Is ERA5 Fit for Purpose? A Global Multi-Variable Evaluation of Reanalysis Strengths and Weaknesses

Reanalysis products, which blend weather model output with observations are commonly used as substitutes for observations to assess numerical weather prediction model forecast skill, the accuracy of climate model historical realizations, and AI training. However, the quality of reanalysis output is not uniform across all variables, times of day, seasons, or geographic settings. This study evaluates the strengths and weaknesses of ERA5 reanalysis (0.25° grid) over a multi-year period by comparing them to worldwide hourly surface observations from over 1200 stations, buoys, and radiosonde vertical profiles.

Our analysis focuses on several metrics across the diurnal cycle (7 AM and 3 PM local time) and during temperature outlier events (< 10th percentile and > 90th percentiles for the 30-year climatology). Results indicate that ERA5 provides reliable 2-meter air temperatures in most regions, but shows a frequent dry bias in dewpoint of greater than 3 ℃ more than 5% of the time for many stations in the Dry and Mediterranean climate zones. ERA5 often underestimates warm events (> 90th percentile), with the largest cold biases, less than -3 ℃ occurring more than 11% of the time in the Mediterranean climate zone. Temperature and dewpoint biases are amplified in complex terrain, and dewpoint biases tend to be larger near coastal locations. To investigate whether higher spatial resolution mitigates these issues, we also examine the performance of the ERA5-Land product  (0.1° grid). These findings emphasize the importance of evaluating the adequacy of purpose when using reanalysis for specific applications, since performance can vary significantly by variable, time of day, season, and climate zone.