A Comparison Between Station Observations and Reanalysis Data in the Identification of Extreme Temperature Events

While many studies comparing atmospheric reanalysis and surface observations have focused on the similarity of mean fields, trends, or frequencies of extreme events, very few have assessed how similar surface observations and reanalysis data sets are in terms of their specific identification of extreme temperature event days. Here, we assess the similarity between surface observations and three reanalysis products: ERA5, ERA5-LAND, and NARR, in terms of the days on which they identify extreme heat and cold events for the period 1979-2016 at 230 locations in the United States and Canada. Cold events have a greater match than heat events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in midlatitude, continental locations, with poorer performance in coastal areas, and the Arctic. Plain Language Summary Atmospheric reanalysis products are simulations of the atmosphere that create gridded historical data sets. While many studies have looked at how well these products match surface observations overall, very few have examined how similar they are in identifying extreme weather event days. Here, we explore this similarity using three reanalysis products: ERA5, ERA5-LAND, and NARR, in terms of the days on which they identify extreme temperature events. We do this for 231 locations in the United States and Canada from 1979-2016, for both extreme heat and cold. Cold events have a greater match than heat events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in midlatitude, continental locations, with poorer performance in coastal areas, and the Arctic.