evolution of warning servicesintegrated hazard information services workshop - oct 2009 greg stumpf...

Evolution of Warning ServicesIntegrated Hazard Information Services Workshop - Oct 2009

Greg StumpfCIMMSNWS-MDL

Evolution of Warning Services

Experiments in Convective Hazard Concepts of Operations,Here and Abroad


NWS Warnings, (then and) now…


One-size-fits-all polygons: “monotonic” information.

Each location under same threat for same time period

Limited Time of Arrival information (pathcasts)

No Time of Departure info beforehand

Each location is assumed 100% certainty of threat

NWS warnings are area forecasts verified by point events.

Just draw larger polygons with longer valid times to improve verification scores!

Drivers for Improvement



Forecaster cannot control motion uncertainty

Difficult to adjust to storm changes after warning issuedSVS procedure very limiting (can’t add areas)

Multiple threats in close space and time proximity are challenging

Users downstream of polygon may get zero information on upstream threat.


A B

User “A” gets many minutes lead time…

A B…while User “B” gets only 0-5 minutes

Very little overlap between adjacent warnings can lead to inequitable lead times for nearly-adjacent locations



Zero Lead Time


Reflectivity Hail Size

Zero Lead Time


Product delivery or information delivery?

Today, the NWS forecaster is encumbered by dealing with product formats, downstream legacy systems, verification, etc., which introduce non-meteorological hedge factors in warning decisions.

Instead, the warning forecaster should provide the best information it can to support decision making, but not make those decisions!

unwarned!


Storm-based warnings:April 2008 - June 2009


Future Nowcasting systems:

Blending extrapolation and NWP

Warn On Forecast with an aim to provide longer lead times.

Warnings (which are just short-term forecasts) become more uncertain with time, therefore the solution will require a probabilistic approach.

Longer lead times really means

Less uncertainty at longer forecast

periods


The meteorologist is the expert on interpreting the hazard and its uncertainty.

The meteorologist cannot anticipate everyone’s exposure and response time

How can weather hazard information be made more adaptable to those that do know their own exposure and response time?

Beyond Storm-Based Warnings:

Adaptive Warnings

Little Sioux Camp

Concrete Dome Home


How will we shape our future?

NWS is moving from a paradigm of issuing products to providing services (Don Berchoff, NWS OS&T Director).

Support the legacy now, but also be adaptable to new operational concepts and foster innovation.

"The future is not something we enter, the future is something we create." -Leonard I. Sweet

"The future is made of the same stuff as the present." -Simone Weil

"The future has already happened, it just isn't very well distributed." -William Gibson


Experimental Warning/Nowcast

Systems

Probabilistic Hazard Information (PHI)U.S. – NSSL Hazardous Weather Testbed

Auto-NowCaster (ANC)U.S. – NCAR

Thunderstorm Interactive Forecast System (TIFS)AustraliaThunderstorm Environmental Strike Probability Algorithm (THESPA)

Canadian Radar Decision Support system (CARDS)

Short-range Warning of Intense Rainfall in Localized Systems (SWIRLS)Hong Kong Observatory (HKO)

SIGnificant weather Object Oriented Nowcasting System (SIGOONS)France


Some characteristics of each system

Digital Hazard Grids

Object-based 2D threat areas

Continuously translating 2D threat areas

Human-machine mix

Uncertainty information


Digital Hazard Grids

Supports emerging products and servicesFlexibility in resolution and refresh rates

Grid layers can provide multi-dimensional infoThreat type, intensity, time of arrival/departure,uncertainty

Can be aggregated into simpler formatsSupport legacy systems/products

Multiple ways to create/modify grids:WarnGen / Drag-Me-To-Storm2D object trackingGrid editorsStorm algorithmsProbabilistic guidance from statistics/NWPHuman-machine mix

HAILWINDTORNADOLIGHTNING


NSSL Probabilistic Hazard Information (PHI)

For each storm object, the forecaster determines

the initial threat area (polygon or ellipse) at time=0, along with

the motion vector, and adds

motion uncertainty information

Parameters used to derive gridded hazard informationtranslating threat area, swath, time of arrival/departure

Each storm object’s properties are adjusted in 10-20 minute intervals to account for changes in motion and intensity.

Right now, this is done completely by the human.




Anticipate discretedevelopment alongsouth flank

Anticipateareaorientationchange

Anticipatenon-linearmotion

PHI Mock-up: Interact with current and forecast states, morphing


Warning automatically translates downstream based on storm motion until adjusted or cancelled.

Provides meaningful information about times of arrival and departure.

Removes warning from area where threat has passed.

A B

Both “A” and “B” get equitable lead time

Continuously translating threat information


Human-Machine Mix

Thunderstorm Interactive Forecast System (TIFS – Australia)Forecaster can interact with past and forecast positions to correct for deficiencies in the automated algorithms

Real-time verification system


SIGnificant weather Object Oriented Nowcasting System (SIGOONS – France)Human can correct past and forecast tracks, motion, intensity, other parameters

Human-Machine Mix


NCAR Auto-NowCaster (ANC)

Forecaster-entered boundary

Initiation

Growth and Decay

Human-Machine Mix


Uncertainty Information

Include uncertainty information on the grids

Based on existence, motion, location, evolution Integration over time results in a probabilistic swath

Probabilities can be derived from a combination of:

Human expertise (e.g., PHI)Storm-motion uncertainty (e.g., PHI) Storm morphology statistics (e.g., THESPA)Storm-type climatology statistics Nowcast and NWP ensembles (e.g., FDP-B08)

PHI

FDP-B08:TIFS/CARDS/SWIRLS

THESPA


Thunderstorm Environmental Strike Probability Algorithm (THESPA - Australia)±10 km h-1; ±30°degWhich probability envelope to use?

Depends on user, acceptable cost-loss (POD, FAR).Note – envelope is NOT a trapezoid!

. A

. B

50%

10%

Slow-moving storm

Uncertainty Information


Real-Time Testing

WMO Forecast Demonstration Projects (FDP)2000 (Sydney); 2008 (Beijing)

Nowcast systems demoed, discussed, etc.

FDP-B08: T-storm strike probability combined three algorithms (TIFS,CARDS, SWIRLS)


Real-Time Testing

NOAA Hazardous Weather Testbed (HWT)Experimental Warning Program (EWP)

Probabilistic Hazard Information (PHI) demoed


Multi-layered dissemination systems: Exploit emerging GIS and GPS and wireless technology, so we can phase out limiting legacy systems (incl. even NWR voice broadcasts!)

Adaptive warnings allow users to set their threshold criteria, or allow third-party enabling technology/systems to do this for them

For super-users: Longer lead time … greater uncertainty, TOA and TOD.

Point warnings for anyone

Geo-located cell phones and navigation systems

Facilities with long lead-time needs

Potential uses


Can issue hazard grids at probability values below expected thresholds for issuing today’s warnings.

Provide greater lead time to high risk users. Will require uncertainty and Time of Arrival/

Departure information

Seamless hazard information across all time and space scales.

Many actions/decision are hierarchical across the hazard timeline

60%

60%

40%

40%

20%

10%

10%

10%

10%

Potential uses


For each grid point in the warning, the intersection of the threat area over time provides time of arrival and time of departure information, and probabilities of the event.

A’B’

1

0

Threat Prob

Time BA

Time Of ArrivalTime Of Departure

Potential uses


Recommended actions:Move indoorsEvacuate mobile homes

Anytown

Tornado threat indexValid 10:00 pm-10:15 pm XDTLast updated: 6 minutes ago

Whatever Co.

Convert probabilities to a “Threat Level Index”.

Intersect threat GIS layer with demographic GIS layers to create tailored calls-to-action

Different calls-to-action based on combination of hazard threat level and unique (and sometimes dynamic) exposure/response times of the individual users.

Potential uses


Any high resolution grid (space and time) can be aggregated into simpler formats

Supports legacy U. S. county-based warning systems (television crawls, local and NOAA Weather radio).

Not every user needs to see the probabilities.

Potential uses


A vision?

A digital gridded weather hazard database that:Will supply hazard information seamlessly across all time and space scalesIs wholly adaptable to users and systems to support and enable their decision making

From this databaseThe NWS can provide some derived watch, warning, and advisory products for public customers (including supporting legacy capabilities). Other public and private partners can derive specific customer-centric start-of-the-art products.


How do we achieve the vision?

Emerging concepts must be vetted across many intersecting disciplines:

MeteorologyTechnologySocial ScienceHuman Factors / Ergonomics

What is the best way to balance innovation and user needs?

"If I had asked people what they wanted, they would have said faster horses." -Henry Ford


Snack on these ideas for the next

2 ½ days!

evolution of warning servicesintegrated hazard information services workshop - oct 2009 greg stumpf...

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