Frequently asked questions (FAQ)
(select/deselect an answer by mouseclick on a specific question)
»» Why radar image forecasts?
These forecasts are the best in short time ranges (0-4 hours,
also called the range of nowcasting). Major advantages vs. numerical forecast
models are the short computing time and, consequently, frequent update rates
(typically every 5-15 min). Forecasts of rainfall, rain accumulation, thunderstorms,
hail, or (in winter) snowfall or freezing rain are possible and helpful for
any activity in free air. Warning messages can be generated in a fully automated
manner. Typical users of radar image forecasts and derived warnings are weather
institutes/companies or traffic maintenance/water management organisations.
But many others, also in private sector, use these forecasts for their
comfort or protection of life.
»» Can I use your forecast technique for my radar images?
Yes. Please have a look to our links Server and
Client at the top-left edge of this page.
Please note that this service is for demo only. You can upload and test as many
examples as you like. But the capacity of our server for this demo is
limited. You will have to wait as long as the server is busy.
»» Which are the costs for customers using trep?
The regular costs depend on
- The size of your images
- The time step between two consecutive forecasts
- The type of your application (end-user, reseller)
- Licensing, maintenance and support are included
Additional costs are unique and depend on our expences for
software modifications (if required) and installation.
Please do not hesitate ordering a proposal.
»» How is the radar forecast calculated?
First, we treat the radar images with a clutter filter. After that, we retrieve
the motion of radar echoes, and we use the motion vectors for extrapolation
into the future. Our technique is novel with respect to the fact that the
advantages of two traditional methods, the box tracking and the cell tracking,
are combined to one single tracking method. In this manner, the advantages of
both methods contribute to the best possible extrapolation, leading to optimal
forecasts for stratiform precipitation and convective storms as well.
»» What is a clutter filter?
Weather radar images are often affected by non-weather echoes, originating
from ground (mountains, buildings, trees ...), or from birds, insects,
aircrafts and so on. Filter techniques try eliminating these disturbing
echoes, called 'clutter', without affecting weather echoes. Clutter filters
are very often in use, but not always effective. Stationary radar echoes from
ground may affect our extrapolation technique. Therefore, we use a novel filter
which is especially designed for removing ground clutter still present in the
»» Why are you using 6 or 7 images for the forecast?
With six images, we have a good sequence for minimizing random variations
in the calculated motion field. The last of the six images is typically
extrapolated into the future. For some applications, it may be desirable
using a modified radar image or even a non-radar image for extrapolation,
e.g., an image showing lightning density. Therefore, a 7th image can be
added in our demo. Obviously, this additional image must have the same
size as the radar images.
»» Are you using a specific intensity scale?
No, the scale is free. Nevertheless, we recommend using a scale starting at 13 dBZ,
rising in steps of 3 dB, and ending at 72 dBZ. This scale has 20 intervals, corresponding to
levels 1 to 20 (out of 255) in your gif images. Please note that 20 intervals only are considered
in our algorithm. All levels larger than 20 are set to zero before processing the images.
»» Who developed the technique?
Many persons have worked on the methodology since many years. Extrapolation
of radar images into the future is a topic of radar meteorology since the
sixties of the last century. One of several basic techniques is TREC
('tracking radar echoes by correlation'), introduced by US scientist
Rinehart in the late seventies. COTREC ('continuity of TREC vectors') was
developed in the nineties by two doctorands at ETH in Zurich. A modified
version, called RAINCAST, is in operational use by meteoradar since 1999.
A major update of the technique has recently been developed by meteoradar.
We call it TREP since the basic idea of the old TREC has remained unchanged.
Various in-house tests demonstrate a further improvement of the forecast
quality of TREP compared with RAINCAST, especially for convective storms.
Therefore, we upgrade our operational forecast applications to TREP in
»» How does the forecast quality changes with forecast lead time?
Naturally, the forecast quality degrades with increasing forecast lead
time. However, the degree of degradation depends on the size of the
phenomenon you are interested in. A broad precipitation front is better
predictable (up to several hours) than a small isolated thunderstorm cell
(less than one hour). We developed a stochastic model for simulation of
these properties. With this model, we can calculate the risk that an event
such as hail or heavy rain may occur at a given location and time. Our
warning system uses this model: a warning message is issued when a pre-defined
risk value is reached for the first time.
© meteoradar 2008