Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Sensible heat flux is a component of the earth’s surface energy balance. It describes turbulent heat exchange between the land surface and the atmosphere and is of interest and importance for agriculture, urban heat budgets, and for understanding consequences of climate change. The sensible heat flux is typically computed using costly eddy covariance measurements, limiting the spatial coverage to a very coarse observational grid. We implement the flux variance method based on convective scaling as an alternative approach. While flux variance has a few limitations and constraints it is an interesting and competitive method for low-cost and power limited wireless sensor networks. These have the potential of providing sensible heat flux over the domain of a much denser network both resolving spatial variability and improving overall representativeness. We propose this method and sensor for implementation as part of a Citizen Observatory, for instance in monitoring networks operated by authorities or amateur scientists. The applicability of the flux variance method for use in wireless sensor networks has been explored in a case study field experiment where the low-cost sensors were tested and compared against reference instruments to evaluate the performance and limitations of these sensors as well as the method with respect to the standard calculations. Comparison experiments were carried out at several sites of different surface types (gravel, grass, water) to gauge the low-cost sensor systems.