Toward a Better Regional Ozone Forecast Over CONUS Using Rapid Data Assimilation of Clouds and Meteorology in WRF-Chem

Details

• Journal Title:
  Journal of Geophysical Research: Atmospheres
• Personal Author:
  Ryu, Young‐Hee ; Hodzic, Alma ; Descombes, Gael ; Hu, Ming ; Barré, Jérôme
• NOAA Program & Office:
  CIRES (Cooperative Institute for Research in Environmental Sciences) ; OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; GSL (Global Systems Laboratory)
• Description:
  Accuracy of cloud predictions in numerical weather models can considerably impact ozone (O-3) forecast skill. This study assesses the benefits in surface O-3 predictions of using the Rapid Refresh (RAP) forecasting system that assimilates clouds as well as conventional meteorological variables at hourly time scales. We evaluate and compare the WRF-Chem simulations driven by RAP and the Global Forecast System (GFS) forecasts over the Contiguous United States (CONUS) for 2016 summer. The day 1 forecasts of surface O-3 and temperature driven by RAP are in better agreements with observations. Reductions of 5 ppb in O-3 mean bias error and 2.4 ppb in O-3 root-mean-square-error are obtained on average over CONUS with RAP compared to those with GFS. The WRF-Chem simulation driven by GFS shows a higher probability of capturing O-3 exceedances but exhibits more frequent false alarms, resulting from its tendency to overpredict O-3. The O-3 concentrations are found to respond mainly to the changes in boundary layer height that directly affects the mixing of O-3 and its precursors. The RAP data assimilation shows improvements in the cloud forecast skill during the initial forecast hours, which reduces O-3 forecast errors at the initial forecast hours especially under cloudy-sky conditions. Sensitivity simulations utilizing satellite clouds show that the WRF-Chem simulation with RAP produces too thick low-level clouds, which leads to O-3 underprediction in the boundary layer.
• Keywords:
  Modeling Precipitation
• Source:
  Journal of Geophysical Research: Atmospheres, 124, 13576-13592
• DOI:
  https://doi.org/10.1029/2019JD031232
• Document Type:
  Journal Article
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:60a0b9cee7243a13bc0508d71e0797ba5b468f240eb6faf83c23b33d4b02c07a022527b7244e4fdca0b85c41f4ca7a4e92c76a2d54b39e0145a8c071696b561e
• Download URL:
  https://repository.library.noaa.gov/view/noaa/25171/noaa_25171_DS1.pdf
• File Type:
  [PDF - 20.30 MB ]