the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Mar 2025
The Lagrangian moisture source and transport diagnostic WaterSip V3.2
Abstract. WaterSip is a diagnostic software tool that identifies the evaporation sources and transport pathways of precipitation or water vapour over a target area based on Lagrangian model output. In addition to the geographic location, WaterSip identifies select thermodynamic properties of the moisture sources, during atmospheric transport, and during arrival over the target area. WaterSip software thereby employs the Lagrangian diagnostic algorithm for quantitative moisture source accounting of Sodemann et al. (2008b). The software tool requires output from Lagrangian particle dispersion models or trajectory models as input for the diagnostic. Moisture sources are then identified from changes in specific humidity along these trajectories at each output time step. The ratio between changes in specific humidity and the specific humidity of the air parcel allow to estimate the quantitative contribution of a moisture source to the air parcel at a specific time and location. Together with the temporal sequence, this provides the basis for identifying moisture source contributions to the final precipitation. WaterSip also identifies and aggregates further thermodynamic and geographic properties of the moisture source and during the moisture transport. Designed to operate on large datasets of regional to global domain-filling trajectories, WaterSip provides the results of the moisture source identification as gridded information in a variety of output files in netCDF format. This paper describes the relevant methodological foundations, the technical set-up and configuration, and provides a consistent example case study to illustrate the use and interpretation of the software tool and its results. Importantly, key uncertainties and caveats are described and discussed throughout the text. Users of WaterSip should be aware of these uncertainties to obtain a valid and reliable interpretation of the diagnostic results.
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Status: open (until 09 May 2025)
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RC1: 'Comment on egusphere-2025-574', Anonymous Referee #1, 18 Mar 2025
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This manuscript presents a comprehensive update and documentation of the WaterSip software (version 3.2), a diagnostic tool for identifying moisture sources and transport pathways associated with precipitation and atmospheric water vapour. The tool implements the Lagrangian diagnostic framework originally introduced by Sodemann et al. (2008), and offers support for trajectory data from models such as LAGRANTO and FLEXPART.
The manuscript is technically detailed and contains extensive explanations of the algorithmic structure, parameter configuration, example case setup, and diagnostic outputs. It represents a valuable contribution to the hydrometeorological community, particularly those using Lagrangian methods for moisture tracking. However, there are several areas where the manuscript could be improved significantly, especially in the following aspects:
- Validation of diagnostic results through comparison with observations or alternative algorithms;
- Technical clarity on certain assumptions and limitations;
- Demonstration of robustness and sensitivity through more systematic experiments;
- Improved structure and clarification of key terminology for broader accessibility.
I recommend major revisions before this manuscript is accepted for publication.
1. Lack of Model Validation and Performance Benchmarking
While the algorithmic principles of WaterSip are well-founded, the manuscript lacks quantitative validation of the diagnostic results. In particular:
- No comparison with independent observational datasets (e.g., precipitation from GPM/IMERG or ERA5 reanalysis P);
- No benchmarking against other Lagrangian diagnostics, such as WAM-2layers, FLEXPART-WATER, or isotope-enabled models (e.g., COSMOiso);
- The Lagrangian precipitation estimate P~\tilde{P}P~ is claimed to have an error of 20–30%, yet this is not demonstrated empirically in the paper.
Recommendation: Include a comparison of WaterSip-derived precipitation estimates and source regions against satellite/reanalysis precipitation and/or results from other established methods. This would help quantify accuracy and justify the use of default parameters (e.g., RHc, ∆q thresholds).
2. Insufficient Sensitivity Experiments
The diagnostic depends heavily on multiple user-defined thresholds, such as:
- Moisture uptake threshold (∆qc),
- Precipitation threshold (∆qp),
- Critical relative humidity (RHc),
- Trajectory length (L) and time step (∆t),
- Boundary-layer height scale (sh).
While some default values are provided, the manuscript does not present any systematic sensitivity tests to justify these defaults or examine result variability.
Recommendation: Provide at least one sensitivity experiment (e.g., with RHc = 60%, 80%, 90% or ∆qc = 0.1, 0.2, 0.3 g/kg/6h) using the Scandinavia case to demonstrate how output fields (e.g., source footprints, P̃) are affected. This will help users understand uncertainty and robustness.
3. Ambiguity in Treatment of Mixing vs. Precipitation
The distinction between moisture losses due to precipitation vs. dry mixing is briefly described but remains ambiguous in practical terms:
- How are “mixing events” defined and treated in the accounting algorithm?
- Are they excluded from precipitation source attribution entirely?
- How does this impact attribution over dry regions or under sub-saturated conditions?
Recommendation: Include a dedicated subsection clarifying how dry mixing events are separated and whether/how they influence the fractional contribution calculation. Provide a sample output or visualization that isolates these cases.
4. Limited Scope of Case Study
The case study over Scandinavia is informative but lacks depth and generality:
- It only covers a short period (10–20 Aug 2022) with one configuration;
- There is no validation of the Lagrangian precipitation estimates against ERA5 or in-situ observations;
- The transport features are discussed qualitatively without statistical summaries (e.g., source region contributions by %).
Recommendation:
- Add a second case study (e.g., a winter event or tropical cyclone) to demonstrate versatility;
- Include plots/tables showing the percent contribution of major source regions (e.g., local vs. oceanic);
- Overlay gridded WaterSip P~\tilde{P}P~ with observational data (e.g., E-OBS or GPCC).
5. No Performance or Computational Cost Analysis
Given the tool is designed for high-volume Lagrangian data, its computational performance, memory usage, and scalability are essential for practical adoption:
Recommendation: Add a short section or table reporting:
- Typical runtime and memory usage for the example case;
- Speedup with OpenMP threads;
- Bottlenecks or limitations for large-scale usage.
Minor Comments & Suggestions
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Clarify terminology early (Section 1):
- Define “uptake”, “accounting”, “residual moisture”, and “arrival grid” explicitly.
- Consider a graphical workflow diagram.
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Equations (6)–(9):
- Include variable definitions in-line with the equations, especially for readers not familiar with the 2008 method.
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Section 2.5: Too long and fragmented. Suggest splitting into:
- "Core algorithm parameters" (∆q, RHc, sh),
- "Grid and output configuration",
- "Optional diagnostics".
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Figures:
- Add scale bars and legends (e.g., units in mm/day);
- Some figures lack clarity (e.g., Fig. 2d – difficult to read e-p shading);
- Add observational overlay for better interpretation.
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Code availability: Ensure a DOI or stable link is provided. Consider creating a GitHub/Zenodo archive.
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Language & Style:
- Mostly clear, but some long and nested sentences in Section 2–3 could be simplified.
- Example: “Air parcels will only be retained for analysis…” → split into clearer bullet rules.
Conclusion
The manuscript presents a valuable and much-needed technical documentation of WaterSip V3.2 and the Lagrangian moisture source diagnostic algorithm. However, to be suitable for publication in a journal such as GMD or HESS Discussions, the following critical issues must be addressed:
- Quantitative validation of results,
- Sensitivity and uncertainty analysis,
- Clear treatment of physical assumptions (e.g., mixing vs. precipitation),
- Extended and comparative case studies.
Citation: https://doi.org/10.5194/egusphere-2025-574-RC1 -
CEC1: 'Comment on egusphere-2025-574', Juan Antonio Añel, 21 Mar 2025
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Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
You have archived your code on a Git site. However, Git sites are not suitable for scientific publication. Therefore, the current situation with your manuscript is irregular. Please, publish your code in one of the appropriate repository (you can check our policy for examples) and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible, as we can not accept manuscripts in Discussions that do not comply with our policy.Please, note that if you do not fix this problem, we will have to reject your manuscript for publication in our journal.
Also, remember that you must include a modified 'Code and Data Availability' section in a potentially reviewed manuscript, containing the link and identifier of the new repository.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-574-CEC1 -
AC1: 'Reply on CEC1', Harald Sodemann, 22 Mar 2025
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As requested, the model source code is now available on the zenodo archive at https://zenodo.org/records/15068066.
Best regards,
Harald Sodeann
Citation: https://doi.org/10.5194/egusphere-2025-574-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 22 Mar 2025
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Dear Prof. Sodemann,
Many thanks for addressing this issue so quickly.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-574-CEC2
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CEC2: 'Reply on AC1', Juan Antonio Añel, 22 Mar 2025
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AC1: 'Reply on CEC1', Harald Sodemann, 22 Mar 2025
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