limited, VOC control is
more effective for ozone reduction.
❖
FNR > 2 (B): NOx-limited, NOx control is
more effective for ozone reduction
❖
1 < FNR < 2 (C): Transitional or Mixed,
both NOx and VOCs are effective for ozone
reduction
Spatial and temporal variability of ozone
sensitivity in China [Jin et al., in review]:
❖
❖
❖
OzoneIsopleths
0.25
0.4
0.2
Transitional regime is dominated over
eastern China in ozone season.
VOC-limited regime is found around large
power plants in North China Plain and
Yangtze River Delta.
Due to increasing NOx emission, China is
experiencing a spatiotemporal expansion
of transitional and VOC-limited regime.
0.15
0.1
0.32
Ozone sensitivity indicator ratio HCHO/NO2
(FNR) [Duncan et al., 2010]:
A
C
B
0.05
0
0
0.5
1
1.5
ROG (ppmC)
2
VOC (ppmC)
EasternUS
EasternChina
Modeledozone
photochemistryis
moreVOC-sensitivein
coldseasonandmore
NOx-sensitiveinwarm
season.
References
NOx
VOC
Measure
ments
MeanBias(Model-Satellite)
❖
Satellite
Model
Data Reliability:
❖
ComparisonwithGFDL-AM3Model
Datasourcesofozoneanditsprecursors
Measurementsare
mostreliablebutvery
limited.
Most NOx in the boundary layer exists in the
form of NO2.
Modeledozone
photochemistryis
moreVOC-sensitive
thansatellite
Developed at NOAA Geophysical Fluid
Dynamics Laboratory (GFDL)
Interactive stratospheric and tropospheric
chemistry nudged to GFS reanalysis winds
[Lin et al., 2012a; Lin et al., 2012b].
❖
❖
GFDL-AM3Model
❖
HCHO is a short-lived oxidation product of
many VOCs, which is considered as an
indicator of reactive VOCs.
MeanBias(Model-Satellite)
OzoneMonitoringInstrument(OMI)
13 km × 14 km resolution (swath data)
❖
0.24
SouthAmerica
DataSources
❖
Europe
The effectiveness of ozone reduction depends
on the relative concentration of NOx to VOCs
in the atmosphere.
0.16
OMINO2
❖
OzonePhotochemicalRegimeinChina(OzoneSeason)
0.08 = O3(g), ppmv
OMIObservationofOzoneSensitivity
❖
Sun-synchronous orbit
EasternChina
NOx(g) (ppmv)
Satellite data have full coverage of the
globe with consistent frequency, which
complement ground-based
measurements in model evaluation.
We use satellite data to evaluate the
Geophysical Fluid Dynamics
Laboratory (GFDL) AM3 model, a
global climate-chemistry model that
has participated in HTAP2 multimodel experiments. We compare the
base simulations of vertical column
density of HCHO and NO2 with
satellite retrieval. HCHO and NO2 are
indicators of surface ozone precursors:
VOC and NOx. The ratio of HCHO to
NO2 (FNR) informs ozone-NOx-VOC
sensitivity, which is important for
effective ozone control strategies. We
compare the model-derived FNR with
satellite data. The results suggest the
recent improvements in satellite
products could benefit model
evaluation.
❖
GFDLAM3Model
EasternUS
Ozone-NOx-VOCSensitivityIndicator
NOx (g)
Abstract
❖
Data Availability:
❖
GFDL AM3 model reproduced
the seasonal and spatial
variation of HCHO, but the
agreement was weaker (R = 0.86)
compared with NO2.
GFDL AM3 model and OMI
observation agreed better over
low latitudes.
Application of AKs improved
the model-satellite agreement.
❖
❖
Comparing with OMI data, GFDL
AM3 model underestimated the
HCHO column over high latitude
areas, such as Europe, China,
Russia, Canada and South Africa,
where OMI HCHO is biased high.
GFDL AM3 model overestimated
the HCHO column in eastern US,
South America and southeast
Asia.
1. Boersma, K. F. et al. (2011), An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech.,
4(9), 1905–1928.
2. Duncan, B. N. et al. (2010), Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation,
Atmospheric Environment, 44, 2213–2223.
3. Jin, X., T. Holloway (2015), Spatial and temporal variability of ozone sensitivity over China observed from the Ozone Monitoring Instrument. In
review at Journal of Geophysical Research Atmospheres.
4. Levelt, P. F., G. H. J. van den Oord, M. R. Dobber, A. Malkki, Huib Visser, Johan de Vries, P. Stammes, J. O. V. Lundell, and H. Saari (2006), The
ozone monitoring instrument, IEEE Transactions on Geoscience and Remote Sensing, 44(5), 1093–1101, doi:10.1109/TGRS.2006.872333.
5. Lin, M. et al. (2012a), Transport of Asian ozone pollution into surface air over the western United States in spring, J. Geophys. Res., 117(D21), doi:
10.1029/2011JD016961.
6. Lin, M., A. M. Fiore, O. R. Cooper, L. W. Horowitz, A. O. Langford, H. Levy II, B. J. Johnson, V. Naik, S. J. Oltmans, and C. J. Senff (2012b),
Springtime high surface ozone events over the western United States: Quantifying the role of stratospheric intrusions, J. Geophys. Res., 117(D21),
doi:10.1029/2012JD018151.
Acknowledgement
Support for this project was provided in part by the NASA Air Quality Applied Sciences Team (AQAST). We
thank the National Atmospheric and Space Administration (NASA) for the free distribution of NO2 and
HCHO products. We also recognize the valuable assistance from colleagues at the University of WisconsinMadison Center for Sustainability and the Global Environment (SAGE), including Dr. Monica Harkey and Mr.
Xiujun Li, as well as AQAST collaborators Dr. Bryan Duncan and Dr. David Streets.