Recent Near-surface Temperature Trends in the Antarctic … · 2020-04-18 · recorded on...

Recent Near-surface Temperature Trends in the Antarctic Peninsulafrom Observed Reanalysis and Regional Climate Model Data

Deniz BOZKURT12 David H BROMWICH3 Jorge CARRASCO4 Keith M HINES3 Juan CarlosMAUREIRA5 and Roberto RONDANELLI62

1Department of Meteorology University of Valparaiacuteso Valparaiacuteso 2340000 Chile2Center for Climate and Resilience Research (CR)2 Santiago 8320000 Chile

3Polar Meteorology Group Byrd Polar and Climate Research Center

The Ohio State University Columbus OH 43210 USA4Centro de Investigacioacuten GAIA Antaacutertica Universidad de Magallanes Punta Arenas 6200000 Chile

5Center for Mathematical Modeling (CMM) University of Chile Santiago 8320000 Chile6Department of Geophysics University of Chile Santiago 8320000 Chile

(Received 1 September 2019 revised 20 January 2020 accepted 22 January 2020)

ABSTRACT

This study investigates the recent near-surface temperature trends over the Antarctic Peninsula We make use ofavailable surface observations ECMWFrsquos ERA5 and its predecessor ERA-Interim as well as numerical simulationsallowing us to contrast different data sources We use hindcast simulations performed with Polar-WRF over the AntarcticPeninsula on a nested domain configuration at 45 km (PWRF-45) and 15 km (PWRF-15) spatial resolutions for the period1991minus2015 In addition we include hindcast simulations of KNMI-RACMO21P obtained from the CORDEX-Antarcticadomain (~50 km) for further comparisons Results show that there is a marked windward warming trend except duringsummer This windward warming trend is particularly notable in the autumn season and likely to be associated with therecent deepening of the AmundsenBellingshausen Sea low and warm advection towards the Antarctic Peninsula On theother hand an overall summer cooling is characterized by the strengthening of the Weddell Sea low as well as ananticyclonic trend over the Amundsen Sea accompanied by northward winds The persistent cooling trend observed at theLarsen Ice Shelf station is not captured by ERA-Interim whereas hindcast simulations indicate that there is a clear patternof windward warming and leeward cooling Furthermore larger temporal correlations and lower differences exhibited byPWRF-15 illustrate the existence of the added value in the higher spatial resolution simulation

Key words dynamical downscaling cloud computing added value reanalysis AmundsenBellingshausen Sea WeddellSea temperature trend

Citation Bozkurt D D H Bromwich J Carrasco K M Hines J C Maureira and R Rondanelli 2020 Recent near-surface temperature trends in the Antarctic Peninsula from observed reanalysis and regional climate model data AdvAtmos Sci 37(5) 477minus493 httpsdoiorg101007s00376-020-9183-x

Article Highlights

bull Recent near-surface temperature trends over the Antarctic Peninsula are assessed using observations reanalysis andnumerical simulationsbull Observed trends show contrasts between summer and autumn An annual warming (cooling) trend is notable at SanMartin (Larsen Ice Shelf) stationbull Unlike the reanalysis numerical simulations indicate a clear pattern of windward warming and leeward cooling at theannual time scale

1 Introduction

The Antarctic continent possesses a unique geography

that is vital for our understanding of climatic phenomena onlocal and large scales In addition some of the strongest andmost convincing evidence of climate change was obtainedfrom studies over West Antarctica and the Antarctic Penin-sula and provided important arguments about the long-termfuture effects of global climate change such as surface warm-

Corresponding author Deniz BOZKURT

Email denizbozkurtuvcl

ADVANCES IN ATMOSPHERIC SCIENCES VOL 37 MAY 2020 477ndash493 bull Original Paper bull

copy The Author(s) 2020 This article is published with open access at linkspringercom

ing and melting (Marshall et al 2006 Steig et al 2009Bromwich et al 2013a 2014 Holland et al 2019) Des-pite the important evidence for climate change and itsimpacts on cryosphere and ecosystem processes (egRignot et al 2004 Cape et al 2014) the Antarctic contin-ent suffers from inadequate observational coverage due toits remote and harsh environmental conditions Thisimposes a limitation on the surface meteorological data tocharacterize and reduce the uncertainty of climate change

Although the Antarctic Peninsula has more research sta-tions compared to the rest of the Antarctic continent sev-eral meteorological stations are underused due to a lack ofarchiving and complete time series (Lazzara et al 2012 Frai-man et al 2014) This is an impediment to expanding ourknowledge of the climate variability of the peninsula In par-ticular the Antarctic Peninsula cordillera constitutes an oro-graphic obstacle to the westerlies and thus the peninsulapresents two different climatic zones a relatively mild andhumid marine climate on the west coast (windward) wherenorthwesterly winds prevail and a cooler continental cli-mate on the east coast (leeward) (Fig 1) mainly affected bysoutherly winds (King and Turner 2009) The steep terrainof the Antarctic Peninsula therefore results in harsh condi-tions that further prevent the deployment of extensive fieldobservations to obtain long-term records On the one handwith the aid of few available long-term surface meteorolo-gical records the Antarctic Peninsula is considered to beone of the most vulnerable climate change ldquohotspotsrdquo with along-term warming trend in near-surface temperatureobserved over the last 50 years [eg FaradayVernadsky sta-tion 294degC (50 yr)minus1] (Marshall et al 2006 Turner et al2016 Jones et al 2019) However since the late 1990s acooling period has been observed in the Antarctic Penin-sula that is attributed to atmospheric teleconnections (Car-

rasco 2013 Turner et al 2016 Oliva et al 2017) On theother hand a sparse observation network prevents extens-ive analyses to minimize the regional-scale uncertainties asso-ciated with climate variability and trends Excluding the relat-ively short time series of satellite products one commonmethod of overcoming the difficulties arising from the inad-equate observational network is to use gridded atmosphericdata at high temporal resolution (ie reanalysis data) andorhigh spatial resolution regional climate models (RCMs) to rep-resent the main surface climatic features as well as toexplore physical mechanisms behind the observed changes

In recent years atmospheric reanalysis data have beenwidely used for various studies such as surface climate charac-teristics of the Antarctic region as well as large-scale atmo-spheric forcing mechanisms modifying the surface climatevariables In a recent study Gossart et al (2019) performeda comprehensive comparison and evaluation of differentreanalysis products in representing the surface climatologyof the Antarctic Ice Sheet They demonstrated that althoughthe reanalysis products could be useful tools they can per-form very differently depending on the region of interest sea-son and variable Regarding the interplay between the local-and large-scale climate in the Antarctic continent Hoskinget al (2013) investigated the AmundsenBellingshausen Sealow (hereafter ASL) using reanalysis data and constructeddiagnostic indices (ie the strength and location of theASL) Also Hosking et al (2013) highlighted that the ASLis an important synoptic system modulating the West Antarc-tic climate variability In another study with the aid of reana-lysis data Rondanelli et al (2019) highlighted the role of trop-ical variability in connection with the highest temperaturerecorded on continental Antarctica and associated large melt-ing events over the Antarctic Peninsula

In addition to surface observations and reanalysis

Fig 1 Study region of the Antarctic Peninsula and meteorological stations (in black) used for the temperatureanalysis The red and blue dashed lines correspond to the windward and leeward sides of the peninsula respectively

478 RECENT TEMPERATURE TRENDS IN THE ANTARCTIC PENINSULA VOLUME 37

products a number of regional weather and climate modelsimulations have been employed over the Antarctic contin-ent particularly over West Antarctica and the Antarctic Penin-sula These modeling studies mainly consisted of the dynam-ical downscaling of boundary conditions provided by reana-lysis and covered a broad of spectrum of applications suchas surface mass balance analysis (Lenaerts et al 2012 vanWessem et al 2014 Gonzalez et al 2018 Agosta et al2019) characterizing surface climate patterns and variabil-ity (van Wessem et al 2015 Deb et al 2018) and foehnevents (Steinhoff et al 2014 Elvidge et al 2015 Bozkurtet al 2018 Datta et al 2019 Zou et al 2019)

Although the aforementioned efforts based on differentdata sources have helped to improve our understanding ofthe local- regional- and large-scale climate variability ofthe Antarctic Peninsula there is still a general lack of mul-tiple-data source comparison and evaluation efforts that com-bine observed reanalysis and RCM data This is importantfor assessing and minimizing uncertainties and possibleerrors of interpreting the data arising from using a singledata source In particular analyzing the recent spatiotem-poral contrasts of temperature trends over the Antarctic Penin-sula using multiple-data sources is crucial for accurately inter-preting the climate variability of the region

The main objective of the present study is therefore toinvestigate recent (1991minus2015) near-surface temperaturetrends of the Antarctic Peninsula by combining observedreanalysis and RCM data Given the different climate charac-teristics of the peninsula on the windward and leeward sidesof the cordillera we first analyze the available near-surfacetemperature records to demonstrate trend differences onboth sides Then we use the ECMWFrsquos ERA5 and its prede-cessor ERA-Interim for further analysis and comparisonFinally we use hindcast simulations performed with thePolar-WRF (v391) RCM forced with ERA-Interim overthe Antarctic Peninsula on a nested domain configuration at45 km and 15 km spatial resolutions for the period1991minus2015 To our knowledge this is the first completehigh-resolution long-term simulation (gt 20 years) includingall seasons performed with Polar-WRF focusing on the Ant-arctic Peninsula In addition we include hindcast simula-tions of the KNMI-RACMO21P model forced with ERA-Interim obtained from the CORDEX-Antarctica domain at aspatial resolution of 50 km for further comparison Thisallows us to contrast the changes in ERA5 and its prede-cessor ERA-Interim as well as the comparison of dynam-ical downscaling simulations with the boundary conditionsfrom ERA-Interim Section 2 describes the observed datareanalysis and numerical simulations Results are presentedin section 3 Section 4 summarizes the results and presentsconcluding remarks

2 Observed data reanalysis and numericalsimulations

21 Meteorological stations

We use four temperature observations located in the cent-

ral and northern section of the Antarctic Peninsula (see Fig 1)Eduardo Frei Montalva Base (Frei station) is the largest Ant-arctic base of Chile located at Fildes Peninsula near the north-ern tip of the Antarctic Peninsula The data is provided bythe Chilean National Weather Service (DireccioacutenMeteoroloacutegica de Chile DMC) Another station used in thenorthern tip of the peninsula is the Argentine MarambioBase Although only ~250 km away from Frei station it hasa different climate as it is located on the leeward side of thenorthern peninsula (see section 31) In a similar mannerwe use two more stations located in the center of the penin-sula the San Martin Base of Argentina on the windwardside and the Larsen Ice Shelf station operated by the Uni-versity of Wisconsin-Madison and the British Antarctic Sur-vey on the leeward side It should be noted that otherweather stations are also available near the San Martin sta-tion namely Rothera and FaradayVernadsky stationsThese two stations have already been extensively used in pre-vious studies (eg Marshall et al 2006 van Wessem et al2015 Turner et al 2016) therefore we use San Martin sta-tion which has received less attention in the literature Onthe leeward side Esperanza station could also be usedhowever Marambio station is located on the more leewardside about 100 kilometers southeast of Esperanza stationand is therefore more representative of the leeward condi-tions over the northern tip of the peninsula

The monthly data from the Marambio San Martin andLarsen Ice Shelf stations are provided by the Scientific Com-mittee on Antarctic Research (SCAR) Reference AntarcticData for Environmental Research (READER Turner et al2004) manned stations (San Martin and Marambio) and auto-matic weather station (Larsen Ice Shelf) Given the diffi-culties of finding a complete long-term record in the regionwe use 1991minus2015 as the period for the analysis Thisperiod is also chosen to have a common period consistentwith the RCM simulations (see section 23) We focus onthe annual as well as summer (DecemberminusJanuaryminusFebru-ary DJF) and autumn (MarchminusAprilminusMay MAM) timescales as both large- and local-scale events can cause temper-atures to rise above freezing resulting in surface melting dur-ing these seasons (eg Nicolas et al 2017 Bozkurt et al2018 Carrasco 2018 Zou et al 2019) Note that LarsenIce Shelf station includes a low percentage of observationsbetween 1990 and 1995 to perform the analysis thereforewe have omitted the data between those years for this sta-tion For station-based comparisons temperature fieldsfrom gridded products (reanalysis and numerical simula-tions) are corrected using a constant lapse rate of 065degC(100 m)minus1 when there is a considerable elevation difference

22 Reanalysis

We use monthly near-surface air temperature mean sealevel pressure 850-hPa specific humidity and wind from theECMWFrsquos ERA-Interim reanalysis dataset (Dee et al2011) in order to present recent changes in surface andlarge-scale circulation patterns The data assimilation sys-tem used to produce ERA-Interim is based on a 2006

MAY 2020 BOZKURT ET AL 479

release of the IFS (Cy31r2) The system includes a 4D vari-ational analysis with a 12-h analysis window The ERA-Interim data assimilation and forecast suite produces (i)four analyses per day at 0000 0600 1200 and 1800 UTCand (ii) two 10-day forecasts per day initialized from ana-lyses at 0000 and 1200 UTC (Berrisford et al 2011) The spa-tial resolution of the dataset is approximately 80 km (T255spectral) on 60 vertical levels from the surface up to 01hPa

In this work we also include the ERA5 reanalysiswhich is the most recent reanalysis product of the ECMWFand an updated version of ERA-Interim that combines largeamounts of historical observations into global estimatesusing advanced modeling systems and data assimilation(C3S 2017) ERA5 uses a more recent and improved ver-sion of the IFS Earth System Model and associated observa-tional assimilation system [Cy41r2 Hersbach and Dee(2016)] ERA5 has a globally improved spatial and verticalresolution on a 028deg times 028deg (~30 km) grid and resolves theatmosphere using 137 levels from the surface up to 001 hPa(~80 km) ERA-Interim has recently been replaced by theERA5 reanalysis The reanalysis data extend from 1950 tothe present and we use the period 1991minus2015 for the ana-lysis In the same way as ERA-Interim we use monthlynear-surface air temperature mean sea level pressure 850-hPa specific humidity and wind components from ERA5This allows us a multi-comparison of reanalysis products aswell as dynamically downscaled simulations versus theirboundary conditions (ERA-Interim) and the new ERA5 reana-lysis A summary of the observations and reanalysisproducts used in this study are given in Table 1

23 Regional climate model simulations

We employ the Polar Weather Research and Forecast-ing Model (Polar-WRF version 391) (Hines and Brom-wich 2008 Bromwich et al 2009 Hines et al 2011)which is a polar-optimized version of the WRF model(Skamarock et al 2008) Polar-WRF solves a fully compress-

ible non-hydrostatic system of equations on an Arakawa C-grid in the horizontal and it includes a terrain-followingcoordinate system in the vertical The model includes modi-fied land-surface model sea-ice representation allowing thespecification of variable sea-ice thickness and snow depthover sea ice These modifications also include optimal val-ues of snow thermal properties and improved heat flux calcu-lations Time-variable fractional sea ice is represented by sep-arate calls to the surface layer scheme for ice and openwater and the surface heat fluxes are areally averaged toobtain the final values for the fractional sea-ice grid box(Steinhoff et al 2014)

Polar-WRF is a limited-area model and it requires inform-ation on the wind temperature geopotential and relativehumidity at the lateral boundaries In addition the surfaceelevation pressure sea-ice conditions and sea surface temper-atures also have to be provided Polar-WRF has been testedover polar ice regions including permanent ice (Hines andBromwich 2008 Bromwich et al 2013b Deb et al 2016Listowski and Lachlan-Cope 2017) Arctic pack ice (Brom-wich et al 2009) and Arctic land (Hines et al 2011Wilson et al 2012) The model has also been used to pro-duce operational real-time weather forecasts for Antarctica(Powers et al 2012)

The modeling experiment consists of two nesteddomains at 04deg (~45 km) and 013deg (~15 km) spatial resolu-tions with a one-way nesting approach on a polar stereo-graphic projection (Fig 2) The mother domain includesmuch of western Antarctica and southern South Americaand has 118 times 114 grid cells (PWRF-45) The inner domainis centralized on the Antarctic Peninsula and Larsen IceShelf and has 208 times 190 grid cells (PWRF-15) Bothdomains employ 61 vertical levels between the surface andthe model top at 10 hPa Initial and lateral boundary condi-tions are provided by ERA-Interim at 6-h intervals with agrid spacing of 075deg times 075deg ERA-Interim (six-hourly075deg times 075deg) sea surface temperature fields initial soil para-meters (soil water moisture and temperature) as well as sur-

Table 1 Meteorological stations reanalysis products and RCM simulations used in this study

(a) Meteorological Stations

Data Source

Stations SCAR-READER ChileanMeteorological Service

(b) Reanalysis ProductsData Source Spatial resolution Vertical levelsERA5 European Centre for Medium-Range

Weather Forecasts (ECMWF)028deg times 028deg (~30 km) 137

ERA-Interim European Centre for Medium-RangeWeather Forecasts (ECMWF)

075deg times 075deg (~80 km) 60

(c) Regional Climate Model SimulationsSimulation Lateral Boundary Conditions Spatial resolution Vertical levelsRACMO21P(CORDEX)

ERA-Interim 044deg times 044deg (~50 km) 40

PWRF-45 ERA-Interim 04deg times 04deg (~45 km) 61PWRF-15 PWRF-45 013deg times 013deg (~15 km) 61


face pressure and skin temperatures are used as surface bound-ary conditions for the mother domain The sea-ice data arebased on the 25-km resolution Bootstrap dataset (Comiso2000) Land-type and topography information for the modelare from the default United States Geological Survey land-use data and GTOPO30 elevation data respectively Spec-tral nudging is applied for wind components (u v) air temper-ature specific humidity and geopotential height with anudging coefficient of 3 times 10minus4 sminus1 and wave numbers (3 3)and (2 2) for the mother and inner domains respectivelyThe choice of spectral nudging parameters is based on previ-ous Polar-WRF simulations performed over West Antarc-tica (Deb et al 2016) The simulations are performed onAmazon Web ServicesminusHigh Performance Computing withan elastic computed cloud instance (c5n18xlarge) and 360cores (10 computing nodes of 36 cores each) The simula-tions are based on a continuous run using restart files ofthree-year batches starting from 1 January 1989 to 31 Decem-ber 2015 and the first year of simulations (1989) is used asthe spin-up period

Based on the previous Polar-WRF experiments per-formed by Deb et al (2016) and Listowski and Lachlan-Cope (2017) as well as a couple of test simulations donewith different physical configurations the Polar-WRF runsare performed using (1) the new version of the rapid radiat-ive transfer model (Iacono et al 2008) for general circula-tion models (RRTMG) for both shortwave and longwave radi-ations (2) the Morrison double-moment microphysicsscheme (Morrison et al 2009) (3) the MellorminusYamadaminusJanjic (MYJ) boundary layer scheme (Janjic 2002) (4) the

GrellminusFreitas ensemble cumulus scheme (Grell and Freitas2013) and (5) the Noah-MP land-surface model (Niu et al2011 Yang et al 2011)

In addition to the Polar-WRF simulations we use theRoyal Netherlands Meteorological Institute (KNMI)Regional Atmospheric Climate Model (KNMI-RACM021Phereafter RACMO) model outputs forced with ERA-Interimfor comparisons RACMO simulations were performed bythe KNMI and obtained from the Coordinated Regional Cli-mate Downscaling Experiment (CORDEX Giorgi et al2009) dedicated to the Antarctic domain at 044deg (~50 km)spatial resolution and 40 vertical levels The reason for choos-ing this simulation is merely based on the availability ofdata and the integrity of the simulations Given thatRACMO simulations end in 2012 we use a common periodof 1991minus2012 for the comparison of RCM simulations andreanalysis products More information about the model andits application in polar regions can be found in vanMeijgaard et al (2008) and Lenaerts et al (2012)

3 Results

31 Observed temperature

Figure 3 shows the mean annual cycle of near-surfacetemperature for the selected stations on the windward(Fig 3a) and leeward (Fig 3b) sides The mean annual tem-perature cycle shows that there are differences of around~3degC (for summer) and 10degC to 15degC (for winter) betweenthe windward and leeward stations of the peninsula The cold-

Fig 2 Mother and nested domain topography at 45 km and 15 km resolutions used for Polar-WRF simulations respectively


est temperatures are observed at the Larsen Ice Shelf sta-tion among the four seasons (eg approximately minus25degC inJuly) The temperature contrast between the windward andleeward sides tends to increase in the central parts of the pen-insula compared to its northern end For instance the meanannual temperature across the peninsula shows a contrast ofaround ~8degC and ~4degC between both sides at the latitude ofSan Martin and Marambio stations respectively (Cook andVaughan 2010)

Figure 4 presents the 1991minus2015 time series of sum-mer autumn and annual mean near-surface temperature forthe windward and leeward stations A trend of summer cool-ing exists on both sides except at the San Martin stationwhere this is a trend of +002degC (10 yr)minus1 (not significant)(Figs 4a and b) The largest summer cooling trend isobserved at the Larsen Ice Shelf station [minus092degC (10 yr)minus1p lt 005] In autumn a marked statistically significant warm-ing takes place at the San Martin station [+064degC (10yr)minus1] Slight autumn warming occurs at the Frei Maram-bio and San Martin stations whereas the Larsen Ice Shelf sta-

tion shows a cooling trend [minus038degC (10 yr)minus1] At theannual scale trends show a notable cooling at the LarsenIce Shelf station [minus11degC (10 yr)minus1 p lt 005] Although Mara-mbio station shows a non-significant annual trend ofminus008degC (10 yr)minus1 a clearer cooling trend exists and autumnwarming is replaced by cooling at Marambio station (notshown) when using the same time period for both LarsenIce Shelf and Marambio on the leeward side (ie1996minus2015) which is consistent with the findings of Joneset al (2019) On the windward side located at a latitudeclose to the Larsen Ice Shelf station the San Martin stationshows a statistically significant warming trend [+052degC (10yr)minus1]

32 Temperature trend in ERA5 and ERA-Interim

Figure 5 compares the near-surface temperature trends[degC (10 yr)minus1 1991minus2015] for ERA5 and ERA-Interim onthe summer autumn and annual time scales In generalboth gridded products indicate a cooling trend in summerfor almost the entire peninsula [minus02degC (10 yr)minus1 to minus1degC

Fig 3 The 26-year (1991minus2015) mean annual cycle of near-surface air temperature for (a)San Martin (dashed black line) and Frei (solid black line) stations on the windward side and(b) Larsen Ice Shelf (dashed gray line) and Marambio (solid gray line) stations on theleeward side Error bars indicate the observed interannual variability of the respective month(plusmn1 sigma)


(10 yr)minus1] which is more pronounced on the leeward sidein agreement with the observed trends However in con-trast to ERA5 ERA-Interim shows a warming trend(although not statistically significant) in the central-south-ern coastal windward side (Alexander Island) (Fig 5b)Unlike the overall cooling trend in summer both productsshow the existence of a clear warming in major parts of thepeninsula in the autumn season Particularly ERA-Interimexhibits a statistically significant warming on the southernwindward coasts and central leeward side (Alexander Islandand Larsen Ice Shelf region) [approximately +15degC (10yr)minus1] This pronounced warming depicted by ERA-Interimappears weakened in ERA5 especially over AlexanderIsland [+06degC (10 yr)minus1 to +10degC (10 yr)minus1] Compared toERA-Interim the weaker warming trend in ERA5 existsalso over the inland territory of the Antarctic Peninsula partic-ularly over the northern and central parts At the annualtime scale the warming on the Larsen Ice Shelf region is not-able in both reanalyses [+02degC (10 yr)minus1 to +06degC (10yr)minus1 mostly non-significant] A general dipole-like trend pat-tern over the Antarctic Peninsula (ie the windward warm-

ing and leeward cooling) exists at the annual time scaleexcept at the Larsen Ice Shelf This dipole-like trend islargely confined to the coastal zones of both sides

To illustrate the potential role of atmospheric circula-tion changes on the temperature trend contrasts of the sum-mer and autumn seasons we compare the summer andautumn trends (1991minus2015) in mean sea level pressure and850-hPa wind components (u v) from ERA5 in Fig 6 In gen-eral the most notable change in the summer season is thestrengthening of the Weddell Sea low [minus2 hPa (10 yr)minus1]and an anticyclonic trend over the Amundsen Sea (Fig 6a)In autumn on the contrary deepening of the ASL [minus4 hPa(10 yr)minus1] dominates over the West Antarctic sector In con-nection with these summerminusautumn surface circulationchanges low-level westerlies (850 hPa) tend to beweakened and strengthened over the South Pacific in the sum-mer and autumn seasons respectively (Fig 6b) The exist-ence of a dipole-like pattern of sea level pressure trend inthe summer season (ie windward anticyclonic and lee-ward cyclonic conditions) is associated with the strengthen-ing of northward (positive) meridional winds over the Antarc-

Fig 4 Time series (1991minus2015) of summer (DJF top plots) autumn (MAM middle plots) and annual (bottomplots) near-surface air temperature for (a) San Martin (dashed black line) and Frei (solid black line) stations on thewindward side and (b) Larsen Ice Shelf (dashed gray line) and Marambio (solid gray line) stations on the leewardside Also included are the trend lines for each plot Note that when using the same time period for both Larsen IceShelf and Marambio on the leeward side (ie 1996minus2015) a clearer cooling trend exists at Marambio station andautumn warming is replaced by cooling


tic Peninsula indicating the possibility of more advection ofcold air from the continent (Fig 6c) On the other hand thestrengthening of southward (negative) meridional winds inthe autumn season could lead to the transport of warmer mid-latitude air to the Antarctic Peninsula particularly to the wind-ward side Compared to ERA5 the amplified leeward warm-ing observed in ERA-Interim in the autumn season could beassociated with a more strengthened ASL [minus5 hPa (10 yr)minus1]and southward winds and thus moister conditions over theAntarctic Peninsula in ERA-Interim [Figs S1 and S2 in the

electronic supplementary material (ESM)]

33 Comparison of numerical simulations toobservations and reanalyses

A comparison of the recent period (1991minus2012) near-sur-face air temperature and sea level pressure climatology fromERA5 ERA-Interim and numerical simulations is providedin the supplementary material (Fig S3 in the ESM) Over-all simulations generally capture the temperature and sealevel pressure climatology that is a relatively mild and

Fig 5 Spatial distribution of near-surface temperature trends (1991minus2015) for summer (DJF top plots)autumn (MAM middle plots) and the whole year (bottom plots) from (a) ERA5 and (b) ERA-Interim Thefilled black circles show the locations of meteorological stations used in this study Regions with statisticallysignificant trends at the 95 confidence level based on a two-tailed Studentrsquos t-test are hatched


humid marine climate on the western coast and a colder con-tinental climate on the east coast

To illustrate more details of the spatiotemporal differ-ences between the simulations and reanalysis products weprovide the mean annual cycle of near-surface temperaturefor the windward and leeward sides in Fig 7 On the wind-ward side ERA5 and ERA-Interim are very close to eachother with temperatures above 0degC in the summer monthsand around minus6degC in the winter months (Fig 7a) Dynamic-ally downscaled simulations show a significantly colderannual cycle to those in the boundary conditions (ERA-Interim) and ERA5 particularly in winter months (~2degC dif-

ference) On the leeward side ERA5 indicates colder temper-atures compared to ERA-Interim especially from April toSeptember (Fig 7b) RACMO reproduces almost the sameannual cycle as its boundary conditions (ERA-Interim)Both Polar-WRF simulations exhibit a similar annual cyclebut with much lower temperatures in winter months (approx-imately minus20degC) Some differences in radiative fluxes (ie sur-face downwelling longwave radiation) in Polar-WRF overthe leeward side (see Fig S4 in the ESM) can lead to amore pronounced radiative cooling with either too littlecloud or clouds that are optically thin (King et al 2015Deb et al 2016 Listowski et al 2017) Station-based com-

Fig 6 Spatial distribution of summer (DJF left plots) and autumn (MAMright plots) trends in (a) mean sea level pressure (b) 850-hPa zonal wind and(c) 850-hPa meridional wind from ERA5 for the period 1991minus2015 Regionswith statistically significant trends at the 95 confidence level based on atwo-tailed Studentrsquos t-test are hatched


parisons indicate that both reanalysis products and numer-ical simulations generally capture the observed annual cycleat each station (Fig S5 in the ESM) However large wintertemperature differences between Polar-WRF and RACMOsimulations at Marambio station (Fig S5b in the ESM)could be associated with differences in other simulated sur-face variables such as wind speed and mean sea level pres-sure (Fig S6 in the ESM)

Figure 8 compares the maps of summer near-surface airtemperature trends (1991minus2012) for dynamically down-scaled simulations and their boundary conditions (ERA-Interim) as well as ERA5 There is an overall summer cool-ing over most of the peninsula exhibited by the reanalysesThe warming trend (although not statistically significant)depicted by ERA-Interim (approximately +04degC (10 yr)minus1Fig 8b] over the central-southern windward coasts (Alexan-der Island) is mostly absent in ERA5 (Fig 8a) as also illus-trated in Fig 5a Numerical simulations reproduce the over-all cooling trend and in contrast to the boundary conditionsof ERA-Interim they show a cooling trend over AlexanderIsland (Figs 8cminuse) It can be speculated that the coarser

local details of the topography and landminusatmosphere phys-ics in ERA-Interim might account for the existence of differ-ent trends In addition unlike the RCMs there is a strengthen-ing of southward (negative) meridional winds at the surface(ie 10 m) in ERA-Interim (Fig S7 in the ESM) Further-more westerlies at 10 m tend to be more strengthened inERA-Interim (p lt 005) which might prevent cold-air advec-tion from the continent towards the central-southern wind-ward coasts in ERA-Interim Over the northern tip of the pen-insula both reanalyses and numerical simulations indicateless cooling [approximately minus02degC (10 yr)minus1] compared tothe rest of the peninsula even with some local warming(non-significant) depicted in the reanalyses and Polar-WRFsimulations

The trend map of the autumn season illustrates import-ant differences between the reanalyses and numerical simula-tions (Fig 9) Overall the reanalyses show a warmingtrend except on the southern leeward coasts (Figs 9a and b)On the other hand the numerical simulations produce avery close trend to each other exhibiting a marked dipole-like trend pattern over the Antarctic Peninsula (ie the wind-

Fig 7 The 22-year (1991minus2012) mean annual cycle of near-surface air temperature for the(a) windward and (b) leeward side of the Antarctic Peninsula Black and gray linescorrespond to ERA5 and ERA-Interim respectively Green light blue and dark blue lines arethe simulations of RACMO PWRF-45 and PWRF-15 respectively


ward warming and leeward cooling) (Figs 9cminuse) Unlikethe reanalyses the simulations show a cooling trend overlarge parts of the leeward side including the Larsen IceShelf region [approximately minus02degC (10 yr)minus1 non-signific-ant] in agreement with the observed trends Furthermorethe simulations show a slight cooling trend over some partsof the central-northern peninsula unlike the boundary condi-tions It can be speculated that the impact of the ASL is some-how confined to the windward side in the simulations (FigS8 in the ESM) and moreover unlike the boundary condi-tions there is a strengthening of northward (positive) windsat the surface over the central-northern peninsula that mightlead to the cooling trend over this region (Fig S9 in theESM) Some differences between the simulations also existon the southeast leeward side in which Polar-WRF simula-tions show larger cooling trends (Figs 9d and e) A compar-ison of the autumn season time series of surface down-welling longwave radiation over the southeast leeward sideshows that Polar-WRF simulations systematically havelower values with negative trends (although not statisticallysignificant) compared to those in RACMO simulations (FigS10a in the ESM) Surface variables also illustrate the increas-ing tendency of drier and colder conditions over the south-east leeward side in Polar-WRF simulations compared toRACMO during the 1991minus2012 period (Figs S10b and c inthe ESM)

The differences in temperature trends between multipledata sources exist in the annual-scale trend map too For

instance unlike in ERA-Interim and ERA5 the simulationsshow a clearer pattern of windward warming and leewardcooling (Figs 10cminuse) On the other hand although the simula-tions largely agree on the cooling trend over the central andsouthern leeward coasts they differ towards the northern tipof the peninsula particularly on the eastern side Forinstance unlike in RACMO Polar-WRF simulations showwarming trends over the Larsen A and Larsen B embay-ments (Figs 10d and e)

The results presented so far have revealed that there is anotable difference between the reanalyses products andnumerical simulations in presenting the recent temperaturetrends on the central windward and leeward coasts Todelve deeper into this finding we close this section by com-paring the reanalyses and numerical simulations with annualtime series of near-surface temperature at the San Martinand Larsen Ice Shelf stations on the central windward and lee-ward slopes respectively San Martin station shows a statistic-ally significant warming trend [+09degC (10 yr)minus1] for the1991minus2012 period (Fig 11a) Both reanalysis productsexhibit statistically significant warming trends +067degC(10 yr)minus1 and +083degC (10 yr)minus1 for ERA5 and ERA-Interimrespectively RACMO and PWRF-45 simulations estimatevery similar warming trends that are smaller than theobserved trend [+023degC (10 yr)minus1 and +027degC (10 yr)minus1respectively] PWRF-15 gives a statistically significant warm-ing trend of +045degC (10 yr)minus1 Station-based comparisonshows that among the reanalysis products and numerical simu-

Fig 8 Spatial distribution of summer (DJF) near-surface temperature trends (1991minus2012) for (a) ERA5 (b) ERA-Interim(c) RACMO (d) PWRF-45 and (e) PWRF-15 The filled black circles show the locations of meteorological stations used inthis study Regions with statistically significant trends at the 95 confidence level based on a two-tailed Studentrsquos t-test arehatched


Fig 9 Spatial distribution of autumn (MAM) near-surface temperature trends (1991minus2012) for (a) ERA5 (b) ERA-Interim(c) RACMO (d) PWRF-45 and (e) PWRF-15 The filled black circles show the locations of meteorological stations used inthis study Regions with statistically significant trends at the 95 confidence level based on a two-tailed Studentrsquos t-test arehatched

Fig 10 Spatial distribution of annual near-surface temperature trends (1991minus2012) for (a) ERA5 (b) ERA-Interim (c)RACMO (d) PWRF-45 and (e) PWRF-15 The filled black circles show the locations of meteorological stations used in thisstudy Regions with statistically significant trends at the 95 confidence level based on a two-tailed Studentrsquos t-test arehatched


lations PWRF-15 has the largest temporal correlation (r =09) and lowest root-mean-square-difference (17degC) for theSan Martin station (Table S1) On the leeward side amarked cooling trend exists for Larsen Ice Shelf station[minus14degC (10 yr)minus1 p lt 005] for the 1996minus2012 period (Fig11b) ERA5 shows a smaller cooling trend for the sameperiod [minus03degC (10 yr)minus1] whereas ERA-Interim does not cap-ture the observed annual-scale cooling trend at this stationOn the other hand dynamically downscaled simulationsforced with ERA-Interim capture the observed cooling trendat this point albeit with magnitudes smaller than observed[minus078degC (10 yr)minus1 for RACMO minus074degC (10 yr)minus1 forPWRF-45 and minus081degC (10 yr)minus1 for PWRF-15] Polar-WRF simulations exhibit the largest temporal correlations (r= 083 for PWRF-45 and r = 079 for PWRF-15) andPWRF-15 has the lowest root-mean-square-difference(19degC) for the Larsen Ice Shelf station comparison (TableS1 in the ESM)

4 Summary and concluding remarks

This study investigates the recent (1991minus2015) near-sur-face temperature trends over the Antarctic Peninsula using

observations ECMWFrsquos ERA5 and its predecessor ERA-Interim and dynamically downscaled RCM simulationsforced with ERA-Interim Given that the peninsula has twodistinct regions with different climate characteristics separ-ated by the Antarctic Peninsula cordillera the aim was toinvestigate whether the reanalyses and dynamical downscal-ing products are able to capture the differences in theobserved trends of temperature on the windward and lee-ward sides This allowed us to contrast the changes inERA5 and its predecessor ERA-Interim as well as comparedynamical downscaling simulations with the boundary condi-tions of ERA-Interim We first assess the recent observed tem-perature trends using four stations namely Frei and San Mar-tin stations (windward) and Marambio and Larsen Ice Shelfstations (leeward) We use hindcast simulations performedwith the Polar-WRF RCM forced with ERA-Interim overthe Antarctic Peninsula on a nested domain configuration at45 km (PWRF-45) and 15 km (PWRF-15) spatial resolu-tions for the period 1991minus2015 In addition we include hind-cast simulations of KNMI-RACMO21P (RACMO)obtained from the CORDEX-Antarctica domain at a 50-kmspatial resolution for further comparisons

Observed near-surface temperature trends indicate im-

Fig 11 Time series of mean annual near-surface air temperature for the (a) San Martin (1991minus2012) and (b)Larsen Ice Shelf (1996minus2012) stations The black solid line denotes the station while the dashed black andgray lines correspond to ERA5 and ERA-Interim respectively The dashed green light blue and dark bluelines are the simulations of RACMO PWRF-45 and PWRF-15 respectively


portant contrasts between summer and autumn for theperiod 1991minus2015 A notable summer cooling exists on thenorthern peninsula (Frei and Marambio stations) and lee-ward side (Larsen Ice Shelf station) The largest summer cool-ing trend is observed at the Larsen Ice Shelf station[minus092degC (10 yr)minus1 p lt 005] On the other hand in autumnSan Martin station on the central windward coasts exhibitsthe largest warming trend [+064degC (10 yr)minus1 p lt 005]Autumn warming is also notable at the other stations exceptthe Larsen Ice Shelf station At the annual time scale thereis a clear warming trend at San Martin station [+052degC(10 yr)minus1 p lt 005] whereas at a close latitude on the lee-ward side the Larsen Ice Shelf station exhibits a marked stat-istically significant cooling [minus11degC (10 yr)minus1]

Both ERA5 and ERA-Interim show a summer coolingthat is more notable on the central-southern leeward side ofthe peninsula [minus064degC (10 yr)minus1 to minus1degC (10 yr)minus1] Theclear windward warming in autumn depicted by the observa-tions is captured by both reanalyses products Howeverimportant differences in magnitude take place on the cent-ral-southern windward coasts For instance ERA-Interimshows a remarkable autumn warming over these regions[approximately +15degC (10 yr)minus1] whereas ERA5 illus-trates less warming especially over Alexander Island[+06degC (10 yr)minus1 to +10degC (10 yr)minus1] A general coastalwindward warming and leeward cooling (except the LarsenIce Shelf) exists at the annual time scale in both reanalyses

RCM simulations in general exhibit good skill in simu-lating the distinct temperature regimes of the Antarctic Penin-sula and reproduce a close spatiotemporal variability to eachother A systematic underestimation of summer and wintertemperatures (1degC to 3degC) exists for both PWRF-45 andPWRF-15 over the northern tip of the peninsula On theother hand PWRF-15 gives the closest annual cycle shapeat the San Martin and Larsen Ice Shelf stations compared tothe other simulations and reanalyses Regarding the temperat-ure trends unlike the boundary conditions (ERA-Interim) aswell as ERA5 Polar-WRF simulations present autumn lee-ward cooling over the Larsen Ice Shelf region [approxim-ately minus02degC (10 yr)minus1] At the annual time scale bothPolar-WRF and RACMO simulations indicate that there is aclear pattern of windward warming and leeward coolingUnlike in the reanalyses the numerical simulations exhibit awidespread leeward cooling including the Larsen Ice Shelfas well as the central-southern parts of the inland territoryof the peninsula Station-based comparisons on the wind-ward side of the central peninsula (San Martin station) showthat both reanalyses and numerical simulations agree wellwith the observed warming trend On the leeward side ofthe central peninsula at the Larsen Ice Shelf station ERA5shows a weaker cooling trend than that depicted by the obser-vations whereas ERA-Interim does not capture the trendOn the other hand dynamically downscaled simulationsforced with ERA-Interim capture the observed coolingtrend indicating the existence of added value

Despite the long-term warming trend recent studies

also show the existence of a regional cooling trend in someparts of Antarctica including the Antarctic Peninsula sincethe late 1990s (Carrasco 2013 Turner et al 2016 Oliva etal 2017) However this recent cooling period on the penin-sula does not yet represent a shift in the overall robust warm-ing trend and is instead attributed to internal climate variabil-ity (Jones et al 2016 Gonzalez and Fortuny 2018 Clem etal 2019 Jones et al 2019) The persistent windward warm-ing trend in the autumn season as well as at the annual timescale during the recent cooling period could lead to import-ant implications for the fate of ice sheet surfaces on the wind-ward coasts Indeed following the general dipole-like trendpattern over the Antarctic Peninsula (ie the windward warm-ing and leeward cooling) the simulations indicate a decreas-ing and increasing trend in sea ice on the windward and lee-ward coasts respectively (not shown) This warming and con-current ice-sheet surface changes observed on the wind-ward coasts are likely to be associated with the recent deepen-ing of the ASL and anomalous northerly warm advectiontowards the West Antarctic sector and Antarctic Peninsuladepicted by the reanalyses This large-scale forcing mechan-ism has also been reported in previous studies (eg Brom-wich et al 2013a Raphael et al 2016 Jones et al 2019)Jones et al (2019) further highlighted the linkage betweenthe recent ASL deepening and a positive Southern AnnularMode trend On the other hand the reanalyses show that thesummer season is characterized by strengthening of the Wed-dell Sea low as well as an anticyclonic trend over the Amund-sen Sea This synoptic spatial variability is accompanied bynorthward (positive) meridional winds which results inincreased transport of cold continental air over the Antarc-tic Peninsula This is consistent with the work of Turner etal (2016) who found that more cyclonic conditions in thenorthern Weddell Sea are associated with the observed cool-ing trend over the Antarctic Peninsula Understanding thedeterminants of the complex interplay between the strengthen-ing phases of the ASL and Weddell Sea low is an intriguingaspect that deserves further investigation

As highlighted by Hosking et al (2013) a correct repres-entation of the ASL is an important factor in representingWest Antarctic surface climate characteristics properly in cli-mate models In a similar manner compared to ERA5 theamplified autumn leeward warming detected in ERA-Interim could be associated with a more strengthened ASLand thus moister conditions over the Antarctic Peninsulawhich might eventually trigger more episodic leewardFoehn warming (eg Cape et al 2015 Bozkurt et al2018 Datta et al 2019) in ERA-Interim The better spatialand temporal resolution of ERA5 compared to ERA-Interimtends to reduce the amplified warming trends detected inERA-Interim over the central-southern windward and lee-ward sides of the Antarctic Peninsula This improvementcould be associated with better representation of large-scaleforcings (eg the ASL) as well as the finer local details ofthe topography and refined landminusatmosphere physics Veryrecently some improvements in the performance of ERA5


over ERA-Interim in representing surface climate characterist-ics of the Antarctic continent were also reported (Tetzner etal 2019 Gossart et al 2019)

Finally regarding numerical simulations we furtherdemonstrate the potential added value introduced by thedynamically downscaled simulations For instance PWRF-15 exhibits higher temporal correlations and lower root-mean-square-differences with respect to the boundary condi-tions of ERA-Interim for the San Martin and Larsen IceShelf stations Further station-based comparisons with thecoarser resolution simulation (ie PWRF-45) also indicatethat PWRF-15 shows an overall better performance in repres-enting the spatiotemporal variability of the near-surface airtemperature highlighting the importance of the spatial resolu-tion As illustrated by van Wessem et al (2015) and Deb etal (2016) the improved RCM simulations using higher spa-tial resolution might be crucially important to achieve a bet-ter assessment of surface meteorological variables over com-plex terrain such as the Antarctic Peninsula particularlyalong the coastal sites For instance Zhang and Zhang(2018) demonstrated that higher resolution simulations areable to resolve foehn warming and thus tend to produce lar-ger warming and larger temperature fluctuations on the lee-ward side of the peninsula including the Larsen Ice Shelfregion In addition to spatial resolution improvement moreresearch is warranted to further investigate the impact ofmodel tuning and physics schemes on the surface climatecharacteristics of the Antarctic Peninsula We haverefrained here from comprehensively analyzing the phys-ical mechanisms of some of the local differences in temperat-ure trends depicted by the reanalyses and RCM simulationsTherefore further research is also needed to better clarifythese mechanisms at both large and local scales that canlead to large differences of temperature trends in the mul-tiple-data sources

Acknowledgements This work was funded by FONDAP-CONICYT (Grant No 15110009) D B acknowledges supportfrom CONICYT-PAI (Grant No 77190080) This paper is Contribu-tion Number 1588 of the Byrd Polar and Climate Research CenterThe authors acknowledge two anonymous reviewers for their con-structive comments that helped to improve the manuscript DBacknowledges the Scientific Committee on Antarctic Research(SCAR) Expert Group on Operation Meteorology in the Antarctic(OPMet) for a partial funding award for the 14th Workshop on Ant-arctic Meteorology and Climate (WAMC) as well as the Year ofPolar Prediction in the Southern Hemisphere (YOPP-SH) meetingin Charleston SC USA between 25 and 28 June 2019 We thankDavid B REUSCH (Department of Earth and Environmental Sci-ence New Mexico Technology) Rodrigo Delgado URZUacuteA(Direccioacuten General de Aeronaacuteutica Civil Chile) Kevin MAN-NING (National Center for Atmospheric Research Boulder Color-ado) Andrew ORR (British Antarctic Survey) and Pranab DEB(Indian Institute of Technology) for useful discussions on thePolar-WRF simulations We are grateful for data from the SCAR-READER dataset and we wish to acknowledge ECMWF for ERA-Interim and ERA5 data The Polar-WRF simulations were per-

formed within a project entitled ldquoSimulaciones climaacuteticasregionales para el continente Antaacutertico y territorio insular Chilenordquofunded by the Chilean Ministry of Environment This research waspartially supported by the Basal Grant AFB 170001 and the super-computing infrastructure of the NLHPC (ECM-02PoweredNLHPC) The authors appreciate the support of Amazon Web Ser-vices (AWS) for the grants PS_R_FY2019_Q1_CR2 amp PS_R_FY2019_Q2_CR2 which allowed us to execute the Polar-WRF sim-ulations on the AWS cloud infrastructure We thank FranciscaMUNtildeOZ Nancy VALDEBENITO and Mirko DEL HOYO atCR2 for post-processing of Polar-WRF simulations

Electronic supplementary material Supplementary materialis available in the online version of this article at httpsdoiorg101007s00376-020-9183-x

Open Access This article is distributed under the terms of theCreative Commons Attribution 40 International License (httpcre-ativecommonsorglicensesby40) which permits unrestricteduse distribution and reproduction in any medium provided yougive appropriate credit to the original author(s) and the sourceprovide a link to the Creative Commons license and indicate ifchanges were made

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ing and melting (Marshall et al 2006 Steig et al 2009Bromwich et al 2013a 2014 Holland et al 2019) Des-pite the important evidence for climate change and itsimpacts on cryosphere and ecosystem processes (egRignot et al 2004 Cape et al 2014) the Antarctic contin-ent suffers from inadequate observational coverage due toits remote and harsh environmental conditions Thisimposes a limitation on the surface meteorological data tocharacterize and reduce the uncertainty of climate change

Although the Antarctic Peninsula has more research sta-tions compared to the rest of the Antarctic continent sev-eral meteorological stations are underused due to a lack ofarchiving and complete time series (Lazzara et al 2012 Frai-man et al 2014) This is an impediment to expanding ourknowledge of the climate variability of the peninsula In par-ticular the Antarctic Peninsula cordillera constitutes an oro-graphic obstacle to the westerlies and thus the peninsulapresents two different climatic zones a relatively mild andhumid marine climate on the west coast (windward) wherenorthwesterly winds prevail and a cooler continental cli-mate on the east coast (leeward) (Fig 1) mainly affected bysoutherly winds (King and Turner 2009) The steep terrainof the Antarctic Peninsula therefore results in harsh condi-tions that further prevent the deployment of extensive fieldobservations to obtain long-term records On the one handwith the aid of few available long-term surface meteorolo-gical records the Antarctic Peninsula is considered to beone of the most vulnerable climate change ldquohotspotsrdquo with along-term warming trend in near-surface temperatureobserved over the last 50 years [eg FaradayVernadsky sta-tion 294degC (50 yr)minus1] (Marshall et al 2006 Turner et al2016 Jones et al 2019) However since the late 1990s acooling period has been observed in the Antarctic Penin-sula that is attributed to atmospheric teleconnections (Car-

rasco 2013 Turner et al 2016 Oliva et al 2017) On theother hand a sparse observation network prevents extens-ive analyses to minimize the regional-scale uncertainties asso-ciated with climate variability and trends Excluding the relat-ively short time series of satellite products one commonmethod of overcoming the difficulties arising from the inad-equate observational network is to use gridded atmosphericdata at high temporal resolution (ie reanalysis data) andorhigh spatial resolution regional climate models (RCMs) to rep-resent the main surface climatic features as well as toexplore physical mechanisms behind the observed changes

In recent years atmospheric reanalysis data have beenwidely used for various studies such as surface climate charac-teristics of the Antarctic region as well as large-scale atmo-spheric forcing mechanisms modifying the surface climatevariables In a recent study Gossart et al (2019) performeda comprehensive comparison and evaluation of differentreanalysis products in representing the surface climatologyof the Antarctic Ice Sheet They demonstrated that althoughthe reanalysis products could be useful tools they can per-form very differently depending on the region of interest sea-son and variable Regarding the interplay between the local-and large-scale climate in the Antarctic continent Hoskinget al (2013) investigated the AmundsenBellingshausen Sealow (hereafter ASL) using reanalysis data and constructeddiagnostic indices (ie the strength and location of theASL) Also Hosking et al (2013) highlighted that the ASLis an important synoptic system modulating the West Antarc-tic climate variability In another study with the aid of reana-lysis data Rondanelli et al (2019) highlighted the role of trop-ical variability in connection with the highest temperaturerecorded on continental Antarctica and associated large melt-ing events over the Antarctic Peninsula

In addition to surface observations and reanalysis

Fig 1 Study region of the Antarctic Peninsula and meteorological stations (in black) used for the temperatureanalysis The red and blue dashed lines correspond to the windward and leeward sides of the peninsula respectively










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Recent Near-surface Temperature Trends in the Antarctic … · 2020-04-18 · recorded on...

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