Upload
conrad-marshall
View
220
Download
3
Tags:
Embed Size (px)
Citation preview
Lok Lamsal, Nickolay Krotkov, Randall Martin, Kenneth Pickering, Chris Loughner, James Crawford, Chris McLinden
TEMPO Science Team MeetingHuntsville, Alabama
27-28 May 2015
Development of TEMPO NO2 Algorithm to Infer Vertical Columns from Total Slant
Columns
1) Stratosphere-troposphere separation2) Sensitivity to NO2 profiles
Attention Needed for Removal of Stratospheric NO2
-150 -100 -5020
30
40
50
60
70
0
0.1
0.2
0.3
0.4
0.5
Fraction of total NO2 column in the troposphere can be smallUrban/Industrial areas: 30-80%
Rural/background areas: 10-30%
Need unbiased method to remove stratospheric NO2
Figure from Chris McLinden
Fraction
OMI (2009) annual mean
GMI model (July average)
6 AM 12 PM 6 PM
Candidate Stratosphere-troposphere Separation Algorithms
1) Reference sector method (zonal invariance and data from Pacific)
2) Image processing /wave analysis
3) Goddard method for OMI (OMNO2)
Observation based, spatial filtering, filling, and interpolation
4) KNMI method for OMI (DOMINO)
Data assimilation
x
Stratospheric NO2
July 21, 2006
NASA GMI model
Adaptation of OMI algorithms to TEMPO may require improvements when there is a large gradient in NO2 field
3) Observation based
4) Assimilation
Candidate Stratosphere-troposphere Separation Algorithms
OMI heritage algorithm for TEMPO
Rapid decline around sunrise, slow increase during day, rapid increase around sunset
Two CMAQ simulations: Model set up
Horizontal resolution 4 km x 4 km
Vertical levels 45 (surface-100 hPa)
Chemical mechanism CB05
Aerosols AE5
Dry deposition M3DRY
Vertical diffusion ACM2
Boundary condition RAQMS; 12 km x 12 km
Biogenic emissions Calculated within CMAQ with BEIS
Biomass burning emissions FINNv1
Lightning emissions Calculated within CMAQ
Anthropogenic emissions NEI-2005 projected to 2012
Simulation 1 Simulation 2
PBL scheme ACM2 (Assymetric Convective Model v2)
YSU (Yonsei Univ.)
High Resolution CMAQ Simulations to Study Retrieval Sensitivity to Diurnal Changes in NO2 Profiles
Evaluation of Modeled NO2 Profiles: Methods
► Location: Padonia, Maryland
► Observation period: 3-4 spirals for 14 days in July 2011 (Hours covered 6
AM – 5 PM, local time)
► NO2 observations:
Aircraft (P3B) measurements (200 m - ~4 km) NCAR data
Surface measurements by photolytic converter instrument
Spatial resolution comparable between model (4x4km) and spiral
(radius ~4km)
► Observed PBL heights: Estimation based on temperature, water vapor, O3
mixing ratios, and RH (Donald Lenschow)
► Collocation and sampling:
Model and surface measurements sampled for the days and time of
aircraft spirals
Spiral data sampled to model vertical grids
Diurnal Changes in NO2 Vertical Distribution
Models capture overall diurnal variation, but some differences related to emissions, PBL height, vertical mixing are evident.
Padonia, MD (July)
3 PM
Surface reflectivities: 0.1 to 0.15 at
0.01 steps
Solar zenith angles: 10° to 85° at 5°
steps
Aerosol optical depths: 0.1 to 0.9 at
0.1 steps
6 AMImproved Model Simulation Reduces Retrieval Errors
Model Need to Well Represent PBL Mixing to Minimize Errors from NO2 Profiles
► PBL scheme alone can
cause different AMF
errors
► Greater performance for
certain hours for both
ACM2 and YSU
► Diurnal pattern in AMF
errors for ACM2
► We need model that
represents PBL mixing
and emissions to
minimize errors in
retrievals