PALM-meteo 2.6: Processor of PALM meteorological input data

Krč, Pavel; Belda, Michal; Bureš, Martin; Eben, Kryštof; Geletič, Jan; Radović, Jelena; Řezníček, Hynek; Resler, Jaroslav

doi:https://doi.org/10.5194/egusphere-2025-4120

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https://doi.org/10.5194/egusphere-2025-4120

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11 Sep 2025

| 11 Sep 2025

Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

PALM-meteo 2.6: Processor of PALM meteorological input data

Pavel Krč, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jelena Radović, Hynek Řezníček, and Jaroslav Resler

Abstract. PALM is a versatile and modular microscale atmospheric modelling system. It supports offline nesting using pre-processed initial and boundary conditions, which are provided via the dynamic driver file, along with other time-dependent input data, such as radiative forcing. PALM-meteo is a new modular tool for preparing the PALM dynamic drivers using data from various mesoscale or global meteorological models as well as other sources, such as measurements. It is derived from an older tool, the WRF_interface, which provided dynamic drivers from the WRF model data. PALM-meteo significantly expands the scope of usable meteorological inputs for PALM, and it is ready to be easily extended with more data sources in the future.

Received: 22 Aug 2025 – Discussion started: 11 Sep 2025

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Pavel Krč, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jelena Radović, Hynek Řezníček, and Jaroslav Resler

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RC1:
'Comment on egusphere-2025-4120', Anonymous Referee #1, 20 Oct 2025 reply
Overview:
PALM-meteo 2.6 is a modular Python-based preprocessor that prepares PALM dynamic drivers from a variety of mesoscale/global models and other sources. Key capabilities include flexible plugin-based import (WRF, ICON, Aladin, CAMx, CAMS, synthetic), horizontal regridding, vertical adaptation (terrain matching with hybrid/sigma/universal methods), several vertical interpolators (NumPy, MetPy, Fortran), mass-balancing across boundaries, chemistry and radiation handling, and wind damping near walls. The manuscript documents architecture, configuration, workflows, gives 2 example applications (Prague and Guelph), and provides code and example data archives.
General comments:
The topic is timely and valuable, and the development effort is highly appreciated. However, the manuscript often reads like user documentation, with detailed procedural descriptions that are not essential for a research paper. I suggest streamlining the main text to emphasize scientific motivation, methods, validation, and results, and moving operational instructions (installation, setup, exhaustive configuration options) to supplementary material or the project’s code repository.

The manuscript does not specify how meteorological variables are treated in the near‑surface gap below the first model level in the 3‑D data. Please clarify whether PALM‑meteo uses mesoscale model surface diagnostics (e.g. 2 m temperature) or whether values are extrapolated from the lowest model level to the ground. If a specific filling or blending method is applied (e.g., log‑law/profile fits or use of surface diagnostics), summarize it in the Methods section. If no special treatment is applied, explain and discuss possible implications for PALM simulations.

The manuscript would be strengthened by a dedicated results/validation section showing PALM simulations prepared with PALM‑meteo. Useful additions would include a sensitivity analysis comparing PALM outputs obtained with different meteorological inputs or a demonstration of how the new PALM‑meteo features improve PALM results compared with earlier preprocessing approaches. Where possible, compare model outputs to available observations for validation (e.g. 10 m wind and 2 m temperature). If new simulations are not feasible, please summarize and re‑evaluate the previously published PALM studies that used PALM‑meteo or extend the already provided example cases. These additions (or a clear justification why they are omitted) would make the manuscript’s scientific contribution more convincing.

Specific comments:
Abstract: The abstract describes PALM‑meteo’s capabilities well but would be stronger if it reported at least one concrete result that illustrates the tool’s scientific or practical impact. Please add a brief outcome from the manuscript (for example, a validation metric, an improvement relative to a previous preprocessing approach, or a result from one of the two example case studies) so readers immediately see the tool’s benefit.

Line 83 – The subsubsection heading "1.3.1 PALM dynamic driver" appears unnecessary because it is the only child heading under 1.3.

The material in subsection 2.1 (Previous studies using PALM‑meteo and its predecessors) reads as background and would be better placed in the Introduction and substantially condensed. In particular, operational/disclaimer details about the PAMORE name and the split with DWD are not scientific content and are more appropriate for the code repository, a short footnote, or the Acknowledgements than for the main text. I suggest the authors merge a short, focused summary of prior applications into the Introduction (for example: “PALM‑meteo evolved from the WRF_interface and has been used in urban studies …) and remove subsection 2.1.

Line 107 contains a typographical error: “Detsche Wetterdienst” should read “Deutscher Wetterdienst (DWD)”.

Line 121 – Please avoid mentioning unpublished studies unless they are directly relevant and publicly accessible.

Figure 1: This figure would benefit from an expanded caption and clearer labelling. Please add subcaptions (a–c) describing each panel, label key elements in the images (e.g., the rectangle in the left panel or the meaning of the boxes in the middle panel) and explain the meaning of the right panel. Also refer explicitly to the panels in the main text so readers know what to look for.

Line 123: Section 2.2 is very implementation‑centered and could be substantially condensed in the main text. For a more detailed description, either supplements, documentation or code repository are better suited.

Line 240: Replace “The simple profiles …” to “The LOD=1 profiles …” or “1D-profiles”, otherwise it is not clear what is meant by “simple profiles”.

Page 12: The current version of Figure 4 is hard to interpret: the panels lack (a–c) labels and the font size in the panels is too small. Please add panel labels and increase the font size.

Line 291: The claim that “linear interpolation” is inconsistent across MetPy versions is surprising: a straightforward linear interpolation on identical inputs should be reproducible. If the authors observed differences, this likely indicates version‑specific bugs. Please document the observed behavior in the code repository or user documentation, and remove the statement from the manuscript, since it is not a scientific result on its own.

Line 300: The wind‑profile power law is generally valid only very near the surface and, even there, provides a rough empirical estimate that is most appropriate under near‑neutral conditions. Please justify the physical validity of applying the power‑law interpolation at the higher levels as discussed here. Did you visualize the resulting profiles to check for discontinuities or abrupt gradients where piecewise functions are joined?

Line 322: Replace “in the PALM” to “in the PALM model”.

Pages 23—26: The results shown in Figures 6-9 are not discussed in the manuscript. Please add a concise interpretation pointing out the main findings. Where possible, support the discussion with quantitative metrics (e.g., bias, RMSE).

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Citation: https://doi.org/10.5194/egusphere-2025-4120-RC1

Pavel Krč, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jelena Radović, Hynek Řezníček, and Jaroslav Resler

Data sets

Dataset for paper PALM-meteo 2.6: Processor of PALM meteorological input data Pavel Krč, Martin Bureš, Jaroslav Resler, Michal Belda, German Meteorological Service, European Centre for Medium-Range Weather Forecasts https://doi.org/10.5281/zenodo.16925022

Model code and software

PALM-meteo: processor of meteorological input data for the PALM model system Pavel Krč, Martin Bureš, Jaroslav Resler, Michal Belda https://doi.org/10.5281/zenodo.16924719

Pavel Krč, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jelena Radović, Hynek Řezníček, and Jaroslav Resler

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Short summary

PALM is a highly versatile open-source microscale atmospheric modelling system. One of its most useful applications is modelling detailed street-level urban climate, e.g. for evaluation of climate change adaptation and mitigation measures in cities. However, to produce real-case microscale simulations, they need to be forced by real or realistic weather conditions. The presented tool enables PALM to use meteorological inputs from a large selection of meteorological models and other sources.


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