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Project Number:
Use of satellite data to improve specifications of land surface parameters
Lead PI:
Richard McNider
Institution(s) Represented:
University of Alabama - Huntsville - Richard McNider, George Mason University - Daniel Tong
AQRP Project Manager:
Vincent Torres
TCEQ Project Liaison:
Bright Dornblaser
Awarded Amount:

Use of Satellite Data to Improve Specifications of land surface Parameters
University of Alabama in Huntsville, NOAA, George Mason University
Land surface processes play a critical role in air quality model performance. Land surface temperatures impact boundary layer heights and turbulent mixing. Temperature gradients can also produce local wind patterns. For example in Houston the land-sea temperature gradient drives both the daytime sea breeze and nighttime land breeze. This growing temperature contrast in the morning is responsible for physical features such as a dead zone ahead of the sea breeze front, which develops as the land sea pressure gradient force opposes the large scale weather pattern. This dead zone allows the accumulation of precursors that are part of the peak ozone levels later in the day as this dead zone moves northward with the sea breeze front.  Surface temperatures also impact air quality levels through temperature dependence of  evaporative emissions and biogenic emissions. Temperatures also control the thermal decomposition of nitrogen species, which in turn impacts the efficiency of ozone production per NO molecule emitted. Thus, not only can temperatures affect ozone production, they can impact the efficacy and efficiency of control strategies.
It is the purpose of this project to evaluate and improve the performance of the land surface models used in the meteorological model (WRF) by the use of satellite skin temperatures to better specify physical parameters associated with land use classes. While considerable work has been done by the national community and especially in Texas to develop improved land use classifications, land use classes themselves are not directly used in models. Rather, physical parameters such as heat capacity, thermal resistance, roughness, surface moisture availability, albedo etc. associated with a land use class are actually used in the land surface model. Many of the land use class associated parameters such as surface moisture availability are dynamic and ill-observed  depending on antecedent precipitation and evaporation, soil transport, the phenological state of the vegetation, irrigation applications etc. Other parameters such as heat capacity, thermal resistance or deep soil temperature are not only difficult to observe they are often unknowable a priori. This project will use satellite data to retrieve or adjust these critical land surface parameters.
The project will first develop skin temperature data sets from geostationary satellites and polar orbiting platforms and make direct comparisons to the skin temperatures from the WRF land surface model. This will be done for intensive field programs such as the recent DISCOVER-AQ  and SEAC4RS campaigns. Second, techniques to use satellite observed skin temperatures to adjust land surface parameters such as surface moisture and surface thermal resistance will be tested to improve WRF skin and air temperatures. Extensive evaluation of model performance will be made against standard National Weather Service observations, special observations made during the DISCOVERY-AQ field campaign in September 2013 and other independent satellite observations.

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