MODISTools R library does not appear to be functioning so switched code to use the PEcAn library, data.remote, for downloading MODIS (which calls a Python script). This code saves the data in a different format (netCDF, one file per band) but it also returns the data as an R matrix, so this is also being saved as an RData object. subsequent code is being modified to use that RData object. Added a boolean variable, useMODISTools, to the global_input_parameters, but at the moment backward compatibility is not functional.  Need to update download.new.modis.data to use the same library and data format
modified create.ndvi.data to use the new MODIS data format from the PEcAn library
modified run.SS.model in order to structure the input timeseries data to RunJAGS as a matrix, with each row being a different year and each column being a different day. In addition, to save space decided to not save the full MCMC output of the state variable, X, but rather just the 95% CI and median. The full MCMC is still saved for the model parameters.
modified RunJAGS to add a second model, which is just a RandomWalk. The choice of models has been added as a global config. The random walk model has also been modified to analyse multiple years of data by treating the input data as a matrix. Even though the observed data has been rescaled based on the JulyAug and JanFeb means, there appears to be summer and winter trends in the GCC data which make the mean state drift outside the [0,1] bounds. Will try adding a logit transform to the state in order to keep the variable within bounds. Also need to develop alternative process models that involve actual process
added useMODISTools and model to global_input_parameters
modified make.SS.plots to use the newly formatted output from run.SS.model
in check.for.FM added a check within the last.update.site to see if we've moved on to a new year. If so it deletes the file so that the code will re-initialize
added num.ensembles to the global variables, so that MCMC size and PF size can be set seperately
modified create.FM.model to load the modified State Space output, to not treat r as a state variable, and to foreward similate the random walk model including the process error. Output now only includes the state X and output files are tagged with the forecast date so that previous forecasts can be easily accessed
extensive updates to update.FM.model

* Added dated to reading and writing of RData objects & moved these files to their own folder.

* redid calculation of uncertainties in the standard deviations, noting that you perform stats after transforming into the SD domain. Hope to treat these as distributions at some point rather than just the median

* fixed error in the log likelihood when data is missing -- code had the wrong variable name and wronge ensemble size

* changed data model to use mean GCC not gcc.90

* changed state variable tracking to just be for X

* changed forecast model to random walk

* added additional output of figures to be in PNG format in addition to PDF format since the former will be easier to display on a webpage

* moved the saving of forecasts and last.date.filename to be within the loop over days. This means that we save the forecast for every day with observations, which makes reconstruction easier and also makes the code more tolerant to crashes.
added 0,1 constraint on model state for random walk model in both State Space and Forecast. Makes SS much slower
removed hardcoded directory in MakeAnimation
modified MODIS update scripts to work with PEcAn data.remote package