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- Author or Editor: F. De Pablo Dávila x
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Abstract
Daily fire risk (DFR) is a forecasting index defined on the basis of two meteorological parameters. Such parameters are associated with the local atmospheric column: dry stability e in 850–700-hPa layer and saturation deficit D in 850-hPa level. In an earlier study, and from data collected over 10 years, a categorization of four type days based on DFR was established. In this way, from evaluation of e and D at 0000 UTC for each particular day, the associated type day was deduced. Consequently, it is possible to know whether that day had either very high, high, low, or very low fire activity. With this technique it is not possible to forecast a numerical value for the number of fires, however.
In this paper a model for estimating the outbreak of fires is presented. On the basis of an autoregressive process, AR(2), it is possible to obtain the predicted number of fires (PNF) during a day d as PNF(d) = F[TD(d), RNF(D − 1), RNF(d − 2)], where TD(d) is the type day according to the categorization established on the basis of e and D (deduced from rawinsoundings at 0000 UTC) and RNF(d − 1) and RNF(d − 2) are the numbers of fires registered over the area during two previous days.
In contrast to other papers in the literature, all fires are considered. No limitations are placed on the burned area or other measures of fire activity. Several statistical computations confirm the validity of this model.
Abstract
Daily fire risk (DFR) is a forecasting index defined on the basis of two meteorological parameters. Such parameters are associated with the local atmospheric column: dry stability e in 850–700-hPa layer and saturation deficit D in 850-hPa level. In an earlier study, and from data collected over 10 years, a categorization of four type days based on DFR was established. In this way, from evaluation of e and D at 0000 UTC for each particular day, the associated type day was deduced. Consequently, it is possible to know whether that day had either very high, high, low, or very low fire activity. With this technique it is not possible to forecast a numerical value for the number of fires, however.
In this paper a model for estimating the outbreak of fires is presented. On the basis of an autoregressive process, AR(2), it is possible to obtain the predicted number of fires (PNF) during a day d as PNF(d) = F[TD(d), RNF(D − 1), RNF(d − 2)], where TD(d) is the type day according to the categorization established on the basis of e and D (deduced from rawinsoundings at 0000 UTC) and RNF(d − 1) and RNF(d − 2) are the numbers of fires registered over the area during two previous days.
In contrast to other papers in the literature, all fires are considered. No limitations are placed on the burned area or other measures of fire activity. Several statistical computations confirm the validity of this model.
Abstract
The theoretical study presented here shows that it is possible to define an energetic parameter that generalizes the dry, saturated, and moist static energies. The properties of the generalized static energy (GSE) are similar to those of dry, saturated, and moist static energies, but GSE can be used in cloudy systems including water vapor, liquid water, and ice, as well as in nonequilibrium conditions.
It is shown that GSE is directly related to the entropy and that it is reduced to dry, saturated, and moist static energies when appropriate assumptions are made. It is also shown that GSE is a conservative parameter when irreversibility and mass flux do not exist or are ignored.
Abstract
The theoretical study presented here shows that it is possible to define an energetic parameter that generalizes the dry, saturated, and moist static energies. The properties of the generalized static energy (GSE) are similar to those of dry, saturated, and moist static energies, but GSE can be used in cloudy systems including water vapor, liquid water, and ice, as well as in nonequilibrium conditions.
It is shown that GSE is directly related to the entropy and that it is reduced to dry, saturated, and moist static energies when appropriate assumptions are made. It is also shown that GSE is a conservative parameter when irreversibility and mass flux do not exist or are ignored.
