Atmospheric River Reconnaissance Research and Operations Workshop

27 – 30 October, 2025

Seaside Forum, Scripps Institution of Oceanography, University of San Diego – La Jolla, California

Driving improved and actionable predictions of land-falling Atmospheric Rivers in the U.S.

From 2015 to 2025, Atmospheric River Reconnaissance (AR Recon) grew from a concept, to a field demonstration, to an operational requirement and federally sponsored mission. It has evolved from 3 storms flown over 2 weeks in 2016 to over 20 flown each water year since 2020 during the period November – March. Currently, AR Recon uses U.S. Air Force Reserve Command C-130s and the NOAA G-IV aircraft to carry out reconnaissance missions collecting high-density flight level observations and atmospheric profiles using dropsondes. The program has also partnered with the Global Drifter Program, led at Scripps Institution of Oceanography by the Lagrangian Drifter Laboratory, to deploy 369 drifting buoys with pressure sensors since 2018. AR Recon also supports innovative technologies such as Airborne Radio Occultation (ARO), and partners with private sector companies like Windborne to carefully coordinate data collection for maximum value. Flight planning and mission declaration is carried out by a diverse team of scientists and forecasters, who consider essential atmospheric structures and input from multiple objective targeting methods.

A steering committee for modeling and data assimilation consisting of a multi-agency team with members from operational centers, research institutions and universities is working together to document the impacts of the observations on analyses and forecasts, and enhance and expand their utility. Robust demonstrations of success to date, along with other factors, have led to a geographic expansion of operations beginning in Water Year 2024 (e.g., US Air Force Reserve Command C-130 flights out of Guam over a two-week period in 2024, and out of Japan over a similar period in 2025). In 2025, we also coordinated with universities throughout the United States to release weather balloons concurrent with AR Recon flights.

Workshop Goals:

Document impacts of the data on forecast outcomes.

Review and refine operational sampling, data collection and dissemination strategies.

Guide future research, including coordinated data impact studies, advances in fundamental science, and exploration of campaign expansion, among other topics.

Plan for implementation of the GARRP demonstration flights.

Agenda

The workshop will cover the following specific topics, under the Research And Operations Partnership (RAOP) framework, with oral sessions, poster sessions, and interactive panel discussions:

• Diagnostic, verification, and validation methods including downstream impacts and the use of the AR scale
• Data assimilation and observation impact studies, including new methods, and coordinated case studies
• Identify leading sources of forecast errors, including the role of mesoscale frontal waves, processes connecting the tropics to midlatitudes, including tropical moisture exports, and systematic model errors
• Physical process studies enabled by AR Recon in support of water applications
• Specific evaluation of flights conducted out of the Northwest Pacific
• Sensitivity, sampling strategies, and targeting methods for essential atmospheric structures
• Expansion of AR Recon to the Central and Western Pacific, and events originating in the Gulf of Mexico and the North Atlantic
• Collaboration and coordination with the other planned campaigns, including the North Atlantic Waveguide, Dry Intrusion, and Downstream Impact Campaign (NAWDIC), the North American Upstream Feature-Resolving and Tropopause Uncertainty Reconnaissance Experiment (NURTURE), the Global Precipitation Experiment (GPEX) and the Office of Naval Research Study of Air-Sea Fluxes and Atmospheric River Intensity (SAFARI)
• New observations and observing systems
• Tying observing and modeling strategies directly to economic and other impacts
• Discussion of a vision for AR Recon 2027 and beyond

Additionally, the 2025 AR Recon Workshop will include sessions for several working groups within the RAOP that will discuss melding recent research advancements with operational sampling strategies to inform future research, targeting strategies, and operational priorities. These include ongoing efforts to operationalize Airborne Radio Occultation data and efforts to work with NOAA NCEP’s WPC, CARCAH, and others on targeted flight tracks for impactful winter storms affecting the Eastern U.S.

This workshop is invitation only. If you would like to present a poster, submit an abstract, or participate in another capacity and did not receive an invitation, or if you have any other questions related to the workshop, please contact Kyla Van Maanen.

Hotels: Click here for a list of CW3E recommended hotels.

Arriving at Scripps Seaside Forum:

There is no designated venue parking available at Scripps Seaside Forum. We strongly encourage attendees to carpool, use rideshare services, or walk if possible. Free side-street parking may be available on a first-come, first-served basis, but it is not guaranteed. Please note that illegal parking is strictly enforced and subject to ticketing. If you have extenuating circumstances and require additional assistance, please contact us.

Atmospheric River Reconnaissance Modeling and Data Assimilation Steering Committee:

F. Martin Ralph (Workshop and Steering Committee Co-Chair), Center for Western Weather and Water Extremes at UC San Diego/Scripps Institution of Oceanography (CW3E)

Vijay Tallapragada (Workshop and Steering Committee Co-Chair), NOAA/NWS/NCEP/Environmental Modeling Center (EMC)

Chris Davis, National Center for Atmospheric Research (NCAR)

Luca Delle Monache, Center for Western Weather and Water Extremes, UC San Diego (CW3E)

Jim Doyle, Naval Research Laboratory (NRL)

Florian Pappenberger, European Centre for Medium-Range Weather Forecasts (ECMWF)

Carolyn Reynolds, Naval Research Laboratory (NRL)

Aneesh Subramanian, University of Colorado Boulder