The challenge to verify operational weather warnings
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The challenge to verify operational weather warnings. Tanja Weusthoff and Marco Arpagaus EMS, 14.09.2011. MeteoSwiss official warnings (24h acc. precip.) for 4th September 2011. 152 warning regions. Introduction. 5 level. 8 different hazards.

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The challenge to verify operational weather warnings

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The challenge to verify operational weather warnings

Tanja Weusthoff and Marco Arpagaus

EMS, 14.09.2011

MeteoSwiss official warnings (24h acc. precip.) for 4th September 2011


152 warning regions

Introduction

5 level

8 different hazards

 currentproject: developmentof an applicationfor an automaticverificationofweatherwarnings


Introduction

specifications:

  • develop an automaticverificationforoperational warnings, whichallows a certaintolerance (spaceand time)

  • usesynergies(e.g. with GIN, a commonplatformfor all naturalhazards in Switzerland: http://www.gin-info.ch/index.html)

    motivation:

  • replacecurrentmanual(subjective) verification in ordertoreleaseresources

  • provethequalityofofficialwarnings

  • singleofficialvoice (SOV, sinceJanuary 2011)  distribution via mediaforlevel 4 and 5


Challenges

  • how to evaluate the usefulness of warnings without knowing the needs of individual users (and their cost/loss)

  • how to interprete „tolerant results“ and what should be communicated to the users

Precautions causes Costs

Having no protection results in Losses


Challenges

  • representativityofobservations

  • accountforfeedbackofauthorities

  • smallstatistics (rare events)

e.g. station Magadino / Cadenazzo (203 m asl) is only wind station for two warn regions with complex terrain (308 and 309)

> 2000 m

< 800 m


Basic Concept

event-oriented verification, warnings as binary events

tolerant in space, time and threshold

distinguish two types of warnings

SHORT: short-term events (e.g. thunderstorms)

AKKU: accumulated events (e.g. 24h precipitation accumulation)

event definition and evaluation is (in principle) the same within each group; differentiate between basic verification (strict) and detailed verification

verification per warning region, summary for specific regions or whole Switzerland


Example: AKKU

Rain  level 3-5

Snowfall (lowlands and mountains) level 3-5

Snowmelt level 3-5

Heat wave level 3

  • snowmelt cannot be verified due to a lack of observations;

  • for snow and rain use of radar data (spatial information) and psychrometer temperature


Event-Definition

WarnEvent (ts to te)

acc/3

ti

issue time

t2

te

ts

t1

ObsEvent

(t1 to t2)

t2 - ti > tv?

AKKU

  • each warning is an event; duration of warning at least as long as accumulation period duration

  • observation: consider hourly 24h, 48h and 72h sum; important is first threshold exceedance (t2)

Hit

 An eventisobservedduring a valid warningandthefirstthresholdexceedance (t2) occursat least accumulationPeriod/3 hours (i.e. 8h,16h,24h) after thebeginningofthe warn event (ts) and not laterthenthe end ofthe warn event (te).

Miss

 A thresholdexceedanceisobservedwithout an activewarningorthefirstthresholdexceedanceoccurs bevor accumulationPeriod/3 hoursafter thebeginningofthewarning (ts).

FalseAlarm

 A warninghasbeenissued, but nothresholdexceedancehasbeenobserved.


Evaluation A: Basic-verification

Present results as:

POD

FAR

FBI

(TS)

 derived from contingency table

AKKU

Missing-D-problem:

what is a „non-event“?

Evaluation B: detailed verification

  • in principle like Evaluation A (Hit, Miss, False Alarm)

  • introduce additional category

    • combination of Hit, Miss und False Alarm  see definitions on next slide


Evaluation B: detailed verification

WarnEvent (ts to te)

ti

issue time

te

t2

ts

t1

ObsEvent

(t1 to t2)

t2 - te < tshift

AKKU

(2.)

(1.)

WarnEvent (ts to te)

acc/4

acc/3

ti

issue time

t2

te

ts

ObsEvent

(t1 to t2)

Specifications

Miss + Hit + False Alarm

 the first threshold exceedance (t2) occurs maximal tshift hours after the end of the warn event (te) or less than accumulatioPeriod/3 (8,16,24h) but more than accumulationPeriod/4 (6,12,18h) after the start of the warning (ts).


Evaluation B: detailed verification

Presentation of results:

„perfect“ hit

„useful“ combined categories including a hit

„bad“ false alarm, miss

AKKU

„good“

... adapted from DWD


Tolerance

Allowtolerances in:

threshold:LowHit = 90% ofthreshold

time:variationoftime components (e.g. tshift)

space:ifpossible, takeintoaccountneighbouring warn regions

applytolerancestobasicanddetailedverification

SHORT: possibilitytorequest a minimumleadtimetvforthewarning (i.e. a hitisonlypossibleifthewarninghasbeenissuedat least tv (= t1 - ti) hoursbeforetheobservedevent, otherwiseitisclassifiedas a miss)

SHORT + AKKU


Application  Flow Diagram

warn DataBase

 warn events

  • Java Application

  • AWV

  • deriveobsevents

  • perform event-basedverificationforeachsettingandeachregion

store warn and obs events on a monthly basis

obs DataBase

 hourly data

per warn region

store evaluation results for each event on a monthly basis

  • aggregateresultsandcalculatescoresforspecificperiod

  • present results

  • per region

  • single event


Luzern

MeteoSwiss official warnings (24h acc. precip.)

for 4th September 2011

Observations (surface stations): 24 h acc.

precipitation analysis for 4th September 2011 (prel.)

Bern

A qualitative example…

Level 3 warning:

WarnIssue04.09.2011 08:56

WarnStart 04.09.2011 12:00

WarnEnd 05.09.2011 12:00

24h acc. precip.

35 mm/24h

50 mm/24h


Thanks for listening …


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