ACCESS NUMBER: 37002/M05AC12302 

STUDY TITLE: Satellite Data Assimilation into Meteorological/Air Quality 

Models 

REPORT TITLE: Satellite Data Assimilation into Meteorological/Air Quality 

Models 

CONTRACT NUMBERS: 1435-01-04-CA-37002/M05AC12302 

SPONSORING OCS REGION: Gulf of Mexico 

APPLICABLE PLANNING AREAS: Central and Western Gulf of Mexico 

FISCAL YEARS OF PROJECT FUNDING: 2004, 2005, 2006, 2007, 2008 

COMPLETION DATE OF REPORT: July 2009 

COSTS: FY 2004: $115,000; FY 2005: $0; FY 2006: $160,192; CUMULATIVE 

PROJECT COST: $275,192 

PROJECT MANAGER: Richard T. McNider 

AFFILIATION: University of Alabama in Huntsville 

ADDRESS: University of Alabama in Huntsville, Huntsville, Alabama 35899 

PRINCIPAL INVESTIGATORS*: Richard T. McNider, Arastoo Pour Biazar 

KEY WORDS: Air quality modeling, satellite assimilation, sea breeze circulation, 

air quality impacts assessment, boundary layer, land surface parameterization, 

Gulf of Mexico, criteria pollutants, NAAQS 

BACKGROUND: Improving understanding of the near shore environment is 

important in order to assess the impact of offshore oil and gas exploration on the 

environment including air quality impacts. Regulators at the federal level and 

coastal states have a responsibility to ensure that State Implementation Plans 

(SIP) and new source review adequately addresses air quality impacts both 

onshore and in the coastal environment of offshore facilities. Since Prevention of 

Significant Deterioration (PSD) regulations incorporate offshore facilities and 

onshore new sources, this responsibility includes developing and assessing tools 

for sources offshore and in the onshore coastal environment. The Minerals 

Management Service (MMS) has a long history of carrying out studies and 

developing tools to improve air quality characterization and prediction in the 

coastal and near shore environment. 

Because of this responsibility, understanding of the coastal atmosphere including 

sea breezes, land breezes and nearshore atmospheric structure is important to 

properly assessing air quality impacts. The vertical shear in sea breeze regimes 

and timing of sea breeze events is important to plume spread and transport both 
for near shore facilities and on shore facilities. The behavior of sea breezes and 

coastal temperature and turbulence structure is tied to both sea surface 

temperatures and onshore land temperatures. Thus, the development of land 

surface parameterizations and parameter specifications (such as moisture 

availability, heat capacity, surface roughness) is important to proper specification 

of the atmospheric structure which is critical to air quality impacts assessment. 

Additionally, the coastal cloud structure is vitally important to surface heating 

rates, impacting boundary layer structure and temperature. Furthermore, coastal 

cloud modification of photolysis fields in photochemical processes is important to 

ozone and aerosol formation and decay. 

The University of Alabama in Hunstville (UAH) has had a long history of working 

with National Aeronautics and Space Administration (NASA), National Oceanic 

and Atmospheric Administration (NOAA) and applied agencies such as the 

National Weather Service, the U.S. Environmental Protection Agency (USEPA) 

and State air quality programs in developing and transferring satellite products 

and techniques to the user community. At the present UAH is supported by a 

NASA Applications Grant to transfer some of the techniques outlined in the 

present report into the USEPA Community Air Quality (CMAQ) modeling system. 

Through this process USEPA works with UAH and the user community in testing 

the techniques. The techniques then become part of the USEPA supported 

system that can be broadly disseminated and used by states and air quality 

consultants. The UAH expects that this synergistic relationship between NASA, 

NOAA and EPA in remote sensing tools will allow the results supported by MMS 

to be extended to a broad user community. 

OBJECTIVES: The overall goal of this project is to improve the performance of 

the meteorological/air quality models used in SIP applications by using satellite 

data. The specific objectives included: 1) utilization of geostationary satellite 

observations of land skin temperature to recover surface moisture content and 

thereby improve the partitioning of surface heat and moisture fluxes. 2) Utilizing 

the satellite observations to recover surface heat capacity. 3) To improve model 

representation of surface energy balance by utilizing satellite observations of 

incident radiation at the surface. 4) To utilize satellite observations of clouds in 

regulating photochemistry within the U.S. Environmental Protection Agency 

(USEPA) Community Multiscale Air Quality (CMAQ) modeling system. 

DESCRIPTION: The work presented in this report is directed at improving the 

specification of surface parameters such as insolation, soil moisture and surface 

heat capacity that control the developing land boundary layer through use of 

satellite data. The tools and techniques using the satellite data are tested in the 

context of the type of boundary layer models used in air quality models. In 

particular, the techniques using satellite data for determining soil moisture 

availability (McNider et al. 1994; Mackaro, 2008), surface heat capacity (McNider 

et al. 2005), insolation (McNider et al 1995) and photolysis fields (Pour-Biazar et 

al. 2007) are examined in the context of recent national level air quality studies 

undertaken along the Texas Gulf Coast (TexAQS2000). 
ACCESS NUMBER: 37002/M05AC12302 

SIGNIFICANT CONCLUSIONS: Use of satellite observed clouds significantly 

improved model predictions of ozone in several locations. The results reveal that 

lack of observed clouds in the standard model can drastically alter the predicted 

atmospheric chemical composition within the boundary layer and exaggerate or 

under-predict ozone concentrations. Cloud impact is acute and more 

pronounced over the emission source regions and leads to large errors in the 

model predictions of ozone and its by-products. Over Houston-Galveston Bay 

area, the presence of clouds altered the chemical composition of the atmosphere 

and reduced the net surface removal of reactive nitrogen compounds. 

The use of satellite observed skin temperature outlined the importance of 

consistent use of skin and aerodynamic temperature representation and iteration 

processes when incorporating surface information from satellite data into 

mesoscale models. The three-temperature system developed and used in this 

project can be directly implemented within currently forecasting systems in which 

the boundary layer parameterization can interact with a slab land surface model. 

While this is a limited set of model configurations, the implications of inconsistent 

temperature use is likely applicable to all situations where surface information 

from satellites is used. 

STUDY RESULTS : This study showed that at some locations the errors in 

ozone concentration arising from inaccurate cloud cover specification reached as 

high as 60 ppb which was mostly corrected by the use of our technique. Such 

errors are significant and can have considerable impact on air quality modeling 

efforts. However, other sources of error in the model due to inadequate cloud 

specification are as important and need to be addressed. The assimilation 

technique presented here only corrected the photolysis rates and did not account 

for the inconsistencies in dynamics and aqueous-phase chemistry. One 

approach to resolve this issue would be the assimilation of observed clouds in a 

dynamically consistent manner in the model.

This study also indicated that the highly uncertain specification of surface 

moisture availability can be improved using satellite data. However, it was also 

shown that the application of assimilation techniques, such as McNider et al. 

1994 technique, must be carefully done within a model framework. Results from 

test cases indicated how sensitive the land surface system is to changes in 

parameters within a surface energy balance. Future work might examine the 

impacts of using more elegant and numerically stable solvers in this system, as 

well as reevalutaing how operator splitting is done within models. 

STUDY PRODUCTS: 

Biazar, A.P., R.T. McNider, and S. Mackaro. 2010. Satellite data assimilation 

into meteorological/air quality models. U.S. Dept. of the Interior, Bureau of 

Ocean Energy Management, Regulation and Enforcement, Gulf of Mexico 

OCS Region, New Orleans, LA. OCS Study BOEMRE 2010-050. 70 pp. 
Mackaro, Scott, 2008: The importance of physically consistent temperature 

representation in land surface satellite assimilation, Ph.D. Dissertation, 

Atmospheric Science Department, University of Alabama in Huntsville, 157pp. 

McNider, Richard T., William M. Lapenta; Arastoo Pour Biazar, Gary J. Jedlovec, 

Ronnie J. Suggs, Jonathan Pleim. Retrieval of Model Grid-Scale Heat 

Capacity Using Geostationary Satellite Products. Part I: First Case-Study 

Application. Journal of Applied Meteorology, Vol. 44, Issue 9, 1346-1360, 

2005. (AN18622838) 

Pour-Biazar, Arastoo, Richard T. McNider, Shawn J. Roselle, Ron Suggs, Gary 

Jedlovec, Soontae Kim , Daewon W. Byun, Jerry C. Lin, Thomas C. Ho, 

Stephanie Haines, Bright Dornblaser, Robert Cameron. (2007), Correcting 

photolysis rates on the basis of satellite observed clouds, J. Geophys. Res, 

112, D10302, doi:10.1029/2006JD007422.