Transcript DSS and Science in the NWS * current and future issues

The relationship between Science
and DSS in the NWS – issues and
discussion
Mike Evans
WFO Binghamton, NY
Some quotes on the increasing
emphasis on decision support services
in the National Weather Service:
• Ten years ago – “If we are not careful and don’t
maintain the importance of science in the NWS,
forecasters will turn into nothing more than
communicators”.
• Earlier this year – “Science is dead”. (joking?)
• So… what is the role of science in the NWS with
the increased focus on DSS and communication?
From the Great Lakes conference this
year:
• “Before you can communicate risk, you have to identify
risk”. – Dick Wagenmaker – MIC DTX.
• Implication is that the science program in the NWS needs
to focus (more than ever) on hazardous weather
identification (increased situational awareness, diagnosis
of significant weather events).
Research and training topics directly
related to improved DSS
• Optimal and efficient use of data sets (we’re being hit by a firehose
of information; NY-meso-net, GOES-R, models / ensembles).
• Convection (factors that promote severe weather outbreaks for
situational awareness, application of high-resolution (convectionallowing) modelling and ensembles, radar diagnostic tools and
techniques).
• Flooding (QPF forecasting, ensembles, probabilistic forecasting,
QPE).
• Winter weather (QPF forecasting, ensembles, probabilistic
forecasting).
• Aviation (IFR forecasting, other aviation hazards).
• Probabilistic forecasting techniques (ensembles, anomalies,
analogs).
• QPF forecasting (role of the human, models, ensembles and model
QPF blending).
Today’s talks from our university
partners:
• Environmental factors that affect lake effect snow
(situational awareness, diagnosis of hazardous
weather).
• Examination of structures in lake effect snow bands
(diagnosis of hazardous weather).
• NY State meso-net (diagnosis / situational awareness).
• Environmental factors that affect convection
(situational awareness / diagnosis).
• Tornado warnings / dual pol radar (diagnosis of
hazardous weather).
• Ensembles and QPF / heavy rainfall (situational
awareness).
SOO meeting science program vision
• Transition to DSS focus, driven by
groundbreaking improvements in modeling
and remote sensing.
• Transition to information-centric mindset and
operating concept (forecast production to
managing the forecast process and
communicating).
• More involvement in research to operations.
• Development and delivery of training
Some issues for the (near) future:
• Automation of routine forecasting tasks will increase –
more time for training, science, communication of
probabilistic information?
• Again – QPF forecasting. Where are we going? Model
blending vs. can humans improve on the models?
• Forecaster personality types – how can we integrate
detail oriented people into a process requiring
increasing communication skills?
• Universities – should this paradigm shift change how
new forecasters are being trained? (communication
and social science vs. traditional forecasting contests).