Currently the optimization performs well when constraining the parameters with AOD. However, AOD is a variable that in most cases is less than two and thus on the order of magnitude of $10^0$. For variables, such as Cloud Liquid Water Path and Cloud Droplet Number Concentration, measurements can be on the order of magnitude of $10^2$ and the variance calculated from MLE should reflect this. Changes need to be made to allow for setting the bounds and initial values of the MLE optimizer.
Currently the optimization performs well when constraining the parameters with AOD. However, AOD is a variable that in most cases is less than two and thus on the order of magnitude of $10^0$. For variables, such as Cloud Liquid Water Path and Cloud Droplet Number Concentration, measurements can be on the order of magnitude of $10^2$ and the variance calculated from MLE should reflect this. Changes need to be made to allow for setting the bounds and initial values of the MLE optimizer.