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 (convection- allowing) 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).