Guest Post by Willis Eschenbach
In a recent post here on WattsUpWithThat, the claim was made that the El Nino influences rainfall. They showed a correlation between various historical proxies and El Nino/La Nina. So I thought I’d take a look at the modern correlation between rainfall and the El Nino. As a measurement of the El Niño, I’m using the Oceanic Nino Index (ONi).
So, what is the ONI when it’s at home? NOAA says:
Oceanic Nino Index
The Oceanic Nino Index (ONI) is one of the primary indices used to monitor the El Nino-Southern Oscillation (ENSO). The ONI is calculated by averaging sea surface temperature anomalies in an area of the east-central equatorial Pacific Ocean, which is called the Nino-3.4 region (5S to 5N; 170W to 120W). Also, a 3-month time average (running mean) is calculated in order to better isolate variability closely related to the ENSO phenomenon.
OK … although I don’t like the 3-month boxcar filter (running mean). It is known to do things like reverse the peaks and valleys of a dataset, and is a horrible choice. So I’ve used the un-averaged version of the ONI
Now, I’ve written about the relationship between temperature and rainfall before, in “Cooling and Warming, Clouds and Thunderstorms” and in “How Thunderstorms Beat The Heat” The TLDR version is that over the ocean, where most of the rain falls, the rainfall amounts go up with increasing temperature. The evaporation of the water to make rain is one of the major mechanisms that keeps the ocean from overheating.
But I digress, I’m here to discuss the El Niño and the Oceanic Nino Index. The paper made a curious claim, that La Nina conditions were wetter, and El Nino conditions were dryer. Here’s the graphic from their paper:
Figure 1, with Original Caption
Now I was born yesterday, but having lived in the South Pacific I do know that there is no general rainfall rule for El Nino and La Nina. Some places like Southern California get wetter in an El Nino year, and some places like Australia get drier. So I found it odd that they identified “wetter” with La Nina and “drier” with El Nino. I thought I’d look at the correlation between the amount of rainfall and the Oceanic Nino Index (ONI). Figure 2 shows that result. A positive correlation (yellow to red) means that a high ONI index (El Nino condition) is accompanied by increased rain. A negative correlation (green and blue), on the other hand, means the opposite—there is less rain during El Nino conditions. The correlation (both positive and negative) with rainfall is at a maximum three months after the change in the ONI.
Figure 2. Correlation of the monthly Oceanic Nino Index (ONI) with the amount of monthly rainfall, 2000-2015. Red box shows the area which is represented by the ONI. Red/white circles show the locations of the proxies shown in Figure 1.
This shows what I started out by saying, which was that an El Nino increases the rain in Southern California and decreases the rain in Australia. In other words, we cannot say “Wet/La Niña-like” or “Dry/El Niño-like” as the authors do.
It also shows the idiosyncratic and convoluted nature of the area of positive and negative correlation. For example, the ONI is generally positive correlated with the northern hemisphere rainfall, and negatively correlated with southern hemisphere rainfall.
Now, the authors of the study say:
The composite record shows pronounced shifts in monsoon rainfall that are antiphased with precipitation records for East Asia and the central-eastern equatorial Pacific. These meridional and zonal patterns are best explained by a poleward expansion of the Australasian Intertropical Convergence Zone and weakening of the Pacific Walker circulation (PWC) between ~1000 and 1500 CE.
I see no need to invoke any such special mechanisms to explain rainfall shifts that are “antiphased” to rainfall shifts in other areas. From an examination of Figure 2 above, such antiphasing is the rule rather than the exception. In La Niña times California gets drier, Australia gets wetter, and the world goes on.
Regards to all on a sunny evening,
My Usual Request: Misunderstandings can be avoided. If you disagree with me or anyone, please quote the exact words you disagree with, so we can all understand the exact nature of your objections. I can defend my own words. I cannot defend someone else’s interpretation of some unidentified words of mine.
My Other Request: If you believe that e.g. I’m using the wrong method or the wrong dataset, please educate me and others by demonstrating the proper use of the right method or the right dataset. Simply claiming I’m wrong about methods doesn’t advance the discussion unless you can point us to the right way to do it.