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Biogeography of Cloud Forests:  Use of satellite data and numerical modeling

Udaysankar S. Nair 1 , Robert O. Lawton 2 , Ron Welch 3 , Qingyuan Han 3 , Jian Zeng 3 , Deepak Ray 3 , Salvi Asefi 3 1 Earth System Science Center, University of Alabama in Huntsville 2 Department of Biological Science, University of Alabama in Huntsville

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Biogeography of Cloud Forests:  Use of satellite data and numerical modeling

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  1. Udaysankar S. Nair1, Robert O. Lawton2, Ron Welch3, Qingyuan Han3, Jian Zeng3, Deepak Ray3, Salvi Asefi3 1 Earth System Science Center, University of Alabama in Huntsville 2 Department of Biological Science, University of Alabama in Huntsville 3 Department of Atmospheric Science, University of Alabama in Huntsville Biogeography of Cloud Forests:  Use of satellite data and numerical modeling

  2. Predictable, frequent and prolonged immersion in orographic clouds. Altitude range 1500 -3500m, coastal areas descends to 1000-300m Tropical montane cloud forests

  3. Cloud forest locations Hamilton et. al., 1996

  4. TMCFs are located within biological hotspots that support about 20% and 16% of plants and vertebrates Retains less than 25% of their original primary vegetation cover Ecological importance of TMCF Myers et. al., 2000

  5. Direct interception of liquid water from orographic clouds by vegetation “Horizontal precipitation” can account for up to 14 – 18 % and 15% - 100% of total precipitation during wet and dry season respectively Hydrological importance

  6. Rain: 4310 mm Horizontal: 3560 mm 1500 m 3600 3100 Rain: 6390 mm Horizontal: 350 mm 2600 1320 m Rain: 4590 mm Horizontal: 240 mm 1200 m 2100 1600 1100 600 Caribbean 100 0 Hydrological importance

  7. Mosses and ferns acts as capacitors, modulating runoff Hydrological importance

  8. TMCFs are fragile ecological hotspots that require specialized conservation management TMCFs are water resources with potential to affect agriculture, water distribution and power generation Characterization of TMCFs are essential for understanding ecology Upscaling of cloud forest hydrology and ecology Why map TMCFs?

  9. Current state of cloud forest mapping • “Version 1”, International TMCF Symposium, 1990, TMCF researchers pointing out locations on a map.

  10. Current state of cloud forest mapping • “Version 2”, Cloud Forest Agenda, based on DEM and “expert testimony” • Review of literature • Information on particular study sites dictated the mapping at the regional scale • EW volcanic chain in Mexico, has pine oak forest in the west, misclassified as cloud forest

  11. 10 30 50 70 90 Current state of cloud forest mapping

  12. “Version 3” Mapping of cloud forests using remotely sensed data • Satellite used to quantify frequency of cloud immersion • Detect cloud using automated cloud masking algorithms • Estimate cloud base height from remotely sensed cloud top pressure, liquid water path

  13. Cloud top height Cloud top pressure Optical depth Effective radius Temperature profile Assumptions Cloud Thickness Estimation of cloud base height from satellite imagery MODIS

  14. Study Area and Data Sources • March 2003, Study region centered in Monteverde, Costa Rica. • MODIS Terra data: Cloud optical properties retrieved from level-1B, Level-2 cloud top pressure,and atmospheric thermodynamic profiles

  15. Study Area and Data Sources • Land Use Cloud Interaction Experiment (LUCIE): Dual mobile radiosondes launched every 3 hours during the day and photographs taken at 6:00 am and 12:00 pm local time

  16. Study Area and Data Sources • Photographic observations of cloud base height

  17. Goals for the first year • Validate cloud base height estimation algorithms - How often can this technique be used - Check validity of different assumptions - Determine sources of errors - Compare against ground based observations • Explore other techniques for estimating cloud base height - Use Lifting Condensation Level (LCL) from global and regional models as a surrogate for cloud base height?

  18. How often can cloud base be estimated?

  19. Interior Is the effective radius constant? Edge

  20. Is the constant liquid water content assumption valid?

  21. Cloud top height determined using MODIS profile

  22. Comparison of MODIS pressure level heights against LUCIE observations

  23. Comparison of MODIS thermodynamic profiles against LUCIE observations

  24. Cloud base determined using MODIS profile, compared to photo observations

  25. Comparison of cloud base heights, estimated using temperature profile from the MODIS and RAMS model

  26. Cloud base height estimates from other sources?

  27. Combination of satellite and model?

  28. During dry season cloud base height may be estimated using MODIS data more that 50 % of the time. Constant effective radius assumption may be valid for orographic clouds Use of MODIS temperature profiles for estimating cloud top height result in significant errors. Remedied using temperature profiles from numerical models With corrections, RMS errors of 200-300m is encountered in cloud base height estimations. Conclusions

  29. Combining frequency of occurrence of clouds derived from satellite data with cloud base height information from numerical models appears to be the most promising approach Conclusions

  30. Further validation! Create detailed TMCF maps for two regions, Costa Rica and Hawaii, using different techniques Evaluation of the product by regional experts Future work

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