Toward Operational Convection-Allowing Ensembles over the United States Craig Schwartz, Glen Romine, Ryan Sobash, and Kate Fossell The National Center for Atmospheric Research ensemble@ucar.edu How many of you know about the NCAR ensemble? And to those forecasters: how many of you have used the NCAR ensemble as part of preparing your forecasts? Are probabilities the dominant thing you look at? NCAR is sponsored by the National Science Foundation This work partially supported by NOAA Grant No. NA15OAR4590238

Real-time 3-km ensemble forecasts Since April 7, 2015, we have been producing real-time, 10-member, 48-hr ensemble forecasts 3-km horizontal grid spacing Initialized at 0000 UTC daily www.ensemble.ucar.edu

Why are we doing this work? One of the forefronts of NWP model research is how to design high-resolution ensembles Also verification and data visualization challenges Demonstrate feasibility of real-time convection-allowing ensemble forecasting over large areas The USA currently does not have an operational convection-allowing ensemble

Challenge with high-resolution ensembles How to design high-resolution ensembles? Vary just initial conditions? Configure different members with different physics or dynamics? We only vary initial and boundary conditions Single set of physics and dynamics for all members Equal likelihood among ensemble members Facilitates investigation of model deficiencies

Components of the NCAR ensemble 1) Ensemble analysis system Assimilate real observations every 6 hours with an ensemble Kalman filter (EnKF) 80 ensemble members 15-km horizontal grid spacing 2) Ensemble prediction system 10-member, 3-km ensemble forecasts 48-hr forecasts initialized at 0000 UTC WRF-ARW model

Continuously cycling EnKF Continuous cycling 6-hr WRF model forecast ens mem 1 background EnKF ens mem 1 analysis … … (Members 2-79) Observations ens mem 80 background ens mem 80 analysis 6-hr WRF model forecast

NCAR ensemble analysis domain 15-km Obs at 0000 UTC 24 May 415 x 325

Observations used in the analysis system Radiosonde Aircraft Satellite wind METAR Oklahoma MESONET 1200 UTC October 23, 2016 Marine GPSRO

EnKF-initialized 3-km ensemble forecasts Dynamically consistent initial conditions 6-hr WRF model forecast Observations Downscale to 3-km and initialize forecast ens mem 1 background EnKF ens mem 1 analysis … … (Members 2-79) Downscale to 3-km and initialize forecast ens mem 80 background ens mem 80 analysis 6-hr WRF model forecast

NCAR ensemble forecast domain 48-hr, 10-member, 3-km forecasts 15-km 3-km initial conditions from downscaled 15-km analyses Obs at 0000 UTC 24 May 3-km 1581 x 986 415 x 325

How to initialize high-resolution ensembles? Use ensemble data assimilation (NCAR way) Ensemble Kalman filter (EnKF) Use existing operational ensembles Cheap and easy but potential for mismatches Add random noise to a single field A bit ad hoc Derive perturbations from external models and add to a single field Potential for mismatches

“Snowzilla” East coast blizzard of January 22-24, 2016 Forecast uncertainty about the northern extent of heavy snow

Forecast initialized 0000 UTC 22 January Ensemble mean 24-hr accumulated snow between 0000 UTC 23 – 0000 UTC 24 January 24-48-hr forecast inches

Forecast initialized 1200 UTC 22 January Ensemble mean 24-hr accumulated snow between 0000 UTC 23 – 0000 UTC 24 January 12-36-hr forecast inches

Forecast initialized 0000 UTC 23 January Ensemble mean 24-hr accumulated snow between 0000 UTC 23 – 0000 UTC 24 January 0-24-hr forecast inches

“Plume diagram” for New York City Forecast initialized 0000 UTC 22 January

“Plume diagram” for New York City Forecast initialized 0000 UTC 23 January

Forecast initialized 0000 UTC 22 January 48-hr accumulated snow between 0000 UTC 22 – 0000 UTC 24 January

Probabilities of 48-hr snowfall > 1 foot within 25 miles of a point Initialized 0000 UTC 22 January Initialized 0000 UTC 23 January Probability

Probabilities of 48-hr snowfall > 2 feet within 25 miles of a point Initialized 0000 UTC 22 January Initialized 0000 UTC 23 January Probability

Simulated reflectivity > 40 dBz Error initializing convection 6-hr forecast Initialized 0000 UTC 22 January

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period May 25, 2015 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period June 20, 2015 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period June 23, 2015 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period Feb. 23, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period Feb. 24, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period July 8, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period July 18, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period July 25, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

Severe weather guidance Smoothed probabilities of the union of hail > 1 inch, wind exceeding 25 m/s, and 2-5-km updraft helicity > 75 m2/s2 within 25 miles of a point over a 24-hr period Aug. 13, 2016 Note probability scales correspond roughly with SPC thresholds. Do a 6-panel. Probability

NCAR ensemble bias Aggregate biases over 451 forecasts 0.25 mm/hr Obs at 0000 UTC 24 May 5.0 mm/hr 10.0 mm/hr 20.0 mm/hr

NCAR ensemble ROC areas ROC areas for 24-hr forecasts of 1-hr accumulated precipitation aggregated over 451 forecasts Obs at 0000 UTC 24 May

NCAR ensemble calibration Attributes diagrams for 24-hr forecasts of 1-hr accumulated precipitation aggregated over 451 forecasts Obs at 0000 UTC 24 May

Seasonal forecast skill 24-hr fractions skill scores (50-km radius of influence) between June 15, 2015 – June 15, 2016 0.25 mm/hr 1.0 mm/hr Date Date

Other research activates Compare EnKF-initialized ensemble forecasts with other, more traditional, methods of initializing high-resolution ensemble forecasts Objective verification against National Weather Service watches and warnings Ensemble sensitivity analysis e.g., relate Snowzilla displacement errors to the initial conditions

Toward 1-km ensembles Fractions skill scores over 32 1-12-hr forecasts

Future work 3-km analysis on current 3-km forecast grid More frequent analyses (at least hourly) Assimilate radar, satellite, lightning observations Requires substantially more computational resources Post-processing and interpretation New tools to interpret predictions of hazards Calibration

AMS tweeted about our paper Documentation Paper in Weather and Forecasting describes the system (Schwartz et al. 2015) AMS tweeted about our paper

Summary NCAR ensemble represents a glimpse of future operational systems We have demonstrated convection-allowing ensembles are operationally feasible over the U.S. Contact us if you’d like to collaborate or want real-time data: ensemble@ucar.edu

Surrogates for tornado forecasting Observed tornadoes 2-5-km AGL updraft helicity 0-3-km AGL updraft helicity 1-km AGL relative vorticity Sobash et al. (2016), Wea. Forecasting

Why ensemble forecasts are desirable Quantification of uncertainty Naturally produces probabilities! Allows forecasters to forecast their “true beliefs” Allows users to make decisions based on expected value and cost-loss scenarios Forecasts combining information across all members are usually more skillful than single deterministic forecasts

NCAR ensemble forecast domain 15-km 3-km initial conditions from downscaled 15-km analyses Obs at 0000 UTC 24 May 3-km 1581 x 986 415 x 325

NCAR ensemble forecast domain 15-km 3-km initial conditions from true 3-km analyses Obs at 0000 UTC 24 May 3-km 1581 x 986 415 x 325

Mean analysis increments August 2015 mean analysis increments at 0000 UTC Lowest model level temperature (K) Lowest model level water vapor (g/kg) Pattern not geographically uniform

Mean analysis increments December 2015 mean analysis increments at 0000 UTC Lowest model level temperature (K) Lowest model level water vapor (g/kg) Different characteristics compared to summer

Why ensembles vs. deterministic forecasts? These forecasts have proven quite popular with the broader community. Thanks to google analytics, we are able to track our site visits and find we have a consistent user base that spans across the country. Top user is NOAA, but we also have a number of private companies, NCAR, weather weenies, and university users. In addition to our web site, we also distribute binary data that goes to a number of additional government, university and private entities. You’ll note there was a recent spike in use in late January, that was the recent crippling snowstorm that impacted the Mid-Atlantic. Let’s take a look at some of the products from that event. Ensemble probabilistic forecast skill exceeds performance of deterministic forecasts from the same prediction system