P. Pai et al., Assessment of the nested grid model estimates for driving regional visibility models in the southwestern United States, J AIR WASTE, 50(5), 2000, pp. 818-825
Citations number
17
Categorie Soggetti
Environment/Ecology,"Environmental Engineering & Energy
The Nested Grid Model (NGM) is a primitive-equation meteorological model th
at is routinely exercised over North America for forecasting purposes by th
e National Meteorological Center. While prognostic meteorological models ar
e being increasingly used to drive air quality models, their use in conduct
ing annual simulations requires significant resources. NGM estimates of win
d fields and other meteorological variables provide an attractive alternati
ve since they are typically archived and readily available for an entire ye
ar. Preliminary evaluation of NGM winds during the summer of 1992 for appli
cation to the region surrounding the Grand Canyon National Park showed seri
ous shortcomings. The NGM winds along the borders between California, Arizo
na and Mexico tend to be northwesterly with a speed of about 6 m/sec, while
the observed flow is predominantly southerly at about 2-5 m/sec. The mesos
cale effect of a thermal low pressure area over the highly heated Southern
California and western Arizona deserts does not appear to be represented by
the NGM because of its coarse resolution and the use of sparse observation
s in that region. Tracer simulations and statistical evaluation against spe
cial high resolution observations of winds in the southwest United States c
learly demonstrate the northwest bias in NGM winds and its adverse effect o
n predictions of an air quality model. The "enhanced" NGM winds, in which s
elected wind observations are incorporated in the NGM winds using a diagnos
tic meteorological model provide additional confirmation on the primary cau
se of the northwest bias. This study has demonstrated that in situations wh
ere limited resources prevent the use of prognostic meteorological models,
previously archived coarse resolution wind fields in which additional obser
vations are incorporated to correct known biases provide an attractive opti
on.