The performance characteristics of some of meteorological sensors utilized in the EMESH nodes do not meet the requirement prescribed by WMO. For example, accuracy of EMESH temperature and humidity sensors are 0.3K and 2% compared to WMO specifications of 0.1K and 1% for similar operating ranges. Despite the slightly inferior performance compared to required specifications, the EMESH nodes can be effectively utilized for research and applied use. When utilized in a high density network, these sensor nodes can be used in studies that focus on phenomena characterized by magnitudes of variability in meteorological fields that exceed these uncertainties. Another strategy is to utilize assimilation of observations into numerical models, which specifically accounts for observational uncertainties. The intended applications of EMESH include monitoring of mesoscale circulations induced by surface heterogeneities such as terrain, land-water boundaries and land cover heterogeneities (e.g. urban heat island). A dense network of EMESH stations, configured to detect particulates and traces gases, could be of utility for air pollution studies – for example monitoring of prescribed burns.
Recently, seventy five EMSESH nodes were deployed during the Great Plains Irrigation Experiment (GRAINEX), conducted over the twelve county region surrounding Lincoln, NE during the summer of 2018. The study domain straddles the boundary between irrigated and non-irrigated agricultural regions. The goal of GRAINEX was to study the impact of irrigation on land-atmosphere interactions in the study area. The high density EMESH network complemented the high quality observations collected by the NCAR Earth Observing Laboratory (two Integrated Sounding Systems and twelve Integrated Surface Flux Systems) and three Doppler on Wheels systems deployed by the Center for Severe Weather Research. The data collected using EMESH will be utilized to characterize heterogeneity of surface meteorological variables resulting from irrigation including mesoscale circulation features induced by such heterogeneities. Observations will also be assimilated in numerical model simulation case studies to better characterize the effects of land surface heterogeneity. Problems encountered and lessons learned from the deployment of the EMESH sensor network during this field experiment, and preliminary findings will be presented.