The history and characteristics of the 1980-2005 Portuguese rural fire database

Abstract. We focus here on a mainland Continental Portuguese Rural Fire Database (PRFD) that includes 450 000 fires, the largest such database in Europe in terms of total number of recorded fires in the 1980–2005 period. In this work, we (a) list the most important factors for triggering and controlling the fire regime in mainland Continental Portugal, (b) describe the dataset's production, (c) discuss procedures adopted to identify and correct different fire data inconsistencies, creating a modified PRFD which we use here and make available as Supplement, (d) explore some basic temporal and completeness properties of the data. We find that the dataset's minimum measured burnt areas have changed with time between AF = 0.1 ha (1980–1990), AF = 0.01 ha (1991–1992), and AF = 0.001 ha (1992–2005), with varying degrees of completeness down to these values. These changes in minimum area measured are responsible for greater numbers of fires being recorded. A relatively small number of large fires in the PRFD are responsible for the majority of the burnt area. For example, fires with AF > 100 ha represent about 1% of all fire records but 75% of total burnt area. Finally, we consider for each Continental Portugal district and for the 26-yr period, the total number of rural fires and area burnt in forests and shrublands, each normalized by district areas. We find that the highest numbers of fires per unit area are in highly populated districts, and that the largest fraction of burnt area is in forested areas, coinciding with large parcels of continuous forests (predominantly rural and moderately urban areas).

[1]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[2]  Domingos Xavier Viegas,et al.  Forest fire propagation , 1998, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[3]  R. Trigo,et al.  Circulation weather types and their influence on the precipitation regime in Portugal. , 2000 .

[4]  Paulo M. Fernandes,et al.  Fire spread prediction in shrub fuels in Portugal , 2001 .

[5]  M. Vasconcelos,et al.  Spatial Prediction of Fire Ignition Probabilities: Comparing Logistic Regression and Neural Networks , 2001 .

[6]  Anders Moberg,et al.  Daily dataset of 20th‐century surface air temperature and precipitation series for the European Climate Assessment , 2002 .

[7]  L. Rivas Soriano,et al.  Study of lightning event duration and flash rate in the Iberian Peninsula using cloud-to-ground lightning data , 2002 .

[8]  S. Pyne,et al.  Fire: A Brief History , 2001 .

[9]  C. Tomás,et al.  Circulation weather types and cloud‐to‐ground flash density over the Iberian Peninsula , 2004 .

[10]  José M. C. Pereira,et al.  Synoptic patterns associated with large summer forest fires in Portugal , 2005 .

[11]  David L. Martell,et al.  A lightning fire occurrence model for Ontario , 2005 .

[12]  T. Sisk,et al.  Mapping the probability of large fire occurrence in northern Arizona, USA , 2006, Landscape Ecology.

[13]  B. Malamud,et al.  Characterizing wildfire regimes in the United States. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[14]  José M. C. Pereira,et al.  Atmospheric conditions associated with the exceptional fire season of 2003 in Portugal , 2006 .

[15]  F. Catry,et al.  Forest fires in cork oak (Quercus suber L.) stands in Portugal , 2006 .

[16]  Ana Isabel Miranda,et al.  Fire activity in Portugal and its relationship to weather and the Canadian Fire Weather Index System , 2008 .

[17]  Ana Isabel Miranda,et al.  Regional-scale weather patterns and wildland fires in central Portugal , 2009 .

[18]  R. Trigo,et al.  Cloud to ground lightning activity over Portugal and its association with circulation weather types , 2011 .

[19]  B. Poulter,et al.  Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages , 2011 .