1. Nowcasting Convective Storms for Aviation in NCAR/RAL Convective Weather Group Cai Huaqing National Center for Atmospheric Research Boulder, CO, USA

2. Outline Very-short term storm forecast (0-2 hr) ---- NCAR Auto-Nowcaster Short-term storm forecast (0-8 hr) ---- FAA CoSPA (Consolidated Storm Prediction for Aviation) Very-short term storm forecast over the ocean (Oceanic Convective Diagnosis and Nowcsting

3. Why We Still Need Nowcasting?

4. Detection and extrapolation of surface convergence boundaries …. ….that trigger thunderstorm initiation and impact storm evolution. The Auto-nowcaster System is unique in its ability to provide nowcasts of storm initiation by…..

5. Weather Forecast Office Washington DC Sydney Australia Forecast Office U. S. Army White Sands Missile Range Central U. S. for the FAA Where has the Auto-nowcaster been demonstrated ? Has being transferred to: Bureau Meteorology Beijing China U.S National Weather Service – Dallas Weather Forecast Office AWIPS

6. Data Sets Radar WSR-88D Satellite Mesonet Profiler Sounding Numerical Model Lightning Analysis Algorithms Predictor Fields Forecaster Input Fuzzy Logic Algorithm - Membership functions - weights - Combined likelihood field Final Prediction Flow Chart for the Auto-Nowcaster System

7. Predictor Fields Large-Scale Environment B-L characteristics Satellite Cloud Typing Boundary characteristics Cumulus development Storm motion and trends

8. Example of Auto-Nowcaster Initiation Forecast 1 hour forecastVerification Initiation nowcasts extrapolation nowcasts

9. CoSPA 0-8 hr blended forecasting system developed by MIT/LL, NOAA GSD and NCAR. It provides VIL and echo top forecasts for Federal Aviation Administration. It uses Hrrr (High resolution rapid refresh) model developed by NOAA GSD. NCAR is responsible for blending the extrapolated forecast provided by MIT/LL and Hrrr forecasts produced by NOAA GSD.

10. CoSPA Functional/Data Flow Slide from Depree et al. 2009

11. Examples of CoSPA Forecasts

12. Forecasting Convection Over the Ocean Why we care storms over the ocean? Diagnosis of oceanic convection Nowcasting of oceanic convection Uplink weather information into the cockpit

13. Air France 447 (0145 UTC 1 June 2009) The wide-area view provided by real-time experimental Global Convection/Turbulence uplinks may have improved pilot situational awareness (approx.) Last verbal contact, 0133 UTC (approx.) Last ACARS message, 0214 UTC (approx.) Last verbal contact, 0133 UTC (approx.) Last ACARS message, 0214 UTC Longwave IR (0145 UTC) Cloud Top Height (0145 UTC) Convection Diagnosis Oceanic (CDO) 0145 UTC + + Motivation : Air France 447

14. “Wx Ahead” Uplink Message valid 0130 UTC 1 June 2009 /EXP CLOUD TOP FI AF447/AN NXXXAF 01 Jun 09 -- '/' Cloud tops 30,000 to 40,000 ft//////CCC///// 'C' Cloud tops above 40,000 ft///////////CC///// *4.0N,30.0W///////// *////////C////////// //*//CC///CCC///////// ///*CCCC/C/CC////////// ////*CCCCCCC//C///////// ///CC*CCCCC///CC//////// ///CCC*CCCCC///////////// //CCCCC*CCCC////////////// //CCCCCCC*CCC////////////// /CCCCCCCCC*CCC///// / //CCCCCCCCCC*CC///// // /// //CCCCCCCCCCC*C///////// ////// /////CCCCCCCCCC*C// // // ////// //////CCCCCCCC//*/ // / ////// CC//////CCCCCCC//* ///////// CCC////////////// * ///////// /C//////////// *1.3N,31.4W //// /////// */ *// / /*/// // /*/// / /*// * // * /// * // // * //// * ///// * ////// * ///// /// * /// Pos Rpt / // * / 0133 // X 1.4S,32.8W // Valid for // / 0130-0200z // Pilot feedback at url: http://[site deleted] Graphical view (EFB concept)Text-based view for ACARS printer 30-39Kft >40Kft /=30-39Kft C=>40Kft

15. Oceanic Diagnosis and Nowcasting System Convective Diagnosis Oceanic (CDO) identifies convective cells CDO Interest CDO Binary Product Convective Nowcasting Oceanic (CNO-Titan) makes 1-hr and 2-hr nowcasts of storm location using an object tracker (Titan) CNO- Titan Nowcast CNO-Gridded produces gridded nowcasts that will more closely resemble storm structures CNO- Gridded Nowcast CNO-RF Random Forest Nowcast CNO-RF utilizes environmental and model-based inputs to better predict storm initiation and decay [Cai et al. (2009)] CTopCClassGCD With Growth/Decay Without Growth/Decay

16. CNO Based on TITAN (Dixon and Wiener, 1993) TITAN for Radar Data An Example of 1 Hr CNO-TITAN *1 hr nowcast of CDO valid at 1315 UTC on August 19, 2007 using TITAN technique is shown on the right; red lines on the right represent CDO = 2.5 verification. *Advantages of TITAN: computationally efficient; capability of addressing growth/decay. *Disadvantages of TITAN: polygons can only roughly represent storm shapes; tends to over-forecasting

17. CNO Based on Modified TITAN---- Gridded Forecast An Example of 1 Hr CNO-Gridded Forecast TITAN Motion Vectors at t 0 Gridded 0 hr TITAN Motion Vectors Temporal & Spatial Smoothing 15-60 min Motion Vectors 15-60 min Forecasts by Advecting Original Satellite Data at t 0 Gridded 1 hr TITAN Motion Vectors Gridded 2 hr TITAN Motion Vectors Merged with GFS Winds Closest in Time Temporal & Spatial Smoothing Temporal & Spatial Smoothing 75-120 min Motion Vectors 135-180 min Motion Vectors 75-120 min Forecasts by Advecting 60 min Nowcasts 135-180 min Forecasts by Advecting 120 min Nowcasts Merged with GFS Winds Closest in Time 1-3 Hr CNO-Gridded Forecast Flow Chart *Advantages of CNO-Gridded: realistic looking storms; low bias. *Disadvantages of CNO-Gridded: could be computationally expensive; no explicit growth/decay capability

18. CNO Based on Random Forest Statistical Analysis and Data Fusion The random forest technique produces an ensemble of decision trees from labeled training instances –during training, RF generates estimates of predictor importance –RF trees “vote” on classification of new data points, comprising a nonlinear empirical model that provides both deterministic predictions and probabilistic information Vote: 1 => 40 votes for “0”, 60 votes for “1”; consensus category “1” Data pt. Tree 1 Vote: 0 Data pt. Tree 2 Vote: 0 Data pt. Tree 3 Vote: 1 Data pt. Tree 4 Vote: 0 Data pt. Tree 100 … *Slide courtesy of John Williams and Dave Ahijevych

19. An Example of CNO- RF Forecast Compared with CNO- TITAN ( 1 hr) *1 hr forecasts valid at 1315 UTC on August 19, 2007 for both techniques; Red lines represent CDO = 2.5 verification *Advantages of random forest technique: more realistic looking storms; taking into account of storm environment to address storm growth/decay. *As a relatively new, novel technique for nowcasting, its potential needs to be fully explored CNO Hurricane Dean A B C D A B C D CNO-RF CNO-TITAN

20. Statistical Evaluation of the Three Nowcasting Techniques CSIBIAS 5 days of data from Aug 19-23, 2007 over the Gulf of Mexico domain are used to calculate the statistics with a grid size of ~ 5 km and CDO threshold of 2.5 All three techniques show skill over persistence RF and gridded forecast perform best at 1 hr lead time TITAN is the best at 2-3 hr lead time Gridded forecast is the best for 4-6 hr lead time

21. Examples of 1 hr Gridded Forecast over the Gulf of Mexico Domain * White lines are CDO=2.5 verification, satellite data available every 30 min A B C D Issue time: 1215 UTC 2009/09/05 Valid time: 1315 UTC 2009/09/05 1 HR

22. Examples of 3 hr Gridded Forecast over the Gulf of Mexico Domain *White lines are CDO=2.5 verification, satellite data available every 30 min A B C DIssue time: 1215 UTC 2009/09/05 Valid time: 1515 UTC 2009/09/05 3 HR

23. Examples of 6 hr Gridded Forecast over the Gulf of Mexico Domain *White lines are CDO=2.5 verification, satellite data available every 30 min A B C DIssue time: 1215 UTC 2009/09/05 Valid time: 1815 UTC 2009/09/05 6 HR

24. Summary Statistics of CNO-Gridded Forecasts 30 days of data from Sep 1-30, 2009 over the Gulf of Mexico domain are used to calculate the statistics with a grid size of ~ 5 km and CDO threshold of 2.5 The results showed here could serve as benchmark performance of extrapolation-based nowcasting techniques for oceanic convection Similar verification for model forecasts need to be done so that a comparison of convective forecasting skills between model and extrapolation can be obtained The black squares are statistics from Aug 19-22, 2007 What are the GFS model scores for oceanic convection???

25. Summary Multiple short-term convective forecasting products, both over land and over ocean, are being researched, developed and tested at NCAR/RAL for various agencies such as FAA, NOAA and NASA. Potential collaborations in the nowcasting areas would be beneficial to all participants.