OPS 2-10
NEON's first light: Uncertainty results for initial data streams
The National Ecological Observatory Network (NEON) is a continental-scale research platform with a projected lifetime of 30 years. NEON’s purpose is to provide high quality data products that will facilitate discovering and understanding the impacts of climate change, land-use change, and invasive species on ecology. To accomplish this, NEON will perform in-situ, sensor-based measurements of approximately 55,000 high-quality data streams and generate uncertainty estimates. Only when uncertainty is sufficiently quantified can meaningful interpretations be made about mean quantities and their interrelations, thus allowing for applied computations such as constructing or constraining process-based models.
Starting the second half of 2013, NEON’s first data streams (i.e., air temperature, PAR, and barometric pressure) are being measured. Uncertainty analyses for individual and temporally averaged measurements are computed for these streams and expanded uncertainty values are disseminated alongside the data. Since then other variables (e.g., 2D wind, biological temperature, etc.) have followed suit; here, preliminary uncertainty results for these measurement streams are outlined.
Results/Conclusions
In several cases NEON’s measurements can provide unprecedented repeatability (precision) and trueness (accuracy). This is a direct result of NEON’s effort to follow calibration, validation and audit procedures that are traceable to national and international standards (e.g., NIST & ISO). For example, the quantifiable repeatability of NEON’s air temperature measurements is < ± 0.002⁰C, with an overall expanded uncertainty < ± 0.05⁰C. One caveat, however, are identifiable though not currently quantifiable uncertainties exist. For many in-situ, sensor based measurements this includes drifts by the sensor itself as well as the data acquisition system. For air temperature measurements, additional errors can originate from varying insolation and aspiration in the radiation shield.
Meaningful interpretations of temporally averaged data products rely on accurate estimates of individual measurement uncertainties. This is because the standard error of temporally averaged data products comprises measurement assembly repeatability and environmental variations. The goal then is to discern between the two, as this will allow quantifying signal-noise ratios, sensor drift, and allow the plausibility of NEON’s sampling rates to be assessed. Ultimately, this will enable the scientific community to improve inferences between environmental drivers and responses using NEON data, such as site-specific meteorological-ecological interactions.