Daniel Philipp's repositories
seviri_ml
SEVIRI_ML: A machine learning based module to derive: (1) A cloud mask, (2) the cloud phase, (3) the cloud top pressure, (4) the cloud top temperature, (4) a multilayer flag and (5) a cloud base height from SEVIRI measurements using its full spectral capabilities. Also to be used as external module with ORAC (https://github.com/ORAC-CC/orac).
atrain_match
Matching A-train Calipso/Cloudsat products with AVHRR/VIIRS/MODIS readiances and products
atrain_plot
Plot CMA/CPH/CTH/CTT validation scores calcualted from atrain_match collocations on spatial map.
cci_tools
Useful tools for ESA Cloud_cci project
granger4climate
Apply Granger Causality tests to climate data.
level3cc4cl
Create Level-3 files from ORAC (CC4CL) L2 files
orac
Optimal Retrieval of Aerosol and Cloud
seviri_util
SEVIRI data reading, writing, and pre-processing utility.