1. Toward Operational Convection-Allowing Ensembles over the United States
Craig Schwartz, Glen Romine,
Ryan Sobash, and Kate Fossell
The National Center for Atmospheric Research
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. NA15OAR

2. 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

3. 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

4. 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

5. 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

6. 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

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

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

9. 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

10. 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

11. 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

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

13. 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

14. 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

15. 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

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

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

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

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

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

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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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

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

34. 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

35. 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

36. Toward 1-km ensembles
Fractions skill scores over hr forecasts

37. 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

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

39. 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:

43. 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

44. 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

45. 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

46. 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

47. 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

48. 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

49. 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