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La Niña, did you orchestrate this?

This is a guest post by Dr. Ángel G. Muñoz who works at the Atmospheric and Oceanic Sciences Program at Princeton University and NOAA Geophysical Fluid Dynamics Laboratory. He focuses on the study of climate extremes and regional climate variability, predictability and model diagnostics, with an emphasis on Latin America and the Caribbean. 

Imagine an orchestra playing your favorite concerto or film score, each instrument contributing its share to the entire piece. Sometimes one of them seems to lead the others, to become soon after just another thread in the musical tapestry, no more important than any other instrument.

Like in concertos, sometimes ENSO (El Niño-Southern Oscillation, as climate scientists call the El Niño & La Niña phenomenon) seems to lead what we could call the “climate symphony,” especially during strong events like the 1988-89 La Niña, or the 1997-98 and 2015-16 Los Niños (the plural of “El Niño” in Spanish).

At other times, like the present weak La Niña, the competing effects of other climate phenomena can be so important that they modify the typical ENSO rainfall patterns in several parts of the world. If we are listening for a moment of dissonance in the climate concerto, let’s replay the score of South America’s rainfall last month, for example.

A Latin American La Niña symphony?

During a La Niña event, we expect above-normal rainfall in northern South America and below-normal rainfall in southeastern South America. And certainly, during December 2016, regions of Colombia and Venezuela, and northern Guyana and Suriname received above-normal precipitation (see the figure below). Although rain was abundant in the low-level plains of coastal Guyana, where 80% of its population lives, the other countries did not observe extreme rainfall events of importance. For example, Luis Alfonzo López, from Colombia’s National Met Service (IDEAM), recently told me that although they received above-normal precipitation in several places, the totals were not extreme.

Precipitation anomaly, Dec 2016

Rainfall anomalies (mm per month) observed in December 2016; green colors correspond to above-normal rainfall (opposite for brown colors). Normal is computed with respect to the period 1981-2010.

The situation was a bit different in southeastern South America, especially in the southern half of Paraguay and most of Uruguay, where above-normal rainfall conditions were observed—the opposite of what we’d expect during La Niña. Max Pastén, who works at the National Met Service of Paraguay (DINAC-DMH), confirmed that they did have extreme rainfall events that were not expected in this season, and especially during a La Niña. Indeed, although our forecast models from the North American Multi-Model Ensemble (NMME) correctly suggested above-normal rainfall for northern South America for December 2016, they predicted the typical La Niña-like below-normal precipitation for southeastern South America. 

Competing instruments

Is it possible that other climate patterns stood in opposition, or in the world of music, counterpointed (footnote 1), the La Niña signal in southeastern South America? Keep in mind that it is sometimes challenging to find ENSO’s thumbprint in a single month (December 2016) of climate anomalies because ENSO is a seasonal (3-month average) climate phenomenon, although its signal can still be in the background.  

When analyzing a month of data or less, sometimes a primary suspect for causing unusual climate conditions is the Madden-Julian Oscillation (MJO), an eastward-propagating area of storminess that modifies rainfall patterns as it travels around the world, completing a loop in 30-60 days (see Wheeler and Hendon, 2004). If, as I do, you tend to think that ENSO has two different faces (El Niño and La Niña), you might think that MJO has eight! Its eight different phases have distinctive rainfall signatures that you can see in this animation.

A quick analysis shows that Phase 6 was the most frequent one in December 2016; this phase is normally associated with below-normal precipitation for most of Uruguay and above-normal rainfall in parts of Paraguay and northern Argentina (see the figure below). Even though Phase 6 was the most common, the MJO strength was very weak or inactive in December. So we can rule out the MJO as a primary suspect in contributing to the precipitation in this region—its weakness is its alibi.

Precipitation anomaly during MJO Phase 6 in Dec 2016

Rainfall anomalies (in mm per day) associated with Phase 6 of MJO, based on historical observations. Colors and reference period are as in the first figure above.

We could also look at more regional phenomena in order to account for the increased precipitation. Two very important patterns of climate variability that impact southeastern South America’s rainfall basically all year around are the Southern Annular Mode (SAM), also known as the Antarctic Oscillation (AAO; see Marshall, 2003)—a pressure system surrounding Antarctica—and the South Atlantic Convergence Zone (SACZ)—a strong elongated region where winds meet across Brazil into the southwest Atlantic (see Carvalho et al., 2002, 2004).  In December, these two patterns (footnote 2) favored persistent wind circulations bringing moisture from the humid Amazon into southern Paraguay and neighboring regions (see the figure below), promoting intense rainfall events (see the first figure in this piece).

This counterpointing  (footnote 1) between ENSO and SACZ, SAM and other climate patterns is more common than one might expect; for details see Muñoz et al. (2015).

Recipe for a tune

As Emily Becker explained in the previous piece on this blog, it is not trivial to disentangle the role of each climate feature—each instrument in the symphony—because they affect each other in complex ways.

A simple way to illustrate how a competing climate signal can play up or play down the ENSO rainfall signal in a particular place is to imagine they have similar strength and consider how synchronized they are (see the figure below). For example, “constructive interference” occurs when they are both in phase (or in the same direction), in which case the rainfall anomaly typically associated with ENSO is enhanced by the presence of the second signal, and thus more pronounced extreme events could happen. Or the signals could be in opposition—destructive interference—and nullify each other, producing near-normal rainfall conditions. And of course, things could be a lot more complicated than these two scenarios, as the presence of a particular climate feature could modify the behavior of another, and vice-versa.

Suppose these interferences are occurring and impacting precipitation somewhere in the world, but we are only focused on the most commonly known, and usually stronger, ENSO signal. We would be expecting a typical El Niño or La Niña rainfall pattern but getting something else because we did not pay enough attention to or could not correctly account for the other signals. This is why it is so important for us that our forecast models can adequately capture these interactions. A better understanding of the global climate symphony and its better representation in our models will most likely provide more skillful predictions around the world.

Acknowledments

Thanks to Mariano Álvarez (CIMA), Luis Alfonso López (IDEAM), Max Pastén (DINAC) and the editors of this blog for useful discussion.

Lead Reviewer: Anthony Barnston, IRI

Footnotes

(1) In music, counterpoint refers to two (or more) melodies in combination with one another, or a melody and the orchestra played in conjunction with one another, and often forming a contrast. More generally, it pertains to a theme creating a contrast to a main element. In climate science, it can be used to describe a combination or interplay of two or more phenomena occurring together, creating a net result.

(2) Since the SACZ index is not available yet in real-time, the author used the relatively new CSIS index, kindly provided by Dr. Mariano Álvarez (CIMA-Universidad de Buenos Aires, Argentina). For details see Álvarez et al (2014).

References

Álvarez, M.S., Vera, C.S., Kiladis, G.N. et al. Clim Dyn (2014) 42: 3253. doi:10.1007/s00382-013-1872-z

Carvalho, L. M. V., C. Jones, and B. Liebmann, 2002: Extreme precipitation events in southeastern South America and large-scale convective patterns in the South Atlantic convergence zone. J. Climate, 15, 2377–2394, doi:10.1175/1520-0442(2002)015,2377: EPEISS.2.0.CO;2.

Carvalho, L. M. V., C. Jones, and B. Liebmann, 2004: The South Atlantic convergence zone: Intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall. J. Climate, 17, 88–108, doi:10.1175/1520-0442(2004)017,0088:TSACZI.2.0.CO;2.

Marshall, G. J., 2003: Trends in the southern annular mode from observations and reanalyses. J. Climate, 16, 4134–4143, doi:10.1175/1520-0442(2003)016,4134:TITSAM.2.0.CO;2.

Muñoz, Á. G., L. Goddard, A. W. Robertson, Y. Kushnir and W.Baethgen, 2015: Cross-time scale interactions and rainfall extreme events in southeastern South America for the Austral Summer. Part I: Potential predictors. J. Climate, 29, 5915-5934.

Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932, doi:10.1175/1520-0493(2004)132,1917:AARMMI.2.0.CO;2.

Comments

That was really fascinating, and a great explanation of a really complex discussion.

Hi Samuel. The drought in Bolivia si terrible. I'm so sorry. Note that I didn't formally address the case of Bolivia, though. Most of the seasonal forecasts we use are showing "no-signal" for Bolivia for February-April, which means it's unclear what will happen in the next three months in your country. Sorry I cannot offer a better forecast. You can see some of these products here: http://www.cpc.ncep.noaa.gov/products/NMME/seasanom.shtml http://www.cmc.org.ve/ole2/medianoplazo.php

I have a hotel in Paita Perú. we are experiencing El Niño rains when last year during El Niño we did not have these rains. So my question is what do we expect for rain down here in Paita for the next few months

Hi Scott. Thanks for your comment. I don't see a lot of rainfall over Paita during last December or even January. I'm using this product, available at the Latin American Observatory's Datoteca: http://datoteca.ole2.org/maproom/Sala_de_Mapas/Vigilancia-Map-2/Anomaly.html.es Probably there are differences with respect to what local stations in Paita are measuring?? (if so, let me know, as that is interesting). Anyway, I don't think the rains you're talking about can be physically linked to an El Niño. I'll need a more detailed analysis to understand what's going on in Paita, but if you want to know what the different seasonal products are suggesting for the next few months in terms of rainfall, you can check with SENAMHI, your local met service. These international products are available too: http://www.cpc.ncep.noaa.gov/products/NMME/seasanom.shtml (NMME) http://www.cmc.org.ve/ole2/medianoplazo.php (Latin American Observatory, IRI, EUROBRISA, ECMWF)

In reply to by Scott

Angel.I liked you post. This is something a tropical forecaster faces each day to do good forecasts. Everyday you have to see the MJO signal and the ENSO background signal (I should say that you have to hear at least two orchestras playing at the same time). Sometimes the two orchestras play the same partitures and complement each other: this means they collaborate each other. I remember this was the case in LA NIÑA 2011....but I have the doubt: it rained a lot of because of LA NIÑA or because of positive phase of MJO? Sometimes they play different partitures and they do not collaborate each other... destruction or like you mention in diplomatic terms: "destructive interference". For short range forecasts, you can see the signal but in case you have to do a long range seasonal forecast you can´t imagine how the MJO signal will be in three months.

Hi Humberto. Thanks for your comment. With respect to your doubt, I don't think we can easily decompose the signal in such a way that we can identify which climate mode (instrument in the orchestra) is responsible. If they are affecting each other in a weak way or if the signals are completely independent, we could use a couple of mathematical tricks; but if we are in the realm of "strong non-linear interactions" between the two (or more) signals, we say they are entangled, and isolating which one is causing --for example-- excess or lack of rainfall might not be possible at all.

This is a great post: right to the point and with great references. Thank you very much Angel. Greetings from Colombia!

Very important to explan the Central American case between two oceans plus MJO, I will use this for teaching

Thanks for discussion of the MJO and ENSO. In California we're focused on the ENSO, I liked the music metaphor and found it helpful. Now if only someone could explain the Ridiculous Resistant Ridge that vanished this but was present for the previous five years.

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