Nonlinear dynamics of mean daily temperature and dewpoint time series at Babolsar, Iran, 1961–2005

Millán, H.; Ghanbarian-Alavijeh, Behzad; García-Fornaris, I.

doi:10.1016/j.atmosres.2010.06.001

Cited by 29 publications

(18 citation statements)

References 35 publications

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“…Td is the temperature at which the vapor pressure is equal to the saturation pressure of the air (water vapor mixing ratio). In the same way, the vapor volume presented in the atmosphere can be expressed through the pressure that this vapor generates [33,39]. However, the total pressure on the atmosphere is the sum of the pressure caused by dry air plus the pressure produced by water vapor [8,40].…”

Section: The Clausius-clapeyron Relationmentioning

confidence: 99%

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

Gutiérrez-López

Cruz-Paz

Mandujano

2019

Climate

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Forecasting extreme precipitations is one of the main priorities of hydrology in Latin America and the Caribbean (LAC). Flood damage in urban areas increases every year, and is mainly caused by convective precipitations and hurricanes. In addition, hydrometeorological monitoring is limited in most countries in this region. Therefore, one of the primary challenges in the LAC region the development of a good rainfall forecasting model that can be used in an early warning system (EWS) or a flood early warning system (FEWS). The aim of this study was to provide an effective forecast of short-term rainfall using a set of climatic variables, based on the Clausius–Clapeyron relationship and taking into account that atmospheric water vapor is one of the variables that determine most meteorological phenomena, particularly regarding precipitation. As a consequence, a simple precipitation forecast model was proposed from data monitored at every minute, such as humidity, surface temperature, atmospheric pressure, and dewpoint. With access to a historical database of 1237 storms, the proposed model allows use of the right combination of these variables to make an accurate forecast of the time of storm onset. The results indicate that the proposed methodology was capable of predicting precipitation onset as a function of the atmospheric pressure, humidity, and dewpoint. The synoptic forecast model was implemented as a hydroinformatics tool in the Extreme Precipitation Monitoring Network of the city of Queretaro, Mexico (RedCIAQ). The improved forecasts provided by the proposed methodology are expected to be useful to support disaster warning systems all over Mexico, mainly during hurricanes and flashfloods.

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Section: The Clausius-clapeyron Relationmentioning

confidence: 99%

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

Gutiérrez-López

Cruz-Paz

Mandujano

2019

Climate

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“…This theory has been widely used in physics, chemistry, biology, geology, earthquake, meteorology and hydrology, and other fields (Sannasiraj et al 2004;Sivakumar 2004;Ma and Liu 2007;Lee and Lin 2008;Sun et al 2009;Ardalani-Farsa and Zolfaghari 2010;Millán et al 2010;Song et al 2010). The atmospheric system is a complex, nonlinear system involving both deterministic and stochastic components (Lorenz 1993).…”

Section: Introductionmentioning

confidence: 97%

A chaotic analysis on air pollution index change over past 10 years in Lanzhou, northwest China

Huang

Liu

et al. 2011

Stoch Environ Res Risk Assess

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In terms of the chaos theory, the phase-spacereconstruction method has been employed to describe the multi-dimensional phase space for the time series of air pollution index (API) during the past 10 years in Lanzhou, northwest China. The mutual information and Cao method were used to determine the reconstruction parameters, and the characteristic quantities including the Lyapunov exponent and the correlation dimension were calculated respectively. As a result, the correlation dimensions were fractioned, and the maximum Lyapunov exponent (k 1 ) [ 0. It shows that these presented the obvious chaotic characteristics that resulted from the evolution of non-linear chaotic dynamic system in the time series of air pollution index over the past 10 years. In the meanwhile, three or even four main dynamic variables were discussed here that could effectively interpret the changes of air pollution index time series and their causes. Some reasonable preventive countermeasures were thus put forward. These findings might provide a scientific basis for probing further into the regional complexity and evolution of the time series of air pollution index.

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“…Yet examples abound in which Lyapunov exponent estimates are provided with neither of these two requirements confirmed (e.g. [3,4,5,6,7,8,9]). Some have emphasised the need to provide confidence limits along with the estimates [10,11], but confidence limits are valuable only when there is evidence of convergence.…”

Section: Introductionmentioning

confidence: 99%

Quantifying chaos: A tale of two maps

Machete

2011

Physics Letters A

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In many applications, there is a desire to determine if the dynamics of interest are chaotic or not. Since positive Lyapunov exponents are a signature for chaos, they are often used to determine this. Reliable estimates of Lyapunov exponents should demonstrate evidence of convergence; but literature abounds in which this evidence lacks. This paper presents two maps through which it highlights the importance of providing evidence of convergence of Lyapunov exponent estimates. The results suggest cautious conclusions when confronted with real data. Moreover, the maps are interesting in their own right.

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Nonlinear dynamics of mean daily temperature and dewpoint time series at Babolsar, Iran, 1961–2005

Cited by 29 publications

References 35 publications

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

A chaotic analysis on air pollution index change over past 10 years in Lanzhou, northwest China

Quantifying chaos: A tale of two maps

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