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- MATLAB 75.2%
- HTML 24.8%
| Filename | Latest commit message | Latest commit date |
|---|---|---|
| html | ||
| .gitattributes | ||
| .gitignore | ||
| all_correction.mat | ||
| all_correction_0-20000-0-06784_TUB120011.mat | ||
| all_correction_0-20008-0-BRN_TUB150046.mat | ||
| all_correction_kse.mat | ||
| all_correction_kse_TUB120011.mat | ||
| all_correction_lindenberg.mat | ||
| all_correction_lindenberg2.mat | ||
| all_correction_pay.mat | ||
| all_correction_pay_TUB120011.mat | ||
| all_correction_pay_TUB140016.mat | ||
| all_correction_pay_TUB200009.mat | ||
| all_correction_SIRTA_TUB140013.mat | ||
| AUTHORS | ||
| calculate_overlap_automatic_structured.m | ||
| calculate_overlap_automatic_structured_2.m | ||
| correct_overlap.m | ||
| invariant_probability_distribution_silagadze.m | ||
| LICENSE | ||
| load_ceilo_and_overlap_data.m | ||
| local_maxima.m | ||
| patcher.m | ||
| plot_overlap_routine_ov_fct.m | ||
| plot_overlap_routine_RCS_GRADRCS.m | ||
| prefix_data_pay.m | ||
| read_gradients.m | ||
| read_L1_EPROFILE_v4.m | ||
| read_overlap_cor_v3.m | ||
| read_overlap_cor_v3_kse.m | ||
| read_overlap_cor_v4.m | ||
| read_overlap_cor_v5.m | ||
| read_overlap_cor_v6_eprofile.m | ||
| readcorrectlyncfile3.m | ||
| README.md | ||
| script_overlap_routine.m | ||
| script_overlap_routine_v2.m | ||
| script_overlap_routine_v3_EPROF.m | ||
| sgolay_smooth.m | ||
| simplePBLdetection.m | ||
| TUB120011_20121112_1024.cfg | ||
| ypcmap2.mat | ||
Overlap correction algorithm
Algorithms for inferring overlap correction for (CHM15k) ceilometers from atmospheric observations under well-mixed boundary layer conditions. Based on Hervo et al. 2016 (https://doi.org/10.5194/amt-9-2947-2016)
Content
- Calculate overlap correction funtion ( script_overlap_routine_v2.m calling calculate_overlap_automatic_structured_2.m)
- plot all results (read_overlap_cor_v5). Including:
- All daily overlap functions
- temperature model
- Impact on gradient and temperature model simple PBL detection
- Gradient Analysis (read_gradient)
Detailed description of standard way of using
1. script_overlap_routine_v3_EPROF.m
a. fill variables :
* stn: wigos-id
* start_time/end_time: time period for which to calculate overlap correction
* folder_data : location of E-PROFILE netCDF level 1 files (NOTE: you'll prefer to transfer ncdf files directly on your machine to improve execution speed (locally ~12hours/1year of data))
* folder_out : output directory (NOTE: prefer a local directory on your machine for speed)
b. run script
2. read_overlap_cor_v6_eprofile.m
a. fill variables:
* station: wigos-id
* folder_ncdata: location of E-PROFILE netCDF level 1 files
* folder_correction: File path of the output created by script_overlap_routine_v3_EPROF.m in step 2)
* folder_output: output directory (NOTE: prefer a local directory for speed)
b. If you are configuring a new station add a case in the station inputs switch. Then specify:
* timerange of the correction files (in info.xxx) + timerange of daily correction visualization for actually testing the correction on measured profiles (in info_test.xxx).
* optical module id (info.tub) and instrument serial number (info.chm). You'll find this information in daily netcdf files attributes.
c. run script
d. filter bad quality overlap estimates
* identify in plots bad quality dates by using the overlap function vs range plot (Figure 2: fig 4) and the dates indicated in the command line output
* add these bad days to list_dates_bad_quality in the station switch
e. run script again
Examples
Raw

Corrected with model
