Northeast Ohio weather and science blog covering severe storms, long term outlooks, climate, behavioral meteorology, technology and other observations
Friday, April 25, 2014
Summer Outlooks Are Different Than Day-to-Day Forecasts
Our WJW FOX8 Summer Outlook first aired on Thursday, April 24th. Not long after, comments and criticism started pouring in stating in part that we should concentrate on getting the daily forecast right rather than trying to forecast the weather months out. This isn't new. It happens after each seasonal outlook.
Actual day to day weather forecasts are developed with analyzing current conditions, radar, satellite and other parameters to make a forecast for a short period of time in the future. 12 Hours, 24 hours, 36 hours, 48 hours. We utilize computer model projections as guidance. Yes, these projections are getting better as more data is utilized and plugged into faster and faster computers with more sophisticated equations.
Seasonal long range outlooks (winter weather forecast, etc) are created by looking at the ocean sea surface temperature patterns (El Nino, etc), pressure patterns over the Arctic and North Atlantic among some other long term atmospheric trends. Some scientists use solar output and other variables. The elements just mentioned are matched up with other years of occurrence. A best possible fit is created. Sometimes this works out well. Sometimes it doesn’t. Again, this is a trend outlook not a specific forecast for a specific day. Individual storms cannot be seen this far out. Forecasts for specific days? Forget it. Too much randomness in the atmosphere that is way beyond our abilities. But by looking at parameters that existed in the past during other storm events, we can say that the chance of say a hurricane making landfall is greater this year than in years past.
For most, all of these forecasts and trend outlooks are lumped into one group even though each are derived using entirely different information. I get it. Its human nature to generalize and simplify complicated subjects like the science of weather prediction. So as a result, we formulate a concrete, black and white, overly scaled down version of the weather. Whether its a long range winter outlook, a climate average for a wedding day, the thunderstorm chances for later this afternoon, lake effect snowfall amounts or a hurricane forecast track. Its all the same animal to most. We subconsciously eliminate the nebulous science, weird looking equations and fancy internet computer animations in favor of a narrative that tells a better story. In short, The Old Farmers’ Almanac fits with how our brains are wired. Its simple. Its folksy with just enough science to make it credible. Why do we continue believing the Old Farmers’ Almanac? The simple answer is it makes us feel good! While I love the Old Farmers Almanac for its articles, I'd trust an actual Meteorologist's forecast first. I wouldn't preemptively dismiss the scientific explanation, ignore the random changes and replace them with the Old Farmers Almanac figuring that its more accurate. Just saying...
So remember that Seasonal Outlooks are by their very nature formulated differently than day-to-day forecasts. Let's sit back and see if this summer will behave like we think it will.
at 6:45:00 AM Posted by Scott Sabol 1 comment:
Labels: biases, dissonance, forecasts, outlooks, psychology
Thursday, April 24, 2014
Is Spring Disappearing?
"It seems like we go straight from winter into summer nowadays."
Its by far one of the most frequent comments I get this time of year. But is it true? Are those traditional spring days from yesteryear being replaced by quicker transitions from winter to warmer days?
A tall order for sure. So rather than relying on our perceptions (I've written extensively how our senses and selective memory fools us by placing more weight on more recent events that match up with our inherent biases) in determining whether or not this "winter-to-summer" trend actually exists, I looked up the average temperatures each day during the meteorological spring months (March through May) over the last 50 years. I plotted the average daily temperature and ran a linear regression of all 92 days (March through May) for each year since 1964 (last 50 years) to determine the rate of warming for each spring.
For example, 2013 looks something like this:
That's great but that's only one year. How about the other 49 years? I won't bore you with each temperature scatterplot but some interesting years stand out. The largest increase per day occurred in 1975. The smallest increase per day occurred in 1973.
Here are the TOP 10 and BOTTOM 10 with the year of occurrence: Only 2 of the TOP TEN occurred in the last 20 years.
I plotted each year's trend with the trend line. The long term trend over the last 50 years is negligible.
However, the same temperature trend data in bar graph form shows HIGHER INCREASES in consecutive years since 2000 (except was 2012). The increase over the last 15 years is steady around 0.35 degrees per day in spring. We also saw some long stretches in the 1980s equal to recent years.
The 1970s though saw WIDER VARIATION YEAR-TO-YEAR with SMALLER INCREASES compared to recent years of about a tenth a degree lower than the last 15 years.
So when someone says "Its seems as if spring is shorter" or "We're jumping from winter into summer faster now than in past years", it seems they would be right...but for a different reason. These changes of a few tenths of a degree over many years are imperceptible to us. My guess is that we take the short term weather changes (a sudden drop from 75 to 35 for example) and believe these changes reflect bigger changes over longer periods. Its a classic example of the RECENCY EFFECT.
at 8:15:00 AM Posted by Scott Sabol No comments:
Labels: climate, linear regression, spring, temperatures
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