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National Weather Service
EXPLORING THE USE OF EXPLORING THE USE OF CONVECTIVE ALLOWING GUIDANCE CONVECTIVE ALLOWING GUIDANCE
TO IMPROVE WARM SEASON TO IMPROVE WARM SEASON QUANTITATIVE PRECIPITATION QUANTITATIVE PRECIPITATION
FORECASTSFORECASTS
THE 2010 SPRING EXPERIMENTTHE 2010 SPRING EXPERIMENT
Bruce Sullivan, Faye Barthold, Richard Bann, Mike Bodner, David Novak, and Robert
OravecHydrometeorological Predication Center
Camp Springs, MD
National Weather Service
MotivationMotivation
HPC Monthly 1.00" Threat Score (June 2005 - March 2010)
0
0.1
0.2
0.3
0.4
0.5
0.6
Jun-0
5Oct Feb
Jun-0
6Oct Feb
Jun-0
7Oct Feb
Jun-0
8Oct Feb
Jun-0
9Oct Feb
•Typically a warm-season phenomenon
•Flash flooding is a leading cause of weather-related deaths in the U.S. (~130 deaths annually)
•Warm-season QPF is difficult
National Weather Service
Warm Season Forecasting ChallengesWarm Season Forecasting Challenges• Model initialization errors—limited observations on
convective scales• Mesoscale boundaries often dominate• Mishandling of MCVs• Model biases• Convection is parameterized in operational models
- Erroneous convective feedback- SREF not calibrated
0.50” in 6h @ F24
Perfec
t
SREF
National Weather Service
2010 Spring Experiment2010 Spring Experiment• GOAL: Explore use of convection-allowing
models (~4 km grid spacing)• 3 components (Severe, Aviation, QPF)• 5 week program (May 17- June 18)• Participants included researchers,
academia, operational forecasters, students• Rotation thru desks• Facilitator at each desk
National Weather Service
Models used in Spring ExperimentModels used in Spring Experiment
Experimental QPF forecasts out to 30 h
Provider Model Delta X Notes LabelCAPS WRF-ARPS
26 member ensemble
4 km Multi-model, multi-physics, multi-IC ensemble system with radar assimilation
Storm scale ensemble forecast (SSEF)
CAPS WRF-ARW 1 km 1 km resolution CAPS 1 km
NCAR WRF-ARW 3 km RUC ICs and GFS LBCs NCAR
NSSL WRF-ARW 4 km NAM ICs and LBCs NSSL
NCEP-EMC WRF-NMM 4 km NAM ICs and LBCs EMC-NMM
NCEP-EMC WRF-ARW 4 km NAM ICs and LBCs EMC-ARW
National Weather Service
The 2010 Spring ExperimentThe 2010 Spring ExperimentQPF Objective/GoalsQPF Objective/Goals
• Document strengths and weaknesses of high res QPF forecasts
• Determine appropriate ways to use operational mesoscale and experimental CAMS/SSEF models in a complementary manner
• Explore creation of probabilistic QPF products
Simply put, do the high res models add value to
the warm season forecast problem?
National Weather Service
Daily QPF ScheduleDaily QPF Schedule• Subjective verification of previous days forecast
• Synoptic overview• Produce experimental 6 hr probabilistic QPF
- .50” and 1” thresholds- Forecasts valid 18-00Z and 00-06Z
• Subjective evaluation of previous days experimental model guidance
• Afternoon briefing and discussion of daily forecasts
and evaluation activities
National Weather Service
Experimental Ensemble ProductsExperimental Ensemble Products
• Probability Matched Mean• Max QPF (based on 4km SSEF members)
SSEF MEANPROB. MATCHED
MEAN MAX QPF
National Weather Service
Experimental Ensemble ProductsExperimental Ensemble Products• Neighborhood Probabilities
-probability of event within 80 km of a point
SSEF PROB NEPROB
National Weather Service
Examples where Examples where Convection Allowing Convection Allowing
Deterministic Forecasts Deterministic Forecasts Improve upon Convective Improve upon Convective
Parameterized ModelsParameterized Models
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 11 June 2010
6hr QPE GFS 35 KM
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 11 June 2010
6hr QPE ECMWF 16 KM
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 11 June 2010
6hr QPE NAM 12 KM
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 11 June 2010
6hr QPE NSSL 4KM
National Weather Service
CASE 2CASE 2• 24 h forecast of 6 hr QPF valid 00z 21 May
2010
6hr QPE NAM12
National Weather Service
CASE 2CASE 2• 24 h forecast of 6 hr QPF valid 00z 21 May
2010
6hr QPE NSSL-ARW 4KM
National Weather Service
CASE 2CASE 2• 24 h forecast of 6 hr QPF valid 00z 21 May
2010
6hr QPE NCEP-ARW 4KM
National Weather Service
Examples where Storm Scale Examples where Storm Scale Ensemble Improves upon Ensemble Improves upon SREF Ensemble ForecastsSREF Ensemble Forecasts
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 2 June 2010
6hr QPE SREF MEAN 32 KM
National Weather Service
CASE 1CASE 1
• 30 h forecast of 6 hr QPF valid 06z 2 June 2010
6hr QPE SSEF MEAN 4 KM
SSEF CORRECTLY ADJUSTS MCS AN ENTIRE STATE SOUTH
National Weather Service
CASE 2CASE 2• 24 h forecast of 6 hr QPF valid 00z 21May
2010
6hr QPE SREF MEAN 32 KM
National Weather Service
CASE 2CASE 2
• 24 h forecast of 6 hr QPF valid 00z 21May 2010
6hr QPE SSEF MEAN 4 KM
SSEF has correct areas of enhanced precipitation
National Weather Service
Examples where Examples where Convection Allowing Convection Allowing
Deterministic Forecasts Deterministic Forecasts Degrade NAMDegrade NAM
National Weather Service
CASE 1CASE 1
• 24 h forecast of 6 hr QPF valid 00z 2 June 2010
6hr QPE NAM12 KM
National Weather Service
CASE 1CASE 1
• 24 h forecast of 6 hr QPF valid 00z 2 June 2010
6hr QPE NCEP-ARW 4 km
National Weather Service
CASE 1CASE 1
• 24 h forecast of 6 hr QPF valid 00z 2 June 2010
6hr QPE SPC-NMM 4 KM
CAM runs too far south
National Weather Service
Example of Example of NMM High BiasNMM High Bias
National Weather Service
CASE 1CASE 1
• 24 h forecast of 6 hr QPF valid 00z 21 May 2010
6hr QPE NAM-12
National Weather Service
CASE 1CASE 1
• 24 h forecast of 6 hr QPF valid 00z 21 May 2010
6hr QPE SPC-NMM
4 INCHES IN 6 HRS!
National Weather Service
Overall ResultsOverall Results
National Weather Service
RESULTSRESULTS2010 HWT Spring Experiment
Percentage of Responses Indicating High Resolution Models Provided Improved Guidance
26/40
24/4214/28
11/2813/42 9/30
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
SSEF NSSLWRF-ARW
CAPSARW
NCEPHRW-ARW
SPCWRF NCARARW
Model
Per
cent
age
SSEF NSSL CAPS 1 km
EMC ARW
EMC NMM
NCAR
National Weather Service
RESULTS (cont)RESULTS (cont)2010 HWT Spring Experiment
Percentage of Responses Indicating High Resolution Models Provided Worse Guidance
18/4212/30
7/287/287/42
3/40
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
SSEF NSSLWRF-ARW
CAPSARW
NCEPHRW-ARW
NCARARW
SPCWRF
Model
Per
cent
age
SSEF NSSL CAPS 1 km
EMC ARW
EMC NMM
NCAR
National Weather Service
Results (cont)Results (cont)Post processed guidance (CAPS ensemble)Post processed guidance (CAPS ensemble)• Ensemble mean—useful, provided a realistic depiction of
amounts and coverage
• Probability matched mean—question about validity of using this technique on a national scale
-Recommendation: recalculate using a regional scheme
• Neighborhood probabilities—probabilities often too high and coverage too broad
-Recommendation: recalculate using different smoothing parameters
• Ensemble maximum precipitation—not useful, values too high
National Weather Service
LIMITATIONS/CHALLENGESLIMITATIONS/CHALLENGES
• Model run time is long• Slow to load on operational workstations• Still have placement/amplitude
errors/failures• Experiment did not cover CONUS• How do we get the data to operations?• Can forecasters issue reliable probability
forecasts given current time and staffing constraints?
National Weather Service
SUMMARYSUMMARY• Although certainly not perfect, convection-
allowing model guidance is useful and can improve warm season QPF- CAPS ensemble particularly impressive
• Further investigation needed to determine best way to incorporate guidance into the forecast process