Abstract:

Carbon cycling is driven by plant biological activity (root respiration, photosynthesis, respiration due to decay), climatic and meteorological factors (pressure, precipitation, ambient air temperature), and the interaction of these two sets of variables. However, ecology research field stations can have data gaps due to equipment failures or human interference (thieves or trespassers). For example, the Sky Oaks Field Station in Warner Springs, CA has sensors for barometric pressure, temperature, relative humidity, wind speed, and direction, as well as atmospheric carbon cycling data. This NERTO internship was to develop a Linear Mixed Effects Model for the interpolation of missing barometric pressure and ambient air temperature values at the Sky Oaks Field Station (Warner Springs, CA) based on METAR data from the National Weather Service stations surrounding the Sky Oaks Field Station as archived from the Iowa State University’s data hub, Iowa Environmental Mesonet. This inverse distance weighting (IDW) interpolation method used geographic data from the United States Geological Survey 3DElevation Program, which improved model accuracy. In addition, one of the Eddy Covariance Towers at the Sky Oaks Field Station was restored to collect gas flux and meteorological data. The Linear Mixed Effects Model produced for barometric pressure was overall highly significant (p=0.007503), but the model’s mean absolute error needs improvement, as it is above the acceptable value of 1 millibar (1.21 millibar). The Linear Mixed Model for the Sky Oaks Field Station temperature failed to find significant correlations between the Sky Oaks Field Station measurements, and its mean absolute error was 2.60 F(1.44 C)