Updated Thunderstorm Probability Updated Thunderstorm Probability Forecast Guidance in Support of Forecast Guidance in Support of Gridded Model Output StatisticsGridded Model Output Statistics

NWA Annual Meeting, Cleveland, OHNWA Annual Meeting, Cleveland, OH October 16, 2006October 16, 2006

E-mail: Kathryn.Gilbert@noaa.govE-mail: Kathryn.Gilbert@noaa.gov

Current State of Ensemble MOSCurrent State of Ensemble MOS

MOS equations are applied to all 15 MOS equations are applied to all 15 members of the GFS ensemble and the members of the GFS ensemble and the operational run to create 16 text operational run to create 16 text messagesmessages• Local applications like getENS Local applications like getENS

generate summary valuesgenerate summary values The current gridded MOS is an example The current gridded MOS is an example

of a lagged ensemble. of a lagged ensemble. • Temperature, dew point, max and Temperature, dew point, max and

min temperature grids are created min temperature grids are created from two runs, weighted 2:1 from two runs, weighted 2:1

Future ensemble MOS requirements are Future ensemble MOS requirements are vaguevague

Image from PSU web site

Enhanced-Resolution MOSEnhanced-Resolution MOSSupport for the operational forecastersSupport for the operational forecasters

Two ApproachesTwo Approaches ““True” Gridded MOSTrue” Gridded MOS

• Observations and forecasts valid on fine gridObservations and forecasts valid on fine grid• Uses remotely-sensed predictand dataUses remotely-sensed predictand data

cloud-to-ground lightning datacloud-to-ground lightning data

““MOS at any point”MOS at any point”• Emphasis on high-density surface networksEmphasis on high-density surface networks• Uses high-resolution geophysical dataUses high-resolution geophysical data

Remotely-Sensed Lightning DataRemotely-Sensed Lightning Data NLDN cloud-to-ground lightning observations define a NLDN cloud-to-ground lightning observations define a

thunderstorm eventthunderstorm event• Observations are the predictandObservations are the predictand

Monthly lightning climatologies were developed from ten Monthly lightning climatologies were developed from ten years of data for 3-, 6-, 12-, and 24-h time periods, to be used years of data for 3-, 6-, 12-, and 24-h time periods, to be used as predictorsas predictors

Observed lightning data are used to Observed lightning data are used to verify the thunderstorm guidanceverify the thunderstorm guidance

Creating the Gridded Lightning Creating the Gridded Lightning Datasets from ObservationsDatasets from Observations

Strikes are summed over the appropriate time period and assigned to Strikes are summed over the appropriate time period and assigned to the center of the grid boxesthe center of the grid boxes

×××××× ××

×× ××××××××

×× ××××

××××××

= thunderstorm = no thunderstorm

Probabilities for Different Grid ResolutionsProbabilities for Different Grid Resolutions

40-km 21-24h period10% contour interval

20-km 21-24h period10% contour interval

Probabilities for Different Time PeriodsProbabilities for Different Time Periods

As the resolution increases in time and space, the magnitude of the probabilities will decrease as the likelihood of an event at an exact time and point in space approaches zero

MOS Thunderstorm Probability GuidanceMOS Thunderstorm Probability GuidanceGiven that: • The area covered by the forecast should be at least as large as the

event• Thunderstorm forecast probabilities traditionally represent an area

within 25 miles of a point, and• We don’t want the probabilities to become so small they lose

information and credibility…

The gridded MOS thunderstorm probability is defined as the probability of one or more cloud-to-ground lightning strikes in a 40-km square grid box during a given time period.

So: So: • The guidance is interpolated to the 5-km NDFD grid using bilinear The guidance is interpolated to the 5-km NDFD grid using bilinear

interpolationinterpolation• It represents the likelihood of a cloud-to-ground lightning strike 40-It represents the likelihood of a cloud-to-ground lightning strike 40-

km around each 5-km grid box, andkm around each 5-km grid box, and• Stations have the value of the 40-km grid box they are sitting in, Stations have the value of the 40-km grid box they are sitting in,

using nearest neighbor assignments, to fill in the text messagesusing nearest neighbor assignments, to fill in the text messages

Thunderstorm Equation DevelopmentThunderstorm Equation Development Equations developed from 5 years of GFS model outputEquations developed from 5 years of GFS model output All 40-km “stations” were combined into one regionAll 40-km “stations” were combined into one region

• increased sample size and eliminated boundariesincreased sample size and eliminated boundaries Separate equations were developed for 3 seasonsSeparate equations were developed for 3 seasons

• Spring: March 16 – June 30Spring: March 16 – June 30• Summer: July 1 – October 15Summer: July 1 – October 15• Cool: October 16 – March 15Cool: October 16 – March 15

3-h time periods through day 3; 6- and 12-h time periods through day 7.3-h time periods through day 3; 6- and 12-h time periods through day 7. Important PredictorsImportant Predictors

• Stability IndicesStability Indices• Convective precipitation amountConvective precipitation amount• Product of vertical velocity * relative humidityProduct of vertical velocity * relative humidity• K-index * thunderstorm relative frequencyK-index * thunderstorm relative frequency• Thunderstorm relative frequenciesThunderstorm relative frequencies

Gridded MOS Thunderstorm ProductsGridded MOS Thunderstorm Products

NDGD web-based NDGD web-based graphicsgraphics

Distributed in GRIB2 Distributed in GRIB2 formatformat

3-,6-, 12-h forecast 3-,6-, 12-h forecast periodsperiods

Available in AWIPS with Available in AWIPS with OB7.1 release, as part OB7.1 release, as part of the gridded MOS of the gridded MOS systemsystem

““Enhanced-Resolution” MOSEnhanced-Resolution” MOS ““True” gridded MOSTrue” gridded MOS

• Uses remotely-sensed data, i.e. the probability of a thunderstormUses remotely-sensed data, i.e. the probability of a thunderstorm

““MOS at any point”MOS at any point”

• Emphasis on high-density surface networks; Co-Op, buoy, mesonet, etcEmphasis on high-density surface networks; Co-Op, buoy, mesonet, etc

• Uses high-resolution geophysical dataUses high-resolution geophysical data

• Analyze forecasts on high-resolution gridAnalyze forecasts on high-resolution grid• Traditional MOS downscales the model output to specific sitesTraditional MOS downscales the model output to specific sites• Examples of weather elementsExamples of weather elements

temperaturetemperature dew point temperature dew point temperature max/min temperature max/min temperature wind speed and direction wind speed and direction relative humidityrelative humidity probability of precipitation (6- and 12-h periods)probability of precipitation (6- and 12-h periods)

Gridded MOS ObjectiveGridded MOS ObjectiveGenerate guidance sufficient for forecast initialization at WFOsGenerate guidance sufficient for forecast initialization at WFOs

Forecaster Feedback is InvaluableForecaster Feedback is InvaluableGridded MOS wind speed problemGridded MOS wind speed problem

•Strange dots

Bad “if test” in a wind post-processing subroutine created calm winds, when the direction was near 0.

•Too many calm mountain winds

A control file setting caused excessive calm winds over the mountains

20060921 1200 UTC21 hour forecast

Forecaster Feedback is InvaluableForecaster Feedback is InvaluableThank youThank you

20060921 1200 UTC21 hour forecast

20060921 1200 UTC21 hour forecast

The subroutine and control files have been fixed and implemented

SummarySummary Gridded MOS thunderstorm probabilities are valid over a 40-km area, Gridded MOS thunderstorm probabilities are valid over a 40-km area,

for each 5-km NDFD grid boxfor each 5-km NDFD grid box Gridded MOS is a work in progressGridded MOS is a work in progress

• more elements are comingmore elements are coming• improvements to current algorithms and equations expectedimprovements to current algorithms and equations expected• increased resolution from 5-km to 2.5-kmincreased resolution from 5-km to 2.5-km

User feedback is critical to define requirements and improve the User feedback is critical to define requirements and improve the productsproducts

Alaska and other OCONUS areas are in the early stages of Alaska and other OCONUS areas are in the early stages of developmentdevelopment

Link to documentation and productshttp://www.weather.gov/mdl/synop/gmos.html