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Biogeography of Tropical Montane Cloud Forests. Part II: Mapping of Orographic Cloud Immersion

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  • * Earth System Science Center, National Space Science and Technology Center, The University of Alabama in Huntsville, Huntsville, Alabama
  • | + Department of Atmospheric Sciences, The University of Alabama in Huntsville, Huntsville, Alabama
  • | # Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana
  • | @ Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, Alabama
  • | 5 Environmental Monitoring and Modelling Research Group, Department of Geography, King’s College London, London, United Kingdom
  • | * *Marshall Space Flight Center, Huntsville, Alabama
  • | ++ Monteverde Cloud Forest Preserve, Monteverde, Costa Rica
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Abstract

This study details two unique methods to quantify cloud-immersion statistics for tropical montane cloud forests (TMCFs). The first technique uses a new algorithm for determining cloud-base height using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products, and the second method uses numerical atmospheric simulation along with geostationary satellite data. Cloud-immersion statistics are determined using MODIS data for March 2003 over the study region consisting of Costa Rica, southern Nicaragua, and northern Panama. Comparison with known locations of cloud forests in northern Costa Rica shows that the MODIS-derived cloud-immersion maps successfully identify known cloud-forest locations in the United Nations Environment Programme (UNEP) World Conservation Monitoring Centre (WCMC) database. Large connected regions of cloud immersion are observed in regions in which the trade wind flow is directly impinging upon the mountain slopes; in areas in which the flow is parallel to the slopes, a fractured spatial distribution of TMCFs is observed. Comparisons of the MODIS-derived cloud-immersion map with the model output show that the MODIS product successfully captures the important cloud-immersion patterns in the Monteverde region of Costa Rica. The areal extent of cloud immersion is at a maximum during morning hours and at a minimum during the afternoon, before increasing again in the evening. Cloud-immersion frequencies generally increase with increasing elevation and tend to be higher on the Caribbean Sea side of the mountains. This study shows that the MODIS data may be used successfully to map the biogeography of cloud forests and to quantify cloud immersion over cloud-forest locations.

Corresponding author address: Udaysankar S. Nair, Earth System Science Center, National Space Science and Technology Center, The University of Alabama in Huntsville, Huntsville, AL 35806. Email: nair@nsstc.uah.edu

Abstract

This study details two unique methods to quantify cloud-immersion statistics for tropical montane cloud forests (TMCFs). The first technique uses a new algorithm for determining cloud-base height using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products, and the second method uses numerical atmospheric simulation along with geostationary satellite data. Cloud-immersion statistics are determined using MODIS data for March 2003 over the study region consisting of Costa Rica, southern Nicaragua, and northern Panama. Comparison with known locations of cloud forests in northern Costa Rica shows that the MODIS-derived cloud-immersion maps successfully identify known cloud-forest locations in the United Nations Environment Programme (UNEP) World Conservation Monitoring Centre (WCMC) database. Large connected regions of cloud immersion are observed in regions in which the trade wind flow is directly impinging upon the mountain slopes; in areas in which the flow is parallel to the slopes, a fractured spatial distribution of TMCFs is observed. Comparisons of the MODIS-derived cloud-immersion map with the model output show that the MODIS product successfully captures the important cloud-immersion patterns in the Monteverde region of Costa Rica. The areal extent of cloud immersion is at a maximum during morning hours and at a minimum during the afternoon, before increasing again in the evening. Cloud-immersion frequencies generally increase with increasing elevation and tend to be higher on the Caribbean Sea side of the mountains. This study shows that the MODIS data may be used successfully to map the biogeography of cloud forests and to quantify cloud immersion over cloud-forest locations.

Corresponding author address: Udaysankar S. Nair, Earth System Science Center, National Space Science and Technology Center, The University of Alabama in Huntsville, Huntsville, AL 35806. Email: nair@nsstc.uah.edu

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