Voices from Communities Affected by Climate Change
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Subtropical Storms in the South Atlantic Basin and Their Correlation with Australian East-Coast Cyclones
2B.5 SUBTROPICAL STORMS IN THE SOUTH ATLANTIC BASIN AND THEIR CORRELATION WITH AUSTRALIAN EAST-COAST CYCLONES Aviva J. Braun* The Pennsylvania State University, University Park, Pennsylvania 1. INTRODUCTION With the exception of warmer SST in the Tasman Sea region (0°−60°S, 25°E−170°W), the climate associated with South Atlantic ST In March 2004, a subtropical storm formed off is very similar to that associated with the coast of Brazil leading to the formation of Australian east-coast cyclones (ECC). A Hurricane Catarina. This was the first coastal mountain range lies along the east documented hurricane to ever occur in the coast of each continent: the Great Dividing South Atlantic basin. It is also the storm that Range in Australia (Fig. 1) and the Serra da has made us reconsider why tropical storms Mantiqueira in the Brazilian Highlands (Fig. 2). (TS) have never been observed in this basin The East Australia Current transports warm, although they regularly form in every other tropical water poleward in the Tasman Sea tropical ocean basin. In fact, every other basin predominantly through transient warm eddies in the world regularly sees tropical storms (Holland et al. 1987), providing a zonal except the South Atlantic. So why is the South temperature gradient important to creating a Atlantic so different? The latitudes in which TS baroclinic environment essential for ST would normally form is subject to 850-200 hPa formation. climatological shears that are far too strong for pure tropical storms (Pezza and Simmonds 2. METHODOLOGY 2006). However, subtropical storms (ST), as defined by Guishard (2006), can form in such a. -
FINAL REPORT Quantitative Instrument to Measure Commune
FINAL REPORT Quantitative Instrument to Measure Commune Effectiveness Prepared for United States Agency for International Development (USAID) Mali Mission, Democracy and Governance (DG) Team Prepared by Dr. Lynette Wood, Team Leader Leslie Fox, Senior Democracy and Governance Specialist ARD, Inc. 159 Bank Street, Third Floor Burlington, VT 05401 USA Telephone: (802) 658-3890 FAX: (802) 658-4247 in cooperation with Bakary Doumbia, Survey and Data Management Specialist InfoStat, Bamako, Mali under the USAID Broadening Access and Strengthening Input Market Systems (BASIS) indefinite quantity contract November 2000 Table of Contents ACRONYMS AND ABBREVIATIONS.......................................................................... i EXECUTIVE SUMMARY............................................................................................... ii 1 INDICATORS OF AN EFFECTIVE COMMUNE............................................... 1 1.1 THE DEMOCRATIC GOVERNANCE STRATEGIC OBJECTIVE..............................................1 1.2 THE EFFECTIVE COMMUNE: A DEVELOPMENT HYPOTHESIS..........................................2 1.2.1 The Development Problem: The Sound of One Hand Clapping ............................ 3 1.3 THE STRATEGIC GOAL – THE COMMUNE AS AN EFFECTIVE ARENA OF DEMOCRATIC LOCAL GOVERNANCE ............................................................................4 1.3.1 The Logic Underlying the Strategic Goal........................................................... 4 1.3.2 Illustrative Indicators: Measuring Performance at the -
Annuaire Statistique 2015 Du Secteur Développement Rural
MINISTERE DE L’AGRICULTURE REPUBLIQUE DU MALI ----------------- Un Peuple - Un But – Une Foi SECRETARIAT GENERAL ----------------- ----------------- CELLULE DE PLANIFICATION ET DE STATISTIQUE / SECTEUR DEVELOPPEMENT RURAL Annuaire Statistique 2015 du Secteur Développement Rural Juin 2016 1 LISTE DES TABLEAUX Tableau 1 : Répartition de la population par région selon le genre en 2015 ............................................................ 10 Tableau 2 : Population agricole par région selon le genre en 2015 ........................................................................ 10 Tableau 3 : Répartition de la Population agricole selon la situation de résidence par région en 2015 .............. 10 Tableau 4 : Répartition de la population agricole par tranche d'âge et par sexe en 2015 ................................. 11 Tableau 5 : Répartition de la population agricole par tranche d'âge et par Région en 2015 ...................................... 11 Tableau 6 : Population agricole par tranche d'âge et selon la situation de résidence en 2015 ............. 12 Tableau 7 : Pluviométrie décadaire enregistrée par station et par mois en 2015 ..................................................... 15 Tableau 8 : Pluviométrie décadaire enregistrée par station et par mois en 2015 (suite) ................................... 16 Tableau 9 : Pluviométrie enregistrée par mois 2015 ........................................................................................ 17 Tableau 10 : Pluviométrie enregistrée par station en 2015 et sa comparaison à -
Régions De SEGOU Et MOPTI République Du Mali P! !
Régions de SEGOU et MOPTI République du Mali P! ! Tin Aicha Minkiri Essakane TOMBOUCTOUC! Madiakoye o Carte de la ville de Ségou M'Bouna Bintagoungou Bourem-Inaly Adarmalane Toya ! Aglal Razelma Kel Tachaharte Hangabera Douekiré ! Hel Check Hamed Garbakoira Gargando Dangha Kanèye Kel Mahla P! Doukouria Tinguéréguif Gari Goundam Arham Kondi Kirchamba o Bourem Sidi Amar ! Lerneb ! Tienkour Chichane Ouest ! ! DiréP Berabiché Haib ! ! Peulguelgobe Daka Ali Tonka Tindirma Saréyamou Adiora Daka Salakoira Sonima Banikane ! ! Daka Fifo Tondidarou Ouro ! ! Foulanes NiafounkoéP! Tingoura ! Soumpi Bambara-Maoude Kel Hassia Saraferé Gossi ! Koumaïra ! Kanioumé Dianké ! Leré Ikawalatenes Kormou © OpenStreetMap (and) contributors, CC-BY-SA N'Gorkou N'Gouma Inadiatafane Sah ! ! Iforgas Mohamed MAURITANIE Diabata Ambiri-Habe ! Akotaf Oska Gathi-Loumo ! ! Agawelene ! ! ! ! Nourani Oullad Mellouk Guirel Boua Moussoulé ! Mame-Yadass ! Korientzé Samanko ! Fraction Lalladji P! Guidio-Saré Youwarou ! Diona ! N'Daki Tanal Gueneibé Nampala Hombori ! ! Sendegué Zoumané Banguita Kikara o ! ! Diaweli Dogo Kérengo ! P! ! Sabary Boré Nokara ! Deberé Dallah Boulel Boni Kérena Dialloubé Pétaka ! ! Rekerkaye DouentzaP! o Boumboum ! Borko Semmi Konna Togueré-Coumbé ! Dogani-Beré Dagabory ! Dianwely-Maoundé ! ! Boudjiguiré Tongo-Tongo ! Djoundjileré ! Akor ! Dioura Diamabacourou Dionki Boundou-Herou Mabrouck Kebé ! Kargue Dogofryba K12 Sokora Deh Sokolo Damada Berdosso Sampara Kendé ! Diabaly Kendié Mondoro-Habe Kobou Sougui Manaco Deguéré Guiré ! ! Kadial ! Diondori -
Chlorophyll Variations Over Coastal Area of China Due to Typhoon Rananim
Indian Journal of Geo Marine Sciences Vol. 47 (04), April, 2018, pp. 804-811 Chlorophyll variations over coastal area of China due to typhoon Rananim Gui Feng & M. V. Subrahmanyam* Department of Marine Science and Technology, Zhejiang Ocean University, Zhoushan, Zhejiang, China 316022 *[E.Mail [email protected]] Received 12 August 2016; revised 12 September 2016 Typhoon winds cause a disturbance over sea surface water in the right side of typhoon where divergence occurred, which leads to upwelling and chlorophyll maximum found after typhoon landfall. Ekman transport at the surface was computed during the typhoon period. Upwelling can be observed through lower SST and Ekman transport at the surface over the coast, and chlorophyll maximum found after typhoon landfall. This study also compared MODIS and SeaWiFS satellite data and also the chlorophyll maximum area. The chlorophyll area decreased 3% and 5.9% while typhoon passing and after landfall area increased 13% and 76% in SeaWiFS and MODIS data respectively. [Key words: chlorophyll, SST, upwelling, Ekman transport, MODIS, SeaWiFS] Introduction runoff, entrainment of riverine-mixing, Integrated Due to its unique and complex geographical Primary Production are also affected by typhoons environment, China becomes a country which has a when passing and landfall25,26,27,28&29. It is well known high frequency of natural disasters and severe that, ocean phytoplankton production (primate influence over coastal area. Since typhoon causes production) plays a considerable role in the severe damage, meteorologists and oceanographers ecosystem. Primary production can be indexed by have studied on the cause and influence of typhoon chlorophyll concentration. The spatial and temporal for a long time. -
Memoire Du Diplome D'etude Approfondie (Dea)
MINISTERE DE L’ENSEIGNEMENT REPUBLIQUE DU MALI SUPERIEUR ET DE LA RECHERCHE Un Peuple-Un But-Une Foi SCIENTIFIQUE INSTITUT SUPERIEUR DE FORMATION ET DE RECHERCHE APPLIQUEE (ISFRA) MEMOIRE DU DIPLOME D’ETUDE APPROFONDIE (DEA) Option : Population-Environnement, Gestion des Zones Humides et Développement Durable THEME : Analyse de l’évolution des pratiques de pêche dans la commune rurale de Zangasso, cercle de Koutiala au Mali Présenté par : Ousmane CISSE Président du Jury : Directeur de mémoire Pr Moussa KAREMBE, Pr Mahamane H. MAIGA, Professeur Professeur Titulaire à l’USTTB Titulaire à l’ISFRA Membres : Co-encadreur de mémoire Dr Hady DIALLO, Maître Dr Edmond TOTIN, Chercheur à Assistant L’ICRISAT Mahamane H. MAIGA, Professeur à l’ISFRA Date et Lieu de soutenance : Année universitaire 2016-2017 10/08/ 2017 à L’ISFRA Avant-propos ............................................................................................................................. V DEDICACE .............................................................................................................................. VI REMERCIEMENTS ............................................................................................................... VII LISTE DES TABLEAUX, DES CARTES, DES PHOTOS, ET DES FIGURES ................ VIII RESUME .................................................................................................................................. IX INTRODUCTION ..................................................................................................................... -
Air-Sea Interaction: Hurricane/Typhoon
Air-sea interaction: Hurricane/Typhoon ATM2106 Typhoon Haiyan, November 2013 Typhoon Vongfong, October 2014 https://youtu.be/WjxZd7fPSVI Movie from https://svs.gsfc.nasa.gov/12772 Hurricane • An intense storm of tropical origin • Winds exceeding 64 knots (74 mph, 119 km/h) Typhoon Cyclone Hurricane Tropical cyclone Hurricane structure Northern hemisphere (relatively) dry air eyewall 18 km Moist air Hurricane tour North Northern hemisphere eyewall West East N W E S South Hurricane Katrina over the Gulf of Mexico on August 28, 2005 Wind Precipitation rate 148 km/h Hurricane Formation • Hurricanes form over tropical waters where • The winds are light • The humidity is high • The surface temperature is warm (>26.5 ℃) • A convergence of the air and a force for the spin • Usually between 5° and 20° where f≠0 Sea surface temperature Number of storms Hurricane Formation • Conditions that prohibit the hurricane formation • Sinking air: near 20°, the air is open sinking associated with the subtropical high. • Strong upper-level winds: strong wind shear tends to disrupt organized convection and disperses heat and moisture. Hurricane Development 1. Sensible heat flux and latent heat release 2. Warmer T aloft near the cluster of thunderstorms 3. Pressure gradient forcing outward 4. A drop of the surface pressure from the warming and diverging the air in the small surface area. 5. The air begins to spin counterclockwise in the northern hemisphere and moves to the center 6. As the area of the circulation decreases, the wind speed increases. Hurricane Development • Hurricanes need energy to develop • Energy sources • Sensible heat from the ocean Q = ⇢ c c u (SST T ) S air p S 10 − air • Latent heat from condensation Q = ⇢ L c u (q⇤(SST) q ) L air e L 10 − air Hurricane Development Q = ⇢ c c u (SST T ) S air p S 10 − air Q = ⇢ L c u (q⇤(SST) q ) L air e L 10 − air • The warmer the water, the greater the transfer of sensible and latent heat into the air above • Greater wind speed promotes higher sensible and latent heat flux from the ocean to the atmosphere. -
White Papers
WHITE PAPERS - 13 - INCREASED SCIENTIFIC EVIDENCE FOR THE LINK OF CLIMATE CHANGE TO HURRICANE INTENSITY Christoph Bals Germanwatch ntil recently, most scientists would have said that there was no or no clear evidence that global warming has had any effect on the planet’s most powerful storms- dubbed hurricanes, typhoons, or cyclones depending on the ocean that spawns them. They would have argued that the changes of the past decade in U these metrics are not so large as to clearly indicate that anything is going on other than the multi-decadal variability that has been well documented since at least 1900 (Gray et al. 1997; Landsea et al. 1999; Goldenberg et al. 2001). 2005 a Turning Point of the Debate? 2005 might prove as a turning point of the debate. Two developments came accomponied. First, the two extreme hurricane years 2004 and 2005 increased attention of scientists: At the latest when Wilma's internal pressure hit 882 millibars, beating a record held by 1988's Gilbert, climatologists took notice. It was the first time a single season had produced four Category 5 hurricanes, the highest stage on the 5-step Saffir-Simpson scale of storm intensity. The 28 tropical storms and hurricanes, that the world faced in 2005, crushed the old mark of 21, set in 1933. Second, a number of new scientific studies provided much more support to the hypotheses by showing that „now ... a connection is emerging between warming oceans and severe tropical cyclones " (Kerr, 2005, 1807). Two papers published in Science and Nature in 2005 started a development described as “Birth for Hurricane Climatology” (Kerr, 2006) by identifying the impact of climate change on hurricane intensity, number and regional distribution. -
M600kv1905mlia1l-Mliadm22303-Sikasso.Pdf (Français)
! ! ! ! ! ! ! ! ! ! ! RÉGION DE SIKASSO - MALI ! ! Map No: MLIADM22303 N'Ga!ssola Yang!asso ! ! ! ! 8°0'W Keninkou 7°0'W Diaforongo 6°0'W 5°0'W Koulala Sourountouna Sanékuy Torodo Baraouéli Diéna ! ! ! Kazangasso ! Niamana Sobala Diéli ! N N ' Mandiakuy ' 0 0 ° ° 3 3 1 Bossofola Yéelekebougou ! 1 ! Kal!aké ! Tiémena Kéme!ni ! Sanando Niala Bla Kalifabougou ! ! Nafadie ! ! Dougouolo ! Karaba Kagoua ! Konobougou Falo Dioundiou Baoulé Diakourouna Nerissso ! ! ! Konkankan ! Diora Koulikoro Gouni S É G O U Somasso Samabogo ! RÉGINOég!ueNla DE SIKASSO P ! Waki 1 ! ! ! Negala Guinina Diaramana Kimparana Begu! ené ^ National Capital Route Pr!incipale ! ! Kambila Dio Gare Gouendo ! M!afouné ! Fana ! Diago ! Safo Talikourou P Chef-lieu Région Rou!te Secondaire Tingolé ! Nianaso! ! Koloni Dombila Kati Kérela Toko!unko ! ! Tienfala ! ! Debéla Baramana Chef-lieu Cercle Tertiary ! ! ! Toura-Kalanga Dialakorodji ! ! Marka-Coungo Kia ! ! ! Chef-lieu Commune FrDoonutibèarbeo Iungteorunationale ! ! ! Tyenfala Sountiani M'Pebougou Pegu!éna Fonfona ! ! Nangola ! ! Kore ! ! ! ! ! ! ! B!ongosso Moribila-Kagoua Kinikai Village Limite Région ! ! ! Toukoro M'Pessoba Zoumanabougou ^ Miéna Dogodouma ! ! Limite Cercle ! M'Pedougou Kenyebaoulé Aéroport ! ! Zan!soni 7 Gouala!bougou ! Wacoro N'Tagonasso ! ! ! M’Pessoba Ou!la ! Faya ! Tasso Fleuve Bamako Baramba ! Koumbia ! ! Sirababougou ! Zone Marécageuse ! Karagouana Mallé! Daboni ! Dandougou N'Tongo!losso ! Kouniana N'Pa!nafa Nien!esso Forêts Classées ! Ouenzzindougou ! K O U L I K O R O ! Bobola-Zangasso ! Lac Kolomosso ! Dorokouma ! Torosogoba Sinde ! 7 ! Bamana N'Tossoni Sorob!asso Djigo!uala Sirake!lé Mountougoula ! ! Ko!un Bele!koro ! Kiffosso 1 Beleko Soba Togobabougou Zangorola Cette carte a été réalisée selon le découpage adminisMtraotnift sd uM Maanldi iàn pgauretisr des ! ! Kon!ina ! Hamidou Goita Dioila ! Gouama Sogotila Famessasso Beledo!ugou ! données de la Direction Nationale des Collectivités Territoriales (DNCT). -
Metropolitanization and Forest Recovery in Santa Catarina, Southern Brazil: a Multiscale Analysis
Metropolitanization and forest recovery in Santa Catarina, southern Brazil: a multiscale analysis Sandra R. Baptista Postdoctoral Research Fellow The Earth Institute at Columbia University Center for International Earth Science Information Network (CIESIN) 2009 Latin American IALE Conference Landscape Ecology in Latin America: Challenges and Perspectives Ecologia de Paisagens na América Latina: Desafios e Perspectivas Symp. 13 – Landscape change and forest transition theory: towards a multiscale approach October 4-7, 2009 Campos do Jordão, São Paulo, Brazil Introduction A multiscale analysis of anthropogenic landscape dynamics in the Florianópolis city-region, Santa Catarina, Brazil Anthropogenic Landscape Heterogeneity Human modification of landscapes and ecosystems within the city-region Photos by S. Baptista http://sedac.ciesin.columbia.edu/gpw/ Gridded Population of the World, version 3 (GPWv3) and the Global Rural- Urban Mapping Project (GRUMP) are the latest developments in the rendering of human populations in a common geo-referenced framework, produced by the Center for International Earth Science Information Network (CIESIN) of the Earth Institute at Columbia University. Atlantic Forest remnants in Brazil, Santa Catarina, and the Florianópolis Metro Region in 2005 Source: Adapted and translated from maps available online from Fundação SOS Mata Atlântica, URL: http://www.sosma.org.br Percent forest cover in Santa Catarina’s 293 municipalities, 2005 Remote sensing data reported by Fundação SOS Mata Atlântica and INPE Florianópolis -
Catarina Sobre a Região Sul Catarinense: Monitoramento E Avaliação Pós-Desastre
IMPACTO DO FURACÃO CATARINA SOBRE A REGIÃO SUL CATARINENSE: MONITORAMENTO E AVALIAÇÃO PÓS-DESASTRE Emerson Vieira MARCELINO1 Frederico de Moraes RUDORFF1 Isabela Pena Viana de Oliveira MARCELINO1 Roberto Fabris GOERL1 Masato KOBIYAMA1 Resumo O presente artigo teve como objetivo identificar as principais características do Furacão Catarina; levantar e analisar os danos e prejuízos; elaborar o mapa de inten- sidade dos danos; e classificar a intensidade do fenômeno. O monitoramento “in loco” foi realizado durante a passagem do fenômeno em Balneário Arroio do Silva. Foram visitados 22 municípios catarinenses, cobrindo um percurso de mais de 3.000 km, e aplicados 161 questionários. O mapa de intensidade foi elaborado a partir da interpolação de 260 pontos de GPS classificados de acordo com o grau de destruição. Os municípios mais afetados foram Passo de Torres, Balneário Gaivota e Balneário Arroio do Silva, todos localizados no litoral, onde milhares de edificações foram danificadas (53.728) e destruídas (2.194). As edificações menos resistentes aos ventos foram as casas de madeira pré-fabricadas e as casas de tijolos (sem vigas e colunas), cobertas com telhas de cimento-amianto. Conforme o furacão se deslocou em direção ao interior sua inten- sidade diminuiu, mostrando um padrão de destruição radial. Baseado nos ventos esti- mados “in loco” e na intensidade dos danos observados na área de impacto do furacão, a intensidade do Catarina pode ser classificado como a de um furacão classe 2 de acordo com a escala Saffir-Simpson. Palavras-chave: Furacão Catarina; monitoramento; avaliação pós-desastre. Abstract Impact of Hurricane Catarina over the southern region of Santa Catarina State (Brazil): monitoring and post-disaster assessment The objectives of this work were to identify the main characteristics of the Hurricane Catarina; to survey and analyze the damages and losses; to elaborate a damage intensity map; and to classify the hurricane’s intensity. -
Global Warming and Natural Disasters
Global Warming and Natural Disasters Prof. Dr. Peter Hoeppe Geo Risks Research Munich Reinsurance Company Geo Risks Research Department of Munich Re - Analyses of natural disasters since 1974 2 GEO-Colleagues in Princeton 2 GEO-Colleagues in Hongkong Major natural disasters of the last few years The last years have brought records in natural disasters in respect to: § Intensities § Frequencies § Damages and losses Dresden, August 2002 Economic losses of total event: €16 bn Insured losses: € 3.4 bn © REUTERS Heat wave of 2003, the largest humanitarian natural catastrophe in Europe for centuries Perceived Temperature on 8 August 2003 and excess mortality Source: German Weather Service, 2004 Heat stress 2,000 extreme † high 2,000 7,000 moderate † † light comfortable 15,000 light moderate † high extreme 4,000 Cold stress † 4,000 † UTC 13:00 Record Hurricane Season 2004 in the Caribbean and Florida Overview of the four Wind speed in hurricanes in 2004 gusts (km/h) causing the greatest losses Loss balance, total of all 4: Total economic loss: US$62 bn Insured market loss: US$31.5 bn 2004: 1st Hurricane in South Atlantic Hurricane Catarina off the Coast of Brasil, March 2004 Source: Image courtesy of Earth Sciences and Image Analysis Laboratory, NASA Johnson Space Center, Bild-Nummer ISS008-E-19646. http://eol.jsc.nasa.gov July/August 2005 – Flooding in India 944 mm within 24 hours, highest ever in India source: Reuters 24.7- 5.8 Flooding in India (1.150 fatalities) Economic losses (US$ m): 5.000 Insured losses (US$ m): 770 August 2005 – Flooding