Comparing Two Advection Solvers in MAQSIPShiang-Yuh Wu, Prasad Pai, Betty K. PunAERSan Ramon, CA17 March 2000

IntroductionAccurate numerical treatment of advection is important because errors can propagate in other processes (e.g., chemistry, deposition)Desired PropertiesMass conservationSmall numerical diffusionSmall phase errorsPositive definiteMonotonic

Bott Scheme and QSTSEBottConcentrations represented by a 4th order polynomial within each cellTemporal integration by flux form discretizationQSTSEConcentrations represented by quintic spline interpolatorsTemporal integration by Taylor series expansion (2 or 4 terms)

2-D Rotating Cone TestFrom Nguyen and Dabdub (2000): BottQSTSE (1)Peak (100)77101Mass Conservation1.0001.000Mass Distribution1.1250.998Relative Time1.02.5

(1) 4th Order Taylor Expansion

MAQSIP Framework

Base Case Model SimulationSCAQS 25-29 August 1987Domain: 63 x 28 grid cells, consistent with previous modeling exercisesGrid Resolution: 5 kmMM5 used to generate input meteorologyEmissions originated from UAM simulation

Upwind Simulation Results

Upwind Numerical Diffusion (Nashville Example)

Nashville Plume-in-Grid Simulation

Simulation Results at Other Sites

Effects of Courant Number

Decreasing CN from 0.7 to 0.5Increases computational time by 30%Results in a maximum difference of 25 ppb after 120 hours

ConclusionsIt is quite straightforward to incorporate a new advection solver into MAQSIPQSTSE shows improved performance compared to Bott solverReduced numerical diffusion at upwind locationsHigher concentrations at downtown and downwind locationsA Courant number of 0.5 or less is recommended

Acknowledgements

This work was funded by EPRI (WO8221-01)

QSTSE was obtained from Prof. Donald Dabdub of University of California, Irvine