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The Importance of Sampling Variability in Assessments of ENSO‐PM2.5 Relationships: A Case Study for the South Central United States

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We assess seasonal mean relationships between the El Niño–Southern Oscillation (ENSO) and surface fine particulate matter (PM2.5) over the United States using observations from 1999 to 2015. Through a case… Click to show full abstract

We assess seasonal mean relationships between the El Niño–Southern Oscillation (ENSO) and surface fine particulate matter (PM2.5) over the United States using observations from 1999 to 2015. Through a case study of the springtime PM2.5 response to ENSO in the South Central United States, we demonstrate that sampling variability is large on the 17‐year time scale of the observations, leading to large uncertainty in the estimated relationships. The PM2.5 response in the South Central United States is dominated by decreases in soil dust concentrations during El Niño, which we link to changes in cloud cover and near‐surface wind speed. The observed dust response during 1999–2015 is about 25% stronger than the long‐term mean ENSO‐forced signal estimated from climate model control simulations. Given a different 17‐year period, this discrepancy could be even larger. Our findings underscore the importance of accounting for sampling uncertainty in studies of ENSO's air quality impacts.

Keywords: case study; south central; united states; sampling variability; central united

Journal Title: Geophysical Research Letters
Year Published: 2019

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