The MATLAB (The MathWorks, USA) code presented here is for calculating absorption coefficient spectra based on the light intensity spectra provided by the Online Hyperspectral Integrating Cavity Absorption Meter (OSCAR, TriOS GmbH, Germany).
The calculations are based on the equations published in: Kirk, J.T., 1997. Point-source integrating-cavity absorption meter: theoretical principles and numerical modeling. Appl. Opt. 36, 6123–6128. Leathers, R.A., Downes, T.V., Davis, C.O., 2000. Analysis of a point-source integrating-cavity absorption meter. Appl. Opt. 39, 6118–6127. Röttgers, R., Schönfeld, W., Kipp, P.-R., Doerffer, R., 2005. Practical test of a point-source integrating cavity absorption meter: the performance of different collector assemblies. Appl. Opt. 44, 5549–5560.
Short instructions for software use:
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Unzip "OSCAR_Code.zip" to retrieve the MATLAB scripts, the "Subfunctions" folder, and the "User_Input_Template.xlsx" file.
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Create a folder "Rawdata" in the same folder where the scripts are.
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Put the "RAW_DARK" and the corresponding "RAW_LIGH" files extracted from the .tar file downloaded from the OSCAR in that folder (either as .dat or .csv). Rename files if necessary (e.g. in case you want to process datasets covering several days).
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Copy the "User_Input_Template.xlsx" and rename the copy into "User_Input.xlsx".
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Fill out the spreadsheet with the necessary information according to the instructions given in the file and put it in the same location where the scripts are.
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Read the instructions in script "A_Import_OSCAR_Data", make the appropriate changes in the "Parameters" section, and execute the script.
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Check the result files and make changes, if required (e.g. delete wrong measurements or give temperature and salinity information in the appropriate columns).
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Read the instructions in script "B_Calculate_Reflectivity", make the appropriate changes in the "Parameters" section, and execute the script.
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Check the result file and make changes, if necessary.
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Read the instructions in script "C_Calculate_Absorption", make the appropriate changes in the "Parameters" section, and execute the script.
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Check the result file.
The script "ExampleData_Figures" creates figures from the example data (different for the two datasets) for checking if everything worked correctly. The dotted lines in the plots are the minimum/maximum values of the variable which have been calculated using the standard deviation of repeated measurements into account.
For questions or feedback contact Jochen Wollschläger, University of Oldenburg, Institute of Biology and Chemistry of the Marine Environment (ICBM) E-Mail: jochen.wollschlaeger@uol.de