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Do climate teleconnections modulate wildfire-prone conditions over the Iberian Peninsula?

Abstract

Climate teleconnections (CT) synchronize and influence weather features such as temperature, precipitation and, subsequently, drought and fuel moisture in many regions across the globe. CTs thus may be related to cycles in wildfire activity, and thereby help fire managers to anticipate fire-prone weather conditions as well as envisaging their future evolution. A wide number of CTs modulate weather in the Iberian Peninsula, exerting different levels of influence at different spatial and seasonal scales on a wide range of weather factors. In this work, we investigated the link between the most relevant CT patterns in the Iberian Peninsula (IP) and fire activity and danger, exploring different spatial and temporal scales of aggregation. We analyzed a period of 36 years (1980-2015) using historical records of fire events (>100ha burned) and the Canadian Fire Weather Index (FWI). Cross-correlation analysis was performed on monthly time series of CTs and fire data. Results pointed towards the North Atlantic Oscillation (in the western half of the IP) and Mediterranean Oscillation Index (along the Mediterranean coast) as the key CTs boosting burned area and fire weather danger in the IP. Both CTs relate to the relative position of the Azorean anticlone, fostering hazardous fire weather conditions during their positive phases, i.e., low rainfall and warm temperature leading to low fuel moisture content. The Scandinavian pattern index also played an important role in the western half of the Peninsula, linked to a decrease in rainfall during its negative phases. Nonetheless, the association between the CTs and burned area (up to 0.5 Pearson's R p<0.05) was weaker than the observed between CTs and FWI (up to 0.75 Pearson's R p<0.05). Rodrigues, Marcos; Peña-Angulo, Dhais; Russo, Ana; Zúñiga Antón, María; Cardil, Adrián

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Do climate teleconnections modulate wildfire-prone conditions over the Iberian Peninsula?

Author: Rodrigues, Marcos; Russo, Ana; Peña-Angulo, Dhais; Cardil, Adrián; Zúñiga Antón, María
Year: 2021
DOI: 10.1088/1748-9326/abe25d
Source: https://zaguan.unizar.es/record/101271/files/texto_completo.pdf
LETTER • OPEN ACCESS
Do clima e eleconnec ions modula e wild i e-p one condi ions o e he
Ibe ian Peninsula?
To ci e his a icle: Ma cos Rod igues e al 2021 En i on. Res. Le . 16 044050
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LETTER
Do clima e eleconnec ions modula e wild i e-p one condi ions
o e he Ibe ian Peninsula?
Ma cos Rod igues1,2,8,∗, Dhais Peña-Angulo3, Ana Russo4, Ma ía Z´
uñiga-An ón5
and Ad i´
an Ca dil2,6,7
1Depa men o Ag icul u al and Fo es enginee ing, Uni e si y o Lleida, Lleida, Spain
2Join Resea ch Uni CTFC—AGROTECNIO—CERCA, Solsona, Spain
3Ins i u o Pi enaico de Ecología, Consejo Supe io de In es igaciones Cien í icas (IPE–CSIC), Za agoza, Spain
4Ins i u o Dom Luiz (IDL), Faculdade de Ciˆ
encias, Uni e sidade de Lisboa, Campo G ande, 1749–016 Lisboa, Po ugal
5GEOT G oup, IUCA, Depa men o Geog aphy and Te i o ial Planning, Uni e si y o Za agoza, Za agoza, Spain
6Depa men o C op and Fo es Sciences, Uni e si y o Lleida, Lleida, Spain
7Technosyl a Inc, La Jolla, CA, Uni ed S a es o Ame ica
8GEOFOREST G oup, IUCA, Depa men o Geog aphy and Te i o ial Planning, Uni e si y o Za agoza, Za agoza, Spain
∗
Au ho o whom any co espondence should be add essed.
E-mail: ma cos. od [email p o ec ed]
Keywo ds: wild i es, clima e eleconnec ions, i e dange , bu ned a ea, Ibe ian Peninsula
Supplemen a y ma e ial o his a icle is a ailable online
Abs ac
Clima e eleconnec ions (CT) synch onize and in luence wea he ea u es such as empe a u e,
p ecipi a ion and, subsequen ly, d ough and uel mois u e in many egions ac oss he globe.
CTs hus may be ela ed o cycles in wild i e ac i i y, and he eby help i e manage s o an icipa e
i e-p one wea he condi ions as well as en isaging hei u u e e olu ion. A wide numbe o CTs
modula e wea he in he Ibe ian Peninsula (IP), exe ing di e en le els o in luence a di e en
spa ial and seasonal scales on a wide ange o wea he ac o s. In his wo k, we in es iga ed he link
be ween he mos ele an CT pa e ns in he IP and i e ac i i y and dange , explo ing di e en
spa ial and empo al scales o agg ega ion. We analyzed a pe iod o 36 yea s (1980–2015) using
his o ical eco ds o i e e en s (>100 ha bu ned) and he Canadian Fi e Wea he Index (FWI).
C oss-co ela ion analysis was pe o med on mon hly ime se ies o CTs and i e da a. Resul s
poin ed owa ds he No h A lan ic Oscilla ion (in he wes e n hal o he IP) and Medi e anean
Oscilla ion Index (along he Medi e anean coas ) as he key CTs boos ing bu ned a ea (BA) and
i e wea he dange in he IP. Bo h CTs ela e o he ela i e posi ion o he Azo ean an iclone,
os e ing haza dous i e wea he condi ions du ing hei posi i e phases, i.e. low ain all and wa m
empe a u e leading o low uel mois u e con en . The Scandina ian pa e n index also played an
impo an ole in he wes e n hal o he Peninsula, linked o a dec ease in ain all du ing i s
nega i e phases. None heless, he associa ion be ween he CTs and BA (up o 0.5 Pea son’s R
p< 0.05) was weake han he obse ed be ween CTs and FWI (up o 0.75 Pea son’s R p < 0.05).
1. In oduc ion
Modes o sea su ace empe a u e (SST) and associ-
a ed clima e eleconnec ions (CT) a e known o in lu-
ence and synch onize wea he om sub-con inen al
o local scales [1], including empe a u e, p ecipi a-
ion and, subsequen ly, d ough [2–4]. These wea he
ea u es ha e a s ong impac on he occu ence and
beha io o wild i es, by al e ing uel mois u e and
igni ion p obabili y o igge ing ligh ning i e e en s
[5–9]. The ole o clima e- ela ed ac o s is expec ed
o s eng hen in he u u e, se ing a con ex in which
CTs a e expec ed o ampli y hei e ec s [10–12].
Se e al au ho s ha e conduc ed esea ch in o
CT pa e ns and hei ela ion wi h clima ic a i-
ables a di e en empo al and spa ial scales wo ld-
wide [13–16] and, speci ically, in he Ibe ian Pen-
insula (IP [17–21]); one o he mos i e-a ec ed
egions in Medi e anean Eu ope [22]. A wide ange
o CTs in luence wea he ac o s in he Wes e n
© 2021 The Au ho (s). Published by IOP Publishing L d
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Medi e anean basin [23], namely he No h A lan ic
Oscilla ion (NAO), he A lan ic Mul idecadal Oscil-
la ion (AMO), he Eas A lan ic (EA) eleconnec-
ion pa e n index, he ‘Niño’ 3.4 SST index (ENSO),
he Medi e anean Oscilla ion (MOI), he Paci ic
Decadal Oscilla ion (PDO), he Scandina ian pa -
e n (SCAND) and he Wes e n Medi e anean oscil-
la ion (WeMOi). Fo ins ance, he annual amoun
o ain all was signi ican ly linked o he WeMOi,
EA, NAO, ENSO, whe eas blocking episodes in he
IP we e linked o SCAND pa e ns [24]. The sea-
sonal and spa ial a iabili y in mean empe a u e was
also associa ed o he di e en phases o CTs. The
NAO and EA pa e ns we e posi i ely co ela ed wi h
annual mean empe a u e in he IP. In u n, he co -
ela ion be ween WeMOi and empe a u e depic s a
g adien , being nega i e in he no h bu posi i e o e
he Medi e anean coas [18]. Mo eo e , he AMO
has been epo ed o con ol he a iabili y in sum-
me leng h o e Eu ope, pa icula ly a e 1979 [25].
Ex ensi e esea ch has been de o ed o un a el-
ling he link be ween CTs and i e ac i i y, showing
how changes in wea he media ed by CTs can di ec ly
impac bu ned a ea (BA) in many egions ac oss he
wo ld [23,26–34]. The analysis o he e ec s o CTs
on wea he , i e dange and ac i i y is no s aigh o -
wa d [35] as hey a e non-s a iona y and associa ions
may a y o e space a sub-con inen al scales. Like-
wise, me hodological app oaches a y depending on
he pu sued goals. Co ela ion and eg ession analysis
using ime se ies [23,33–35] and - es [36] we e e-
quen ly applied when dealing wi h ‘local’ spa ial pa -
e ns, while mo e sophis ica ed echniques (wa ele
cohe ence o supe posed epoch analysis) ha e been
used o p o ide in-dep h insigh s a sub-con inen al
scales [32,37–39]. Some s udies op ed by analyzing
he in luence o clima e on i es based on ci cula ion-
wea he pa e ns [5,6,40] o local-scale wea he
o cing condi ions [41]. Recen ad ances in Global
Clima e Models (GCMs) o e an al e na i e o s a -
is ical app oaches [42] hough uncommon in he li -
e a u e [38,39]. Howe e , aw GCM’s ou pu s canno
be di ec ly used o quan i a i e wild i e e alua ions.
Sys ema ic biases o he models om o he obse ed
clima e leads o signi ican de iancies o i s s a is ical
p ope ies [43]. Fu he mo e, hei coa se spa ial es-
olu ion is usually no sui able o add essing he local
i e-wea he condi ions [42].
Howe e , s udies add essing CTs and wild i es in
he Medi e anean Eu ope a e sca ce, e en hough
he unde s anding o he clima e- i e dependen ela-
ionships would allow an icipa ing i e dange , hus
imp o ing p e en ion and p epa edness (e.g. s a-
egically a ange supp ession esou ces o educe uel
loads).
Mul iple ac o s may exe an in luence in i e
ac i i y and i e wea he . As a consequence, he IP
is qui e di e se in e ms o i e egimes and i s
unde lying d i e s, which a y ac oss ime and space
[44–46]. A ecen wo k by [23] epo ed no iceable
co ela ion be ween SCAND, NAO and MOI/WeMOI
in Spain and Po ugal, hough hei CT- ela ed ana-
lyses we e conduc ed a he na ional (coun ywide)
and yea ly scales in di e en ime ames (s a -
ing in he 70s un il 2017). None heless, he e is
e idence o CT in e ac ions modula ing and exace -
ba ing wea he a iabili y [32,36,37], subsequen ly
in luencing i e ac i i y [47]. Howe e , he e is no a
clea pic u e o he e ec s o CT on i e ac i i y in he
IP, and speci ically on he coupled e ec s o CTs, on
i e ac i i y a mul iple empo al scales o agg ega ion.
The e o e, wi h his pape we in end o ill he
e e ed lacunae, aiming a iden i ying he in luence
o he mos signi ican SST modes and CTs, indi idu-
ally o coupled, a ec ing i e dange and ac i i y in
he IP. We de eloped a no el amewo k o un a el
he spa ial pa e ns o he mos in luen ial CTs while
iden i ying syne gies and empo al scales modula -
ing hei signal. We u he ex end o e o me ana-
lyses by digging in o he spa ial dis ibu ion o he
links be ween wild i es and CTs, p o iding a ans-
bounda y assessmen using homogeneous i e egime
zones, deepe insigh s in o mon hly and seasonal
associa ions, and inco po a ing wild i e dange a ing
indices in o he assessmen . Speci ically, we add ess
he ollowing esea ch ques ions: (a) how do CTs
ela e o me eo ological i e-wea he a ing indices
and i e ac i i y? (b) do CT-wild i e ela ionships a y
o e space? (c) a e he e coupled e ec s among CTs
leaning owa ds a empo al window wi h highe i e
dange and/o ac i i y? (d) is he e ec o CTs indices
on i e dange and i e ac i i y lagged in anyway?
2. Ma e ials and me hods
2.1. Da a
2.1.1. Fi e da a
His o ical i e da a was e ie ed om he Spanish
EGIF (‘Es adís ica Gene al de Incendios Fo es ales’)
[48] and Po uguese DECIF (‘Disposi i o Especial
de Comba e a Incˆ
endios Flo es ais’) [49] o icial i e
da abases. We compiled a ha monized da ase ga h-
e ing i e eco ds om bo h da abases. Acco ding o
Pe ei a e al [49], i es below he 100 ha h eshold
we e no compiled consis en ly du ing he 80s. To
ensu e he homogenei y (missing eco ds, lack o
in o ma ion, e c) in he inal i e da ase , we selec-
ed only hose i e e en s la ge han 100 ha in he
pe iod 1980–2015. Addi ional in o ma ion including
he s a ing loca ion (a NUTS3 le el) and he da e
o igni ion was also e ie ed om i e da abases o
enable u he analyses.
Fi es we e o ganized acco ding o hei py o e-
gion o o igin (see igu e 1) as ou lined by T igo e al
[44], who de ined ou mac o egions wi h homo-
geneous i e egimes (N: No h, NW: No hwes , SW:
Sou hwes and E: Eas ). Then, i e e en s we e agg eg-
a ed on a mon hly basis in e ms o BA.
2
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Figu e 1. Desc ip ion o he s udy egion. (A) Spa ial dis ibu ion o numbe o i e e en s and no malized bu ned a ea (bu ned
a ea di ided by egion size) a NUTS3 le el, 1980–2015; (B) physical map o he Ibe ian Peninsula.
2.1.2. Fi e wea he dange
We used he Canadian Fi e Wea he Index (FWI)
as an indica o o i e-conduci e wea he condi-
ions. The FWI [50] is a nume ical a ing sys em
ha summa izes he chances o a i e o igni e
and p opaga e, widely used o moni o and o esee
haza dous condi ions (e.g. he Eu opean Fo es Fi e
In o ma ion Sys em). I is based on a combina ion o
componen s buil -up om aw wea he in o ma ion
such as ela i e humidi y, accumula ed ain all in he
las 24 h, empe a u e and wind speed. The FWI da a
we e gene a ed by he Eu opean Cen e o Medium-
Range Wea he Fo ecas s om he ERA5 eanalysis
da ase [51]. Daily g ids o FWI a 0.25◦ esolu ion
we e e ie ed om he Cope nicus Clima e Sys em
(C3S), la e agg ega ed in o mon hly ime se ies as he
mean FWI pe mon h and g id cell. No e ha he g id
cell se ed as spa ial uni o analysis in FWI analyses
whe eas BA was add essed a egion le el.
2.1.3. Clima e eleconnec ions
We chose he mos impo an CT pa e ns (a
mon hly le el) in he Wes e n Medi e anean Basin
based on p e ious s udies ([2,24,44,49,50];
able S1 (a ailable online a s acks.iop.o g/ERL/16/
044050/mmedia)): NAO, AMO, EA, ENSO (El Niño),
MOI, PDO, SCAND, and WeMOi.
The NAO pa e n has been quan i ied by means
o he dipole-like s anda dized su ace p essu e
di e ence be ween he No h A lan ic Sub opical
High (whose da a can be aken om Pon a Delgada-
Azo es, Lisbon o Gib al a ) and a second s a ion
close o he Icelandic Low (Reykja ik) [52]. The pos-
i i e phase in ol es a subs an ial de elopmen o a
low p essu e cen e in Iceland and a high p essu e
cen e o e he Azo es, which is associa ed o below-
no mal ain all o e sou he n Eu ope. The oppos-
i e pa e n is ound du ing nega i e phases, when
he Icelandic Low and he Azo es High a e weake
han usual. The EA is s uc u ally simila o NAO.
I consis s o a no h–sou h dipole o anomaly cen-
e s spanning he No h A lan ic om eas o wes
[53]. The posi i e phase o EA is associa ed wi h
a wa m condi ions in Wes e n Eu ope and below-
a e age p ecipi a ion ac oss sou he n Eu ope. The
AMO pa e n is de ined as a de ended a e age o
3
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
SST anomalies in he No h A lan ic [54]. The pos-
i i e phase o he AMO is associa ed wi h inc eased
mean su ace ai empe a u e, especially p onounced
o e No h Ame ica and Eu ope du ing summe [55].
The SCAND consis s o a p ima y ci cula ion cen e
o e Scandina ia, wi h weake cen e s o opposi e
sign o e wes e n Eu ope and eas e n Russia/wes e n
Mongolia [54]. The posi i e phase o SCAND is
associa ed wi h abo e-a e age p ecipi a ion ac oss
cen al and sou he n Eu ope. The MOI was de ined
in o de o explain opposing a mosphe ic dynam-
ics be ween he wes e n and eas e n sec o s o he
Medi e anean basin. The MOI is ma ked as he no -
malized p essu e di e ence be ween Algie s and El
Cai o [53]. A second e sion o his index can be
calcula ed as he di e ence o s anda dized p essu e
anomalies a Gib al a and he Is aeli me eo ological
s a ion o Lod. The WeMOi pa e n is calcula ed as
a s anda dized p essu e di e ence be ween no he n
I aly (Padua) and sou he n Spain (San Fe nando).
The posi i e phase is cha ac e ized by he an icyc-
lone o e he Azo es and a low-p essu e cen e o e
he Gul o Genoa; he nega i e phase comp ises he
Cen al Eu opean an icyclone loca ed in he no h
o I aly, and low-p essu es in he Gul o Cadiz [24].
The ENSO/‘Niño’ 3.4 SST index was calcula ed om
he HadISST1 as he a e age o SST anomalies o e
he egion om 5◦S–5◦N o 170–120◦W [56]. The
PDO is mos equen ly e e ed o as a long-li ed
El-Niño like pa e n o he Paci ic clima e a iabili y.
The PDO pa e n is de i ed as he leading p incipal
componen (PC) o mon hly SST anomalies in he
No h Paci ic Ocean, polewa d o 20◦N [57].
2.2. S a is ical analyses
2.2.1. PC analysis
PC analysis (PCA) o mon hly ime se ies o CTs
was applied o add ess po en ial synch onic e ec s
o in e ac ions be ween hem, and o build a smal-
le subse o CT indices. PC we e selec ed acco ding
o he Kaise c i e ion, i.e. e aining hose PCs wi h
s anda d de ia ion highe han 1 [56]. The con ibu-
ion o each CT o each PC was add essed ia a -
imax o a ion [58]. PCA loadings and sco es we e
subsequen ly compa ed o mon hly ime se ies o BA,
analyzing each egion sepa a ely.
2.2.2. C oss-co ela ion ime se ies analysis
The co e o ou s a is ical analysis is based on he
calcula ion o Pea son’s c oss-co ela ion R coe i-
cien s a mul iple empo al and spa ial scales. Pai ed
mon hly ime se ies o BA, CTs and FWI we e
explo ed o in es iga e he lagged associa ion o BA
and CTs, and FWI and CTs, espec i ely. Fou di -
e en iming windows o FWI and BA we e in es ig-
a ed (Ap il–June, AMJ; May–July, MJJ; June–Augus ,
JJA; and July–Sep embe , JAS) o accoun o po en-
ial di e ences be ween ea ly o la e summe condi-
ions ( igu e 2). Se e al lag in e als (i.e. synch ony,
Figu e 2. Illus a ion o empo al scales o agg ega ion.
O ange indica es he empo al window o FWI o BA (JJA
in he example). (A) 3 mon h agg ega ion (scale) o CTs,
wi h lag 0 (synch onic o FWI/BA); (B) 4 mon h scale,
lag 0; (C) 5 mon hs scale, lag −1; (D) 6 mon h scale, lag −2.
om 0 o 6 mon hs be o e) and scales o agg ega ion
( om 3 o 6 a e aged mon hs) o CTs wi h BA and
CTs we e analyzed (see igu e 2).
S a iona i y in he ime se ies was es ed be o e
he co ela ion analysis was pe o med using he Aug-
men ed Dickey–Fulle es [57]. Those se ies ound
non-s a iona y we e de ended by sub ac ing he
end componen a e applying a Seasonal-T end
decomposi ion [59]. Co ela ions be ween BA and
coupled CTs we e add essed a egional le el, calcu-
la ing he co ela ion be ween 3 mon h a e aged BA
( o accoun o a season-like ime span) and PCA’s
sco es. BA assessmen s we e conduc ed in he ou
i e egions ( igu e 1) sepa a ely. Co ela ion ou pu s
o BA we e o ganized based on he combina ion o
egion and ime window, epo ing he mos co -
ela ed lag and scale ( able 2). Co ela ions be ween
FWI and indi idual CTs we e calcula ed a FWI pixel
le el (0.25◦). Co ela ions we e summa ized as a se o
maps epo ing he mos and second mos co ela ed
CT pe pixel ( igu e 4) and i s co esponding ime
window, lag and scale o agg ega ion ( igu e 5).
3. Resul s
3.1. Associa ion be ween CT pa e ns and BA
We e ained ou PCs (labeled om PC1 o PC4)
acco ding o he Kaise c i e ion, explaining 72% o
he o iginal a iance. Each PC depic ed a speci ic
pa e n o associa ion wi h CT eleconnec ion pa -
e ns ( igu e 3; see h ps://c s-ba-ip.ne li y.app [60]
o addi ional ou pu s) ha was cha ac e ized acco d-
ing o he loading con ibu ion o each indi idual
CT p ojec ed o each componen ( able 1). Below we
desc ibe he ou main componen s a ending o he
mos ele an CTs:
•PC1: synch onic MOI, NAO (bo h show a close
loading alue and sign, −0.54) and WeMOi
(−0.38) opposed o he AMO phase (0.30). The
highes he PC’s sco e he lowe he associa ion
wi h MOI/NAO/WeMOi. Likewise, high sco es
poin owa ds a low AMO index.
4

En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Figu e 3. In e ac ion be ween CTs (PC1 and PC2) and seasonal dis ibu ion o bu ned a ea in he Ibe ian Peninsula (1980–2015).
Colo indica es season whe eas size ela e o bu ned a ea. Each do ep esen s he BA in an indi idual mon h.
Table 1. Summa y o p incipal componen analysis. Sd, s anda d de ia ion; Exp. Va , explained a iance; Cum. Va , accumula ed
a iance. Bold ace indica es signi ican loadings in Va imax o a ion. Loadings highe han 0.4 we e highligh ed in g ay.
Summa y Loadings
Sd Exp. a Cum. a AMO EA MOI NAO ENSO PDO SCAND WeMOi
PC1 1.36 0.23 0.23 0.30 −0.23 −0.54 −0.54 −0.20 −0.23 0.20 −0.38
PC2 1.30 0.21 0.44 −0.47 −0.31 −0.22 −0.25 0.42 0.61 0.15 −0.02
PC3 1.06 0.14 0.58 0.36 0.56 −0.07 0.04 0.58 0.15 −0.06 −0.44
PC4 1.05 0.14 0.72 −0.16 −0.30 −0.04 0.15 −0.08 0.01 −0.79 −0.47
•PC2: his PC summa izes he in luence o PDO
and ENSO (loadings 0.61 and 0.42, espec i ely)
opposed o AMO (−0.47). The highes he sco e
he highes he PDO/ENSO. High sco es ela e o
−AMO phase.
•PC3 ep esen s synch onic (simila loading alue)
ENSO/EA/AMO opposed o WeMOi. High sco es
o he PC indica e high ENSO/EA indices; low
sco es depic ed low WEMOI. High alues ela e o
+AMO phase
•PC4: conjunc ion o SCAND (−0.79) and WeMOi
(−0.47) phases. The highes he PC’s sco e he low-
es SCAND/WeMOi index alue.
PCA e ealed in e es ing pa e ns o associa ion
be ween CTs and he seasonal dis ibu ion o BA
size ( igu e 3; see igu e S1 in supplemen a y ma e i-
als o addi ional biplo combina ions). MOI, NAO,
WeMOi and, o a lesse ex en EA, we e posi i ely
linked o summe BA (mainly in PC1), i.e. he
main i e season in he IP. Likewise, AMO showed
an in e se associa ion, hough sligh ly linked o BA
du ing all.
None heless, spa ial and empo al di e ences
we e obse ed a egion le el since p essu e cen e s
a ec di e en ly he di e en a eas o he IP in e ms
o p ecipi a ion and he e o e ha is e lec ed in e ms
o d ough and ege a ion de elopmen ( able 2). PC1
(MOI/NAO/WeMOi) showed signi ican associa ions
wi h BA in all egions, excep in he SW a ea. Posi -
i e phases o ei he NAO o MOI os e ed inc eased
BA. This associa ion was obse ed consis en ly a
mul iple empo al scales hough i was mo e in ense
a 4–6 mon hs (lag) be o e June. The conjunc ion
o posi i e ENSO and PDO (PC2) was ela ed o an
inc eased BA in ea ly and la e summe in he N (MJJ
and JAS) and, wi h he main i e season in he SW
(JJA). An immedia e associa ion (lag 0) was epo -
ed in he N whe eas he signal was sligh ly delayed in
he SE (3 mon hs lag). Synch onic (lag 0) low WeMOi
index unde posi i e phases o EA and ENSO (PC3)
was associa ed wi h a la ge BA in he E egion. The
wes e n hal o he peninsula (NW and SW) showed
con as ing associa ions be ween ea ly and la e sum-
me . BA in he MJJ pe iod beha ed like he E egion
while he s onges associa ion in JJA and JAS depic-
ed in e se co ela ions in he NW, hus BA co el-
a ion was nega i e ENSO and EA phases and posi -
i e wi h WEMOI. Finally, PC4 (SCAND +WEMOI)
showed nega i e sho - e m (lag 0 and scale 3) co el-
a ions wi h BA in la e summe in all egions excep in
he SW a ea. Con e sely, high WEMOI and SCAND
du ing he win e p io summe was associa ed wi h
an inc eased BA in AMJ.
3.2. The in luence o CTs on i e wea he dange
In o de o comple e he analysis o his o ical i e
incidence we in es iga ed he po en ial associa ion
be ween CTs and FWI ( igu e 4; see h ps://c s- wi-
ip.ne li y.app [61] o see he indi idual maps o CTs’
co ela ion pa e ns). The mos in luen ial CTs we e
MOI, SCAND, NAO, PDO and AMO. MOI, NAO
5
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Table 2. Co ela ion coe icien s pe egion, ime window, lag and scale be ween bu ned a ea and CTs. Columns heade s deno e he empo al window o bu ned a ea agg ega ion: AMJ, Ap il–June; MJJ, May–July; JJA, June–Augus ;
JAS, June–Sep embe . E, Eas egion; N, no h egion; NW, no hwes egion; SW, sou hwes egion. Bold alues indica e signi ican co ela ions (p< 0.05). N indica es he numbe o i es analyzed.
AMJ MJJ JJA JAS
Region RLag Scale N R Lag Scale N R Lag Scale N R Lag Scale N
PC1 E0.49 3 5 213 −0.41 4 3 640 −0.45 5 3 1092 −0.48 6 3 1118
N−0.56 6 3 312 −0.42 6 4 258 −0.37 1 5 752 −0.34 3 3 1384
NW −0.50 3 5 247 −0.28 4 3 896 −0.33 3 3 2956 0.42 6 5 3917
MOI/WeMOi
and NAO SW 0.20 6 4 422 0.28 5 5 1745 −0.26 4 5 3665 −0.21 5 3 4231
PC2 E−0.34 6 5 213 0.24 6 5 640 −0.28 5 3 1092 0.32 0 5 1118
N0.38 0 3 312 0.43 1 3 258 −0.31 5 4 752 0.43 0 3 1384
NW −0.26 6 3 247 −0.19 4 4 896 0.33 2 4 2956 0.23 6 5 3917
PDO and
ENSO SW −0.31 1 3 422 −0.22 4 3 1745 0.37 3 3 3665 0.32 4 3 4231
PC3 E0.39 6 5 213 0.19 0 4 640 0.36 0 3 1092 0.40 1 3 1118
N 0.32 5 4 312 −0.28 5 3 258 0.31 2 3 752 −0.20 4 3 1384
NW 0.30 4 5 247 0.47 0 5 896 −0.41 0 3 2956 −0.42 1 3 3917
ENSO.
EA and
AMO SW −0.23 1 4 422 0.38 1 3 1745 −0.27 6 3 3665 0.23 4 4 4231
PC4 E 0.26 6 5 213 −0.34 6 4 640 −0.24 0 3 1092 −0.39 0 3 1118
N0.41 5 3 312 0.40 6 5 258 −0.24 1 3 752 −0.45 0 4 1384
NW 0.32 2 4 247 0.28 4 3 896 −0.29 2 5 2956 −0.38 6 3 3917
SCAND
and
WeMOi SW 0.59 5 5 422 −0.27 0 4 1745 −0.41 6 5 3665 −0.31 5 5 4231
6
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Figu e 4. Spa ial dis ibu ion o mos in luencing CTs on FWI. Top mos (A) and second mos (B) co ela ed eleconnec ion.
Bo om, Pea son’s R co ela ion coe icien o mos (C) and second mos (D) co ela ed CT. All co ela ion alues we e
signi ican a p< 0.05.
and AMO displayed a posi i e ela ionship, i.e. he
highe he index he highe he i e wea he dange .
These CTs ela e o sus ained an icyclone condi ions
du ing hei posi i e phases. Con e sely, SCAND and
PDO showed an in e se associa ion pa e n, possibly
linked o he lack o p ecipi a ion du ing hei neg-
a i e phases. The spa ial dis ibu ion o he mos co -
ela ed CTs e ealed a dissimila pa e n ac oss he IP.
The MOI domina es he Medi e anean coas (E) and
he eas e n hal o he SW egion (R> 0.6, p< 0.05),
in e mingling wi h smalle encla es o AMO in he
sou h and SCAND in he no heas . The seasonal
e olu ion o hese CTs, app aised in he supplemen -
a y ma e ials, e eals a s ong and pe sis en in lu-
ence o AMO om June o Sep embe , wi h SCAND
being s onge du ing he cen al summe mon hs
(JJA). In he wes e n hal o he Peninsula (SW and
NW), NAO (R> 0.5, p< 0.05), PDO and SCAND
(R<−0.6, p< 0.05) modes we e he mos co ela ed.
The i s was main ope a ing in ea ly summe (MJJ
a scale 3) whe eas he la e exe ed inc easing in lu-
ence om ea ly o la e summe , especially he PDO,
which a ec s JJA and JAS he mos (see h ps://c s-
wi-ip.ne li y.app).
7
En i on. Res. Le . 16 (2021) 044050 M Rod igues e al
Figu e 5. Spa ial dis ibu ion o empo al pa ame e s o mos in luencing CTs on FWI. Top pe iod wi h highes co ela ion o he
mos (A) and second mos (B) co ela ed eleconnec ion. Mid, scale (numbe o a e aged mon hs) wi h highes co ela ion o
he mos (C) and second mos (D) co ela ed CT. Bo om, lag (mon hs delay) wi h highes co ela ion o hemos (E) and second
mos (F) co ela ed CT. All co ela ion alues we e signi ican a p< 0.05.
8