1. 1 The Proposed Next-Generation NCEP Production Suite EMC Senior Staff January 2007 NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems

2. 2 Overview Preparing for the future Production Suite: Conceptual prototype Benefits Summary

3. 3 Preparing for the Future (1) Improved forecast services –Greater focus on high-impact events –Additional environmental information service responsibilities –Provide more information to users and access to more info Support forecast offices –Efficient Grid Initialization (e.g. SmartInit) –Analysis of Record (and RTMA) –Probabilistic and ensemble methods Respond to external (NRC) reports –“Completing the Forecast” –“Fair Weather” Respond to NOAA Science Advisory Board reviews –Ocean modeling (National “backbone”) –Hurricane intensity (ensemble-based system)

4. 4 Preparing for the Future (2) Observations (number and availability) –Advanced Polar and Geostationary sounders (~100 X greater) NPOESS (<60 minutes globally) – 2012-2015 (or later) METOP (1-4) – 2007 NPP (90-120 minutes globally) – 2009 GOES-R – 2013 (or later) –Next-generation Doppler radar Advanced post-processing techniques for multi-model ensemble (e.g. NAEFS project) –Bias correction –2 nd moment correction –CPC “consolidation” to quantify “value-added” Advanced dissemination strategies –E.g. NOMADS (“Fat server/Thin Client” technology) Next-Generation Air Traffic-control System (NGATS) –Geographically consistent solutions –Global to terminal scales –At least hourly updating globally

5. 5 Preparing for the Future (3) Three principals for moving forward 1.Maturing, ensemble-based, probabilistic systems offer the most potential benefits across wide spectrum of forecast services “Model of the day” is not a scientifically supportable solution for the future 2.Ensemble composition a.Managed component diversity b.Components must be institutionally supported (operational or major research institution) 3.Product delivery a.Time is critical (perishable product) b.Information availability must be maximized

6. 6 Production Suite: Conceptual Prototype Products Three levels of information –Routinely delivered 1.Pointwise, single-valued, downscaled Most Likely Forecast from all available guidance on NDGD grid 2.Description of forecast uncertainty through probability density function (pdf) –“On-demand” (via publicly accessible server) 3.Individual ensemble member forecasts available Prototype: NOMADS

7. 7 Production Suite: Conceptual Prototype Application Areas Focus on high impact weather –Hurricane intensity (and track) and coastal impacts –Other “High impact” defined by Users Type of event –Goal: “warn on forecast” for highest resolution events (e.g. tornado) Examples of other new applications –Surface transportation (e.g. “winter weather”) –Environmental monitoring (AQ + Atmos. Constituents) –Ocean (HABs & ecosystems, fog & visibility, coastal inundation, dynamic storm surge) –Hydrology (water quality, drought) Hourly updating –RTMA  AOR (through Reanalysis/Reforecast) –Regional assimilation –Global assimilation + + if requirement and available computing and human resources

8. 8 Production Suite: Schematic Overview Model Region 1 Model Region 2 Global/Regional Model Domain Analysis Concurrent execution of global and regional applications –More efficient execution of rapid updating In-core updating for analysis increments Regional (CONUS, Alaska, Hawaii, Caribbean & Puerto Rico) Global (if requirements and resources) –All ensemble members may exchange information during execution ESMF-based Common Modeling Infrastructure

9. 9 Analysis -------------- Other Forecast Systems Physics (1,2,3) ESMF Utilities (clock, error handling, etc) Post processor & Product Generator Verification Resolution change 1-1 1-2 1-3 2-1 2-2 2-3 ESMF Superstructure (component definitions, “mpi” communications, etc) Multi-component ensemble + Stochastic forcing Coupler Dynamics (1,2) Application Driver ESMF* Compliant Component System * Earth System Modeling Framework (NCAR/CISL, NASA/GMAO, Navy (NRL), NCEP/EMC) 2, 3 etc: institutionally (non-NCEP) supported

10. 10 CFS MFS WAV CFS & MFS GENS/NAEFS GFS Next Generation Prototype Phase 4 - 2015 Regional Rap Refresh Global HUR SREF Reforecast Hydro / NIDIS/FF Hydro NAM GDAS RDAS RTOFS AQ NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems AQ Computing factor: 81 Concurrent GFS * NAM SREF Hourly GDAS RDAS Rapid Refresh Expanded Hurricane capability (hires) Hydro/NIDIS Reforecast * Earlier delivery of GFS  concurrent combined products from NAM, GFS, SREF

11. 11 CFS & MFS CFS MFS WAV GFS Regional Rap Refresh Global SREF Reforecast Hydro NAM GDAS RDAS RTOFS CFS & MFS AQHydro / NIDIS/FFAQ GENS/NAEFS >100% of 2015 computing Next Generation Prototype Final – 2017+ NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems GLOBAL NGATS HUR Computing factor: > 240 ECOSYSTEMS SPACE WEATHER HENS

12. 12 Summary of Benefits GDAS and RDAS with advanced assimilation techniques –Use high density time and space observations more completely –Prepare for NPOESS, METOP, next-generation radar obs –Provide potential for expanded Rapid Refresh capability to serve NGATS Concurrency and unified post-processing provide –Earlier delivery of GFS products –Real time boundary conditions for regional systems –Global and regional ensembles giving complementary uncertainty measures based on different physical mechanisms –Unified “D(prog)/Dt view from all guidance products Reanalysis/Reforecast capability –Enables maximum forecast skill and independent skill assessment –Provides Operationally supported probabilistic systems Updated skill evaluation as forecast systems evolve Grouping of regional ocean applications allows –Hurricanes to use real-time ocean state –Coastal applications to run concurrently

13. 13 Summary Phased evolution of the NCEP Production Suite –2009-2015 Results in –Improved services for high impact weather –Application of advanced data assimilation techniques for improved model initial conditions –More efficient Use of computing Incorporation of new product lines for improved services –Earlier product delivery –More uniform and informative product stream Advanced ensemble suite including components supported outside NCEP Improved statistical post-processing Reforecast and Reanalysis become operationally supported Consistent with existing ESMF & global data assimilation development and interagency collaborations with –NASA –DOD –NCAR

14. 14 Thanks Questions?

15. 15 Extras

16. 16 GDAS GFS anal NAM anal CFS RTOFS SREF NAM AQ GFS HUR RDAS Current (2007) GENS/NAEFS Current - 2007 NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems

17. 17 CFS MFS WAV CFS & MFS GENS/NAEFS GFS Next Generation Prototype Phase 4 - 2015 Regional Rap Refresh Global HUR SREF Reforecast Hydro / NIDIS/FF Hydro NAM GDAS RDAS RTOFS AQ NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems AQ

18. 18 Community-based Development Strategy and roles: –Focus on single component instead of entire model system –Collaborative, not competitive –NCEP/EMC Maintains primary components for each part of Production Suite and for each application Supports ESMF applications in operations In collaboration with community –Integrates new ESMF-based components into operations –Performs final testing and preparation of upgrades of supported components in operations –Collaborators Provide –Component upgrades to be tested in operational setting –Institutional support for their contributed components –Diversity and expertise complementary to operations Work through DTC, JCSDA, CTB, etc.

19. 19 Conceptual Prototype: Numerical Forecast Guidance (1) Information should be optimally combined from all available sources –Domestic and international models (global, e.g. NAEFS and regional) –Same product format for all time scales (unified post- processing) Progress in numerical forecast system development should not be constrained by post- processing –Improved products come from development of improved systems Robust training and outreach program must –Accompany new probabilistic- based system –Support NWS Field Operations, commercial sector and international users –Support advanced dissemination of forecast information on all time and space scales

20. 20 Conceptual Prototype: Forecast System Development Areas Observations processing –JCSDA –Increased focus on quality control –Contribute to future observing system design Data assimilation –Coordinated development of advanced techniques Simplified 4-D Var (NCEP/EMC), annual updates thru 2008 “Classical” 4-D Var (with NASA/GMAO) Ensemble Data Assimilation (with ESRL, UMD and others) Development coordinated with NASA-NOAA-DOD JCSDA 2008 decision  2010 implementation –Better use of high time and space density, remotely-sensed data Model accuracy (dynamics and physics) –Hybrid vertical coordinate (sigma-pressure-theta) –Semi-lagrangian, Semi or Fully Implicit –Advanced radiation, shallow convection, deep convection –Stochastic forcing –Land surface tiling –Increased collaboration with community (Test Beds) Post-processing –Unified system across time and space scales and models –Includes bias correction and downscaling

21. 21 NCEP’s Next Generation Operational Forecast System YearsYearsWeeksWeeksMinutesMinutesDaysDaysHoursHoursSeasonsSeasonsMonthsMonths Type of Guidance Warnings & Alert Coordination Watches Forecasts Threat Assessments Guidance Outlook Lead Time Protection of Life/Property Flood mitigation Navigation Transportation Fire weather HydropowerAgriculture EcosystemHealth CommerceEnergy Initial Condition Sensitivity Boundary Condition Sensitivity Reservoir control Recreation Forecast Uncertainty Forecast Uncertainty “Forecast Countdown for the Seamless Suite”

22. 22 Concurrent execution of global and regional forecast models (2) Model Region 1 Model Region 2 Global/Regional Model Domain Analysis Local Solution Real time boundary and initial conditions available hourly –“On-demand” downscaling to local applications Similar to current hurricane runs but run either –Centrally at NCEP OR –Locally (B.C, I. C. retrieved from on-line data at NCEP) No boundary or initial conditions older than 1 hour –Flexibility for “over capacity” runs Using climate fraction must be planned No impact on remainder of services Consistent solution from global to local with a single forecast system and ensembles providing estimate of uncertainty

23. 23 ESMF Component Framework Application Change Resolution Surface Cycling Atmosphere ATM Dynamics ATM Physics Post Vertical Post Product Generator Output GRIB/BUFR some other Coupler some other Component

24. 24 GDAS GFS anal NAM anal CFS RTOFS SREF NAM AQ GFS HUR RDAS Data processing Current (2007) GENS/NAEFS Current - 2007 NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems

25. 25 CFS MFS Regional Rap Refresh Global Refcst Hydro HOURLY RTOFS AQ NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems Ideal State DATA ASSIM GA RA GO RO HU RTOFS-ECOS Hydro / NIDIS/FF AQ HUR SREF GFS GENS/NAEFS WAV NAM Med Range Refcst Wk2 MFS & CFS

26. 26 Reforecast NAM anal CFS SREF NAM GFS WAV HUR Next Generation Prototype Phase 1 - 2009 3-hourly GDAS (2) 1-hourly RDAS (6) GENS/NAEFS RTOFS AQ GFS Anal NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems Added 1-Hourly RDAS 3-Hourly GDAS Reanalysis/ Reforecast Computing factor: 3

27. 27 Reforecast GFS Anal NAM Anal CFS & MFS GFS WAV HUR GENS/NAEFS Next Generation Prototype Phase 2 - 2011 GDAS SREF RDAS RTOFS Hydro / NIDIS AQ NAM NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems AQ Added Hydro/NIDIS products Moved GFS ½ h earlier Expanded Hurricane & wave products Incorporated Multi-domain rapid updating Computing factor: 9

28. 28 Reforecast GFS Anal NAM Anal CFS & MFS GFS WAV HUR GENS/NAEFS Next Generation Prototype Phase 3 - 2013 GDAS SREF RDAS RTOFS NAM NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems AQ Hydro / NIDIS/FF AQ Computing factor: 27 Added Flash flood products Moved SREF concurrent to NAM Expanded Reforecast capability

29. 29 EVOLUTION of the Next-Generation NCEP Production Suite (1) PhaseDateComputer Power* Human Resources Implementation of new services 120093 +8 (2 - 2008 3- 2007 2 – 2008 1 - 2009) Increased forecast accuracy with hourly RDAS/LDAS, 3 hourly GDAS/GLDAS (2), and Advanced Data Assimilation (2010) Reanalysis-Reforecast (5) HABs (1) 220119 +6 (2 – 2007 1 – 2008 3 – 2009) ESMF-based in-core system (5) Downscaled 4 Domain RR with Firewx Global hourly Aviation products Land-HYDRO-NIDIS seasonal products (1) 3201327 +3 (1- 2010 2 – 2011) Concurrent NAM, SREF Coupled Land-Hydro & Flash Flood (FF) guidance (1) Biogeochemical tracers (2) * Relative to NCEP’s 2007 computer

30. 30 EVOLUTION of the Next-Generation NCEP Production Suite (2) PhaseDateComputer Power* Human Resources Implementation of new services 4201581 @ +5 (2 – 2011) (3-2010) Hourly GDAS + Concurrent GFS + Fully coupled global atmosphere-ocean Advanced global ensemble system Hurricane ensemble (1) @ Dynamic storm surge ensemble (1) @ NGATS support@ Final2017 (+) 240 +2 (2 – 2015) Concurrent GEFS/NAEFS Hurricane ensemble Dynamic storm surge ensemble Full ecosystem support (2) NGATS support * Relative to NCEP’s 2007 computer @ additional 3x computing upgrade in 2009 required + If positive upgrade to services

31. 31 Traditional NWP Process

32. 32 Future NWP Process THORPEX PROGRAM

33. 33 Primary & Secondary Components and Models Primary components –Observations ingest, processing and quality control –Data assimilation –Forecast model –Post-processing –Product delivery Primary model –Used in data assimilation cycle –Supported by EMC for NCEP’s operations Risk reduction Optimum maintenance Optimum enhancement –Continued exposure to observations –Model improvements impact analysis and forecast Secondary model –Initialized from analysis –Not cycled –Must add value to operational system Skill Diversity Unique application –Supported institutionally by external (to EMC) organization E.g. Navy (through NUOPC) First line of support at EMC (one person) –Applications Ensemble membership (managed diversity) Not fully supportable by EMC (e.g. ecosystems)

34. 34 The Environmental Forecast Process Observations Analysis Model Forecast Post-processed Model Data Forecaster User (public, industry…) Numerical Forecast System Data Assimilation

35. 35 EMP Model Strategy & ESMF Concept of operations –Single system for global and regional models –Performance permitting Migration to single model or Multiple dynamics and physics options in single structure –Single verification, observations data base obeying WMO standards –Single analysis code –System perturbations from Model diversity Stochastic physics (preferred) System supports both operational and research components –Dynamics –Physics Overall positive experience at Met Office ECMWF maintains single model & data assimilation system for global wx & short-term climate forecasting

36. 36 Forecast System Development Strategy As far as possible, based on quantitative assessment: –A single physics –Applied across multiple scales –E. g. global weather and climate Possible extension to mesoscale Successful for hurricane (GFS physics, NAM microphysics)  GFDL) Excellent characteristics from all applications tested on other scales and implemented when ready Single model (and DA) structure makes this feasible Ensemble application –Requires approximately equal skill and system diversity –Secondary models and diverse components create manageable system if ESMF compatible and institutional support Disciplined competition fosters the best system

37. 37 Overview of Future Jigsaw Enabled by ESMF Hourly global data assimilation analyses Hourly global rapid refresh –Supports NGATS Concurrent global and mesoscale and mesoscale ensemble Reforecast window Target 2015+

38. 38 Timing Summary (2015) Current (%)Future (%)Current Start Time Future Start Time Current End Time Future End Time GDAS5.412.06:001:306:301:40 RDAS3.27.25:301:306:001:40 GFSanal4.40.82:551:303:201:40 NAManal1.90.81:231:301:321:40 Rapid Refresh2.24.81:251:301:47 NAMfcst9.64.01:331:403:00 GFSfcst12.86.53:211:404:403:30 GENS/NAEFS7.17.63:233:305:306:00 SREF7.87.60:301:301:223:40 HUR7.77.84:303:404:306:00 RTOFS7.77.2xxxxx WAV2.43.14:323:404:536:00 AQFS2.42.12:002:305:00 CFS/MFS25.417.1xxxxxxxxxxx Hydro-NIDIS01.25xxxxx Reforecast011.5None Bold=Earlier Red=Later

39. 39 The ultimate target is a completed NOAA Framework of ESMF Components within which NOAA scientists can work efficiently. One solution is outlined in the next few slides. A Project to Create the NOAA/NCEP Framework of ESMF Components Mark Iredell

40. 40 Proposed NOAA ESMF-based System Components (1) Change Resolution –Imports ATM state on one grid –Exports ATM state on another grid, possibly changing variables and units Surface Cycling –Imports ATM boundary –Exports ATM boundary updated Atmosphere –Imports ATM state –Exports ATM state later in time Post –Imports ATM state –Exports selected products

41. 41 Dynamics –Imports ATM state –Exports ATM state later in time Physics –Imports ATM state –Exports ATM state adjusted Proposed NOAA ESMF-based System Components (2)

42. 42 Vertical Post –Imports ATM state –Exports fields on selected levels but model grid Product generator –Imports fields on one grid –Exports fields on another grid as requested Output –Imports fields –Writes GRIB2 files (or BUFR or netCDF) Proposed NOAA ESMF-based System Components (3)

43. 43 Independent validation for each component that anyone can theoretically run Examples –Dynamical core Held-Suarez, etc. –Physics Single column, etc. –Atmosphere NWP and climate verifications and diagnostics –GFS with GDAS Full parallel validation Proposed NOAA ESMF-based System Components (3)

44. 44 Other Components Other components that could be coupled to the global atmospheric model using ESMF: Obs. Processing Variational Analysis Ensemble Members Mesoscale Model Storm Model Ocean Model Ice Model Hydrology Model Chemistry Model Space Model

45. 45 Model Framework Time and People costs Estimated cost to NOAA for building: –4 years –17 man-years Maintenance cost unknown –Multiple major developers –Possible lack of coordination –Coordination may slow development and system enhancement

46. 46 Code/Algorithm Assessment and/or Development Transition Steps (Modeling) Identification for Selection 1 2 Interface with Operational Codes 3 Level I: Preliminary Testing (Lower Resolution) 4 Level II: Preliminary Testing (DA/Higher Resolution) 5 EMC Pre-Implementation Testing (Packaging/Calibration) 6 NCO Pre-Implementation Testing 7 Implementation/Delivery 8

47. 47 EMC NCO R&D Operations Delivery Criteria Transition from Research to Operations Requirements EMC NCEP’s Role in the Model Transition Process OPS Life cycle Support Service Centers NOAA Research Concept of Operations Service Centers Test Beds JCSDA CTB DTC JHT User Observation System Launch List – Model Implementation Process Field Offices Effort EMC and NCO have critical roles in the transition from NOAA R&D to operations Other Agencies & International Forecast benefits, Efficiency, IT Compatibility, Sustainability

48. 48 Component Requirements Code standards and documentation –ESMF interfaces fully described –Lightweight so as to not impede research Some compile-time and run-time flexibility –Somewhat flexible processor and thread layout –Somewhat flexible memory indexing layout –Somewhat flexible import and export fields Standard metadata –CF convention –GRIB2, etc. Distributed grid support under ESMF to enable coupling Standalone validation

49. 49 Given this solution is acceptable, how can we manage to get there? One framework project plan is given in the next few slides.

50. 50 Steps in creating model framework a)Planning and coordination b)GFS I/O components c)GFS ATM gridded component d)GFS physics component e)GFS dynamics component f)UMO dynamics component g)GFS post component h)Change resolution component i)Surface cycling component j)Coupler components k)Land component l)Ocean component m)Ice component n)Aerosol component o)Ionosphere component p)Mesoscale components q)GSI component r)Configuration management

51. 51 Substeps in model framework (1) a)Planning and coordination (1.2) 1.Unified Model Infrastructure Group (UMIG) 2.coordinate with EMC and other NOAA groups b)GFS I/O components (0.2) 1.I: input analysis, export distributed grid 2.O: import distributed grid, export history file 3.ESMF-ize c)GFS ATM gridded component (0.2) 1.import and export distributed reduced Gaussian grid 2.internal state is both spectral and grid 3.faster than current GFS 4.keep dynamics and physics embedded at first 5.ESMF-ize d)GFS physics component (0.2) 1.combine radiation and other physics 2.standardize import and export states 3.run on any set of points 4.run with or without land model 5.ESMF-ize

52. 52 Substeps in model framework (2) e)GFS dynamics component (0.2) 1.import and export distributed reduced Gaussian grid 2.all spectral data and transforms are internal 3.may have two phases (two modes of invocation) 4.ESMF-ize f)UMO dynamics component (0.2) 1.Import and export distributed UMO grid 2.may have two phases 3.ESMF-ize g)GFS post component (1.0) 1.adapt WRF post to GFS 2.import distributed model grid 3.write data in GRIB2 4.ESMF-ize h)Change resolution coupler component (0.2) 1.import one ATM model state and convert to another 2.ESMF-ize i)Surface cycling component (0.2) 1.adapt current surface cycling component 2.ESMF-ize

53. 53 Substeps in model framework (3) j)Coupler components (4.0) 1.between ATM and ice and ocean for CFS 2.adapted from Sheinin’s coupler 3.ensemble coupler 4.other couplers as well – generic coupler? 5.ESMF-ize k)Land component (1.0) 1.ESMF-ize Noah land model l)Ocean component (1.0) 1.ESMF-ize MOM4 minimally 2.EMSF-ize HYCOM m)Ice component (1.0) 1.ESMF-ize NCEP fast ice physics 2.ESMF-ize GFDL slow ice physics n)Aerosol component (1.0) 1.ESMF-ize GOCART aerosol model o)Ionosphere component (0.8) 1.ESMF-ize IDEA ionosphere model

54. 54 Substeps in model framework (4) p)Mesoscale components (2.6) 1.non-WRF NMM 2.WRF and HWRF 3.run nested or standalone 4.ESMF-ize q)GSI component (1.6) 1.minimal subroutinization 2.ESMF-ize r)Configuration management (0.4) 1.Install and maintain Subversion 2.Subversion training and support 3.Version control on scripts and code for CCS, R&D, and local servers

55. 55 Dependence on ESMF software developed and maintained by NCAR Risk: e.g., ESMF did not compile on “mist” (turned out to be a compiler deficiency) Potential critical mass of users (NOAA, DOD, NASA) Potential support from IT contractors Further layering (e.g., MAPL from NASA)

56. 56 What is an ESMF Component? An ESMF Component has 3 methods: initialize, run, finalize Methods have a standard interface, including 1 import state and 1 export state A component also has an internal state, which contains whatever persistent data the component needs, and which is generally not visible to other components

57. 57 Gaussian Kernels “Frequentist” methods “Bayesian” methods Construction of Optimum Forecast Guidance from Multi-Model Ensembles 1.Multiple independent realizations 2.Historical “reforecast” data set 3.Optimal postprocessing to produce “the best” forecast 4.Compact information dissemination