March Warmth As A Guide To Summer Temperatures

During each transition season of spring and fall, people incorrectly attempt to predict the next season's warmth or cold by using the current season's temperatures as a guide. The conversations go something like this:

"This warm March means we're in for a super hot summer" or "This cold and rainy fall means we're in for tons of snow this winter." or some other combination like this.

Does this line of thinking work?

I checked the top 10 warmest March years for 8 cities (Cleveland, Cincinnati, Detroit, Indianapolis, Cincinnati, Pittsburgh, Milwaukee and Buffalo) and ranked them. I found the top 10 warmest years that occurred the most frequently for all of the cities and plotted a summer (June through August) composite (blend) temperature map of these years weighting the more frequent--top 6--warm years higher.

Summer blend - Most Frequent Top 10 Warm March Years - Top 6 Weighted Higher

I next plotted the blend of only the top 6 most frequent years of occurrence that were previously weighted. Notice the warmth become more widespread in this blend.

Neither one of these composites above are blast furnace summers by any stretch.

The problem is that both of these composites mask the individual year extremes. Look at each of the top 5 most frequent years of occurrence?  Each summer varies a great deal. A more detailed look at March 2012 (hottest on record in northern Ohio HERE) 

When we create our summer outlook each year, we perform an in-depth analysis of specific current conditions and combine it with computer projections of these conditions into the future. We combine this with some statistical analysis (similar to the above maps) to come up with a consensus outlook. Its more complicated than saying "its warm or cool now therefore it will be warm or cool next month/next season".

Bottom line, seasonal outlooks are very complex.  Don't be fooled by monthly warmth especially in early spring. It doesn't necessarily mean that an equally warmer than normal summer is ahead.

More on the summer outlook later in April.

Why is PI so important? 2016 Edition

It's one of my favorite days of the year!  A day when geeks of all ages can show off their PI stuff and skills at recitation.  I have PI memorized to 75 digits. Chicks dig it. My wife digs it...so she says. Your kids might have PI day activities planned at school today (Tuesday). I gave my son my PI shirt to wear. Reluctantly, he's going to do it.

I'm sure back in 1737 when Leonard Euler first used the symbol π, he never envisioned the fascination with π that developed since.  There are t-shirts, π plates (yes, I have two), π mugs...and on and on. Novelty websites have just about every π trinket you can think of!

What is PI " π"?

PI is the number that represents the ration of a circle's circumference to its diameter.

As we entered the computer age, the calculation for more digits became a test for computer system efficiency and accuracy. In 2014, scientist Ed Karrel calculated more than 10 QUADRILLION bits (unfortunately not in base 10 units) decimals of PI.  Here is his blog.

The interesting part is that PI is non-repeating and never ending so its very nature is an approximation. Mathematicians have tried to find patterns within π since ancient times. Archaeologists believe that the ancient Egyptians constructed the Great Pyramid of Giza with knowledge of π.  Greek mathematician Archimedes was the first to calculate a range for π  using polygons.

Throughout it's history, π has become a fascination among mathematicians and more recently computer programmers. Welsh mathematician William Jones was the first to use the symbol π to represent the ratio of a circle's circumference to it's diameter in the early 1700s. In the 1940s, a little over 1000 digits of π were known.

As we entered the computer age, the calculation for more digits became a test of computer system efficiency, power and accuracy. In 2014, scientist Ed Karrel calculated more than 10 QUADRILLION hexadecimal digit of PI.  Using hexadecimals make it faster to calculate. Converting hex to base 10 numbers which we all is very difficult when you have these many digits according to Ed.  Here is his blog.

To put the number of digits in Ed Karrel's calculation into perspective, you only need 39 digits of PI to calculate the circumference of the observable universe (assuming it's a sphere) to the accuracy of a width of the inside of an atom!

To put it another way, if you were to recite EVERY digit, it would take you 317,000,000 years to complete. You'd need to start before the dinosaurs were alive in order to finish today!

All of this great if you are a math or computer geek. But why should the rest of us care?

PI is present in every aspect of our lives. PI is used in most calculation in the development of all the world's infrastructure. All communications, CAT scans, MRI machines, genetic research, propulsion systems (space and military aircraft), quantum physics....the list goes on.

Famous scientific discoveries and the math that describes them incorporate PI:

* The calculation for determining the horsepower of your car has PI in it.

* Einstein's famous equations that describe relativity which is now directly applied in
   satellite calibration has PI in it. Here it is in very simple form:

* The math that determines electric force (electricity) includes PI.

*  How about the speed and volume of blood flow inside the first artificial heart? You bet.
    PI is included in that calculation too.

* Want to figure out the position of two planets nearest to the earth? You need PI.

* Radio communications, cellphones, GPS satellites (see Einstein's equation above) computer hard drive/processor technology were both developed using mathematics that incorporates the number "PI".

* Airlines use PI to calculate flying distance around the earth

* Manufacturing uses PI to figure out how much of a substance will fit into a volume
   of circular or cylindrical space


You might not like math. You might not get PI.  Just remember that PI (3.14159...) is integrated into our everyday life unlike any other number. Without it, your daily life would be totally different.

How About the 2017 Oscars?

Here are some potential best picture nominees a year from now.  Keep this list handy.


SILENCE
PASSENGERS
LA LA LAND
WARCRAFT
LONG HALFTIME WALK
HAIL, CAESAR!
ANGRY BIRDS

THE BIRTH OF A NATION
CERTAIN WOMEN
SLEIGHT
INDIGNATION
SWISS ARMY MAN
MONEY MONSTER
SULLY
THE FOUNDER
THE LIGHT BETWEEN OCEANS
STORY OF YOUR LIFE

OTHER MOVIES TO CHECK OUT:


FRANTZ
COMANCHERIA
A HOLOGRAM FROM THE KING
I, DANIEL BLAKE
THE GREAT WALL
WAR MACHINE
SLACK BOY
COLOSSAL
AFTER THE STORM
INSECTS

CHRISTINE
ON THE MILKY ROAD
WAR ON EVERYONE
FREE FIRE
QUEEN OF KATWE
STAY VERTICAL
LOVE AND FRIENDSHIP
MORGAN                                 EVERYBODY WANTS SOME
HHHH                                 ELLE
THE WOODS         DOG EAT DOG

UNA                 THE NICE GUYS
AMERICAN PASTORIAL LO AND BEHOLD REVERIES OF THE CONNECTED WORLD
THE CIRCLE         SALT AND FIRE
WILSON         PERSONAL SHOPPER
TRESPASS AGAINST US THE UNKNOWN GIRL
THE PROMISE        WEIGHTLESS
BOURNE 5                 VOYAGE OF TIME
A MONSTER CALLS JULIETA
A UNITED KINGDOM THE SALESMAN

COMPLETE UNKNOWN PATERSON

Mindset Behind My Snowfall Forecasts

Sandusky, Ohio snow on February 25, 2016.  Photo courtesy: Bryan Edwards (Twitter)

Snowfall forecasts are very difficult animals both in the meteorology that's used to create them and the public's perception of the numbers you display.

Tuesday morning, I posted a general low resolution hand drawn preliminary forecast for Thursday's snowfall. 

Preliminary Thursday Snow Forecast Issued Tuesday Morning

Yet, many people on social media interpreted this preliminary forecast too literally. Several on Twitter freaked out when they saw Lorain close to the 3-5" range contour.  I told them it probably didn't matter since its--A RANGE!  Sure, Lorain was closer to the potentially heavier snowfall but the overall difference using the range for Lorain was small, probably an inch or two. Yet many on social media see it differently. 

Yesterday morning (Wednesday), I adjusted the area of heavier snow further west but KEPT THE RANGES THE SAME. Once again, people on social media interpreted this as a huge alteration in the snowfall forecast to which I replied, "Use the ranges NOT absolute numbers".  In reality, the overall forecast within the confines of our ranges remained the pretty much the same aside from shifting the heavier amounts west a bit. Yet the perception by the some was that Lorain went from five inches to one inch.  

Most meteorologists on television, the public sector (National Weather Service) and in private industry use snowfall ranges in their forecasts. This works best because it takes into account the variance in movement and intensity of the many individual bands of snowfall within snowfall systems. The problem for the meteorologist is that most people want A SPECIFIC SNOWFALL NUMBER for their backyard.  Yet many people see a snowfall forecast during the morning newscast and believe that this holds for the entire day. Nothing is further from the truth. These forecasts are not one-and-done. They evolve throughout the day as the event unfolds. Forecasts change as the conditions change. People see individual snowfall amounts on their phone apps and believe these over human derived forecasts. They want absolute specifics yet more often than not, one snowfall amount number for any location will not work.

For example, here was my official snowfall forecast issued Thursday morning at 4am for the entire day using ranges:

One specific (WRF 4km) high resolution computer model early in the morning cranked out these amounts for Thursday's snowfall.  While these were in line with our official snowfall forecast above, people fixated on some of the individual numbers and were confused. 

How do we combat this confusion on social and broadcast media? Good question. 

My soft policy is that I rarely post computer model snowfall output unless we are inside 24 hours before a snowfall event. If my intention is to highlight the general outlook for the week ahead, I will post snowfall accumulations without numbers.  A quality controlled "hand drawn" map is another option. My ultimate goal is to present information that describes the weather without creating confusion.  

Situations like this reminds me of the psychology behind the weather forecast. Most people want exactness in there forecasts. Remember that we are all hard wired to simplify uncertainty. So when a snowfall forecast range is posted on a map, people immediately find a number within that range that best fits. I'd like to say that I make a forecast with a cold, rational eye but I don't. I take into account how people with react to EACH WORD knowing that many people with perceive selective elements to fit their location.  I learned that real quick after my first major lake effect event twenty years ago.

If I could make a poster with bullet points for meteorologists, it would list these five at the top

*  Public perception is very powerful

*  We need to be better communicators of information

*  Choice of words is of the utmost importance in conveying severity of the weather

*  Risk is personal (public).  Mass media is for the masses. Yet people want personal forecasts. Huge conundrum.

*  Too much emphasis on uncertainty breeds confusion, inaction and ultimately apathy when the next snow or weather event or importance happens. This is basic psychology that's been well documented over the years. We need to find a delicate balance between voicing uncertainty and sticking to a forecast.

5 Distinct Snow Makers This Week

Coldest air of the season Friday and Saturday

Snowfall forecast by Thursday early afternoon

Canned Ham and Fresca

Why Do We Believe in Ground Hog Predictions?

Ground Hog Day is a neat little holiday for many folks around the country who like to place the slothish behavior of a rodent on a pedestal. He's cute. Its old fashioned. Its tradition. There are top hats. Who wouldn't like to be a part of that?

So why do we like Ground Hog Day so much?

Our brains are hard-wired for simple stories. Go back to our earliest ancestors. Information was passed through stories.

We desire a good weather story (a feel-good forecast with some folklore) versus something data/science driven.  Why is this? A data driven paragraph by itself only activates the language processing centers (Broca’s area and Wernicke’s area ) of the brain. Brain scans show that if you incorporate stories with descriptive metaphors, it will active multiple sensory parts of the brain like the Motor Cortex (body movements) and the Insular Cortex (emotional region) at once. In other words, descriptive story with less data make our brains work harder by relating the story to our our own personal experiences! Given that personal stories make up more than 65% of our conversations, this makes perfect sense.

What does this have to do with weather forecasts?

Typically, our brains work much better with a theme or a story that has a beginning, middle and an end. In this daily forecast example, we visualize a line of showers that moves in at a specific time; it stays for a select amount of time and then moves out without fanfare. Our brains involuntarily take this weather story and creates a visualization by melding our personal experiences with the information. The forecast instantly becomes relatable!. It becomes personal!  Unfortunately, weather events rarely behave in this manner.

For our minds to grasp weather probabilities, we need to be able to handle multiple possible outcomes at once. Weather has many, many outcomes over a large area over a significant period of time. Change the initial weather conditions (humidity, wind flow, frontal position, upper level energy, etc) and you create more uncertainty. Factor in time and the probability becomes significantly higher. Unfortunately, when meteorologists attempt to use a data driven narrative to explain why something did or didn't happen, the emotional centers of the brain described above are not activated. The emotional centers of our brain are not activated when presented with probabilities. Our brains simplify the probability using a story (narrative) that we can relate to. If not, there is no nice and tidy story here for our brains to trigger an emotional response.  Simply put, we feel uneasy.

Instead, we favor more simplified stories like the folklore of the Ground Hog or the Old Farmers Almanac.  Without asking your brain subconsciously shrugs off probability and uncertainty narratives and replaces them with predictions and stories from the Old Farmers' Almanac or Punxsutawney Phil.

So why do we believe Ground Hog predictions? It makes us feel good.

2016 Nor'easter Snow Totals

Why is it so cold in Rome, Ohio?

Last winter, Rome, Ohio in Ashtabula County reached an unofficial state record low temperature of -39. Why is Rome, Ohio so cold compared to other rural locations?  It lies in a valley surrounded by higher elevation. The denser, colder air drains into the valley when the sky conditions are clear and the winds are relatively calm. The heavy snow cover also promotes more cold.

I emailed a variety of people within the National Weather Service asking why this temperature was not certified as the new state record low. Gerry Creager explains:

"In general (and there are others on here who can correct me if I'm wrong), US NWS, and climatological records are recorded by the National Weather Service Forecast Office with responsibility for that area, as well as the Operational Monitoring Branch of the Climate Prediction Center (http://www.cpc.ncep.noaa.gov/information/who_we_are/miss_analysis.shtml).

In addition, the various State Climatologists are responsible for their local data, and report to their own State, often as direct reports (at least on paper) to their Governor.
There are three networks of stations that might use for climate monitoring, including the Historical Climate Network, the Climate Reference Network, and the Federally maintained ASOS sensors usually found at airports. To the best of my knowledge, unofficial, and Citizen-Science sources are not included in monitoring extremes for records, but may be used, as they are in operational meteorology, as sanity checks for other observations. 

I believe you can pull the MADIS Mesonet records, and look at METARs as well. There are several climate data sets in there, but the ASOS data are present, as are the CWOP data. You might also want to peruse http://www.noaa.inel.gov/crn/crn.htm, and the NCDC holdings.

Note: This is based on my knowledge and interpretation due to my research, and some of the work I do with the CWOP servers. There are other folks, associated with the Federal side of CWOP and MADIS, included here, who can provide more authoritative data, perhaps."

Regards
Gerry Creager
4-22-2015

John Horel from NOAA reiterated the same ...

"Gerry covered the issue very well. It is very difficult to get the Climate Extremes Committee managed by NCDC to use networks beyond NWS/FAA.

See http://www.ncdc.noaa.gov/extremes/scec/records
for more details on the process, etc."

Regards
John

So it doesn't look promising that Rome, Ohio will officially break the all-time state low temperature record set back in 1899 in Milligan, Ohio

Winter Pattern Taking Shape

Back in September, I strongly speculated on the possible winter pattern. This was my initial outlook given the initial conditions and projections FOR DECEMBER back in September.  In reality, the southern jet stream hadn't established itself as a winter storm driver.

The position of the warmth was too far west for December.  The arctic air over the North Pole was very stable. The ridge was powerful across the east. Heavy rain and severe storms/deadly tornadoes during the month were common around Christmas.

On December 6th, I opined using videos (bottom half of the post at this link) showing the stronger position and intensity of the southern jet stream in January.

Our final winter outlook in late October echoed this southern panhandle storm track for the second half of winter

The extended models are this southern storm track (panhandle lows) as the dominant track through much of February.  Here are the snapshots on six periods of seven days each ending during the third week of February.

Most of the teleconnections (NAO, AO and PNA--EPO bouncing back a bit) showing troughiness in the east overall.

All of these factors seem to be the real deal which will lead to colder temperatures and higher chances of panhandle low type systems to interact with colder air leading to an eastward push of snow!

Lake Erie ice cover is nearly non-existent. Last year (before the record setting cold developed) ice cover was only 5% through the first 8 days of January. The current water temperature is still at 40 degrees.  The average water temperature is 35 on the 8th. Any cold outbreak like what we will see next week will aid in dropping the water temperature versus adding lake ice outside of the western basin where the water depth is shallow. Bottom line, lake effect snow is more possible January through March than in past years.