Some of the hardest things you can do in effectively influencing behaviour in emergencies is to find the balance between risk, forecast, and actual impacts. This has been heavily impacted by the rise of social media, and the ability for people to access products they’ve never seen before, and without interpretation, or a weighing of accuracy, can lead to undue concern or complacency.
A perfect example is looking at the Qualitative Precipitation Forecast (QPF) models from the National Weather Service’s Storm Prediction Center. The forecasts are helpful if you understand that they aren’t gospel, especially when you get to the 5 or 7 day forecasts. These can be helpful in determining the possibility of heavy rainfall, and even provide some clarity as to heavy concentrations, but shouldn’t be taken as a true representation of actual risk. What we’ve also seen is that depending on the nature of the meteorological conditions creating the potential rainfall, they can be incredibly hard to predict. This tweet from Dan Reilly, the Warning Coordination Meterologist for NWS Houston/Galveston shows a perfect example:
Another example of how models struggle with convective rainfall. Images show 33 hr total rainfall from 00Z runs of hrrr and 12km NAM essentially showing model depiction of rainfall through Mon night. Big diffs for SE TX, Houston. pic.twitter.com/f6jZUTKGmh
— Dan Reilly (@DReillyWx) September 3, 2018
Leaders in meteorology, emergency management, and media need to be cautious with the power they hold. Sharing these images without concurrent interpretation can cause a mis-balance of truth v. possibility. A better strategy is to post a video where the image cannot be separated from the interpretation…
What are good ways to balance forecast with modeling? How can we make messages actionable without causing undue concern?