Aircraft-based observations are some of the most important meteorological sources within the modern global observing system. Flight reductions related to the Covid-19 pandemic have raised questions about whether the loss of meteorological observations from aircraft-mounted sensors could affect the accuracy of operational forecast models.
A new study, published in the American Meteorological Society’s Journal of Applied Meteorology and Climatology, has sought to quantify the impact of these missing observations on the forecasts produced by US-based NOAA’s most advanced experimental short-term weather model, Rapid Refresh (RAP). The study was led by CIRES (Cooperative Institute for Research In Environmental Sciences) and the NOAA Global Systems Laboratory (GSL).
According to the study, a controlled experiment used weather observations from surface stations, satellites, radar, wind profilers, and commercial aircraft from discrete 10-day periods in 2018 and 2019. It found reduced skill in several outputs from the most recent version of the RAP – RAPv5 – when the model was denied observations that would be expected from normal air travel patterns.
It is notable that NOAA Research continuously seeks to improve weather forecasts by developing new and upgraded models that are rigorously tested to evaluate their performance. Once evaluation criteria are met, upgrades are transitioned to the National Weather Service for use in generating official forecast products. This new version of the RAP is due to transition to the NWS operational suite of models before the end of the year.
