Near Real Time Data
Access Near-Real-Time (NRT) Eddy-Covariance (EC) data has become important to improve model data fusion (MDF) processing and in particular land surface model (LSM) which simulate terrestrial biosphere exchanges of matter and energy.
As known and unfortunately, EC flux data are noisy and potentially biased.
This means that each calculated flux contains the “true” value plus both systematic and random errors, which represent the total uncertainties resulting from sample measurements and also from processing options.
Because uncertainties enter directly into MDF, misspecification of this quantity affects parameter estimates and propagates into the model predictions.