Uncertainty of Atmospheric Winds in the Reanalysis Datasets

Atmospheric winds are essential to transport heat, moisture, momentum, and chemical species and enable the interactions between components of Earth’s climate system. However, direct observations of three-dimensional distributions of atmospheric winds are scarce. Existing studies rely heavily on the wind fields from reanalysis datasets. In this study, we analyze the uncertainty of atmospheric winds in three reanalysis (ERA5, MERRA2 and CFSv2) datasets. We show that the mean wind vector differences (WVDs) between the reanalysis datasets are about 3–6 m s-1 in the troposphere. The mean absolute wind direction differences (WDDs) can be more than 50°. Large WVDs greater than 5 m s-1 are found for 30–50% of the time when the observed precipitation rate is larger than 0.1 mm hr-1 over Eastern Pacific, Indian Ocean, Atlantic and some mountain areas. The uncertainty of wind shear is correlated with the uncertainty of winds. The uncertainty of vorticity and divergence is comparable to their mean values. Compared to the dropsonde wind measurements from the Convective Processes Experiment-Aerosols & Winds (CPEX-AW) field campaign, ERA5 is the closest to the observations while MERRA2 has the largest error among the three reanalysis datasets.