Updates to run 12 months of mean daily precipitation using a variety of models. Includes using gamm() to incorporate spatial effects in addition to the smooth parameters. Not all clean and cozy yet, uploading as a work-in-progress...

Further updates to interpolation procedures including:

1) bugfix in MOD06_L2_data_compile. Root access is needed to run swtif in its current directory (bad design!).
2) Switched to UTM output from swtif (from sinusoidal) becuase it looked like gdal was struggling with integerized sinusoidal...

Modified GAM.R interpolation script to 1) simplify validation results, 2) add full prediction (rather than just stations) and 3) some other (hopefully) simplifications and improvements.

Updated GHCN_stations script to:

1) draw station location information from postgres database and perform merge/join query within database rather than r
2) add function to buffer region of interest to include stations outside region (to minimize edge effects)

Merging with bp/interp to use some of Benoit's code for precip interpolation

Merge branch 'bp/interp' into aw/precip

More updates to output plots

OR data preparation, initial commit for extraction of covariates from raster stack

OR data preparation task#363, modified code for ghcn to create a shapefile

added import of station data to ghcn postgres script

updated directory paths and related comments

Added initial version of LST_Landcover exploration (not finished). Also moved prior version of interpolation procedure (bayesian krig) into repository.

Minor updates to dataset size calculation

Initial commit adding UML flowchart

added processing for 'very cloudy days'

Added PRISM comparison to MOD06_summary and added script to calculate 'back-of-the-envelope' estimates of total daily climate layer sizes

GHNCD station data selection using Postgres database, initial commit, task #363

GAM LST, added specific and general diagnostic measures (e.g.MAE) GAM+Kriging, task #364 and #406

Updated MOD06 compile script to process the tiles in parallel using GRASS. This brings processing time for 10 year archive for oregon from 48 hours to ~2 hours on 24 cores. Also added several exploratory analysis to the data_summary script.

Added cloud flag to outputs

First 10-year processing of daily mean tifs

First full processing of daily mean tifs

GAM LST, adding lines to summarize samling RMSE using plots, task #409

GAM LST, first code to test effect of sampling on GAM, task #409

GAM LST, added model and modified summary plots, run on 365 dates GAM+Kriging, task #364 and #406