NOAA: Why do El Niño-Southern Oscillation (ENSO) Weather Forecasts Use Probabilities?
                
                                                                                                                                                                                                                                                                                                                           
                                                                                                                            Last Updated on Sunday, 22 June 2014 05:12                                                                                                                       
                                                                   June 19, 2014 - By Anthony Barnston - Many people are interested in  knowing which ENSO category (La Niña, neutral or El Niño) is expected by  the climate experts, just as they might want to know the weather  forecast for tomorrow.
 They usually prefer a simple answer—one  with little or no uncertainty. Unfortunately, however, weather and  climate forecasts are never about certainty: they’re about probability.  Using probabilities allows us to describe the uncertainty in  quantitative terms. If there were no uncertainty about what the climate  would be like in the future, then one outcome would be given a 100%  chance of occurring, while any other outcome(s) would have a 0% chance.  While probabilities near 0% and 100% often occur in astronomy and solid  state physics problems, they are virtually nonexistent in weather and  climate forecasting, due to the fluid and chaotic nature of the ocean  and the atmosphere.
Let’s take the example of the bar chart  below, showing the latest forecast probabilities for the three ENSO  categories for 3-month periods going out to early 2015, issued by  CPC/IRI on June 5. How should we interpret this chart?
For each  season forecasted, the heights of the three bars indicate the current  probabilities for La Niña (blue), ENSO-neutral (gray), and El Niño  (red). The sum of the three probabilities for each bar cluster must  always add to 100%, because no other outcomes are possible: the sea  surface temperature (SST) in the Niño3.4 region has to be either colder  than average by a sufficient amount (La Niña), warmer than average by a  sufficient amount (El Niño), or near average (neutral). Currently, the  official sufficient amount of deviation from average is 0.5?C.
For  all of the seasons being predicted in this particular forecast, El Niño  is the most likely category, with the red bars towering over the other  bars.  During the latter part of 2014 its probability is near or above  80%. This is a fairly confident forecast for El Niño, but it does still  leave about a 20% (1 in 5) chance of it not happening.
	
	
	
		
		
		
		
	
	
Vertical  bar histogram showing probabilities for La Niña, neutral, and El Niño  conditions for the remainder of 2014 and into early 2015. Dashed lines  show climatological (historical average) probabilities for these same  three ENSO conditions. Chart by NOAA Climate.gov, based on data provided  by IRI.
So what does historical probability tell us?
 An 80% chance is a pretty high probability, which means if the climate  were a betting game, we’d be wise to bet on El Niño. But what if the  models predicted that the odds of El Niño this winter were 50%? Should  we shrug that off?
This is where it helps to have a second kind  of information: the climatological probability—the average odds of El  Niño, La Niña, and neutral conditions based on how frequently they’ve  occurred over a long historical record.
When people envision  random chance (“we don't know”), they may think of a two-sided coin  flip, with each side having a 50% chance of occurring.  However, in the  case of ENSO forecasting there are three possible outcomes: El Niño,  neutral, and La Niña. Imagine a coin with a very thick edge, so that the  chances of getting heads, tails, or having the coin land on its edge  are all 33.3%. For any random coin toss—any given season we might  consider—intuition might tell us there is a 1 in 3 chance of it being an  El Niño season.  
While a 1 in 3 chance of El Niño, neutral, or  La Niña is a reasonable starting point for a “first guess” as to what we  might expect, observations from a recent 30-year period tell a somewhat  different story. Those baseline, or climatological probabilities, are  shown on the chart as dashed lines.
[HIGHLIGHT]As you can see in the figure,  the climatological probabilities are not flat, horizontal lines at  33.3% all year round. Rather, they vary noticeably by season. Looking at  the lines on the figure, we see that during NDJ  (November-December-January), the climatological probability for El Niño  or La Niña is higher than at any other time of the year, and exceeds 35%  for each, leaving less than a 30% likelihood for neutral ENSO. By  contrast, during the late spring and summer the reverse is true, as the  typical chance of neutral conditions exceeds 50%[/HIGHLIGHT].
[HIGHLIGHT]Any bar that is  greater than the dashed line of the same color (showing the  climatological probability) indicates a heightened chance of that ENSO  category occurring relative to the historical average. For example, in  the case of the second season being forecast in the figure (JJA), the  probability of El Niño is 69% (red bar), but the climatological  probability is only 26% (red line), meaning that the chance of it  occurring is considerably higher than average—more than double.
[/HIGHLIGHT]The  difference between the forecast probability and the climatological  probability, called theprobability anomaly (69% minus 26%, or 43% in  this example), can be important in decision-making, such as in the case  when El Niño is associated with drought and/or increased forest fire  danger. When a consequence is negative, the probability anomaly may be  as important as the actual probability in terms of preparedness for  adverse impacts.
[HIGHLIGHT]Going back to our hypothetical example, if the  probability of El Niño this winter were 50% instead of 80%, that would  still represent an increase of 24% above the historical average odds. If  we were trying to evaluate risk or vulnerability to an EL Niño-related  impact, it would help us to consider the odds within the longer-term  context[/HIGHLIGHT].
Why are the odds different in different seasons?
 This seasonal difference in the climatolological probabilities of El  Niño or La Niña is related to the fact that, during fall, the  year-to-year variability of the sea surface temperature (SST) in the  Niño3.4 region is usually larger than it is in the spring, so that  excursions below -0.5C or above 0.5C are more frequent in fall. This  seasonal change in the amount of variability is consistent with the fact  that that spring is often the time of year when El Niño or La Niña  events are either at their very beginning or have just ended, so the  SSTs tend to be closer to their average, while during fall and early  winter, ENSO events are in full swing and typically peak.
Although  an explanation of why ENSO events follow this seasonal cycle is not  fully known and is still being actively researched, facts that are  agreed to play a role are, first, that the normal SST in the Niño3.4  region follows a seasonal cycle in which it is warmest during April to  June each year, and coldest during November to January.
It is  thought that El Niño is encouraged to develop around May because it is  usually the basin’s warmest time of year. If other conditions are also  met—such as westerly low level wind anomalies that can warm the ocean  temperatures above their average, as we observed early this year—the  basin is already in a favorable, warm state.
As for why ENSO  events tend to dissipate about 9-12 months later, there is a theory  calledDelayed Oscillator Theory (Suarez and Schopf 1988), in which the  low-level westerly wind anomalies trigger two oceanic waves—first, a  Kelvin wave that moves to the east and increases the oceanic heat  content to the east of the anomalous wind location; and second, a Rossby  wave that moves to the west until it hits the Indonesia land mass. The  Rossby wave then reflects back toward the east as a “reverse” Kelvin  wave, and it acts to cool the subsurface. The cooling subsequently ends  the El Niño episode (and sometimes even triggers a La Niña event) about  10 months after it had begun.
 The nearly one year time duration  of the episode is due to the speeds of the two waves, and the distance  between the west and east boundaries of the equatorial Pacific  (Indonesia to South America). La Niña is thought to operate  approximately symmetrically oppositely to El Niño in these dynamics. It  should be noted that the “Delayed Oscillator Theory” is not the only  existing hypothesis explaining the typical duration of an ENSO event,  but it is one of the most actively researched. More detail about this  theory, with illustrative diagrams, is available on a number of links on  the Web, such as 
http://orca.rsmas.miami.edu/~melicie/dmodel1.htm.