1. 1 9/21/2015 Science and Technology Infusion Plan for Numerical Prediction Science and Technology Infusion Plan for Numerical Prediction NWS S&T Committee September 17, 2002 NWS S&T Committee September 17, 2002 Jeff McQueen

2. 2 9/21/2015 Outline Team Composition Vision Key Service Gaps Key NP Solutions Outstanding R&D Needs Infusion Strategy Summary Team Composition Vision Key Service Gaps Key NP Solutions Outstanding R&D Needs Infusion Strategy Summary

3. 3 9/21/2015 Numerical Prediction Team Composition Jeff McQueen – NWS/OST Paul Dallavalle – NWS/OST Steve Koch – OAR/FSL Ralph Petersen – NWS/NCEP Jeff McQueen – NWS/OST Paul Dallavalle – NWS/OST Steve Koch – OAR/FSL Ralph Petersen – NWS/NCEP Dave Stensrud – OAR/NSSL Stan Benjamin – OAR/FSL Michael Smith – NWS/OHD

4. 4 9/21/2015 Increased Probabilistic Forecasts thru Ensembling & Postprocessing Numerical Prediction Improved Model Predictions: Improved Initialization: - Increased Use of Remote Sensed Data - Improved Small-Scale Data Assimilation More Realistic Physics: -Clouds, PBL, Radiation, Land & Water Interactions Increased Resolution __ Vision Common Model Framework For Climate/Weather/Water Drive Improved Applications - Aviation, Marine, Hydro, Tropical, AQ…

5. 5 9/21/2015 Numerical Prediction Pathway to Unified Common Model Framework 2002 20072012 Global/ Climate 2020 Ocean Regional Hydrologic Hurricane Hazards/AQ GFS ROFS Eta RUC SFM NOAH/ AHPS Hysplit GFDL Coupled atm-ocean global model Coupled (L/A/H/AQ) WRF Framework Unified fully coupled framework for climate/weather/water time Deterministic &Probabilistic Coupled Land-atm-ocean-ice global model Coupled (L/A/H/AQ) WRF Framework Deterministic &Probabilistic

6. 6 9/21/2015 Numerical Prediction Key Service Gaps Linking Model Advances to Service Improvements Improve Forecasts of Mesoscale Phenomena: –Severe Storm, Gravity Waves, Turbulence –Precip Types, Cloud, Surface Properties Improve Confidence Levels and Range of Probabilities More Accurate Warm and Cool Season QPF Storm Track & Intensity Forecasts & Associated QPF Improve Week Two to Seasonal Range Forecasting Improved Forecasts of Global Ocean Conditions Implement Air Quality Forecasts Improve Forecasts of Mesoscale Phenomena: –Severe Storm, Gravity Waves, Turbulence –Precip Types, Cloud, Surface Properties Improve Confidence Levels and Range of Probabilities More Accurate Warm and Cool Season QPF Storm Track & Intensity Forecasts & Associated QPF Improve Week Two to Seasonal Range Forecasting Improved Forecasts of Global Ocean Conditions Implement Air Quality Forecasts

7. 7 9/21/2015 Improved Confidence Levels and Range of Probabilities More Accurate Mesoscale Phenomena Forecasts Service Gap Numerical Prediction Key Solutions Impact Provide a Range of Forecasts & Uncertainty Improved Forecasts Downstream of Data- Sparse Areas Advanced Ensembles (SREF;GFS) (SREF;GFS) Targeted Obs Techniques Ensemble PDFs, Neural Nets Improved Low-Level Wind Forecasts by 20% Improved Convection Forecasts by 15% Improved Cloud Properties (Icing, C&V..) Improved Visibility by 10% Improved QPF by 10% WRF(NA, HRW, RRW), SREF Advanced Data Assimilation Remote Sensing Upgrades Advanced Cloud Physics (WRF)Cloud Physics Improved Land Surface Models (NOAH) & hydrologic coupling (NOAH) Improved Observations into Cloud Analyses & LDAS Projected Solution

8. 8 9/21/2015 Numerical Prediction Key Solutions Provide Consistent Guidance Support EPA Mission Implement IOC w/ Transition to Fully Coupled WRF-Chem Implement Air Quality Forecasts Increased Accuracy of ENSO/SST Anomalies 100% Ocean/Lake Coverage Gulf stream position Upgrade Global Ocean Data Assimilation System(GODAS) Coupled Land/Ocean/Ice GFS Land/Ocean/Ice GFS Upgrade Wave Model (10 km) Great Lakes System Improve Forecasts of Global Ocean Conditions Improve Week Two to Seasonal Forecasts of Temp/Precip/Hazards GFS, Global Ensembles Seasonal Forecast Model Coupled Ocean/Atm/Land Ocean/Atm/Land Improve Long Range Forecasting 20% increase in Intensity Marine: 20% Improvement Hurricane WRF DA/Model North Amer. WRF, GFS, HRW Ensembles/ Targeted obs ImpactProjected SolutionService Gap More Accurate Warm Season Precipitation More Accurate Cool Season Precipitation North Amer. WRF, GFS Ensembles/ Targeted obs R/S Resolved w/in 30km Mtn QPF Resolved to 30km

9. 9 9/21/2015 Numerical Prediction Key S&T Solutions 03 04 05060708 09 10 1112 02 Deployment Global, SREF Probabilistic WRF SREF Multi-model* Hydrologic Hybrid veg/soil Distributed basin* GFS T254 Global Coupled* ocean/atm/land Common* Global-30/ Regional-3 Adv. Assim. * NPOESS Radar Data Assimilation Cloud/GODAS Regional/AQ WRF: NA-8, RR, HRWEta, RUC,HRW cpld AQ WRF-4* Ozone Physics Existing cloud physics Explicit cloud* & Adv physics Coupled AQ DTE R&D OTE Common* SFM/GFS Climate Global Ocean Model AHPS SFM T62 Eta/GFS MOS Ensemble PDF Neural Nets Super Computing 80x36x14x2x9x

10. 10 9/21/2015 Numerical Prediction Outstanding R&D Needs Enhanced Methods to Assimilate Increasing Volume of Remote Sensed Data Develop Small-scale Assimilation Techniques and Deploy Obs Database Improve High Resolution Physics Improved Hydrological-Ocean-Atmosphere coupling Develop Mesoscale Verification Techniques Improved Methods to Convey Confidence Levels and Range of Probabilities –Reduced Model Biases –Merge Ensembles with High-Resolution Models Enhanced Methods to Assimilate Increasing Volume of Remote Sensed Data Develop Small-scale Assimilation Techniques and Deploy Obs Database Improve High Resolution Physics Improved Hydrological-Ocean-Atmosphere coupling Develop Mesoscale Verification Techniques Improved Methods to Convey Confidence Levels and Range of Probabilities –Reduced Model Biases –Merge Ensembles with High-Resolution Models

11. 11 9/21/2015 Numerical Prediction Infusion Strategy Emphasize Partnerships –WRF; ESMF (NOAA, NCAR, FAA, AFWA, Navy, NASA, Universities) Develop Common Architecture –Common Model/Data Assimilation Framework WRF, Radiative Transfer Models, ESMF –Multi-disciplinary Coupled Codes Atmosphere, Hydrologic, Ocean, AQ –Teragrid Concept for Increased Data Nodes Implement Modeling Testbed –JCSDA –NOAA/NCAR DTC Emphasize Partnerships –WRF; ESMF (NOAA, NCAR, FAA, AFWA, Navy, NASA, Universities) Develop Common Architecture –Common Model/Data Assimilation Framework WRF, Radiative Transfer Models, ESMF –Multi-disciplinary Coupled Codes Atmosphere, Hydrologic, Ocean, AQ –Teragrid Concept for Increased Data Nodes Implement Modeling Testbed –JCSDA –NOAA/NCAR DTC NWS Avia tion Coastal Marine Severe Observ ations NWP Climate Satellite Hurricane Universities, Labs, Other Universities, Labs, Other Universities, Labs, Other Universities, Labs, Other

12. 12 9/21/2015 Numerical Prediction Towards a Common Modeling Infrastructure Weather Research and Forecast (WRF) Model State-of-the-Science, Common Infrastructure System Supporting Advanced Regional- to Local-Scale Research & Operational Forecasting More Effective and Timely Transition of Research into Operations Partners: NOAA, NCAR, USAF, USN, FAA Unified Global, Climate and Mesoscale Numerical Forecast System Improve Climate/Global/Weather predictions Weather Research and Forecast (WRF) Model State-of-the-Science, Common Infrastructure System Supporting Advanced Regional- to Local-Scale Research & Operational Forecasting More Effective and Timely Transition of Research into Operations Partners: NOAA, NCAR, USAF, USN, FAA Unified Global, Climate and Mesoscale Numerical Forecast System Improve Climate/Global/Weather predictions

13. 13 9/21/2015 Numerical Prediction WRF Framework Supports Deterministic & Probabilistic Forecasts WRF Core 2 (ESMF) WRF Core 3 WRF Core 1 Data Assimilation Initial Conditions & Ensemble Perturbations Physics Options Aviation Marine Tropical Severe Storms Winter Wx Hydrologic Air Quality Hazards

14. 14 9/21/2015 Numerical Prediction Infusion Strategy: Testbed Developmental Test Centers Operational Test Centers NCAR OAR NCEP FNMOC AFWA Universities & Labs WRF Contributed Code WRF Reference Code WRF Operational Code NRL

15. 15 9/21/2015 Numerical Prediction Summary 2007 2012 Increasing Performance 2020 2002 R&D Needs Assimilation of Increasing Volume of Remote Sensed DataAssimilation of Increasing Volume of Remote Sensed Data Small-scale Assimilation TechniquesSmall-scale Assimilation Techniques Improved Representation of Non- Hydrostatic Scale PhysicsImproved Representation of Non- Hydrostatic Scale Physics Probabilistic Approaches Probabilistic Approaches Mesoscale Verification TechniquesMesoscale Verification Techniques Common Climate/ Global System More Realistic Cloud Physics Improve Use of Existing & New Observations WRF Framework Advanced Ensembling Cloud Analysis Adv. Small-scale Data Assimilation Adv. Physics/ Coupled AQ Vision Common Model Framework For Climate/Weather/Water Supporting NWS Service missions

16. 16 9/21/2015 Back Ups Roadmaps Resolution Time-Series Observational Needs

17. 17 9/21/2015 Data Assimilation Roadmap

18. 18 9/21/2015 Numerical Prediction Roadmap 20002 2004

19. 19 9/21/2015 Architecture Key S&T NP Timeline 03 04 05060708 09 10 1112 02 Deployment OTE DTE R&D GFS 95kL42 SREF 48kL50 Probabilistic Multi-model 70kL60 SREF 12kL64 Ocean North America (4x/day) Cpld 80kL64 Annual AGCM 381k28L 7mo-1/mon Climate (1/mon) SFM 95kL64 HRW (1x/day) NMM 8kL64 48h/3 h Global (4x/day) GFS 55k64L 384h/3h GFS 45k64L 384h /1h Cpld 30kL100 RUC 20kL50/12h RRW (8x/day) ROFS 20k/Atl 48h/ 24h GFS 90kL42 SREF 18kL60 Eta 12k64L 84h/3h RRW 11kL60/12h RRW 8kL70/18h 12x WRF 8k70L 84h/1h WRF 4k/100L 96h/1h WRF6kL70 48h/2 h WRF 2k/100L 48h/1 h ROFS 20k/glb 5 day Cpld 20k/glb 2 week

20. 20 9/21/2015 200320072012 Physics Dta Assim Regional Global Numerical Prediction Advances Resolution and Ensemble Members

21. 21 9/21/2015 Numerical Prediction Advances Supercomputing Increases FY03: 1408 1.3 Ghz SP Processors

22. 22 9/21/2015 Numerical Prediction Key Observational Gaps and S&T Solutions Observational GAP Projected SolutionExpected Impact Mesoscale wind thru troposphere (highest res in PBL) Better use of existing obs Enhanced ACARS/MDCRS Space borne wind lidars, NPOESS Upgrade NOAA profilers Improved accuracy of short- term trop. Wind forecasts Mesoscale moisture especially in PBL WVSS-2/AMDAR upgrades GPS IPW Improved accuracy of short- term cloud, visibility, temperature forecasts Improved observations in data sensitive areas Targeted observations methods Improved winter/tropical storm prediction Improved cloud properties observations Dual pole radars 88D superobs GIFTS Improved storm & cloud analysis and prediction Improved land/water/ snow surface roperties NPOESS COOP modernization Improved hydrologic & short term temperature forecasts

23. 23 9/21/2015 Ensemble Forecasts Ensembles can provide information on the likely range of forecast parameters and forecast uncertainty to users Mean value Range Ensemble spread can be used to determine how observational data influences neighboring regions in data assimilation schemes

24. 24 9/21/2015 Next-Generation Operational Models Cloud-scale Modeling ( dx = dy = 2 km, dz = 500 m, dt = 12 s, 160 x 160 x 20 km domain ) Surface temperature, surface winds and cloud field at 2 hours Many Science and Technology Questions Remain

25. 25 9/21/2015 Potential Cloud-scale model benefits 12-hour NWS Forecast (unable to representindividualthunderstorms) Moore, OK Tornadic Storm 2-Hour CAPS Computer Forecast Down to the Scale of Counties NEXRAD Radar Observations Moore, OK Tornadic Storm

26. 26 9/21/2015 Numerical Prediction Advances Dissemination Requirements 2007

27. 27 9/21/2015 Current Operational Forecast Models Operational forecast models predict: Mesoscale and synoptic flow patterns Precipitation via parameterizations that are unable to resolve individual storms Important storm-scale weather cannot be resolved : Operational forecast models predict: Mesoscale and synoptic flow patterns Precipitation via parameterizations that are unable to resolve individual storms Important storm-scale weather cannot be resolved : USING THIS TO ANTICIPATE THIS

28. 28 9/21/2015 Towards a Coupled Modeling System with downscaling to hydrology models SST PREDICTION GENERAL CIRCULATION LATERAL B.C. REGIONAL COUPLED ATMOS-LAND MODEL 10 - 30 km PRECIP, Ts, LAND-SFC FORCING REGIONAL UNCOUPLED LAND-HYDRO MODEL 1-10 km RUNOFF SNOWPACK STREAMFLOW SOIL MOIST GLOBAL COUPLED ATMOS-LAND MODEL 30 - 100 km GLOBAL LAND 4DDA GLOBAL ATMOS 4DDA GLOBAL OCEAN 4DDA REGIONAL LAND 4DDA REGIONAL ATMOS 4DDA GLOBAL COUPLED OCEAN-ATMOS LAND MODEL 100 - 500 km

29. 29 9/21/2015