Meteorological applications and numerical
models becoming increasingly accurate
 Actual observing systems provide high resolution data in space and time
 Allow to detect high impact weather
 Nowcasting tools to forecast high impact weather well established and the
most important component in the warning process
 Research needed to replace “Warning on Detection” by “Warning on
Forecast”
 Convection permitting models and especially ensembles are a big step
forward
 Can give good indication of convective activity, heavy rain or high winds
 But still not good enough for real warning operation
 Short and medium range ensemble systems provide accurate and reliable
forecasts
Early warning for winter storms, large scale flooding, extreme
temperature events possible
 The bulk of meteorological products can be created automatically
WWOSC, August 2014, Montreal
The role of the forecaster
 No more product generation that could be created
automatically without loss of quality
 High impact weather remains the domain of the
forecaster
 Forecaster still in the loop for quite some time
Providing actual warnings and weather watches
 Forecasters need to focus on where manual
intervention is still needed
Forecasters need to constantly adapt to new data,
applications and models (increased complexity,
conceptual models, scientific understanding)
Technical system need to take care of final product
generation and distribution
 Forecasters work gets an additional focus
 Providing advice (new products)
 Supporting collaborative decision making(crisis mgmt.,
airports)
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NMSs and the private sector
 Let each partner do what they do best
 Cooperate when it makes sense
Private sector can help to distribute warnings
But, don’t compromise official single voice!
Example: forecasts for renewable energy in
Germany
DWD is optimizing its models including the
usage of data from wind and solar parks
Met. Service providers optimize their power
forecasts
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Cooperation with academia
 Germany established a (virtual) research
network (Hans Ertel Center) to better link
basic research and teaching with the
needs of DWD
 Focus onto the areas that are relevant to
weather forecasting
 Strengthening DWD’s subjects in the
universities curricula
 Establish permanent research groups in five
priority research areas
Research Themes:
 Dynamics and Predictability
 Data Assimilation
 Model Development
 Climate Monitoring & Diagnostics
 Use of weather forecasting for
the general public
WWOSC, August 2014, Montreal