**[NASA Earth Science Enterprise]{.smallcaps}**

**[Applications Division]{.smallcaps}**

*Air Quality Applications Project\
Prototyping and evaluating the use of satellite data to improve\
the Community Mesoscale Air Quality(CMAQ) Model*

![](media/image1.wmf){width="1.1901574803149606in"
height="0.9838582677165354in"}![](media/image2.png){width="1.3200787401574803in"
height="1.1456692913385826in"}

**"Project CMAQ" Project Plan**

[1 Project CMAQ Purpose 3](#project-cmaq-purpose)

[1.1 Purpose & Scope 3](#purpose-scope)

[1.2 Project Goal & Objectives 3](#project-goal-objectives)

[2 Project CMAQ Team 4](#project-cmaq-team)

[2.1 CMAQ Team Partnerships 4](#cmaq-team-partnerships)

[2.2 CMAQ Team Collaboration Roles 4](#cmaq-team-collaboration-roles)

[3 Project CMAQ Work Breakdown Structure
5](#project-cmaq-work-breakdown-structure)

[4 Project CMAQ Implementation 5](#project-cmaq-implementation)

[4.1 Implementation Approach 5](#implementation-approach)

[4.2 Project CMAQ Deliverables 8](#project-cmaq-deliverables)

[4.3 Project CMAQ Schedule & Milestones
9](#project-cmaq-schedule-milestones)

[4.4 Budget 10](#budget)

[4.5 Performance Measures 10](#performance-measures)

[5 Project CMAQ References 10](#project-cmaq-references)

[6 Project CMAQ Signature Page 11](#project-cmaq-signature-page)

# Project CMAQ Purpose

## Purpose & Scope

The U.S. Environmental Protection Agency's Community Multiscale Air
Quality (CMAQ) modeling system was developed to improve the
environmental management (federal, state, Tribal, and local) community's
ability to evaluate the impact of air quality management practices for
multiple pollutants at multiple scales and to improve the scientist's
ability to better probe, understand, and simulate chemical and physical
interactions in the atmosphere.

US EPA utilizes monitoring data and air quality simulation models for
performing assessments of compliance with the National Ambient Air
Quality Standards (NAAQS), and the development of control strategies in
the required State Implementation Plans (SIPSs). Sources of secondary
pollutants such as ozone and fine particulate matter are transported
over large domains, both regional and continental, as well as locally
produced through photochemical and heterogeneous processes. The effect
of global and supra-regional pollution events on regional air quality is
not well understood from the current monitoring of surface distributions
and current regional modeling domains. Often the lateral boundary
conditions for the regional models are a fixed set of climatological
mean values. The vertical domain of current regional air quality models
extends to at most the troposphere, which is inadequate to reflect
stratospheric influence.

Regional air quality model simulations may be greatly improved when
upper and lateral boundary air pollutant data are available. Such data
can provide more realistic and accurate descriptions of influx of
pollutants, and provide a means to account for the contributions of
pollutants transported over larger distances. The goal of this project
is to determine if multi-scale modeling and data assimilation frameworks
for linking satellite and in-situ measurements of atmospheric chemical
species can improve the prediction of large-scale transport and local
productions of surface ozone.

## Project Goal & Objectives

The primary objectives of this project are to prototype and evaluate the
efficacy of two techniques to provide boundary conditions for ozone into
the Models-3 Community Multiscale Air Quality (CMAQ) using satellite
retrievals. The first approach is to provide lateral boundary conditions
generated from a global model output through a global assimilation of
satellite-observed ozone. The second approach adds the direct
assimilation of satellite ozone retrievals from GOES into the Models-3
Community Multiscale Air Quality (CMAQ) system.

Predicated on adequate and timely funding, this project will meet the
following goals and objectives:

A. By summer 2004, a Task Order or equivalent will be in place to fund
the non-NASA work required to evaluate the use of satellite data as
boundary conditions in CMAQ.

B. By March, 2005, results of the analysis will be discussed among the
team members and partners in technical meeting(s).

C. Transition plans for the use of boundary conditions in CMAQ will be
formulated based on the project's outcome and implemented by the user
Agency (US EPA).

The project is expected to be complete in 1-2 years.

# Project CMAQ Team 

## CMAQ Team Partnerships 

The CMAQ project is scientist-led, in a 'NASA senior researcher/group
leader-to-external Agency senior researcher/group leader' project model.
The Principal Investigator engages a team of NASA, EPA, NOAA,
university, and private industry personnel to achieve the project
objectives. The activity is highly collaborative, not directive, and as
such requires agreement on shared goals and objectives. Many of the key
participants are not funded by NASA, and participate on the basis of
professional respect for the NASA work and close alignment of the work
with their functional or research responsibilities. Consequently, NASA
management of these activities is modeled along the lines of Research
and Analysis tasks.

NASA's primary roles in the CMAQ project include the end-to-end
responsibility of fostering inter-Agency relationships at the senior
researcher/ responsible group leader level, the establishment of
inter-Agency mutually-agreed requirements and goals for the project's
evolution, establishment and supervision of the specific jointly-funded
task agreement with the CMAQ developers, interpretation of the outcome
of the analysis with advice on next steps in EPA's development of CMAQ.

## CMAQ Team Collaboration Roles

The specific partner organizations for the CMAQ project and their
general role in the collaboration are as follows:

1\. NASA air quality applications team at NASA (Code YO )

2\. NASA RAQMS Principal Investigator and co-Investigators (Code YS )

3\. US EPA ORD/ NERL/Model Evaluation and Applications Research Branch
(Alice Gilliland, Chief, CMAQ)

4\. Dr. Daewon Byun, University of Houston, formerly of US EPA (CMAQ
Development)

5\. NOAA NESDIS, Office of Research and Applications, Satellite
Meteorology and Climatology Division (Dr. Shoba Kondragunta, GOES Data)

6\. Space Science and Engineering Center (SSEC) at the University of
Wisconsin (Drs. Jun Li and Chris Schmidt, GOES ozone algorithms)

> In this project, investments by NASA's Earth Science Division in
> measurements, models, and analysis will be leveraged to strengthen the
> understanding of air pollution modeling. Space based, airborne, and
> surface measurement networks all contribute significantly to the
> project's success. NASA Research and Analysis program has funded the
> development of models and analysis tools for the understanding of
> atmospheric composition that we use in this project, and we gratefully
> acknowledge this support.

# Project CMAQ Work Breakdown Structure

This project operates under the WBS provided here at top level.

1.  CMAQ Project Management (D.O.Neil, NASA)

2.  Test CMAQ with globally assimilated satellite data as boundary
    conditions (BC). (Lead, D. Byun, UH with A. Gilliland, US EPA)

3.  Evaluate CMAQ performance with globally assimilated satellite data
    as BC. (Lead, R.B. Pierce, NASA)

4.  Test CMAQ with direct assimilation of GOES ozone data.. (Lead, D.
    Byun, UH with S. Kondragunta, NOAA NESDIS)

5.  Evaluate CMAQ with direct assimilation of GOES ozone data. (Lead,
    R.B. Pierce, NASA)

6.  Prepare benchmark report. (Lead, NASA).

# Project CMAQ Implementation

## Implementation Approach

The global ozone analysis that provides lateral boundary conditions is
generated from a chemical assimilation approach that assimilates
stratospheric as well as tropospheric chemical species. T

he approach involves the joint assimilation of stratospheric profile and
total column retrievals. This is a logical extension of the work of
Fishman, et al. \[1990\] who demonstrated that one could extract
seasonal tropospheric ozone residuals (TOR) from differences between
total O3 and stratospheric column inferred from stratospheric O3 profile
measurements. By assimilating both the stratospheric profile and total
column measurements physically consistent O3 distributions can be
produced. By adequately accounting for the spatial and temporal
variations in the stratospheric column, the errors that limited previous
daily TOR analyses to the tropics and subtropics \[Fishman and Balok,
1999\] will be reduced.

The modeling tools used for the global assimilation are the LaRC
Lagrangian Chemical Transport Model (LCTM) \[Pierce et al., 1997, 1999,
2003\], and the LaRC/UW Regional Air Quality Modeling System (RAQMS).
RAQMS is a global to regional scale air quality modeling/data
assimilation system developed at NASA LaRC in collaboration with
researchers at the University of Wisconsin. These models are used to
assimilate global satellite observations through a Statistical Digital
Filter (SDF) assimilation system \[Stobie, 1985, 2000\]. SDF is a
relatively simple optimal interpolation approach to data assimilation
developed at the Goddard Space Flight Center Data Assimilation Office.

The RAQMS global assimilation is decomposed into two parts. Solar
occultation measurements are assimilated first. In this step the LCTM is
initialized with stratospheric solar occultation measurements which are
trajectory mapped to the assimilation times (6 hourly). The solar
occultation ozone measurements are retained for up to 5 days, depending
on the local chemical lifetime. The mapped measurements are used to
define a local incremental adjustment to the stratospheric ozone within
the RAQMS vertical grid structure. The TOMS total column measurements
are assimilated next. This step involves determining a total column
"first guess" and then TOMS column measurements within +/- 3hrs of the
assimilation time are used to define an incremental adjustment to the
total column. This incremental adjustment is distributed uniformly as a
constant mixing ratio increment within RAQMS. The resulting 6 hourly
global chemical analysis will be used to constrain initial and lateral
bounary conditions for CMAQ regional chemical predictions.

The specific description of the tasks involved in implementing this
project are described below.

***Task 1. CMAQ Simulation Runs and Analysis of Results (Case Study
Approach -- Southern Oxidation Study 1999 (SOS 99))***

Using CMAQ version 4.3 with SDF, conduct a model simulation for the SOS
99 period of June 15 --July 15. The modeling domain shall be the Eastern
half of US continent. The model input datasets (meteorology, emissions,
and time dependent lateral boundary condition) covering the SOS 99
period will be provided. The partners shall work in a collaborative
fashion on the development of the methodologies to ingest the lateral
and top boundary conditions from global RAMQS simulation into CMAQ
v.4.3. All partners shall work with NASA and the US EPA to benchmark the
performance of the CMAQ simulation with lateral boundary conditions as
follows:

The Model Evaluation and Applications Research Branch of the Atmospheric
Modeling Division within the National Exposure Research Laboratory of US
EPA Office of Research and Development has completed a simulation using
CMAQ v.4.3 for the period from June 15 to July 15. The benchmark
activity will be a controlled test where the simulation from EPA will be
used to define the baseline. A comparison will be made to identify
resulting differences. The comparison shall include the model predicted
concentrations from the baseline CMAQ v.4.3 simulation with the fixed
boundary conditions and with the satellite/RAQMS-derived lateral /top
boundary conditions against observed (SOS 99) data. Using standard
statistical measures typically used to evaluate model performance (e.g.,
root mean square, mean bias, normalized mean bias, correlation
coefficient, etc.) the contractor shall assess whether the CMAQ v.4.3
simulation with lateral boundary conditions shows better performance.

1)  Test read of RAQMS 6hrly global chemical fields in Netcdf format.
    Determine additional auxiliary data requirements from RAQMS.

2)  Define mapping of RAQMS chemical species into CMAQ CB4 mechanism

-   decompose NOy, Ox, families into individual species

-   repartition NMHC species to account for RAQMS extension of CB4

(Note: CMAQ does not have long-life species such as Cly and Bry, etc.)

3)  Define UH CMAQ experimental constraints to assure compliance with
    previous (no lateral boundary conditions) EPA SOS assessment run

-   emission inventories

-   chemical mechanism

-   vertical/horizontal grid resolution

-   CMAQ version

4)  Acquire 6hr global RAQMS chemical fields/auxiliary data from
    NASA/LaRC

-   map RAQMS chemical fields to CMAQ horizontal, vertical, and temporal
    resolution

-   map RAQMS chemical fields to CMAQ CB4 chemical species

5)  Acquire meteorological fields (MM5/MCIP) from EPA/ORD for UH CMAQ
    experiment

-   characterize key meteorological parameters affecting pollutant
    transport

6)  Acquire emission data sets (SMOKE) for EPA/ORD UH CMAQ experiment

-   Perform quality assurance check of the emissions data

7)  Acquire SOS observation dataset for evaluation

-   Obtain SOS analysis data from EPA and NASA/LaRC

8\) Conduct test (short period) CMAQ standard (no BC) assessment run

-   verify that UH CMAQ run is identical to EPA SOS99 assessment run

8)  9\) Conduct June-July, 1999 CMAQ assessment run

***Task 2. Evaluation of the impact of GOES ozone on SOS99 CMAQ
assessment modeling (in partnership with UW-SSEC)***

1)  Determine appropriate point within CMAQ modeling system to interface
    UW SDF assimilation

> \- should be point in CMAQ time-stepping loop where output files are
> written
>
> \- assimilation requires gridded first guess ozone field and first
> guess error field

-   SDF column assimilation interface uses model output history files
    and outputted first guess error fields

-   SDF column assimilation is a separate executable which is spawned
    from RAQMS and updates the model output history files

-   RAQMS then reads in model output history files, replacing first
    guess ozone with assimilated ozone

2)  Port SDF (Fortran) software onto UH Linux platform

-   Currently running on Linux (RedHat) platform, being implemented SGI
    UNIX platform

-   Modify Makefile for UH parallel Linux machine

3)  Modify SDF to conduct GOES instead of solar occultation + TOMS
    assimilation

-   replace solar occultation assimilation step (subroutine call) with
    build of ozone column above CMAQ upper boundary (obtained from RAQMS
    global ozone)

-   total column ozone is CMAQ column to model top + RAQMS global column
    above

-   GOES column assimilation is then identical to TOMS column
    assimilation procedure

-   NOTE: Need to consider replacing CMAQ ozone profile with RAQMS
    global analyses at levels below CMAQ upper boundary since CMAQ may
    not provide a good "first guess" in the upper troposphere.

4)  Implement SDF interface and error growth model in CMAQ

5)  Acquire GOES ozone column for June-July, 1999

-   Jun Li (CIMSS) is PI of the GOES ozone column data project, and
    Chris Schmit (CIMSS) developed the retrieval

-   Provide NASA/LaRC acquired data from CIMSS, and involve NESDIS for
    providing GOES ozone data to UH

6)  Acquire software from NASA/LaRC to convert GOES files into SDF input
    files

-   Use ASCII file conversion LaRC

7)  Repeat step 7 of Task 1, SOS99 CMAQ assessment modeling experiment
    with SDF assimilation of GOES data

> \- error growth model requires estimate of standard deviation of
> errors, this means that two assimilation runs need to be conducted,
> the first run assumes a constant (%) model error and the standard
> deviation of errors are calculated from the increment. The second run
> is the final one, it uses the standard deviation of errors and the
> error growth model to estimate the first guess error.

Coordinate with EPA/ORD, NASA/LaRC, and NOAA/NESDIS in statistical
evaluation of the impact of lateral BC and GOES assimilation on CMAQ
SOS99 assessment experiment

## Project CMAQ Deliverables

The ozone project will be complete in FY05. Deliverables include:

1.0 Task 1 Deliverable: Evaluation of Global RAQMS-CMAQ simulation
results.

2.0 Task 2 Deliverable: Evaluation of GOES/SDF-CMAQ results.

3.0 A final project technical report of work done, including the
following components:

> Evaluation report (Dr. Byun)
>
> Benchmarking report (NASA)

4.0 Scientific article will be published in refereed journals for the
scientific community.

We expect to initiate a closely related project to evaluate the use of
satellite observations of aerosol in CMAQ. Additional team members will
participate in this CMAQ aerosol project, to represent the science
expertise in aerosol modeling (Dr. M.Chin) and in aerosol retrievals
(MODIS AOD, Dr. A. Chu; CALIPSO products, Dr. O. Ali, and others). The
CMAQ aerosol project will be further defined in FY05.

## Project CMAQ Schedule & Milestones 

![](media/image3.wmf){width="9.994444444444444in"
height="4.034027777777778in"}

Project CMAQ, developed by the IDEA team, is one project under NASA's
National Air Quality Applications Program. This project is designed to
address environmental data needs in modeling for federal decision
making. US EPA and NOAA are partners with NASA in this prototype for the
use of satellite data as constraints on the chemical modeling of the
lower atmosphere for use in air quality management on behalf of the
public.

## Budget 

NASA's Air Quality Program plan assigns \$600K for FY 04 and \$650 K for
FY 05 to Project CMAQ as procurement funding (civil service expenses are
excluded from this funding). Specific expenses in FY 04 and FY05 include
support staff to deliver RAQMS results for the CMAQ testing, partial
funding to UW-SSEC for transition of assimilation software to US EPA,
funding for Dr. Byun, and contractor travel.

## Performance Measures

Progress on the CMAQ project can be assessed through:

1.  Task in place with Dr. Byun/University of Houston as scheduled.

2.  Technical interchange meetings occur as scheduled.

3.  Benchmark report prepared and submitted to NASA HQ.

4.  Results of this project will be presented in scientific conferences
    and peer-reviewed journals.

5.  Additional, informal documentation of progress is demonstrated
    through occasional key activity reports through the internal NASA
    reporting system.

# Project CMAQ References

Fishman, Jack; Watson, Catherine E; Larsen, Jack C; Logan, Jennifer A.
Distribution of tropospheric ozone determined from satellite data.
Journal of Geophysical Research, Washington, DC. Vol. 95, no. D4, pp.
3599-3617. 1990.

Fishman, Jack and Amy E. Balok. Calculation of daily tropospheric ozone
residuals using TOMS and empirically improved SBUV measurements:
Application to an ozone pollution episode over the eastern United
States. JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 104, NO. D23, PAGES
30,319--30,340, 1999

Fairlie, T. Duncan, R. Bradley Pierce, William L. Grose, Gretchen
Lingenfelser, Max Loewenstein, James R. Podolske. Lagrangian forecasting
during ASHOE/MAESA: Analysis of predictive skill for analyzed and
reverse-domain-filled potential vorticity. JOURNAL OF GEOPHYSICAL
RESEARCH, VOL. 102, NO. D11, PAGES 13,169--13,182, 1997.

Lingenfelser, Gretchen S., William L. Grose, Ellis E. Remsberg, T.
Duncan Fairlie, R. Bradley Pierce. Comparison of satellite and in situ
ozone measurements in the lower stratosphere. JOURNAL OF GEOPHYSICAL
RESEARCH, VOL. 104, NO. D11, PAGES 13,971--13,980, 1999.

R. B. Pierce, J. Al-Saadi, T. D. Fairlie, M. Natarajan, V. L. Harvey, W.
L. Grose, J. M. Russell III, R. Bevilacqua, S. D. Eckermann, D. Fahey,
P. Popp, E. Richard, R. Stimpfle, G. C. Toon, C. R. Webster, J. Elkins.
Large-scale chemical evolution of the Arctic vortex during the 1999/2000
winter: HALOE/POAM III Lagrangian photochemical modeling for the SAGE
III---Ozone Loss and Validation Experiment (SOLVE) campaign. JOURNAL OF
GEOPHYSICAL RESEARCH, VOL. 108, NO. D5, 8317, doi:10.1029/2001JD001063,
2003.

#  Project CMAQ Signature Page

This document contains the project plan to evaluate the use of satellite
data as boundary/initial conditions to improve the Community Mesoscale
Air Quality Model (CMAQ) under the joint auspices of NASA (Air Quality
Applications) and US EPA (Office of Research and Development) with the
partnership of environmental data from NOAA.

The National Applications Program has reviewed the plan and agrees that
the plan appropriately reflects the goals, objectives, and activities
for the program element to serve the Earth Science Applications Program,
ESE, NASA, the Administration, and Society.

+------------------------------------------------+----+---------------+
| Doreen Osowski Neil                            |    | Date          |
|                                                |    |               |
| Air Quality Applications Group Leader          |    |               |
|                                                |    |               |
| NASA Langley Research Center                   |    |               |
|                                                |    |               |
| Hampton, VA 23681-0001                         |    |               |
+------------------------------------------------+----+---------------+
|                                                |    |               |
+------------------------------------------------+----+---------------+
| S T Rao                                        |    | Date          |
|                                                |    |               |
| Director, Air Quality Modeling Division        |    |               |
|                                                |    |               |
| E243-02                                        |    |               |
|                                                |    |               |
| USEPA Mailroom                                 |    |               |
|                                                |    |               |
| Research Triangle Park, NC 27711 919-541-4542  |    |               |
+------------------------------------------------+----+---------------+
|                                                |    |               |
+------------------------------------------------+----+---------------+
| Mitch D. Goldberg                              |    | Date          |
|                                                |    |               |
| Director, Satellite Meteorology and            |    |               |
| Climatology Division                           |    |               |
|                                                |    |               |
| NESDIS HQTR Route: E/RA2                       |    |               |
|                                                |    |               |
| Camp Springs, MD                               |    |               |
+------------------------------------------------+----+---------------+
|                                                |    |               |
+------------------------------------------------+----+---------------+
| Lawrence Friedl                                |    | Date          |
|                                                |    |               |
| Air Quality Program Manager                    |    |               |
|                                                |    |               |
| NASA Earth Science Applications Program        |    |               |
|                                                |    |               |
| NASA Headquarters, Washington, DC              |    |               |
+------------------------------------------------+----+---------------+
|                                                |    |               |
+------------------------------------------------+----+---------------+
| Ronald J. Birk                                 |    | Date          |
|                                                |    |               |
| Director, Earth Science Applications Division  |    |               |
|                                                |    |               |
| NASA Earth Science Applications Program        |    |               |
|                                                |    |               |
| NASA Headquarters, Washington, DC              |    |               |
+------------------------------------------------+----+---------------+