Spatial relationships between lightning-induced forest fires and topography, vegetation, climate and lightning characteristics were analyzed in the province of León (NW Spain). The study was based on reported lightning-induced forest fires in the period 2002-2007. A statistical model based on logistic regression was developed to estimate the probability of occurrence of a lightning-induced fire in a 3 x 3 km grid. The importance of accurate location of the ignition point was also investigated in order to evaluate the sensitivity of the model developed to uncertainty of the location. The model developed with accurate ignition point data showed a better predictive ability than the model constructed with all the ignition points available. The former model was therefore selected for long-term prediction of the occurrence of lightning-induced fires in the province. According to this model, the probability of a forest stand being affected by lightning-induced fire increased with decreasing altitude, and when there was a high proportion of coniferous species in the stand, a high percentage of lightning strikes in forest areas and a high number of dry storm days in the area. Although the model has not been validated, the results can be considered spatially robust because it shows good classification ability and the predicted spatial probability distribution is consistent with the observed historical fire records. The model will be useful in the spatially explicit assessment of fire risk, the planning and coordination of regional efforts to identify areas at greatest risk, and in designing long-term wildfire management strategies.

<p>Hailpads networks allow knowing the characteristics of the stones precipitated by hail storms. The province of Lleida (Spain) has an excellent network of hailpads (managed by the ADV Terres de Ponent and the Servei Meteorologic de Catalunya) which is located south of the Pyrenees. To the north of it and in French territory, there is another similar one (placed in Hautes Pyrénées and Midi Pyrénées), managed by ANELFA. A large part of the hail storms that affect this French area are formed in Spanish territory, crossing the mountainous barrier of the Pyrenees, so it is interesting to know their characteristics from one side to the other. In both cases, historical series of more than 20 years are available.</p> <p>We have taken the database of all the days in which hail falls have been detected in one or another hailpads network and we have calculated the diameter and maximum energy of the precipitated stones. With the data obtained, we have found the corresponding statistical distributions.</p> <p>Once we have obtained these four databases (ie two for each of the networks) we have analyzed the statistical parameters that characterize them. We have also studied the temporal trend of hail precipitation on both sides of the Pyrenees</p> <p>Finally, we have studied the meteorological factors that intervene in the formation of hail and the dependence they have on the maximum diameter and the maximum expected energy.</p> <p>The results show a greater severity in the stones precipitated on the South side of the Pyrenees and the meteorological factors involved in the formation of hailstorms.</p>

This study presents the characteristics of cloud‐to‐ground lightning in the province of León (Spain), based on data collected via the lightning detection network of the Spanish Meteorological Agency. A total of 146 081 flashes and 279 220 strokes were recorded between 2000 and 2010. Spatial analysis (total, negative and positive flash density, and mean peak currents of positive and negative flashes) was performed at a resolution of 1 km. The maximum density recorded for total negative and positive flashes was 2.0 flashes km−2 year−1; 2.3 for negative flashes only and 0.178 for positive flashes. There was a different spatial distribution for positive compared with negative flashes, resulting from meteorological mechanisms involved with their polarities. The density distribution corresponding to both total and negative flashes appears to be clearly associated with topography. Interestingly, there is a clear inverse spatial correlation between the density and peak current parameters, which has important implications for constructing risk maps of lightning activity. This correlation has been quantified and confirmed for both positive and negative flashes by two separate regression equations. In the second part of the present study, a statistical model was constructed to predict lightning in the province of León, using a quadratic discriminant function that encompasses three meteorological variables obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis: lifted index, K‐index and precipitable water. To construct the model, data were used from May to September over 2002–2007, and then applied to an independent sample of years from 2008 to 2010. Results were verified using skill scores probability of detection, false alarm rate, critical success index and true skill statistic. Scores obtained for the samples were 0.79, 0.45, 0.48 and 0.53 (respectively) for model construction, and 0.78, 0.14, 0.69 and 0.65 (respectively) for application to the independent sample.