Hello,
I'm a PhD student conducting a study on backtracking air masses arriving at an atmospheric station. Specifically, I'm analyzing greenhouse gases such as CO₂, CH₄, H₂O vapor, and CO.
I would like advice on what time intervals are typically used in such studies. For example tubidy, should I backtrack air masses for 6-hour intervals over a 10-day period, or is there a more suitable or standard approach for this kind of analysis?
My objective is to perform a statistical analysis to determine the origin of air masses and correlate them with detected greenhouse gas concentrations. I am currently using GDAS 1-degree meteorological data, as it is the only dataset available for my study region (Morocco).
If anyone can provide guidance, especially with references to relevant articles, datasets, or books. I would really appreciate your help.
Thank you for your attention!![:D]( "Very Happy")
I'm a PhD student conducting a study on backtracking air masses arriving at an atmospheric station. Specifically, I'm analyzing greenhouse gases such as CO₂, CH₄, H₂O vapor, and CO.
I would like advice on what time intervals are typically used in such studies. For example tubidy, should I backtrack air masses for 6-hour intervals over a 10-day period, or is there a more suitable or standard approach for this kind of analysis?
My objective is to perform a statistical analysis to determine the origin of air masses and correlate them with detected greenhouse gas concentrations. I am currently using GDAS 1-degree meteorological data, as it is the only dataset available for my study region (Morocco).
If anyone can provide guidance, especially with references to relevant articles, datasets, or books. I would really appreciate your help.
Thank you for your attention!
Statistics: Posted by wolffy28 — April 16th, 2025, 11:33 am