Earth System Prediction Capability (ESPC)

Transcription

1 Earth System Prediction Capability (ESPC) November 2012 Jessie Carman, ESPC DPM Earth System Prediction Capability ESPC 1

2 ESPC Overview Introduction ESPC is an interagency collaboration between DoD (Navy, Air Force), NOAA, DoE, NASA, and NSF for coordination of research to operations for an earth system analysis and extended range prediction capability. It does not replace or take precedence over Agency requirements or resource decisions but rather seeks to improve communication and synergy, especially in the area of global medium range environmental forecasting at the challenging timescales of the weather to climate interface. Thrusts Common prediction requirements and forecast model standards that enable agencies to improve leverage and collaboration. A national research agenda that will improve predictions from days to decades. Cooperative five-year demonstration projects to inform S&T and R&D efforts. Integration of atmosphere-ocean-land-ice and space predictions into a fully coupled global prediction capability. Earth System Prediction Capability ESPC 2

3 Phase 0: Ongoing Programs (0-100 days) Global Atmospheric Models in an Inter-agency Multi-Model Ensemble via the National Unified Operational Prediction Capability (NUOPC) Currently GFS, NOGAPS, GEM. Global Multi-model Ensemble is more accurate than any of the component models. Distributed Production Centers leverage multi-agency and international computer infrastructure and investments. Currently 1 deg/0-15 days going to 0.5 deg/0-30 days Next-generation Global Atmospheric Cloud Resolving Models (GCRM) Candidates NMMB, FIM/NIM, Cubed Sphere, MPAS, NUMA 10-15km initially, ultimately 4km or finer horizontal resolution Adaptive/unstructured mesh allows computational efficiency Improved prediction at weather to climate scales (5-100 days) Improved hurricane track/ intensity prediction and regional climate lat-lon a ( k, i, j ) NIM: a [ k, indx) Earth System Prediction Capability ESPC 3

4 Phase I: Sources of Extended Range Predictability: Subseasonal, Intraseasonal and Interannual (ISI) Timescales ESPC Focus Assessment of Intraseasonal to Interannual Climate Prediction and Earth System Prediction Capability Predictability, 2010, THE NATIONAL ACADEMIES PRESS 500 Fifth ESPC 4 Street, N.W. Washington, DC 20001

5 Phase I: ESPC Demonstrations Workshop Results Interim Science Steering Group (ISSG) Workshop March, 2012 The most needed and most scientifically feasible forecast timescales are in the 10-day to 1-2 year range based on our current and near term understanding and capability (ISI Timescales) Linkages identified between climate research (USGCRP, CLIVAR, WCRP, etc.), weather research (US THORPEX, WWRP, etc.) and ESPC development and transition to operations for coordination. Demonstrations Workshop Nov, 2012 Attended by Demo team leads, working group participants, Agency/lab representatives (for coordination) Organized around Demo groups: Preliminary talks, breakouts for working group discussions, reconvened/summarized Draft working plans showing Operational needs/customer driving factors, requirements Background science Mechanisms and linkages leading to predictability Ongoing efforts, present capability Data available Key issues and gaps Earth System Prediction Capability ESPC 5

6 Phase I: ESPC Demonstrations (10 days to 1-2 years) Extreme Weather Events: Predictability of Blocking Events and High Impact Weather at Lead Times of 1-6 Weeks (Stan Benjamin*, ESRL) Seasonal Tropical Cyclone Threat: Predictability of Tropical Cyclone Likelihood, Mean Track, and Intensity from Weekly to Seasonal Timescales (Melinda Peng*, NRL MRY) Arctic Sea Ice Extent and Seasonal Ice Free Dates: Predictability from Weekly to Seasonal Timescales (Phil Jones*, LANL) Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks (Gregg Jacobs*, NRL SSC) Open Ocean: Predictability of the Atlantic Meridional Overturning Circulation (AMOC) from Monthly to Decadal Timescales for Improved Weather and Climate Forecasts (Jim Richman*, NRL SSC) * Demonstration Coordinator/ Contact Earth System Prediction Capability ESPC 6

7 Extreme Weather Events: Predictability of Blocking Events and Related High Impact Weather at Lead Times of 1-6 Weeks ESPC Demonstration #1 Improved guidance for extreme weather events related to atmospheric blocking flow (flooding, drought, persistent anomalously cold/warm conditions). Objective: Apply our current understanding of the blocking process to develop and assess utility of model diagnostics to current state and forecast. Thrusts: Diagnose longer-term weather anomalies from atmospheric blocking (quasi-stationary events with duration of at least 4 days to 2+ months) Predict seasonal statistics (below/normal/above average conditions) at various lead times up to six months. Predict individual events (onset/ persistence/ cessation) Predict outcomes (floods, droughts, fires, extreme temps, snow). Challenges: Several possible causes are postulated each with unique sources of predictability and technical approach. These include MJO interaction, TCs/extratropical transition, SSW events, and early season snow cover or melting. Earth System Prediction Capability ESPC 7

8 Extreme Weather Events: Predictability of Blocking Events and Related High Impact Weather at Lead Times of 1-6 Weeks Key Research Questions: What is predictability at 1-6 wks of duration of blocking and stationary waves from existing global models? What is the minimum horizontal and vertical resolution needed for global models to capture blocking events? For predicting onset/cessation of stationary wave events, to what extent is it necessary to accurately predict MJO, stratospheric warming events? Subtropical jets (existence, persistence)? Planetary wave breaking (with anticyclonic jets)? To what extent are deficiencies in prediction of blocking dependent on model physics suite (deep convection, radiation)? July 2010 Atmospheric flow and temperature anomalies Earth System Prediction Capability ESPC 8

9 Seasonal Tropical Cyclone Threat: Predictability of Tropical Cyclone Likelihood, Mean Track, and Intensity from Weekly to Seasonal Timescales ESPC Demonstration #2 Improved pre-season guidance of tropical cyclone seasonal track and frequency statistics as well as sub-seasonal outlooks for civil and military planning. Objectives: Prediction of seasonal basin scale tropical cyclone genesis and track distributions and potential intensity. Thrusts: Initial value, short range prediction improvements for track and structure. Boundary value, longer range probabilistic forecasts of maximum likelihood genesis, track, intensity. Landfall probability with the accompanying potential intensity and precipitation to support resource management, evacuation plans, ship routing, etc. Challenges: Goswami et al (2003) Maloney and Hartmann (2000) Multi-scale convective processes and interaction between tropical cyclone and the large scale environment, and our understanding and ability to predict them vary widely from basin to basin. Earth System Prediction Capability ESPC 9

10 Final TC Considerations: Seasonal Tropical Cyclone Threat: Predictability of Tropical Cyclone Likelihood, Mean Track, and Intensity from Weekly to Seasonal Timescales MJO and ENSO exert large-scale control on TC activity. The impact is markedly different during different phases of MJO and ENSO Seasonal prediction remains a significant challenge; however, models such as HiRam show promise Genesis of actual cyclone within enhanced region remains statistical Intensity remains much less predictable than track Multi-scale convective processes and interaction between tropical cyclone and the large scale environment, and our understanding and ability to predict them vary widely from basin to basin. Earth System Prediction Capability ESPC 10

11 Arctic Sea Ice Extent and Seasonal Ice Free Dates: Predictability from Weekly to Seasonal Timescales ESPC Demonstration #3 Improved pre-season guidance of arctic sea ice changes, navigability of Arctic passages, and sub-seasonal forecasts of ice conditions for civil and military planning. Objectives: Further explore limits of predictability of sea ice extent and volume, and freeze and melt onset dates, at 3-12 month leads. Extend prediction to regional scale areas of interest (e.g. Northern and Northwest passages). Extend forecast variables to other ice and atmosphere properties (ice thickness/movement, marginal ice, snow, fog, etc.) Thrusts: Assessing adequacy of current sea ice models (that produce accurate hindcasts) for use as forecast models when conditions are changing. Predictability and suitability of different approaches at different forecast timescales as ice thins and system persistence is reduced. Challenges: Models reproduce historical records well when forced with observations (reanalysis) in a bulk sense, but the fidelity needed for Arctic shipping and other operations is poorly characterized. Predictability of thinning/single year ice and seasonal/annual conditions is uncertain. Earth System Prediction Capability ESPC 11

12 Arctic Sea Ice Extent and Seasonal Ice Free Dates: Predictability from Weekly to Seasonal Timescales New 2012 ice minimum record as of Aug 26, Image courtesy NASA/NSIDC Goal: Understand factors affecting predictability Initial state Ocn/atm forcing Internal ice processes Changing ice regimes Improve assimilation strategies Key Research Questions: Ice area shows some memory at 1-2 yr timescales through persistence of thick ice and SST/salinity anomalies How will predictability change as ice thins, persistence is eliminated? How is longer-term predictability affected by external forcing? Natural variability Anthropogenic causes Approach: Compare and evaluate several existing predictive models and methods, establish baseline for current predictive skill. Use existing coupled models/ simulations to explore model sensitivity to initial conditions and forcing, causes of persistence and predictability, 12 changes in predictability in seasonal-ice regime Earth System Prediction Capability ESPC 12

13 Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks ESPC Demonstration #4 Establish, at a range of lead times beyond the present weather prediction scales, the forecast skill for Harmful Algal Blooms (HABs) and coastal sea hypoxia. Objectives: Identify effects in global forecasts of the physical earth system that lead to conditions conducive to HABS and hypoxia. Communicate global forecasts, uncertainty, and variability to physical predictions for specific regionally affected areas (downscaling). Predict impact of globally forecasts on local area biology/chemistry. Thrusts: Relevant physical earth system observations and coupled predictions. Local physical conditions in under-observed, high resolution regions particular to areas in which HABS and hypoxia are significant concerns. Challenges: Precipitation residence times and nutrient loading changes from watershed to coastal waters is not well characterized in forecast models and difficult to efficiently represent numerically in a unified vertical coordinate system. Upwelling, driven by 3-dimensional air and ocean circulations, and modified by waves, bathymetry, and topography, also a major cause of HABs and hypoxia. Earth System Prediction Capability ESPC 13

14 Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks Fundamental concepts/research questions: Prior work indicates a complex interaction between physical and biological processes. No one factor has overall dominance; different factors drive different circumstances. Connecting physical and biological understanding requires local expertise (which factors affect which regions) Downscaling will be a critical factor in the demonstration: Characterizing episodic phenomena Physical scales from open ocean forcing through coastal through bay/harbor to runoff sources Community needs: Trend, trigger indicators for regulatory action Safe areas for facility locations Harvesting strategy Rehabilitated species release Glider Track Superimposed on Surface Chlorophyll Expression of a K. brevis Bloom: Oct R. Weisberg, U So Florida Earth System Prediction Capability ESPC 14

15 Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks NOAA operational forecast zones reflect differentiation in local biology and physics leading to local HABS NOAA s Marine Forecast Zones HAB events in US over prior decade ESPC demonstration follows this approach, which allows Natural concentration of expertise to local biological processes Natural application of focused research to local physics Natural leveraging of developed knowledge and skills Natural integration into operational environment Earth System Prediction Capability ESPC 15

16 Open Ocean: Predictability of the Atlantic Meridional Overturning Circulation (AMOC) from Monthly to Decadal Timescales for Improved Weather and Climate Forecasts ESPC Demonstration #5 Improved representation of basin scale three dimensional ocean circulation from months to years for use in coupled climate and weather models. Objectives: Assess model representation and predictability of ocean circulation from monthly to decadal timescales using RAPID and other long duration multi-level ocean observational datasets. Thrusts: Build upon the existing IPCC, ECCO, HYCOM and USGCRP/CLIVAR efforts to assess basic predictability of the net transport and sensitivity to forcing in order to identify knowledge gaps and design new studies. Conduct high resolution coupled model simulations to look at detailed structure and air-ocean feedback. Challenges: It is not clear what is predictable about the AMOC. The AMOC is thought to be an important driver for the oceanic meridional heat flux and sea surface temperature, although the link between the AMOC and climate is not clear. Recent climate model studies have shown a slowdown in the AMOC with possible impacts on European regional seasonal climate, ENSO and hurricanes in the Atlantic Ocean. Earth System Prediction Capability ESPC 16

17 Open Ocean: Predictability of the Atlantic Meridional Overturning Circulation (AMOC) from Monthly to Decadal Timescales for Improved Weather and Climate Forecasts Goals: Decadal prediction of AMOC RAPID observations Secondary prediction for other shorter or less complete observations MOVE 16N, MV Oleander (Upper Ocean only) SAMOC 30S (proposed) Determine what is predictable on 10 year time scale Mean value Variance Seasonal cycle Key Research Questions: Can we produce better predictions of climate variations and change using initial condition information in addition to radiative forcing changes? What are mechanisms underlying decadal vs. sub-decadal variations? Approach: Examine results from CMIP AMOC comparisons and sensitivity What is the strength and depth of the AMOC in current generation of coupled and uncoupled models? For the models with long runs, what is the variability and trend of the AMOC? Additional considerations: Uncertainties in the climate system response to radiative forcing changes (esp. aerosols) Sustain and enhance observing system; deal with changing observing systems Earth System Prediction Capability ESPC 17

18 ISI Prediction: Challenge and Opportunity High resolution, ensemble, and global coupled model approaches will bring a significant increase in data volume and computational cost. What forecast products are most needed and how do we characterize the return on this investment? ESPC demonstrations seek to exploit potential sources of predictability in the coupled system that exceed the limit in predictability of deterministic NWP approaches. Forecast skill from these ensemble-based products will vary depending on the presence of low-order modes in the initial conditions. What do you see as the biggest utility of long range products with quantifiable but variable confidence levels? Are there better ways of establishing prediction credibility? Are there better ways of communicating ensemble-based products and data? Example NMME seasonal product. Monthly predictability of the NAO based on strong/weak MJO in Initial Conditions. Earth System Prediction Capability ESPC 18

19 Discussion Earth System Prediction Capability ESPC 19

20 Seek Sources of Predictability through: Approach Improved Model Physics Coupled global modeling Improved resolution & parameterization Improve Initial Value Problem through Joint observational retrievals New hybrid DA approaches Increase Forecast Information through Stochastic prediction and post-model processing National Multi-model ensembles Seamless prediction Increase System Resolution affordably through Efficient Computational Architectures Efficient Numerics/Discretization Earth System Prediction Capability ESPC 20

21 Phase I: An Earth-System Prediction Initiative An Earth-System Prediction Initiative for the Twenty-First Century (Shapiro et al.) Addressing the Complexity of the Earth System (Nobre et al.) Toward a New Generation of World Climate Research and Computing Facilities (Shukla et al.) Collaboration of the Weather and Climate Communities to Advance Subseasonal-to-Seasonal Prediction (Brunet et al.) Earth System Prediction Capability ESPC 21

22 Global Coupled Models Global air-sea coupled models were first implemented for climate applications but are increasingly being used at subseasonal to ISI timescales. Benefit is seen especially in the tropics in both atmospheric and oceanic verification with largely comparable skill in extra-tropics; some benefit seen at higher latitudes from coupling in the Southern Hemisphere. At week two and beyond, coupling produces skill improvements comparable to doubling resolution in some research cases. Crown copyright Met Office Earth System Prediction Capability ESPC 22

23 Charter Goals (2010) establish and maintain a multi-agency initiative that provides leadership and coordination to meet broad, but specific, agency mission requirements and interests for an earth system analysis and prediction/projection framework to support global forecasts from hours to decades at appropriate horizontal and vertical resolutions. 1. A national approach to an earth system numerical prediction capability providing advanced data assimilation, improved numerical model physics and increased computational efficiencies; 2. A common set of requirements and standards that enable agencies to meet their own mission requirements while providing improved leverage and collaboration where these missions can be mutually supportive; 3. A mechanism to develop a national research agenda that will improve earth system projections and predictions from days to decades; and 4. A cooperative set of demonstrations to inform future research and development efforts encompassing Federal, private and academic organizations. Earth System Prediction Capability ESPC 23

24 Charter Additions(2012) a Science Steering Group will be established composed of subject matter experts representing the Department of Commerce (NOAA), the Department of Defense (Navy and Air Force), Department of Energy, the National Aeronautics and Space Administration and the National Science Foundation as recommended by each Agency s members. The Program Manager will initially be a Federal employee hired and employed by the US Navy or NOAA. The position rotates every three years with the Deputy Program Manager position. The ESPC Program Office is located within NOAA in Silver Spring, MD and Program Office office space, support staff, internet/ IT services and other administrative functions will be provided by NOAA. Earth System Prediction Capability ESPC 24

25 ESG Membership Dr. Bob Detrick Ms. Laura Furgione RDML Brian Brown RADM Jon White Dr. Frank Herr Dr. Fred Lewis Dr. Jack Kaye Dr. Gary Geernaert Assistant Administrator, NOAA Office of Oceanic and Atmospheric Research (OAR) Assistant Administrator, NOAA Office of Weather Services (NWS) (Acting) Commander, Naval Meteorology and Oceanography Command Oceanographer/Navigator of the Navy Head, Ocean Battlespace Sensing Dept, ONR Air Force Deputy Director of Weather Assoc. Director, Earth Science Research, NASA Director, Climate and Environmental Science Division, DOE Dr. Marge Cavanaugh Assistant Director for Geosciences, NSF (Acting) Earth System Prediction Capability ESPC 25

26 ESPC Program Office Updates Program Manager (Dr. Daniel Eleuterio) from Navy/ONR and Deputy Program Manager (Dr. Jessie Carman) from NOAA/OAR/OWAQ. ESPC Website at Outreach through AMS, AGU, THORPEX, USGCRP, NOAA Environmental Modeling Group, National Ocean Council, etc. Earth System Prediction Capability ESPC 26

27 NUOPC 2010 NUOPC/ESPC Relationship and Strategy Implementation IOC 2012 ~ FOC Operations/Sustainment/Transitions 2018 ~2025 ESPC Plan R&D DEMO Design/Develop/Implement NUOPC Implement operational, global, multi-model atmospheric ensemble system Develop common NUOPC research agenda and lead common model architecture (CMA) Transition ESPC accomplishments/advancements ESPC Focus on next generation system, integrated earth system prediction at extended ranges Develop common ESPC research agenda and support common model architecture (CMA) enhancements for ESPC systems Coordinate interagency R&D efforts, engaging multiple federal, private and academic organizations towards extended range prediction beyond current operational forecast ranges through leverage of weather and climate communities Earth System Prediction Capability ESPC 27 IOC FOC

28 Phase II: Decadal Prediction (5-30+ years) The decadal to multi-decadal prediction issue is more complex and more focused on the forced problem and limits of predictability Physical solar variability, aerosols, volcanic, albedo, glacial and sea ice melt, ocean circulation and acidification, desertification Biogeochemical ocean microbial, migrations including human, plant and animal. Societal deforestation, agriculture, urbanization, industrial Political carbon limits, economic cycles, policy, water resources, warfare, Leverage National and International ongoing efforts in defining operational capability at these timescales: availability and reliability of information against decision requirements and format and mechanism for operational product generation, validation, and distribution. Earth System Prediction Capability ESPC 28

29 Extreme Weather Events: Predictability of Blocking Events and Related High Impact Weather at Lead Times of 1-6 Weeks Stan Benjamin Chief, Assimilation and Modeling Branch GSD, Earth Systems Research Laboratory 325 Broadway Boulder, CO Earth System Prediction Capability ESPC 29

30 Seasonal Tropical Cyclone Threat: Predictability of Tropical Cyclone Likelihood, Mean Track, and Intensity from Weekly to Seasonal Timescales Melinda Peng Atmospheric Dynamics and Prediction Branch Code 7530 Marine Meteorology Division Naval Research Laboratory #7 Grace Hopper Ave Monterey, CA (831) Earth System Prediction Capability ESPC 30

31 Arctic Sea Ice Extent and Seasonal Ice Free Dates: Predictability from Weekly to Seasonal Timescales Phil Jones Climate, Ocean and Sea Ice Modeling T-3 MS B216 Los Alamos National Laboratory PO Box 1663 Los Alamos, NM Earth System Prediction Capability ESPC 31

32 Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks Gregg Jacobs Naval Research Laboratory Bldg Code 7320 Stennis Space Center, MS (228) Earth System Prediction Capability ESPC 32

33 Open Ocean: Predictability of the Atlantic Meridional Overturning Circulation (AMOC) from Monthly to Decadal Timescales for Improved Weather and Climate Forecasts Jim Richman Naval Research Laboratory Bldg Code 7323 Stennis Space Center, MS (228) Earth System Prediction Capability ESPC 33