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Departamento De Física Tesis Doctoral
Departamento de Física Tesis Doctoral ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND AZORES Irene Peñate de la Rosa Las Palmas de Gran Canaria Noviembre de 2015 UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA Programa de doctorado Física Fundamental y Aplicada Departamento de Física ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND THE AZORES Tesis Doctoral presentada por D" Irene Peñate de la Rosa Dirigida por el Dr. D. Juan Manuel Martin González y Codirigida por el Dr. D. Germán Rodríguez Rodríguez El Director, El Codirector, La Doctoranda, (firma) (firma) (firma) \ Las Palmas de Gran Canaria, a 17 de noviembre de 2015 DEPARTAMENTO DE FÍSICA PROGRAMA DE DOCTORADO: FÍSICA FUNDAMENTAL Y APLICADA TESIS DOCTORAL ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND AZORES PRESENTADA POR: IRENE PEÑATE DE LA ROSA DIRIGA POR EL DR. D. JUAN MANUEL MARTÍN GONZÁLEZ CODIRIGIDA POR EL DR. D. GERMÁN RODRÍGUEZ RODRÍGUEZ LAS PALMAS DE GRAN CANARIA, 2015 Para Pedro y Ángela (mis padres), Andrés, Alejandra y Jorge Irene ACKNOWLEDGEMENTS This thesis has been carried out within the framework of a research collaboration between the Spanish Agency of Meteorology (AEMET) and the Bermuda Weather Service (BWS), such cooperative efforts have been very successful in accomplishing my meteorological training and research objectives. I would like to acknowledge the support to both institutions, especially to Mark Guishard (BWS) for his passionate discussions and by way of his outstanding knowledge about contemporary scientific theories relevant to tropical cyclone forecasting, including case studies of local events. -
Pico Island (Portugal) Heather As Much As Several Metres High
figs but has since been largely abandoned and is now extensively covered by vegetation, mainly clumps of Pico Island (Portugal) heather as much as several metres high. Within the nominated Criação Velha area, traditional wine- No 1117 Rev growing continues, producing a sweet, much-prized and once-widely exported desert wine called ‘Verdelho’. The nominated site consists of: 1. BASIC DATA Network of small walled fields State Party: Portugal Field shelters Rock tracks along shore and between the fields Name of property: Landscape of the Pico Island Vineyard Small ports & functional buildings Culture Tidal wells Location: Azores Houses, manor houses & churches Date received: 31 January 2002 Network of small walled fieldsThe most dramatic part of Category of property: this nomination is the intense network of small dry fields that intensively cover the strip of flat land along the coast. In terms of the categories of cultural property set out in Constructed from irregular weather-worn black basalt Article 1 of the 1972 World Heritage Convention, this is a stones, gathered on site, these tiny fields covered rocky site. In terms of Operational Guidelines paragraph 39, it is land of no use for arable cultivation. also a cultural landscape. The fields stretch in a largely geometrical network all over Brief description: the nominated site. They were constructed to shelter vines from sea breezes with walls around two metres high. Most Pico is a volcanic island lying among the archipelago of of the small fields are almost square. Groups of fields have the Azores, some 1500 km out into the Atlantic due west two types of patterns. -
Study on State Asset Management in the EU
Study on State asset management in the EU Final study report for Pillar 2 – Portugal Contract: ECFIN/187/2016/740792 Written by KPMG and Bocconi University February 2018 EUROPEAN COMMISSION Directorate-General for Economic and Financial Affairs Directorate Fiscal policy and policy mix and Directorate Investment, growth and structural reforms European Commission B-1049 Brussels 2 Portugal This Country fiche presents a quantitative overview of the mix of non-financial assets owned by the Portuguese General government. A recap and a summary table on sources of data and valuation methods used to map and assess (as far as possible) non-financial assets owned by the Portuguese General government is reported in the Appendix (Table C). 1. OVERVIEW OF NON-FINANCIAL ASSETS In 2015, the estimated value of Non-financial assets owned by the Portuguese General government was equal to 119.6 Eur Bn, accounting for about 82.9% of the estimated value of all assets (including Financial assets) owned by the General government1. Figure 1 General government’s Financial and Non-financial assets (Eur Bn), Portugal, 2015 Source: KPMG elaboration. Data on Gross Domestic Product were directly retrivied from Eurostat on 19th September 2017. (1) Estimated values refer to 2015 as the latest available year for both financial assets and all clusters of non-financial assets. (2) In this chart, the “estimated value” of financial assets is reported in terms of Total Assets of the country’s PSHs as weighted by the stake(s) owned by the Public sector into the PSHs themselves2. (3) Values of Dwellings, and Buildings other than dwellings were directly retrieved from Eurostat, while values for other Non-financial assets were estimated according to the valuation approaches explained in the Methodological Notes for Pillar 2. -
Aena Magazine Rich.Indd 11 21/5/07 18:15:12 12 347332392383475498774709909029989935499
An official report for the aviation community. 3 Contents P.4 Javier Marin Director of Spanish airports Madrid Barajas A national asset P.8 José Manuel Hesse The ‘architect’ of Plan Barajas Award-winning P.27 Architectural design Maria Dolores Izquierdo P.33 P.11 Retail – every case is different Plan Barcelona The engine of Catalonia Innovation in IT P.38 P.17 First-rate, in-house expertise The Malaga plan A benchmark for tourist airports A three-way partnership P.20 Air navigation, airlines and airports The Levante Plan P.41 Alicante and Valencia Security P.24First, last and always Canarias plan P.47 The lucky airports P.51 4 Madrid Barajas Spain’s window on the world Airport Business asked Aena’s director of Spanish airports Javier Marin to spell out the significance of Plan Barajas, including the award-winning Madrid Barajas Terminal 4. John Frank-Keyes reports. “ 5 adrid Barajas is absolutely vital for air transport in Spain because of its hub function. However, we faced significant capacity limitations, so these infrastructure developments were crucial – and not just for Madrid, but for Spain and indeed for Europe. We now have the capacity to move up from being Europe’s fifth-ranked airport, and indeed it is something we have been able to achieve as we are now fourth in the first quarter of 2007,” Marin replied. Previously, Barajas had hourly runway capacity of 78 movements per hour with passenger mgrowth of about 8% a year. “The full benefits of the new capacity have really been felt with the advent of the winter season when we have been able to offer 90 movements per hour. -
Evaluation of the Tourism Climate Index in the Canary Islands
sustainability Article Evaluation of the Tourism Climate Index in the Canary Islands Silvia Alonso-Pérez 1,*, Javier López-Solano 1,2, Lourdes Rodríguez-Mayor 3 and José Miguel Márquez-Martinón 1 1 School of Architecture, Universidad Europea de Canarias, 38300 La Orotava, Spain; [email protected] (J.L.-S.); [email protected] (J.M.M.-M.) 2 Centro de Investigación Atmosférica de Izaña, Agencia Estatal de Meteorología, 28071 Madrid, Spain 3 Independent Researcher, 28001 Madrid, Spain; [email protected] * Correspondence: [email protected] Abstract: In this study, we performed a diagnostic and evolutive analysis of the bioclimatology of the Canary Islands, an Atlantic archipelago where the climate itself is a main feature promoting tourism. Among all the tourist-climate indices described in the literature, we evaluated the most widely used, which is the Tourism Climate Index (TCI) proposed by Mieczkowski (1985). Monthly mean TCI time series were calculated using meteorological data from the Spanish State Meteorological Agency database and the European Climate Assessment and Dataset. Our results show TCI values greater than 50 during almost every month in the period 1950–2018, with mean values over the entire time series between 70 and 80. According to the TCI classification scheme, these values correspond to a very good thermal comfort along all of the period. Our results also point to spring as the season with the best TCI, with maximum values around 80 for this index in April—excellent according to the TCI classification. However, we did not find a correlation between inbound arrivals and the TCI index, which might point to a lack of information available to tourists. -
Annual Report 2010
2010 ANNUAL REPORT 2010 2010 ANNUAL REPORT 2. Annual Report 2010 Contents .3 CONTENTS 4. Ineco in figures 6. Internationalization and the new brand 8. Management team 10. Board of Directors 12. Our clients 14. Another step towards internationalization 22. Corporate information 24. Responsible management in times of crisis 26. Aula Carlos Roa, analysys and debate on transportation 28. Innovation as a driving force for modern times 32. A strong, well-prepared team 36. Areas of activity 38. Railways 52. Aeronautics 64. Roads 70. Intermodal 78. Annual accounts 80. Balance sheet 81. Income statement 82. Offices 4. Annual Report 2010 INECO IN FIGURES In 2010, Ineco achieved revenues of €266.4m for its business activities. This slight decrease in revenue is associated with an austerity plan, which has allowed us to adapt ourselves to the needs of our clients while still maintaining productivity at constant prices and achieving satisfactory results. The portfolio at year end reached €353.9m, a similar level to the previous year. TURNOVER CHANGES IN EARNINGS million EUR million EUR 2008 2008 276.3 37.7 2009 2009 285.4 28.7 2010 2010 266.4 16.2 CHANGES IN WORKFORCE PORTFOLIO BY SECTOR at December 31, 2010 in % / 2010 2008 Railways 2,879 80.9 58.3 2009 Aeronautics 3,126 11.8 19.4 2010 Roads 3,182 5.7 2.9 Consulting 1.6 19.4 National portfolio International portfolio Ineco in figures .5 266.4 REVENUE BY CLIENT Turnover million EUR (million EUR) Aena 62.6 Adif 141.4 Renfe Operadora 5.5 Ministry of Public Works 29.0 International 12.2 Other National 15.7 REVENUE BY SECTOR million EUR / at December 31, 2010 Railways 186.0 Aeronautics 61.2 Roads 9.0 Consulting 10.2 6. -
Evaluations of Cultural Properties
WHC-04/28COM/INF.14A UNESCO WORLD HERITAGE CONVENTION WORLD HERITAGE COMMITTEE 28th ordinary session (28 June – 7 July 2004) Suzhou (China) EVALUATIONS OF CULTURAL PROPERTIES Prepared by the International Council on Monuments and Sites (ICOMOS) The IUCN and ICOMOS evaluations are made available to members of the World Heritage Committee. A small number of additional copies are also available from the secretariat. Thank you 2004 WORLD HERITAGE LIST Nominations 2004 I NOMINATIONS OF MIXED PROPERTIES TO THE WORLD HERITAGE LIST A Europe – North America Extensions of properties inscribed on the World Heritage List United Kingdom – [N/C 387 bis] - St Kilda (Hirta) 1 B Latin America and the Caribbean New nominations Ecuador – [N/C 1124] - Cajas Lakes and the Ruins of Paredones 5 II NOMINATIONS OF CULTURAL PROPERTIES TO THE WORLD HERITAGE LIST A Africa New nominations Mali – [C 1139] - Tomb of Askia 9 Togo – [C 1140] - Koutammakou, the Land of the Batammariba 13 B Arab States New nominations Jordan – [C 1093] - Um er-Rasas (Kastron Mefa'a) 17 Properties deferred or referred back by previous sessions of the World Heritage Committee Morocco – [C 1058 rev] See addendum: - Portuguese City of El Jadida (Mazagan) WHC-04/28.COM/INF.15A Add C Asia – Pacific New nominations Australia – [C 1131] - Royal Exhibition Building and Carlton Gardens 19 China – [C 1135] - Capital Cities and Tombs of the Ancient Koguryo Kingdom 24 India – [C 1101] - Champaner-Pavagadh Archaeological Park 26 Iran – [C 1106] - Pasargadae (Pasargad) 30 Japan – [C 1142] - Sacred Sites -
Spain and Portugal Customized Tours | Eatour Specialist
Azores Islands of Sao Miguel Pico Terceira and Faial ☆ ☆ ☆ ☆ ☆ 0 User Reviews 11 Days / 10 Ponta Delgada On Request Nights Best Rate.00€ In the Açores Islands you will discover natural beauty at its best. On this trip you will visit 4 of the 9 islands. On each Island you with take a private tour and then have time on your own to explore the islands General Overview Country: Portugal Type: Package Region: Azores Islands Theme: Customized Tours and Trip Ideas City: Ponta Delgada Group Size: 1 - 6 People Duration: 11 Days / 10 Nights Price from: € Introduction In the Açores Islands you will discover natural beauty at its best. On this trip you will visit 4 of the 9 islands. On each Island you with take a private tour and then have time on your own to explore the islands as you please. If you like walking and hiking or even whale watching. You will enjoy this trip. Accommodations on this trip have been selected for their rural beauty and location for wandering the islands. Day by day itinerary DAY 1: LISBON - (FLY) PONTA DELGADA, SAO MIGUEL - VILA FRANCA DO CAMPO - Take a morning flight from Lisbon to Ponta Delgada Airport (PDL), Sao Miguel *not included - Upon arrival you will be met by a chauffeur who will transfer you to your accommodation - Check in accommodation - Rest of the day at your own leisure - Lunch & Dinner on your own - Overnight in Vila Franco do Campo DAY 2: VILA FRANCA DO CAMPO - EXPLORE SAO MIGUEL ISLAND - Breakfast - Day free to explore Sao Miguel Island on your own or choose from one of our privately guided tours (see -
Departamento De Física Tesis Doctoral ANALYSIS OF
Departamento de Física Tesis Doctoral ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND AZORES Irene Peñate de la Rosa Las Palmas de Gran Canaria Noviembre de 2015 UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA Programa de doctorado Física Fundamental y Aplicada Departamento de Física ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND THE AZORES Tesis Doctoral presentada por D" Irene Peñate de la Rosa Dirigida por el Dr. D. Juan Manuel Martin González y Codirigida por el Dr. D. Germán Rodríguez Rodríguez El Director, El Codirector, La Doctoranda, (firma) (firma) (firma) \ Las Palmas de Gran Canaria, a 17 de noviembre de 2015 DEPARTAMENTO DE FÍSICA PROGRAMA DE DOCTORADO: FÍSICA FUNDAMENTAL Y APLICADA TESIS DOCTORAL ANALYSIS OF THE RAINFALL VARIABILITY IN THE SUBTROPICAL NORTH ATLANTIC REGION: BERMUDA, CANARY ISLANDS, MADEIRA AND AZORES PRESENTADA POR: IRENE PEÑATE DE LA ROSA DIRIGA POR EL DR. D. JUAN MANUEL MARTÍN GONZÁLEZ CODIRIGIDA POR EL DR. D. GERMÁN RODRÍGUEZ RODRÍGUEZ LAS PALMAS DE GRAN CANARIA, 2015 Para Pedro y Ángela (mis padres), Andrés, Alejandra y Jorge Irene ACKNOWLEDGEMENTS This thesis has been carried out within the framework of a research collaboration between the Spanish Agency of Meteorology (AEMET) and the Bermuda Weather Service (BWS), such cooperative efforts have been very successful in accomplishing my meteorological training and research objectives. I would like to acknowledge the support to both institutions, especially to Mark Guishard (BWS) for his passionate discussions and by way of his outstanding knowledge about contemporary scientific theories relevant to tropical cyclone forecasting, including case studies of local events. -
KODY LOTNISK ICAO Niniejsze Zestawienie Zawiera 8372 Kody Lotnisk
KODY LOTNISK ICAO Niniejsze zestawienie zawiera 8372 kody lotnisk. Zestawienie uszeregowano: Kod ICAO = Nazwa portu lotniczego = Lokalizacja portu lotniczego AGAF=Afutara Airport=Afutara AGAR=Ulawa Airport=Arona, Ulawa Island AGAT=Uru Harbour=Atoifi, Malaita AGBA=Barakoma Airport=Barakoma AGBT=Batuna Airport=Batuna AGEV=Geva Airport=Geva AGGA=Auki Airport=Auki AGGB=Bellona/Anua Airport=Bellona/Anua AGGC=Choiseul Bay Airport=Choiseul Bay, Taro Island AGGD=Mbambanakira Airport=Mbambanakira AGGE=Balalae Airport=Shortland Island AGGF=Fera/Maringe Airport=Fera Island, Santa Isabel Island AGGG=Honiara FIR=Honiara, Guadalcanal AGGH=Honiara International Airport=Honiara, Guadalcanal AGGI=Babanakira Airport=Babanakira AGGJ=Avu Avu Airport=Avu Avu AGGK=Kirakira Airport=Kirakira AGGL=Santa Cruz/Graciosa Bay/Luova Airport=Santa Cruz/Graciosa Bay/Luova, Santa Cruz Island AGGM=Munda Airport=Munda, New Georgia Island AGGN=Nusatupe Airport=Gizo Island AGGO=Mono Airport=Mono Island AGGP=Marau Sound Airport=Marau Sound AGGQ=Ontong Java Airport=Ontong Java AGGR=Rennell/Tingoa Airport=Rennell/Tingoa, Rennell Island AGGS=Seghe Airport=Seghe AGGT=Santa Anna Airport=Santa Anna AGGU=Marau Airport=Marau AGGV=Suavanao Airport=Suavanao AGGY=Yandina Airport=Yandina AGIN=Isuna Heliport=Isuna AGKG=Kaghau Airport=Kaghau AGKU=Kukudu Airport=Kukudu AGOK=Gatokae Aerodrome=Gatokae AGRC=Ringi Cove Airport=Ringi Cove AGRM=Ramata Airport=Ramata ANYN=Nauru International Airport=Yaren (ICAO code formerly ANAU) AYBK=Buka Airport=Buka AYCH=Chimbu Airport=Kundiawa AYDU=Daru Airport=Daru -
Safetaxi Europe Coverage List – 21S5 Cycle
SafeTaxi Europe Coverage List – 21S5 Cycle Albania Identifier Aerodrome Name City Country LATI Tirana International Airport Tirana Albania Armenia Identifier Aerodrome Name City Country UDSG Shirak International Airport Gyumri Armenia UDYE Erebuni Airport Yerevan Armenia UDYZ Zvartnots International Airport Yerevan Armenia Armenia-Georgia Identifier Aerodrome Name City Country UGAM Ambrolauri Airport Ambrolauri Armenia-Georgia UGGT Telavi Airport Telavi Armenia-Georgia UGKO Kopitnari International Airport Kutaisi Armenia-Georgia UGSA Natakhtari Airport Natakhtari Armenia-Georgia UGSB Batumi International Airport Batumi Armenia-Georgia UGTB Tbilisi International Airport Tbilisi Armenia-Georgia Austria Identifier Aerodrome Name City Country LOAV Voslau Airport Voslau Austria LOLW Wels Airport Wels Austria LOWG Graz Airport Graz Austria LOWI Innsbruck Airport Innsbruck Austria LOWK Klagenfurt Airport Klagenfurt Austria LOWL Linz Airport Linz Austria LOWS Salzburg Airport Salzburg Austria LOWW Wien-Schwechat Airport Wien-Schwechat Austria LOWZ Zell Am See Airport Zell Am See Austria LOXT Brumowski Air Base Tulln Austria LOXZ Zeltweg Airport Zeltweg Austria Azerbaijan Identifier Aerodrome Name City Country UBBB Baku - Heydar Aliyev Airport Baku Azerbaijan UBBG Ganja Airport Ganja Azerbaijan UBBL Lenkoran Airport Lenkoran Azerbaijan UBBN Nakhchivan Airport Nakhchivan Azerbaijan UBBQ Gabala Airport Gabala Azerbaijan UBBY Zagatala Airport Zagatala Azerbaijan Belarus Identifier Aerodrome Name City Country UMBB Brest Airport Brest Belarus UMGG -
Numerical Methods for Spectral Clustering a Spectral Cluster Analysis of the European Air Traffic Network, Using Schur-Wielandt Deflation
DEGREE PROJECT IN TECHNOLOGY, FIRST CYCLE, 15 CREDITS STOCKHOLM, SWEDEN 2020 Numerical Methods for Spectral Clustering A Spectral Cluster analysis of the European Air Traffic Network, using Schur-Wielandt Deflation JOHAN LARSSON ISAK ÅGREN KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES Abstract The Aviation industry is important to the European economy and development, therefore a study of the sensitivity of the European flight network is interesting. If clusters exist within the network, that could indicate possible vulnerabilities or bottlenecks, since that would represent a group of airports poorly connected to other parts of the network. In this paper a cluster analysis using spectral clustering is performed with flight data from 34 different European countries. The report also looks at how to implement the spectral clustering algorithm for large data sets. After performing the spectral clustering it appears as if the European flight network is not clustered, and thus does not appear to be sensitive. Sammanfattning Flygindustrin ¨arviktig f¨orden europeiska ekonomin och utvecklingen, d¨arf¨or¨aren studie av k¨ansligheten f¨ordet europeiska flygn¨atetintressant. Om det finns kluster i n¨atverket kan det indikera m¨ojligas˚arbarhetereller flaskhalsar, eftersom det skulle representera en grupp flygplatser som ¨ard˚aligtanslutna till andra delar av n¨atver- ket. I denna rapport utf¨orsen klusteranalys med spektralklustering p˚aflygdata fr˚an 34 olika europeiska l¨ander.Rapporten tittar ocks˚ap˚ahur man implementerar spek- tralklustering f¨orstora datam¨angder.Efter att ha utf¨ortspektralklustering verkar det som om det europeiska flygn¨atverket inte ¨arklusterat och d¨arf¨orverkar det inte som att det ¨ark¨ansligt.