Real-time parameter estimation of dynamic temperature and humidity models for greenhouse adaptive climate control

A real-time parameter estimator for the climate discrete-time dynamic models of a greenhouse located at the North of Portugal are presented. The experiments showed that the second order models identified for the air temperature and humidity achieve a close agreement between simulated and experimantal data.

An evaluation of the accuracy of models for the determination of the weighted mean temperature of the atmosphere

The estimates of the zenith wet delay resulting from the analysis of data from space techniques, such as GPS and VLBI, have a strong potential in climate modeling and weather forecast applications. In order to be useful to meteorology, these estimates have to be converted to precipitable water vapor, a process that requires the knowledge of the weighted mean temperature of the atmosphere, which varies both in space and time. In recent years, several models have been proposed to predict this quantity. Using a database of mean temperature values obtained by ray-tracing radiosonde profiles of more than 100 stations covering the globe, and about 2.5 year’s worth of data, we have analyzed several of these models. Based on data from the European region, we have concluded that the models provide identical levels of precision, but different levels of accuracy. Our results indicate that regionally-optimized models do not provide superior performance compared to the global models.