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Project Number:
 
14-025
Title:
 
Development and Evaluation of an Interactive Sub-Grid Cloud Framework for the CAMx Photochemical Model
Lead PI:
 
Christopher Emery
Institution(s) Represented:
 
Environ - Christopher Emery, Texas A&M University - John Nielson-Gammon
AQRP Project Manager:
 
Gary McGaughey
TCEQ Project Liaison:
 
Khalid Al-Wali
Awarded Amount:
 
$256,261.00

Abstract
Development and Evaluation of an Interactive Sub-Grid Cloud
Framework for the CAMx Photochemical Model
 
The US Environmental Protection Agency (EPA) requires the use of photochemical models to demonstrate that emission control plans will achieve the federal standard for ground-level ozone (EPA, 2007).  The TCEQ uses the Comprehensive Air quality Model with extensions (CAMx) for research and regulatory photochemical modeling.  Previous research conducted for the TCEQ has concluded that improvements to the CAMx modeling system, including a sub-grid cloud convection treatment, are necessary to reduce model under prediction biases in oxidized nitrogen compounds in the upper troposphere.  Cloud convection at sub-grid scales is an important mechanism for exchanging boundary layer air with the free troposphere and for chemical processing.  The current sub-grid cloud approach within CAMx influences photolysis rates, scavenging by rainfall, and aqueous chemistry at grid scale, but does not explicitly treat these processes at cloud scale and does not include sub-grid convective transport.
  
Small-scale clouds are often widespread but they are not explicitly resolved by the grid scales employed in regional meteorological and photochemical modeling applications.  The physical effects from these sub-grid clouds are difficult to characterize accurately, but they can substantially influence many different atmospheric processes, including: boundary layer mixing, ventilation, and deep vertical transport of heat, moisture, and chemical tracers; radiative transfer and surface heat budgets; spatio-temporal precipitation patterns, intensity and wet scavenging rates; chemistry via photolysis and aqueous reactions; and certain environmentally-sensitive emission sectors (e.g., biogenic).  Cloud convection is also an important component for long-range transport of ozone, PM, and precursors.  The effects of sub-grid clouds on vertical transport, chemistry, and wet scavenging are addressed to varying degrees in off-line photochemical models (i.e., models like CAMx that operate separately from meteorological models that supply environmental inputs).  However, the spatio-temporal distributions of such clouds, and all the processes that occur within them, must be re-diagnosed because meteorological models do not export necessary information from their sub-grid cloud parameterizations.  This leads to potentially large inconsistencies between the models.  
 
Under this AQRP Project, ENVIRON and collaborators at the Texas A&M University (TAMU) will incorporate and extensively evaluate an explicit sub-grid cloud model within CAMx.  The primary goal of this work is to introduce shallow and deep convective cloud mixing at sub-grid scales.  Further, the investigators will develop an approach to improve interactions with chemistry and wet deposition to operate explicitly at sub-grid scales in tandem with the cloud mixing scheme.  The approach will tie into recent updates implemented in the Weather Research and Forecasting (WRF) model by researchers at EPA, whereby specific sub-grid cloud fields will be passed to CAMx to define their spatio-temporal distributions and mixing rates for the new sub-grid cloud algorithm.  This will yield a more consistent cloud-mixing-chemistry system across the WRF and CAMx models.  The new CAMx treatment will be tested for three convective episodes that occurred during the September 2013 Houston DISCOVER-AQ field study and the Spring 2008 START08 field study, particularly addressing tropospheric profiles of NOx, ozone, and other chemical tracers by comparing to in situ profiles from aircraft measurements.  The new model will be provided to TCEQ to support future regulatory and research-oriented ozone and PM modeling.  




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