How should forecasting tools be designed?
The two most important forecasting tool modules are,
of course,
forecasters and tools.
In any forecasting tool design, the requirements of these two parts should
considered first:
the system should be designed around these two parts.
What kinds of tools would best serve the operational forecaster?
Tools should adapt to help forecasters to work more effectively,
not vice versa.
They should be designed as "intellectual levers",
not as "intellectual siphons".
Forecasters need:
Design for modular decision support systems for weather forecasting
Note in the design how the two smart parts/modules/agents,
the two sources of complementary intelligence,
the forecaster and the
artificial intelligence
(AI) module, share top-level positions for controlling data processing.
Other easy-to-update modules would
handle communication of data
between these two agents
-- data is what the agents act upon --
or simply supply improved data to the system.
Any improvements in data (observing technology,
NWP, and NWP-based products)
would be external to the system and would be readily ingested by the system.
The system is designed to enable forecasters
and forecasting rules to
further improve the data
--
"post-process", perform "weather watch", "intervene", nowcast,
make better weather forecasts
--
efficiently.
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The main idea behind the design is to enable
National Meteorological Services
to take maximal advantage of
modernization
opportunities based on improving pieces of technology,
by building around the three most fundamental "modules" of a
forecaster workstation
-- forecasters, forecasting rules, and data --
the modules whose requirements must be satisfied:
Bjarne Hansen
![]() ![]() Last updated 31 May 2003. Opinions expressed here are solely those of the author except where indicated as otherwise. |