It has been an active weather week with a series of Nor’easters impacting the East Coast of the United States, and another one looms. With such storms you often hear terms like bomb, bomb cyclone, or superstorm. I enjoy writing my Forbes blogs because I can teach about such terms and provide my professional insights on a science that I have loved since 6th grade. Even with the increasing amount of weather information available, I still find that people have basic misconceptions about weather that live on and on and on and on and on and on……………… I often call lingering incorrect assertions about climate “zombie theories.” Last week someone asked me a question about forecasting that made me realize that we also have “weather zombie theories.”
Will it rain on my daughter’s outdoor wedding reception 9 months from now? Honestly, a credible meteorologist will say, “I do not know” then provide them with climatological guidance on what the typical weather is like for the reception location. Many people that I speak with do not realize that day-to-day forecasts are rooted in numerical weather prediction. Computer models solve complex dynamics and thermodynamics equations to predict how a fluid (the atmosphere) is going to change in four dimensions on a rotating planet. When I ask the average person how a weather forecast is made, the answers typically are “satellites, radars, weather balloons, shifting the weather from east to west, or even guess.” The science of weather forecasting certainly involves these elements, but computer models are critical.
However, there are limits. National Weather Service Director Dr. Louis Uccellini summarizes it nicely in a 2013 Washington Post Article. He told Brian Palmer, “We sustain higher accuracy out to two to three days in advance; then it starts dropping off faster at days six through eight.” I think the 10-14 day time frame is where we currently are, but there will always be limits beyond that time frame given the nature of the problem. There are methods involving understanding long-term patterns like El Nino that can provide some skill to provide weekly to seasonal forecasts but not at the level of specificity on an hour-to-hour, daily forecast that far out.
Apps, Apps, Apps. This is the era of “app-mospheric science.” Virtually everyone has a weather App on their phones. Don’t get me wrong, there is very useful information that help plan your week or perhaps day. My good friend and colleague, Marshall Moss of Accuweather is quick to remind me that all Apps are not created equal and should not be painted with the same broad stroke. I suspect my colleagues at Weather.com, Weather Underground, and others would agree. However, it is important to understand the limitations of Apps in rapidly evolving severe weather, snow, or hazardous weather. Too many times in my own personal circle, I hear people make statements based on Apps that just aren’t true.
Recently, Georgia was experiencing pretty significant rainfall and flooding. A person at my University said, “my App says this is going to stop by this afternoon.” I pulled up the NOAA HRRR weather model and the current radar. Both indicated that there was no way that was going to happen. My advice is simply to use your App responsibly but not as a rubber stamp.
Will it rain tomorrow in my garden located 3 feet from the fence in the backyard? I am often amused at the expectation that the current state of meteorology can deliver pinpoint forecasts for a location. Weather radar and other techniques can provide the ability to somewhat address the hypothetical question that I posed on a near-term basis, but precipitation is a particularly challenging forecast problem. It is one of the very reasons precipitation forecasts are conveyed as a probability. As I wrote in a previous blog,
On a recent tubing trip, I heard a woman lamenting about rain. She said there was only a 20% chance of rain so ‘why was it raining, those meteorologists always get it wrong.’ I thought to myself, ‘it wasn’t 0% so why the complaints.’ Studies and my own personal experience reveal that the public doesn’t understand the concept of % chance of rain, and it may contribute to misguided conclusions like ‘meteorologists are wrong half the time.’
By the way, meteorologists are not wrong half the time and are accurate most of the time. Human nature causes people to focus more on the occasional errant forecast, particularly if they are impacted. Was the forecast correct today as you read this? Probably. Did you tweet props to the meteorologist? Probably not. But, I digress. Percent chance of rain encompasses forecaster confidence that a certain percentage of an area will receive precipitation. For a quick review, I recommend this link.
It is hot today so that means global warming/It is cold today so that means no global warming, right? As a meteorologist and atmospheric sciences professor, I often get asked if I “believe” in global warming or climate change. Once I get over the incorrect framing of science as a belief system, I usually explain what the data shows and then jokingly ask, “do you believe in gravity?” Another common thing that I hear is defining climate based on the weather today or this week. As my colleague Dr. John Knox once said (and I now use often), “weather is your mood, climate is your personality.” I also like to point out that weather is what clothing you wore for today’s weather, climate is the range of clothing in your closet for all types of conditions. Either way, it is important to understand the difference. It is also important to understand that climate changes naturally and that we always had hurricanes and storms. I promise that most climate scientists know this and do not need to be reminded. However, it is perfectly logical that such natural variations can have a human amplification on top of it. My yard keeper recently applied fertilizer to my lawn. Well, gee, I certainly know that grass always grew naturally, but I also know that fertilizer is going to change how it grows too.
But the Farmer’s Almanac or Groundhog said. I am not going to spend much time on this one. A groundhog is a rodent (and I think. most people understand it is folklore and fun), and meteorologist Paul Knight covers the almanacs. In a Penn State University press release Knight notes
The ability to predict events that far in advance is zero… There’s no proven skill, there’s no technique that’s agreed upon in science to be able to do that……I could say things like October 8 to 15 in this area: generally dry, very cool weather expected; first frost and freezes in the valleys. And I would be right probably eight out of 10 years…..I could say February 12 to 19: heavy snow along parts of the eastern seaboard. I’m going to be right seven out of 10 years. There is some relative frequency to these things, but to say that this is of great scientific accuracy would be a real misnomer.
Knight is basically pointing out the differences between climatological forecasting and modern-day deterministic forecasting from aforementioned computer models. Capital Weather Gang Chief Meteorologist Jason Samenow has also written extensively on this issue.
By the way, what other weather zombie theories can you think of?
More Info: www.forbes.com
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