Where to start with precipitation traceback? examples?

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geokon
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Joined: August 18th, 2021, 2:06 am
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Where to start with precipitation traceback? examples?

Post by geokon »

As I understand it, HYSPLIT was originally designed for particle traceback. The research sections on this board seem to corroborate this (volcanic ash, smoke, dust, etc.)

Nonetheless I often see HYSPLIT being used for tracing back the origin of the moisture that forms rain. I've seen multiple papers to that effect and this forum often has question along those lines

viewtopic.php?f=31&t=1884
viewtopic.php?f=33&t=2097

The PySPLIT conference talk goes into this a tiny little bit tangentially as well (but thin on details)

So in general this seems like a common use-case. However all the tutorials and manual information is really geared towards particle traceback and I'm not quite sure how to approach solving our research problem. I'm hesitant to just blindly copy the research methodology from a similar study - but nor am I a HYSPLIT expert to craft something from scratch.

Are there some canonical examples to look at? Some instructions or guidance when it comes to looking at the origin of precipitation events?

In my case we are doing a geological study in Thailand and we've collected several years of d18O isotope data from rain on the Thai peninsula. We are looking to reexamine these rain events to determine their approximate origin (South China Sea vs Indian Ocean vs. local precipitation). I'm not necessarily looking for some turn-key solution, and I'm trying to get up to speed with the relevant meteorology (though this is challenging at times b/c all the HYSPLIT literature assumes some prior knowledge) - but HYSPLIT does have a lot of input parameters such as starting altitudes, traceback lengths, surface moisture "pick up" etc. and I'm not quite sure where to start.

It's also a situation where it's quite hard to know if you've done something embarrassing and made wrong assumptions on your inputs :D

Any guidance suggestion or examples would be much appreciated!
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