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Books on the topic 'Intraseasonal Oscillation in Atmosphere'

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Published: 6 September 2023

Last updated: 7 September 2023

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1

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-13914-7.

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2

Lau, William K. M. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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3

E, Waliser Duane, ed. Intraseasonal variability in the atmosphere-ocean climate system. Berlin: Springer-Verlag, 2005.

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4

G, Vincent Dayton, and United States. National Aeronautics and Space Administration., eds. Relationship between intraseasonal oscillation and subtropical wind maxima over the South Pacific Ocean. [Washington, DC: National Aeronautics and Space Administration, 1991.

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5

Allan, Robert J. El Niño, southern oscillation & climatic variability. Collingwood, Vic., Australia: CSIRO, 1996.

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6

Wright, Peter B. Relationships between surface observations over the global oceans and the southern oscillation. Seattle, Wash: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1985.

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7

F, Diaz Henry, and Markgraf Vera, eds. El Niño: Historical and paleoclimatic aspects of the southern oscillation. Cambridge [England]: Cambridge University Press, 1992.

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8

El Niño, La Niña, and the southern oscillation. San Diego: Academic Press, 1990.

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9

Kikuchi, Kazuyoshi. Data analysis studies on the propagation characteristics of the Madden-Julian Oscillation (MJO). [Tokyo]: Center for Climate System Research, University of Tokyo, 2006.

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10

Allan, Rob. El Niño Southern Oscillation and climatic variability. Collingwood, Vict: CSIRO PUblishing, 1996.

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11

Fiedler, Paul C. Seasonal climatologies and variability of eastern tropical Pacific surface waters. [Seattle, Wash.]: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, 1992.

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12

ENSO yu hai yang huan jing he Zhongguo qi hou yi chang. Beijing: Ke xue chu ban she, 2013.

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13

Giese, Benjamin S. Equatorial oceanic response to forcing on time scales from days to months. Seattle, Wash: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Pacific Marine Environmental Laboratory, 1989.

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14

Western Pacific International Meeting and Workshop on TOGA COARE (1989 Centre ORSTOM de Nouméa). Proceedings of the Western Pacific International Meeting and Workshop on TOGA COARE, held at Centre ORSTOM de Nouméa, New Caledonia, May 24-30, 1989. [Nouméa, New Caledonia]: Institut français de recherche scientifique pour le développement en coopération, Centre de Nouméa, 1989.

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15

Fiedler, Paul C. Seasonal Climatologies and variability of eastern tropical Pacific surface waters. Silver Spring, Md.]: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, 1992.

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16

Halpert, Michael S. Atlas of tropical sea surface temperature and surface winds. Silver Spring, MD: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1989.

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17

Hayashi, Michiya. A modeling study on coupling between westerly wind events and ENSO. Tokyo]: Division of Climate System Research, Atmosphere and Ocean Research Institute, The University of Tokyo, 2018.

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18

Wallace, John M. El Niño and climate prediction. [Washington, D.C.?]: National Oceanic and Atmosphere Administration, 1999.

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19

M, Wallace John. El Niño and climate prediction. [Boulder, Colo.]: [University Corporation for Atmospheric Research, Office for Interdisciplinary Earth Studies], 1994.

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20

National Research Council (U.S.). Advisory Panel for the Tropical Oceans and Global Atmosphere Program., ed. Learning to predict climate variations associated with El Niño and the southern oscillation: Accomplishments and legacies of the TOGA program. Washington, D.C: National Academy Press, 1996.

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21

The Role of Radiative Processes in the Tropical Intraseasonal Oscillation. Storming Media, 1997.

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22

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b138817.

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23

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Springer, 2010.

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24

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Springer, 2012.

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25

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Springer, 2009.

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26

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Springer London, Limited, 2007.

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27

Lau, William K. M., and Duane E. Waliser. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Springer, 2013.

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28

Atmospheric model intercomparison project (AMIP): Intraseasonal oscillations in 15 atmospheric general circulation models (results from an AMIP diagnostic subproject). Geneva, Switzerland: Joint Planning Staff for WCRP, World Meteorological Organization, 1995.

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29

Wang, Bin. Intraseasonal Modulation of the Indian Summer Monsoon. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.616.

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The strongest Indian summer monsoon (ISM) on the planet features prolonged clustered spells of wet and dry conditions often lasting for two to three weeks, known as active and break monsoons. The active and break monsoons are attributed to a quasi-periodic intraseasonal oscillation (ISO), which is an extremely important form of the ISM variability bridging weather and climate variation. The ISO over India is part of the ISO in global tropics. The latter is one of the most important meteorological phenomena discovered during the 20th century (Madden & Julian, 1971, 1972). The extreme dry and wet events are regulated by the boreal summer ISO (BSISO). The BSISO over Indian monsoon region consists of northward propagating 30–60 day and westward propagating 10–20 day modes. The “clustering” of synoptic activity was separately modulated by both the 30–60 day and 10–20 day BSISO modes in approximately equal amounts. The clustering is particularly strong when the enhancement effect from both modes acts in concert. The northward propagation of BSISO is primarily originated from the easterly vertical shear (increasing easterly winds with height) of the monsoon flows, which by interacting with the BSISO convective system can generate boundary layer convergence to the north of the convective system that promotes its northward movement. The BSISO-ocean interaction through wind-evaporation feedback and cloud-radiation feedback can also contribute to the northward propagation of BSISO from the equator. The 10–20 day oscillation is primarily produced by convectively coupled Rossby waves modified by the monsoon mean flows. Using coupled general circulation models (GCMs) for ISO prediction is an important advance in subseasonal forecasts. The major modes of ISO over Indian monsoon region are potentially predictable up to 40–45 days as estimated by multiple GCM ensemble hindcast experiments. The current dynamical models’ prediction skills for the large initial amplitude cases are approximately 20–25 days, but the prediction of developing BSISO disturbance is much more difficult than the prediction of the mature BSISO disturbances. This article provides a synthesis of our current knowledge on the observed spatial and temporal structure of the ISO over India and the important physical processes through which the BSISO regulates the ISM active-break cycles and severe weather events. Our present capability and shortcomings in simulating and predicting the monsoon ISO and outstanding issues are also discussed.

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30

(Editor), Henry Frank Diaz, and Vera Markgraf (Editor), eds. El Niño: Historical and Paleoclimatic Aspects of the Southern Oscillation. Cambridge University Press, 1993.

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31

Dixit, Sanjay. Simulation of tropical pacific circulation anomalies with linear atmosphere and ocean models. 1987.

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32

Ahn, Joong Bae. A study of El Niño/southern oscillation: Numerical experiments and data analysis. 1990.

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33

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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34

(Editor), S. George Philander, James R. Holton (Series Editor), and Renata Dmowska (Series Editor), eds. El Nino, La Nina, and the Southern Oscillation, Volume 46 (International Geophysics). Academic Press, 1989.

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35

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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36

Yang, Kun. Observed Regional Climate Change in Tibet over the Last Decades. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.587.

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The Tibetan Plateau (TP) is subjected to strong interactions among the atmosphere, hydrosphere, cryosphere, and biosphere. The Plateau exerts huge thermal forcing on the mid-troposphere over the mid-latitude of the Northern Hemisphere during spring and summer. This region also contains the headwaters of major rivers in Asia and provides a large portion of the water resources used for economic activities in adjacent regions. Since the beginning of the 1980s, the TP has undergone evident climate changes, with overall surface air warming and moistening, solar dimming, and decrease in wind speed. Surface warming, which depends on elevation and its horizontal pattern (warming in most of the TP but cooling in the westernmost TP), was consistent with glacial changes. Accompanying the warming was air moistening, with a sudden increase in precipitable water in 1998. Both triggered more deep clouds, which resulted in solar dimming. Surface wind speed declined from the 1970s and started to recover in 2002, as a result of atmospheric circulation adjustment caused by the differential surface warming between Asian high latitudes and low latitudes.The climate changes over the TP have changed energy and water cycles and has thus reshaped the local environment. Thermal forcing over the TP has weakened. The warming and decrease in wind speed lowered the Bowen ratio and has led to less surface sensible heating. Atmospheric radiative cooling has been enhanced, mainly through outgoing longwave emission from the warming planetary system and slightly enhanced solar radiation reflection. The trend in both energy terms has contributed to the weakening of thermal forcing over the Plateau. The water cycle has been significantly altered by the climate changes. The monsoon-impacted region (i.e., the southern and eastern regions of the TP) has received less precipitation, more evaporation, less soil moisture and less runoff, which has resulted in the general shrinkage of lakes and pools in this region, although glacier melt has increased. The region dominated by westerlies (i.e., central, northern and western regions of the TP) received more precipitation, more evaporation, more soil moisture and more runoff, which together with more glacier melt resulted in the general expansion of lakes in this region. The overall wetting in the TP is due to both the warmer and moister conditions at the surface, which increased convective available potential energy and may eventually depend on decadal variability of atmospheric circulations such as Atlantic Multi-decadal Oscillation and an intensified Siberian High. The drying process in the southern region is perhaps related to the expansion of Hadley circulation. All these processes have not been well understood.

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