Precipitation and El Ninos: West Coast Rains Not Always A Lock

Not all El Ninos are alike. We've heard this time and time again. Sea surface temperatures are never exactly alike. Jet stream position varies. Overall winter temperatures vary too as does the location of above and below normal precipitation. We remember the El Nino of 1997-98 that produced heavy rains out west.  But that's not always the case.

We examine the top El Ninos according to the ONI Index from this site. We only examined the El Ninos that are ranked MODERATE, STRONG AND VERY STRONG.

THE STRONGEST EL NINOS (1997-98 and 1982-83)  

Storm track kept heaviest precipitation along the west coast and in the southeast.  At or below normal precipitation around the Great Lakes.

STRONG EL NINOS - RANK #3, #4 AND #5

Storm track is still strong in the deep south with a southerly shift out over the Gulf of Mexico with above normal precipitation.  Aside from the winter of 1957-58, precipitation along the west coast is less in these years. Still below normal precipitation across much of the Great Lakes.

MODERATE EL NINOS

Southern storm track is still strong but weaker during the winters of 1986-87 and 1963-64. Storm track shifted much further north into the Ohio Valley and Mid-Atlantic during the winters of 2002-03 and 2009-10 with heavy wet snows. During many of these winter, well below normal precipitation was observed along the west coast especially during the winter of 1963-64

Contrary to what you hear, its not a guarantee that El Ninos always produce heavy precipitation events across the west coast and the Pacific Northwest. It does appear that the chances are greater with stronger El Ninos per the ONI Index.  The southern storm track seems to be more consistent--with varying intensities--in each of top El Ninos. 

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A few side notes:

* Another modulator of the El Nino and storm track is the mode of the PDO (Pacific Multidecadal Oscillation). The winters of 1957-58, 86-87, 87-88, 97-98, 2002-03 and this year so far all have PDO values strongly positive.

* Yet another area of the Pacific that may have ties to the evolution of El Nino is the Pacific Meridional Mode located between the equator and Baja California. The link between the two is being studied. Here is a paper published in 2014.  Looking at the data from late summer through fall during early El Ninos, late 1957, 1986, 2009, 2015 (and partly 1982 although it was trending cooler) all had positive values (above normal water temperatures).

Do we see some matches above for this winter?  Hmmmm.

Northern Most Hurricane EVER!

Hurricane Joaquin is still churning out in the open Atlantic more than 14 days since it become a tropical depression on September 28th in the Caribbean.

The official track from the NHC has it sustaining tropical characteristics through the upcoming weekend as it tracks as it approaches Europe.

This had me wondering what the furthest NORTH any hurricane has traveled. The award goes to Hurricane Faith in 1966. This system started out off the coast of western Africa, headed toward the Caribbean then north off the coast of the U.S. then out to sea. It lasted 26 days and traveled more than 6800 miles. 

What I find fascinating is that according to the official track data (wind, position and date) it held hurricane strength over incredibly cold water. The hurricane crossed into water below 20 degrees Celsius off the coast of Nova Scotia yet it stayed at category 2 strength for another two and a half days.

WATER TEMPERATURE IN CELSIUS

The storm didn't officially weaken until it reached the north of Great Britain where the water temperatures dropped to between 10 and 12 degrees Celsius. The "X" marks the approximate location where Hurricane faith was downgraded to a tropical storm....yet it continued as an extra tropical storm/low into Scandinavia for another week!

The National Hurricane Center has a great summary on the hurricane season that year. They show a  map of Faith denoting its movement into the arctic north of the Arctic Circle into the Soviet Union then north into the Barents Sea where water temperatures were barely above freezing.

Air temperatures were in the 30s and 40s.

It finally ended its journey over an uninhabited island chain north of the Arctic Circle around 600 miles from the North Pole.

How Many Gallons of Water Fell over Parts of South Carolina?

Photo Courtesy: CNN.com

Some are calling this rain event a "Thousand Year Rain Event".



Many locations have received more than 20" of rain since Friday.  The final rainfall totals map here as of Tuesday 5:30am.

The National Weather Service office in Columbia, South Carolina has a great summary HERE. Eyeballing this map shows roughly seven counties with at least 15" across at least 90% of each county as of Sunday evening.

So how much rain in gallons is 15"?  A quick volume calculation will give us the answer: The area of the 7 county region (Richland, Sumter, Clarendon, Williamsburg, Berkeley, Calhoun and half of Charleston counties) is 10,317 square miles. Convert 15 inches into miles and you get 0.000237 miles. Multiply these together you get 2.44 cubic miles. Convert cubic miles into gallons and the answer is:

2,690,000,000,000 gallons (trillion)! 

This is DOUBLE the volume of Lake Okeechobee in Florida.

So image dumping Lake Okeechobee TWICE over these 7 counties over a 3 days period!

Human Nature and the Uncertainty in this Weekend Forecast

A hurricane off the east coast, strong cold front, gulf moisture, Atlantic moisture. These are just a few of the factors that will drive the rain and wind this weekend. In my opinion, one of the most difficult forecasts in recent memory.

The various computer projections are taking Hurricane Joaquin and the other tropical disturbances in all sorts of directions as it begins its interaction with the other variables above. Each line represents a different computer model representation of each outcome.  Are you confused yet? 

Our minds don't easily handle probability. We especially hate probabilities in our weather forecasts especially when confronted with a map like this.

Why is this?

For our minds to grasp probabilities, we need to be able to handle multiple possible outcomes at once. Just our luck. 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.

Typically, our brains work much better with a theme that is linear: A story that has a beginning, middle and an end. We want to visualize a line of showers that moves in at a specific time, stays for a select amount of time and then moves out without fanfare. Unfortunately, rain events rarely behave in this manner.

Much to the chagrin of the general public—probabilities are the only way to tell the weather story. We use 90% chance of rain, 40% chance of rain, etc. Yet if it doesn't rain over their house when the probability is 90% chance of rain, the forecaster is wrong even if the rest of the area was hit with a good downpour. We want to know if it will rain or not; a black and white scenario without caveats. Yet the behavior of some small scale weather events like warm frontal rain/storms can behave semi-independently of the overall large scale pattern. Meteorologist try to convey this idea on the air. Most of the time this falls on deaf ears.

It all goes back to basic human nature. A good weather narrative (a feel-good forecast with some folklore) is desired versus something data/science driven. Nebulous weather data and science makes most of us feel uncomfortable even if the on-air meteorologist has the best of intentions.

In recent years,  some highly sophisticated models of the atmosphere have been developed that can make some very good “probabilistic” outcomes for weather events. Yet a level of uncertainty still remains and we humans don’t like it!  We try to rationalize the irrational. Our biases quickly dismiss the probabilistic science as irrelevant or at the very worst, an excuse.

Instead, we favor more simplified stories even though that story might gloss over important details. Our minds involuntarily cherry-pick elements of the story so that it fits our biases. Think of a time when someone told you a weather fact or forecast which you didn’t believe. You felt uneasy. Your mind shrugged it aside only to be replaced by a story, forecast or explanation that made you feel better…accuracy be damned.

* Narratives (straight forward simple weather forecasts) are about hitting emotional buttons making the reader feel good by focusing on less qualitative aspects (weather science and probability) of an issue.

* Narratives (weather forecast) are/is about the outcome not the process (explanation of the science and probability)

* The process (weather science) is important in developing solid results

So remember the psychology. How you react when you hear a weather forecast?  Do you dismiss the science? How do you handle probability?  Do you like hearing an explanation to why the weather does what it does? Do you overly simplify the weather? Are you aware of your biases?

Cognitive Biases: How Do These Affect Your Decision Making?

Click on the image to maximize it.

The Upcoming Winter Weather (2015-16) MIGHT Look like This

North Country Public Radio

I'm thinking out loud today so bare with me.

Over the last few days, I was playing around with the constructed analogs of similar winter years. Using a set of 6 best fit years and weighting them equally, I constructed a blend for each month starting in November and ending with February showing the upper level pattern across the North American Continent. The color colors show where the storm system would develop (Low pressure). The warmer colors show where High Pressure systems reside.

The first burst of colder air occurs in November, the pattern relaxes in December then reloads after the first of the year. Can you see how the southern jet stream becomes very active, dominant force in the second half of the winter. February shows the much higher frequency and strength of low pressure systems from the southwest. This indicates a higher propensity for wetter snows from northern Texas, northeast into the Mid Atlantic states and Ohio Valley similar to 2010.


UPPER AIR PRESSURE (500 mB)

NOVEMBER BLEND

DECEMBER BLEND

JANUARY BLEND

FEBRUARY BLEND

SURFACE TEMPERATURES


Last winter's actual temperatures versus our Winter Outlook issued in October.  Not bad.

The overall temperatures for this winter according to the best matches are not as cold across the eastern 2/3rds of the US when compared to the winters of 2014-15 (recap of last winter at this link) or 2013-14.

NOVEMBER BLEND

DECEMBER BLEND

JANUARY BLEND

FEBRUARY BLEND

Snowfall departures (above or below average) are much higher in January and February during moderate to strong El Ninos especially when these El Ninos are more central based (Modoki, using the EMI Index). 

Will this strong El Nino have some central based signature tendencies? Maybe more eastern El Nino characteristics thus a warmer winter overall with little snow? 

The Constructive Analog from Huug van den Dool's page on the CPC site shows the core of the ENSO warmth in the ENSO 3.4 region with a slow drift WEST toward the Dateline by late winter.

Will this verify?  Only time will tell. 

Many meteorologists in the private sector don't like using the Analog Method too literally because the probability of finding an exact match over such a large area is incredibly small. I get that. However, I have found that analogs give a glimpse into how the atmosphere responds to the various drivers in closely matched years. This group of "best fits" for this winter has stayed consistent over the last several months.  Several notes: Analogs are only one of several tools that I use in assessing seasonal outlooks. El Nino is only one of the many factors that will play a role in our winter weather. I did not include any ENSO dynamic model guidance in this post. That is a story for another time.

Huge Rainfall Differences: Summer 2014 vs 2015

After the record setting rains of late spring early summer, conditions have dried out considerably for much of Ohio.  Look at the differences between last summer and this summer as we compare rainfall from June 1st through July 4th.

2014

2015

Who thought the deficit would this large two week from Labor Day given the overall pattern

A Deeper Look At The Top 10 El Ninos Since 1870

As this current El Nino continues to evolve, it helps to visualize how these changes in the tropical Pacific ocean temperatures drive the changes in the hemispheric circulation which impact our winter weather across the US.

How do we define an El Nino? The Climate Prediction Center uses the ONI (Oceanic Nino Index) to define El Nino and La Nina events. Their definition for El Nino/La Nina using the ONI is as follows:

An El Nino event is defined when the three month running mean of (ERSST.v4) sea surface temperature anomalies in the Niño 3.4 region climb above the threshold of 0.5^o for five consecutive overlapping three month periods.

In other words, we take the average ocean temperature anomaly in the 3.4 region over a 3 month period, say September through January.  Take the next five month overlapping periods--October through December and November through January--(the first two for example) and find these averages. That is your five consecutive, 3 month running mean. If this period's average is at or above +0.5 degrees, we classify this as an El Nino. The ERSST.v4 dataset goes back to 1850.  Using this methodology, the top 10 strongest E Ninos are easy to find. Hat tip to Eric Webb for compiling the ERSSTv4 data.

The top ten El Ninos are as follows:
1877-78, 1888-89, 1982-83, 1997-98, 1896-97, 1902-03, 1905-06, 1940-41, 1957-58, 1972-73
What do the sea surface temperatures for each of these El Ninos look like? I created an animation of each El Nino's six, three month overlapping period starting with the September-November period ending with the February-April period.  Each El Nino evolves differently. The position of the equatorial warm water, position and strength of the warm/cool pools in the PDO region are different with some, similar to others. Here is each sea surface temperature anomaly animation from the list above.

1877-78 El Nino

1888-89 El Nino

1982-83

1997-98

1896-97

1902-03

1905-06

1940-41

1957-58

1972-73

How does the atmosphere respond in each of these cases at the 300mB level?  More on this later.

What were the winter temperatures like in each of these strong (both eastern and central) El Ninos?


One glaring similarity is that each of these El Nino events (1888-89, 1940-41 and 1957-58) average temperatures across the eastern US stayed close or slightly above average in December and in January. Then in February, the bottom falls out and temperatures drop significantly below average across a large area of the east. If you look at the Pacific sea surface temperature configuration of these winters (eyeballing the ENSO region, Eastern Pacific/west coast/Gulf of Alaska regions and Pacific Meridional Mode area), they closely resemble this year!