When researchers talk about ‘missing data,’ they are referring to replacing previously estimated values with actual, real values in various explanatory models. This can be particularly important in climate change models. Even though approximate values provide a good picture of future climate change, the more reliable the measurement points are, the more robust the model becomes.
