Contribution of radio occultation data to atmospheric river landfall forecasts in the eastern North Pacific

Abstract

AbstractThis study assesses the impact of Global Navigation Satellite System radio occultation (RO) data assimilation (DA) on low‐predictability atmospheric river (AR) landfall forecasts. The period of study is October–March 2020–2022, focusing on AR events over the eastern North Pacific. Eighteen AR landfall events with large forecast errors in the Global Forecast System of the National Centers for Environmental Prediction are selected. Two numerical experiments are conducted for each AR event. One assimilates RO data using a non‐local excess phase operator to improve its initial condition (labeled as EPH forecast), while the other does not (reference run; labeled as REF forecast). Relative to REF, the root‐mean‐squared errors of integrated water vapor transport (IVT), moisture, and wind are reduced by EPH in the main AR activity areas throughout the whole forecast period, except for zonal winds. EPH significantly reduces the underestimation of strong IVT occurrence rate by 2.6%–4.8% and the underestimation of IVT intensity by 15.7–35.0 kg·m−1·s−1, compared to REF. EPH also substantially improves the precipitable water distribution and AR‐related precipitation over the ocean. Despite these basin‐wide improvements, AR coverage, location, and precipitation over land are not significantly affected by RO DA. Specifically, the main contribution of RO DA to the root‐mean‐squared error reduction of AR forecast is the wind improvement prior to AR landfall and the mid‐level moisture improvement after AR landfall. In summary, this study highlights the potential positive contributions of RO DA to AR forecasts, and explores the mechanisms and spatial and temporal characteristics of the improvements.