Finisterra
,
LX
(
129
), 202
5, e37506
ISSN: 0430
-
5027
doi: 10.18055/Finis37506
Artigo
Published under the terms and conditions of an Attribution
-
NonCommercial
-
NoDerivatives 4.0 International license.
THE VANISHING SNOW COVER IN SERRA DA ESTRELA:
LEVERAGING SCARCE DATA FOR DIAGNOSTICS AND FUTURE SCENARIOS
C
ARLA
M
ORA
1
,
2
G
ONÇALO
V
IEIRA
1,2
ABSTRACT
–
This study investigates the evolution of snow cover in Serra da Estrela, the highest
mountain in
mainland Portugal, by integrating observational data from the Penhas Douradas meteorological station, remote sensing
imagery, and climate model outputs. Results reveal a marked decline in the number of snow cover days at Penhas
Douradas, droppi
ng from an average of 53 days in the 1950s to 28 days in the 2010s, corresponding to an overall
decrease of 5.4 days per decade. The rate of decline has slowed since the 1980s, as the station’s elevation still allows
for snow during cold events but not for
its sustained presence. To address the lack of observational data from higher
elevations, we integrated multiple data sources
–
including low
-
elevation records, satellite imagery, and climate model
projections
—
to reconstruct snow cover dynamics on the T
orre Plateau since the late 19th century. Our reconstruction
indicates a decrease from approximately 170 to 120 snow cover days in recent decades. Future projections under
different climate scenarios suggest a continued and substantial reduction in snow co
ver, potentially reaching zero days
by the end of the century under high
-
emission scenarios. Under the most extreme scenario, the Torre Plateau could
experience snow conditions similar to those currently observed at 900 metres of elevation.
Keywords:
Snow
,
climate change
,
remote sensing
,
Serra da Estrela.
RESUMO
–
O DECLÍNIO DA COBERTURA DE NEVE NA SERRA DA ESTRELA:
APROVEITAMENTO DE DADOS
ESCASSOS PARA
DIAGNÓSTICO E CENÁRIOS FUTUROS.
E
ste estudo investiga a evolução da cobertura de neve na Serra da
Estrela, a montanha mais elevada de Portugal continental, através da integração de dados observacionais da estação meteorológ
ica
das Penhas Douradas, imagens de deteção remota e resultados de modelos climáticos. Os resultados revelam uma redução acentuad
a
no número de dias com cobertura de neve nas Penhas Douradas, passando de uma média de 53 dias na década de 1950 para 28 dias
na década de 2010, o que corresponde a um decréscimo global de 5,4 dias por década. A taxa de declínio abrandou desde a décad
a de
1
980, uma vez que a altitude da estação ainda permite a ocorrência de neve em eventos frios, mas não a sua permanência. Para
colmatar a escassez de dados observacionais nas cotas mais elevadas, integrámos diversas fontes
–
incluindo registos de menor
altitu
de, imagens de satélite e projeções de modelos climáticos
—
de modo a reconstruir a dinâmica da cobertura de neve no Planalto
da Torre desde o final do século XIX. A reconstrução aponta para uma redução do número de dias com neve de aproximadamente 17
0
par
a 120 dias nas últimas décadas. As projeções futuras, baseadas em diferentes cenários climáticos, indicam uma redução continu
ada
e significativa da cobertura de neve, podendo esta desaparecer por completo até ao final do século em cenários de elevadas em
is
sões.
No cenário mais extremo, o Planalto da Torre poderá apresentar condições de cobertura de neve semelhantes às atualmente
observadas a 900 metros de altitude.
Palavras
-
chave:
Neve
,
alterações climáticas
,
deteção remota
,
Serra da Estrela.
HIGHLIGHTS
Snow cover at Penhas Douradas declined by 5.4 days per decade since the 1950s.
A warming trend of +0.17 °C per decade was recorded from 1883 to 2020.
The snow season now starts one month later and ends one month earlier, with major losses in
December, Ja
nuary, and March.
Torre Plateau snow cover dropped from approximately 170 to 120 days per year since the late 19
th
century.
All scenarios except SSP1
-
2.6 project less snow on Torre Plateau than current levels at Penhas
Douradas.
Recebido:
9
/0
9
/2024. Aceite:
15
/
05
/202
5
.
Publicado: 21/07/2025.
1
Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do
Território
, Universidade d
e Lisboa
,
Edíficio, IGOT,
R.
Branca Edmée Marques, 1600
-
276
,
Lisboa
,
Portugal
. E
-
mail:
carlamora@edu.ulisboa.pt
,
vieira@edu.ulisboa.pt
2
Laboratório Associado TERRA
Mora, C., Vieira, G
.,
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(129), 2025,
37506
2
1.
INTRODUCTION
Snow is a key element of Earth's cryosphere with a major impact on climate at the global level
and representing an important natural resource. Snowmelt provides drinking water to approximately
17% of the world’s population and is used for hydropower, agric
ulture, and industry (Bormann
et
al
.,
2018). Despite the limited observational data from mountains, a significant decline in Northern
Hemisphere spring snow cover has been reported, with the largest decreases over higher latitudes and
in mountain regions,
a fact strongly associated to atmospheric warming (Bormann
et
al
., 2018). The
amplified effect of the decrease of snow and ice at high latitudes is well
-
known, but there is growing
evidence that the rate of warming is also amplified with elevation and, as
such, mountain environments
are and will suffer more drastic changes under a warming climate (Pepin
et
al.
, 2015).
Changes in the duration, extent, and timing of the onset and melting of snow cover have major
impacts in mountains (Liston
& Hiemstra
, 2011).
Modifications on the snow albedo and snow melt also
influence energy fluxes and mountains’ local and
microclimates
(Brun & Pomeroy, 2001). The duration
of water storage in the snowpack affects soil moisture and catchment hydrology (Diffenbaugh
et
al.
,
201
3; Brown, 2019) and impacts water availability for consumption, agriculture, tourism, and
hydropower production (Barnett
et
al
., 2005; Bormann
et
al
., 2018). The changes in mountain snow
cover also impact the sensitive alpine and sub
-
alpine ecosystems.
The
impacts of climate change on the cryosphere in mountains in warm and dry mid
-
latitudes,
such as the Mediterranean, is highly relevant. These have been shown in several mountain regions
where snowmelt is the main component of the surface water resources du
ring the summer, such as
the Spanish Sierra Nevada (Perez
-
Palazón
et
al
., 2018), the eastern Pyrenees (López
-
Moreno
et
al
.,
2009) and the Atlas Mountains (Marchane
et
al
., 2015). Mediterranean mountains show hotspots of
high environmental value, such as bi
osphere reserves with rare endemisms. They host an
exceptionally high number of cold
-
adapted endemic plants and are exposed to a high risk of
biodiversity loss due to climate change (Di Musciano
et
al
., 2018; Lamprecht
et
al
., 2021). Species are
subject to
great stress and need biotic adaptation responses to modifications on climate, such as the
decrease of precipitation and the increase of the air
temperatures that
together give rise to a
shortening of the snow cover extent and duration, and ultimately tra
nslate to a reduction in summer
water availability (Lamprecht
et
al
., 2021).
Increasing variability of precipitation and air temperatures also affect mainland Portugal, as a
result of its position in the transition between the Mediterranean basin and the N
E Atlantic (Carvalho
et
al
., 2014; Ramos
et
al
., 2011; Soares
et
al
. 2017). Most precipitation in Portugal falls as rain and snow
below 1500m occurs only in rare events. Hence, snow cover is confined
to the highest mountains of
northern and central Portugal. The Serra da Estrela, rising to 1993m above sea level is the range where
snow cover lasts for longer, but data allowing for its quantification is scarce and studies are lacking.
The Estrela has be
en traditionally the location in Portugal for snow leisure activities (Andrade
et
al
.
1992; Carvalho 2007), with a small ski resort installed in the plateau between 1850 and 1990m above
sea level, which struggles to maintain conditions f
or ski practice. Un
til the 1970
s, a small ski piste was
maintained at approximately 1700m above sea level close to the Penhas da Saúde at Piornos but was
then abandoned due to lacking snow. Despite the reduction in snow cover duration, the Serra da
Estrela continues to be as
sociated to snow in Portugal, with numerous tourists visiting the upper areas
(Silva
et
al
.
,
2018), which are easily accessible by car on a national road.
The elevation of the Serra da Estrela and geomorphology traits marked by the Pleistocene
glaciations
, together with a long history of grazing, gave origin to a rich biodiversity. The Estrela
plateaus are integrated in a Natural Park, are protected by the Natura2000 network and include a
Ramsar site under the Convention on Wetlands, as well as biogenetic
reserves. They show the last
remnants of alpine and sub
-
alpine ecosystems in Portugal and are home to several important species,
such as the Lacerta monticola in the Red List of the vertebrates of Portugal (Oliveira
et
al
., 2005),
several of them depending
on the effects of snow cover.
Most direct observations on snow cover in the Estrela
plateaus ceased in the mid
-
1980
s and are
currently done only at the meteorological station
of Penhas Douradas, which at 1
380m above sea level
is now too low for snow resea
rch. The snow and its fate, an issue that crosscuts different environment
-
related disciplines and socio
-
economic activities, are central issues for a proper management of this
sensitive mountain area, which holds a status of both a Natural Park and a UNESC
O Global Geopark
(Vieira
et
al
., 2020).
This study aims at filling the gap on understanding the evolution of the snow cover and its spatial
Mora, C., Vieira, G
.,
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3
distribution in the Serra da Estrela since the late 19
th
century, as well to provide an outlook on its
evolution dur
ing the 21
st
century. Our key objectives are to: i
)
provide a characterization of the
evolution of the snow cover based on observational data from the mid
-
elevatio
n plateau of Penhas
Douradas (1
360m asl
) since the 1950’s, ii
)
reconstruct the potential time
-
series of snow cover for the
Penhas Douradas and the upper plateaus of the Serra da Estrela since 1880, and iii
)
assess the possible
futures of the Estrela snow cover and briefly discuss the potential impacts of the expected changes.
To overcome the lack
of observational data at high elevation, we analysed the series from the
Penhas Douradas observatory, together with remote sensing imagery and climate modelling data.
Scarce observational data, coarse
-
grained re
-
analysis that poorly represents the upper
mountain
conditions and a cold season with high cloudiness, limiting the application of multispectral remote
sensing, pose significant limitations to the analysis we present here. However, the synergistic
exploration of the available data allows for a firs
t insight into the recent evolution and fate of the
Estrela snow cover. Given this framework, the results need to be used with special care.
2.
STUDY AREA
The Serra da Estrela is part of the Iberian Central Cordillera and is the highest mountain in
mainland Portugal (fig. 1). Its plateaus that rise between 1400 and 1993
m westwards of the Zêzere
–
Alforfa val
leys, and between 1400 and 1750
m eastwards, are a key feature of the mountain’s relief,
affecting its climate and hydrology. In the Pleistocene c
old periods, these plateaus were responsible
for fast and extensive glacial inception due to their position just below the equilibrium line altitude
(Vieira, 2008; Vieira & Woronko, 2021; Vieira
et
al
., 2021), and they are key to the present
-
day snow
dynam
ics.
Fig. 1
–
Relief of the Serra da Estrela and location of sites mentioned in the text.
Water bodies represented in blue.
Colour figure available online.
Fig. 1
–
Relevo da Serra da Estrela e localização dos sítios mencionados no texto. As massas de
á
gua estão representadas
a azul. Figura a cores disponível online.
Mora, C., Vieira, G
.,
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4
The mountain massif shows a NNE
-
SSW orientation and forms a barrier to the prevailing
atmospheric circulation that brings moist air masses from the Atlantic into inner Iberia (Mora & Vieira
,
2020). The climate is typically Mediterranean, with dry and warm summers and a wet cold semester
(Mora, 2010). Daveau
et
al
. (1977) estimated a mean annual pr
ecipitation for 1931
-
60 of 2500
mm at
the summit of the mountain. Data from the Penhas Dourada
s s
hows a precipitation of 1817
mm f
or
1941
-
1970 decreasing to 1511
mm in 1981
-
2010. Mean annual air temperatures were estimated by
Vieira and Mora (1998) to be close to 4°C at the summit in 1941
-
70.
Andrade
et
al
. (1992) analyzed snow cover data from 1957 to 1
985 from three meteorological
stations: Penhas Douradas (1380m), Penhas da Saúde (1510m) and Lagoa Comprida (1604m).
They
showed that snowfall events were more frequent from December to March, but only in February the
number of snowfall days surpassed the
number of rainfall days, highlighting the warm characteristics
of the precipitation, even during the winter.
Snow cover was characterized by large interannual and intermonthly irregularity, and snow
cover was more frequent, above 1800m, lasting for severa
l weeks in winter. However, even at that
elevation, warm rainy episodes generated extensive snow melting, interrupting the persistence of
winter snow cover. The authors reported a median of 26 days with snow cover at 1600m and
estimated about 70 days for t
he Torre plateau.
3.
DATA AND METHODS
3.1.
Introduction
Studies of snow cover in the Serra da Estrela, as well as in other Portuguese mountains have
been hampered
by the lack of good data
-
series and absent data from high elevation sites. To
characterize the past changes in snow cover we have analyzed monthly precipitation, air temperature
and snow cover duration from 1954 to 2019 using data from the Penhas Douradas
Observatory, the
highest meteorological station in Portugal still operational (fig. 1). To complement these observations
and extend the analysis to higher elevations, we analyzed daily MODIS
(Moderate Resolution Imaging
Spectroradiometer)
optical imagery
from 2001 to 2020.
This allowed us to generate a dataset with the presence of snow in different sectors of the
plateaus. Besides the observational data, we analyzed modelling datasets and compared them to
observations. This was done for the ERA
-
5 Land reanalysis snow cover p
roduct that extends
back to
1950 at 9
km spatial resolution, as well as for the FSM
-
WRF Iberian Peninsula dataset at 10km
resolution from 1981 to 2014, that models snow thickness for different elevations using the ERA
-
Interim (Alonso
-
Gonz
ález
et al
.
,
2019
).
The evolution of the snow cover duration for the upper areas
of the Estrela range was estimated by linear regression modelling at decadal intervals using
temperature data from the Penhas Douradas, with model results validated for the period with
observati
on data. This allowed us to reconstruct the snow cover duration in the Torre Plateau since
the 1890
s. The future evolution of the snow cover climate scenarios was assessed using climate change
scenarios obtained from WorldClim 2.1 until 2080
-
2100.
3.2.
Data f
rom the Penhas Douradas Meteorological station
The highest meteorological station with a long time
-
series is located at the Penhas Douradas, an
observatory of the Portuguese Institute of the
Sea and Atmosphere (IPMA), at 1
380m
above sea level
(fig. 1). Despite its low elevation when compared to
the plateaus that range from 1
400 to almost
2000m, it is the only high mountain station in Portugal. Thus, its observational data set is crucial for
analyzing the snow cover and for validating the remot
e sensing and modeling data that complement
our analysis, enabling insight into the snow cover regimes at higher elevations.
The Penhas Douradas station is located at the top of the Z
êzere valley slope, in the upper
Manteigas basin at in the northeastern l
imit
of the Penhas Douradas plateau
. Surrounded by a
Pinus
sylvestris
forest, the site shows different topographic and vegetation conditions from the rest of the
Estrela plateaus at similar elevation, which are
wide
-
open
areas mostly dominated by heathland
.
Monthly mean air temperatures and precipitation data is available from 1883 to 2020 for the
Penhas Douradas, but the data series has several gaps. The station changed location before being
definitively installed at the current site in 1938. From 1882 un
til 1898 it was located at the nearby
Mora, C., Vieira, G
.,
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(129), 2025,
37506
5
Poio Negro at 1450
m above sea level, while from 1899 to 1903, was moved d
ownslope to Carvalheira
at 1216m
. Since 1903, the Penhas Douradas station has been at the current location, but until 1938 the
instruments were a
t the roof of the observatory building, before being moved to the ground at the
current location. Considering the changes in elevation and the location in the vicinity of the current
site, we have corrected the annual average temperatures
from 1883 to 1898
and from 1898 to 1903
using a lapse rate of
-
0.6
ºC/100m as estimated by Mora (2006) from a regional network of
meteorological stations.
At sub
-
daily time scales and mainly under stable anticyclonic conditions and
in the early morning, temperature inversio
ns have been recorded in the Serra da Estrela, especially in
valleys and glacial cirques (
Mora, 2009
,
Mora
et al
., 2001). However, these are not long lasting and
have a minimal impact in the annual averages.
No corrections were made
for the temperatures from
1903 to 1938, neither for the precipitation.
The Penhas Douradas station provides data on the daily snow depth, a series
that
we have
obtained from the IPMA for 1954 to 2019. From
it,
we calculated the number of days with snow c
over
by considering the days with more than one cm of snow in the ground. After 2004
,
the series has many
short gaps without observations. These concentrate in weekends or following high snowfall events, a
pattern likely due to the fact, that the meteorolo
gical observer, which until then lived at the
observatory, since 2004 commutes daily to the observatory and in deep snow cannot reach it (oral
information).
To address the missing snow cover data in Penhas Douradas from 2004 to 2019, we focused on
the per
iod from October to May, when snow can potentially cover the ground for more than one day.
This analysis resulted in 1,517 days without observations. We then examined these days to identify
those with snow cover using visible MODIS imagery on cloud
-
free da
ys, along with air temperature
and precipitation records:
1.
Periods between observed days without snow, which showed no snow in MODIS imagery
or had
positive
temperatures during cloudy conditions, were classified as snow
-
free.
2.
Periods of a few days between o
bserved days with snow were classified as snow
-
covered.
3.
Longer periods that were only preceded or only followed by snow cover were analyzed
using MODIS imagery. If the scenes were cloud
-
covered, half of the period was classified
as snow
-
covered and the oth
er half as snow
-
free. These periods never exceeded two days
and were very rare, accounting for a potential error below 1.6% of all missing data.
This approach resulted in a good
-
quality dataset for the period with gaps, which was 2004 to
2019.
All trends
p
resented were calculated using the Theil
-
Sen slope method and the statistical
significance evaluated using the Mann
-
Kendall test.
3.3.
Optical remote sensing data
Optical satellite imagery allow for the accurate mapping of snow cover, both using visual
analysis of single scenes or by applying multispectral indexes (Rees, 2006
). The MODIS Terra and Aqua
satellites provide visible daily imagery at a resolution of 250m
since 2001. Optical sensors are
affected
by cloudiness, a very important limiting factor
in the Serra da Estrela, where cloudy conditions are
frequent during the cold semester. Hence, optical satellite imagery is useful only in clear sky
conditions.
Synthetic Aperture Radar
(SAR) satellite data may be an alternative (Mora
et al
., 2017), but
lo
ng data series of SAR at high resolution, such as Copernicus Sentinel 1 are still lacking, since these
have only been active since 2015. Other SAR satellites
show either
low spatial resolution (passive
microwave) or lack continuous acquisitions at the glob
al scale.
Even though MODIS imagery presents the above
-
mentioned limitations, it is still the best
satellite data to complement the observations from the Penhas Douradas meteorological station from
2001 to 2020, allowing to provide spatial and temporal i
nformation about the snow cover regime in
the Serra da Estrela plateaus. Hence, in addition to using MODIS to fill data gaps at the Penhas
Douradas Observatory series as explained above, we used the daily visible imagery dataset to identify
the spatial dis
tribution of snow cover in the Estrela plateaus from 2001 to 2020. The days were
classified based on the presence of snow as follows (fig. 2):
1.
Snow present only in the Torre Plateau.
2.
Snow present in the Lagoa Comprida Plateau and above.
3.
Snow present in
both the Penhas da Saúde and Lagoa Comprida plateaus and above.
However, the data
-
series show long periods with cloud cover that limit the ground observations.
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.,
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6
Fig. 2
–
Examples of MO
DIS RGB composite scenes at 250
m resolution for the Serra da Estrela us
ed for snow extent
classification: A) Snow cover in the Penhas da Saúde plateau and above; B) Snow cover in the Lagoa Comprida and
above; C) Snow cover in the Torre Plateau. Colour figure available online.
Fig. 2
–
Exemplos de imagens compósitas RGB de sat
é
lite MODIS com resolução de 250
m para a Serra da Estrela, usadas
na classificação da cobertura de neve: A) Presença de neve nas Penhas da Saúde e no planalto superior; B) Presença de
neve na Lagoa Comprida e áreas mais altas; C) presença de neve no planal
to da Torre. Figura a cores disponível online.
Source:
https://wvs.earthdata.nasa.gov/
These affect 48% of the days and in some cloudy winters, MODIS imagery provides essentially
sample glimpes of the snow
cover. In order to be able to make best use of the exiting MODIS imagery,
we applied the following approach to fill the gaps without data:
1.
If snow cover was observed
before and after the cloudy period, all cloud
-
obscured days
were counted as snow
-
covered. Hence, in these situations, our classification scheme is
based on the assumption that in these conditions, the period was fully snow
-
covered.
2.
If the cloudy period wa
s preceded by a snow
-
free day and followed by a snow
-
covered
day (or vice versa), the snow
-
covered days were counted as half the duration of the cloudy
period. These periods were very rare and account only for about 3% of cloudy days.
3.4.
ERA
-
5 Land reanalysi
s data
Reanalysis products generate physically modeled data from multi
-
source observations from
across the world into a global gridded dataset. ERA5
-
Land covers the period since 1950 at 9km
resolution, with its core being the tiled ECMWF Scheme for Surfac
e Exchanges over Land incorporating
land surface hydrology (H
-
TESSEL), using the version CY45R1 of the IFS (
Muñoz
-
Sabater
et al
., 2021
).
Despite the coarse spatial resolution and the difficulty to accurately resolve
the relief of mountains,
such as the Serra da Estrela, the fact that this is a plateau mountain, reduces the terrain complexity.
Here, we have evaluated the ERA5
-
Land data feasibility for the reconstruction of the snow cover and
to complement observationa
l datasets.
We have used the snow cover product at 00 UTC, referring to the percentage covered area within
the cell within which the coordinate 40.3205
ºN, 7.613ºW is located. The number of monthly and
annual days with snow cover was classified by counting
the days with: i) more than 0%; ii) more than
5%; iii) more than 10% and iv) more than 25% area covered by snow, within the cell. From these, we
selected the one better describing the snow cover duration in the Estrela plateaus. This was done by
correlati
on analysis with observational data from the Penhas Douradas observatory (1954
-
2019) and
from the MODIS analysis (2000
-
2019).
3.5.
FSM
-
WRF Iberian Peninsula snow depth at 10km dataset
Alonso
-
Gonz
ález
et al.
(20
20
) developed the FSM
-
WRF dataset of daily snow d
epth and snow
water equivalent at 10km resolution for the Iberian Peninsula for 1980
-
2014. The dataset was
produced using the MODIS data for 2000
-
2014 and a physically based snow model
–
the Factorial Snow
Mod
el (FSM)
–
driven by the WRF Weather Research a
nd Forecast model. The results were validated
Mora, C., Vieira, G
.,
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7
using observations from meteorological stations in Spain. Using a k
-
means clustering, four main types
of snow cover regime were shown to characterize the Iberian mountains. The two plateaus of the Serra
da Estr
ela show up as the only areas in Portugal classified as cluster 3, which encompasses mountains
with significant snow cover in most cold seasons, but with the possibility of occurrence of years with
shallow snowpacks.
The accurate identification of the Est
rela plateaus in this regional model led us to evaluate the
FSM
-
WRF dataset to better assess the snow cover characteristics. The dataset provides data for
different elevation levels at 100m intervals. We have selected a cell based on a data point at the Al
to
da Torre and analysed the daily snow
-
depth data for 1500, 1600, 1700, 1800, 1900 and 2000m above
sea level. The series was transformed into daily occurrence of snow using thickness thresholds of >0,
>2 and >5 cm, which were compared with data from PD to
assess the possibility to use FSM
-
WRF data
for improving the characterization of the Estrela snow cover.
3.6.
WorldClim 2.1
WorldClim 2.1
is a global
-
grided dataset of downscaled climate data for past and future climate.
For the past data, the dataset uses interpolation from weather station data using thin
-
plate splines and
covariates such as
elevation,
distance to the coast, and MODIS
-
deri
ved maximum and minimum land
surface temperatures, as well as cloud cover (Fick & Hijmans, 2017). Mean air temperature, which is
the variable we used here, have shown low RMSE values and are accurate, especially in regions with a
high density of meteorolog
ical stations (Cerasoli
et al
., 2022; Fick & Hijmans, 2017).
Future scenarios in
WorldClim 2.1
have been downscaled from CMIP6 Earth System Models.
Here, we have used the
EC
-
Earth3
-
Veg
model (D
öscher
et al
., 2022) mean annual air temperature data
for the
periods 2040
-
60
, 2060
-
80 and 2080
-
2100 at a 30sec grid (c. 1
km at the equator). We use the
standard socioeconomic pathways (SSP) 1
-
2.6, 2
-
4.5, 3
-
7.0 and 5
-
8.5. SSP5
-
8.5 is the so
-
called fossil
-
fueled development scenario at the upper end of the warming pa
thways, with high emissions
(Meinshausen
et al
., 2020; O’Neill
et al
.
,
2016). SSP3
-
7.0 is based
on nationalism driving policy and a
focus on regional and national problems, rather than on global development. It represents the medium
to high end of the range of pathways. SSP2
-
4.5 is an intermediate scenario, which corresponds
approximately to the pre
vious RCP4.5, and includes moderate conditions for land use change and
aerosols. SSP1
-
2.6 represents the low end of the pathways and is a sustainability
-
based pathway, with
policies addressing human well
-
being, clean energy, and nature conservation. It rep
resents values
below 2ºC warming at 2100 as compared to pre
-
industrial levels (O’Neill
et al
., 2016).
The data was
collected from the bioclimatic variables data set of
WorldClim 2.1
. However, ssp370 for 2041
-
2060 and
ssp245 for 2081
-
2100 had missing data.
Hence, for those two scenarios, we used the climate variables
to average the mean temperatures from the monthly maxima and minima.
4.
RESULTS
4.1.
Climate and snow cover evolution in the Penhas Douradas Observatory
4.1.1.
Air temperature and precipitation in Penhas
Douradas from 1883 to 2020
A clear warming trend is present in the mean annual air temperature (MAAT) in the Penhas
Douradas meteorological station for the last circa 140 years (1883 to 2020) (fig. 3). MAATs in the early
1900
’s were around +8.6ºC and in 2019 were close to +10.6ºC. Despite the trend, three periods can be
distinguished. From 1883 until around 1949 the temperatures increased, with the warmest period
being between 1945 and 1949. The following three decades were do
minated by a cooling trend that
lasted until around 1972. MAATs in the 1970’s were close to those of the 1920’s, but since then
temperatures started to increase at fast pace, until they peaked at 11.6ºC in 2017. The warming trend
from 1883 to 2020 in the P
enhas Douradas was +0.164ºC/decade with a p
-
value <0.0001.
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
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8
Fig. 3
–
(A)
Mean annual temperature
, (B)
total annual precipitation
, and (C
)
Mean annual air te
mperatures (MAAT)
per decade
in the Penhas Douradas meteorological station from 1884
t
o 2020 (
MAAT corrected for site changes of the
observatory before 1938).
Colour figure available online.
Fig. 3
–
(A)
Temperatura média anual
, (B)
precipitação anual
e (C) temperatura média anual por década
na estação
meteorológica das Penhas Douradas entre 1884 e
2020 (
a temperatura média foi corrigida em função da altitude devido
a modificações no local de observação antes de 1938).
Figura a cores disponível online.
The decadal data evidences the period of 1941
-
50 as anomalously warm, interrupting a series
that
otherwise would have been stable to slightly warming from the beginning of the 20
th
century until
1971
-
80 (fig. 3). Since 1981
-
90
,
all the decades are warmer than the previous and the warming rate is
steeper
.
The precipitation regime
needs to be analyzed w
ith care
, especially before 1938 due to the
changes in location in the Penhas Douradas observatory before that year. The data shows high
interannual variability, with a decrease in annual totals. Pre
cipitation values averaged c. 2300mm in
1920
-
40, c. 2000
m
m in 1941
-
50 and cont
inued decreasing until around 1
600 to
1400
mm since the
1980
s. However, the high values before 1938 are possibly biased due to changes in station location,
with the trend since then being of
-
51.16mm/decade with a p
-
value of 0.014.
4.1.2.
Sno
w cover in Penhas Douradas from 1954 to 2020
Penhas Douradas is the only meteorological observatory at high elevation in Portugal with a
long data
-
series for snow cover. The data from 1954 to 2020 shows a very strong reduction in snow
cover, with a trend of
-
5 days/decade (at p<0.00003), from an aver
age of 53 days in 1951
-
1960 to 28
Days in 2011
-
2020 (table I). The data shows a period with longer duration of snow cover from 1969
to 1976, which is reflected in a peak with an average of 68.6 days in 1971
-
1980. A sharp change
occurred in the following de
cade, with a strong reduction to an average of 34 days in 1981
-
1990. Since
then, the reduction rate was slower at
-
2 days/decade, with some years in the early 2000
s and in the
mid of the decade of 2011
-
2020 showing longer snow cover (fig. 4).
Mora, C., Vieira, G
.,
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(129), 2025,
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9
Table I
–
Mean annual air temperature and mean annual snow cover days per decade in the Penhas Douradas, from
1951 to 2020.
Quadro I
–
Temperatura media anual e média anual do número de dias com cobertura de neve por década nas Penhas
Douradas entre 1951 e 2020.
Mean annual air temperature
(ºC)
Number of days with
snow cover
1951
-
60
8.8
53.3
1961
-
70
9.1
47.0
1971
-
80
8.6
68.6
1981
-
90
9.5
33.6
1991
-
00
9.6
32.5
2001
-
10
9.9
31.0
2011
-
20
10.4
28.0
Source:
Instituto Portugu
ês do Mar e da Atmosfera, with data
estimated for snow cover after 2004
Fig. 4
–
Number of days with snow cover at Penhas Douradas meteorological station from 1954 to 202
0. Upper graph:
annual values. L
ower graph: decadal box
-
plots with D1, Q1, Median, Q3 and D9.
Colour figure available
online.
Fig. 4
–
Número de dias com cobertura de neve na estação meteorológica das Penhas Douradas de1954 a 2020.
Gráfico
superior: valores anuais. G
ráfico inferior: box
-
plots decenais com indicação do D1, Q1, Mediana, Q3 e D9. Figura a cores
disponível o
nline.
Source: Instituto Portugu
ês do Mar e da Atmosfera, modified after 2004
4.1.3.
Seasonal changes in snow cover
Besides the reduction trend in the number of days with snow cover at Penhas Douradas, the
monthly distribution has also changed since 1954 (fig. 5). September and October have always been
months of very scarce snow, but while until the late 1960
’s snow cov
er occurred for a few days per
year in September, it disappeared after that.
Mora, C., Vieira, G
.,
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(129), 2025,
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10
Fig. 5
–
Number of days with snow cover in the Penhas Douradas Observatory from 1954 to 2020.
Colour figure
available online.
Fig. 5
–
Número de dias com cobertura de neve na
estação meteorológica das Penhas Douradas de 1954 a 2020. Figura a
cores disponível online.
Source: Instituto Português do Mar e Atmosfera, corrected in the period 2004
-
2020
October frequently recorded a few days of snow cover in the beginning of
the ser
ies, but after
the 1980
s became a month with very rare occurrences, starting to mirror the characteristics of
September at the beginning of the 1950s (fig. 5). These are two months with still warm ground and
sporadic snowfall events. November had always a
small number of days with snow cover (decadal
averages from 1.5 to 4.4 days) and high interannual irregularity. No trend for this month is visible,
meaning that sporadic snow events continued to occur during the whole period, but that snow did not
last for
more than a few days, independently of the year (fig. 6).
Mora, C., Vieira, G
.,
Finisterra,
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(129), 2025,
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11
Fig. 6
–
Decadal variability of days with snow cover for the cold season months in the Penhas Douradas Observatory.
Decadal box
-
plots with D1, Q1, Median, Q3 and D9.
Colour figure available
online.
Fig. 6
–
Variabilidade decenal do número de dias com cobertura de neve para os meses da estação fria no observatório
das Penhas Douradas.
Box
-
plots decenais com D1, Q1, Mediana, Q3 e D9. Figura a cores disponível online.
Source: Instituto Portugu
ês
do Mar e da Atmosfera, modified after 2004
December showed marked changes in the 1950’s, with two distinct periods (fig. 5). Until the
mid
-
1970s, the ground was frequently snow
-
covered for about two weeks, but after that, the snow
cover showed very short
duration lasting only for a few days each year. This became clearer after 1980
and resulted in a remarkable reduction of the snow during that month (fig. 6).
January has been a very irregular month and is characterized by its interannual irregularity (fig
.
6), having recorded full snow cover in 1971/72 to 1973/74 (fig. 5). In the last two
decades,
it became
more irregular and even lacked snow cover in some years after 2000. In the second decade of the 21
st
century January recorded a regime comparab
le to
December in the late 1970
s. February, similar to
January was marked by high irregularity, but since 2002 it clearly became the month with more snow
cover (figs. 5 and 6).
March was a very irregular month, influenced by sporadic
snowfall
events. Its genera
l behavior
during the period is comparable to December, reflecting the strong reduction of the snow cover in the
shoulder seasons (fig. 5). However, March reflects a much stronger reduction in snow cover after the
1980's, than any other month (fig. 6).
Apr
il has been a month of sporadic snow and despite the general reduction, its behavior is very
irregular (fig. 5), depending on the advection regime of spring cold and wet air masses. It seems to be
losing its original characteristics to March (fig. 6). May
has been typically a month with little snow,
peaking in the cold early 1970s, but with negligible snow cover days before and after (fig. 5
). April in
the 2010s
becam
e comparable to May in the 1970
s, which may mean a fast shift towards a Mayification
of Ap
ril. The warm season, lasting from June to September is a regular period without snow cover in
the Penhas Douradas.
In synthesis, the Penhas Douradas snow cover regime has been marked since the mid
-
20
th
century by an increasing interannual irregularity and
by a shortening of the snow period. Snow cover
at the observatory only approached what could be called a seasonal snow cover from 1971 to 1974,
but otherwise, snow rarely covered the ground for over a month in a row. The cold period of the early
1970
s is
remarkable on its effects on the duration of snow cover, but overall, a trend for a strongly
decreasing snow cover is clear during the whole time
-
series. The season with snow on the ground
starts about one month later and ends one month earlier. November a
nd April, show small reduction
Mora, C., Vieira, G
.,
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(129), 2025,
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12
trends, with December, March and January being the months showing larger reduction in snow cover
duration.
4.2.
Attempting to evaluate the recent evolution of snow cover from satellite imagery (2001
-
2020)
The analysis of the MOD
IS optical imagery at 1
-
day intervals and 250m spatial resolution
allowed insight on the snow cover duration at the plateaus of the Serra da Estrela from 2001 to 2020.
This is currently the best option for reconstructing the spatial extent of snow in the E
strela plateaus,
but it is an approach that is based on continuity assumptions during cloudy periods, which implies that
it needs to be used with extreme care, since cloudy days are very frequent in the cold season.
Figure 7 represents the reconstructed da
ys with snow cover at least down to the Penhas da
Sa
úde Plateau (circa 1500
m), down to the Lagoa Comprida
–
upper Penhas Douradas Plateau (circa
1600
m) and the days with snow only in the Torre Plateau (circa 1800 m). Similarly to what has been
obser
ved
in the Penhas Douradas at 1
360m, the observations show the high interannual irregularity
of the snow cover. In some
years,
the Torre plateau showed continuous snow cover for several months,
such as 2008/09 with snow from late November to early May, or 200
5/06 with snow from late
November to mid
-
April. However, in several years, especially towards the end of the series, as in the
winters of 2011/12 and 2019/20, snow lasted for only a few days even at upper areas of the Estrela.
Fig. 7
–
Reconstructed snow cover in the Serra da Estrela plateaus (from MODIS imagery analysis, 2001
-
2020).
Colour
figure available online.
Fig. 7
–
Reconstrução da cobertura de neve nos planaltos da Serra da Estrela a partir da análise de imagens MODIS
(
2001
-
2020).
Figura a cores disponível online.
The observations show a trend for shorter snow seasons, a significant delay in the onset of snow
cover and for less days of snow at lower elevations, as well as a regime where years with seasonal
snow alternat
e with years with sporadid snow, even at the Torre Plateau (fig. 7). While the Torre
Plateau may have snow cover at the beginning of the cold season, snow lasting for several days down
to Penhas da Saúde before mid
-
January almost ceased to occur in the las
t decade.
Typically, longer lasting snow cover starts from higher to lower elevation, but with the delaying
of the snow onset to January
-
February, several years showed an abrupt initiation of multi
-
day snow
cov
er at all elevations above 1500
m. This may
be also related with the warmer ground until later in
the cold season, limiting snow accumulation or by later and scarcer snow events. The end of the snow
period was generally more gradual and started from lower to higher elevation. Snow did not last long
at the Penhas da Saúde plateau after mid
-
March, especially in the last decade. In
April,
snow cover was
frequent only in the Torre Plateau, but in some years, it extended down to Lagoa Comprida.
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
37506
13
In rare years, April has shown snow down to Penhas da Saúde
for several days, but these have
been mainly years of late snow occurrence and probably marked by cold snow events, with snow cover
benefiting from the cool
er ground from a preceding snow
-
free period. May showed very rare snow
cover. The data clearly shows
that despite the delay in the onset of the snow cover, the start of the
snow
-
free period did not change and concentrates in April. The period 2011
-
2020 has shown more
snow in April than the preceding decade.
4.3.
Evaluation of climate models for reconstructin
g the snow cover
4.3.1.
Snow cover reconstruction from ERA5
-
Land
ERA5
-
Land provides meteorological data since 1950 for a global grid with 9km resolution. Here
we evaluate its application to the Serra da Estrela by comparing ERA5
-
Land data with observations
from
the Penhas Douradas and with the MODIS snow cover series retrieved for the plateaus. From the
ERA5
-
Land, we calculated the annual days with snow cover for different limits of snow
-
covered area
within the grid point: >0, >1, >5, >10 and >25% area. The comp
arison of the resulting series with the
number of days with snow cover at Penhas Douradas resulted in r from 0.57 to 0.63, significant at
p<0.05 (table II and fig. 8A). Correlations with the MODIS series for the Torre Plateau are worst (0.32
to 0.41), but
still statistically significant.
Table II
–
Correlations (r) between the number of days with snow cover at Penhas Douradas and at the Torre Plateau,
with the ERA5
-
Land days with snow cover above different area thresholds (>0%, >1%, >5%, 10% and >25%),
using
annual days and mean annual days per decade.
Quadro II
–
Correlações (r) entre o número de dias com cobertura de neve nas Penhas Douradas e no planalto da Torre,
com o número de dias acima de vários limiares de cobertura de neve (>0%, >1%, >5%, 10% e
>25%) da ERA5
-
Land. São
apresentados o número anual e a média por década.
ERA5
-
Land Snow
Cover days (area)
Penhas Douradas days with snow
cover (Observations)
Torre Plateau days with snow
cover (MODIS)
Annual
Decadal
Annual
>0%
0.57
0.97
0.41
>1%
0.62
0.96
0.37
>5%
0.63
0.93
0.33
>10%
0.61
0.92
0.33
>25%
0.59
0.91
0.32
Fig. 8
–
Correlations between ERA5
-
Land of snow cover days and observations from the
Penhas Douradas
Observatory. (A)
ERA5
-
Land days with more than 5% area of snow cover (annual totals).
(B)
ERA5
-
Land days with
more than 0% area of snow cover (decadal averages).
Fig. 8
–
Correlações entre o número de dias com cobertura de neve da ERA5
-
Land e as observações d
as Penhas Dou
radas.
(A)
Dias com mais de 5% da área coberta por neve na ERA5
-
Land (totais anuais).
(B)
Dias com mais de 0% da área
coberta por neve (médias decenais).
Mora, C., Vieira, G
.,
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(129), 2025,
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14
The analysis of the decadal means is useful for evaluating long
-
term scenarios. The comparison
of ERA5
-
Land snow cover days for the Serra da Estrela with the snow cover days at the Penhas
Douradas observatory resulted in very strong positive correlations from 0.91 to
0.97 (t
able
II
), while
the data for the Torre Plateau did not provide statistically signif
icant results. The MODIS results cannot
be used for the decades since the series started only in 2000.
Figure 8B shows the example of the correlations between ERA5 Land days with snow presence
at the grid and the observations from Penhas Douradas. It is,
however, important to notice that the
high correlations may be a result of the overall control of mean annual air temperature on the snow
cover duration, rather than of the real performance of ERA5
-
Land in modeling the snow cover
dynamics. Actually, as we
show below, at the decadal level, colder periods have resulted clearly in
longer
-
lasting snow cover.
4.3.2.
FSM
-
WRF Modeled snow cover duration (1980
-
2014)
The FSM
-
WRF modeled snow cover thickness is a dataset gridded at 10 km resolution for the
Iberian Peninsula from 1981 to 2014, for 100m elevation intervals, from which we calculated the
number of days with over 0, 2 and 5cm of snow depth. We assessed the s
eries performance for the
Serra da Estrela from 1500 to 2000m elevation by comparing it with the Penhas Douradas
observations and with the MODIS
-
derived dataset. Statistically significant correlations at p<0.05 were
found for elevations above 1900
m, but no
t for all variables (table III). The best correlations were
obtained for the Torre Plateau snow cover from MODIS, with a correlation of 0.79 for days over five
cm of snow (fig. 9). The decadal means are not analyzed due to the short time
-
series of the FSM
-
WRF.
Table III
–
Correlation (r) between the observed number of days with snow cover in Penhas Douradas (PD_Snow),
Torre Plateau (TSnowRS), above the Lagoa Comprida (PTSnowRS) and above the Penhas da Saúde Plateau
(PSSnow_RS), with the number of days with
snow depth (SD) above
0, 2 and 5
cm at 2000 and 1900m, from the FSM
-
WRF model (1981
-
2019).
Correlations at p<0.05 in bold.
Quadro III
–
Correlações (r) entre o número observado de dias com cobertura de neve nas Penhas Douradas (PD_Snow),
Planalto da Torre
(TSnowRS), acima da Lagoa Comprida (PTSnowRS) e acima do planalto das Penhas da Saúde
(PSSnow_RS), com o número de dias com espessura
de neve (SD) maior que 0, 2 e 5cm a 2000 e 1900
m de altitude.
Resultados baseados no modelo FSM
-
WRF (1981
-
2019). Correlaçõ
es p<0.05 a negrito.
SD FSM
-
WRF
PD_Snow
TSnowRS
PTSnow_RS
PSSnow_RS
> 0 cm (2000 m)
0.32
0.50
0.65
0.47
> 2 cm (2000 m)
0.40
0.65
0.77
0.59
> 5 cm (2000 m)
0.41
0.68
0.79
0.61
> 0 cm (1900 m)
0.22
0.40
0.53
0.42
> 2 cm (1900 m)
0.16
0.47
0.56
0.43
>
5 cm (1900 m)
0.16
0.43
0.51
0.38
4.3.3.
Modeling snow cover duration at Penhas Douradas
a)
Mean annual air temperature and snow cover
The correlation of the mean annual air temperatures (MAAT) with the number of days with
snow cover in the Penhas Douradas
shows a r of
-
0.66 at p<0.05, reveals both the control of air
temperature on snowfall, but also on melting (fig. 9). Based on this correlation, we approach
reconstructing the Estrela snow cover series along the 20
th
century. This implies the assumption of a
similar climatic regime during the period of analysis, especially on the seasonality of precipitation.
Since observational and model data show that precipitation has been decreasing and temperature
increasing duri
ng last century (fig. 3), our approach is based on the broad assumption that present
conditions of higher temperature and lower precipitation at high elevation, may be comparable with
past conditions at lower elevations.
To improve the statistical signifi
cance, we reconstructed long
-
term snow cover trends using the
correlation of the decadal averages of the MAAT and snow cover. For Penhas Douradas, the time series
from 1955 to 2019 was used, but the values are constrained by the low elevation of the site,
not
showing large numbers of days with snow nor very low MAAT. To overcome this problem, we have
included in the regression observations from
days with snow cover from the MODIS reconstruction
Mora, C., Vieira, G
.,
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(129), 2025,
37506
15
for the decades of 2001
-
2010 and 2011
-
2020, paired with
extrapo
lated MAAT for the Torre Plateau
(1800 m), Lagoa Comprida (1600m) and Penhas da Sa
úde (1500m).
This allowed for better constraining of the best
-
fit line (fig. 10), resulting in a r value of
-
0.97 at
p<0.05, allowing for high confid
ence in the application
of the equation:
Snow cover days (decadal
mean) =
-
27.114 MAAT + 298.89
(Eq. 1)
. The plateau
-
dominated relief and smooth summit surfaces of
the Serra da Estrela favor the applicability of this elevation
-
based model, but it is important to note
that small t
opographical effects that depend on slope and aspect are not resolved with this approach.
Fig. 9
–
Mean annual air temperature and number of days of snow cover at the Penhas Observatory from 1954 to
2020
.
Colour figure available online.
Fig. 9
–
Temperatura média anual do ar e número de dias com solo coberto de neve no observatório das Penhas entre
1954 to 2020. Figura a cores disponível online.
Source:
Instituto Portugu
ês do Mar e da Atmosfera, modificado a partir de 2004
Fig. 10
–
Correlation
between the decadal mean annual air temperatures and days with snow cover based on
observational data from the Penhas Douradas for 1954
-
2019, and on MODIS reconstructed snow cover and
extrapolated decadal mean annual tempe
ratures for 1500, 1600 and 1800
m
for 2001
-
2020.
Colour figure available
online.
Fig. 10
–
Correlação entre as médias decenais da temperatura média do ar e o número de dias com solo coberto de neve,
baseada nos dados do observatório das Penhas Douradas (1954
-
2019) e na análise de imagens MODIS e extrapolação da
temperatura média anual decenal p
ara 1500, 1600 e 1800
m de altitude (2001
-
2020).
Figura a cores disponível online.
b)
Reconstruction of the snow cover duration at the Alto da Torre
We used the mean annual air temperatures fo
r the Alto da Torre at 1993
m asl estimated at the
decadal level t
o reconstruct the number of days with snow since 1883 (fig. 11). Although the results
need to be examined with care, they allow for insight into the likely evolution of the snow cover
duration in the upper reaches of the Serra da Estrela. Following atmosph
eric warming, snow cover
duration has been decreasing from around 170 days in the late 19
th
century, to about 160 days from
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
37506
16
1951 to 1980, and sharply declined to an average of about 120 days in the last decade. The last decade
also showed increased
irregularity with some winters showing barely any snow cover, which
according to the estimations, had never occurred since 1884. The decade of 1941
-
50 showed
anomalously low snow, while the cold 1970s showed values like those of the first half of the 20
th
century.
The model shows a reduction of almost two months in snow cover duration in the Alto da
Torre since the late 19
th
century (fig. 11).
Figure 11
–
Estimated duration of the snow cover in the Alto da Torre from 1884 to 2020.
Figure 11
–
Duração
estimada da cobertura de neve no Alto da Torre entre 1884 to 2020.
4.3.4.
Snow cover at the end of the 21
st
Century
The projection of the mean annual air temperatu
res for the Torre Plateau (1900
m asl) until
2100 on the EC
-
Earth3
-
Veg under different
socioeconomic pathways and WorldClim 2.1, shows very
high warming (
f
ig. 12).
Fig. 12
–
Modeled decadal averaged mean annual air temperatures (A) and mean days with snow cover
(B)
at the
Torre Plateau
(1900m) from 1880 to 2020
and scenarios following different Standard Socioeconomical Pathways
until 2100. The scenarios are 20
-
year means from the EC
-
Earth3
-
Veg (WorldClim2.1).
Colour figure available online.
Fig. 12
–
Modelos das médias da temperatura média anual por década (A) e
do número médio de dias com cobertura de
neve (B)
no planalto da Torre (1900
m) de 1880 a 2020, segundo os cenários Standard Socioeconomical Pathways até
2100. Os cenários usados são médias de 20 anos do EC
-
Earth3
-
Veg (WorldClim2.1).
Figura a cores disponív
el online.
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
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17
Temperatures at the end of the century may reach around 13
ºC under ssp5
-
8.5, 11.6ºC under
ssp3
-
7.0, 10.2ºC under ssp2
-
4.5 and 8.6ºC under ssp1
-
2.6, being only in the latter that a slight cooling
is expected to start in 2080
-
2100.
Accounting for the assumptions presented above and for the limitations in the modeling, the
past and future evolution of the snow cover days for the Torre Plateau can be estimated using Equation
1. The results show that the number of snow cover days at the
Torre Plateau will be 0 around 2070
under ssp5
-
8.5 and 10 years later under ssp3
-
7.0 (fig. 12). Ssp2
-
4.5 shows about 20 days of snow by
the end of the century, a value below today
’s Penhas Douradas, while ssp1
-
2.6 shows a stabilization at
around 60 days o
f snow cover, which is a reduction to almost half of present
-
day’s values, even in the
best climate scenario.
5.
DISCUSSION
5.1.
The evolution of snow cover in the Penhas Douradas since the 1954
Snow cover since the mid
-
20
th
century in the Penhas Douradas station at 1380m shows a clear
declining trend of c. 5.4 days/decade, with a peak in the late 1960
s to early 1970s. The records show
change in average number of days with snow cover from 53 days in 1951
-
1960 to 28
d
ays in
2011
-
2020. Similar reductions in snow are widespread in other mountain regions in Europe and the World
(
Intergovernmental Panel on Climate Change
, 2019) and follow the atmospheric warming that has
been occurring since the industrial revolution
(Carvalho
et
al
., 2014, Ramos
et al
., 2011, Soares
et al
.,
2017)
.
Since the 1980
s
,
the decline in snow cover duration has occurred at a slower pace in the Penhas
Douradas, despite the continued warming. This seemingly relates to the elevation of the observatory
being
just high enough to record snowfall in cold meteorological events, but not high enough to
maintain the snow in the ground for longer periods. The 1980s seem to have been the transition
decade to these new conditions, where snow lasting for several weeks c
eased to occur. This hypothesis
needs to be further tested by analyzing the events with snowfall and the changes in synoptic conditions
causing them. On the other hand,
the reduction in snow cover days in December and January, may also
be controlled by the
warmer ground temperatures in late Fall and early Winter, not allowing for snow
to be maintained before, with snow onset moving towards February.
5.2.
The evolution of snow cover in Serra da Estrela since the late 19
th
century
Most of the area of the Serra d
a Estrela plateaus is above the Penhas Douradas Observatory and
lacks observational data, while those are also the areas where snow is more relevant for the
ecosystems and as a natural resource. The lack of observations in the plateaus is a major issue tha
t has
been seriously affecting the assessment of the impacts of the changing snow cover in the Estrela. Here,
we tried to exploit data available, by using data from the Penhas Douradas observatory, from remote
sensing imagery and from reanalysis. However,
the joint use of these sources for the reconstruction of
the snow cover duration time
-
series was constrained by the low elevation of the observatory, by the
short time
-
series of remote sensing imagery and by problems with clouds affecting the optical image
ry.
Furthermore, the reanalysis
-
based models showed limited ability for accurately resolving the
topography of the Estrela. The comparison of observations from the Penhas Douradas with remote
sensing imagery and reanalysis data at the monthly and annual le
vels, showed
limitations, which were
only solved using decadal averages to reconstruct the snow,
cover duration time
-
series. The
interannual variability was lost, but we were able to capture the overall signal associated with the
changing climate conditions. As such, the reconstructions that we present here are supported by the
decadal correlation be
tween the snow cover duration and mean annual air temperatures and allow a
first insight into the recent evolution of the snow cover in the Estrela.
The reconstructed time
-
series for the days with snow cover in the Torre Plateau show 170 days
in the late
19
th
century, which changed to about 160 days from 1951 to 1980, and sharply declined to
an average of about 120 days in the last decade. Interannual variability has increased significantly,
with more years with scarce snow towards the end of the period. L
autensach (1929) refering to oral
information from the meteorological observer of the Penhas Douradas Observatory, indicated that
snow in the Torre Plateau lasted for about 8.5 months, from mid
-
October to late June, while in Penhas
Mora, C., Vieira, G
.,
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18
Douradas it lasted for a
bout five months. It is not clear if these values referred to a continuous
snowpack, or rather to isolated snow patches. Our reconstruction is more conservative, which suggests
that Lautensach’s information may relate to presence of snow patches.
The gene
ral warming in the Estrela has
led
to a shortening and a delay of the snow cover season
even at the Torre plateau, where MODIS
-
derived observations for the last two decades show a cold
semester marked by irregularity in snow conditions. While some years sh
ow snow from December to
April, most years show sporadic snow with snow
-
free periods even in mid
-
winter at the Torre Plateau.
Extreme years like 2018/19 have almost entirely lacked snow cover.
If we compare the snow cover in
the Alto da Torre in 2011
-
2020
with the conditions in the 1970s, the current conditions are close to
those of the upper Lagoa Comprida area (at c.1700m) then, which gives a good approximation of the
magnitude of the changes that have occurred.
Similar to the Serra da Estrela, a decrease
of snow cover has been recorded in other Iberian
mountains during the second half of the 20
th
and early 21
st
centuries (
Bonsoms
et al
.
, 2021; L
ópez
-
Moreno, 2005;
L
ópez
-
Moreno
et al
., 2020). Annual and winter precipitation in the Iberian Peninsula
between
1961 and 2011 decreased at a rate of 18.7mm/decade (Vicente
-
Serrano
et al
., 2017), with
snowfall days in the the northern Iberian Peninsula having recorded a 50% decrease since the mid
-
1970s (
Lopez
-
Moreno
et al
.
,
2020
; Pons
et al
., 2010;). The North Atlantic Oscillation (NAO) has been
identified
as the main driver of precipitation in Iberian Peninsula in winter, as well as of snowfall in
the western and central Pyrenees (López
-
Moreno, 2005; Revuelto
et al
., 2012). The predominance
of
NAO positive phases in winter over the 20
th
century has lead to a reduction of weather types associated
with precipitation (
Bonsoms
et al
., 2021
; López
-
Bustins
et al
., 2008).
Further south, in the Atlas mountain range in North Africa the large interan
nual variability of
winter precipitation (400%) is affecting the mass balance of the snowpack. The disappearance of many
perennial snowpatches in the last decades reflects the warming trend of summer air temperatures
since the 1970s (Hughes
et al
.
,
2020).
5.3.
The fate of the Serra da Estrela snow cover
Our estimates of the evolution of the duration of snow cover for the 21
st
century show drastic
changes occurring at fast pace. All scenarios, except ssp126 place the Torre Plateau
before the end of
the century
with less snow than today
’s Penhas Douradas (fig. 12). This means that the Serra da Estrela
will clearly enter a sporadic snow cover regime, which will result in dramatic changes in the high
elevation ecosystems.
However,
even at the short
-
term, a
lmost al
l scenarios show the snow cover
duration in 2030
-
2040 to become about half that recorded in the early 1970
’s, which calls for urgent
actions in the management of the plateaus.
Snow reduction scenarios are also foreseen in other mountain ranges in Iberia.
For example,
Pérez
-
Palazón
et al.
(2018)
modeled snowfall for the end of the century
for the Sierra Nevada
and
found a decreasing tren
d in snowfall from 0.21 to 0.55
mm
·year
−
1
, under
representative concentration
pathways (RCP) 4.5 and RCP 8.5, respectively.
Snowfall days are expected to decrease from −0.068
days·year
−
1
under RCP 4.5 to −0.111 days·year
−
1
under RCP 8.5, accompanied by an increase in the
torrentiality of snowfall. As an example of the socioeconomic impacts of the changes in snow,
Spandre
et al
.
(2019)
showed that under RCP8.5 projections, there would no longer be snow ski resort in the
French Alps and the Pyrenees (France and Spain) by the end of the century
.
5.4.
The future environmental setting Serra da Estrela
The impacts of the modeled 21
st
century warming may be analyzed by plotting future air
temperatures as its corresponding changes in elevation. Since precipitation is also forecasted to
diminish significantly, a future pseudo
-
lowering of the Estrela accompanied by a precipitation
reductio
n, will result in climate conditions closer to current ones in lower mountains in the region, as
precipitation is much controlled by elevation in Central Portugal (Daveau, 1977; Mora & Vieira, 2020).
For this, we used the altitudinal lapse rate for the Ser
ra da Estrela by Mora (2006).
Figure 13 shows simulated comparative altitudinal modifications of the Torre Plateau,
considering the SSPs and changes in mean annual temperatures compared to present
-
day. The results
show that at 2080
-
2100 under ssp585, the
Alto da Torre will hav
e MAAT close to those of c. 900
m asl
today (Caldas de Manteigas). SSP370 will lead to warming comparable to an elevation
of c. 1150
m
today (Po
ço do Inferno). SSP245 will lead to a Va
le do Rossim
-
like climate (1400
m), and the best
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
37506
19
scen
ario, SSP125 to a lowering of about 200 m bringing the summit to the current
Lagoa Comprida
conditions (1650
m).
In
2040, the Torre Plateau should have MAAT between those today at c. 1600m (ssp585) and c.
1750m (ssp126). It reaches present
-
day
’s Vale do Ro
ssim’s (c. 1450m) conditions around 2055 under
ssp585, 10 years later for ssp370 and by 2080 for ssp245. Only under ssp126 those conditions will
not
be
met.
Fig. 13
–
Estimated pseudo
-
lowering of the Torre Plateau during the 21
st
century using different air temperature
scenarios from the EC
-
Earth3
-
Veg model downscaled in WorldClim2.1.
Colour figure available online.
Fig. 13
–
Pseudo
-
subsidência do Planalto da Torre ao longo do século XXI com base em vários cenários para a
temperat
ura do ar do modelo EC
-
Earth3
-
Veg obtidos a partir do WorldClim2.1. Figura a cores disponível online.
5.5.
Impacts of a warmer and snow
-
depleted Estrela
The Serra da Estrela will suffer drastic warming and snow cover reduction during the 21
st
century, with ve
ry fast modifications already under way. These changes will have profound impacts
on its sensitive ecosystems and land management systems. The plateaus will be drier and much
warmer with conditions similar to those of much lower mountains today, such as Se
rra da Gardunha
or even lower.
This lowering of the Estrela will affect the sub
-
alpine ecosystems of the plateaus, including key
conservation habitats in the biogenetic reserve and Ramsar site, such as the peatlands, with high
impacts
for endemic species.
The last 140 years have seen strong changes in the E
strela, with a
warming of +0.17
ºC/decade and a strong decrease of snow cover. The Torre Plateau is accompanying
these changes by moving from a clearly seasonal snow
-
covered environment to one with sporadic
snow and with some years showing almost no snow at all. With the reduction of she
pherding in the
plateau and with the warming, an expansion of the shrub formations is expected to occur. But the
drying and warming will also lead to
more extreme
soil drought during the summer, increasingly
exposing soils to water erosion and degradation
during Fall and reducing even more its ecological
potential.
The impacts of the vanishing snow on the hydrology can also impact water availability.
An
increase of water retention in the plateaus, which can be properly done having healthier and deeper
soil
s and a denser protecting vegetation cover, is urgently needed. Conditions must be found to adapt
to climate change and properly manage the vegetation in the plateaus, protecting key locations and
controlling grazing, while protecting the area from wildfir
e.
Despite the scarce research on changes in snow cover, the reduction of snow is clear. Several
tourism and regional development studies during the last decade have emphasised on the needs for
adaptation of the regional tourism economy in order to divers
ify and become more resilient to climate
change (Mota
et al.
, 2023). Public policies and private investments have also been following this line,
with tourist numbers increasing in all season. Despite more research needed, it is likely that the
changes in s
now cover will not have a strong impact on the local tourism industry, which is adapting
to the new climate scenarios. However, it is important to note that the forecasted disappearance of
seasonal snow and climate warming clearly shows that the Torre ski
infrastructure has no future and
that the investments made in recent years were poorly advised. The ski resort expansion in the last
two decades has furthermore resulted in high impacts on the landscape, with urgent action needed for
Mora, C., Vieira, G
.,
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(129), 2025,
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20
renaturalizing the slo
pes and for the timely removal of the infrastructure. Similar approaches are being
conducted in other mountains, such as the Alps in Austria, France and Italy (Moreno
-
Gené
et al
., 2018;
Polderman
et al
., 2020).
6.
CONCLUSIONS
The analysis of the snow
cover trends in the Serra da Estrela, specifically at the Penhas Douradas
station, reveals a significant decline in snow cover days from the mid
-
20
th
century to the present, with
a reduction rate of approximately 5.4 days per decade. This decline, from an average of 53 snow cover
days in the 1950s dro
p
ping to just 28 days in the 2010s, mirrors similar trends observed in other
European and global mounta
in regions, largely attributed to ongoing atmospheric warming since the
industrial revolution.
Despite warming, the rate of decline in snow cover at Penhas Douradas has slowed since the
1980s. This deceleration is likely due to the station's elevation, whi
ch is sufficient to record snowfall
during cold episodes but not high enough to sustain prolonged snow cover. The 1980s mark a shift to
these new conditions, where snow lasting for several weeks has become rare.
Further complicating the assessment of snow
cover trends in Serra da Estrela is the lack of
observational data from the higher plateaus, which are crucial for understanding the full impact of
changing snow cover on the ecosystem and natural resources. Attempts to reconstruct snow cover
duration usin
g data from Penhas Douradas, remote sensing, and reanalysis models faced significant
challenges due to the observatory's low elevation, limitations in data resolution and optical imagery
completeness. Hence, our observations need to be used with care, espe
cially the spatial reconstruction
attempt using MODIS for the period of 2001 to 2020. The reconstructed time
-
series indicate a
substantial decline in snow cover days in the Torre plateau, from about 170 days in the late 19
th
century to approximately 120 da
ys in the last decade, with increased interannual variability and more
years experiencing scarce snowfall.
Projections for the 21
st
century under various climate scenarios predict drastic reductions in
snow cover for the Torre Plateau, with some scenarios
suggesting conditions by the end of the century
will resemble those currently observed at much lower elevations. This anticipated decline will have
profound impacts on the high
-
elevation ecosystems, hydrology, and land management systems of the
Serra da Es
trela. The sensitive sub
-
alpine ecosystems, including peatlands and endemic species
habitats, will face increased threats from warming and drying conditions, leading to soil degradation
and reduced ecological potential.
In response to these changes, adapti
ve management strategies are urgently needed to protect
and enhance the resilience of the plateau's ecosystems. This includes improving water retention
through soil and vegetation management, controlling grazing, and mitigating wildfire risks. The
foreseen
disappearance of seasonal snow covering the ground also calls for a reevaluation of local
infrastructure investments, particularly the Torre ski resort, which is unlikely to remain viable.
Instead, efforts should focus on renaturalizing impacted areas, fo
llowing examples from other
mountain regions like the Alps.
Overall, the findings underscore the critical need for comprehensive and forward
-
looking
strategies to manage the impacts of climate change on snow cover and associated environmental and
socioecon
omic systems in the Serra da Estrela.
ACKNOWLEDGEMENTS
This research is a contribution to the
Project ReMonStar (Ref PD23
-
00005) funded by Fundação La
Caixa and F
undação para a Ciência e a Tecnologia
through the PROMOVE program.
Thanks are due to the
tw
o anonymous referee
s
for the comments
which contributed
to an improvement of the manuscript.
The
Instituto Português do Mar e da Atmosfera
is thanked for providing
d
ata from the Pe
n
has Douradas
meteorological station
.
Mora, C., Vieira, G
.,
Finisterra,
LX
(129), 2025,
37506
21
AUTHORS CONTRIBUTIONS
Carla Mora
: Conceptualization; Methodology; Software; Validation; Formal analysis; Investigation;
Resources; Data curation; Writing
–
original draft preparation; Writing
–
review & editing; Visualization.
Gonçalo Vieira
: Conceptualization; Methodology; Software; Val
idation; Formal analysis; Investigation;
Resources; Data curation; Writing
–
original draft preparation; Writing
–
review & editing; Visualization.
ORCID
Carla Mora
https://orcid.org/0000
-
0002
-
0843
-
3658
Gon
ç
alo Vieira
https://orcid.org/0000
-
0001
-
7611
-
3464
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