ONR Marine Meteorology Program DRI

Overcoming the Barrier to Extended Range Prediction over the Arctic

Details of the DRI

Overcoming the Barrier to Extended Range Prediction over the Arctic

For a variety of reasons, small but intense cyclones are very poorly predicted over the Arctic even by the most skillful NWP models. The inability to predict this forcing is a predictability barrier that must be overcome if intra- and interseasonal predictions of sea ice are to become a reality. The overarching objective of this DRI is to gain a new understanding of the basic processes governing the development and evolution of Arctic cyclones as well as their relationship to tropopause polar vortices (TPVs) and their influence on coupled air-sea-ice processes.

cyclone

The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured this natural-color mosaic image on Aug. 6, 2012. The center of the storm at that date was located in the middle of the Arctic Ocean.
Credit: NASA/Goddard/MODIS Rapid Response Team

Scientific Issues
Supported investigations focus on the understanding Arctic cyclones, their mesoscale attendant features (e.g., low-level jets, fronts, tropopause folds), polar lows, and TPVs through theory, simulations, observations and model development. Besides identifying the shortcomings of current NWP models, a goal is to identify methods to improve the skill of future NWP systems. The following are examples of some research topics that are envisioned to address the overarching scientific issues related to improving prediction of these phenomena:

  1. Can multi-scale modeling systems be used to bridge the climate/weather domain inhabited by Arctic cyclones and TPVs and increase predictability of this seasonal driver of smaller scale forcing events?
  2. What factors influence the predictability of Arctic cyclones and what are the most important parameters and observations required for skillful forecasts of high-latitude cyclones and smaller-scale polar lows?
  3. How do air-sea-ice interaction processes occurring at the lower boundary respond to the influence of Arctic cyclones? How does the ocean-ice boundary morphology influence polar low genesis?
  4. What processes contribute to the intensification, properties, precipitation, and evolution of Arctic cyclones and their interactions with clouds and the boundary layer?
This DRI is expected to run for five years, from FY18 to FY22.

For more info on the DRI, visit the ONR Arctic DRI page.

DRI THINICE Planning

Spring, 2021

The ONR Arctic DRI is planning for THINICE, a field campaign in the high-latitude north Atlantic with our partners in France. The base of operation for the French SAFIRE Falcon aircraft is Svalbard, Norway. Svarbald is centrally situated near the mean marginal ice zone, and a short flight duration to the climatological location of phenomena of scientific interest (e.g., TPVs, ACs, VRILEs).

PIs: log-in for a copy of the Science Plan

DRI Virtual Summer Meeting

July 7-8, 2020

The virtual DRI meeting took place over two days and included short summary presentations of research progress and desired observational capabilites on a future field campaign from all of the DRI PIs and information about European campaign planning.

PIs and Guests can log-in here to access the agenda and slides.

DRI Meeting @ AMS Polar

May 19, 2019

The ONR Arctic DRI meeting was held on May 19 (at the CIRES Fellow Room, U. Colorado Campus. The meeting focused on a discussion of observing strategies and requirements for the field campaign portion of the DRI form the perspective of the PI's project goals.

PIs: log-in for a copy of the agenda

DRI Meeting @ AGU Fall Meeting

Dec 13, 2018

A half-day meeting was held on Thursday Dec 13 in the Arctic Community Meeting Rooms hosted by ARCUS at the Cambria Hotel Washington, D.C. Convention Center

PIs: log-in for a copy of the agenda

DRI Kick-Off Meeting Outcomes: Research Areas

May 30-31, 2018

The Arctic Cyclone DRI kick-off meeting took place in Monterey, CA on May 30-31, 2018. Over the two day meeting, the PIs presented their proposed projects and discussed future avenues of collaboration.

Four key research areas were highlighted:

  1. Mesoscale strucutre and dynamics (from the troposphere to the lower stratosphere) of TPVs, Arctic Cyclones, and Polar Lows
  2. Interaction of TPVs, Arctic Cyclones and Polar Lows with sea ice, the Arctic boundary layer and near surface phenomena and processes
  3. Synoptic-planetary and extratropical-Arctic interactions and impacts on TPCs, Arctic Cyclones, and sea-ice extend
  4. Coupled prediction, data assimilation and predictability for the Arctic

DRI Research Team

The ONR DRI research team includes scientists affliated with 12 projects. The project titles and team members can be found below:

Scientists Affiliation Project Title
Cecilia Bitz (PI) and Ed Blanchard-Wrigglesworth (Co-PI) University of Washington Advancing understanding of Arctic sea ice and weather interactions in summer and fall to improve forecasts on day to month timescales
Lance Bosart (PI) and Daniel Keyser (co-PI) University at Albany, SUNY Phenomenological and Predictability Studies of the Structure and Evolution of Arctic Cyclones, Polar Lows, and Tropopause polar vortices
David Bromwich (PI) and Zhiquan (Jake) Liu, Ian Simmonds (co-PIs) Ohio State University Characteristics and Predictability of Arctic Cyclones
Steven Businger (PI) and Paolo Antonelli (co-PI) University of Hawaii Advanced Use of Soundings from Hyperspectral IR Space-borne Observations to Improve Arctic Prediction
Steven Cavallo (PI) and Bill Skamarock (co-PI) University of Oklahoma & NCAR Tropopause polar vortices and multi-scale Arctic predictability
James Doyle (PI) and Neil Barton, Dave Ryglicki, Yi Jin, Anthony Bucholtz, and Will Komarom (co-PIs) NRL Multi-scale Simulation and Predictability of Arctic Cyclones and Their Influence on Sea Ice
Ron Ferek (PI) ONR Applied Arctic Research
Andrea Lopez Lang (PI) University at Albany, SUNY Understanding the role of the stratosphere in subseasonal–to–seasonal variability and predictability of Arctic weather systems
Ryan Torn (PI) University at Albany, SUNY Comparison of Polar and Midlatitude Cyclone Predictability using Ensemble-based Sensitivity Analysis
David Parsons (PI) and Steven Cavalllo (co-PI) University of Oklahoma Understanding and Improving Prediction of the Impacts of Rossby Wave Breaking on Tropopause Polar Vortices and Arctic Cyclones
Ola Persson (PI) and Janet Intrieri, Matthew Shupe, Amy Solomon, Gijs de Boer (co-PIs) NOAA/ESRL Arctic Cyclone Interactions with Tropopause Polar Vortices, Free-Troposphere Diabatic Forcing, and the Surface
Xuguang Wang (PI) and Aaron Johnson (co-PI) University of Oklahoma Understanding and Improving the Predictability of Arctic Meso- and Synoptic-scale Cyclones through Multi-scale Ensemble based Data Assimilation and Ensemble Forecast
Zhuo Wang (PI) and Melinda Peng, John Walsh (co-PIs) University of Illinois Cross-latitude Teleconnection via Rossby Wave Breaking and Its Impacts on Arctic Variability and Prediction

DRI PIs can find more info by logging in here.

About the DRI

This ONR Departmental Research Initiative (DRI) is to enhance the understanding of dynamics of Arctic cyclones and their relationship to the tropopause polar vortex (TPV).

The DRI is motivated by recent studies which lent support to the hypothesis that year-to-year variations in sea ice are driven to a great extent by a relatively small number of intense storms—Arctic cyclones.

ONR

News and Updates

DRI Planning for Aug 2021 THINICE

Spring

The DRI team is prepping for August THINICE campaign.

News and Updates

DRI Update Meeting Summer 2020

July 7-8, 2020

The virtual DRI meeting took place over two days and included short summary presentations of research progress and desired observational capabilites on a future field campaign from all of the DRI PIs.

Contact Info

DRI Program Officer:
Dr. Daniel Eleuterio (current) and Dr. Ronald J. Ferek (former)
Marine Meteorology and Space Program
Ocean, Atmosphere and Space Research Division, Code 322
Office of Naval Research
Email: daniel dot eleuterio at navy.mil