Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona

Andrew Comrie, Jeremy E. Diem

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.

Original languageEnglish (US)
Pages (from-to)5023-5036
Number of pages14
JournalAtmospheric Environment
Volume33
Issue number30
DOIs
StatePublished - Dec 1999

Fingerprint

Climatology
carbon monoxide
Carbon monoxide
climatology
modeling
Error statistics
Meteorology
prediction
meteorology
forecast
timescale

Keywords

  • Air pollution forecast
  • Climate
  • Inversion
  • Statistical modeling
  • Urban air quality

ASJC Scopus subject areas

  • Atmospheric Science
  • Environmental Science(all)
  • Pollution

Cite this

Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona. / Comrie, Andrew; Diem, Jeremy E.

In: Atmospheric Environment, Vol. 33, No. 30, 12.1999, p. 5023-5036.

Research output: Contribution to journalArticle

@article{aa413e3c299e47f6aba302ba17ceed6d,
title = "Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona",
abstract = "We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.",
keywords = "Air pollution forecast, Climate, Inversion, Statistical modeling, Urban air quality",
author = "Andrew Comrie and Diem, {Jeremy E.}",
year = "1999",
month = "12",
doi = "10.1016/S1352-2310(99)00314-3",
language = "English (US)",
volume = "33",
pages = "5023--5036",
journal = "Atmospheric Environment",
issn = "1352-2310",
publisher = "Elsevier Limited",
number = "30",

}

TY - JOUR

T1 - Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona

AU - Comrie, Andrew

AU - Diem, Jeremy E.

PY - 1999/12

Y1 - 1999/12

N2 - We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.

AB - We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.

KW - Air pollution forecast

KW - Climate

KW - Inversion

KW - Statistical modeling

KW - Urban air quality

UR - http://www.scopus.com/inward/record.url?scp=0032599709&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032599709&partnerID=8YFLogxK

U2 - 10.1016/S1352-2310(99)00314-3

DO - 10.1016/S1352-2310(99)00314-3

M3 - Article

AN - SCOPUS:0032599709

VL - 33

SP - 5023

EP - 5036

JO - Atmospheric Environment

JF - Atmospheric Environment

SN - 1352-2310

IS - 30

ER -