Tourism and climate in Lisbon: an assessment based on weather types

ToUriSM aND CLiMaTE iN LiSBoN. aN aSSESSMENT BaSED oN WEaTHEr TYpES raquel Machete1 antónio lopeS2 Ma Belén góMez-Martín3 helder fraga4 abstract – although climate is perceived as an essential part of tourism, influencing touristic regional and seasonal distribution patterns, ideal climate conditions for tourism are often assumed, rather than demonstrated. after reviewing the distinct tools that have been applied in order to evaluate climate potential for tourism, as well as tourists’ preferences, Besancenots’ weather-types method was chosen. this model was adapted and applied to Lisbon, evaluating the suitability of the summer season for tourism activities. the resulting weather type pattern was then crossed with the seasonal tourist demands (visitation statistics), allowing to conclude that even when the weather is categorized as extremely hot (type 7) or unfavourable for tourism (type 8) it does not reflect in the room occupation rates of the city of Lisbon, reinforcing recent advances in tourism climatology, that defy expert based thresholds of thermal preferences and comfort. a reformulation of the weather type model with our findings can be a useful tool for future assessments of tourist potential under projected climate changes. Keywords: tourism and climate, weather-types, climate change, Lisbon, Portugal. resumo – turiSMo e cliMa eM liSBoa. análiSe coM BaSe noS “tipoS de teMp o”. ainda que o clima seja visto como parte essencial das actividades turísticas, influenciando os padrões de distribuição espácio-temporal dos fluxos de viajantes, as condições climáticas ideais para o turismo são frequentemente vistas como auto-explicativas. O método dos tipos de tempo de Besancenot foi seleccionado, após uma revisão dos vários métodos que received: May 2014 accepted: september 2014 1 researcher at the Centro de estudos Geográficos and PhD student at the instituto de Geografia e Ordenamento do território da Universidade de Lisboa. e-mail: [email protected] 2 Coordinator of the Zephyrus research unit of the Centro de estudos Geográficos and Professor at the instituto de Geografia e Ordenamento do território, University of Lisbon. e-mail: [email protected] 3 Professor at the Department of Physical Geography and regional analysis, faculty of Geo graphy and History, University of Barcelona. e-mail: [email protected] 4 researcher in the Centre for the research and technology of agro-environmental and Biological sciences, University of trás-os-Montes e alto Douro. e-mail:[email protected] Finisterra, XLiX, 98, 2014, pp. 153-176 154 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga têm vindo a ser aplicados para calcular o potencial do clima para o turismo, bem como para avaliar as preferências dos turistas. este método foi adaptado e aplicado a Lisboa, de modo a analisar a aptidão turística da estação estival. O padrão de tipos de tempo resultante desta análise foi, em seguida, cruzado com indicadores de procura turística (estatísticas de ocupação hoteleira), permitindo-nos concluir que, mesmo quando o estado do tempo é categorizado como extremamente quente (tipo de tempo 7) ou desfavorável para o turismo (tipo de tempo 8), não se reflecte de forma negativa nas taxas de ocupação hote leira da cidade de Lisboa. Deste modo, o estudo vem reforçar conclusões recentes de estudos climáticos aplicados ao turismo que têm vindo a contestar os limiares de preferências e conforto térmico anteriormente definidos por peritos. reformulado com as conclusões deste estudo, o modelo de tipos de tempo pode ser uma ferramenta útil para a análise futura do potencial turís tico atendendo às alterações climáticas projectadas. Palavras-chave: turismo e clima, tipos de tempo, alterações climáticas, Lisboa, Portugal. résumé – touriSMe et cliMat à liSBonne. analySe de typeS de teMpS. Bien que le climat soit considéré comme un élément essentiel, à tenir en compte pour les pratiques touristiques et qu’il influence la répartition régionale et saisonnière des touristes, les climats dits favorables sont plus souvent estimés que décrits. On étudie ici la saison d’été à Lisbonne, en lui appliquant le modèle des types de temps distingués par Besancenot, adapt é à Lisbonne. Or, même lors des types de temps 7 (extrêmement chaud) ou 8 (défavorable au tourisme), on n’y constate aucune diminution du taux d’occupation des chambres. Cela donne raison à certains auteurs qui mettent en doute les limites climatiques utilisées pour déterminer la préférence thermique et le confort. Les présents résultats pourront être utiles pour une reformulation du modèle des types de temps et pour l’évaluation du potentiel touristique futur tenant en compte les projections de changement climatique. Mots-clés: tourisme et climat, types de temps, changement climatique, Lisbonne, Portugal. i. intrODUCtiOn the importance of tourism to the Portuguese economy and the unequivocal links the sector has with the elements of the atmosphere highlight the need to consider climate in all its aspects. Weather and climate conditions are key elements in the majority of tourism products provided by tourist destinations in Portugal. thus it is important to consider the atmospheric aspects at the present moment but it is also important to consider any future changes in the atmospheric conditions (smith, 155 1993; Wall and Badke, 1994; Gómez-Martín, 2005; Hall, 2008; Becken and Hay, 2007; Becken, 2010). Weather and climate have a great importance in tourists’ decision-making and in travel experience. Weather and climate experienced at the destination and at the place of origin are relevant motivators for tourism (eugenio-Martin and Campos- -soria, 2010; scott et al., 2012). Weather and climate at the destination play an impor tant role in decision making because they act as a resource that enables or d eters the fulfilment of a number of tourism activities (Perry, 1997; Goméz-Martín, 2005; Becken and Wilson, 2013) and because they act as an attraction factor (Lohma n and Kaim, 1999; Hamilton and Lau, 2004). Weather and climate in the place of origin can determine travel motivation, timing of travel and choice of destination (scott and Lemieux, 2009, 2010). according to smith (1993) and Wall (2007), there is a statistical fit between the arrival of British tourists in Portugal and the amount of rain in the previous summer in Britain. Other analyses (agnew, 1997) have also found a correspondence between the increase in the outbound tourism following a cold winter. there are also several other factors weighing in the selection of a destination. tourism literature has explained the motivation for travelling and destination selection as the result of two interacting strengths, the need to travel (“push”) and the attractiveness factors (“pull”, Crompton, 1979) the latter covering elements such as the landscape, climate and culture (static), but equally hospitality services as well as accessibility (dynamic) and current decisions (prices, promotion and even fashion trends), whereas “push” factors are related to a set of intangible needs felt by the individual (Crompton, 1979; Chon, 1989; Lubbe, 1998; Kozak, 2002). Weather is an intrinsic component of the travel experience (scott et al., 2012), and for many travellers weather conditions at the destination can influence the degree of satisfaction (Hübner and Gössling, 2012). in a study undertaken to assess touristweather interactions, Becken and Wilson (2013) concluded that tourists that had to adjust their travel routes, the timing of travel or the activities during their holiday due to adverse weather conditions were less satisfied than those that reported no changes. Climate and weather can allow tourists to enjoy their holiday activities safely and comfortably, helping them fulfil the desires that originally brought them to the resort and, consequently, raising their satisfaction levels (Gómez-Martín, 2005). this is signi ficant for a number of reasons, especially the economic repercussions, since satis faction should influence future visits: satisfied tourists tend to return to the destination, whereas dissatisfied tourists may seek new destinations (Becken, 2010; Hübner and Gössling, 2012) or provide negative word-of-mouth recommendations to family and friends (Gössling et al., 2006; Mansfeld et al., 2007). in a survey undertaken at the Caribbean island of Martinique during an extreme weather event (prolonged, heavy rainfall during the dry season), 17% of the inquired indicated that they were unlikely to return and 4% reported that they would not return, without a doubt, due to the expe rienced weather parameters (Hübner and Gössling, 2012).the importance that atmospheric conditions have on tourists’ decision-making and in travel Tourism and Climate in Lisbon 156 expe rience requires the evaluation of climate-tourist potential at the destinations. the a ssessment of climate resources can play an important role in providing information to tourists and operators. Climate information for long-term planned trips can determine − apart from destination choice − the time of travel and the planning of activities. Prior to the departure, climate and weather information will also be of use for packing (adequate clothing and equipment) and scheduling the travel route. During holidays, time will most definitely mark the on-site behaviour of the tourist, and render viable or unviable the activities that had been formerly planned. Climate and weather information is just as important for the tourism supply, meaning, tourism agents and operators, either when deciding whether to make the i nvestment (and have a real analysis on expected returns), as for operating costs. Decisions on the location of new resorts, building and landscape design and cons truction timing (scott and Lemieux, 2010) can benefit from information on the normal values of climatic elements such as temperature, humidity, rainfall, prevailing winds (Goméz- -Martín, 2005). the construction materials, the site, thickness, shape, colour and orientation of the roof and façades should all take into account the historical climate in order to provide comfortable and safe areas for leisure. Landscape planning should also be adequate to the climate requirements of the destination mode rating the influence of some atmospheric elements (Goméz-Martín, 2005). suited architecture can, additionally, help reduce costs with artificial heating or coolin g systems. the assessment of climate resources can be a fundamental tool in the planning of tourist destinations currently and in the future. the purpose of this paper is to asses s the climate suitability of Lisbon for tourism, making use of the weather type methodology in order to establish a baseline for a future assessment of the city’s potential under the projected climate scenarios. to achieve these aims, the paper presents the defining characteristics of tourism in the geographical area of study and examines the vulnerability of the sector to climate change. then it describes the methodology and data used, and the main results and conclusions obtained. ii. stUDy area 1. Tourism in Lisbon (portugal) europe remains the most popular holiday destination in the world, hosting over half of the total tourist arrivals, having surpassed, for the first time ever, the one b illion mark in 2012 – quadrupling the arrivals registered in 1950 (UnWtO -World tourism Organization, 2013). international tourism revenue grows along with the arrivals rate, totalling 837 billion € in 2012. Within europe, the Medi terranean still holds a privileged position. Portugal is one of the southern european countries that has been outdoing the sub-region, in terms of demand share (UnWtO, 2013). almost 7.7 million tourists entered Portugal in 2012 (UnWtO, 2013). it is the 6th country in terms of number of international arrivals in the southern europe/MediR. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga 157 terranean region, falling behind spain, italy, turkey, Greece and Croatia and 5th in terms of tourism expenditures, with 11,056 million € accounted for in 2012 (UnWtO, 2013). adding up to that, domestic tourism is, by no means, something to disregard (over 6 million people) (turismo de Portugal, 2013b). Lisbon has been undergoing an increase in tourism demand for the last decades (turismo de Lisboa, 2011; Brito Henriques, 2003). During the 1990s and the first decade of the 21st century, several international events concurred for the boosting of the capitals’ international image (european Capital of Culture in 1994, Lisbon World exhibition 1998, Uefa european football Championship in 2004). Mega events have been widely used to attract visitors and investment (edwards et al., 2002; richards and Wilson, 2004). the emergence and expansion of low-cost airlines have also contributed to improve the accessibility to the region and, hence, stimulate its growing role as a city break destination (World travel and tourism Council, 2007). Lisbon is known for its warm and dry summers (rainfall occurs predominantly between October and april). the pleasant temperatures that typify the region’s weather (maximum average temperature in Lisbon in July is 28.1ºC and the minimum average for January is 8.1ºC) derive from regional geographic factors, such as latitude and the proximity to the atlantic Ocean. the favourable natural assets can explain, to a great extent, Lisbon’s central location. two sunny costal lines – estoril and arrábida – sheltered from the frequent north and nW winds by the topographic configuration partly explain the tourist attrac tiveness of the region. so, after having come in third place for a very long period of time, behind the algarve and Madeira, Lisbon is now the second national tourism destination. from January to October 2013 the Portuguese statistics institute estimated over 4 million guests in Lisbon, totalling up to 9.5 million overnights, most of which from foreign markets (2.78 million international guests against 1.3 million domestic tourists) (turis mo de Portugal, 2013a). in the last years, the city has been awarded numerous distinctions (for instance, it was voted, repeatedly, Europe’s Leading Destination, Europe’s Leading City Break Destination and Europe’s Leading Cruise Destination, by the World Travel Awards) and, it has been granted many references from international media (turismo de Lisboa, 2011). although the influence of media coverage of Lisbon’s popularity has yet to be demonstrated, literature emphasizes the role of media regarding perceptions (Hübner and Gössling, 2012) and as being able to stimulate, create or reduce interest in places and activities (Butler, 1990 and 2011). the tourism demand pattern in the city demonstrates some seasonality. an analy sis of Lisbon’s room occupation rates from 2005 to 2010 (fig.1) shows clearly three distinctive periods: a lower demand season that stretches from november to february, higher peeks of demand in april, May, august, september and October and some months in between – March, June and July – that present slightly lower room occupation shares, but still around 60/70 %. Tourism and Climate in Lisbon 158 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga according to Butler and Mao (1997) typology for seasonality, a destination that demonstrates two time-spans of higher demand would fit under the two-peak seasonality pattern. fig. 1 – room-occupation rates of the city of Lisbon, per month, from 2005 to 2010. Fig. 1 – Taxa de ocupação-quarto da cidade de Lisboa, por mês, de 2005 a 2010. source: Turismo de Lisboa the city’s tourism offer is quite diversified. in a recent study undertaken by the turismo de Lisboa, tourists made reference to the local hospitality, the accessi bility of interest points, abundance of cultural heritage and architecture, quality of the gastronomy and climate as some of the determining pull factors in Lisbon. in the evaluation of the parameters most influential for the overall satisfaction, climate and weather and monuments were the only parameters collecting an average rating greater than 8.5 (or, alternatively, a degree of satisfaction of 85%) according to Observatório do turismo de Lisboa (2011). 2. Vulnerability of tourism to climate change in Lisbon (portugal) studies about climate change in Portugal (using different climate scenarios) indicate that temperature will tend to increase in the order of 3ºC to 7ºC for the s ummer season in mainland Portugal, particularly affecting the northern and Central regions. in the area of Lisbon the temperature will increase on average 1.7 ºC and 2.5ºC (B2 and a2 scenarios) (Wilbanks et al., 2007) by mid XXi century, while that change could reach 2 to 4ºC by mid XXi century and 5 to 9ºC by the end of the century, for the maximum summer temperatures (santos and Miranda, 2006). Different scenarios forecast a reduction in annual rainfall in mainland Portugal by 20% to 40% of current levels, mostly due to a reduced rainy season which is expec ted to be more concentrated in spring and autumn. the majority of the models predict a moderate rainfall increase in the north during the winter season for the period 159 2070-2099 in comparison to the baseline period of 1961-1990. M odel projections are less consistent for the Centre and south in the winter season for the same period (s antos et al., 2001). according to the second report of the siaM project (Climate Change in Portugal - scenarios, impacts and adaptation Measures), a reduc tion of 150 mm in median annual rainfall is estimated until 2050, within the four different scenarios; the reduction would be especially accentua ted in the autumn (santos and Miranda, 2006). although some global climate models, such as coupled atmosphere–ocean general circulation model eCHaM4/OPyC3 (semenov and Bengtsson, 2002) and the Hadley Centre model (allen and ingram, 2002 and allan and soden, 2008) suggest that, in the future, precipitation will occur predominantly as short-term heavy rainfall events. it should be noted that there is no evidence of an increase of heavy rainfall events in the past three decades in Lisbon (aguiar, 2010). the projected changes in the study area could have direct and indirect i mpacts that may affect the tourist sector in opposing ways. Changes in climate parameters will cause significant changes in present climate-tourism potential of the area. these could materialize in a favourable expansion of the tourist season, spreading occupan cy rates more evenly through spring, autumn and summer. However, part of the summer tourist season may suffer an important decrease in comfort levels (amelung and Viner, 2006; Moreno and amelung, 2009). rutty and scott (2014) provide some new insights on tourist thermal preferences for beach tourism and on the number of ideal or unacceptable months of Mediterranean beach and urban tourist destinations by early, mid and end of the XXi century. the future climate scenario could represent an opportunity to reduce the seasonality that has traditionally characterized the touris t sector in the study region (Hein et al., 2009). according to Hadwen et al. (2011) places where a marked variation in climate (differences in winter and summer temperatures, or pronounced wet or dry seasons) exists, seasonality is mainly driven by these differences. in contrast, the reduction in precipitation could lead to a reduction in the availability of water supplies and an increase of water quality problems risks. the decreased runoff in the spanish part of the transboundary river basins is likely to accentuate even further the expected decrease of water availability in the Portuguese territory (santos et al, 2001). that situation would oblige the reassessing of tourism development models – especially for projects that d emand great amounts of water, such as resorts with vast gardens that demand constant irrigation (Gössling et al., 2001; Brito H enriques et al., 2010), swimming pools, golf courses − and to reassess management of the current hydric resources in order to deal with the future, possibly increased, d emand for water (Gössling et al., 2011; eU, 2007). iii. MetHODs anD Data 1. Methods to evaluate climate potential for tourism according to scott et al., (2008) the numerous attempts to identify most favourable or optimal climatic conditions for tourism, both in general and for specific Tourism and Climate in Lisbon 160 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga tourism segments and activities (rutty and scott, 2013) can be clustered into three types of approaches: expert-based, revealed preference and stated preference. a) included in the expert-based approach are the climate evaluating methods that several geographers have transposed from bioclimatology in order to adequately evaluate the climate potential of regions for tourism. these methods (often i ndexes) classify the integrated effect of climate parameters on people, associating a number of meteorological variables perceived as decisive for pursuing outdoor recreation. a first generation of indexes was proposed by researchers such as B urnet (1963), Hughes (1967), Davis (1968) or sarraméa (1980), based on arithmetical operations with climate parameters such as sunshine hours, temperature or precipitation and number of days with occurrence of rainfall. sarraméa’s climatico-marin index had the particularity of incorporating water temperature, wind speed, fog, ice and snow. n otwithstanding their utility, these methods were the object of criticism. One of the critics raised by Besancenot (1990) is the calculation of these indexes through the use of climate parameters expressed in different units of measurement. another recurrin g critic concerned the failure to use the totality of atmospheric environmental attributes important to tourism (De freitas, 2003, 2008; Gómez-Martín, 2006). Lastly, these indexes completely overlook consumer preference (Gómez-Martín, 2006). in 1985 Mieczkowski developed a comprehensive approach, framed within this first generation indexes, the Tourism Climate Index (tCi) that combined seven variables and is still frequently applied (Morgan et al., 2000; scott and McBoyle 2001; scott et al., 2004; amelung and Viner, 2007). the value of each climate parameter is divided into classes and each class is ascribed an index, reflecting its adequacy for tourism. tCi was designed bearing in mind the practice of s ightseeing activities. rates and weights were based on expert judgment and on M ieczkowski’s own opinion (Moreno, 2010). this subjectivity is one of the criticisms directed at this index. furthermore, as it is calculated with average climate data, instead of actual observations, it rarely expresses weather as experienced by tourists (Besancenot, 1990). simultaneously, Besancenot et al., (1978) and Besancenot (1985, 1990) developed another tool: weather typing. instead of using average data, this method provides a synthesis of the combination of daily climate elements. Originally, the classification elaborated by Besancenot was developed to comprehend the d emands of sea-side tourism and was adapted to mass tourism afterwards. it encompassed nine types of weather, seven of which are favourable to the practice of outdoor recrea tion (even if they include a light degree of discomfort) and two are unfavourable for outdoor leisure. in order to provide a holistic evaluation of climate, the weather type methodology combined the following daily parameters: sunshine (hours), cloud cover (octas), precipitation (duration or quantity), maximum temperature, wind speed (m/s) and vapour pressure (hPa). the thresholds were first drawn from the observation of vacationer’s behaviour on the european seaside (and next adapted to different world sites) and from bioclimatological known thresholds. Criticisms to this method have been raised (scott et al., 2008, 2012), particularly because weather typing was primarily based on subjective expert opinion 167 two sources of data were used in this research: 1) for the assessment of weather-types in Lisbon, Daily sunshine (h), cloud cover (octas), precipitation (mm), daily temperatures (ºC), wind speed (m/s) and relative humidity (%) values were collected, in order to calculate Pet, from nCDC portal (http://www.ncdc.noaa.gov/cdo-web/) for the Lisbon/Gago Cou tinho, a first order observatory (38° 46’n latitude, 9° 08’W longitude and 105 m altitude). the studied period was 2000-2010 (including the latter and exclu ding 2005, due to a great number of gaps). the months under analysis were, as pre viously referred, June to september. each day was classified separately into one of the weather-types class of table ii and the frequency of the different weathe r types were calculated per decade. this is the most suitable temporal scale when giving information on weather in temperate climates that have a pronounced annual cycle (Lin and Matzarakis, 2008). its adequacy for tourism and climate information for tourists is reinforced by the fact that holidays usually last a week or a fortnight, rather than a month. 2) to assess the possible climate conditions in the future, taking into account projected climate changes, minimum and maximum temperature were drawn from 9 regional climate model (rCM) simulation based on the international Panel on Climate Change (iPCC) – synthesis report on emission scenarios (sres), a1B emission scenario (Nakićenović et al., 2000) from the enseMBLes project (http://ensembles-eu.metoffice.com; van der Linden and Mitchell 2009). the datasets were extracted over the european sector (27ºn – 72ºn, 22ºW – 45ºe) and were bilinearly interpolated from their original rotated grids to regular grids of 0.25º× 0.25º. Lastly, the grid-box over Lisbon was isolated. iV. resULts anD DisCUssiOn in summertime, 70 to 90% of the days are fit for outdoor recreation in Lisbon, if we assume type 8 as the sole weather type inadequate for tourism. even if we exclu de type 7 (extremely hot weather) from favourable types of weather, the frequency of occurrence of the types of weather 1 to 6 would always exceed 50%, varying from 51% to 81% (which means that 5 to 8 days out of 10 are suitable for visiting). type 7, classified by its excessive maximum air temperature or by a situation of extreme heat stress (PET ≥35ºC) reaches its highest frequency during August and the first ten days of september, precisely when the cities’ tourist occupation is at one of its highest points. We can distinguish three different regimes of weather-types in Lisbon: i) the two first decades of June, ii) the third decade of June, July and august and iii) september (particularly the last 20 days, although the first decade already shows some differences). i) in June, during the first ten-day interval, the frequency of cool days (type 4) is almost the same as hot, sultry days (type 3) but, as the month progresses, cool days become less and less frequent. the rate of unfavourable days (type 8) is supe rior to the one registered on the two months ahead, but inferior to september. Tourism and Climate in Lisbon 168 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga fig. 2 – summer weather type frequencies for 10-day periods in Lisbon (2000-2010). (coloured figure online) Fig. 2 – Frequência de ocorrência de tipos de tempo no Verão em Lisboa, em períodos de 10 dias (2000-2010). (versão a cores online) 169 ii) throughout July and august the weather type pattern is quite homo geneous. type 1 (very good, sunny weather) occurs in circa 30% of the cases (or more) and alternates with types 3 and 7 as the most frequent. Unfavourable weather occurs in less than 10% of the days. iii) in september there is a larger proportion of type 8 (unfavourable weathe r for tourism). in most cases, it is justified by the occurrence of precipitation (50%), by a particularly low number of sunshine hours (28%) or by nebulosity (18%). in september there is also a decline in the frequency of type 1, recording lower rates than in any of the other months but type 2 occurs more often than in the preceding months. fig. 3 – Proportion of favourable days (1-7 weather types) per ten-day interval, for each month. Fig. 3 – Proporção de dias favoráveis (tipos de tempo 1 a 7) por intervalos de dez dias, para cada mês. as can be verified in figure 3, whereas June, July and august are fairly r egular, the amount of favourable days in september can be quite diverse from year to year, usually declining as the month progresses, transitioning from summer to autumn. the existing ways of validating the climatic preferences of vacationers are: a) analysis of the relation between meteorological conditions and demand b ehaviour (revealed preference); b) conclusions deducted from surveys (stated Tourism and Climate in Lisbon 170 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga preferences). the second was used in this study. further, as it had been pre viously noted in the assessment of Catalonia by Gómez-Martín (2006) or in the assessmen t of rutty and scott (2014), there seems to be a discrepancy between visitation and thermal comfort – considering the frequency of extremely hot weather in July and august which, accor ding to the thermo-physiological indexes, would be unpleasan t. as justified by Gómez-Martín (2006) this discrepancy may have a number of explanations. On the one hand, climate is only one of the determinants for the period chosen for vacations. the climate experienced at the origin (B ecken, 2010) or the existence of other resour ces (heritage, sports, events and the like) are determinant for the demand. seasona lity depends as much on climate as on the work flexibility or school calendar. flight and room rates cannot be disregarded when analysing the demand pattern. there is also a distribution of the tourism demand throughout a big part of the year (excluding the period from november to february) that relates with a new trend in travelling: diversifying the number of short length journeys (during a long weekend) as tourists are no longer satisfied with a sole period of vacations or a single destination. this is easier nowadays thanks to lower air fares. notwithstanding the high tourist demand during periods where the occurrenc e of weather type 7 (Extremely hot weather) is frequent, we considered it as the least accep table weather type for tourism. although previous studies have registered air temperature preferences that would justify pushing it to the optimal air temperature spectrum (Martinez-ibarra and Gómez-Martín, 2012; rutty and scott, 2014) and, hence, classify it within weather types 1-3, those studies reflected preferences for beach tourism. We do not exclude the 3s (sun, sea, sand) tourism as possible in Lisbon (within the Metropolitan area there are several sea-side resorts) but it is not the primary motivation when travelling to Lisbon (Observatório do turismo de Lisboa, 2011). in order to understand thermal perceptions and behavioural responses we would need to question tourists and monitor their behaviour during days classified as weather type 7. temperature thresholds that were previously defined in the weather-type cata logue were crossed with projections of summer maximum and minimum daily temperatures for 2020 and 2050 (fig. 4), under a1b scenario, in order to verify whether climate would still be ideal in Lisbon during the summer months. Maximu m tempe ratures for the summer of 2020 are expected to be within the ideal range at all times projected (Nakićenović et al., 2000; van der Linden and Mitchell, 2009), whereas in 2050 some days are expected to be unacceptably hot (about 9% of the daily maximum temperatures during summer are expected to be >33ºC) and, of course, tempera ture has to be related with the other climate variables. nonetheless, we can see in figure 4 that the highest increase is related to a change in minimum temperatures, rather than in the maximum temperatures. P erhaps minimum temperatures should be included in future index formulation. 171 fig. 4 – Maximum and minimum daily temperatures projected for summers 2020 and 2050 (a1b scenario). Fig. 4 – Temperaturas mínimas e máximas diárias previstas para os Verões de 2020 e 2050 (cenário A1b). COnCLUsiOns the weather type model was selected and implemented to provide in a detailed temporal scale a comprehensive interpretation of the weather conditions experienced by tourists in Lisbon during the summer. several helpful factors contributed to the selection of this methodology, one of which was the integration of a thermo physiological index and the other the integration of tourist preferences in the definition of thresholds. Predominantly, we followed the ones defined for the weather type application to Catalonia (which were based on defined biometeorological ratings and tourists perceptions and preferences). However, the observed behaviour of tourists in Lisbon leads us to modify type 7, integrating an “Extremely hot weather” type. recurring to data from a first-order observatory (June-september, for the perio d 2000-2010), an analysis of the weather in the summer with this typology was performed. Crossing the data with hotel occupancy, results indicate that in september, despite the higher frequency of days classified as type 8 (unfavourable for tou rism), hotel occupation registered its highest rates. as previous studies had already refuted the validity of thermal comfort thresholds and ideal temperature ranges defined by experts, crossing our analysis with tourist demand also leads us to reinforce the question of whether the assumed widespread boundaries are adequate. assumed thermal comfort thresholds were on the basis of projections of the Mediterranean’s declining attractiveness. Tourism and Climate in Lisbon 172 R. Machete, A. Lopes, M. B. Gómez-Martín and H. Fraga as mentioned previously, comfort expectations are referred to by many authors as a decisive part of tourist thermal perceptions. therefore, further research is needed to understand what expectations tourists have when travelling to urban destinations in southern europe, which air temperature spectrum is perceived as optimal, which is considered tolerable and how are perceptions and preferences going to shape the responses of tourists to future climate scenarios. What is more, exposure to atmospheric conditions is lower in urban tourism than in beach tourism or nature tourism and unfavourable conditions can be easier to avoid by replacing outdoor activities for indoor activities, such as shopping, visiting museums/monuments, or dining (Lopes et al., 2011). applying the weather–type model to the future, through series of estimated temperature and precipitation, can provide information on the suitability of climate to tourism in the decades ahead. an analysis of simulated summer temperatures (a1b scenario) demonstrates that changes are more pronounced in minimum temperatures than in maximum temperatures (maximum temperatures are expected to exceed the optimal temperature threshold in august, but only in 2050, remaining ideal during the remaining summer months). nevertheless, just as important as real climate and weather, or even more, is the perception of climate and weather (Becken, 2010). further, when it comes to perceptions, the media have a very important role to play that can both stimulate, create or reduce interest in places and activities (Butler, 2011). it is thus of the greatest importance to make reliable climate information available for all participants in the tourism sector. aCKnOWLeDGeMents the project Urban Tourism and Climate Change (UrBan/aUr/0003/2008) was sponsored by the fundação para a Ciência e tecnologia (fCt); the Portuguese team was coordinated by the late Prof. Henrique andrade. raquel Machete would like to express her sincerest gratitude to Professor Henrique andrade for his intelectual guidance, training and for his friendship. 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