Developed in the Laboratory of Atmospheric Physics of Thessaloniki, Greece.
To process the data from broadband instruments of LAP.
Some plots and reports should be found in my personal site here under the Data display section.
Name | Rows | Size | Values | Vars | Fill | Bytes/Value |
---|---|---|---|---|---|---|
Broad Band LAP duckdb | 19034700 | 5.4 GiB | 1.147e+09 | 2045 | 62.07% | 5.03 |
Raw files hashes | 927335 | 4.9 MiB | 3709340 | 4 | 100% | 1.39 |
Total | 19962035 | 5.4 GiB | 1.151e+09 | 2049 | NA% | 5.01 |
Table: Datasets sizes on 2025-03-22
- 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
md5sum
of 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.R
interactive plot of some data in the duckdbinspect_days_DB.R
interactive plot of some data in the DBinspect_days_Lap.R
interactive plot of some data from source filesinspect_days_Lap_sirena.R
interactive 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
duckdb
database 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
duckdb
andarrow
library, and alsodplyr
anddata.table
for 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.md
or 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
renv
R package to keep track of the projects dependencies. - Maybe will use a
nix-shell
environment as a more robust and portable method.
Contains parts of the logbook of the instruments maintenance and other notes.