Complex formalism is often convenient to describe, in a compact and unified way, a vectorial data set in two dimensions, such as wind field, electromagnetic field, as well as measurements out-coming from any two dimensional vectorial field. This representation is rarely considered in Geostatistics, although interesting applications can be found in environmental sciences and meteorology. In such a case, some practical issues related to the prediction step have to be faced. In this paper, some essential aspects on complex formalism, such as fitting a complex covariance function and predicting a complex-valued random field through an ad-hoc GSLib routine, are given. An environmental application to wind data has been furnished.
Predictions of complex-valued random fields
DE IACO, Sandra;POSA, Donato;PALMA, Monica;MAGGIO, Sabrina
2015-01-01
Abstract
Complex formalism is often convenient to describe, in a compact and unified way, a vectorial data set in two dimensions, such as wind field, electromagnetic field, as well as measurements out-coming from any two dimensional vectorial field. This representation is rarely considered in Geostatistics, although interesting applications can be found in environmental sciences and meteorology. In such a case, some practical issues related to the prediction step have to be faced. In this paper, some essential aspects on complex formalism, such as fitting a complex covariance function and predicting a complex-valued random field through an ad-hoc GSLib routine, are given. An environmental application to wind data has been furnished.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
