1 FY10-14 Planning

2 Vision for 2015 NOAA is closer to its customers and better able to respond to severe events. NOAA information is routinely incorporated into critical decision making. Improved communication of uncertainty and risk associated with high impact events Integrated information presented in useful formats (e.g., geo- referenced, appropriate temporal and spatial resolution, probabilistic, etc.) NOAA helps communities to become more resilient to severe events.

3 High Impact Operations Planning FY Objectives Optimal use of state-of-the-art science and technology A skilled and diversely specialized workforce able to provide most effective response to high impact events. Improved integration of NOAA’s environmental information in the operational setting and in the resulting products and services.

4 High Impact Operations Planning FY Approach Hazard Resiliency –Decision Aids Test Beds/ Proving Grounds Warn-On-Forecast Probabilistic Work (Ensembles) Integrated Environmental Information NOAA/NIST Partnership –Operations Integrated Services Training IMET Expansion Transitions –Preparedness Situational Awareness and Response R&D Enhanced Outreach Science/Tech Infusion to Improve Core Mission Functions –Radar TDWR MPAR NEXRAD NPI VORTEX II –Operations Training Transitions AWIPS II –Mass Dissemination Systems

5 FY10-14 Planning Challenges Obs Requirements Performance Measures NGATS Sustaining of Critical Systems –NEXRAD O&M –ASOS O&M –Wind Profiler –Weather Radio

6 Current R&D The following slides show examples of OAR initiatives supporting high impact operations and integrated services. This is not a complete survey – just a sampling to show the opportunities for planning on the service delivery side.

7 The NMQ Project The National Mosaic and QPE (NMQ) Project is a framework for scientific and community wide convergence towards high resolution, accurate quantitative precipitation estimation (QPE) and very short term quantitative precipitation forecast (VSTQPF) for all scales, seasons and geography. The NMQ is a real-time, around-the-clock, data infusion and applications development and evaluation environment that includes data quality control, automatic algorithm comparison and verification. A National Testbed for MSQPE and VSTQPF

8LightningLightning Upper Air Sfc Obs SatelliteSatellite ModelsModels Radar Networks Radar Networks Integrated approach to precipitation water monitoring and prediction for water resource management and flood prediction.

9LightningLightning Upper Air Sfc Obs SatelliteSatellite ModelsModels Radar Networks Radar Networks Seamless High Resolution Quantitative Precipitation Estimation - Incremental Complexity 1x1 km North America Precipitation Estimation Update Every 5 minutes CONUS

10 Data Ingest/Remap Quality Control Data Integration National 3D Mosaic Data Ingest/Remap Quality Control Data Integration National 3D Mosaic NMQ SystemLightningLightning Upper Air Sfc Obs SatelliteSatellite ModelsModels Radars Networks Radars Networks Real Time QPE & VSTQPF Development and Run Environment Real Time QPE & VSTQPF Development and Run Environment Verification and Assessment (QVS) Operational Infusion and Enhancement Continuous (tilt by tilt) ingest and processing of base radar data from nearly and 5 cm radars HMT

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12 The future evolution of warning decision-making science Forecaster-based uncertainty “Warn on detection” (deterministic) Blended statistics NWP WRF storm typing Statistics-based uncertainty NWP “Warn on forecast” Storm-scale NWP EnKF analysis / storm typing Existing storms Newly initiated convection Present2010 (± 2 yr)2017 (± 5 yr)2025 (± 10 yr) Forecast convection (doesn’t yet exist) WSR-88DDual-Polarization RadarPhased Array Radar

13 Probabilistic Warning Guidance Existing building blocks: Analysis1-hr forecast Extrapolative Forecast Techniques Diagnostic Applications Rotation Tracks Satellite Numerical models Radar Lightning Surface Multi-radar/multi-sensor environment (e.g. WDSS-II) “Hail Swath” with dense verification Enhanced verification of severe storms 2-hr max MESH

14 Probabilistic Warning Guidance Future building blocks: Dual-pol radar output Expanded enhanced severe storm verification Scientific advancement: Straight-line winds Climatological storm type statistics Greater computational ability Initial threat area30 min. threat probability 1 hr threat swath (accum)Est. time of arrival

15 NOAA Hazardous Weather Testbed EFP - SPC/NSSL Spring Experiments Recent Spring Experiments examined Short-Range Ensembles and convection-allowing WRF models –Can new NWP concepts provide useful guidance for severe weather forecasting? –Partnerships with EMC, NCAR, and OU-CAPS –Developed & tested many new SREF and high resolution WRF guidance tools that were subsequently transferred to operations SREF Spaghetti Chart 4.5 km WRF-NMM Reflectivity

16 4 km WRF-ARW4.5 km WRF-NMM 2 km WRF-ARWRADAR VERIFICATION

17 WRF 24 hr Reflectivity Forecasts Valid 00z 26 May 2005 ARW4 ARW2 NMM4 RADAR 4 km WRF-ARW 2 km WRF-ARW 4.5 km WRF-NMM RADAR VERIFICATION

18 Proposed HWT Activities: EFP-Spring 2007 Annual SPC/NSSL Spring Experiment (EFP) –First year of multi-year effort ( ) –Contributing Partners: SPC, NSSL, CAPS, EMC, NCAR, OUN (unique diversity of backgrounds and expertise) –Apply cutting edge science and technology leading to improved NWS services Scientific Objectives: Improve high resolution WRF models –Further explore impacts of physics (PBL, microphysics, etc.) »Pre-convective environment, PBL sounding structure, and convective storm development –Impact of resolution on WRF simulation of stormscale structures (e.g., supercells, bow echoes, etc.)

19 Proposed HWT Activities: EFP-Spring 2007 Annual SPC/NSSL Spring Experiment (EFP) Scientific Objectives (cont’d) –Begin to explore utility of a daily 4 km convection-allowing 10 member WRF ensemble for short-term (12-30h) prediction of severe convection Investigate IC versus physics in convection-allowing ensemble Explore impact of physics on ensemble performance –Environment; convective initiation, intensity and mode Compare to “higher” resolution deterministic WRF –2 km WRF (CAPS) and 3 km WRF (NCAR and EMC) Begin developing interrogation tools to extract ensemble-based information for hazardous weather events – A “baby step” in early testing of Warn on Forecast-type concept –Probabilistic information from convection-allowing ensemble

20 Probabilistic Forecasting Two foci: –How to develop better ensemble systems Multi-physics Initial condition perturbations Ensemble data assimilation –Postprocessing of ensemble data

21 Postprocessing Using various methods to postprocess ensemble data leads to forecasts that are better than MOS for T, Td, and PQPF

OAR PPES BriefingDRAFT - PREDECISIONAL 22 Now: NWS warning operation warnings (~ 13 min lead time) 3-6 hours: Large-scale weather prediction model output 1-3 hours: Monitor surface and satellite for initiation 0-1 hour: Warn from a single Doppler radar, spotter reports… 2020: NWS warning operations (~30+ min lead time?) 3-6 hours: Ultra-high resolution model output (e.g., km) 1-3 hours: State and local mesonets, micronets, profilers, ultra-high-res satellite Other exotic data sources (e.g., UAV’s?) 0- 1 hour: Multiple radars in metropolitan areas (public and private) x more data per radar (PAR, polarization variables) Live streaming video from news media and public Gap filling, mobile radars (public and private?) Warn on “Forecast” in : “Fire Hydrant” Data Stream Severe weather warnings Increased lead time having dense information content Storm-Scale NWP Probabilistic 0-1 hour forecasts of individual storms, potential damage swaths from tornadoes, wind, and hail Forecaster NWS PAR Surface Ob Satellite GapF radar Mesoscale Analysis/Fcst Spotter Public reports GIS Information 1 of 5 Manageable Complexity? Overwhelming Complexity! NSSL Warn on Forecast Briefing March 5, 2007 TV Radar

23 Warn on Forecast in 2020: What might it look like? Probabilistic tornado warning: Forecast looks on track, storm circulation (hook echo) is tracking along centerline of highest tornadic probabilities Radar and Initial Forecast at 2100 CSTRadar at 2130 CST: Accurate Forecast Most Likely Tornado Path T=2120 CST T=2150 T=2130 T= % 50% 30% T=2200 CST Developing thunderstorm 2 of 5 NSSL Warn on Forecast Briefing March 5, 2007 Most Likely Tornado Path T=2120 CST T=2150 T=2130 T=2140 T=2200 CST An ensemble of storm-scale NWP models predict the path of a potentially tornadic supercell during the next 1 hour. The ensemble is used to create a probabilistic tornado warning. 70% 50% 30%

24 Warn on Forecast 2020: Continuously updating the forecast based on current observations and trends…. 30% Storm is moving more northerly and slightly faster! Tornadic circulation is farther NW! New Tornado Probability Path T=2130 CST T=2200 T=2140 T= % 20% 10% New Most Likely Tornado Path Old Tornado Probability Path T=2120 CST T=2140 T=2200 CST Current radar observation 3 of 5 NSSL Warn on Forecast Briefing March 5, % 50% 30% Radar at 2130 CST: Forecast in error!New forecast created using 2130 radar data T=2210 CST

25 WoF 2020 Vision: Ultra High-Resolution Radar Data and Numerical Models Storm-scale Numerical Weather Prediction Data Quality Control Data Assimilation Storm-scale Analysis Storm-scale Forecast Visualization Model Analysis + Forecast! PAR TDWR WSR-88D TDWR PAR Reflectivity Radial Velocity 4 of 5 NSSL Warn on Forecast Briefing March 5, 2007

26 Science and Technology Enabling the Change: Storm-scale Numerical Weather Prediction North Texas Region (DFW area) 1975: was represented by a single grid point in our NWP models North Texas Region (DFW area) 2007: now can be represented by ~ 10,000 grid points Can resolve a single tornadic storm.. DFW Model grid resolution ~ 200 km Tornadic Supercell 1975 NWP Model Grid 30 years of atmospheric research + computers which are 10 million times faster Model grid resolution ~ 2 km 5 of 5 NSSL Warn on Forecast Briefing March 5, 2007