Geoscience Reference
In-Depth Information
offer the possibility for the NHMS to add their own specialized products into their systems.
Many of the countries mentioned above in fact use a combination of products from their
own systems and those of the manufacturers. Information is readily available in trade shows
or on their web sites. The ideal requirement is a seamless, user-friendly integrated
visualization, decision-making and production system to cover all scales (the seamless
prediction concept) and this is the trend in many NHMS' for all data, products and so radar
only processing or visualization systems are an interim step towards this and requires
investment, resources, time and effort to achieve. NinJo and AWIPS (not described here)
provides an example of how radar is expected to be integrated into a comprehensive
forecast analysis, diagnosis, prognosis and production tool.
The purpose of this contribution was to illustrate the issues faced by NHMS's. There is a
push to use meteorological technology as much as possible and to automate as much as
possible. Computing technology is still a limiting factor - computers, telecommunications
and data/product storage are all continuing issues that can always be faster and bigger. If
there is the time, the resources and the expertise, manual interpretation of basic radar
products is still the best way to provide severe weather warning services and to optimally
utilize the considerable capabilities of the forecasters. However, tools are needed to
streamline and accelerate the process but this is highly dependent on organizational factors.
Automated products introduce another level of complexity and knowledge requirement.
They can be black boxes that bewilder the user. However, creating black boxes without
diagnostic capabilities, providing poor tools and denying access to basic products and
information, is self-defeating. It is a sure way of making smart people (appear) “dumb”. The
algorithms aren't perfect given the need for high POD. They never will be and they can be
better and substantial work on data quality, feature detection and prediction are needed.
The systems described exhibit the great efforts and resources are expended to do this.
Saving a single button click or a mouse movement can make the difference between a bad
and a good system. This is difficult to describe as a requirement and prototyping and
demonstration projects are the only way to appreciate this.
While reliable weather radars and expertise play a central role in the warning process, this is
still a challenge for many countries. Satellite and lightning systems are now available that
have minimal support requirements. Stand alone applications for severe weather can and
are being developed for these system. In the absence of radars, there is no question that they
will provide benefits but their efficacy, the forecast process and the service level for severe
weather warnings need to be demonstrated. No doubt that they should also enhance
existing systems that rely on weather radar networks. This is occurring but beyond the
scope of this contribution. No convective scale warning service has been soley developed
without radar and so this is a new area to investigate. Understanding the technology,
interpretation of the data and the products will require more development, enhanced
expertise, demonstration and decision-making skills.
For the convective weather problem, dual-polarization radar will have benefits in data
quality, hail detection and rainfall estimation but this is again beyond the scope of this
contribution (Frame et al, 2009). Earth curvature and beam propagation preclude low level
detection and so many of the hazardous phenomena are not actually measured beyond a
few tens of kilometer from the radar site and must therefore be inferred from measurements
aloft. The CASA (Cooperative Adapting and Sensing of the Atmosphere) is a network of X
