Dr. Frank Herr

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ONR's Arctic and Global Prediction Program
Dr. Frank Herr Ocean Battlespace Sensing
ST Department Head Dr. Scott L. Harper Program
Officer Team Lead, 322AGP Dr. Martin O.
Jeffries Program Officer Arctic Science Advisor
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The Changing Arctic

• Naval Needs and Key Questions
• Task Force Climate Change Arctic Roadmap
• Must have Arctic environmental information and
  predictions to support investment and policy
  decisions, and future operations
• NORTHCOM
• Must improve ability to observe and predict the
  Arctic environment
• N2N6E Capabilities Based Assessment Capability
  Gap in Provision of Environmental Information
• Insufficient ability to provide oceanographic
  information, ice reports, accurate navigation
  charts, meteorological analysis and forecasts

• How little sea ice will there be, and when will
  the key changes occur?
• Need better prediction capability underpinned by
  basic research
• How is the Arctic region as a whole going to be
  different?
• Need research into how the entire Arctic
  environmental system functions
• What does the Navy need to know to operate in the
  Arctic?
• Need sustained observations and improved
  predictions of the state of the Arctic
• How will the changing Arctic affect the rest of
  the earth, and vice-versa?
• Need an Arctic environmental system model
  integrated within global prediction models

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Emerging Dynamics of the Marginal Ice Zone DRI

• Department Research Initiative (DRI) FY12-FY16
• Main field experiment in spring-summer-early
  autumn 2014 in the Beaufort Sea.
• Components
• Deployment of acoustic navigation and
  communication array, under-ice gliders and
  floats, ice-tethered profilers, ice mass balance
  buoys, wave buoys on ice and in open water.
• Development of the Marginal Ice Zone Modeling and
  Assimilation System (MIZMAS) and Arctic-Cap
  Nowcast/Forecast System for improved sea ice
  prediction.
• Objectives
• Collect and analyze a benchmark data set that
  resolves the key processes controlling the
  evolution of the new MIZ.
• Identify key interactions and feedbacks in the
  ice-ocean-atmosphere system and investigate how
  these might change with the predicted increased
  seasonality of the Arctic sea ice cover.
• Evaluate the ability of existing models to
  predict the seasonal evolution of the MIZ.
  Improve parameterization of key processes with
  the goal of enhancing seasonal forecast
  capability.

August 1990
August 2012
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Sea State and Boundary Layer Physics of the
Emerging Arctic Ocean DRI

• Department Research Initiative (DRI) FY13-FY17
• Main field experiment in summer-early autumn 2015
  in the Beaufort and Chukchi seas.
• Proposals are currently under review
• Anticipate deployment of moorings with
  upward-looking acoustic wave profilers, drifting
  wave and meteorological buoys in open water and
  in the marginal ice zone, synthetic aperture
  radar (SAR) remote sensing of wind and wave
  spectra, and efforts to improve wave models for
  both open ocean and sea ice cover in the Arctic.
• Objectives
• Understand the physics of heat and mass transfer
  from the ocean to the atmosphere, and the
  seasonal variability of fluxes during summer ice
  retreat and autumn ice advance.
• Develop a new sea state climatology, identify
  factors affecting the spatial and temporal
  variability of sea state, and improve forecasting
  of waves on the open ocean and in the marginal
  ice zone in the Arctic.
• Develop a climatology of and improve theory of
  wave attenuation and scattering in the sea ice
  cover.
• Use wave scattering theory directly in integrated
  Arctic system models, and indirectly to define an
  ice rheology for use in Arctic system models.

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High-Resolution Arctic Prediction Assimilating
SAR Data
Merging of data from multiple platforms will
provide daily coverage of the Arctic at high
spatial resolution.

• Develop an improved modeling capability for the
  Arctic for both basic understanding and
  prediction
• Coupling ocean models with ice, wave, and
  atmospheric models in the Arctic
• Data assimilation techniques for the Arctic Ocean
• Building tools to help optimize the Arctic
  observing system
• Role of remote sensing and in situ data in
  constraining Arctic models
• Improved models and methods for prediction of sea
  ice (nowcast to 6 months)

• Algorithm development for data assimilation into
  predictive models
• Ice concentration and dynamics
• Ice ridges
• Ice types
• Open water waves
• Data collections are beginning now, with a focus
  on the Bering Strait, Beaufort and Chukchi Sea
  areas in preparation to support the DRI field
  efforts in 2014 and 2015.

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