evaluation of pm in the merra aerosol...
TRANSCRIPT
Evaluation of PM2.5 in the MERRA Aerosol Reanalysis
Arlindo da Silva(1) [email protected]
Virginie Buchard-Marchant(1,2), Pete Colarco, Ravi Govindaradju(1,3) et al. (1) Global Modeling and Assimilation Office, NASA/GSFC (2) GESTAR (3) Science Systems and Applications Inc.
Air Quality Applied Sciences Team 5th Semi-annual Meeting @ Umd College Park, MD, 4-6 June 2013
1
Overview GEOS-5 at a Glance Model Data assimilation
GEOS-5 during DISCOVER-AQ Maryland MERRAero AOT evaluation PM2.5 evaluation
Concluding Remarks 2
GEOS-5 Atmospheric Data Assimilation System
Near Real-time System
GOCART Component
hydrophobic
hydrophilic
hydrophobic
hydrophilic
radi
us
radi
us
Dust
Seasalt
Black Carbon
Organic Carbon
Sulfate
Mass
• Goddard Chemistry, Aerosol, Radiation, and Transport Model [Chin et al. 2002]
• Sources and sinks for 5 non-interactive species
• Convective and large scale wet removal • Dry deposition (and sedimentation for
dust and sea salt) • Optics based primarily on OPAC
dust wind and topographic source, 5 mass bins
sea salt wind driven source, 5 mass bins black carbon anthropogenic and wildfire source, mass
hydrophic and hydrophilic
organic carbon
anthropogenic, biogenic, and wildfire source, mass hydrophic and hydrophilic
sulfate anthropogenic and wildfire source of SO2, oxidation to SO4 mass
Aerosol Data Assimilation Focus on NASA EOS
instruments, MODIS for now
Global, high resolution (1/4 deg) AOD analysis
3D increments by means of Lagrangian Displacement Ensembles (LDE)
Simultaneous estimates of background bias (Dee and da Silva 1998)
Adaptive Statistical Quality Control (Dee et al. 1999): State dependent (adapts to
the error of the day) Background and Buddy
checks based on log-transformed AOD innovation
Error covariance models (Dee and da Silva 1999): Innovation based Maximum likelihood
6
Observational Bias Original MODIS AOD Bias Corrected AOD
GEOS-5/GOCART Forecasts
CO
Smoke
SO4
http://gmao.gsfc.nasa.gov/projects/DISCOVER-AQ/
Global 5-day chemical forecasts customized for each campaign O3, aerosols, CO, CO2, SO2
Resolution: Nomally 25 km Driven by real-time biomass
emissions from MODIS Aerosols interacts with
circulation through radiation
GEOS-5 During D-AQ Maryland
9 July 2011
HSRL Extinction Profiles
10
Revised GEOS-5 PBL Height
11
AERONET “DRAGON” Stations
12
AOD / PM2.5 Challenges AOD assimilation
constrains column mass as long as mass extinction
efficiency is OK Accurate PM2.5
determination still depends on Speciation Vertical structure
Joint AOD & PM2.5 assimilation requires unbiased observing system
13
PM 2.5 at MDE Stations
14
MERRAero Overview Feature Description
Model GEOS-5 Earth Modeling System (w/ GOCART) Constrained by MERRA Meteorology (Replay) Land sees obs. precipitation (like MERRALand) Driven by QFED daily Biomass Emissions
Aerosol Data Assimilation
Local Displacement Ensembles (LDE) MODIS reflectances AERONET Calibrated AOD’s (Neural Net) Stringent cloud screening
Period mid 2002-present (Aqua + Terra)
Resolution Horizontal: nominally 50 km Vertical: 72 layers, top ~85 km
Aerosol Species Dust, sea-salt, sulfates, organic & black carbon 15
AERONET Validation
16
Annual Mean PM2.5
17
PM2.5 Data Source EPA’s AQS PM2.5 Local Conditions
(88101) Daily means Rural & Suburban Period: 2003-12
18
http://www.epa.gov/ttn/airs/airsaqs/
PM2.5 Regional Annual Means
19
MERRAero PM2.5 Bias
20
PM2.5 Regional Climatology
21
PM2.5 Regional Daily Joint p.d.f.
22
MERRAero PM2.5 Correlation
23
Status Report While MERRAero produces AOD that is
unbiased w.r.t. AERONET, its surface PM2.5 concentrations have a low bias. erroneous PBL height, missing species, mass
extinction efficiencies are likely causes Joint assimilation of AOD/PM2.5
assimilation cannot proceed until this observation bias issue can be resolved. or else spurious time variability will arise
24
Work in progress Examine PM2.5 speciation Detailed diagnostic for all DISCOVER-AQ
deployments, other field campaigns On-going model development
Aerosol microphysics (MAM) Include nitrates, SOA treatment Improve emission processes
On-going data assimilation development Statistical observation operator for PM2.5
EnKF (radiance based) New data types: MISR, VIIRS, OMI, CALIPSO, etc.
25
Extra Slides
Sulfates, etc.
26
PM2.5 Regional Daily Diff p.d.f.
27
GEOS-5 Sulfates (2010)
28
SO2 Lifetime in GEOS-5
29
Mass Budget
30
Decomposing the Mass Flux
31
Annual Carbonaceous Flux Potential
32
Total
Eddy
Mean Flow
IAU
Annual Sulfate Flux Potential
33
Total
Eddy
Mean Flow
IAU