atmosphere

Article Fire Danger Harmonization Based on the Fire Weather Index for Transboundary Events between and

Daniela Alves 1,* , Miguel Almeida 1, Domingos Xavier Viegas 1, Ilda Novo 2 and M. Yolanda Luna 3

1 Department of Mechanical Engineering, University of Coimbra, ADAI, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal; [email protected] (M.A.); [email protected] (D.X.V.) 2 Portuguese Institute for Sea and Atmosphere (IPMA), Rua C do Aeroporto, 1749-077 Lisboa, Portugal; [email protected] 3 State Meteorological Agency, (AEMET), 28071 Madrid, Spain; [email protected] * Correspondence: [email protected]; Tel.: +351-239708580

Abstract: Portugal and Spain have a cross-border cooperation protocol on wildfires response for a buffer strip of 25 km for each side of the border. In spite of the success of this collaboration, there are issues to be improved, since Portuguese and Spanish authorities use different methodologies to assess the daily fire danger. A methodology to harmonize fire danger and its interpretation by the Portuguese and Spanish Civil protection authorities in the transboundary buffer strip area is hereby presented. The fire danger index used is the Canadian Fire Weather Index (FWI), which requires input from meteorological data and gives an indication of fire intensity. The fire danger class is an important decision support tool for preventing and fighting wildfires. Since the meaning of FWI

 values change from region-to-region according to its specific characteristics, a calibration process  was performed based on statistical data of the daily FWI values, the number of fires and burned area

Citation: Alves, D.; Almeida, M.; between 2005 and 2013. The results of the FWI calibration and harmonization of the data for the five Viegas, D.X.; Novo, I.; Luna, M.Y. Fire danger classes minimizes the fire danger discrepancies across the border. This methodology has the Danger Harmonization Based on the potential to be reproduced in other areas. Fire Weather Index for Transboundary Events between Keywords: fire danger; data calibration; data harmonization; FWI; transboundary wildfires; interna- Portugal and Spain. Atmosphere 2021, tional collaboration; regional scales 12, 1087. https://doi.org/10.3390/ atmos12091087

Academic Editor: Jason C. Knievel 1. Introduction Several systems in studying the more favorable conditions for wildfire occurrence and Received: 2 July 2021 spread were developed, in order to anticipate the daily fire occurrence and behavior [1,2], Accepted: 21 August 2021 Published: 24 August 2021 which may be incorporated in decision support tools and transferred to operational de- cisions. These systems define a “Fire danger” index to support the management of fire

Publisher’s Note: MDPI stays neutral prevention and fire suppression forces in each region. “Fire danger” is hereby defined as with regard to jurisdictional claims in the potential for damage by fire in a certain area [3]. The intensity of wildfire danger is published maps and institutional affil- summarized by assessing the changes in the frequency of different classes of danger (from iations. relatively low values of danger up to higher values linked with maximum fire danger) [4]. In some countries, the danger classes are not established with the same criteria and more than one system is used to estimate the fire danger, leaving the decision to users in adopting the most appropriate level of danger in each situation [5]. The Canadian Fire Danger Rating System (CFFDRS) is the result of a research Copyright: © 2021 by the authors. program conducted in Canada since 1968 [6] having as a main outcome the Canadian Licensee MDPI, Basel, Switzerland. This article is an open access article Forest Fire Weather Index System (CFFWIS) that was developed by Van Wagner in 1987 [7]. distributed under the terms and The CFFWIS produces the Fire Weather Index (FWI), which is a composite index that conditions of the Creative Commons represents the meteorological conditions and gives an indication of the fire intensity [7]. Attribution (CC BY) license (https:// Due to the few input data, which are required and the good performance presented, creativecommons.org/licenses/by/ the FWI has been adopted in many countries and has been evaluated in several regions, 4.0/). for example the Canadian Boreal Forest [8], Tuscany in Italy, Thessaloniki, Athens and

Atmosphere 2021, 12, 1087. https://doi.org/10.3390/atmos12091087 https://www.mdpi.com/journal/atmosphere Atmosphere 2021, 12, 1087 2 of 20

Heraklion in Greece [9] or the Daxing’anling in China [10]. Several proposals of other fire danger indexes [11,12] were made, but none achieving the wide recognition of FWI. Among five methods for the evaluation of fire danger in six Mediterranean regions tested by [1], FWI showed the best performance especially for the summer season. The FWI is only based on meteorological information, but we recognize that other factors (e.g., topography, cover, human activity, fire detection and suppression capacity) affect fire ignition and spread, and consequently the fire danger. For these reason, FWI should be calibrated. The Canadian FWI system is being used by the national meteorological services to assess the fire danger in Portugal by the Portuguese Institute for Sea and Atmosphere (IPMA) since the decade of 1990 and in Spain by the Spanish State Meteorological Agency (AEMET) since 2008 [13,14]. In spite of the specific characteristics of each country, the FWI and its sub-indexes present good performance in assessing past fire events when related to the number of fire occurrences and the burned area [1,15,16]. The authors in [17] developed several regression models with good performance relating the monthly area burned and number of fires with the Canadian indexes for each Portuguese district, based on historical data. The authors in [16] showed good relationships between the FWI and the number of fires events for the Spanish province of Coruña and with the area burned for the Spanish [16]. While the authors in [17] developed daily fire occurrence models based on the Canadian fire danger indexes and on geographic factors organizing the country in 53 eco-regions, instead of the administrative division commonly followed. The occurrence of transboundary fire events between Portugal and Spain is very fre- quent, sometimes requiring the intervention of civil protection forces from both countries. According to the data provided by the Portuguese Civil Protection and Emergency Author- ity (ANEPC), from 2012 to 2015, 134 international fire events (99 transboundary missions in Portugal and 35 transboundary missions in Spain), involving 1358 Portuguese and Spanish agents, occurred in the transboundary area between both countries [18]. A joint declaration [19] from the PT-ES ministers of internal affairs after the XXIV Luso-Spanish Summit in 2009, refers the establishment of a protocol for technical cooperation and mutual assistance in the field of civil protection. According to this agreement, both civil protection authorities are allowed to intervene in any wildfire occurring in the transboundary strip up to 25 km from each side of the international border without a previous notification of the authorities where the wildfire is occurring. Despite the importance of this agreement, no provisions were made to define a common methodology to assess fire danger conditions. In order to illustrate the consequences of using different methodologies to assess the daily fire danger, Figure1 presents as an example, the classification of the fire danger classes based on FWI, in Portugal and Spain in 12 June 2014. As shown in Figure1 both countries currently have five fire danger classes using different color codes, from class 1 to class 5, they are usually named as Low, Moderate, High, Very high and Maximum, respectively. When the international border is crossed, the discrepancies that are shown in Figure1 arise due to the different methodologies that were used in Portugal and Spain to estimate the FWI values. As FWI is based on meteorological data obtained from weather stations, it must be recognized that each station represents the microclimate of the place where it is installed, which may not represent the average conditions in the region well. As a consequence, the value of FWI from a given station does not have the character of an absolute value but it must be considered as a relative value. This is an additional reason to perform the calibration of the FWI scale. The Portuguese decision makers and first responders use data provided by IPMA and the corresponding Spanish agencies use data provided by AEMET or by regional mete- orological services, each one using different fire danger classifications. This discrepancy in data and their interpretation hampers joint actions between the two countries, both in fire prevention and fire suppression activities. Therefore, the existence of common and shared information and a mutual interpretation of fire danger is essential for improving Atmosphere 2021, 12, 1087 3 of 20

Atmosphere 2021, 12, x FOR PEER REVIEW 3 of 21 the efficiency of collaborative fire management operations, especially in the transboundary areas.

Figure 1. ClassificationFigure 1. Classification of the fire danger of the classesfire danger based classes on FWI based in Portugal on FWI (PT)in Portugal and Spain (PT) (SP) and inSpain 12 June (SP) 2014. in 12 The black line representsJune the 2014. border The between black line PT represents and SP. the border between PT and SP.

When the internationalThis study border reports is the crossed, results the of adiscrepancies fire danger assessment that are shown harmonization in Figure based on the 1 arise due to theFWI different calibration methodologies performed forthat the were districts used in and Portugal provinces and enclosed Spain to withinestimate the cooperative the FWI values.zone As 25FWI km is ofbased each on side meteorolog of the internationalical data obtained border. from The weather objective stations, of this study is the it must be recognizedharmonization that each of thestation fire dangerrepresents assessment the microclimate to achieve of a the common place firewhere danger it to support is installed, whichfire management may not represent activities. the The average study was conditions performed in usingthe region the data well. of theAsmain a fire season consequence, ofthe this value region, of FWI typically from froma given 1 June station to 30 does September, not have between the character 2005 to of 2013 an for Portugal absolute valueand but Spain. it must As be a result,considered a table as witha relative FWI classvalue. limits This foris an each additional of the five reason fire danger classes to perform theis calibration proposed toof bethe adopted FWI scale. in the respective regions. The PortugueseBesides decision the specificmakers interestand first of responders the calibration use valuesdata provided found for by the IPMA cross-border area and the correspondingbetween Portugal Spanish andagencies Spain, use this data study provided presents by great AEMET benefits or givenby regional that it can be easily meteorologicalreplicated services, in each other regionsone using of the different globe. fire danger classifications. This discrepancy in data and their interpretation hampers joint actions between the two 2. Methodology countries, both in fire prevention and fire suppression activities. Therefore, the existence of common and2.1. shared Study information Area and Dataset and a mutual interpretation of fire danger is essential for improving the efficiencyThe calibration of collaborative was performed fire management considering operations, the transboundary especially region in the between Portu- transboundarygal areas. and Spain as shown in Figure2. This figure also presents the available climatological This studyweather reports stations the results in the of a study. fire danger assessment harmonization based on the FWI calibration performedThe map for of the Figure districts2 presents and provinces the stations enclosed that existed within in the the cooperative considered period and zone 25 km ofthose each that side were of the used international to calculate theborder. FWI. The objective of this study is the harmonization of theThere fire are danger some assessment meteorological to achieve stations a withcommon missing fire meteorologicaldanger to support data (gaps), since fire managementthe FWIactivities. needs The to be study calculated was performed without gaps, using the the stations data of outside the main 25 kmfire were used to season of thismanage region, thetypically missing from data 1 foundJune to in 30 the September, 25 km study between area. In2005 Portugal, to 2013 IPMA for determines Portugal and Spain.the missing As a result, data bya table interpolation with FWI class to get limits a complete for each dataset.of the five In fire Spain, danger AEMET use the classes is proposedR-package to be CLIMATOLadopted in the [20 ]respective to determine regions. the missing data. The stations outside the 25 km Besides thelimits specific and whichinterest are of markedthe calibration on the mapvalues were found used for to the replace cross-border gaps. area between Portugal andIn Portugal, Spain, this the study territory presents was dividedgreat benefits into districts given that while it can in Spain be easily the territory was replicated in otherdivided regions into provinces.of the globe. Figure 3 presents this administrative organization in both countries for the study area of interest.

Atmosphere 2021, 12, x FOR PEER REVIEW 4 of 21

2. Methodology 2.1. Study Area and Dataset Atmosphere 2021, 12, 1087 The calibration was performed considering the transboundary region between Por- 4 of 20 tugal and Spain as shown in Figure 2. This figure also presents the available climatological weather stations in the study.

Atmosphere 2021, 12Figure, x FOR 2PEER 2.. AreaArea REVIEW of ofinterest interest (25 (25km kmfor each for each side sideof the of transboundary the transboundary strip between stripbetween Portugal Portugaland and5 of 21

Spain) and and available available climatological climatological weather weather stations. stations.

The map of Figure 2 presents the stations that existed in the considered period and those that were used to calculate the FWI. There are some meteorological stations with missing meteorological data (gaps), since the FWI needs to be calculated without gaps, the stations outside 25 km were used to manage the missing data found in the 25 km study area. In Portugal, IPMA determines the missing data by interpolation to get a complete dataset. In Spain, AEMET use the R- package CLIMATOL [20] to determine the missing data. The stations outside the 25 km limits and which are marked on the map were used to replace gaps. In Portugal, the territory was divided into districts while in Spain the territory was divided into provinces. Figure 3 presents this administrative organization in both coun- tries for the study area of interest.

Figure 3. AdministrativeFigure 3. Administrative organization in organization the study area in thefor Portugal study area (PT) for and Portugal Spain (SP). (PT) The and green Spain area (SP). represents The green the Portuguese districts, and the red area represents the Spanish provinces. area represents the Portuguese districts, and the red area represents the Spanish provinces. The area of interest is the strip with a width of 50 km (25 km for each side of the border). Given the different geopolitical characteristics of both countries, we chose to per- form an analysis at district level for Portugal and at Province level for Spain, particularly due to the relevance of these administrative areas for fire management purposes. A second reason to choose this administrative division was the need for sufficient fire occurrence data to develop the proposed calibration process. In many cases, Portuguese districts have a border with more than one Spanish prov- ince, and vice versa (Figure 3). This correspondence was considered, in order to have a common calibration for the adjacent Portuguese districts and Spanish provinces resulting in 14 “district–province pairs”. The calibration was limited to the transboundary strip. The calibration between two adjacent Spanish provinces or two adjacent Portuguese districts was not considered. The dataset is composed by meteorological data and fire history. The temporal scale used in this study was for the main fire season considered from 1 June to 30 September, from 2005 to 2013. For the Spanish provinces of and the meteorologi- cal data were available only from 2006–2013. As defined by [7], the FWI is calculated at 12:00 (local time), since in normal situa- tions, it reflects the most adverse meteorological conditions for (temperature and relative humidity) during the day. The noon meteorological data from the weather sta- tions of IPMA and AEMET were used to determine the historical daily values of FWI: (i) Air temperature, (ii) relative humidity, (iii) wind speed and (iv) rainfall. In the fire history of each region, the number of fires and the burned area in each day were considered. FWI requires a prior calibration to take into account the specific properties of a re- gion, in this study the FWI calibration is performed through the fire history data as pro- posed by [2]. The statistical data on wildfires in Portugal were obtained through [21] while the data for Spain were obtained through [22]. Table 1 presents the period of extension of the statistical dataset, and includes the daily average of number of fires (NF) and burned area (ha) for each region.

Atmosphere 2021, 12, 1087 5 of 20

The area of interest is the strip with a width of 50 km (25 km for each side of the border). Given the different geopolitical characteristics of both countries, we chose to perform an analysis at district level for Portugal and at Province level for Spain, particularly due to the relevance of these administrative areas for fire management purposes. A second reason to choose this administrative division was the need for sufficient fire occurrence data to develop the proposed calibration process. In many cases, Portuguese districts have a border with more than one Spanish province, and vice versa (Figure3). This correspondence was considered, in order to have a common calibration for the adjacent Portuguese districts and Spanish provinces resulting in 14 “district–province pairs”. The calibration was limited to the transboundary strip. The calibration between two adjacent Spanish provinces or two adjacent Portuguese districts was not considered. The dataset is composed by meteorological data and fire history. The temporal scale used in this study was for the main fire season considered from 1 June to 30 September, from 2005 to 2013. For the Spanish provinces of Huelva and Pontevedra the meteorological data were available only from 2006–2013. As defined by [7], the FWI is calculated at 12:00 (local time), since in normal situations, it reflects the most adverse meteorological conditions for wildfires (temperature and relative humidity) during the day. The noon meteorological data from the weather stations of IPMA and AEMET were used to determine the historical daily values of FWI: (i) Air temperature, (ii) relative humidity, (iii) wind speed and (iv) rainfall. In the fire history of each region, the number of fires and the burned area in each day were considered. FWI requires a prior calibration to take into account the specific properties of a region, in this study the FWI calibration is performed through the fire history data as proposed by [2]. The statistical data on wildfires in Portugal were obtained through [21] while the data for Spain were obtained through [22]. Table1 presents the period of extension of the statistical dataset, and includes the daily average of number of fires (NF) and burned area (ha) for each region.

Table 1. Temporal scale and daily average number of fires (NF) and burned area (BA) in the study regions.

Daily Average District (PT) or Province (SP) Season Period NF BA (ha) do Castelo (PT) Jun.–Sep. 2005–2013 5.4 29.1 Pontevedra (SP) Jun.–Sep. 2006–2013 5.3 26.2 (SP) Jun.–Sep. 2005–2013 2.6 14.2 Braga (PT) Jun.–Sep. 2005–2013 8.9 27.2 Vila Real (PT) Jun.–Sep. 2005–2013 5.5 38.5 Bragança (PT) Jun.–Sep. 2005–2013 2.6 25.4 Zamora (SP) Jun.–Sep. 2005–2013 0.6 6.5 Salamanca (SP) Jun.–Sep. 2005–2013 0.2 2.2 Guarda (PT) Jun.–Sep. 2005–2013 3.6 39.4 Castelo Branco (PT) Jun.–Sep. 2005–2013 2.0 11.7 Caceres (SP) Jun.–Sep. 2005–2013 0.5 7.4 Portalegre (PT) Jun.–Sep. 2005–2013 1.2 3.4 (SP) Jun.–Sep. 2005–2013 0.3 1.7 Évora (PT) Jun.–Sep. 2005–2013 1.4 4.1 Beja (PT) Jun.–Sep. 2005–2013 1.3 5.3 Huelva (SP) Jun.–Sep. 2006–2013 0.3 2.7 Faro (PT) Jun.–Sep. 2005–2013 1.8 9.4

Table1 clearly reflects the differences in the number of fires and burned area between Portugal and Spain. There are similarities in Portuguese districts of Viana do Castelo, Braga and Bragança with the Spanish . In the adjacent regions with Salamanca, Badajoz or Huelva the differences are quite large. The low values of fire Atmosphere 2021, 12, 1087 6 of 20

occurrence (both NF, and BA) in some areas, like for example in Huelva, has implications for statistical evaluation.

2.2. Determination of the Daily Value of FWI The daily FWI values were determined according to [7]. The study area is limited by a line 25 km apart from the border between both countries, but for the estimation of FWI weather stations, located in a buffer zone with a width of 35 km to each side of the border were adopted. We used the daily values of the meteorological parameters provided by the weather stations of the Portuguese districts and Spanish provinces to determine the FWI values for each transboundary region. For the regions without a weather station, the meteorological parameters provided by the two nearest weather stations were interpolated to determine the FWI values. Since the data were not available for all the identified stations in Spain, we selected those for which we had more data. The weather stations used in Portugal and in Spain are listed in Table A1 and in Table A2, respectively.

2.3. Calibration In order to calibrate and harmonize the FWI at the border between both countries we followed the methodology proposed in [2]. This study was published in 2004 being applied for Portugal with a dataset from 1988 and 1996 for the period between 15 May and 15 October [2]. The FWI calibration range values and classes presented in [2] for each Portuguese district were used for several years by IPMA [23]. The FWI calibration range values were re-determined by [24] using meteorological data from 2001 to 2012. The values and classes found in [24were very similar to those published by [2] indicating that the calibration method is quite robust and did not change much in the period of 15 years that Separated both sets of data. Considering the required parameters defined in [2], we analyzed for each region the following data: • Daily FWI values • Daily number of fires (NF), and • Daily burned area (BA). Maintaining the correspondence between all data, in each area it was rearranged by ordering the FWI in an ascending order. Afterwards, a numerical incremental field, named incremental day was included, with the value of “1” being attributed to the day with the lowest value of FWI, and consecutively adding “1” to the following data. So the last data is the “total number of days”. The probability (P) is calculated by dividing the Incremental day (dn) number by the total number of days (dTotal) as presented in Equation (1) This cumulative probability reflects the weight that a given day (and its respective FWI) has in respect to the total number of days:

Incremental day (d ) P = n (1) Incremental day total(dTotal)

The FWI values limiting each class of fire danger based on the occurrence probability of a given FWI daily value were established according to the probability or percentile values indicated in Table2. The “probability” term and the “percentile” term have a similar meaning for us; we designate by percentile the group of values of FWI that have a given probability of occurrence that is indicated in the percentile value or class. For example, a percentile P40 refers to all values of FWI, NF, BA, which have a probability of occurrence equal to, or lower than, 0.4. We maintain the word “percentile” as it is a simpler way to refer to the group of values of the data set (FWI, NF, BA) that have a probability of occurrence corresponding to the respective percentile. Atmosphere 2021, 12, 1087 7 of 20

Table 2. Percentile values of FWI used for the initial proposal.

Fire Danger Class Percentile Values 1—Low 0 ≤ FWI < P40 2—Moderate P40 ≤ FWI < P60 3—High P60 ≤ FWI < P80 4—Very High P80 ≤ FWI < P95 5—Maximum FW ≥ P95

The initial classification is based on Table2 of probability of occurrence values and then adjusted to the region of application. The limiting values of the classes of probability are arbitrary and they are established initially based on what is expected for an “average” or “normal” region. To make the classification meaningful, for the final proposal we consider that no more than 5% of the days should be on the “maximum” or extreme class. In some regions we find that there are no more than 2 or 3% of days in the historical record that have outstanding extreme days, and the Maximum (Class 5) percentile threshold was changed accordingly. We also consider that, on average, 40% of the days in a fire season have a low risk, so we set the first class in this percentile; but in some regions, the number of days without fires or with very small fires can correspond to 50 or 60% of the total number of days. In those cases, we have to change the corresponding percentile and the limiting values of FWI. This is applicable to the other intermediate classes so these adjustments can be made with a wide range of discretion without breaking the proposed methodology. Atmosphere 2021, 12, x FOR PEER REVIEW 8 of 21 In order to check the relevance of FWI to assess the fire danger in a given area both in terms of average values of NF and BA, the relationship between the two pairs of variables was performed: FWI and the number of fires (NF). ItIt is is assumed assumed that that in in each each region region in in a asufficiently sufficiently large large period period of oftime, time, there there exists exists a regulara regular and and monotonic monotonic relationship relationship between between the the average average number number of of fires fires NF NF or or of of the the burned area BA, and the value of FWI, expressed respectively by functions f (2) and f (3). burned area BA, and the value of FWI, expressed respectively by functions f11 (2) and f2 2(3).

NFNF= = f𝑓1((FWIFWI)) (2)(2)

BA = f (FWI) (3) BA = 𝑓2(FWI) (3)

FunctionsFunctions f1f 1andand f2f were2 were analyzed analyzed for for the the pairs pairs of of Portuguese Portuguese districts districts and and Spanish Spanish provincesprovinces (see (see Figure Figure 3,3 above)., above). The The pairs pairs “Viana “Viana do Castelo-Pont do Castelo-Pontevedra”,evedra”, “Guarda-Sala- “Guarda- manca”Salamanca” and “Faro-Huelva” and “Faro-Huelva” are presented are presented in Figures in Figures 4, 54 and–6, respectively.6, respectively. Figures Figures for thefor theremaining remaining pairs pairs are are shown shown in Appendixin AppendixB (Figures B (Figures A1– A1–A11).A11).

(a) (b)

FigureFigure 4. 4. AverageAverage number ofof dailydaily firesfires (NF) (NF) and and burned burned area area (BA) (BA) as aas function a function of FWI of FWI for: (for:a) Portuguese (a) Portuguese district district of Viana of Viana do Castelo; and (b) the Spanish province of Pontevedra. do Castelo; and (b) the Spanish province of Pontevedra.

(a) (b) Figure 5. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) Portuguese district of Guarda; and (b) Spanish .

(a) (b) Figure 6. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) Portuguese district of Faro; and (b) the Spanish .

Atmosphere 2021,, 12,, xx FORFOR PEERPEER REVIEWREVIEW 8 of 21

ItIt isis assumedassumed thatthat inin eacheach regionregion inin aa sufficientlysufficiently largelarge periodperiod ofof time,time, therethere existsexists aa regular and monotonic relationship between the average number of fires NF or of the burned area BA, and the value of FWI, expressed respectively by functions ff11 (2)(2) andand ff22 (3).(3).

NF = 𝑓(FWI) (2)(2)

BA = 𝑓(FWI) (3)(3)

Functions ff11 andand ff22 werewere analyzedanalyzed forfor thethe pairspairs ofof PortuguesePortuguese districtsdistricts andand SpanishSpanish provinces (see Figure 3, above). The pairs “Viana do Castelo-Pontevedra”, “Guarda-Sala- manca” and “Faro-Huelva” are presented in Figures 4, 5 and 6, respectively. Figures for thethe remainingremaining pairspairs areare shownshown inin AppendixAppendix BB (Figures(Figures A1–A11).A1–A11).

((a)) ((b)) Atmosphere 2021, 12, 1087 8 of 20 Figure 4. Average number of daily fires (NF) and burned areaarea (BA)(BA) asas aa functionfunction ofof FWIFWI for:for: ((a)) PortuguesePortuguese districtdistrict ofof Viana do Castelo; and (b)) thethe SpanishSpanish provinceprovince ofof PontevedraPontevedra..

((a)) ((b))

FigureFigure 5.. Average 5. Average number number of daily of daily fires fires (NF) (NF) and and burned burned areaarea (BA)(BA) as asasa aa function functionfunction of ofof FWI FWIFWI for: for:for: (a) ( Portuguese(a)) PortuguesePortuguese district districtdistrict of ofof Guarda;Guarda; and ( andb)) SpanishSpanish (b) Spanish provinceprovince province ofof Salamanca ofSalamanca Salamanca...

((a)) ((b))

FigureFigure 6. Average 6. Average number number of daily of daily fires fires (NF) (NF) and and burned burned areaarea area (BA)(BA) asas a aa function functionfunction of ofof FWI FWIFWI for: for:for: (a ) ((a Portuguese)) PortuguesePortuguese district districtdistrict of Faro; ofof Faro;Faro; and (band)) thethe (b SpanishSpanish) the Spanish provinceprovince province ofof Huelva.Huelva. of Huelva.

In the Portuguese districts presented in the previous figures, the FWI increases with overall increase in number of fires and burned area, but in some Spanish Provinces a this behavior was not found. There are some adjacent regions that have similarities as there is a continuity of the landscape, land use, as well as the meteorological conditions reflected in the FWI, that it is the case of the pair of the Portuguese district of Viana do Castelo and the Spanish province of Pontevedra (Figure4). In this pair, the number of fires and burned area (Table1) is also similar which causes the same FWI variation in both regions. The pair of District of Guarda and (Figure5) show that for comparable values of FWI, the values of number of fires and burned area in Guarda are very different from those found in the Province of Salamanca. These differences are mostly due the different topography and land use between these regions. The Portuguese districts are characterized by rugged and mountainous territory elevation while Salamanca is flatter as can be seen in the elevation map of Figure2. We believe that this geologic difference was crucial in the international border historical definition. The topography of each country is indirectly being used in the calibration through the NF and BA, since mountainous regions have associated higher number of fires and burned area. Figure6 presents the pair for the Portuguese district of Faro and the Spanish province of Huelva. In the pair of “Faro-Huelva” the average number of daily fire events is larger in Huelva region, but the burned area is much larger in the Faro region. This may be due to different approaches that are followed by the different fire management strategies followed in Portugal and Spain, like the different policies and resources that are available for higher Atmosphere 2021, 12, 1087 9 of 20

values of FWI. The small number of cases in the Spanish province of Huelva (Table1) has implications for statistical evaluation. The non-monotonic behavior is more evident in the regions where the number of fire events and/or burned area have lower values such as in the southern areas. The relationship between the number of fires and burned area with the FWI depends on the meteorological station used. For example, in Salamanca, depending on the meteo- rological station used, the relationship is different, but the burned area is the same. This fact can be interpreted as the ability of the FWI to describe local conditions, showing that it is a good indicator of the potential extension and intensity of a fire, since high values of burned area are associated with high values of FWI. Considering the analysis of all 14 pairs, we assume that, in general terms, the FWI is a good indicator of fire danger in all these regions in the period of analysis. Since we proposed to determine the FWI threshold values for each pair of Portuguese district and Spanish province, according to the five danger classes adopted, the calibration results are presented in Section3.

2.4. Harmonization We started by calibrating the historical FWI values by assigning them a class using the methodology described previously. A comparison of the fire danger class for the same day and for two adjacent regions of Portugal and Spain was carried out. The percentile adjustments for the final proposal were made mainly in classes 1 and 5, but in some cases, the intermediate classes were also modified. The objective was to have the same number of days in a given class for both sides of the border. This is expressed by the percentiles that were very similar in each class for both sides of the border in the final proposal. It was found that there were cases whereby the proposed classification did not agree on both sides of the border, meaning that, on some days, the class value for Portugal was one value above or below the class value found on the Spanish side. Discrepancies of more than one class were not found in the initial calibration. To quantify these days, the following conditions were counted: • The number of days in which the fire danger class estimated in Portugal was one level lower than the fire danger class estimate in Spain, were labeled “−1”. • The number of days with perfect arrangement (no discrepancies were found), were labeled “0”. • The number of days in which the fire danger class estimated in Portugal was one level higher than the fire danger class estimate in Spain, were labeled “1”. In order to reduce or even avoid the number of discrepancies, the initial threshold FWI values from one side or from both sides were changed. In the end, the same counting was performed. Harmonization results are presented in the Section3.

3. Results 3.1. Calibration Table3 presents the FWI calibration range values and classes considering the two- step process: (i) Initial proposal, and (ii) final proposal resulted from the calibration and harmonization step. The classes numbered from 1 to 5 correspond usually to the following names, respectively: Low, Moderate, High, Very high and Maximum. The influence of local factors, such as orography, is very pronounced in the North of Portugal and Spain (see elevation map in Figure2). This orography influences the FWI values for very close regions where the average meteorological conditions are similar. For example, in Viana Castelo the danger classes change if we take Pontevedra or Ourense, and the same occurs for the other cases. The FWI differences highlighted in Table3 explain the need for harmonization. Atmosphere 2021, 12, 1087 10 of 20

Table 3. FWI values that limit the fire danger classes according to the initial and final proposal. Classes names: 1—Low, 2—Moderate, 3—High, 4—Very high, and 5—Maximum.

District (PT) Fire Danger Classes—Initial Proposal Fire Danger Classes—Final Proposal * Province (SP) 1 2 3 4 5 1 2 3 4 5 Viana do Castelo <28 36 43 53 >53 <24 36 42 61 >61 Pontevedra <12 17 22 35 >35 <10 17 22 42 >42 Viana do Castelo <16 20 27 37 >37 <15 22 27 36 >36 Ourense <2 4 6 10 >10 <2 4 6 10 >10 Braga <21 27 33 43 >43 <21 28 33 47 >47 Ourense <2 4 6 10 >10 <2 4 6 13 >13 Vila Real <22 28 33 42 >42 <22 29 34 45 >45 Ourense <2 4 6 10 >10 <2 4 6 12 >12 Bragança <32 41 45 55 >55 <35 43 51 58 >58 Ourense <1 3 4 6 >6 <2 4 6 7 >7 Bragança <35 41 46 56 >56 <32 40 48 56 >56 Zamora <31 37 44 55 >55 <27 36 46 55 >55 Bragança <33 39 55 >55 <33 39 45 55 >55 45 57 Salamanca <40 48 71 >71 <40 48 57 71 >71 Guarda <30 37 43 54 >54 <18 37 46 57 >57 Salamanca <40 48 57 71 >71 <30 48 61 74 >74 Castelo Branco <35 42 48 57 >57 <20 40 48 71 >71 Caceres <34 38 43 50 >50 <25 37 43 58 >58 Portalegre <37 43 50 58 >58 <37 43 50 58 >58 Cáceres <34 38 43 50 >50 <34 38 43 50 >50 Portalegre <36 42 48 56 >56 <30 43 48 58 >58 Badajoz <33 37 43 53 >53 <28 38 43 54 >54 Évora <36 42 49 59 >59 <32 44 50 60 >60 Badajoz <33 37 43 53 >53 <29 38 44 53 >53 Beja <38 43 48 56 >56 <23 35 48 59 >59 Huelva <30 36 43 54 >54 <19 28 43 60 >60 Faro <39 45 52 68 >68 <33 44 55 69 >69 Huelva <30 36 43 54 >54 <26 34 45 54 >54 * Values determined after the percentile’s adjustments.

In the final proposal, the FWI values for each pair were determined by the harmoniza- tion analysis. The “Fire danger classes—final proposal” (Table3), is the main outcome from the study that can be adopted in wildfire management operations in the transboundary areas. The percentile adjustments between “initial proposal” and “final proposal” were made mainly in “Class 1” and “Class 5” in order to reduce the percentage of days with low danger and avoiding the days with maximum danger (as mentioned in the calibration process). An example of the percentile’s adjustments is presented in Table4 for the pair “Viana do Castelo—Pontevedra”.

Table 4. FWI values and Percentile’s that limit the fire danger classes according to the initial and final proposal for the pair “Viana do Castelo—Pontevedra”. Classes names: 1—Low, 2—Moderate, 3—High, 4—Very high, and 5—Maximum.

District (PT) Initial Proposal Final Proposal Province (SP) Classes 1 2 3 4 5 1 2 3 4 5 Viana do FWI <28 36 43 53 >53 <24 36 42 61 >61 Castelo (PT) Percentile <40 60 80 95 >95 <30 60 78 98 >98 FWI <12 17 22 35 >35 <10 17 22 42 >42 Pontevedra (SP) Percentile <40 60 80 95 >95 <30 60 80 98 >98 Atmosphere 2021, 12, 1087 11 of 20

3.2. Harmonization In Table5, the results of the harmonization exercise for each pair of areas are presented according to the percentile and considering in the initial proposal and the percentile adjustments considering for the final proposal.

Table 5. Number of days in which the fire danger class estimated in Portugal was one level lower than the class estimated in Spain (−1), number of days with perfect agreement (0), and number of days in which the fire danger class estimated in Portugal was one level lower than the class estimated in Spain (1).

Differences Districts (PT)—Provinces (SP) Days Initial Final −1 0 1 −1 0 1 Viana do Castelo—Pontevedra 646 38 604 4 8 634 4 Viana do Castelo—Ourense 881 28 778 75 2 861 18 Braga—Ourense 882 56 814 12 29 853 0 Vila Real—Ourense 881 13 813 55 15 858 8 Bragança—Ourense 774 168 606 0 11 754 9 Bragança—Zamora 594 14 573 7 1 590 3 Bragança—Salamanca 774 1 765 8 1 765 8 Guarda—Salamanca 774 0 744 30 0 769 5 Castelo Branco—Cáceres 800 11 778 11 0 793 7 Portalegre—Cáceres 800 0 793 7 0 793 7 Portalegre—Badajoz 682 2 660 20 12 668 2 Évora—Badajoz 682 3 633 46 6 674 2 Beja—Huelva 349 1 339 9 0 339 0 Faro—Huelva 347 0 338 9 0 347 0

The column “Days” presents the number of days with weather data available and that it was considered suitable for calculating the FWI. For example, in years where the data were available up to a certain day, for example 20 September, we used the data until that day, since we reached a number of days without gaps acceptable for FWI calculation and for the analysis of the pair. Similar situations have occurred for the pairs resulting for each one in a particular number of days for analysis. Considering the differences in the initial proposal, the FWI threshold values were adjusted for each pair. In the final proposal, the number of cases in the “0” column significantly increased. Along with the harmonization performed in the second step, (Table5) the number of days classified as “ −1” was 85 and those classified as “1” was 73 making a total of 158 days with a minor discrepancy of one value in the class. Considering that the total number of days considered in the analysis was 9866, in less than 1.60% of the days the harmonization did not work. This percentage was quite reduced from the 6.37% of the initial proposal. We consider that this is acceptable for practical applications.

4. Discussion To achieve a common methodology and minimize the discrepancies found in the ap- plication of different methodologies by the national meteorological services, we performed a calibration and harmonization of the data based on the FWI, number of fires and burned area. According to the final proposal of Table3, Figure7 presents the result of the study for the buffer strip of about 50 km (25 km for each side) on the 12 June 2014. Comparing with the figure before the data harmonization (Figure1) for the same day, in Figure7 the fire danger classes are more harmonized, making the border operations easier since they should use the same interpretation of the fire danger information. As a representative example Figure8 presents the FWI calibration range values for the class “Very high” (level 4), for the all pairs of Portuguese districts and Spanish provinces, under analysis. The values come from the final proposal for the fire danger (Table3). The figures for the classes “Low” (level 1), “Moderate” (level 2) and “High” (level 3) are Atmosphere 2021, 12, x FOR PEER REVIEW 12 of 21

Portalegre—Cáceres 800 0 793 7 0 793 7 Portalegre—Badajoz 682 2 660 20 12 668 2 Évora—Badajoz 682 3 633 46 6 674 2 Beja—Huelva 349 1 339 9 0 339 0 Faro—Huelva 347 0 338 9 0 347 0

Considering the differences in the initial proposal, the FWI threshold values were adjusted for each pair. In the final proposal, the number of cases in the “0” column signif- icantly increased. Along with the harmonization performed in the second step, (Table 5) the number of days classified as “−1” was 85 and those classified as “1” was 73 making a total of 158 days with a minor discrepancy of one value in the class. Considering that the total number of days considered in the analysis was 9866, in less than 1.60% of the days the harmonization did not work. This percentage was quite reduced from the 6.37% of the initial proposal. We consider that this is acceptable for practical applications.

4. Discussion Atmosphere 2021, 12, 1087 12 of 20 To achieve a common methodology and minimize the discrepancies found in the ap- plication of different methodologies by the national meteorological services, we per- presentedformed a in calibration AppendixC. and The FWIharmonization calibration range of the values da forta based class “Maximum” on the FWI, (level number 5) of fires and areburned any value area. above According those presented to the final for class proposal “Very high”, of Table for this 3, Figure reason the7 presents figure for the result of the classstudy “Maximum” for the buffer is not presented.strip of about 50 km (25 km for each side) on the 12 June 2014.

FigureFigure 7. 7.Classification Classification of the of danger the danger level based level on FWIbased in the on transboundary FWI in the transboundary area between Portugal area between Portu- (PT)gal and(PT) Spain and (SP) Spain in 12 (SP) June 2014—afterin 12 June data 2014—after harmonization. data The harmonization. black line represents The theblack border line represents the betweenborder PTbetween and SP. PT and SP.

FromComparing North to South,with thethe limiting figure valuesbefore of the FWIdata classes harmonization change, having (Figure usually 1) for the same higher values in the Southern regions. If we analyze the fire activity through the cross- borderday, in (see Figure Table1 )7 we the verify fire thatdanger the number classes of occurrencesare more harmonized, and burned areas making are higher the border opera- intions the North, easier which since explains they should the reason use why the the same FWI threshold interpretation values are of lower the fire in southern danger information. regions.As Northern a representative regions are moreexample prone Figure to wildfire 8 pres occurrencesents the so FWI a lower calibration FWI value isrange values for indicativethe class of“Very conditions high” more (level favorable 4), for for the wildfires all pair ins comparison of Portuguese with more districts Southern and Spanish prov- regions. This situation reinforces the need of the FWI calibration based on number of fires inces, under analysis. The values come from the final proposal for the fire danger (Table and burned area. 3). TheFrom figures the Portuguese for the to classes the Spanish “Low” side, we(level can see1), that“Moderate” after the data (level harmonization 2) and “High” (level 3) theare threshold presented FWI in value Appendix is commonly C. The similar FWI on bothcalibration sides of the range border, values however for there class “Maximum” are(level still certain5) are regions any value where above the threshold those FWI presented value changes for abruptlyclass “Very when high”, the border for is this reason the crossedfigure asfor is class the case “Maximum” of Ourense. The is not Spanish presented. presents low values of FWI in comparison to neighboring regions because the Ourense weather station represents local conditions (mountain or valley stations) and do not represent wider areas of the region. Another case is the pair “Guarda—Salamanca”, the Portuguese district of Guarda that has low values of threshold FWI value when it is compared to the Spanish province of Salamanca. Guarda has much higher fire activity (see Table1) and it is also more mountainous than Salamanca (see elevation on Figure2), which can explain the differences. Although two adjacent regions have usually similar meteorological conditions, in this calibration we consider other factors, such as cultural habits in the use of fire and the organization of fire management agencies and policies that contribute to the differences on the limit values of the FWI. In general, the number of fires in the Portuguese Districts is higher than in the Spanish Provinces, which means that, in order to have a high fire danger level in Spain, a much higher FWI value is needed than in Portugal. Some factors that affect the danger level and also have a great relevance in the number of fires and burned area are the specific topography of each country, structural aspects, firefighting response capacity or cultural differences like the use of fire that may produce Atmosphere 2021, 12, 1087 13 of 20

several ignitions. These factors are considered indirectly in the proposed methodology of calibration, since the FWI was calibrated with the number of fires and burned area Atmosphere 2021, 12, x FOR PEER REVIEW 13 of 21 that consider the historical role of those factors. For similar weather conditions, in both countries, the FWI value may the same but the fire danger interpretation is different.

FigureFigure 8.8.Final Final proposalproposal ofof thethe thresholdthreshold FWIFWI valuesvalues forfor each each pair pair of of District District in in Portugal Portugal (PT) (PT) and and ProvinceProvince and and Spain Spain (SP)—Class (SP)—Class “Very “Very high” high” (Level (Level 4 4 of of 5). 5).

5. ConclusionsFrom North to South, the limiting values of the FWI classes change, having usually higherThe values application in the ofSouthern the Canadian regions. Forest If we Fire analyze Weather the Indexfire activity System, through which producesthe cross- theborder FWI (see to assessTable 1) the we fire verify danger that the requires number a priorof occurrences calibration and to burned consider areas the are specific higher characteristicsin the North, which of a region. explains The the proposed reason why calibration the FWI threshold methodology values results are lower in a rangein south- of FWIern regions. values associated Northern regions with fire are danger more prone classes to applied to occurrences each region. so Therefore, a lower FWI the value fire dangeris indicative in a given of conditions region can more be determinedfavorable fo byr wildfires calculating in comparison the meteorological with more index Southern FWI, therebyregions. avoiding This situation the calculation reinforces the of other need conjuncturalof the FWI calibration or combined based indexes, on number which of fires are moreand burned complex area. and require more input data. InFrom this the study, Portuguese a methodology to the Spanish for calibration side, we and can harmonizationsee that after the of data the harmonization FWI to define thethe firethreshold danger FWI classes value between is commonly border regionssimilar ofon Portugalboth sides and of Spainthe border, was developed however there and appliedare still tocertain adjacent regions administrative where the threshold areas (Portuguese FWI value districts changes and abruptly Spanish when provinces) the border of eachis crossed country. as is the case of Ourense. The Spanish province of Ourense presents low values of FWIThe in methodology comparison isto basedneighboring on statistical region datas because of about the nine Ourense years weather of dataon station FWI, repre- daily numbersents local of fires conditions and burned (mountain area for or the valley period stations) between and June do and not September,represent wider between areas 2005 of andthe 2013.region. Another case is the pair “Guarda—Salamanca”, the Portuguese district of GuardaPredefined that has values low values of probability of threshold of occurrence FWI value of FWIwhen values it is compared in each region to the were Spanish used andprovince five danger of Salamanca. classes wereGuarda defined has much (Low, higher Moderate, fire activity High, Very (see highTable and 1) and Maximum). it is also Themore threshold mountainous FWI values than Salamanca for each class (see were elevation determined on Figure resulting 2), which on ancan initial explain proposal the dif- forferences. the fire danger classes. The existence of discrepancies in the estimated fire danger classesAlthough for neighboring two adjacent areas region in a numbers have ofusually days wassimilar observed. meteorological In a second conditions, step, the in thresholdthis calibration FWI values we consider were adjusted other factors, in order such to as harmonize cultural habits the estimation in the use ofof firefire dangerand the andorganization reduce the of number fire management of discrepancies agencies to less and than policies 1.6% ofthat the contribute days. As a to result, the differences threshold valueson the oflimit FWI values to define of the the FWI. fire In danger general, classes the number for each of Portuguese fires in the district Portuguese and SpanishDistricts provinceis higher werethan proposedin the Spanish to harmonize Provinces, the which assessment means inthat, the in transboundary order to have area.a high This fire outcomedanger level corresponds in Spain, to a themuch final higher proposal FWI for value the FWIis needed calibration than in range Portugal. values and classes. Some factors that affect the danger level and also have a great relevance in the num- ber of fires and burned area are the specific topography of each country, structural aspects, firefighting response capacity or cultural differences like the use of fire that may produce several ignitions. These factors are considered indirectly in the proposed methodology of calibration, since the FWI was calibrated with the number of fires and burned area that

Atmosphere 2021, 12, 1087 14 of 20

The relationship of the FWI with number of fires and burned area for all the study regions verified that it is a good indicator of the potential extension and intensity of a wildfire. This methodology can be applied to other transboundary areas, national or interna- tional as the dataset, including the FWI values, the number of fires and the area burned are available. In future work we suggest undertaking the following: (i) Reproduce the methodology for a larger dataset and analyze how the FWI threshold values were changed; (ii) validate the methodology for the most recent years, (iii) analyze other methods of weather data interpolation; (iv) a detailed analysis about the factors that cause the discrepancies (deter- mined in harmonization process) in neighbor’s regions on the border; and (v) study the recent cases of wildfires in the border.

Author Contributions: Conceptualization, D.A., M.A., D.X.V., I.N., M.Y.L.; methodology, D.A., M.A., D.X.V., I.N., M.Y.L.; resources, I.N., M.Y.L.; writing—original draft: D.A., M.A., D.X.V., I.N., M.Y.L.; writing—review & editing: D.A., M.A., D.X.V., I.N., M.Y.L.; supervision, D.X.V. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the research project supported by the Portuguese Science and Technology Foundation-FCT: “FireStorm: Meteorology and fire storm behavior” under the reference PCIF/GFC/0109/2017. Acknowledgments: The Authors wish to acknowledge to European Commission for the sup- port given to project “SpitFire: Spanish-Portuguese Meteorological Information System for Trans- Boundary Operations in Forest Fires” under the agreement number ECHO/SUB/2014/693768. The contribution provided by the following research projects supported by the Portuguese Science and Technology Foundation-FCT is also acknowledged: “MCFire: Measuring the moisture content of forest fuels and assessing their behaviour within the new climate realities” under the reference PCIF/MPG/0108/2017, and “SmokeStorm: “Forecasting and communicating wildland fire smoke effects” under the reference PCIF/MPG/0147/2019. The authors would like to express their gratitude to the SpitFire Colleagues from ADAI, IPMA, AEMET and ANEPC. Daniela Alves would like to thank the project Centro 2020 for its contract with the reference Centro-04-3559-FSE-000144. Conflicts of Interest: The authors declare no conflict of interest.

Appendix A

Table A1. Portuguese weather stations used. The code and the meteo station designations are those used by IPMA.

District Code Weather Station 551 Viana do Castelo 606 Melgaço (Lam. Mouro) Viana do Castelo 605 Monção 615 Ponte de Lima 604 Vila Nova de Cerveira 622 Braga Braga 630 Cabeceiras de Basto 616 Chaves Vila Real 611 Montalegre 575 Bragança 635 Miranda do Douro Bragança 637 Mogadouro 800 Torres de Moncorvo (Sabugal) 671 Almeida (F.C. Rodrigo) Guarda 683 Guarda Atmosphere 2021, 12, 1087 15 of 20

Table A1. Cont.

District Code Weather Station 570 Castelo Branco Castelo Branco 803 Idanha-a-Nova 806 Proença-a-Nova 571 Portalegre Portalegre 835 Elvas 837 Estremoz Évora 558 Évora 562 Beja Beja 863 Mértola 850 Moura Faro 867 Castro Marim

Table A2. Spanish weather stations used. The code and the meteo station designations are those used by AEMET.

Province Code Weather Station Pontevedra 1495 Peinador Ourense 1700X Carballiño O. Zamora 2775X Villar de Ciervos Salamanca 2916A Vitigudino Cáceres 3536X Hoyos

Atmosphere 2021, 12, x FOR PEER REVIEW Badajoz 4452 Badajoz/Talavera16 of 21 Real Huelva 4554X (Pemares) Atmosphere 2021, 12, x FOR PEER REVIEW 16 of 21

Appendix B Appendix B Appendix B

(a) (b)

Figure A1. Average number(a of) daily fires (NF) and burned area (BA) as a function of FWI( bfor:) (a) the Portuguese District Figure A1. Averageof Viana do number Castelo and of daily (b) the fires Spanish (NF) Province and burned of Ourense. area (BA) as a function of FWI for: (a) the Portuguese District of Viana do CasteloFigure andA1. Average (b) the number Spanish of daily Province fires (NF) of Ourense.and burned area (BA) as a function of FWI for: (a) the Portuguese District of Viana do Castelo and (b) the Spanish Province of Ourense.

(a) (b)

Figure A2. Average number of(a daily) fires (NF) and burned area (BA) as a function of FWI(b for:) (a) the Portuguese District of Braga and (b) the Spanish Province of Ourense. Figure A2. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District Figure A2. a Averageof Braga and number (b) the Spanish of daily Province fires (NF) of Ourense. and burned area (BA) as a function of FWI for: ( ) the Portuguese District of Braga and (b) the Spanish Province of Ourense.

(a) (b)

Figure A3. Average number (ofa) daily fires (NF) and burned area (BA) as a function of FWI(b )for: (a) the Portuguese District of Vila Real and (b) the Spanish Province of Ourense. Figure A3. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Vila Real and (b) the Spanish Province of Ourense.

Atmosphere 2021, 12, x FOR PEER REVIEW 16 of 21

Appendix B

(a) (b) Figure A1. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Viana do Castelo and (b) the Spanish Province of Ourense.

Atmosphere 2021, 12, 1087 (a) (b) 16 of 20 Figure A2. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Braga and (b) the Spanish Province of Ourense.

(a) (b) AtmosphereFigure 2021, A3.12, xAverage FOR PEER number REVIEW of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District 17 of 21 Figure A3. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Atmosphereof Vila Real 2021 ,and 12, x ( bFOR) the PEER Spanish REVIEW Province of Ourense. 17 of 21 Vila Real and (b) the Spanish Province of Ourense. Atmosphere 2021, 12, x FOR PEER REVIEW 17 of 21

(a) (b) (a) (b) Figure A4. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District Figure A4. Average number of daily(a) fires (NF) and burned area (BA) as a function of FWI(b) for: (a) the Portuguese District of Figureof A4. Bragança Average and number (b) the Spanish of daily Province fires (NF) of Ourense. and burned area (BA) as a function of FWI for: (a) the Portuguese District Bragançaof Bragança andFigure (b) and theA4. Average( Spanishb) the Spanish number Province ofProvince daily of fires Ourense. of (NF)Ourense. and burned area (BA) as a function of FWI for: (a) the Portuguese District of Bragança and (b) the Spanish Province of Ourense.

(a) (b)

Figure A5. Average number(a )of daily fires (NF) and burned area (BA) as a function of FWI for:(b) (a) the Portuguese District of Bragança and (b) the( aSpanish) Province of Salamanca. (b) Figure A5. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District Figure A5. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Figureof A5. Bragança Average and number (b) the Spanish of daily Province fires (NF) of Salamanca. and burned area (BA) as a function of FWI for: (a) the Portuguese District Bragançaof Bragança and (b) and the ( Spanishb) the Spanish Province Province of Salamanca. of Salamanca.

(a) (b)

Figure A6. Average number of(a )daily fires (NF) and burned area (BA) as a function of FWI( bfor:) (a) the Portuguese District of Bragança and (b) the Spanish . Figure A6. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Bragança and (b) the Spanish Province of Zamora. (a) (b)

FigureFigure A6. Average A6. Average number number of daily of daily fires fires (NF) (NF) and and burned burned area area (BA) (BA) asas aa functionfunction of of FWI FWI for: for: (a ()a the) the Portuguese Portuguese District District of of Bragança and (b) the Spanish Province of Zamora. Bragança and (b) the Spanish Province of Zamora.

Atmosphere 2021, 12, 1087 17 of 20 Atmosphere 2021, 12, x FOR PEER REVIEW 18 of 21 Atmosphere 2021, 12, x FOR PEER REVIEW 18 of 21

Atmosphere 2021, 12, x FOR PEER REVIEW 18 of 21

Atmosphere 2021, 12, x FOR PEER REVIEW 18 of 21

(a) (b) (a) (b) Figure A7. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District Figure A7. Average number of daily(a) fires (NF) and burned area (BA) as a function of FWI(b) for: (a) the Portuguese District of Figureof Castelo A7. Branco Average and number (b) the of Spanish daily fires Province (NF) andof Cáceres. burned area (BA) as a function of FWI for: (a) the Portuguese District CasteloofFigure BrancoCastelo A7. Branco and Average (b and) the number (b Spanish) the ofSpanish( adaily Province) firesProvince (NF) of C ofandáceres. Cáceres. burned area (BA) as a function of FWI(b for:) (a) the Portuguese District ofFigure Castelo A7. Branco Average and number (b) the ofSpanish daily fires Province (NF) ofand Cáceres. burned area (BA) as a function of FWI for: (a) the Portuguese District of Castelo Branco and (b) the Spanish Province of Cáceres.

(a) (b) (a) (b) Figure A8. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District (a) (b) FigureFigureof A8. PortalegreAverage A8. Average and number (b )number the Spanish of dailyof daily Province fires fires (NF) (NF) of andCáceres. and burned burned area area (BA)(BA) asas a function of of FWI FWI for: for: (a) ( athe) the Portuguese Portuguese District District of ofFigure Portalegre A8. Average and (b) numberthe Spanish of (dailya Province) fires (NF)of Cáceres. and burned area (BA) as a function of FWI(b) for: (a) the Portuguese District Portalegre and (b) the Spanish Province of Cáceres. ofFigure Portalegre A8. Average and (b) number the Spanish of daily Province fires (NF)of Cáceres. and burned area (BA) as a function of FWI for: (a) the Portuguese District of Portalegre and (b) the Spanish Province of Cáceres.

(a) (b) (a) (b) Figure A9. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District (a) (b) Figureof Portalegre A9. Average and (b )number the Spanish of daily Province fires (NF) of Badajoz. and burned area (BA) as a function of FWI for: (a) the Portuguese District Figure A9. Average number of( dailya) fires (NF) and burned area (BA) as a function of FWI(b) for: (a) the Portuguese District FigureofA9. PortalegreAverage and number (b) the Spanish of daily Province fires (NF) of andBadajoz. burned area (BA) as a function of FWI for: (a) the Portuguese District of of Portalegre and (b) the Spanish . PortalegreFigure and A9. (b Average) the Spanish number Province of daily fires of Badajoz. (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Portalegre and (b) the Spanish Province of Badajoz.

(a) (b) (a) (b) (a) (b) (a) (b)

Figure A10. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District

of Évora and (b) the Spanish Province of Badajoz.

Atmosphere 2021, 12, x FOR PEER REVIEW 19 of 21

Atmosphere 2021, 12, 1087 18 of 20 Atmosphere 2021, 12, x FOR PEER REVIEW 19 of 21 Figure A10. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Évora and (b) the Spanish Province of Badajoz.

Figure A10. Average number of daily fires (NF) and burned area (BA) as a function of FWI for: (a) the Portuguese District of Évora and (b) the Spanish Province of Badajoz.

(a) (b) (a) (b) FigureFigure A11. A11.Average Average number number of dailyof daily fires fires (NF) (NF) and and burned burned area (BA) (BA) as as a afunction function of FWI of FWI for: for:(a) the (a) Portuguese the Portuguese District District Figureof Beja A11. and Average (b) the numberSpanish of Province daily fires of (NF) Huelva. and burned area (BA) as a function of FWI for: (a) the Portuguese District of Bejaof andBeja and (b) ( theb) the Spanish Spanish Province of ofHuelva. Huelva. Appendix C AppendixAppendix C C

Atmosphere 2021, 12, x FOR PEER REVIEWFigureFigure A12. A12. FinalFinal proposal proposal of the threshold of the threshold FWI values FWIfor each values pair of for District each in pair Portugal of District (PT) andin Portugal20 of 21 (PT) and

ProvinceProvince and and Spain Spain (SP)—Class (SP)—Class “Low” (Level “Low” 1 of (Level 5). 1 of 5). Figure A12. Final proposal of the threshold FWI values for each pair of District in Portugal (PT) and Province and Spain (SP)—Class “Low” (Level 1 of 5).

FigureFigure A13. A13. FinalFinal proposal proposal of the of threshold the threshold FWI values FWI values for each for pair each of District pair of in District Portugal in (PT) Portugal and (PT) and Province and Spain (SP)—Class “Moderate” (Level 2 of 5). Province and Spain (SP)—Class “Moderate” (Level 2 of 5).

Figure A14. Final proposal of the threshold FWI values for each pair of District in Portugal (PT) and Province and Spain (SP)—Class 3 of 5 danger classes.

References 1. Viegas, D.X.; Bovio, G.; Ferreira, A.; Nosenzo, A.; Sol, B. Comparative study of various methods of fire danger evaluation in southern Europe. Int. J. Wildland Fire 1999, 9, 235–246, doi:10.1071/wf00015. 2. Viegas, D.X.; Reis, R.M.; Cruz, M.G.; Viegas, M.T. Calibração do sistema Canadiano de Perigo de Incêndio para apli-cação em Portugal. Silva Lusit. 2004, 12, 77–94. (In Portuguese) 3. Countryman, C.M. Rating fire danger by the multiple basic index system. J. For. 1966, 64, 531–536. 4. Costa, H.; de Rigo, D.; Libertà; G.; Houston Durrant, T.; San-Miguel-Ayanz, J. European Wildfire Danger and Vulnerability in a Changing Climate: Towards Integrating Risk Dimensions, EUR 30116 EN; Publications Office of the European Union: Luxembourg, 2020, ISBN 978-92-76-16898-0, doi:10.2760/46951. 5. Viegas, D.X.; Rossa, C.; Ribeiro, L.M. Incêndios Florestais; Verlag Dashofer: Lisboa, Portugal, 2011. 6. Stocks, B.J.; Lynham, T.J.; Lawson, B.D.; Alexander, M.E.; Van Wagner, C.E.; McAlpine, R.S.; Dubé, D.E. Canadian Forest Fire Danger Rating System: An Overview. For. Chron. 1989, 65, 258–265, doi:10.5558/tfc65258-4. 7. Van Wagner, C.E. Development and structure of the Canadian Forest Fire Weather Index System; Ontario Technical Report 1987; Government of Canada, Canadian Forestry Service: Ottawa, ON, Canada, 1987; 37p.

Atmosphere 2021, 12, x FOR PEER REVIEW 20 of 21

Atmosphere 2021, 12, 1087 19 of 20 Figure A13. Final proposal of the threshold FWI values for each pair of District in Portugal (PT) and Province and Spain (SP)—Class “Moderate” (Level 2 of 5).

Figure A14. Final proposal of the threshold FWI values for each pair of District in Portugal (PT) and Province and Spain (SP)—Class 33 ofof 55 dangerdanger classes.classes.

ReferencesReferences 1.1. Viegas, D.X.;D.X.; Bovio,Bovio, G.;G.; Ferreira,Ferreira, A.;A.; Nosenzo,Nosenzo, A.;A.; Sol,Sol, B.B. ComparativeComparative study of variousvarious methodsmethods of firefire dangerdanger evaluationevaluation inin southernsouthern Europe.Europe. Int.Int. J. Wildland FireFire 1999,, 99,, 235–246.235–246, [doi:10.1071/wf00015.CrossRef] 2.2. Viegas, D.X.;D.X.; Reis,Reis, R.M.;R.M.; Cruz,Cruz, M.G.;M.G.; Viegas,Viegas, M.T.M.T. CalibraçCalibraçãoão dodo sistemasistema CanadianoCanadiano dede PerigoPerigo dede IncIncêndioêndio parapara apli-caçapli-caçãoão emem Portugal. Silva Lusit. 2004, 12, 77–94. (In Portuguese) 3.3. Countryman, C.M.C.M. RatingRating firefire dangerdanger byby thethe multiplemultiple basicbasic indexindex system.system. J.J. For.For. 19661966,, 6464,, 531–536.531–536. 4.4. Costa, H.; de Rigo, D.; LibertLibertà;à, G.; HoustonHouston Durrant, T.; San-Miguel-Ayanz,San-Miguel-Ayanz, J. European WildfireWildfire DangerDanger andand VulnerabilityVulnerability inin aa ChangingChanging Climate:Climate: Towards IntegratingIntegrating RiskRisk Dimensions,Dimensions, EUREUR 30116 EN;; PublicationsPublications OfficeOffice ofof the European Union: Luxembourg, 2020;2020, ISBNISBN 978-92-76-16898-0.978-92-76-16898-0, [doi:10.2760/46951.CrossRef] 5.5. Viegas, D.X.;D.X.; Rossa,Rossa, C.;C.; Ribeiro,Ribeiro, L.M.L.M. IncIncêndiosêndios FlorestaisFlorestais;; VerlagVerlag Dashofer: Dashofer: Lisboa, Lisboa, Portugal, Portugal, 2011. 2011. 6.6. Stocks, B.J.; Lynham, T.J.; Lawson,Lawson, B.D.; Alexander, M.E.; Van Wagner,Wagner, C.E.;C.E.; McAlpine,McAlpine, R.S.;R.S.; DubDubé,é, D.E.D.E. CanadianCanadian ForestForest FireFire Danger RatingRating System:System: An Overview. For.For. Chron.Chron. 19891989,, 6565,, 258–265.258–265, [doi:10.5558/tfc65258-4.CrossRef] 7.7. Van Wagner,Wagner, C.E.C.E.Development Development andand Structurestructure ofof thethe CanadianCanadian ForestForest FireFire WeatherWeather IndexIndex SystemSystem;; OntarioOntario ForestryForestry TechnicalTechnical ReportReport 1987;1987; GovernmentGovernment ofof Canada,Canada, CanadianCanadian ForestryForestry Service:Service: Ottawa,Ottawa, ON,ON, Canada,Canada, 1987;1987; 37p.37p. 8. Amiro, B.D.; Logan, K.A.; Wotton, B.M.; Flannigan, M.; Todd, J.B.; Stocks, B.J.; Martell, D.L. Fire weather index system components for large fires in the Canadian boreal forest. Int. J. Wildland Fire 2004, 13, 391–400. [CrossRef] 9. Good, P.; Moriondo, M.; Giannakopoulos, C.; Bindi, M. The meteorological conditions associated with extreme fire risk in Italy and Greece: Relevance to climate model studies. Int. J. Wildland Fire 2008, 17, 155–165. [CrossRef] 10. Tian, X.; McRae, D.J.; Jin, J.; Shu, L.; Zhao, F.; Wang, M. Wildfires and the Canadian Forest Fire Weather Index system for the Daxing’anling region of China. Int. J. Wildland Fire 2011, 20, 963–973. [CrossRef] 11. Carrega, P. A Meteorological Index of Forest Fire Hazard in Mediterranean France. Int. J. Wildland Fire 1991, 1, 79–86. [CrossRef] 12. De Vicente, J.; Crespo, F. A new wildland fire danger index for a Mediterranean region and some validation aspects. Int. J. Wildland Fire 2012, 21, 1030–1041. [CrossRef] 13. Mestre, A.; Allue, M.; Peral, C.; Santamaría, R.; Lazcano, M. Operational Fire Danger System in Spain. In Proceedings of the International Workshop on Advances in Operational Weather Systems for Fire Danger Rating, Edmonton, AB, Canada, 14–16 July 2008. 14. Romero, R.; Mestre, B.A.; Botey, M.R. Nueva Calibración para el Índice de Incendios en AEMET. XXXIII Jornadas Científicas de la Asociación Meteorológica Española. 2014. Available online: http://hdl.handle.net/20.500.11765/6039 (accessed on 17 April 2021). 15. Carvalho, A.; Flannigan, M.; Logan, K.; Miranda, A.; Borrego, C. Fire activity in Portugal and its relationship to weather and the Canadian Fire Weather Index System. Int. J. Wildland Fire 2008, 17, 328–338. [CrossRef] 16. Mestre, A.; Manta, M.I. A fire weather index as a basis for an early warning system in Spain. Int. J. Wildland Fire 2014, 23, 510–519. [CrossRef] 17. Padilla, M.; Vega-García, C. On the comparative importance of fire danger rating indices and their integration with spatial and temporal variables for predicting daily human-caused fire occurrences in Spain. Int. J. Wildland Fire 2011, 20, 46–58. [CrossRef] 18. Martins, M. 1st SpitFire Workshop: Operational Pt. Autoridade Nacional de Emergência e Proteção Civil, Lisboa. 2015. Available online: https://firehelp.wixsite.com/spitfire/events (accessed on 18 August 2021). Atmosphere 2021, 12, 1087 20 of 20

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