|Kabela, A - DOE|
|Hornbuckle, B - IOWA STATE UNIVERSITY|
|Gleason, M - IOWA STATE UNIVERSITY|
Submitted to: Specialist Meeting on Microwave Remote Sensing
Publication Type: Abstract Only
Publication Acceptance Date: August 30, 2008
Publication Date: October 20, 2008
Citation: Kabela, E., Hornbuckle, B.K., Cosh, M.H., Anderson, M.C., Gleason, M. 2008. Dew frequency, duration, amount, and distribution in corn soybean during SMEX05 [abstract]. International Workshop on Microwave Remote Sensing for Land Hydrology. 2008 CDROM. Technical Abstract: Dew affects the brightness temperature of vegetation and backscatter from vegetation at microwave wavelengths. Must this effect must be taken into account in order to avoid corrupting remotely-sensed observations of important ecosystem variables such as soil moisture? As a first step towards answering this question, we report the frequency and duration of dew events, the total amount of dew in the canopy, and the distribution of dew within the canopy for two different types of crop canopy, corn and soybean, during SMEX05, a twenty-one day field experiment conducted during June and July, 2005, in Iowa, USA. We observed dew to be present more than 50% of the time in both corn and soybean at common satellite overpass times of 1:30 and 6:00 CST. Dew was most likely to be present between 12:00 and 6:30 CST, and as late as 9:00 CST. Two different methods to scale the liquid water measured on single leaves to the entire vegetation canopy produced similar results, and we observed dew amounts that were comparable, and in some cases higher, than those that have been shown to affect the microwave brightness temperature and backscatter. The distribution of dew within the canopy among the top and bottom of a leaf and (for corn) the leaf collar may influence its effect on remotely-sensed measurements. We found that this distribution is different for light, moderate, and heavy dew events. A modeling approach will be necessary to estimate dew at larger spatial scales associated with satellite remote sensing. The Atmosphere-Land Exchange (ALEX) model, a land surface process model that accounts for both dewfall and distillation, produced estimates of dew amount and duration that were in agreement with manual observations and observations made with leaf wetness sensors.