Evaluating the performance of regional-scale photochemical modeling systems Part III - Precursor predictions

Biswas, J; Hogrefe, C; Rao, ST; Hao, W; Sistla, G

HERO ID

150701

Reference Type

Journal Article

Year

2001

HERO ID 150701
In Press No
Year 2001
Title Evaluating the performance of regional-scale photochemical modeling systems Part III - Precursor predictions
Authors Biswas, J; Hogrefe, C; Rao, ST; Hao, W; Sistla, G
Journal Atmospheric Environment
Volume 35
Issue 35
Page Numbers 6129-6149
Abstract Two regional-scale photochemical modeling systems, RAMS/UAM-V and MM5/MAQSIP, are used to simulate precursor concentrations for 4 June--31 August 1995 period. The time series of simulated and observed precursor concentrations are spectrally decomposed into intra-day, diurnal, synoptic, and longer-term (baseline) forcings and compared on each time scale. The results reveal that the observed and modeled precursor concentrations are uncorrelated on the intra-day time scale for both modeling systems while correlations are higher on longer time scales. In observations, the variability in NO, concentrations is dominated by the diurnal and synoptic-scale processes, while NOy is found to vary most on the synoptic time scale. In observations of volatile organic compounds (VOCs), the variability is dominated by the diurnal and synoptic processes for both biogenic and anthropogenic hydrocarbons. The pattern seen in the observations, in terms of the relative contribution of different temporal components to the total variance, is better captured by the two modeling systems for NO, than for NO, and VOCs. There are differences between model predictions and observations in terms of the actual magnitudes of variances of each temporal component. These results suggest the need to cover longer time periods in modeling simulations to resolve longer-term processes, because they seem to play a dominant role in dictating the precursor variability. (C) 2001 Elsevier Science Ltd. All rights reserved.
Doi 10.1016/S1352-2310(01)00401-0
Wosid WOS:000172958000007
Url http://linkinghub.elsevier.com/retrieve/pii/S1352231001004010
Is Certified Translation No
Dupe Override No
Comments Source: Web of Science WOS:000172958000007
Is Public Yes
Keyword air pollution modeling; ozone precursor analysis; model evaluation; time series analysis
Is Qa No