Recent and Planned Updates to the NCAR Auto-Nowcast (ANC) System Thomas Saxen, Rita Roberts, Huaqing Cai, Eric Nelson, Dan Breed National Center for Atmospheric Research 5 th International Conference on Mesoscale Meteorology and Typhoon Boulder, Colorado October 31 th, 2006

Outline Intro on ANC system Addition of multiple convective regimes Predicting elevated convection Transitioning output to probabilities Future work

What is the ANC system? It’s an automated, data fusion system that weights and combines all available data sets to produce short-term 0-1 hr nowcasts of thunderstorm initiation, growth and decay. Large-Scale Environmental Information Trigger Mechanism Information Initial Signs of Development Information ANC Initiation Philosophy Stability/Moisture Outflow Bdrys/Fronts BL Convergence Growing Cu Clouds New Development Along Bdry

How does the ANC system work? 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

Convergence Sample Predictor Field Membership Function Convergence Likelihood Likelihood Fuzzy Logic Algorithm Same process is applied to multiple predictor fields. The resulting likelihood fields are then weighted and summed.

Initiation Interest Field Blue Regions - Little chance of storm development Green Regions - Moderate likelihood Red Regions - Areas of forecast initiation

Convective Regimes Some predictor fields work well in certain situations, but not so well in others. Users set the expected convective regime to use forecast logic tailored for that situation. Current regimes: –Cold front –Warm/Stationary front –Dry line –Advecting MCS –Air-mass –Mixed –No storms expected

Convective Regimes Examples Dry Line ExampleAir Mass Example White contour: Initiation Forecast Contour Bdry Characteristics CAPE Initiation Interest IR Rate of Change Initiation Interest

Elevated Convection Original ANC system focused on surface based convection. Consensus in the research community that ~ 50% of convective storms originate above the surface, based on Eta model diagnoses (Kain et al. 2003) and IHOP field experiment (Wilson and Roberts, 2005). Approach is to use similar predictor fields (CAPE, CIN, Frontal Features, etc), but look at elevated levels.

Elevated Convection Example White Contour: Verification Contour Surface Initiation InterestElevated Initiation Interest

Probabilistic Forecast Output Accounts for uncertainty in convective forecasting More information is provided in the output Needed for improved decision making Verification reflectivities (> 35 dBZ) are overlaid. Growth/Decay Component Merged with Initiation Interest Work in progress

Future Work Directions Explore use of total lightning data in ANC system Explore several statistical based forecast tuning algorithms

Thank you. Questions?