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Der Einfluß externen Rauschens auf die Klimavariabilität in vereinfachten Modellen (2010)

Sura, Philip

Univ. Hamburg

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Publikationsdatum: 2021-03-29

Beschreibung: thesis

Schlagwort(e): 551.6 ; 550 ; TVF 000 ; TWB 000 ; TWH 100 ; Allgemeine Zirkulation der Atmosphäre {Meteorologie} ; Statistische Klimatologie und Klimatologische Modelle ; Einfluss der Verteilung von Land und Meer {Klimatologie}

Sprache: Deutsch

Materialart: monograph , publishedVersion

Format: application/pdf

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Non-Gaussian Analysis of Observations from the Atmospheric Infrared Sounder Compared with ERA and MERRA Reanalyses (2017)

De Souza-Machado, Sergio ; Tangborn, Andrew ; Sura, Philip ; [weitere]

American Meteorological Society

In: Journal of Applied Meteorology and Climatology. 2017; 56(5): 1463-1481. Published 2017 May 01. doi: 10.1175/jamc-d-16-0278.1.

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Publikationsdatum: 2017-05-01

Beschreibung: Statistical relationships between higher-order moments of probability density functions (PDFs) are used to analyze top-of-atmosphere radiance measurements made by the Atmospheric Infrared Sounder (AIRS) and radiance calculations from the ECMWF Re-Analysis (ERA) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) over a 10-yr period. The statistical analysis used in this paper has previously been applied to sea surface temperature, and here the authors show that direct satellite radiance observations of atmospheric variability also exhibit stochastic forcing characteristics. The authors have chosen six different AIRS channels based on the sensitivity of their measured radiances to a variety of geophysical properties. In each of these channels, the authors have found evidence of correlated additive and multiplicative (CAM) stochastic forcing. In general, channels sensitive to tropospheric humidity and surface temperature show the strongest evidence of CAM forcing, while those sensitive to stratospheric temperature and ozone exhibit the weakest forcing. Radiance calculations from ERA and MERRA agree well with AIRS measurements in the Gaussian part of the PDFs but show some differences in the tails, indicating that the reanalyses may be missing some extrema there. The CAM forcing is investigated through numerical simulation of simple stochastic differential equations (SDEs). The authors show how measurements agree better with weaker CAM forcing, achieved by reducing the multiplicative forcing or by increasing the spatial correlation of the added noise in the case of an SDE with one spatial dimension. This indicates that atmospheric models could be improved by adjusting nonlinear terms that couple long and short time scales.

Print ISSN: 1558-8424

Digitale ISSN: 1558-8432

Thema: Geographie , Physik

Publiziert von American Meteorological Society

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Multiscale Impacts of Variable Heating in Climate (2007)

Sardeshmukh, Prashant D. ; Sura, Philip

American Meteorological Society

In: Journal of Climate. 2007; 20(23): 5677-5695. Published 2007 Dec 01. doi: 10.1175/2007jcli1411.1.

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Publikationsdatum: 2007-12-01

Beschreibung: While it is obvious that the mean diabatic forcing of the atmosphere is crucial for maintaining the mean climate, the importance of diabatic forcing fluctuations is less evident in this regard. Such fluctuations do not appear directly in the equations of the mean climate but affect the mean indirectly through their effects on the time-mean transient-eddy fluxes of heat, momentum, and moisture. How large are these effects? What are the effects of tropical phenomena associated with substantial heating variations such as ENSO and the MJO? To what extent do variations of the extratropical surface heat fluxes and precipitation affect the mean climate? What are the effects of the rapid “stochastic” components of the heating fluctuations? Most current climate models misrepresent ENSO and the MJO and ignore stochastic forcing; they therefore also misrepresent their mean effects. To what extent does this contribute to climate model biases and to projections of climate change? This paper provides an assessment of such impacts by comparing with observations a long simulation of the northern winter climate by a dry adiabatic general circulation model forced only with the observed time-mean diabatic forcing as a constant forcing. Remarkably, despite the total neglect of all forcing variations, the model reproduces most features of the observed circulation variability and the mean climate, with biases similar to those of some state-of-the-art general circulation models. In particular, the spatial structures of the circulation variability are remarkably well reproduced. Their amplitudes, however, are progressively underestimated from the synoptic to the subseasonal to interannual and longer time scales. This underestimation is attributed to the neglect of the variable forcing. The model also excites significant tropical variability from the extratropics on interannual scales, which is overwhelmed in reality by the response to tropical heating variability. It is argued that the results of this study suggest a role for the stochastic, and not only the coherent, components of transient diabatic forcing in the dynamics of climate variability and the mean climate.

Print ISSN: 0894-8755

Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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The Impact of Rapid Wind Variability upon Air–Sea Thermal Coupling (2008)

Sura, Philip ; Newman, Matthew

American Meteorological Society

In: Journal of Climate. 2008; 21(4): 621-637. Published 2008 Feb 15. doi: 10.1175/2007jcli1708.1.

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Publikationsdatum: 2008-02-15

Beschreibung: The basic effect of extratropical atmosphere–ocean thermal coupling is to enhance the variance of both anomalous sea surface temperatures (SSTs) and air temperatures (AIRT) due to a decreased energy flux between the atmosphere and ocean, called reduced thermal damping. In this paper it is shown that rapidly varying surface winds, through their influence upon the turbulent surface heat fluxes that drive this coupling, act to effectively weaken the coupling and thus partially counteract the reduced thermal damping. In effect, rapid fluctuations in wind speed somewhat insulate the atmosphere and ocean from each other. The nonlinear relationship between the rapidly varying wind speed anomalies and SST and AIRT anomalies results in a rapidly varying component of the surface heat fluxes. The clear separation between the dynamical time scales of the ocean and atmosphere allows this rapidly varying flux to be simply approximated by a stochastic process in which rapidly varying wind speed is represented as Gaussian white noise whose amplitude is modulated by the more slowly evolving thermal anomalies. Such state-dependent (multiplicative) noise can alter the dynamics of atmosphere–ocean coupling because it induces an additional heat flux term, the noise-induced drift, that effectively acts to weaken both coupling and dissipation. Another key implication of the outlined theory is that air–sea coupling includes both deterministic and stochastic components. The theory is tested by examining daily observations during extended winter (November–April) at several ocean weather stations (OWSs). Two important results are found. First, multiplicative noise at OWS P effectively decreases the coupling by about one-third, with about a 10% (20%) decrease in the damping of SST (AIRT). This suggests that multiplicative noise may be responsible for roughly half of the AIRT variability at OWS P on subseasonal time scales. Second, OWS observations reveal that joint probability distribution functions of daily averaged SST and AIRT anomalies are significantly non-Gaussian. It is shown that treating the rapidly varying boundary layer heat fluxes as state-dependent noise can reproduce this observed non-Gaussianity. It is concluded that the effect of state-dependent noise is crucial to understand and model atmosphere–ocean coupling.

Print ISSN: 0894-8755

Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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Reconciling Non-Gaussian Climate Statistics with Linear Dynamics (2009)

Sardeshmukh, Prashant D. ; Sura, Philip

American Meteorological Society

In: Journal of Climate. 2009; 22(5): 1193-1207. Published 2009 Mar 01. doi: 10.1175/2008jcli2358.1.

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Publikationsdatum: 2009-03-01

Beschreibung: Linear stochastically forced models have been found to be competitive with comprehensive nonlinear weather and climate models at representing many features of the observed covariance statistics and at predictions beyond a week. Their success seems at odds with the fact that the observed statistics can be significantly non-Gaussian, which is often attributed to nonlinear dynamics. The stochastic noise in the linear models can be a mixture of state-independent (“additive”) and linearly state-dependent (“multiplicative”) Gaussian white noises. It is shown here that such mixtures can produce not only symmetric but also skewed non-Gaussian probability distributions if the additive and multiplicative noises are correlated. Such correlations are readily anticipated from first principles. A generic stochastically generated skewed (SGS) distribution can be analytically derived from the Fokker–Planck equation for a single-component system. In addition to skew, all such SGS distributions have power-law tails, as well as a striking property that the (excess) kurtosis K is always greater than 1.5 times the square of the skew S. Remarkably, this K–S inequality is found to be satisfied by circulation variables even in the observed multicomponent climate system. A principle of “diagonal dominance” in the multicomponent moment equations is introduced to understand this behavior. To clarify the nature of the stochastic noises (turbulent adiabatic versus diabatic fluctuations) responsible for the observed non-Gaussian statistics, a long 1200-winter simulation of the northern winter climate is generated using a dry adiabatic atmospheric general circulation model forced only with the observed long-term winter-mean diabatic forcing as a constant forcing. Despite the complete neglect of diabatic variations, the model reproduces the observed K–S relationships and also the spatial patterns of the skew and kurtosis of the daily tropospheric circulation anomalies. This suggests that the stochastic generators of these higher moments are mostly associated with local adiabatic turbulent fluxes. The model also simulates fifth moments that are approximately 10 times the skew, and probability densities with power-law tails, as predicted by the linear theory.

Print ISSN: 0894-8755

Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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Quantifying the Non-Gaussianity of Wintertime Daily Maximum and Minimum Temperatures in the Southeast (2013)

Stefanova, Lydia ; Sura, Philip ; Griffin, Melissa

American Meteorological Society

In: Journal of Climate. 2013; 26(3): 838-850. Published 2013 Feb 01. doi: 10.1175/jcli-d-12-00161.1.

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Publikationsdatum: 2013-02-01

Beschreibung: In this paper the statistics of daily maximum and minimum surface air temperature at weather stations in the southeast United States are examined as a function of the El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) phase. A limited number of studies address how the ENSO and/or AO affect U.S. daily—as opposed to monthly or seasonal—temperature averages. The details of the effect of the ENSO or AO on the higher-order statistics for wintertime daily minimum and maximum temperatures have not been clearly documented. Quality-controlled daily observations collected from 1960 to 2009 from 272 National Weather Service Cooperative Observing Network stations throughout Florida, Georgia, Alabama, and South and North Carolina are used to calculate the first four statistical moments of minimum and maximum daily temperature distributions. It is found that, over the U.S. Southeast, winter minimum temperatures have higher variability than maximum temperatures and La Niña winters have greater variability of both minimum and maximum temperatures. With the exception of the Florida peninsula, minimum temperatures are positively skewed, while maximum temperatures are negatively skewed. Stations in peninsular Florida exhibit negative skewness for both maximum and minimum temperatures. During the relatively warmer winters associated with either a La Niña or AO+, negative skewnesses are exacerbated and positive skewnesses are reduced. To a lesser extent, the converse is true of the El Niño and AO−. The ENSO and AO are also shown to have a statistically significant effect on the change in kurtosis of daily maximum and minimum temperatures throughout the domain.

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Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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Perspectives of Non-Gaussianity in Atmospheric Synoptic and Low-Frequency Variability (2015)

Sura, Philip ; Hannachi, Abdel

American Meteorological Society

In: Journal of Climate. 2015; 28(13): 5091-5114. Published 2015 Jul 01. doi: 10.1175/jcli-d-14-00572.1.

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Publikationsdatum: 2015-07-01

Beschreibung: Understanding non-Gaussian statistics of atmospheric synoptic and low-frequency variability has important consequences in the atmospheric sciences, not least because weather and climate risk assessment depends on knowing and understanding the exact shape of the system’s probability density function. While there is no doubt that many atmospheric variables exhibit non-Gaussian statistics on many time (and spatial) scales, a full and complete understanding of this phenomenon remains a challenge. Various mechanisms behind the observed atmospheric non-Gaussian statistics have been proposed but remain, however, multifaceted and scattered in the literature: nonlinear dynamics, multiplicative noise, cross-frequency coupling, nonlinear boundary layer drag, and others. Given the importance of this subject for weather and climate research, and in an attempt to contribute to this topic, a thorough review and discussion of the different mechanisms that lead to non-Gaussian weather and climate variability are presented in this paper and an outlook is given.

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Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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Climatology of Non-Gaussian Atmospheric Statistics (2013)

Perron, Maxime ; Sura, Philip

American Meteorological Society

In: Journal of Climate. 2013; 26(3): 1063-1083. Published 2013 Feb 01. doi: 10.1175/jcli-d-11-00504.1.

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Publikationsdatum: 2013-02-01

Beschreibung: A common assumption in the earth sciences is the Gaussianity of data over time. However, several independent studies in the past few decades have shown this assumption to be mostly false. To be able to study non-Gaussian climate statistics, one must first compile a systematic climatology of the higher statistical moments (skewness and kurtosis; the third and fourth central statistical moments, respectively). Sixty-two years of daily data from the NCEP–NCAR Reanalysis I project are analyzed. The skewness and kurtosis of the data are found at each spatial grid point for the entire time domain. Nine atmospheric variables were chosen for their physical and dynamical relevance in the climate system: geopotential height, relative vorticity, quasigeostrophic potential vorticity, zonal wind, meridional wind, horizontal wind speed, vertical velocity in pressure coordinates, air temperature, and specific humidity. For each variable, plots of significant global skewness and kurtosis are shown for December–February and June–August at a specified pressure level. Additionally, the statistical moments are then zonally averaged to show the vertical dependence of the non-Gaussian statistics. This is a more comprehensive look at non-Gaussian atmospheric statistics than has been taken in previous studies on this topic.

Print ISSN: 0894-8755

Digitale ISSN: 1520-0442

Thema: Geographie , Geologie und Paläontologie , Physik

Publiziert von American Meteorological Society

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