@InProceedings{DouglasMejiKill:2006:DeClCl,
               author = "Douglas, Michael W. and Mejia, John F. and Killeen, Timothy J.",
          affiliation = "National Severe Storms Laboratory/NOAA, Norman, Oklahoma USA 
                         (Douglas) and CIMMS/University of Oklahoma, Norman, Oklahoma, USA 
                         (Mejia) and Center for Applied Biodiversity Science at 
                         Conservation International, 1919 M Street NW, Washingtion DC 20036 
                         USA (Killeen) and {}",
                title = "Developing cloudiness climatologies from satellite imagery to map 
                         cloud forests and other vegetation features over the tropical 
                         Americas",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Vera, Carolina and Nobre, Carlos",
                pages = "1015--1020",
         organization = "International Conference on Southern Hemisphere Meteorology and 
                         Oceanography, 8. (ICSHMO).",
            publisher = "American Meteorological Society (AMS)",
              address = "45 Beacon Hill Road, Boston, MA, USA",
             keywords = "cloud forests, MODIS, GOES, cloudiness, vegetation.",
             abstract = "Cloud forests along the eastern slopes of the tropical Andes are 
                         associated with high cloudiness and high annual precipitation. 
                         These regions possess very high biodiversity and as such are a 
                         conservation priority. Detailed mapping of the cloud forests and 
                         adjacent environments is essential for aiding conservation 
                         strategies. Mapping is also important for studies that model 
                         biodiversity, for interpreting both past and future climatic 
                         scenarios, and for modeling the impact of climate change on the 
                         vegetation distribution and associated biodiversity. 
                         Unfortunately, mapping cloud forests is difficult. In general, 
                         rainfall data is quite limited in the cloud forest environment, 
                         since the eastern Andean slopes are sparsely populated and 
                         relatively few roads cross the zone. Precipitation analyses 
                         produced from the unevenly distributed station data do not reveal 
                         the detailed geography of the cloud forest vegetation. Our study 
                         has involved generating cloud climatologies from GOES and MODIS 
                         imagery to help determine potential cloud forest environments. 
                         MODIS imagery at 250m spatial scale provides a very high 
                         resolution look at the distribution of cloudiness and its 
                         relationship with topography, while GOES imagery at 1km and 4 km 
                         (IR) scale help to define the diurnal cycle of cloudiness. In 
                         addition to mean cloudiness patterns, we will also show the 
                         seasonal evolution of the cloudiness and some stratifications of 
                         cloudiness based on synoptic flow orientation. Limitations of our 
                         procedures in identifying cloud forests will also be discussed. 
                         Finally, some examples will be shown of the applicability of our 
                         techniques to other regions in the tropical Americas.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "24-28 Apr. 2006",
             language = "en",
         organisation = "American Meteorological Society (AMS)",
                  ibi = "cptec.inpe.br/adm_conf/2005/11.01.01.06",
                  url = "http://urlib.net/ibi/cptec.inpe.br/adm_conf/2005/11.01.01.06",
           targetfile = "1015-1020.pdf",
                 type = "Monsoon systems and continental rainfall",
        urlaccessdate = "12 maio 2024"
}