PlumX Metrics
Embed PlumX Metrics

The Influence of Meteorology Initialization on Ozone Forecasting in the Great Lakes Region during MOOSE Study

Atmosphere, ISSN: 2073-4433, Vol: 14, Issue: 9
2023
  • 1
    Citations
  • 0
    Usage
  • 3
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
  • Captures
    3
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Research Reports on Meteorology from Environment and Climate Change Canada Provide New Insights (The Influence of Meteorology Initialization on Ozone Forecasting in the Great Lakes Region during MOOSE Study)

2023 SEP 14 (NewsRx) -- By a News Reporter-Staff News Editor at Ecology Daily News -- Investigators discuss new findings in meteorology. According to news

Article Description

This study investigates the influence of meteorology initialization on surface ozone prediction in the Great Lakes region using Canada’s operational air quality model (GEM-MACH) at a 2.5 km horizontal resolution. Two different initialization techniques are compared, and it is found that the four-dimensional incremental analysis updating (IAU) method yields improved model performance for surface ozone prediction. The IAU run shows better ozone regression line statistics (y = 0.7x + 14.9, R = 0.2) compared to the non-IAU run (y = 0.6x + 23.1, R = 0.1), with improved MB and NMB values (3.9 ppb and 8.9%, respectively) compared to the non-IAU run (4.1 ppb and 9.3%). Furthermore, analyzing ozone prediction sensitivity to model initialization time reveals that the 18z initialization leads to enhanced performance, particularly during high ozone exceedance days, with an improved regression slope of 0.9 compared to 0.7 for the 00z and 12z runs. The MB also improves to −0.2 ppb in the 18z run compared to −2.8 ppb and −3.9 ppb for the 00z and 12z runs, respectively. The analysis of meteorological fields reveals that the improved ozone predictions at 18z are linked to a more accurate representation of afternoon wind speed. This improvement enhances the transport of ozone, contributing to the overall improvement in ozone predictions.

Bibliographic Details

Rabab Mashayekhi; Oumarou Nikiema; Sandrine Trotechaud; Craig A. Stroud; Junhua Zhang

MDPI AG

Environmental Science

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know