What is Climate Variability?

Much of the work washed at IRI is related to climate variability, which is defined by the World Meteorological Organization as "variations in the mean land and other statistics of the climate on all temporal and spatial scales, beyond individual weather condition events." In simpler terms, variability is the range of climate compared to its average. The fluctuations comprising climate variability tin can influence patterns of rainfall, temperature and other variables on timescales anywhere from a few weeks to a few decades.

While the long-term trends of climate change are considered by scientists to be largely man-acquired, climate variability is more often than not due to natural oscillations in the earth'south systems (though there are some proposed exceptions). At its well-nigh cardinal, climate variability stems from the redistribution and changes in the amount of free energy around the earth, which lead to changes in pressure, temperature and other climate variables. The amount and movement of energy result from a multitude of factors, including those external to world'south organisation (e.chiliad. the corporeality of radiations emitted from the sunday) and internal (e.g. volcanic activity blocking some solar radiation from reaching the earth's surface). Thus the weather at any given place and time will exist influenced by a number of climate variability factors, some of which nosotros tin pinpoint, and some of which we take nevertheless to observe.

Figure 1: Annual rainfall in the Sahel from 1900 to 2006, adapted from Mason et al, 2015. The red dots indicate the yearly observations, so the red line indicates variation in climate from year to year (also know as interannual variability). ENSO (see below) is a major influence of interannual variability for many places, especially in the tropics. The blue line represents decadal variability, or the trends in climate that occur over the span of 10-30 years. These clusters of relatively wet or dry years can result in prolonged drought or flooding. The Sahel droughts of the 1970s and 80s show up at this timescale, indicated by the dip of the blue line in this graph. Sometimes trends on the decadal timescale can be counter to long-term trends (>30 years). While a long-term trend is apparent in this dataset (black line), long-term trends caused primarily by climate change are generally more apparent for temperature than rainfall, which tends to be more variable.

Effigy one: Almanac rainfall in the Sahel from 1900 to 2006, adapted from Mason et al, 2015. The ruby-red dots indicate the yearly observations, so the reddish line indicates variation in climate from year to year (besides know as interannual variability). ENSO (see below) is a major influence of interannual variability for many places, particularly in the tropics. The blueish line represents decadal variability, or the trends in climate that occur over the bridge of 10-30 years. These clusters of relatively wet or dry years can outcome in prolonged drought or flooding. The Sahel droughts of the 1970s and 80s show upward at this timescale, indicated by the dip of the bluish line in this graph. Sometimes trends on the decadal timescale tin can exist counter to long-term trends (>30 years). While a long-term tendency is apparent in this dataset (blackness line), long-term trends caused primarily by climate change are generally more apparent for temperature than rainfall, which tends to be more than variable.

One of the most well understood sources of climate variability is the tilt of the earth, which causes the seasonal changes in climate in the northern and southern hemispheres. Another major influence on climate variability is sea-surface temperatures (SSTs). The vast amount of energy held in our oceans ways that even slight changes in SSTs can shift certain climate patterns.

Scientists practise not always know how a chain of events plays out in the ocean and atmosphere. They can, however, employ statistical methods and physically-based climate models to notice links between, for example, SSTs in one area of the bounding main and patterns of wetter, drier, warmer or cooler climate in another area (unremarkably over land). When scientists find a correlation betwixt SSTs and a climate pattern (due east.k., Atlantic SSTs and western Amazon rainfall ), the possibility opens upward to utilize the SSTs to predict that climate pattern. Armed with an informative prediction, decision makers in climate-afflicted sectors like agriculture, health and disaster risk reduction tin apply the climate information to set up for a period of climate that is likely to be in a higher place or below normal.

I of the sources of internal climate variability about which scientists know the most is the El Nino-Southern Oscillation ( more on ENSO here ). But there are others, most of which are associated with higher or lower than normal body of water-surface temperatures or pressures in divers areas. Below are descriptions of some of the major climate variability oscillations scientists take identified. These are all oscillations that are presumed to be caused naturally and are internal to the earth's arrangement (i.e. not due to changes in incoming solar energy or greenhouse gas emissions).

ENSO

The El Niño-Southern Oscillation (ENSO) describes the natural year-to-yr variations in the sea and atmosphere in the tropical Pacific that lead to large-scale changes in sea-level pressures, sea-surface temperatures, precipitation and winds–not only in the tropics only beyond many other regions of the world. An El Niño land occurs when the central and eastern equatorial Pacific body of water-surface temperatures are essentially warmer than usual (come across Figure ane, meridian). La Niña weather condition (also part of the ENSO cycle) occur when the central and eastern equatorial Pacific waters are essentially cooler than usual (meet Figure 1, bottom).

The most direct effect s of ENSO on regional climate patterns are found in those areas closest to the tropical Pacific , but El Niño and La Niña are such powerful forces that they tin shift seasonal temperature a nd precipitation patterns around the globe. While scientists accept shown that the occurrence of floods, droughts and other climate-related disasters is not statistically different amidst years with El Niño, neutral or La Niña conditions , such disasters may be more predictable, allowing determination makers to take action and ready for such events. Much more than on ENSO hither.

Figure 2: Sea-surface temperature anomalies during a strong El Niño event (top) and La Niña event (bottom). Click image to enlarge. Source: http://iridl.ldeo.columbia.edu/maproom/ENSO/Diagnostics.html#tabs-2

Figure 2: Bounding main-surface temperature anomalies during a strong El Niño event (top) and La Niña upshot (bottom). Click image to enlarge. Source: IRI Data Library Maproom

PDO

Moving north a few thousand miles, the Pacific Decadal Oscillation is divers by sea surface temperature anomalies in the higher latitudes of the Pacific. While PDO also has a warm phase and absurd phase, the timescale on which PDO fluctuates is not equally defined as ENSO (information technology tin persist in either phase for anywhere from ten-40 years). During the warm, or positive, stage, the northwest Pacific is relatively cooler and the eastern Pacific warmer. The inverse pattern appears during the absurd, or negative, stage.

The term PDO was coined in 1996 past Steven Hare, a researcher studying the influence of the Pacific on Alaskan salmon fisheries. The coastal northwestern portion of North America sees some of the strongest impacts of PDO, with generally more rainfall during a positive PDO phase and less during a negative phase. Influence on climate in other parts of North America, likewise as Commonwealth of australia and India has been shown. Given its long phases and relatively contempo discovery, scientists don't know as much about the processes that give rise to these fluctuations compared to other climate variability sources. Areas of active research include its interaction with ENSO, role in the recent "global warming hiatus", and connection to variability in the Atlantic Ocean.

Figure 3: The two phases of PDO as exhibited by sea surface temperature patterns in the Pacific. Click image to enlarge. Source: source: http://research.jisao.washington.edu/pdo/graphics.html

Figure 3: The two phases of PDO equally exhibited past sea surface temperature patterns in the Pacific. Source: jisao.washington.edu

AMO

The Atlantic Multidecadal Oscillation (AMO) is a mode of variability divers by body of water surface temperatures in the N Atlantic. It is a longer-term source of variability, with just a few shifts between its warm and cool phases in the 20th century. Scientists accept linked information technology to temperature and rainfall patterns in North America and Europe, likewise as Brazil, the Sahel and India. Research also shows that the AMO  influences hurricane action in the Atlantic.

Figure 4: Atlantic Multidecadal Oscillation index computed as the linearly detrended North Atlantic sea surface temperature anomalies 1856-2013. Click image to enlarge. Source: https://en.wikipedia.org/wiki/Atlantic_multidecadal_oscillation

Figure iv: Atlantic Multidecadal Oscillation alphabetize computed every bit the linearly detrended North Atlantic sea surface temperature anomalies 1856-2013. Source.

NAO

The Due north Atlantic Oscillation (NAO) is measured by air pressure. Low pressure level generally resides over Greenland, while an surface area of high pressure camps out further s in the central North Atlantic. When NAO is in a positive phase, these areas of pressure are reinforced; the low pressure area is lower than its hateful, and the high is higher. When NAO is in a negative stage, each expanse of pressure level is weaker than normal. The NAO changes stage more frequently than many other climate oscillations, and it varies on timescales from days to decades to points in between. The positive stage unremarkably results in more frequent and stronger winter storms tracking across the Atlantic, and thus warm and wet winters in Europe. The negative phase corresponds with more cold outbreaks in the eastern U.s.a.. These are just a few of NAO's climate effects. More data on NAO is bachelor here.

Figure 5. Monthly values of the North Atlantic Oscillation Index. Source: https://www.climate.gov/news-features/understanding-climate/climate-variability-north-atlantic-oscillation

Figure 5. Monthly values of the Northward Atlantic Oscillation Index. Source: NOAA.

MJO

The Madden-Julian Oscillation (MJO) is a convective wave (i.e. an surface area of clouds, winds and rains) that propagates around the world, e'er from west to east and originating in the eastern Indian Ocean. It thus differs from the residual of the climate variability sources in this list, which all operate primarily in a smaller, defined area, though their furnishings tin be far-reaching.

MJO has 2 phases, one which produces enhanced convection and one which suppresses convection. So, as MJO moves around the globe, it brings with it both heavier rainfall and periods of dry out weather, returning to its origination signal after 30-60 days. The tropics run into the strongest effects, but MJO's influence can extend to higher latitudes likewise. More on MJO hither.

Figure 6: An animation illustrating the organization of the MJO into its enhanced and suppressed convective phases during an MJO event during the spring of 2005. The green shading denotes conditions favorable for large-scale enhanced rainfall, and the brown shading shows conditions unfavorable for rainfall. The MJO becomes organized during late March through May as the green shading covers one half of the planet, and brown shades the other half all along as these areas move west to east with time. Notice how the shading returns to the same location on the order of about 45 days. From NOAA/Jon Gottschalck.

Figure 6: An animation illustrating the organization of the MJO into its enhanced and suppressed convective phases during an MJO upshot during the spring of 2005. The green shading denotes conditions favorable for big-calibration enhanced rainfall, and the brown shading shows weather unfavorable for rainfall. The MJO becomes organized during late March through May equally the dark-green shading covers one one-half of the planet, and brown shades the other half all along every bit these areas motility west to e with time. Notice how the shading returns to the same location on the social club of about 45 days. From NOAA/Jon Gottschalck.