Earth Observation Data Group

Abstract:

This work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the considered European mid-latitudes. Artificial neural networks (ANNs) are intrinsically non-linear systems, hence they are expected to cope with TO series better than classical statistics do. Moreover, neural networks do not assume the stationarity of the data series so they are also able to follow time-changing situations among the implicated variables. These two features turn NNs into a promising tool to catch the interactions between atmospheric variables, and therefore to extract as much information as possible from the available data in order to make, for example, time series reconstructions or future predictions. Models based on NNs have also proved to be very suitable for the treatment of missing values within the data series. In this paper we present several models based on neural networks to fill the missing periods of data within a total ozone time series, and models able to reconstruct the data series. The results released by the ANNs have been compared with those obtained by using classical statistics methods, and better accuracy has been achieved with the non linear ANNs techniques. Different network structures and training strategies have been tested depending on the specific task to be accomplished. © European Geosciences Union 2004.

Abstract:

Analytical expressions are found for the derivatives of commonly used Mie scattering parameters, in particular the absorption and the scattering efficiencies, and for the angular intensity functions. These expressions are based on the analytical derivatives of the Mie scattering amplitudes a(n) and b(n) with respect to the particle size parameter and complex refractive index. In addition, analytical derivatives are found for the volume absorption and scattering coefficients, as well as for the intensity functions of a population of particles with log normal size distribution. These derivatives are given with respect to the total number density, to the median radius and spread of the distribution, and to the refractive index. Comparison between analytically and numerically computed derivatives showed the analytical version to be 2.5 to 6.5 times as fast for the single-particle and particle-distribution cases, respectively. (C) 2004 Optical Society of America.

Abstract:

Analytical expressions are found for the derivatives of commonly used Mie scattering parameters, in particular the absorption and the scattering efficiencies, and for the angular intensity functions. These expressions are based on the analytical derivatives of the Mie scattering amplitudes a(n) and b(n) with respect to the particle size parameter and complex refractive index. In addition, analytical derivatives are found for the volume absorption and scattering coefficients, as well as for the intensity functions of a population of particles with log normal size distribution. These derivatives are given with respect to the total number density, to the median radius and spread of the distribution, and to the refractive index. Comparison between analytically and numerically computed derivatives showed the analytical version to be 2.5 to 6.5 times as fast for the single-particle and particle-distribution cases, respectively.

Abstract:

A simple physical model of the atmospheric effects of large explosive volcanic eruptions is developed. Using only one input parameter-the initial amount of sulphur dioxide injected into the stratosphere-the global-average stratospheric optical-depth perturbation and surface temperature response are modelled. The simplicity of this model avoids issues of incomplete data (applicable to more comprehensive models), making it a powerful and useful tool for atmospheric diagnostics of this climate forcing mechanism. It may also provide a computationally inexpensive and accurate way of introducing volcanic activity into larger climate models. The modelled surface temperature response for an initial sulphur-dioxide injection, coupled with emission-hi story statistics, is used to demonstrate that the most climatically significant volcanic eruptions are those of sufficient explosivity to just reach into the stratosphere (and achieve longevity). This study also highlights the fact that this measure of significance is highly sensitive to the representation of the climatic response and the frequency data used, and that we are far from producing a definitive history of explosive volcanism for at least the past 1000 years. Given this high degree of uncertainty, these results suggest that eruptions that release around and above 0.1 Mt SO2 into the stratosphere have the maximum climatic impact.