5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

National Scale Probabilistic Storm Forecasting for Aviation Planning

Talk Focus - Storm Coverage

Presenter: Dr James O. Pinto, NCAR/RALCollaborators: Rasmussen, Steiner, Megenhardt, Rehak, Dixon, Phillips

Acknowledgements : FAA AWRP

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Playbook at 1200 UTC

Need for Reliable Storm Nowcasts of 8+ hrs for Strategic Planning

Fcst valid : 2040 – 0240 UTC

6 hr Probability Forecast

Playbook: Revised at 2000 UTC

Verification

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Storm Characteristics Determine Impact of Air Traffic

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Outline

• Motivation– Need for probability of storm orientation, organization and

coverage (e.g., storm permeability)

• Current Probabilistic Storm Forecast Systems

• Current Research – Storm Coverage Forecasts– Assess explicit model prediction of storm coverage and echo

top heights– Use model and obs climatologies to determine relationship

between storm coverage and forecast valid time, environmental conditions, location.

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Outline

• Motivation– Need for probability of storm orientation, organization and

coverage (IOW: storm permeability)

• Current Probabilistic Storm Forecast Systems

• Current Research – Storm Coverage Forecasts– Assess explicit model prediction of storm coverage and echo

top heights– Use model and obs climatologies to determine relationship

between storm coverage and forecast valid time, environmental conditions, location.

Extrapolation

Deterministic Forecasts of Precipitation - Extrap

12 13 14 15 16 17 18 UTC

1 hrfcst

3 hrfcst

6 hrfcst

Successive fcsts valid at same time.

Verification

1 h

P

2 h

P

Probabilistic Forecast of Convective Hazard

Probabilities may be interpreted as:

-likelihood of storms exceeding 35 dbz at a given time and location

-the coverage of storms exceeding 35 dbz (if reliable).

Probabilities determined via spatial filter and a VIL threshold.

Spatial filter increases with fcst lead time (after Germann and Zawadzki 2004)

Probabilities also influenced by observed trends, environmental conditions and climo.

NCWF2 Hazard Detection with Probabilistic Fcsts

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Probabilistic Forecasts Systems

Probabilities based on:

– Spatial coverage of convective precip predicted by the RUC-20 model

– 3-member time-lagged ensemble

– Square filter of 180 km

– Precipitation rate threshold for convection (1-2 mm/hr)

– Tuned using 40 km truth data set

P.

RUC Convective Prob. Forecast

12 13 14 15 16 17 18 19 20 21 UTC9 hrfcst

7 hrfcst

Successive fcsts valid at same time.

8 hrfcst } 3-member ensemble valid at 21 UTC

7 hr fcst Valid: 21 UTC

Verification

Comparison with Operational 2 hour TSTM Fcst Products

From Seseke et al. 2006 QA ReportNOAA/Earth System Research Lab

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Outline

• Motivation– Need for probability of storm orientation, organization and

coverage (IOW: storm permeability)

• Current Probabilistic Storm Forecast Systems

• Current Research – Storm Coverage Forecasts– Assess explicit model prediction of storm coverage and echo

top heights– Use model and obs climatologies to determine relationship

between storm coverage and forecast valid time, environmental conditions, location.

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Methodology for Improving Storm Coverage Fcsts

• Storm-resolving forecasts using WRF• Compare model and obs distribution of storm

coverages (regionally dependent)– Focus on Southeastern US where scattered storms common– Assess predictability of storm coverage for each region as a

function of environmental conditions, time of day, etc.

• Verification – standard skill scores to assess reliability – Need for more descriptive skill scores such as those available

in MODE (object-based verification).• E.g. storm spacing

WRF Model Reflectivity

Deterministic Forecasts of Convection

Verification – WSI Mosaic

Successive fcsts valid at same time.– Storm-resolving realtime fcsts run in

collab. with Wang and Weismann

– WSM Microphysics, MYJ PBL, Noah LSM

– BCs: NAM – 40 km grid 212

– No Data Assimilation

– Run Jun/Jul 2005 (0Z) & 2006 (00,12 Z)

REPLACE – July 19th

00 ……12 13 14 15 16 17 18 19 20 UTC

8 hrfcst

20 hrfcst

Case Study- 2006 July 19

WRF-ARW (4km) – 20hr fcstWRF-ARW (4km) – 08hr fcst

WRF-ARW (4km) – 20hr fcstWRF-ARW (4km) – 08hr fcst

WRF vs WSI Coverages

Deterministic Forecasts of Storm Coverage

Verification – WSI Mosaic

00 ……12 13 14 15 16 17 18 19 20 UTC

8 hrfcst

20 hrfcst

Successive fcsts valid at same time. – Threshold = 35 dBZ

– Impressive accuracy of timing and location of max coverage areas

– Coverage forecast improves as fcst length decreases

Case Study- 2006 July 19

model

obs

WSI Refl - 2000 UTC

Titan Storm Detections – WSI Reflectivity

– WSI reflectivity mosaic from WSR-88D radar

– Degraded to 4 km using spatial filter

– 35 dBZ and 75 km2 thresholds

r =100 km

Storm Spacing – WRF Reflectivity (20 hr fcst)

– WRF reflectivity – max in column from 00 UTC run

– 35 dBZ and 75 km2 thresholds

100 km

Update with WRF imager =100 km

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Conclusions

•User needs (e.g., aviation planning) drive the system requirements

•Likelihood of storm at a given location not enough info for users in decision making

•Need for PDF expressing likelihood of coverages and joint PDFs of coverage / echo top likelihood.

•Current technology in predicting storm coverages have limited reliability.

•Convection resolving simulations may offer hope in predicting storm coverages and spacing.

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

-END-

NRC Report on Weather Forecasting Accuracy for FAA Traffic Flow Management

“Because accurate deterministic 2- to 6-hour forecasts are not available, it is necessary to develop probabilistic forecasts that can readily be used by both humans and automated air traffic management decision support tools.”

NRC Report, 2003

NCWF2 Convective Hazard Detection (NCWD)

Unisys VIL Vaisala CG Ltg

Unisys Echo Tops

Data Feeds

Unisys VILVIL (Stratiform areas blue) VIL (Stratiform Removed)VIL (Echo Tops > 15 kft contoured)VIL (Echo > 15 kft removed)Hazard Detection (filtered VIL + Ltg)

Convective Hazard Detection (NCWD)

Inputs: Unisys VIL & Echo Tops, NLDN C-to-G Ltg

Steps to produce NCWD

1) Stratiform Filter (Steiner et al. 1995)

2) Echo tops Filter (remove echo < 15 Kft)

3) Combine with Lightning

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

0 1 2 3 4 5 6 Forecast Length, hours

.2

.4

.6

.8

1.0

Accuracy of Rainfall Nowcasts

>2 mm/h

Extrapolation

Goal - idealized

NWP(CSI)

Current Skill of Nowcasting Technologies

Forecast Skill

5th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006

Algorithm for Blending Probabilistic Forecasts (e.g., 4 hr forecast)

ProbabilisticExtrapolation

Fcsts

RUC Probabilistic ConvectionForecasts

Frontal Interest

Climato-logical Interest

Thermo-dynamic

Mask

Merged Forecast ** Amenable to Forecaster Modification

StatisticalPerformance

Weights

Preprocessing

Blending