Biswadev (Dev) Roy

1
Application of Satellite Data to Improve Model
Performance and Evaluation

• Biswadev (Dev) Roy
• EPA Post-doc. (Dec. 28, 2003 to July 07, 2007)
• Currently with EPA/Region-6 Air Planning Section,
  Dallas, TX
• September 20, 2007
• AMD Seminar
• C-111C, NERL, RTP, NC 27711

2
EPA Post-doc Projects
1. Improvement of fire emissions inventory using
satellite information - study impact of wildfire
emissions reallocations on CMAQ - compare CMAQ
predicted CO columns with MOPITT - use
MODIS fire count information and ground
observations record for creating 2005 fire
emissions for NEI 2. Compare CMAQ optical depth
with MODIS observations - compare CMAQ
w/AERONET, MODIS and IMPROVE - develop PM2.5-AOD
relationship 3. Evaluation of MM5 ground
temperature output - compare with
aircraft, GOES, and MODIS - inter-relate
skin temperature errors with PBL height errors
MODIS
CMAQ
MOPITT
3
Data Sources

• MODIS Moderate Resolution Imaging
  Spectroradiometer
• MOPITT Measurement of Pollution in the
  Troposphere
• (correlation radiometer)
• GOES Geost. Operational Environmental Satellite
• AERONET NASA/Aerosol Robotic Network
• IMPROVE Interagency monitoring network for class
  I areas
• STN monitoring network for urban areas
• MTP microwave temperature profiler (JPL) TEXAQS
  I
• Heimann IR Probes aircraft mounted sensor (JPL)
  TEXAQS I

4
1. Study the impact of fire emissions
reallocation using MODIS fire signatures

• Objective
• Reallocate NEI using MODIS fire signatures and
  check its impact on CMAQ using PM2.5 and Total
  Carbon data from IMPROVE

With George Pouliot, Alice Gilliland, Tom
Pierce, Bill Benjey, Prakash Bhave, and Steven
Howard
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Steps taken for emissions reallocation

• MODIS Fire-pixel counts were gridded into
  respective CMAQ grid cells
• 90 of the NEI monthly prescribed burns and
  wildfire emissions for each state-month are
  distributed in space and time using the MODIS
  fire counts
• -- States monthly emissions in the NEI were
  multiplied by fraction of pixel count for each
  grid cell over the monthly count for the state
  and by the fraction of each grid cell in that
  particular state
• -- Spatially reallocated emissions were
  distributed temporally using the ratio of the
  pixel count per day and pixel count per month for
  each grid cell

6
CMAQ Options
MM5-CMAQ ? Pre-release version of CMAQ 4.4
used ? Simulations using CB-IV chemical
mechanism ? Modal Aerosol Model and ISORROPIA
thermodynamic equilibrium model ? Chemical BCs
for CMAQ based on GEOS-CHEM ? Meteorological
inputs from MM5, 34 vertical layers collapsed to
14 layers ? 36 km x 36 km horizontal grid
7
MODIS RR fire pixel counts
Reallocated minus base case PM2.5 emission rates
in g s-1 OCEC
8
Monthly average spatial plot of CMAQ total carbon
before and after emissions reallocation for May
and August 2001
r0.36
May (Base)
r0.58
May (Reallocated)
r0.26
August (Base)
r0.51
August (Reallocated)
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r0.82
Monthly average spatial plot of CMAQ predicted
PM2.5 before and after emissions reallocation for
May and August 2001
r0.84
r0.64
r0.75
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1b. CMAQ CO evaluation using MOPITT

• Improvement of fire emissions inventory using
  satellite information
• - study impact of wildfire emissions
  reallocations on CMAQ
• - compare CMAQ predicted CO columns with MOPITT
  obs.
• - use MODIS fire count information and
  ground observations record for creating 2005 fire
  emissions for NEI
• Compare CMAQ optical depth with MODIS
  observations
• - compare CMAQ w/AERONET, MODIS and IMPROVE
• - develop PM2.5-AOD relationship
• Evaluation of MM5 ground temperature output
• - compare with aircraft, GOES, and MODIS
• - inter-relate skin temperature errors
  with PBL height errors

• While reallocating fire emissions does it improve
  CO comparison with data?
• With J. Szykman (EPA/NASA), C. Kittaka
  (NASA/LaRC/SAIC), Jim Godowitch, and Tom Pierce

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Passive MOPITT does not match CMAQ vertical
resolution hence weighting fn. used
IIdentity Matrix AAvg. kernel Cerror cov.
matrix
Using weighting function the mixing ratio is
adjusted at each level due to effects of all
possible levels.
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CMAQ Column CO Base and Reallocated columns with
MOPITT
Initial CMAQ MOPITT Data Revised CMAQ
13
CMAQ CO vs. MOPITT CO at MOPITT pressure levels
Base Fire Emissions and Reallocated Fire
Emissions - August 22-31Pacific Northwest Domain
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1c. 2005 fire emissions

• Improvement of fire emissions inventory using
  satellite information
• - study impact of wildfire emissions
  reallocations on CMAQ
• - compare CMAQ predicted CO columns with MOPITT
• - use MODIS fire count information and
  ground observations record for creating 2005 fire
  emissions
• Compare CMAQ optical depth with MODIS
  observations
• - compare CMAQ w/AERONET, MODIS and IMPROVE
• - develop PM2.5-AOD relationship
• Evaluation of MM5 ground temperature output
• - compare with aircraft, GOES, and MODIS
• - inter-relate skin temperature errors
  with PBL height errors

• Develop relationship between ground-based area
  burned and MODIS fire counts for 2002 and use the
  same for creating 2005 fire emissions

With George Pouliot, Tom Pace, David Mobley,
and Tom Pierce
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TERRA
Terra collects data on descending node
AQUA
Aqua collects data on ascending node
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Estimate Burned Area using Np
A is area burned in a spatial region labeled by
index i and during a fixed time period labeled
by index t Np No. of fire pixels obs. within
the same region during same time
period aconstant ? Area Burned/Np obtained
Region-wise
17
Scheme for MODIS pixel clustering and match up
with ground-reports

• Adjacency test

L lifetime of the fire n no. of obs.
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Burned Area in Acres/month and PM2.5 Emissions -
2002
Spring Prescribed Summer wildfire
19
MODIS imagery August 12, 2002 and PM2.5 emissions
from Biscuit Fire, OR. using Np-Area burned
relationship
NEI All emissions in 1 grid Satellite aids
in spatial re-distribution removal of excess NOx
hence over-estimate of surface ozone
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Summary on wildfire emissions study

• Emissions reallocation has re-distributed the
  total carbon concentrations from state-wide
  extent to a more localized fashion
• Transport patterns suggest that the MM5
  simulation captured shifts in wind direction
  adequately
• Reallocated CMAQ simulation adjusted with
  plume-rise predicts higher total carbon
  concentration
• Emissions reallocation can reduce biases in the
  base simulation of total carbon during non-fire
  periods
• Emissions reallocation yield a better
  correlation with IMPROVE data obtained from
  locations having a significant separation from
  the fire location
• CMAQ CO columns agree better after using MOPITT
  kernels
• MODIS fire detect information can improve spatial
  and temporal allocation of emissions from large
  fires with a high degree of confidence.

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2a, 2b CMAQ AOD comparison

• Improvement of fire emissions inventory using
  satellite information
• - study impact of wildfire emissions
  reallocations on CMAQ
• - compare CMAQ predicted CO columns with MOPITT
• - use MODIS fire count information and
  ground observations record for creating 2005 fire
  emissions for NEI
• Compare CMAQ optical depth with MODIS
  observations
• - compare CMAQ w/AERONET, MODIS and IMPROVE
• - spatial variability of AOD and develop
  PM2.5-AOD relationship
• Evaluation of MM5 ground temperature output
• - compare with aircraft, GOES, and MODIS
• - inter-relate skin temperature errors
  with PBL height errors

• To thoroughly characterize the performance of the
  emissions meteorological and chemical transport
  modeling components of the Models-3 system

2a With Rohit Mathur, Alice Gilliland, and
Steven Howard 2b With Adam Reff, Brian Eder
Steven Howard
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Two fold objective -- evaluation of CMAQ AOD

• To thoroughly characterize the performance of the
  emissions, meteorological and chemical/transport
  modeling components of the Models-3 system and
  build confidence within community.
• To pursue inter-relating satellite AOD with PM2.5
  (modeled and measured).

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CMAQ and Terra/MODIS AOD comparison
? Satellite Aerosol Optical Depth (AOD) products
offer new and challenging opportunities for
studying regional distribution of particulate
matter and scopes for rigorous operational
evaluation of modeling systems ? EPA standards
are based on total PM2.5 hence it is important to
assess model performance of total PM2.5 and the
impact of CMAQ model performance for individual
species on the total. -- First need to establish
whether AOD satellite data can be useful as
additional information for PM2.5 model
evaluation. -- Summer period of 2001 selected
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CMAQ-Terra/MODIS comparison
14 Layer
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CMAQ AOD Method
Based on Reconstructed Mass-Extinction Method
(Malm et al. 1994, Binkowski Roselle,
2003)Reconstructed extinction coefficients are
based on assumption that organic mass is soluble
up to 50 by mass
? OMOrganic mass, FSFine Soil, LACLight
Absorbing Carbon (elemental carbon), CMCoarse
mass. Concentration are in mg m-3 ? The
specific scattering coefficient 0.003, 0.004,
0.001 and 0.0006 are based on assuming
log-normal particle size distribution. ?
Modeled pressure, water-vapor mixing ratio and
temperature are used to compute the vapor
pressure and RH. ? Layer RH value is used to
calculate the exact humidity growth factor from
an LUT (Malm et al. 1994 Binkowski Roselle,
2003)
26
CMAQ AOD vs MODIS AOD on some eventful days
Regional Pattern ---Frontal activity
27
Time-series of CMAQ AOD, SSA and MODIS AOD
CMAQ Grid-cell 114, 30 having large fire in FL
(May 19-29)
CMAQ Grid-cell 30, 90 having large fire in WA.
(Aug 11-21)
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Wildfire signature on MODIS AOD
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Sulfate contributes 40
30
CMAQ AOD X 2 JJA 2001
MODIS Avg. AOD JJA 2001
2cmaq aod
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AOD Correlation Modis CMAQ JJA 2001
32
AOD NMB and NME JJA 2001
Normalized mean error (SABS(Model-Obs)/SObs)
100
Normalized mean bias (S(Model-Obs)/SObs) 100
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Good Days Bad Days JJA 2001
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Satellite AOD Imputation performed for cloudy
days

• Non-cloudy (Modis-AOD/Cmaq-AOD) Ratio
• Mean Ratio for each Land Use Type
• Gamma distribute Ratio for each LUSE
• Cloudy Day Use distribution to draw Ratio for
  LUSE
• Ratio Cmaq-AOD Imputed AOD

37
Summary on AOD study for JJA 2001

• CMAQ surface extinction due to particle
  scattering compares well with the IMPROVE
  nephelometer data
• Ratio of MODIS to CMAQ AOD is most of the time a
  factor of 1 to 10 higher than ratio of MODIS mass
  concentration to CMAQ PM2.5 mass concentration
  data
• Mean difference between MODIS and CMAQ AOD
  columns is 0.2
• Sulfate is found to be a dominant contributor to
  CMAQ AOD
• CMAQ AOD patterns reflect synoptic activities
  very clearly

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3a. MM5 skin temperature evaluation

• Improvement of fire emissions inventory using
  satellite information
• - study impact of wildfire emissions
  reallocations on CMAQ
• - compare CMAQ predicted CO columns with MOPITT
• - use MODIS fire count information and
  ground observations record for creating 2005 fire
  emissions for NEI
• Compare CMAQ optical depth with MODIS
  observations
• - compare CMAQ w/AERONET, MODIS and IMPROVE
• - develop PM2.5-AOD relationship
• Evaluation of MM5 ground temperature output
• - compare GT with aircraft, GOES, and
  MODIS
• - inter-relate skin temperature errors
  with PBL height errors

• Comparison of MM5 GT with MODIS, GOES and
  aircraft obs. over Houston during TexAQS-2000
• With Jason Ching Michael Mahoney (NASA/JPL)

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Terra/MODIS land surface temperature product

• MOD11A1 1 km gridded day, night global data.
• Provides per-pixel temperature in Kelvin with a
  cross track view-angle dependent algorithm
  applied to observations.
• Accuracy 1oK for land use (IGBP) with known
  emissivity

MOD11A1 1km LST Product
Footnote Processing comparison with GOES
aircraft LST product Data in integerized
sinusoidal (ISIN) projection re-sampled to
geographic system using MODIS Reprojection Tool
v3.3. Environment for Visualization (ENVI v4.2)
used for geo-referencing re-sampled data over the
Texas domain. A fair correspondence found between
4km aggregated MODIS LST and 4km GOES LST for the
hatched domain (GOES warmer by 1.5K to 2.5K
during daytime)
40
MM5 GT compares with GOES 4km windowed and MODIS
1km native
41
Sector-wise difference in thermal property
UCP data-rich zone (heavy built-up area)
42
Skin temperatures from MODIS provides a
diagnostic indicator of model performance.

• Inside Morphology database region
• Urbanized model predicts urban heat island
  successfully i.e., model bias is small in urban
  sector when compared to MODIS.
• Standard MM5 using Roughness approach produces
  poor description of the Houston heat island.
  Model bias is high in urban area.
• Outside Morphology database region
• Model predictions of skin temperatures are
  problematic an avenue to explore is the
  possibility of inaccurate land use specification.
  
• Model UCP extrapolation methodology,
  reexamination of designation of land use in
  mesoscale models and their physical properties
  are needed.
• Other simulation days, and nighttime results
  exhibit similar features

43
3b. Relate skin temperature error and PBL height
error

• Improvement of fire emissions inventory using
  satellite information
• - study impact of wildfire emissions
  reallocations on CMAQ
• - compare CMAQ predicted CO columns with MOPITT
• - use MODIS fire count information and
  ground observations record for creating 2005 fire
  emissions for NEI
• Compare CMAQ optical depth with MODIS
  observations
• - compare CMAQ w/AERONET, MODIS and IMPROVE
• - develop PM2.5-AOD relationship
• Evaluation of MM5 ground temperature output
• - compare with aircraft, GOES, and MODIS
• - inter-relate skin temperature errors
  with PBL height errors

• Infer inter-relation between skin temperature and
  PBL height error using EMD/HT method

44
Block avg T, PBL Height Spectra
TFE Spectra - Temperature
Temperature
PBL Height
Obs
Heimann Probe
Model
MM5 GT
TFE Spectra -PBL Height
Obs
Model

• Time --?

45
Hilbert Spectra to ascertain Tskin-Mixing Ht.
Relation
Heimann Skin Temp. minus MM5 Skin Temp.
MTP PBL Height minus MM5
Treating skin temperature PBL height error
(obs. Minus model) series as being non-stationary
46
Publications from CMAQ related projects

• NEI Fire emissions using MODIS 1 pub. In AE
  (reallocation-First Author) 1 pub. In Int. J.
  Appl. Rem. Sens. (with Pouliot) (Second author)
• Evaluation of CMAQ AOD using Semi-Empirical
  method 1 pub. (First Author) in JGR-A.
• Evaluation of MM5 skin temp. using MODIS GOES
  2 pubs.-Env. Model. Software Rem. Sens.
  Environment (First author in both)
• Evaluation of CMAQ Carbon Monoxide columns 1
  pub. (with Jim Szykman LaRC team) Geophys. Res.
  Lett. (Third author)
• CMAQ AOD spatial variability and connection with
  surface PM2.5 1 pub. Geophys. Res. Lett. (with
  Reff Eder)

Published Being Prepared Ready
for Communication
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Thank youRoy.Dev_at_EPA.gov(919) 541-5338till
October 31, 2007