Books: 'Variabilita interannuale'

1

James, Philip B. Interannual variability of Mars' south polar cap. St. Louis, Mo: Physics Dept., University of Missouri--St. Louis, 1987.

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2

Bell, Gerald D. Interseasonal and interannual variability--1986 to 1993. Camp Springs, MD: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1995.

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3

Nicholson, Sharon E. Atlas of African rainfall and its interannual variability. Tallahasee, Fla: Florida State University, Department of Meteorology, 1988.

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4

La Viollette, Paul E., ed. Seasonal and Interannual Variability of the Western Mediterranean Sea. Washington, D. C.: American Geophysical Union, 1994. http://dx.doi.org/10.1029/ce046.

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5

E, La Violette Paul, ed. Seasonal and interannual variability of the western Mediterranean Sea. Washington, DC: American Geophysical Union, 1994.

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6

Chiodi, Andrew M. Characterizing the interannual variability of the equatorial Pacific: An OLR perspective. Seattle, WA: Pacific Marine Environmental Laboratory, 2008.

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7

V, Ramesh K. Time-mean oceanic response and interannual variability in a global ocean GCM simulation. Pune: Indian Institute of Tropical Meteorology, 2003.

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8

L, Stanford J., ed. Spectral analyses, climatology and interannual variability of Nimbus-7 TOMS version 6 total column ozone. Washington D.C: National Aeronautics and Space Administration, 1995.

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9

1938-, Stanford John L., and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch, eds. Spectral analyses, climatology, and interannual variability of Nimbus-7 TOMS version 6 total column ozone. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1995.

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10

C, Bridger Alison F., Haberle Robert M, and United States. National Aeronautics and Space Administration., eds. Intraseasonal and interannual variability of Mars' present climate: A NASA Ames Research Center joint research interchange, final report : University Consortium Agreement: NCC2-5094, project duration: 25 August 1994-24 February 1996. [Washington, DC: National Aeronautics and Space Administration, 1996.

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11

Friederichs, Petra. Interannuelle und Dekadische Variabilität der Atmosphärischen Zirkulation in Gekoppelten und SST-Getriebenen GCM-Experimenten. Bonn: Asgard Verlag, 2000.

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12

Levitus, Sydney. NOAA Atlas NESDIS 16: Climatological and interannual variability of temperature, heat storage, and rate storage in the upper ocean. Silver Spring, Maryland (1315 East-West Highway, Silver Spring 20910-3282): National Oceanographic Data Center, User Services Branch, 1997.

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13

United States. National Aeronautics and Space Administration., ed. Interannual variation of seasonal means and subseasonal variability of cloud streets off the east coast of North America, 1984-1987. [Greeley, Colo.]: Univ. of Northern Colorado, Geography Dept., 1990.

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14

United States. National Oceanic and Atmospheric Administration., ed. CLIMATOLOGICAL AND INTERANNUAL VARIABILITY OF TEMPERATURE, HEAT STORAGE, AND RATE OF HEAT STORAGE IN THE UPPER OCEAN... NOAA ATLAS NESDIS 16. [S.l: s.n., 1998.

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15

Organization, World Meteorological, World Climate Research Programme, Monsoon Numerical Experimentation Group, and Workshop on Simulation of Interannual and Intraseasonal Monsoon Variability (1991 : Boulder, Colo.), eds. Simulation of interannual and intraseasonal monsoon variability: Report of workshop, National Center for Atmospheric Research, Boulder,Colorado, U.S.A., 21-24 October 1991. [Geneva, Switzerland]: World Meteorological Organization, 1992.

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16

Broughton, Betsy. General trends and interannual variability in prey selection by larval cod and haddock from the southern flank of Georges Bank, May 1993-1999. Woods Hole, Mass: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Northeast Fisheries Science Center, 2010.

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17

National Aeronautics and Space Administration (NASA) Staff. Intraseasonal and Interannual Variability of Mars Present Climate. Independently Published, 2018.

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18

Violette, Paul E. La. Seasonal and Interannual Variability of the Western Mediterranean Sea. Wiley & Sons, Limited, John, 2013.

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19

Kucharski, Fred, and Muhammad Adnan Abid. Interannual Variability of the Indian Monsoon and Its Link to ENSO. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.615.

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The interannual variability of Indian summer monsoon is probably one of the most intensively studied phenomena in the research area of climate variability. This is because even relatively small variations of about 10% to 20% from the mean rainfall may have dramatic consequences for regional agricultural production. Forecasting such variations months in advance could help agricultural planning substantially. Unfortunately, a perfect forecast of Indian monsoon variations, like any other regional climate variations, is impossible in a long-term prediction (that is, more than 2 weeks or so in advance). The reason is that part of the atmospheric variations influencing the monsoon have an inherent predictability limit of about 2 weeks. Therefore, such predictions will always be probabilistic, and only likelihoods of droughts, excessive rains, or normal conditions may be provided. However, even such probabilistic information may still be useful for agricultural planning. In research regarding interannual Indian monsoon rainfall variations, the main focus is therefore to identify the remaining predictable component and to estimate what fraction of the total variation this component accounts for. It turns out that slowly varying (with respect to atmospheric intrinsic variability) sea-surface temperatures (SSTs) provide the dominant part of the predictable component of Indian monsoon variability. Of the predictable part arising from SSTs, it is the El Niño Southern Oscillation (ENSO) that provides the main part. This is not to say that other forcings may be neglected. Other forcings that have been identified are, for example, SST patterns in the Indian Ocean, Atlantic Ocean, and parts of the Pacific Ocean different from the traditional ENSO region, and springtime snow depth in the Himalayas, as well as aerosols. These other forcings may interact constructively or destructively with the ENSO impact and thus enhance or reduce the ENSO-induced predictable signal. This may result in decade-long changes in the connection between ENSO and the Indian monsoon. The physical mechanism for the connection between ENSO and the Indian monsoon may be understood as large-scale adjustment of atmospheric heatings and circulations to the ENSO-induced SST variations. These adjustments modify the Walker circulation and connect the rising/sinking motion in the central-eastern Pacific during a warm/cold ENSO event with sinking/rising motion in the Indian region, leading to reduced/increased rainfall.

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20

Levitus, Sydney, John Antonov, and Timothy P. Boyer. World Ocean Atlas: 1994 Interannual Variability of Upper Ocean Thermal Structure. Diane Pub Co, 1994.

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21

National Aeronautics and Space Administration (NASA) Staff. Seasonal and Interannual Variability of the Budgets of N2o and Ccl3f. Independently Published, 2018.

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22

Purdy, Meghan. The interannual variability of carbon monoxide transport pathways to the Arctic. 2009, 2009.

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23

Numerical investigation on wind induced interannual variability of the North Indian Ocean SST. Pune: [Indian Institute of Tropical Meteorology], 1999.

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24

Bilbao, Pablo A. Interannual and interdecadal variability in the timing and strength of the spring transitions along the United States west coast. 1999.

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25

Bakun, Andrew. Applications of maritime data to the study of surface forcing of seasonal and interannual ocean variability in eastern boundary regions. 1987.

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26

Goswami, B. N., and Soumi Chakravorty. Dynamics of the Indian Summer Monsoon Climate. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.613.

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Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.

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27

Norrgård, Stefan. Changes in Precipitation Over West Africa During Recent Centuries. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.536.

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Water, not temperature, governs life in West Africa, and the region is both temporally and spatially greatly affected by rainfall variability. Recent rainfall anomalies, for example, have greatly reduced crop productivity in the Sahel area. Rainfall indices from recent centuries show that multidecadal droughts reoccur and, furthermore, that interannual rainfall variations are high in West Africa. Current knowledge of historical rainfall patterns is, however, fairly limited. A detailed rainfall chronology of West Africa is currently only available from the beginning of the 19th century. For the 18th century and earlier, the records are still sporadic, and an interannual rainfall chronology has so far only been obtained for parts of the Guinea Coast. Thus, there is a need to extend the rainfall record to fully understand past precipitation changes in West Africa.The main challenge when investigating historical rainfall variability in West Africa is the scarcity of detailed and continuous data. Readily available meteorological data barely covers the last century, whereas in Europe and the United States for example, the data sometimes extend back two or more centuries. Data availability strongly correlates with the historical development of West Africa. The strong oral traditions that prevailed in the pre-literate societies meant that only some of the region’s history was recorded in writing before the arrival of the Europeans in the 16th century. From the 19th century onwards, there are, therefore, three types of documents available, and they are closely linked to the colonization of West Africa. These are: official records started by the colonial governments continuing to modern day; regular reporting stations started by the colonial powers; and finally, temporary nongovernmental observations of various kinds. For earlier periods, the researcher depends on noninstrumental observations found in letters, reports, or travel journals made by European slave traders, adventurers, and explorers. Spatially, these documents are confined to the coastal areas, as Europeans seldom ventured inland before the mid-1800s. Thus, the inland regions are generally poorly represented. Arabic chronicles from the Sahel provide the only source of information, but as historical documents, they include several spatiotemporal uncertainties. Climate researchers often complement historical data with proxy-data from nature’s own archives. However, the West African environment is restrictive. Reliable proxy-data, such as tree-rings, cannot be exploited effectively. Tropical trees have different growth patterns than trees in temperate regions and do not generate growth rings in the same manner. Sediment cores from Lake Bosumtwi in Ghana have provided, so far, the best centennial overview when it comes to understanding precipitation patterns during recent centuries. These reveal that there have been considerable changes in historical rainfall patterns—West Africa may have been even drier than it is today.

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28

Hameed, Saji N. The Indian Ocean Dipole. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.619.

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Discovered at the very end of the 20th century, the Indian Ocean Dipole (IOD) is a mode of natural climate variability that arises out of coupled ocean–atmosphere interaction in the Indian Ocean. It is associated with some of the largest changes of ocean–atmosphere state over the equatorial Indian Ocean on interannual time scales. IOD variability is prominent during the boreal summer and fall seasons, with its maximum intensity developing at the end of the boreal-fall season. Between the peaks of its negative and positive phases, IOD manifests a markedly zonal see-saw in anomalous sea surface temperature (SST) and rainfall—leading, in its positive phase, to a pronounced cooling of the eastern equatorial Indian Ocean, and a moderate warming of the western and central equatorial Indian Ocean; this is accompanied by deficit rainfall over the eastern Indian Ocean and surplus rainfall over the western Indian Ocean. Changes in midtropospheric heating accompanying the rainfall anomalies drive wind anomalies that anomalously lift the thermocline in the equatorial eastern Indian Ocean and anomalously deepen them in the central Indian Ocean. The thermocline anomalies further modulate coastal and open-ocean upwelling, thereby influencing biological productivity and fish catches across the Indian Ocean. The hydrometeorological anomalies that accompany IOD exacerbate forest fires in Indonesia and Australia and bring floods and infectious diseases to equatorial East Africa. The coupled ocean–atmosphere instability that is responsible for generating and sustaining IOD develops on a mean state that is strongly modulated by the seasonal cycle of the Austral-Asian monsoon; this setting gives the IOD its unique character and dynamics, including a strong phase-lock to the seasonal cycle. While IOD operates independently of the El Niño and Southern Oscillation (ENSO), the proximity between the Indian and Pacific Oceans, and the existence of oceanic and atmospheric pathways, facilitate mutual interactions between these tropical climate modes.

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29

Nash, David. Changes in Precipitation Over Southern Africa During Recent Centuries. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.539.

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Precipitation levels in southern Africa exhibit a marked east–west gradient and are characterized by strong seasonality and high interannual variability. Much of the mainland south of 15°S exhibits a semiarid to dry subhumid climate. More than 66 percent of rainfall in the extreme southwest of the subcontinent occurs between April and September. Rainfall in this region—termed the winter rainfall zone (WRZ)—is most commonly associated with the passage of midlatitude frontal systems embedded in the austral westerlies. In contrast, more than 66 percent of mean annual precipitation over much of the remainder of the subcontinent falls between October and March. Climates in this summer rainfall zone (SRZ) are dictated by the seasonal interplay between subtropical high-pressure systems and the migration of easterly flows associated with the Intertropical Convergence Zone. Fluctuations in both SRZ and WRZ rainfall are linked to the variability of sea-surface temperatures in the oceans surrounding southern Africa and are modulated by the interplay of large-scale modes of climate variability, including the El Niño-Southern Oscillation (ENSO), Southern Indian Ocean Dipole, and Southern Annular Mode.Ideas about long-term rainfall variability in southern Africa have shifted over time. During the early to mid-19th century, the prevailing narrative was that the climate was progressively desiccating. By the late 19th to early 20th century, when gauged precipitation data became more readily available, debate shifted toward the identification of cyclical rainfall variation. The integration of gauge data, evidence from historical documents, and information from natural proxies such as tree rings during the late 20th and early 21st centuries, has allowed the nature of precipitation variability since ~1800 to be more fully explored.Drought episodes affecting large areas of the SRZ occurred during the first decade of the 19th century, in the early and late 1820s, late 1850s–mid-1860s, mid-late 1870s, earlymid-1880s, and mid-late 1890s. Of these episodes, the drought during the early 1860s was the most severe of the 19th century, with those of the 1820s and 1890s the most protracted. Many of these droughts correspond with more extreme ENSO warm phases.Widespread wetter conditions are less easily identified. The year 1816 appears to have been relatively wet across the Kalahari and other areas of south central Africa. Other wetter episodes were centered on the late 1830s–early 1840s, 1855, 1870, and 1890. In the WRZ, drier conditions occurred during the first decade of the 19th century, for much of the mid-late 1830s through to the mid-1840s, during the late 1850s and early 1860s, and in the early-mid-1880s and mid-late 1890s. As for the SRZ, markedly wetter years are less easily identified, although the periods around 1815, the early 1830s, mid-1840s, mid-late 1870s, and early 1890s saw enhanced rainfall. Reconstructed rainfall anomalies for the SRZ suggest that, on average, the region was significantly wetter during the 19th century than the 20th and that there appears to have been a drying trend during the 20th century that has continued into the early 21st. In the WRZ, average annual rainfall levels appear to have been relatively consistent between the 19th and 20th centuries, although rainfall variability increased during the 20th century compared to the 19th.

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Books on the topic 'Variabilita interannuale'

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