- Digest raw data
- Signal from CHP-1
- Tracker "async"
- CHP-1 internal temperature from thermistor
- Bad data ranges flagging
- From manual set execution ranges
- From acquisition signal physical limits
- Converts signal to radiation
- Computes temperature correction when possible
- Plots
- Overview of Clean/Dirty signal
- Daily signal with and without dark
- Overview of Direct radiation measurements
- Daily Direct radiation measurements
- Digest raw data
- Signal from CHP-1
- Bad data ranges flagging
- From manual set execution ranges
- From acquisition signal physical limits
- Converts signal to radiation
- Plots
- Overview of Clean/Dirty signal
- Daily signal with and without dark
- Digest async and step files for later analysis
- Quality Check of radiation data (QCRad)
- Flags data using mainly the algorithm of C. N. Long and Y. Shi (2006)
- Clear sky identification (CSid)
- Flags data as affected by clouds or not with the algorithm of M. J. Reno and C. W. Hansen (2016)
- Investigate long-term trends (Work in progress)
- Process similar to A. Natsis, A. Bais and C. Meleti (2023)
- Creates TSI data used in analysis
- Imports atmospheric pressure data from proxies
- Keeps an
md5sumof all input files to check for bit rot and other data corruption.
- Digest raw data
- Signal from EPPLEY-IR
- Digest raw data
- Signal from an Inclined CHP-1
- Parse Global radiation data prepared with an external and independent process
- Read *.TOT files
- Do some plots and comparisons
inspect_days_duckdb.Rinteractive plot of some data in the duckdbinspect_days_DB.Rinteractive plot of some data in the DBinspect_days_Lap.Rinteractive plot of some data from source filesinspect_days_Lap_sirena.Rinteractive plot of some data from source files
- Process more instruments
- Import libRadtran data
- Improve CSid algorithm
- Import other references
Some aspects on the implementation of this project.
- We use a
duckdbdatabase for all measurements and additional data. - There are some files with extra meta data for the data in the database and the analysis performed.
- We use features of the
duckdbandarrowlibrary, and alsodplyranddata.tablefor data manipulations. - The analysis should be able to be performed with under 8Gb of RAM, but this is not assured.
- There is a trade-of with the disk usage/wearing, especially when starting from scratch.
- New data should be easy to be added on daily base on all levels.
- New process and analysis should be easy to added for all data.
- This is intended as a framework for all broadband instruments data analysis and processing.
There is no centralized documentation for the project. Although you can refer to:
Readme.mdor other markdown files for a relevant overview- Summary notes on the start of each script
- Comments inside each script
- Compiled reports from each script
- Follow the sequence of the scripts in 'execution' folder
- We use the
renvR package to keep track of the projects dependencies. - Maybe will use a
nix-shellenvironment as a more robust and portable method.
Contains parts of the logbook of the instruments maintenance and other notes.