Ensemble-Based Observation Targeting for Improving Ozone Prediction in Houston and the Surrounding Area Academic Article

abstract

• This study examines the effectiveness of targeted meteorological observations for improving ozone prediction in Houston and the surrounding area based on perfect-model simulation experiments. Supplementary observations are targeted for the location that has the highest impact factor (maximum Kalman gain) estimated from an ensemble and is expected to minimize ozone forecast uncertainty at the verification time. It is found that the observational impact factor field varies with time and is sensitive to ensemble resolutions and physics parameterizations. The efficiency of observation targeting is further examined through assimilating observations in areas with different impact factors using an ensemble Kalman filter. It is found that the ensemble sensitivity analysis is capable of locating supplementary observations that may reduce meteorological and ozone forecast error, but not as effectively as expected. 2011 Springer Basel AG.

authors

• Nielsen-Gammon, John

published proceedings

• PURE AND APPLIED GEOPHYSICS

author list (cited authors)

• Bei, N., Zhang, F., & Nielsen-Gammon, J. W.

citation count

• 4

complete list of authors

• Bei, Naifang||Zhang, Fuqing||Nielsen-Gammon, John W

publication date

• March 2012

publisher

• Springer Nature  Publisher

keywords

• Data Assimilation
• Observation Targeting
• Observational Impact Factor
• Ozone Prediction

Digital Object Identifier (DOI)

• 10.1007/s00024-011-0386-z

start page

• 539

end page

• 554

volume

• 169

issue

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1007%2Fs00024-011-0386-z