JP1.15
Biogeography of cloud forests: Use of satellite remote sensing and numerical modeling

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Tuesday, 31 January 2006
Biogeography of cloud forests: Use of satellite remote sensing and numerical modeling
Exhibit Hall A2 (Georgia World Congress Center)
U. S. Nair, University of Alabama, Huntsville, AL; and D. K. Ray, S. Asefi, R. M. Welch, and R. O. Lawton

Cloud forests, characterized by frequent, prolonged immersion in orographic clouds lie at the core of biological hot spots distributed around the globe.  Cloud forest ecosystems derive a significant amount of their moisture input from direct harvesting of cloud water by the vegetation.  In addition their ecological importance of supporting biodiversity, they are also important to local hydrology since the direct capture of cloud water contributes significantly to stream flow.  Due to their ecological and hydrological importance there is a considerable interest in understanding not only the geographical distribution of the cloud forest ecosystems and also in quantifying the cloud immersion experienced by these ecosystems. This study examines the use of cloud base height estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) data in conjunction with high resolution topography to determine the frequency of cloud immersion over Monteverde, Costa Rica.  Comparison of MODIS retrieved cloud base heights against ground based observations suggests that it is possible to retrieve cloud base height with accuracies of approximately 200m.  However, since MODIS is on polar orbiting platform, it is not possible to determine diurnal variations from this data.  However, cloudiness information derived from Geostationary Operational Environmental Satellite (GOES) may potentially be combined with cloud base heights or Lifting Condensation Level (LCL), a proxy to cloud base height, derived from numerical model outputs.  Cloud immersion frequency derived using this technique was evaluated by field ecologists and it was found to be in good qualitative agreement with conditions experienced at the ground.  Spatial distribution of cloud immersion frequency derived from MODIS is currently being compared to that derived using the combination of GOES and numerical model output and the results from this comparison will be presented at the talk.