edu.ucar.opensky::articles:43886 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T17:44:52.873986 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7571hfh https://doi.org/10.5065/D6PG1QDD https Related Dataset #1 NCEP/EMC 4KM Gridded Data (GRIB) Stage IV Data. Version 1.0 https://doi.org/10.6075/J09P321J https Related Dataset #2 Airborne radio occultation observations retrieved during atmospheric river reconnaissance 2023 field campaign, version 1. In Global Navigation Satellite System (GNSS) Airborne Radio Occultation (ARO) Observations from the Atmospheric River Reconnaissance Field Campaigns https://doi.org/10.5281/zenodo.15007835 https Related Software #1 Software package of modified 2D ARO bending operator based on ROPP https://doi.org/10.5281/zenodo.15008169 https Related Software #2 Software package of NCAR MPAS workflow with modifications for ARO Impact of airborne radio occultation observations on short term precipitation forecasts of an Atmospheric River 2025-07-16T00:00:00Z publication https://n2t.net/ark:/85065/d7571hfh https://doi.org/10.1029/2025GL115639 Do, P. author Haase, J. S. author Baños, Ivette Hernández author Hordyniec, P. author Cao, B. author UCAR/NCAR - Library publisher Atmospheric River Reconnaissance (AR Recon) collects targeted observations during major winter weather events associated with heavy precipitation and flooding on the US West Coast. Ten WC&#8208;130J weather reconnaissance aircraft equipped with Global Navigation Satellite System airborne radio occultation (ARO) technology provide additional data on the broader AR environment, specifically as the AR approaches the coastline. This study evaluates the impact of assimilating ARO bending angle observations using the Model for Prediction Across Scales&#8212;Atmosphere&#8212;Joint Effort for Data assimilation Integration (MPAS&#8208;JEDI). Experiments use the Local Ensemble Transform Kalman Filter and Three&#8208;Dimensional Ensemble&#8208;Variational algorithms. The control experiment assimilates only global conventional data, while the other experiments incorporate additional ARO observations. The results show that ARO assimilation corrects moisture, temperature, and wind fields, and reduces the error in the integrated vapor transport forecast at landfall. The changes mitigate overestimated precipitation in mountainous regions of Washington and Idaho. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span> None eng geoscientificInformation