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New Applications for Forecasters. EGOWS 2007 Heleen ter Pelkwijk. The items of this presentation. Rich Intranet Application Dashboard Product Generation Application for the use of Conditional Climatology. Rich Intranet Application. Purpose:

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new applications for forecasters

New Applications for Forecasters

EGOWS 2007

Heleen ter Pelkwijk

the items of this presentation
The items of this presentation
  • Rich Intranet Application
  • Dashboard
  • Product Generation
  • Application for the use of Conditional Climatology
rich intranet application
Rich Intranet Application
  • Purpose:

Create an easily accessible operational intranet environment (weather items) for the forecasters.

rich intranet application1
Rich Intranet Application
  • Reason:
  • More than half of the forecasters make frequent use of internet/intranet
  • Researchers want to have an easily accessible outlet to show the forecasters their experimental products.
rich intranet application2
Rich Intranet Application
  • Method:

- Creation of two intranet domains:

Proeftuin.knmi.nl (the playground for scientists)

Oper.knmi.nl (the operational website)

- Creation of a combined menu (portal)

rich intranet application3
Rich Intranet Application
  • Method:

Definition of operational intranet system:

Data streams, data processing and the server are monitored and when needed repaired 24 X 7.

The experimental site has an operational server but no operational data!

rich intranet application4
Rich Intranet Application
  • Result:
  • The menu is created from a database
  • All information has a tag “oper” or “exper”
  • All information has its own unique product number
rich intranet application12
Rich Intranet Application
  • Conclusion:

Do we still need a dedicated meteorological workstation?

the items of this presentation1
The items of this presentation
  • Rich Intranet Application
  • Dashboard
  • Product Generation
  • Application for the use of Conditional Climatology
dashboard
Dashboard
  • Purpose:

- Dashboard = the interface of a monitoring tool

- Dashboard gives a signal (trigger) in case a severe event occurs.

dashboard1
Dashboard
  • Reason:

- The forecaster has to handle more and more data

- The forecaster has to make the right decision as soon as possible

  • Desired results:
  • Makes the forecaster aware of important phenomenon as soon as possible
  • Quality and efficiency
  • Optimal man-machine mix
dashboard2
Dashboard
  • Method: Possible monitoring types

- observations – products (standard/incidental)

- observations – model

- model – model

- model – product (difference can be a choice)

- observation – observation

- product – product (consistency)

- Product – time (monitoring)

slide20

Dashboard:

the concept

RADAR

model

ground obs.

product editor

trigger module

detailed info (intranet)

trigger dashboard

dashboard3
Dashboard
  • Realised at this moment
  • Observations – product

- accumulation of precipitation from the radar / limit for a weather alarm

- thunderstorm data from “FLITS” / limit for a weather alarm

- wind observations / limit for a weather alarm

- snow and blowing snow / limit for a weather alarm

2. Model – product

- EPS / limit for a weather alarm

- EPS / warnings for customers

dashboard4
Dashboard
  • Result: What does it look like?
dashboard5
Dashboard
  • Result: What does it look like?
dashboard6
Dashboard
  • Problems:

- Not too many triggers!

- How to keep it conveniently arranged

dashboard7
Dashboard
  • Solutions:

- The use of smart mechanisms to reduce the amount of triggers

- Filter and sort possibilities

- Link triggers to the content of the forecasts

the items of this presentation2
The items of this presentation
  • Rich Intranet Application
  • Dashboard
  • Product Generation
  • Application for the use of Conditional Climatology
product generation
Product Generation
  • Purpose:

Reducing the “routine jobs” by automate part of the standard production.

product generation1
Product Generation
  • Reason:
  • To make more efficient use of the time of the forecaster.
  • To make more time for the important things during the shift like advising customers and severe weather monitoring.
  • To make it possible to work with weather dependent shifts…..more time for applied research.
slide30

data

objective

post processing

automatic

Product generation

customers

automatic

monitoring

Forecaster:

1. Monitoring

2. Monitoring and adapt automatic product generation

3. Not automatic production

4. Not automatic monitoring

The red data streams are not monitored by the forecasters!

slide31

dashboard

auto

+ mets

  • Generation of:
  • Texts (retrieval / text generation)
  • pictures
  • triggers

Weather dependent loop

Basis data

(Observations, models, statistic values)

Product parts

(Text, pictures)

Products

(product layout)

slide32

Weather dependent control by the forecaster

Crossing of

fixed

threshold value(s)?

no

yes

Trigger to the forecaster;

A check and possible adjustments.

Then distribution.

Automatic distribution

Extra attention when the product becomes more important

slide34

Average of 3 stations: Vlissingen, Brasschaat (of Woensdrecht) en Gilze Rijen

EPS output

Modified long term forecast

Precipitation forecast Zoommeer

product generation4
Product Generation
  • At this moment:

Pilot with the use of e-forms

the items of this presentation3
The items of this presentation
  • Rich Intranet Application
  • Dashboard
  • Product Generation
  • Application for the use of Conditional Climatology
application for the use of conditional climatology
Application for the use of Conditional Climatology
  • Purpose:

An application which makes it possible to give an quick overview of the change in, for instance the visibility, during the next 12 hours, based on climatology.

This systems works for fog/low visibility/low clouds

application for the use of conditional climatology1
Application for the use of Conditional Climatology
  • Reason:

Give the forecaster an easy access to recent climatological reference material (1977-2006) to help him/her to make the forecast.

application for the use of conditional climatology2
Application for the use of Conditional Climatology
  • Methode:
  • conditionally
  • Use of classes (colours => autotaf)

Fog (in m) Cloud height (in ft)

0-200 0-200

200-500 200-500

500-800 500-1000

800-1500 1000-1500

1500-3000

application for the use of conditional climatology3
Application for the use of Conditional Climatology
  • Used:
  • Hourly synops over the past 30 years
  • 20 stations