Representation of Dropsonde‐Observed Atmospheric River Conditions in Reanalyses
Alison Cobb, Luca Delle Monache, Forest Cannon, F. Martin Ralph
Abstract
Abstract Atmospheric rivers (ARs) are the primary mechanism for mid‐latitude water vapor transport, and are identified by a key variable, integrated water vapor transport (IVT). The ability of atmospheric reanalyses in providing a ground‐truth dataset for the IVT field is assessed by comparing ERA5, MERRA‐2, and JRA‐55 data against a large sample (>1,700) of dropsonde profiles deployed in and around ARs. Bias and error increase with IVT magnitude, although asymmetrically around the AR core. A partitioning of the source of error reveals that humidity contributes more to the difference in IVT above 800 hPa, while wind is the dominant source in the lowest levels (to 950 hPa). This quantification of reanalysis error and bias identifies ERA5 as the dataset with the lowest IVT errors and demonstrates remaining challenges in representing the observed state in ARs.