A33H-0278
Quantifying Amount and Variability of Cloud Water Inputs Using Active-Strand Collector, Ceilometer, Dewpoint, and Photographic Measurements

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Martha A Scholl1, Maoya Bassiouni2, Sheila F Murphy3, Grizelle Gonzalez4, Ashley E Van Beusekom4, Angel Torres-Sanchez5 and Carlos Estrada-Ruiz4, (1)U.S. Geological Survey, Reston, VA, United States, (2)USGS Pacific Islands Water Science, Honolulu, HI, United States, (3)USGS Central Region Offices Denver, Denver, CO, United States, (4)USDA Forest Service, International Institute of Tropical Forestry, San Juan, PR, United States, (5)US Geological Survey, Guaynabo, PR, United States
Abstract:
Cloud water associated with orographic processes contributes to soil moisture and streamflow, suppresses transpiration, and moderates drought in tropical mountain forests. It is difficult to quantify, yet may be vulnerable to changes in amount and frequency due to warming climate. Cloud immersion is characterized and monitored as part of the ecohydrology research of the USGS Water, Energy and Biogeochemical Budgets (WEBB) program and the Luquillo Critical Zone Observatory (CZO). Stable-isotope studies indicated cloud water may contribute significantly to headwater streamflow, and measurements with an active-strand collector yielded estimates of overnight cloud water deposition rates on Pico del Este (1050 m); but cloud liquid water content and spatial and temporal variability are not well understood. At five sites spanning the lifting condensation level to ridge-top (600-1000 m) in the Luquillo Mountains, cloud immersion conditions are monitored using time-lapse photography and temperature/ relative humidity (T/RH) sensors. A ceilometer, installed at 99 m on the windward slope on 4/29/2013, provides longer-term data to understand variation in cloud base altitude and to detect changes that may occur with warming climate. The cloud-zone sites range from tropical wet forest (mixed species) to rain forest (sierra palm) to elfin cloud forest. T/RH sensors indicated foggy conditions when temperature < dewpoint, but they are not sensitive to varying water content in the cloud. Images were processed to determine frequency and duration of immersion and estimates of optical density of cloud. Spatial heterogeneity in cloud immersion is assessed by comparing ceilometer measurements to the images. These complementary data sets provide quantification of spatial and temporal patterns of cloud immersion, and areal estimates of cloud water deposition will be made to determine importance in the water budget.