Validation of a Commercial System for Remote Estimation of Wetness Duration

Abstract

To assess the accuracy of remote, real-time mathematical simulations of wetness duration and air temperature, hourly measurements of wetness duration and air temperature at 18 sites in the United States and Canada from May to September 1995 were compared with simulations for these sites provided by SkyBit, Inc. SkyBit simulations of mean, maximum, and minimum daily air temperatures varied from on-site measurements by less than 0.7°C but underestimated the duration of wet periods by an average of 3.4 h/day. At five of six stations tested, SkyBit underestimates of wetness duration were significantly (P < 0.01) larger on days when no rain was measured than on rainy days, indicating that simulations of dew-period duration were much less accurate than simulations of rain-period duration. The vast majority of hours SkyBit misclassified as dry occurred either when entire wet periods were missed (59.3%) or when the onset of a wet period was detected late (28.4%). The results suggest that revision of SkyBit wetness-simulation models should focus on reducing error rates during dew events. In simulations using two disease-warning models, TOM-CAST and Melcast, with mean values of measured and SkyBit-simulated wetness duration, SkyBit-simulated values resulted in fewer and later fungicide spray advisories than did measured values. The magnitude of these impacts varied with the magnitude of the simulation errors and with differences in the models' decision rules.

Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study

“…An assessment of SkyBit estimates for sites in the Midwest U.S. found that estimation error was less for temperature than for LWD (Gleason et al, 1997). Similarly, for the western U.S. site-specific estimation network, Thomas et al (2002) noted that station-to-station data correlation was highest for temperature, intermediate for RH and dew point, and lowest for LWD.…”

Impacts on Plant Pathogens

“…Duration of surface wetness and relative humidity, which critically infl uence infection and disease development by many plant pathogens, have not been easily obtained from GCM output until recently. Usefulness of remotely gathered site-specifi c wetness and other data for plant pathology research has been variable (Gleason et al 1997 ), andSeem et al ( 2000 ) provide a more detailed discussion on this topic.…”

Remote sensing and interpolation methods can obtain weather data for disease prediction

“…Spatial interpolation approaches can be applied to weather data at different temporal scales including hourly, daily and with 30-year average data. The hourly and daily estimates of weather data are suitable for daily disease risk warnings (Gleason et al 1997). On the other hand, the long-term weather data are useful for identifying areas where the climate conditions are favourable for a certain disease, e.g.…”

“…Satellites can be used to obtain weather data for variables that are rarely measured at local weather stations. For example, leaf wetness duration is rarely measured at AWSs although is an important variable in the development of many fungal diseases (Gleason et al 1997). Satellite data can also be used to detect free water on crop surfaces.…”