Chris Bedford is one of the most respected meteorologists in the sport of sailing. Through his company Sailwx.com he has worked in literally every grand prix sailing event – from the America’s Cup to the Olympics.
This year he has teamed up with 2x America’s Cup winning navigator, Peter Isler to create “Marine Weather University” – an online school designed to help sailors raise their weather IQ. Chris has designed a unique curriculum that helps sailors learn how to go beyond their weather app.
Scuttlebutt readers can get 10% off any MWU class or course with the coupon code SBUTTFAM at www.marineweatheru.com. The next MWU lecture (LOCAL & REGIONAL WINDS) will be presented as a live webinar on Tuesday, August 11 @ 8PM EDT before being posted online with all of MWU class.
Why go to school when Bob Dylan says, “You don’t need a weather man to know which way the wind blows“? Chris explains…
The flood of always changing data, observations, models, and circumstances make the task of weather prediction extraordinarily challenging. Personally, I feel that every forecast I make is obsolete the instant I send it out as there is always new information coming that will alter the forecast.
Every meteorologist has developed their own approach and process to making a forecast. But there are common aspects that every trained forecaster follows before they apply their own spin on the problem. The common process is scientifically based. The individualized portion is the “art” of weather prediction, and that is unique to a particular forecaster.
Meteorology is an established science. Conceptualized as a fluid, the atmosphere follows the laws of physics and chemistry. Chuck Doswell, a renowned severe weather meteorologist, refers to a good forecaster as one that can balance the “triad of components of a healthy science: 1) Theory, 2) Observation, and 3) Modeling.”
If your forecast process is comprised primarily of looking at a bunch of models (aka “what’s your favorite weather app?) and deciding which to believe, then you are a) not forecasting, and b) wasting your time.
Of the myriad of models available (and there are literally over a hundred you could look at to make a single forecast), how do you know which is the “correct” one or, as some people refer to it, “the model of the day.” The goal is to ADD VALUE over the model, and that can only be accomplished by analyzing data (observations and weather charts) and applying your understanding of meteorological theory. Models are a GUIDE in that process (In fact, meteorologists refer to models as “Guidance”).
Weather forecasting is not black and white. Adding value to a weather forecast doesn’t necessarily mean getting the lowest error score. You can have the lowest error score but make one wrong forecast at the wrong time and the impact on the user could be huge. For example, you could predict the maximum racing wind speed and be correct 9 out of 10 times (90%). But the only day you will care about is the one when you were wrong and, as a result, failed to include a race winning sail in your inventory.
The real emphasis is on providing actionable information for a user. Let me explain by example. Let us say the race committee has an established race wind speed limit of 25 knots, above which racing is canned. Predicting whether the wind will exceed 25 knots is key and quite frankly an easier “GO/NO GO” forecast than predicting the maximum wind speed for the day.
But for this particular case, you add value by identifying WHEN during the day that limit will be exceeded AND communicating it effectively. Will it be over 25 knots all day or can some of the day be salvaged for racing? If so, when will that be so that mark-set boats and race crews are not sitting on the water all day waiting or not going out at all only to see a perfectly race-able period missed?
So, as you are sitting down to review the weather before a race, think about your process. Have you reviewed the observations and analyzed the existing state of the atmosphere? Can you identify the processes at play (without models!) and understand their causes and potential outcomes based on meteorological theory?
What is/are the forecast problem(s) for the day? Do the models adequately and consistently reflect the initial state of the atmosphere? Am I respecting and adequately reflecting uncertainty in my forecast and adding value over, say, a model consensus forecast? Learn more about Peter Isler and Chris Bedford's Marine Weather University here