Cool Season QPF Workshop “Plan for Success”

1. Cool Season QPF Workshop“Plan for Success” “Where America’s Climate and Weather Services Begin” Louis W. Uccellini Director, NCEP Boulder, CO February 2, 2004

2. Overview • Background • Keep in mind: • Think boldly with stretch goals • Focused efforts – Test Beds – Yield results • Consider entire spectrum of forecast process • Role of THORPEX

3. Background • Need for improved QPFs well established • Warm season • Flood prediction (flash floods) • Water resources • Cool season • Flood prediction • Water resources • Transportation • Business • Safety • QPF to PQPF • Uncertainty matters • New paradigm for forecasters – Ensemble approach

4. USWRP Foci Air Quality Surface Transportation Future Foci Hurricane at Landfall CAMEX CBLAST JHT Extended/QPF Forecasts Warm Season (IHOP) Cool Season Hydromet Test Bed Primary USWRP Science Foci IPO Lead Scientist Societal Impacts Science Processes Coordination IPO and USWRP Program Requirements & Support Optimal Mix THORPEX WRF/DTC/OTC JCSDA/SPoRT

5. Think Boldly with Stretch Goals • Don’t let past rate of improvement encumber future progress • How far to extend? Day 7? (remember PQPF) • Skill increases: 2 days per decade?

6. NHC Yearly-averaged Atlantic Track Forecast Errors 24 hr 48 hr 72 hr

7. Focused Efforts Work • Emphasize Service – Science linkage • Test beds created (JHT, JCSDA, HWFT, DTC) • Scores improve • Transfer from research to operations accelerated • QPF needs a Hydrometeorological Test Bed (Distributed?)

8. TPC Atlantic 72 hr Track Forecast Errors

9. Thursday, 9/18/03 12 PM EDT 5-day forecast Hurricane Isabel 3-day forecast

11. Consider Entire Forecast Process • Collaborative Forecast Process • Consider each component a challenge

12. 1998

13. Role of THORPEX • Warm season has its large scale program: North American Monsoon Experiment (NAME) • Cool season should adopt THORPEX • To forecast locally, regionally, and nationally, need to think globally! • Global data drives the data assimilation/model forecast systems • Data is primarily satellite • We are in the pre-NPOESS era • Activity should link with JCSDA, WRF, ESMF Fundamental Principle

14. NPOESS Era Data Volume Five Order of Magnitude Increase in Satellite Data Over Next Ten Years Daily Satellite Observation Count 2003 125 M obs 2002 100 M obs Count (Millions) 1990 2000 2010 2010-10%of obs

15. THORPEX • 4 Science Areas • Predictability and Dynamical Processes • Observing Systems • Data Assimilation and Observing Strategies • Societal and Economic Applications • 1 New Paradigm: designed to accelerate forecast improvement in the 3-14 day range • A metric for success should be QPF advancements

16. SCIENCE OBJECTIVE: REVOLUTIONIZE NWP PROCESS -INTEGRATED, ADAPTIVE, USER CONTROLLABLE TRADITIONAL NWP Each discipline developed on its own Disjoint steps in forecast process Little or no feedback One-way flow of information Uncertainty in process ignored NEW NWP Sub-systems developed in coordination End-to-end forecast process Strong feedback among components Two-way interaction Error/uncertainty accounted for SERVICE GOAL: IMPROVE 3-14 DAY FORECASTS

17. HPC QPF Verification1-inch Threat Score

18. HPC QPF verification vs. the modelsDay 1, 1 inch

19. HPC QPF verification Day 1, 1 inch, Jan-Dec 2003

20. Summary • Look forward to building the QPF “cool season” within USWRP with stretch goals • Service advancement depends on this focused effort • Success will depend upon a spectrum of contributions from “global” to “local”; must account for needs related to the entire forecast process • A Hydromet Test Bed will be a key component to insure success

21. Appendix

22. Science Questions – Activities - 1 • OBSERVING SYSTEM • New in-situ and remote instruments/platforms to complement existing network • Adaptive observing instruments/platforms • For large data sets • Super-obing etc prior to OR within data assimil. (Joint work with data assimilation) • Obs. error estimation (correlated/uncorrelated)

23. Science Questions – Activities - 2 • DATA ASSIMILATION • Improve techniques • Forward models, transfer codes • Thinning of data • Treatment of data with correlated errors • Advanced methods to use flow dependent covariance • 4DVAR research, e.g., continual update of error covariance • Ensemble based techniques • Treatment of model errors • Adaptive observing techniques • Quick use of targeted data (“pre-emptive” forecasting) • Methods in the presence of • Strong non-linearities • Model error • Effectiveness of targeted data in analyses/forecasts • Effect on climatological applications of data

24. Science Questions– Activities - 3 • FORECAST PROCEDURES • Initial ensemble perturbations (Joint with data assimilation) • Role of non-modal behavior • Separate model related error from initial value errors • Systematic vs. random errors • Atmospheric features most affected • Critical model features responsible for different errors • Improve model formulation to reduce errors (Coupling techniques) • Techniques to account for remaining uncertainty in ensembles (physics, etc) • Adaptive modeling and ensemble techniques

25. Science Questions – Activities - 4 • SOCIO-ECONOMIC APPLICATIONS • Probabilistic forecasting • Statistical post-processing • New procedures for intermediate and end users • Add-on costs of new THORPEX NWP process • Cost of data from multi-use satellite platforms (Joint with Observtns.) • Incremental societal/economic benefits of new NWP process • New NWP verification measure • Societal aspects of new adaptive NWP procedures • Equitable use of NWP resources, how adaptive procedures applied nationally and internationally

26. NOAA THORPEX PROGRAM OVERVIEW - DELIVERABLES DELIVERABLES New forecast techniques Observing, data assimilation, forecasting, application tools Accelerated forecast improvements Integrated, adaptive, user controllable NWP Cost effective operational system Based on cost/benefit analysis Enhanced user interface COSTS Research Grant Program Integrated program - Four sub-areas & cross-cutting activities Operational Test Facility Simulated forecast process; Database Real-time test/implementation Data transmission, Computations, Training OVERALL MEASURE OF SUCCESS: SOCIO-ECONOMIC BENEFITS MUST OUTWEIGH OPERATIONAL COSTS