Climate variability

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Short description: Variation in climate beyond individual weather events


Climate variability is the term to describe variations in the mean state and other characteristics of climate (such as chances or possibility of extreme weather, etc.) "on all spatial and temporal scales beyond that of individual weather events."[1] Some of the variability does not appear to be caused systematically and occurs at random times. Such variability is called random variability or noise. On the other hand, periodic variability occurs relatively regularly and in distinct modes of variability or climate patterns.[2]

Over the years, the definitions of climate variability and the related term climate change have shifted. While the term climate change now implies change that is both long-term and of human causation, in the 1960s the word climate change was used for what we now describe as climate variability, that is, climatic inconsistencies and anomalies.[2]

Modes of variability

El Niño impacts
La Niña impacts

There are different modes of variability: recurring patterns of temperature or other climate variables. They are quantified with different indices. Much in the way the Dow Jones Industrial Average, which is based on the stock prices of 30 companies, is used to represent the fluctuations in the stock market as a whole, climate indices are used to represent the essential elements of climate. Climate indices are generally devised with the twin objectives of simplicity and completeness, and each index typically represents the status and timing of the climate factor it represents. By their very nature, indices are simple, and combine many details into a generalized, overall description of the atmosphere or ocean which can be used to characterize the factors which impact the global climate system.

A climate oscillation or climate cycle is any recurring cyclical oscillation within global or regional climate, and is a type of climate pattern. These fluctuations in atmospheric temperature, sea surface temperature, precipitation or other parameters can be quasi-periodic, often occurring on inter-annual, multi-annual, decadal, multidecadal, century-wide, millennial or longer timescales. They are not perfectly periodic and a Fourier analysis of the data does not give a sharp spectrum.

A prominent example is the El Niño Southern Oscillation, involving sea surface temperatures along a stretch of the equatorial Central and East Pacific Ocean and the western coast of tropical South America, but which affects climate worldwide.

Records of past climate conditions are recovered through geological examination of proxies, found in glacier ice, sea bed sediment, tree ring studies or otherwise.

El Niño–Southern Oscillation

El Niño–Southern Oscillation (ENSO) is a global coupled ocean-atmosphere phenomenon. El Niño and La Niña are important temperature fluctuations in surface waters of the tropical Eastern Pacific Ocean. The name El Niño, from the Spanish for "the little boy", refers to the Christ child, because the phenomenon is usually noticed around Christmas time in the Pacific Ocean off the west coast of South America.[3] La Niña means "the little girl".[4] Their effects on climate in the subtropics and the tropics are profound. The air pressure difference between Tahiti and Darwin fluctuates monthly or seasonally as the Southern Oscillation (SO). ENSO is a set of interacting parts of a single global system of coupled ocean-atmosphere climate fluctuations caused by oceanic and atmospheric circulation. ENSO is the most prominent known source of inter-annual variability in weather and climate around the world. The cycle occurs every two to seven years, with El Niño lasting nine months to two years within the longer term cycle,[5] though not all areas globally are affected. ENSO has signatures in the Pacific, Atlantic and Indian Oceans.

Madden–Julian oscillation

Note how the MJO moves eastward with time.

The Madden–Julian oscillation (MJO) is an equatorial traveling pattern of anomalous rainfall that is planetary in scale. It is characterized by an eastward progression of large regions of both enhanced and suppressed tropical rainfall, observed mainly over the Indian and Pacific Oceans. The anomalous rainfall is usually first evident over the western Indian Ocean, and remains evident as it propagates over the very warm ocean waters of the western and central tropical Pacific. This pattern of tropical rainfall then generally becomes very faint as it moves over the cooler ocean waters of the eastern Pacific, but reappears over the tropical Atlantic and Indian Oceans. The wet phase of enhanced convection and precipitation is followed by a dry phase where convection is suppressed. Each cycle lasts approximately 30–60 days. The MJO is also known as the 30 to 60-day oscillation, 30 to 60-day wave, or the intraseasonal oscillation.

North Atlantic oscillation (NAO)

Indices of the NAO are based on the difference of normalized sea level pressure (SLP) between Ponta Delgada, Azores and Stykkisholmur/Reykjavik, Iceland. The SLP anomalies at each station were normalized by division of each seasonal mean pressure by the long-term mean (1865–1984) standard deviation. Normalization is done to avoid the series being dominated by the greater variability of the northern of the two stations. Positive values of the index indicate stronger-than-average westerlies over the middle latitudes.[6]

Northern Annular Mode (NAM) or Arctic oscillation (AO)

The NAM, or AO, is defined as the first EOF of northern hemisphere winter SLP data from the tropics and subtropics.[clarification needed] It explains 23% of the average winter (December–March) variance, and it is dominated by the NAO structure in the Atlantic. Although there are some subtle differences from the regional pattern over the Atlantic and Arctic, the main difference is larger amplitude anomalies over the North Pacific of the same sign as those over the Atlantic. This feature gives the NAM a more annular (ring-shaped or zonally symmetric) structure.[6]

Pacific decadal oscillation (PDO)

The PDO is a pattern of Pacific climate variability that shifts phases on at least inter-decadal time scale, usually about 20 to 30 years. The PDO is detected as warm or cool surface waters in the Pacific Ocean, north of 20° N. During a "warm", or "positive", phase, the west Pacific becomes cool and part of the eastern ocean warms; during a "cool" or "negative" phase, the opposite pattern occurs. The mechanism by which the pattern lasts over several years has not been identified; one suggestion is that a thin layer of warm water during summer may shield deeper cold waters. A PDO signal has been reconstructed to 1661 through tree-ring chronologies in the Baja California area.

Interdecadal Pacific oscillation (IPO)

The Interdecadal Pacific oscillation (IPO or ID) displays similar sea surface temperature (SST) and sea level pressure patterns to the PDO, with a cycle of 15–30 years, but affects both the north and south Pacific. In the tropical Pacific, maximum SST anomalies are found away from the equator. This is quite different from the quasi-decadal oscillation (QDO) with a period of 8–12 years and maximum SST anomalies straddling the equator, thus resembling ENSO.

Examples

Many oscillations on different time-scales have been found or hypothesized. Here is a list of known or proposed climatic oscillations.[7][additional citation(s) needed]:

Some natural periodicities in the sun exist, and these may or may not show up as periodicities in climate:

Anomalies in oscillations sometimes occur when they coincide, as in the Arctic dipole anomaly (a combination of the Arctic and North Atlantic oscillations) and the longer-term Younger Dryas, a sudden non-linear cooling event that occurred at the onset of the current Holocene interglacial. In the case of volcanoes, large eruptions such as Mount Tambora in 1816, which led to the Year Without a Summer, typically cool the climate, especially when the volcano is located in the tropics. Around 70 000 years ago the Toba supervolcano eruption created an especially cold period during the ice age, leading to a possible genetic bottleneck in human populations. However, outgassing from large igneous provinces such as the Permian Siberian Traps can input carbon dioxide into the atmosphere, warming the climate. Triggering of other mechanisms, such as methane clathrate deposits as during the Paleocene-Eocene Thermal Maximum, increased the rate of climatic temperature change and oceanic extinctions.

Another longer-term near-millennial oscillation involves the Dansgaard-Oeschger cycles, occurring on roughly 1,500-year cycles during the last glacial maximum. They may be related to the Holocene Bond events, and may involve factors similar to those responsible for Heinrich events.

Origins and causes

There are close correlations between Earth's climate oscillations and astronomical factors (barycenter changes, solar variation, cosmic ray flux, cloud albedo feedback, Milankovic cycles), and modes of heat distribution between the ocean-atmosphere climate system. In some cases, current, historical and paleoclimatological natural oscillations may be masked by significant volcanic eruptions, impact events, irregularities in climate proxy data, positive feedback processes or anthropogenic emissions of substances such as greenhouse gases.[15]

Effects

Extreme phases of short-term climate oscillations such as ENSO can result in characteristic patterns of floods and droughts (including megadroughts), monsoonal disruption and extreme temperatures in the form of heat waves and cold waves. Shorter-term climate oscillations typically do not directly result in longer-term climate change in temperatures. However, the effects of underlying climate trends such as recent global warming and oscillations can be cumulative to global temperature, producing shorter-term fluctuations in the instrumental and satellite temperature records.

Collapses of past civilizations such as the Maya may be related to cycles of precipitation, especially drought, that in this example also correlates to the Western Hemisphere Warm Pool.

One example of possible correlations between factors affecting the climate and global events, popular with the media, is a 2003 study on the correlation between wheat prices and sunspot numbers.[18]

Analysis and uncertainties

Radiative forcings and other factors in a climate oscillation must obey the laws of atmospheric thermodynamics. However, because Earth's climate is inherently a complex system, simple Fourier analysis or climate modelling often does not create a perfect replication of the observed or inferred conditions. No climate cycle is found to be perfectly periodic, although the Milankovich cycles (based on multiple superimposed orbital cycles and Earth's precession) are quite close to being periodic (perhaps almost periodic?).

One difficulty in detecting climate cycles is that the Earth's climate has been changing in non-cyclic ways over most paleoclimatological timescales. For instance, we are now in a period of anthropogenic global warming. In a larger timeframe, the Earth is emerging from the latest ice age, cooling from the Holocene climatic optimum and warming from the so-called "Little Ice Age", which means that climate has been constantly changing over the last 15,000 years or so. During warm periods, temperature fluctuations are often of a lesser amplitude. The Pleistocene period, dominated by repeated glaciations, developed out of more stable conditions in the Miocene and Pliocene climate. Holocene climate has been relatively stable. All of these changes complicate the task of looking for cyclical behavior in the climate.

Positive feedback, negative feedback, and ecological inertia from the land-ocean-atmosphere system often attenuate or reverse smaller effects, whether from orbital forcings, solar variations or changes in concentrations of greenhouse gases. Most climatologists recognize the existence of various tipping points that push small forcings beyond a certain threshold that makes the change irreversible while the forcings are still in place. Certain feedbacks involving processes such as clouds are also uncertain; for contrails, natural cirrus clouds, oceanic dimethyl sulfide and a land-based equivalent, competing theories exist concerning effects on climatic temperatures, for example contrasting the Iris hypothesis and CLAW hypothesis.

Through geologic and historical time

Climate change over the past 65 million years, using proxy data including Oxygen-18 ratios from foraminifera.
Temperature change over the past 12 000 years, from various sources. The thick black curve is an average.

Various climate forcings are typically in flux throughout geologic time, and some processes of the Earth's temperature may be self-regulating. For example, during the Snowball Earth period, large glacial ice sheets spanned to Earth's equator, covering nearly its entire surface, and very high albedo created extremely low temperatures, while the accumulation of snow and ice likely removed carbon dioxide through atmospheric deposition. However, the absence of plant cover to absorb atmospheric CO2 emitted by volcanoes meant that the greenhouse gas could accumulate in the atmosphere. There was also an absence of exposed silicate rocks, which use CO2 when they undergo weathering. This created a warming that later melted the ice and brought Earth's temperature back to equilibrium. During the following eons of the Paleozoic, cosmic ray flux and occasional nearby supernova explosions (one hypothesis for the cause of the Ordovician–Silurian extinction event) and gamma ray bursts may have induced ice ages or other sudden climate changes.

Throughout the Cenozoic, multiple climate forcings led to warming and cooling of the atmosphere, which led to the early formation of the Antarctic ice sheet, subsequent melting, and its later reglaciation. The temperature changes occurred somewhat suddenly, at carbon dioxide concentrations of about 600–760 ppm and temperatures approximately 4 °C warmer than today. During the Pleistocene, cycles of glaciations and interglacials occurred on cycles of roughly 100,000 years, but may stay longer within an interglacial when orbital eccentricity approaches zero, as during the current interglacial. Previous interglacials such as the Eemian phase created temperatures higher than today, higher sea levels, and some partial melting of the West Antarctic ice sheet. The warmest part of the current interglacial occurred during the early Holocene Optimum, when temperatures were a few degrees Celsius warmer than today, and a strong African Monsoon created grassland conditions in the Sahara during the Neolithic Subpluvial. Since that time, several cooling events have occurred, including:

In contrast, several warm periods have also taken place, and they include but are not limited to:

Certain effects have occurred during these cycles. For example, during the Medieval Warm Period, the American Midwest was in drought, including the Sand Hills of Nebraska which were active sand dunes. The black death plague of Yersinia pestis also occurred during Medieval temperature fluctuations, and may be related to changing climates.

Given that records of solar activity are accurate, solar activity may have contributed to part of the modern warming that peaked in the 1930s, in addition to the 60-year temperature cycles that result in roughly 0.5 °C of warming during the increasing temperature phase. However, solar cycles fail to account for warming observed since the 1980s to the present day [citation needed]. Events such as the opening of the Northwest Passage and recent record low ice minima of the modern Arctic shrinkage have not taken place for at least several centuries, as early explorers were all unable to make an Arctic crossing, even in summer. Shifts in biomes and habitat ranges are also unprecedented, occurring at rates that do not coincide with known climate oscillations [citation needed]. The extinction of many tropical amphibian species, especially in cloud forests, have been attributed to changing global temperatures, fungal disease and possible influence from unusually extreme phases of oceanic climate oscillations.

See also

Books and reports

References

  1. IPCC AR5 WG1 Glossary 2013, p. 1451.
  2. 2.0 2.1 Rohli & Vega 2018, p. 274.
  3. "El Niño Information". http://www.dfg.ca.gov/mrd/elnino.html. 
  4. "La Niña.". http://library.advanced.org/20901/la_nina.htm. Retrieved 27 May 2018. 
  5. Climate Prediction Center (December 19, 2005). "ENSO FAQ: How often do El Niño and La Niña typically occur?". National Centers for Environmental Prediction. http://www.cpc.noaa.gov/products/analysis_monitoring/ensostuff/ensofaq.shtml#HOWOFTEN. Retrieved July 26, 2009. 
  6. 6.0 6.1 National Center for Atmospheric Research. Climate Analysis Section. Retrieved on June 7, 2007.
  7. "El Niño & Other Oscillations". https://www.whoi.edu/main/topic/el-nino-other-oscillations. 
  8. "What is the MJO, and why do we care? | NOAA Climate.gov" (in en). https://www.climate.gov/news-features/blogs/enso/what-mjo-and-why-do-we-care. 
  9. Baldwin, M. P.; Gray, L. J.; Dunkerton, T. J.; Hamilton, K.; Haynes, P. H.; Randel, W. J.; Holton, J. R.; Alexander, M. J. et al. (2001). "The quasi-biennial oscillation" (in en). Reviews of Geophysics 39 (2): 179–229. doi:10.1029/1999RG000073. Bibcode2001RvGeo..39..179B. https://semanticscholar.org/paper/9932e0c6bf0e61c76c018147e607ffd86d40a886. 
  10. Wang, Chunzai (2018). "A review of ENSO theories" (in en). National Science Review 5 (6): 813–825. doi:10.1093/nsr/nwy104. ISSN 2095-5138. 
  11. Bruun, John T.; Allen, J. Icarus; Smyth, Timothy J. (2017). "Heartbeat of the Southern Oscillation explains ENSO climatic resonances" (in en). Journal of Geophysical Research: Oceans 122 (8): 6746–6772. doi:10.1002/2017JC012892. ISSN 2169-9291. Bibcode2017JGRC..122.6746B. 
  12. Newman, Matthew; Alexander, Michael A.; Ault, Toby R.; Cobb, Kim M.; Deser, Clara; Di Lorenzo, Emanuele; Mantua, Nathan J.; Miller, Arthur J. et al. (2016). "The Pacific Decadal Oscillation, Revisited". Journal of Climate 29 (12): 4399–4427. doi:10.1175/JCLI-D-15-0508.1. ISSN 0894-8755. Bibcode2016JCli...29.4399N. https://semanticscholar.org/paper/1e3e1bdf5cdb64c6f6d414139dbebb607c124aef. 
  13. "Interdecadal Pacific Oscillation" (in en). 2016-01-19. https://www.niwa.co.nz/node/111124. 
  14. Kuijpers, Antoon; Bo Holm Jacobsen; Seidenkrantz, Marit-Solveig; Knudsen, Mads Faurschou (2011). "Tracking the Atlantic Multidecadal Oscillation through the last 8,000 years" (in en). Nature Communications 2: 178–. doi:10.1038/ncomms1186. ISSN 2041-1723. PMID 21285956. Bibcode2011NatCo...2..178K. 
  15. 15.0 15.1 Scafetta, Nicola (May 15, 2010). "Empirical evidence for a celestial origin of the climate oscillations". Journal of Atmospheric and Solar-Terrestrial Physics 72: 951–970. doi:10.1016/j.jastp.2010.04.015. Bibcode2010JASTP..72..951S. http://www.fel.duke.edu/~scafetta/pdf/scafetta-JSTP2.pdf. Retrieved 20 July 2011. 
  16. 16.0 16.1 16.2 16.3 https://pubs.usgs.gov/fs/fs-0095-00/fs-0095-00.pdf United States Geological Survey - The Sun and Climate
  17. National Institutes of Health - The sunspot cycle no. 24 in relation to long term solar activity variation
  18. Sunspot activity impacts on crop success New Scientist, 18 Nov. 2004

External links

cs:Variabilita klimatu et:Kliimatsüklid fa:نوسان اقلیم fr:Oscillation climatique ja:気候サイクル ms:Pengayunan iklim zh:气候振荡





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