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Hydrometeorological Predication Center

Published byBenjamin Robertson Modified over 6 years ago

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Presentation on theme: "Hydrometeorological Predication Center"— Presentation transcript:

1 Hydrometeorological Predication Center
EXPLORING THE USE OF CONVECTIVE ALLOWING GUIDANCE TO IMPROVE WARM SEASON QUANTITATIVE PRECIPITATION FORECASTS THE 2010 SPRING EXPERIMENT Bruce Sullivan, Faye Barthold, Richard Bann, Mike Bodner, David Novak, and Robert Oravec Hydrometeorological Predication Center Camp Springs, MD

2 Motivation Flash flooding is a leading cause of weather-related deaths in the U.S. (~130 deaths annually) Flash flooding is often associated with convection. Atlanta: Sept. 21, 2009

3 MIN DURING SUMMER MONTHS
Motivation 14% 22% MIN DURING SUMMER MONTHS 3

4 QPF Desk 6-h QPF to 72 h Graphical and gridded QPF Discussion
HPC Most likely areal-averaged QPF Categorical probability of exceeding flash flood guidance (Out to Day 3)

5 Warm Season Forecasting Challenges
Model initialization errors—limited observations on convective scales Mesoscale boundaries often dominate Model biases Convection is parameterized in most operational models Precip bulls-eyes Low bias at high thresholds SREF not calibrated 0.50” in F24 Perfect SREF

6 2010 Spring Experiment Intro
3 components (Severe, Aviation, QPF) -explore use of hi-res convective allowing models 5 week program (May 17- June 18) Participants included researchers, academia, operational forecasts, students Rotation thru desks Facilitator at each desk

7 Models used in Spring Experiment
Experimental qpf forecasts limited to 30 hrs

8 The 2010 Spring Experiment Objective/Goals
Explore utility of 00z high res convective allowing models and SSEF system to provide useful guidance in the creation of experimental probabilistic 6-hr qpf products Document strength and weaknesses of high res qpf forecasts and determine appropriate ways to use operational mesoscale and experimental CAMS/SSEF models in a complementary manner Using experimental and operational data sets, determine if forecasters can create reliable probabilistic QPF products for .50” and 1” thresholds valid for the 18-00z and 00-06z periods encompassing the diurnal cycle Share knowledge learned between HWT and HPC’s HMT Simply put, do the high res models add value to the warm season forecast problem.

9 Daily QPF Schedule Subjective verification of previous days forecast
Synoptic overview - area of common interest selected Produce experimental 6 hr probabilistic qpfs Subjective evaluation of previous days experimental model guidance Afternoon briefing and discussion of daily forecasts and evaluation activities

10 Experimental Products
Probability Matched Mean Max QPF (based on 4km SSEF members) PROB. MATCHED MEAN SSEF MEAN MAX QPF

11 Experimental Products
Neighborhood Probabilities -expanded probability areas due to inherent predictability issues NEPROB SSEF PROB

12 Examples where Convection Allowing Deterministic Forecasts Improve upon Convective Parameterized Models

13 CASE 1 30 hr 6 hr qpf forecast valid 06z June GFS 6hr QPE

14 CASE 1 30 hr 6 hr qpf forecast valid 06z June ECMWF 6hr QPE

15 CASE 1 30 hr 6 hr qpf forecast valid 06z June NAM 6hr QPE

16 CASE 1 30 hr 6 hr qpf forecast valid 06z June NSSL 4KM 6hr QPE

17 CASE 2 24 hr 6 hr qpf forecast valid 00z May NAM12 6hr QPE

18 CASE 2 24 hr 6 hr qpf forecast valid 00z May NSSL-ARW 6hr QPE

19 CASE 2 24 hr 6 hr qpf forecast valid 00z May NCEP-ARW 6hr QPE

20 Examples where Storm Scale Ensemble Improves upon SREF Ensemble Forecasts

21 CASE 1 30 hr 6 hr qpf forecast valid 06z June SREF MEAN 6hr QPE

22 SSEF CORRECTLY ADJUSTS MCS AN ENTIRE STATE SOUTH
CASE 1 30 hr 6 hr qpf forecast valid 06z June SSEF CORRECTLY ADJUSTS MCS AN ENTIRE STATE SOUTH SSEF MEAN 6hr QPE

23 CASE 2 24 hr 6 hr qpf forecast valid 00z May SREF MEAN 6hr QPE

24 SSEF has correct areas of enhanced precipitation
CASE 2 24 hr 6 hr qpf forecast valid 00z May SSEF has correct areas of enhanced precipitation SSEF MEAN 6hr QPE

25 Examples where Convection Allowing Deterministic Forecasts Degrade NAM
25

26 CASE 1 24 hr 6 hr qpf forecast valid 00z June NAM12 6hr QPE

27 CASE 1 24 hr 6 hr qpf forecast valid 00z June NCEP-ARW 6hr QPE

28 CASE 1 24 hr 6 hr qpf forecast valid 00z June 2 2010 SPC-NMM 6hr QPE
CAM runs too far south SPC-NMM 6hr QPE

29 Examples of NMM High Bias
29

30 CASE 1 24 hr 6 hr qpf forecast valid 00z May NAM-12 6hr QPE

31 CASE 1 24 hr 6 hr qpf forecast valid 00z May 212010 SPC-NMM 6hr QPE
4 INCHES IN 6 HRS! SPC-NMM 6hr QPE

32 CASE 2 30 hr 6 hr qpf forecast valid 06z June NAM-12 6hr QPE

33 CASE 2 30 hr 6 hr qpf forecast valid 06z June 5 2010 SPC-NMM 6hr QPE
8 INCHES IN 6 HRS! SPC-NMM 6hr QPE

34 RESULTS

35 RESULTS (cont)

36 LIMITATIONS/CHALLENGES
Model run time is long Slow to load Model qpfs still have placement/amplitude errors Experiment did not cover Conus How do we get the data to operations? How best way to incorporate probability forecasts with current time/staffing constraints?

37 SUMMARY Convection allowing model guidance is useful and can improve warm season qpf - precip placement/biases still exist - CAPS ensemble particularly impressive Need further experiments to determine best way to incorporate CAM guidance into the forecast process

38 FUTURE PLANS Add afternoon activities to QPF component
Add 06z-12z forecast period Investigate access to NSSL WRF-ARW at HPC Investigate utility of “poor mans” ensemble made up of available CAM guidance until suitable SSEF model becomes operationally viable

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