Refining the Lagrangian approach for moisture source identification through sensitivity testing of assumptions using BTrIMS1.1

Mu, Yinglin; Evans, Jason P.; Taschetto, Andréa S.; Holgate, Chiara

doi:10.5194/gmd-19-1367-2026

Articles | Volume 19, issue 3

https://doi.org/10.5194/gmd-19-1367-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-1367-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 3

Development and technical paper

|

12 Feb 2026

Development and technical paper |

| 12 Feb 2026

Refining the Lagrangian approach for moisture source identification through sensitivity testing of assumptions using BTrIMS1.1

Yinglin Mu, Jason P. Evans, Andréa S. Taschetto, and Chiara Holgate

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Cumulative views and downloads (calculated since 22 Jul 2025)

Month	HTML	PDF	XML	Total
Jul 2025	182	34	4	220
Aug 2025	948	54	12	1,014
Sep 2025	3,426	32	22	3,480
Oct 2025	150	14	4	168
Nov 2025	74	58	12	144
Dec 2025	66	118	16	200
Jan 2026	152	54	12	218
Feb 2026	353	89	18	460
Mar 2026	245	119	16	380
Apr 2026	189	117	16	322
May 2026	177	69	6	252
Jun 2026	29	15	8	52
Jul 2026	177	50	10	237
Aug 2026	70	30	9	109
Sep 2026	208	86	58	352
Oct 2026	178	86	38	302
Nov 2026	29	5	1	35

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Short summary

Lagrangian approaches have been increasingly employed due to their suitability for extreme events and climatological studies in finding moisture sources of precipitation. However, as these approaches track independent air parcels carrying moisture – rather than simulate processes based on governing physical equations – they rely on several underlying assumptions. This study tests these assumptions and refines the approaches to enhance their broader applicability.