COPC Environmental Modeling CONOPS Spring COPC 2007

1. COPC Environmental Modeling CONOPSSpring COPC 2007 Mr Mike Clancy, Mr Mike Howland, Dr John Harding, CDR Mark Moran

2. Table of Contents • Purpose:To establish and document COPC partners’ roles, procedures, and methods employed in mutual collaboration for execution, enhancement, data sharing from, and backup of NOAA and DoD operational environmental models. • Executive Summary: • Introduction: • Background • Guiding Principles • Information Assurance • Challenges • Advantages of Collaboration • Relationship of this CONOPS to NUOPC

3. Table of Contents • OPC Modeling Responsibilities and Capabilities • Modeling Responsibilities • Current Capability Overview • Collaborative Modeling Capability • Modeling missions/capabilities targeted for collaborationor leveraged • Ensemble Modeling • Operations • Global Modeling • Limited Area Modeling • Space Modeling • Operations Coordination Process • Catastrophic Backup

4. Table of Contents • Infrastructure • R&D Transition • Performance Metrics • Business Practices

5. Executive Summary • Atmospheric Modeling • Keep near term focus on NAEFS and JEFS projects • Need proof of concept/methods to support ensemble production • Global ensemble first production target; path to NUOPC • Limited Area Modeling • Clarify center responsibilities; minimize duplication • Establish DoD Continuity of Operations (COOP) Agreement • Establish migration path for shared ensemble production • Formalize DoD/NOAA production dependency agreements • Ocean Modeling • Share Navy Global Ocean Fields as boundary conditions and backup for NCEP regional circulation models • Continue public sharing of Navy global ocean fields via NOAA NESDIS National Coastal Data Development Center (NCDDC) • Explore use of ensemble methods for ocean wave modeling

6. Executive Summary (Continued) • Other Modeling • NAVO continues Arctic sea ice forecast data delivery to National Ice Center • AFWA continues cloud and snow analysis data delivery to Navy/NOAA • Space Modeling • Focus on transition to physics based space models • Improve NCEP/AFWA collaboration on space environment sensing and shared assimilation • Formalize national space environment COOP capability • R&D • Seek common modeling infrastructure to ease R&D reuse • Establish R&D coordination process to reduce duplication of effort • Near term DoD collaboration on aerosols/dust transport • Establish virtual DoD Development Test Center (DTC) and define relationship to NCEP DTC • Continue Navy/NCEP ocean collaboration on HYCOM and ESMF

7. Executive Summary (Continued) • Data Exchange and Communications • Standardize data exchange parameters, formats, & grids • Determine best method for ensemble data exchange • Scope communication bandwidth needs/costs • Management Processes • Establish shared operational modeling metrics process and tracking/reporting practices including atmospheric parameters relevant to ocean models • Establish defined process for operational run coordination • Establish and exercise COOP process • Establish agreement on practices and shared ground rules to meet Information Assurance demands

8. Introduction

9. Guiding Principles • CONOPS must help, not hinder, each Agency’s ability to support its customer base. • The Agencies will identify and coordinate needed additions to ESMF to establish a common modeling software framework • Must support the full range of models we collectively run • Transition to full use will be long term effort • A common modeling framework will facilitate: • Coordinated and shared R&D • Operational collaboration • Managed diversity of ensemble suites • Interoperability and backup

10. Guiding Principles • Through coordinated and shared R&D, Agencies will minimize redundant research, and team up to address problems jointly agreed to as highest priority. • Through operational collaboration, each Agency will leverage the modeling capabilities of the others: • Coordination of limited-area model windows • Contribution of members to unified ensemble suites • Reliance on another Center’s modeling capabilities to meet a particular requirement

11. Guiding Principles • Through managed diversity of ensemble suites, each Agency will: • Recognize and support the growing National focus on ensemble-based prediction • Contribute members and value to multi-model ensembles • Through interoperability and backup, each Agency will: • Contribute to an enhanced capability to deliver meteorological and oceanographic prediction support to the nation • Sustain national capability even in the event of catastrophic outage at one of the four Centers

12. Collaboration Advantages • Accelerated improvement in national ability to characterize the natural environment • Acceleration of ability to provide stochastic forecasting • Reduced cost per capability for environmental modeling • Reduced duplication of effort • Reduction in both R&D transition time and cost of transition • Enhanced ability to exchange and reuse developed software • Ability to surge beyond any single center capability • Improvement in national continuity of operations • Payback by: More effective military operations, improved resource and human life protection, improved commerce, enhanced national aviation and surface transportation system effectiveness

13. Challenges • DoD Information Assurance restrictions on data/software exchange • Ongoing tightening of DoD IA constraints on network connectivity • Differing: • Customer bases and requirements • Production run schedules • Data distribution methods and architectures • Modeling infrastructures • Model verification methods and metrics • Software Configuration Management (CM) processes • Software coding standards • R&D transition and model governance processes • Financial planning, programming, budgeting and execution systems • Cultures

14. Information Assurance • Information Assurance (IA) is defined as: Measures that protect and defend information and information systems by ensuring their availability, integrity, authentication, confidentiality and non-repudiation. • IA is a priority concern to DoD and increasing concern to NOAA; the frequency and sophistication of attacks on U.S./Defense Information Systems continues to increase • IA constraints and requirements differ markedly between DoD and NOAA, and even between Navy and Air Force • IA issues will present a significant challenge to the stand-up and sustainment of this CONOPS as well as for NUOPC follow-on collaborative activities

15. Information Assurance • Areas of particular concern are: • Network security • Use of software developed/modified by uncleared foreign nationals in mission-critical systems • Release of operational NWP software to a wide community, including potential adversary nations • The biggest issue initially will be Network Security: • Each Center must accommodate the Network Security requirements of the others sufficiently to allow data exchange • For example, this may include use of: • Public Key Infrastructure (PKI) technology • Mandated closure of certain network communications ports, • Exclusion of certain common communications protocols

16. Key Assumptions • Agreements generated by this CONOPS for specific inter-agency and inter-service capability dependencies and partnerships will be documented by MOA and fully coordinated with DOC, USAF, USN, Joint Staff, and OSD • COPC centers will find mutually acceptable common ground for IA practices necessary for collaboration

17. CONOPS Relationship to NUOPC • COPC CONOPS focus is near term (1-3 years) • Emphasis on near term operational effectiveness gains • COPC CONOPS broader - not limited to Global NWP focus • Near term COPC efforts closely coordinated with NUOPC • Longer term efforts deferred to NUOPC and beyond • NUOPC effort will eventually broaden beyond Global NWP • Provides living CONOPS • Flexible - reshaped as necessary • Transition path to NUOPC • Provides CONOPS framework to expand NUOPC scope to broad range of national environmental modeling

18. OPC Modeling Responsibilities and Capabilities Note: Content of this section moved to backup slides for 2 May briefing to COPC

19. Collaborative Modeling Capability

20. Modeling Missions/Capabilities Targeted for Collaboration or Leveraged • Global NWP Models • NCEP provides to AFWA for limited-area model support (pre national ensemble production) • FNMOC provides to NCEP for unified ensemble (production of a national ensemble global NWP capability) • AFWA, FNMOC, & NAVO use NCEP unified global ensemble • FNMOC provides to NCEP and AFWA as backup • NCEP provides to FNMOC as backup • Other Global Models • FNMOC and NCEP use AFWA Snow Depth Model • FNMOC uses AFWA Cloud Analysis • AFWA uses FNMOC/NAVO SST

21. Modeling Missions/Capabilities Targeted for Collaboration or Leveraged • Global Ocean Circulation Modeling • NAVO/FNMOC provides to NCEP for regional ocean model boundary conditions • NAVO/FNMOC provides to NCEP as backup for regional models (NOTE: NCEP planning to implement global model by FY10) • NAVO/FNMOC share global ocean fields via NOAA NESDIS National Coastal Data Development Center • Global Ocean Wave Prediction • NCEP provides to FNMOC for unified ensemble • FNMOC unified ensemble provided to NCEP and NAVO • FNMOC provides to NAVO for limited-area model support • FNMOC provides to NCEP as backup • NCEP provides to FNMOC as backup

22. Modeling Missions/Capabilities Targeted for Collaboration or Leveraged • Limited Area NWP Models • DoD reliance on NCEP for CONUS and N. A. theater • Production of 3-4 DoD theater-scale mesoscale ensembles • AFWA and FNMOC provide all classified limited area NWP • Agreed DoD lead responsibilities for designated nested theater hi-res NWP; full coordination for non-designated • Tropical Storm mesoscale: Shared NCEP/Navy mission • NCEP reliance on DoD for OCONUS windows(within resource availability; cannot significantly conflict with DoD operational mission) • FNMOC provides to AFWA at TS/SCI classification level • FNMOC provides to NAVO to drive limited-area ocean models

23. AFWA WRF5km in Blue FNMOC COAMPS6km in Red 5km 5km 6km Example Limited Area Modeling DoD Collaboration Shared contribution to theater ensemble; deconflicted AF/Navy inner nests

24. Modeling Missions/Capabilities Targeted for Collaboration or Leveraged • Space Models • AFWA/NCEP collaborate on space sensing & assimilation • NCEP uses AFWA GAIM and HAF • Other Models • Land Information System (LIS) • AFWA/NCEP/NASA collaborative project • Couples to Global or Mesoscale NWP • Global and Limited Area Aerosol and Dust Transport Applications/Models • Convergence to single embedded NWP capability/method • Shared algorithms and assimilation methods • Merge/reuse or eliminate duplication of FNMOC aerosol capability with AFWA Dust Transport Application • Seek common global/limited-area models/infrastructure

25. Migration to Ensemble Modeling

26. Ensemble Modeling • Two near term projects are critical pathfinders for OPC operational migration to global and limited area NWP ensembles • DoD led Joint Ensemble Forecast System (JEFS) • NWS/NCEP led North American Ensemble Forecast System (NAEFS) • JEFS/NAEFS are center of gravity for near-term NWP collaboration • Lessons learned on methods, calibration, post processed products, and data exchange are critical to shape execution detail for this CONOPS and follow-on NUOPC efforts • Examples of key issues we must address via JEFS/NAEFS: • Common methods for calibration and post processing • What ensemble members/roll-up results are basis for data exchange? • How much value is added for cost to run ensembles for hi-res nests? • Can downscaling at higher resolution nests be more cost effective? • What are minimum shared ensemble end-result products?

27. DoD Ensemble Modeling Pathfinder - JEFS GOAL: Prove the value, utility, and operational feasibility of EF to DoD operations. FOCUS: How to best exploit EF output within forecasting and decision processes. Joint Global Ensemble (JGE) 58/40 members, 1 1, 7 day, 2 cycle/day  FNMOC Medium Range Ensemble 18 NOGAPS runs (T119, 1 cycle/day)  NCEP Medium Range Ensemble 20 GFS runs (T126, 4 cycles/day) • Joint Mesoscale Ensemble (JME) • 20 members, 15/5km, 60 hr, 2 cycles/day • JGE supports init./lat. boundary conditions • Ensemble Transform Kalman Filter I.C.s • Multimodel (WRF-ARW, COAMPS) • Varied model physics configurations • Perturbed surface boundary conditions 5km × 58 × 20  Products: Tailored to operational weather sensitivities of the warfighter Products: Tailored to support the warfighter planning processes

28. North American Ensemble Forecast System(NAEFS) • Combines global ensemble forecasts from Canada & USA • Now:CAN 40/day out to 16 days, US – 56/day out to 16 days • ’07 – CAN 40/day out to 16 days, US – 80/day out to 16 days • Generates products for • Intermediate users: NCEP, WFOs, academia, media, private sector • Specialized users: hydrologic applications • End users: public forecasts for US, Canada and Mexico • 7 Domains (Global, NH, NA, CONUS, SA, Caribbean, Africa) • Future activities • Adding products (probabilistic in nature) • Unified evaluation/verification procedures • Incorporating ensemble data from other centers (e.g., FNMOC) • Preliminary evaluation by Dec 07 • Operational implementation by Dec 08 (subject to improved performance)

29. Operations Note: Content of this section moved to backup slides for 2 May briefing to COPC

30. Model Performance Metrics

31. Model Performance Metrics • Model metrics shall be tracked to ensure collaborative/leveraged modeling and R&D insertion meets key agency performance needs • Should be based on shared uniform measures of model quality • Design model skill metrics based upon user missions, e.g., AFWA’s Generalized Operational (GO) index was based upon AF and Army mission need parameters. Weighting Scheme

32. Model Performance Metrics • Candidate general categories for indexes • Military Operations • Fixed wing aviation • Rotary wing aviation • Fleet operations • Ground operations • Littoral operations • Resource Protection • Commerce • Commercial aviation • Commercial shipping • Public Safety • Ground transportation • Agriculture

33. Model Performance Metrics • Comparisons require common post-processing algorithms for derived parameters to avoid biasing • Need to isolate performance of base model output from performance of post processing algorithms • Similar approach could be used to assess and identify the “best” post-processor algorithms • To the extent possible, collaborative decisions about which model(s) will be used to support categories of user mission will be based on these objective measures of skill

34. Infrastructure

35. Information Assurance • The Agencies shall establish a Joint Information Assurance Team, with representation from each Center, to: • Share information on IA requirements and constraints • Seek mutually acceptable IA policies and technical solutions that will allow continued exchange of data and software between the Centers • The Centers shall implement the IA policies and technical solutions identified and agreed to by the Joint IA Team.

36. Modeling Framework • The Agencies shall adopt and build upon the Earth Systems Modeling Framework (ESMF) as the common framework for all model implementations at the Centers • The Agencies shall form a team to identify required enhancements to ESMF needed to support and easily reuse model components (assimilation schemes, physics packages, post processing, etc.) • The Agency team shall come to consensus agreement on how ESMF (with enhancements) will be applied at the Centers: • Superstructure • Infrastructure • Level to which ESMF will be applied in the model codes

37. Modeling Framework(Cont’) • The Agencies shall actively engage the ESMF development community to ensure that: • Necessary enhancements to ESMF are developed • Operational requirements and priorities are met • Information Assurance concerns are addressed • The Centers shall phase in the use of ESMF with new model implementations and upgrades

38. Software • The Agencies shall form a Joint Software Standards Team, with representation from each of the Centers, to: • Share information on software coding and documentation • Seek a mutually acceptable set of software coding and documentation standards that will facilitate sharing of software among the Centers • The Centers and the supporting R&D community shall phase in the software coding and documentation standards identified by the Joint Software Standards Team with new model implementations and upgrades

39. Hardware • Hardware should support open computing standards with minimum degree of vendor extensions to support HPC requirements • The Agencies will coordinate major hardware buys and consider opportunities for shared purchase when feasible as means for cost reduction • Each center shall keep other OPC partners informed of planned significant changes in hardware architecture

40. R&D Transition Note: Content of this section moved to backup slides for 2 May briefing to COPC

41. Summary

42. Summary • Atmospheric Modeling • Keep near term focus on NAEFS and JEFS projects • Clarify and define center roles for national capability and backup • Global ensemble first production target; path to NUOPC • Establish DoD/NOAA Continuity of Operations (COOP) agreements • Establish migration path for shared ensemble production • Ocean Modeling • Share Navy Global Ocean Fields as boundary conditions and backup for NCEP regional circulation models • Continue sharing of Navy global ocean fields via NESDIS NCDDC • Explore use of ensemble methods for ocean wave modeling • Space Modeling • Focus on transition to physics based space models • Improve NCEP/AFWA collaboration on space environment sensing and shared assimilation and mutual COOP

43. Summary • Other Modeling • NAVO continues Arctic sea ice forecast data delivery to National Ice Center • AFWA continues cloud and snow analysis data delivery to Navy/NOAA • Establish agreed mutual approach to address IA concerns • Establish team(s) to: • Define common modeling software standards • Define and input changes to ESMF as basis for shared common modeling infrastructure • Define methods, formats, grids, parameters, for data exchange • Scope communication bandwidth needs/costs • Formalize DoD/NOAA production dependency and COOP/backup agreements

44. Discussion

45. Backup Slides

46. OPC Modeling Responsibilities and Capabilities

47. Modeling Responsibilities(FNMOC) • Global NWP with focus on: • Marine environment and marine boundary layer • Surface winds, wind stresses and heat fluxes to drive ocean and ice models at NAVO • Global Tropical Cyclone (TC) track prediction • Ensemble products • Global depiction of aerosols • Extension into the stratosphere to support classified applications • TC modeling • High-resolution moving nest • Global application • Multiple simultaneous storms

48. Modeling Responsibilities(FNMOC/NAVO) • Global ocean modeling with focus on: • Support for automated global high-winds and high-seas warnings • Support for safety of navigation ( e.g., automated global OTSR) • Support for near-shore & shallow-water wave models • Support for surf and coastal wave process models • Ensemble products • Sea Surface Temperature (SST) to support global NWP • 3D ocean sound speed structure and currents in support of Anti-Submarine Warfare (ASW), Mine Warfare (MIW) and Naval Special Warfare (NSW) • Arctic Ice prediction in support of safety of navigation and ASW

49. Modeling Responsibilities(FNMOC/NAVO) • Limited-area meteorological and oceanographic modeling with focus on: • Integrated depiction of the sea-air-land environment in the coastal zone • Prediction of ocean sound speed structure and currents in support of ASW, MIW & NSW • Prediction of Electro-Magnetic/Electro-Optical (EM/EO) refraction and ducting conditions • Prediction of the transport and dispersion of hazardous materials • Prediction of sea-level and storm surge • Assimilation of classified data • Classified limited-area model domains • On-demand and rapid application/re-location

50. Modeling Responsibilities(AFWA) • Global NWP • Leverage external global NWP modeling (NCEP and FNMOC) • Imported global NWP feeds limited area and specialized models • Centralized global NWP post processing applications and dissemination for AF and Army Ops • Lead DoD JEFS as proof of concept project for ensemble NWP • Determine methods and product line for migration from deterministic to ensemble based stochastic NWP forecasts and decision aid applications • Pathfinder for AFWA/FNMOC production ensemble NWP • Global Cloud Modeling • Hourly worldwide cloud analysis • Short and medium range cloud forecast models