A179-0002
Data Gaps within Atmospheric Rivers over the Northeastern Pacific
Tuesday, 15 December 2020
Poster
Minghua Zheng, Scripps Institution of Oceanography, La Jolla, CA, United States, Luca Delle Monache, Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States, Xingren Wu, EMC/NCEP/NWS/NOAA, Crofton, MD, United States, F Martin Ralph, Scripps Institution of Oceanography, UC San Diego, Center for Western Weather and Water Extremes, La Jolla, CA, United States, Bruce D Cornuelle, University of California San Diego, La Jolla, CA, United States, Vijay Tallapragada, NOAA/NCEP/EMC, College Park, MD, United States, Jennifer S Haase, UCSD, La Jolla, CA, United States, Anna Maria Wilson, Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, Matthew R Mazloff, SIO, La Jolla, CA, United States, Aneesh Subramanian, University of Colorado Boulder, Boulder, CO, United States and Forest Cannon, Scripps Institution of Oceanography - Center for Western Weather & Water Extremes, La Jolla, CA, United States
Abstract:
Conventional observations of Atmospheric Rivers (ARs) over the northeastern Pacific Ocean are sparse. Satellite radiances are affected by the presence of clouds and heavy precipitation, which impact their distribution in the lower atmosphere and in precipitating areas. The goal of this study is to document a data gap in existing observations of ARs in the northeastern Pacific, and to investigate how a targeted field campaign called AR Reconnaissance (AR Recon) can effectively fill this gap.
When reconnaissance data are excluded, there is a gap in AR regions from near the surface to middle troposphere (below 450 hPa), where most water vapor and its transport are concentrated. All-sky microwave radiances provide data within the AR object, but their quality is degraded near the AR core and its leading edge, due to the existence of thick clouds and precipitation. AR Recon samples ARs and surrounding areas to improve downstream precipitation forecasts over the western United States. This study demonstrates that despite the apparently extensive swaths of modern satellite radiances, which is critical to estimate large-scale flow, the data collected during 15 AR Recon cases in 2016, 2018, and 2019 supply about 99% of humidity, 78% of temperature, and 45% of wind observations in the critical maximum water vapor transport layer from the ocean surface to 700 hPa in ARs. The high-vertical-resolution dropsonde observations in the lower atmosphere over the northeastern Pacific Ocean can significantly improve the sampling of low-level jets transporting water vapor to high-impact precipitation events in the western United States.
