1. Using HIPPO observations to constrain the atmospheric budgets of black carbon (BC) and methane
Qiaoqiao Wang, Kevin Wecht, Daniel Jacob
Anne Perring, Joshua Schwarz, Ryan Spackman, David Fahey
NOAA
Eric Kort, Steven Wofsy
Harvard University
With support from NSF (HIPPO), NASA (ACMAP, CMS) 1

2. AeroCom models show large errors for BC in remote air
Multimodel intercomparisons and comparisons to observations
Multimodel intercomparison and comparison to observations
AeroCom models show large errors for BC in remote air
ARCTAS (Arctic spring)
TC4 (Costa Rica, summer)
Observed
Models
Pressure, hPa
BC, ng kg-1
BC, ng kg-1
HIPPO over Pacific (Jan)
Models differ by order of magnitude between themselves and with observations
Discrepancy must be driven by model errors in scavenging
Pressure, hPa
obs
models
20S-20N
obs
models
60-80N
BC, ng kg-1
BC, ng kg-1
Koch et al. [2009], Schwarz et al. [2010]

3. Global BC simulation in GEOS-Chem
2ox2.5o horizontal resolution, GEOS-5 assimilated meteorological data
2009 emissions x2
x0.7
Steven Barrett , Federal aviation administration;
The dataset was generated using the Aviation Emissions Inventory Code (AEIC).
Anthropogenic emission dominates globally, biomass burning may dominate regionally and seasonally
GFED3
Bond et al. [2007], scaled
Anthropogenic ≡ fossil fuel + biofuel

4. Previous application to Arctic spring (ARCTAS)
GEOS-Chem aerosol scavenging scheme
Cloud updraft scavenging
Anvil precipitation
Large scale precipitation
CCN
IN+CCN
CCN+IN,
impaction
Below-cloud scavenging (accumulation mode aerosol),
different for rain and snow
Partial or complete re-evaporation (virga)
entrainment
BC has 1-day time scale for conversion from hydrophobic (non-CCN) to hydrophilic
detrainment
vertical position of the aerosol particle, the scavenging process can be in-cloud or below-cloud.
In-cloud: aerosols enter cloud droplets or ice crystals when they act as cloud condensation or ice nuclei and also by the process of impaction with the cloud droplets and crystals
Below-cloud: is the capture of aerosol particles by precipitating rain droplets or snow particles, and is usually described by a first order decay equation.
No systematic biases when compared to aerosol observations
210Pb tropospheric lifetime of 8.6 days (consistent with best estimate of 9 days)

5. Testing model BC emissions with observed surface air concentrations in source regions
NMB= -27%
Circles: annual mean observations (2006 in China, in Europe, 2009 in US)
Solid contours: model
Model is too low by 10-30% -
small error for our purposes
NMB= 6.6%
Underestimation in Europe is mainly due to three sites in northern Italy and Belgium. Without these three sites the NMB would decrease to -0.7%.
NMB= -12%

6. Previous GEOS-Chem evaluation in Arctic winter-spring
Mean ARCTAS aircraft profile, April 2008
Model vs. observed
snow BC content,
Surface concentrations at Barrow, 2008
Observed
Model
Russia
fuel
Dominant BC contributions from fuel in N American Arctic, fires in Russian Arctic
Russia fuel source higher than expected
Wang et al. [2011]

7. HIPPO BC curtains across Pacific
Observed Model
Jan 09
Oct-Nov 09
Mar-Apr 10
Concentrations are lowest in the deep tropics (scavenging)
SH concentrations are highest in Oct-Nov (open fires) but remain higher than tropics in other seasons (fuel sources)

8. Latitudinal dependence of BC concentrations
Geometric mean ±sd vs. latitude
Latitudinal dependence of BC concentrations
Observed
Model
Secondary maximum in southern extratropics reflects significant anthropogenic source, seasonal amplification by open fires
Model tends to overestimate low end of observations and is unable to reproduce frequent observed concentrations <0.05 ng m-3 STP in the deep tropics
Discrepancy suggests insufficient scavenging in very old air; implication for indirect radiative effect?
NMB = +11%
Model vs. observed BC

9. BC and CO are correlated in fire seasons but not otherwise
Oct-Nov
20-60S
Jan
20-60N
Over the tropics, within 10% (30%)
Arctic, % higher
Lack of BC-CO correlation outside of fire seasons reflects diversity of sources, large lifetime difference

10. Seasonal mean BC vertical profiles from HIPPO 1-3
Mid-latitudes show peak in mid-troposphere from WCB lifting
Highest concentrations in NH in spring when WCB lifting is most frequent
General decrease with altitude in the tropics due to deep convective scavenging

11. Zonal mean BC in GEOS-Chem
Zonal annual mean BC concentrations in GEOS-Chem
Pressure, hPa
The annual global burden of BC in the troposphere  is 74 Gg, 34% of which is present in the free troposphere (>2 km). Only 23% of the burden is in SH.
The annual global contribution of fire emissions to BC burden is 30%, with most fire emissions originate in Africa, accounting for 69% of fire BC in the troposphere.
Anthropogenic BC in the atmosphere is mainly from NH, accounting for more than 80%, with similar regional contributions as those to anthropogenic emission.  
34% of BC mass is in free troposphere (> 2 km): expect large radiative forcing implications (stay tuned!)

12. Methane in HIPPO: enabling inverse models of sources
1. Model evaluation and error correlation length scales
HIPPO-3, Mar-Apr 2010
southbound northbound
200
600
1000
Observed
Pressure, hPa
200
600
1000
GEOS-Chem
prior
50S N S N
2. TES v5 satellite instrument validation: two pieces of info for methane
100
1000 10
Pressure, hPa
Bias: lat-dep ±29 ppb
Bias: 42 ±27 ppb
Averaging
kernel
Wecht et al. [2012]

13. Correction factors for GEOS-Chem emissions from preliminary inversion
Using satellite observations in adjoint inversion of methane emissions in North America
GEOS-Chem nested model (0.5ox0.67o) with HIPPO-tested boundary conditions
SCIAMACHY mixing ratios (Jul-Aug 2004)
1700
1800
ppb
Correction factors for GEOS-Chem emissions
from preliminary inversion
EPA emission inventory underestimates emissions from oil/gas, livestock
GEOS-Chem wetland emissions (Kaplan) are too high
Inversion is underconstrained on 0.5ox0.67o model grid; spatial clustering is necessary (stay tuned!)
0.8
1.2