the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Mar 2025
Benefits of km-scale climate modeling for winds in complex terrain: strong versus weak winds
Abstract. The existence of many different wind types in complex terrain and the difficulty of obtaining representative wind observations hinder the analysis of the general benefits of high-resolution climate modeling for winds. We show that the added value of km-scale modeling is particularly pronounced in mountainous terrain and increases substantially with wind speed, with the km-scale model and observations reaching twice larger speeds than a coarser model with 12 km grid spacing. At the same time, synoptically calm conditions are prone to local thermally generated circulations with typically weak winds, whose modeling results can also be considerably affected by the model resolution. We therefore focus on the mountainous region of the southern Scandinavian mountains and analyze the winds at two ends of the wind distribution: very strong winds, generally forced by large-scale weather systems, and local, thermally generated winds in synoptically calm conditions. Strong winds in the present climate are influenced more by the terrain height and high model resolution than by the large-scale forcing, while the future change is mostly governed by the global-model large-scale circulation change. For the thermal winds in summer, in contrast to the coarse model, the km-scale model captures glacier downslope wind in the high mountains and the resulting convergence zone as well as the increased cloud cover where the glacier wind meets the daytime upslope wind. The future change in thermal winds is primarily influenced by the future temperature change and the high model resolution. Since the future temperature changes are considerably less uncertain than the changes in large-scale circulation, the future of local weak thermal winds can be estimated with less uncertainty compared to stronger winds.
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Status: open (until 23 May 2025)
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RC1: 'Comment on egusphere-2025-1281', Anonymous Referee #1, 20 Apr 2025
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This is a necessary study addressing the performance and added value of convection-permitting climate models (CPMs) for representing wind patterns in complex terrain. Wind speed remains a challenging variable to model accurately due to its sensitivity to local topography, and its implications extend across various sectors including ecology, energy, and risk management. The authors present a clear and well-structured text, with interesting novel results. However, there are several aspects that would benefit from further clarification, additional background, and minor textual improvements. In general, there is a lack of context in the introduction and discussion of the results with previous work that would help to understand the novelty and importance of the results obtained this work. Despite being well written, clear and direct, the text should be more fluid, using more connectors between sentences.
General comments:
The introduction would benefit from a broader context of the results of previous studies on the added value of CPMs compared to their parent regional climate models (RCMs). Additionally, it is needed a larger discussion of the relevance of wind speed modeling in the context of climate and environmental systems (e.g. dispersion of pollutants, erosion, wind energy). One reason wind is less studied than temperature or precipitation is the scarcity and heterogeneity of wind observations, particularly in mountainous regions. Expanding on these points and providing relevant references (e.g., Pryor et al., 2020; Vautard et al., 2010) would strengthen the motivation for the study.
- Related to the wind observations used, a more detailed description of the observational data used for model validation is needed. Please clarify:
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The number of stations used in each geographical category (inland flat areas, mountains, coastal zones), to ensure that all regions are equally represented.
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The spatial distribution of these stations, especially in relation to the domain’s topography. The manuscript would be benefit of a map with the spatial distribution of the stations and its altitude.
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Any data filtering or quality control procedures applied in the treatment of outliers or continuity of time series.
- In the statement “Strong winds are selected using the 95th percentile of daily wind maxima,” it is unclear which time period is used to define this percentile. Is this based on the historical simulation only, or the entire simulation ensemble? Please specify the temporal reference used to compute the threshold.
- The description of the results should be more detailed, including numbers for the wind values in sentences such as: ‘Interestingly, ERA5 somewhat overestimates wind speeds for all but the strongest winds in winter. What is considered moderate or strong wind in this case?
- Since there is no direct measurement of the improvement of higher resolution, interpretation of results and comparison between simulations in sentences such as ‘HCLIM3 is also independent of GCM forcing, but the increase in wind speed with terrain height is much larger than for HCLIM12’ would benefit from a trend analysis such as the Mann-Kendal test.
- The reasons of choosing the stable/unstable conditions in the next sentence ‘The presence of snow cover generally lowers the surface temperature compared to the equivalent conditions without snow cover and can cause downslope glacier wind even in daytime conditions. As typical representatives of unstable and stable conditions, we choose summer daytime and winter nighttime situations, respectively, for further analysis.’ could be better referenced.
- As already mentioned in the general comments, the Conclusions section should become a Conclusions and Discussion section. Although it is possible that the novelty of this work is such that similar results are difficult to find or be comparable, this should be reflected in the text. It is necessary to include a few sentences indicating the objectives and novelty of the work in reference to previous results.
- I miss a brief discussion of how ERA5 wind simulations compare to observations in previous studies, particularly in complex terrain. Are the known limitations of ERA5 reflected in your results? Referencing past evaluations (e.g., Olauson, 2018; Molina et al., 2021, Gutierrez et al., 2024) could help contextualize your findings.
- The mentioned Figures not shown on the manuscript might be shown and referenced on the supplementary material.
Minor comments:
- L60: Rewrite this for clarity: ‘The 21-year long evaluation simulation (1998-2018) downscaled
ERA-Interim (Dee et al., 2011)’ to ‘the 21-year long-term evaluation simulation is (1998-2018) reduced from ERA-Interim (Dee et al., 2011)’.
- L98: correct ‘for the strongest winds’
- L140: ‘percentage decrease’ by percentage of decrease.
- L202: correct to : ‘neighbouring’.
- L233: correct to: ‘the dynamics of the glacier wind were not reproduced’.
Citation: https://doi.org/10.5194/egusphere-2025-1281-RC1 -
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RC2: 'more information on the categorization and interpretation of the results are needed', Anonymous Referee #2, 25 Apr 2025
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This manuscript explores the advantages of km-scale climate models for the simulation of wind patterns over Scandinavia. The authors prove evidence that km-scale models (dx=3km) are able to simulate the wind speeds over complex, mountainous terrain with a higher skill compared to models with dx=12km. The authors attribute this improvement to better-resolved topography and a more realistic simulation of thermally-induced circulations, which are common over complex terrain. The manuscript is generally well written and provides a valuable contribution to the (large) research question on which processes are relevant for the successful simulation of wind speeds over complex topography. However, I have a few questions on the categorization and interpretation of the results, among some minor remarks.
Major comments
1) Interpretation of the thermally-induced circulations over mountainous terrain:
The authors argue that the 3km simulations have an improved representation of the thermally-induced circulation, and especially anabatic/katabatic slope winds. However, I would argue that the thermally-induced circulation (or Alpine pumping), also includes the large-scale plain-to-mountain circulation, and as a result, either up-valley (daytime) or down-valley (nighttime) flows (Zardi and Whiteman, 2013) are equally important in this study. I was surprised that these two circulations are not mentioned in the manuscript, because they even act on larger scales (ie., plain-to-mountain scales or entire valleys) than small-scale slope flows. This might have implications for the interpretation of the model results. Previous studies (Langhans et al, 2013; Graf et al, 2015) argue that thermally-induced flows are well-represented in km-scale climate models, in agreement with the findings of this manuscript.
My second question would be the following: Since purely thermally-induced valley winds could reach wind speeds up to 10m/s (Mikkola et al, 2023; Schmidli et al, 2018), can we be sure that weather situations with a valley wind fall into the weak-wind category?2) Horizontal resolution required to simulate slope flows (either anabatic or katabatic)
How can we be sure that the model at dx=3km is able to simulate anabatic or katabatic slope winds, given their small vertical extent and short-term variability? As Wagner et al (2014) suggest, at least 10 grid points across a valley are necessary to simulate the relevant thermally-induced flows, including slope winds. Furthermore, Schmidli et al (2018) and Goger and Dipankar (2024) show that at at least a horizontal grid spacing of 1km might be necessary to simulate the up-valley flow. However, slope flows might be present, but inaccurately simulated.3) The glacier wind
The authors often mention the katabatic glacier winds in their results. I am aware that glaciers are present in Southern Norway (Haualand et al, 2024). However, how well are the glaciers represented in the climate model at dx=3km? Are there ice surfaces with the according land-use categories (ice) and albedo (larger than 0.6) present?
Furthermore, even if the glaciers are present in the model, how well is a purely katabatically-driven flow represented in the model? To my current knowledge, even models at the LES range (dx=50m or less, e.g., Goger et al, 2022) struggle to represent katabatic winds over glaciers (mostly due to too coarse vertical levels). Furthermore, Cuxart (2015) states that dx=5m is necessary to simulate stable boundary layers and katabatic flows.
Furthermore, at several occasions in the manuscript, the term "glacier wind" is used, while mostly katabatically-forced downslope winds are described, so it might make sense to stay with the term "katabatic winds".Minor comments
line 45: "large-scale winds accelerated by terrain": What do you mean exactly? Downslope windstorms, such as foehn and bora?
Section 2.1, Model simulations: This section would benefit if a table with the different simulations and their configurations were added
lines70-75: How exactly did you categorize the weather stations into the categories (flat/coast/mountains)? If an extra Figure would be too much addition to the manuscript, you could also add it as a supplementary figure.
line158: " The presence of snow cover generally lowers the surface temperature compared to the equivalent conditions without snow cover and can cause downslope glacier wind even in daytime conditions." - This is the first occasion where you mention glacier winds, but over snow-covered surfaces (independent of whether there is a glacier below the snow cover) it would make sense to stay with the more general term "katabatic winds".
line180: "confirming the upslope anabatic nature of the summer daytime circulation" - the positive vertical velocities could also be associated with the development of a convective boundary layer in the valleys (e.g., Goger et al 2024, Their Fig...)
line183: "This suggests that the downslope flow direction is the result of the katabatic glacier wind" - here is a second mention of the glacier wind, but it seems only to appear during winter when snow cover increases. Would the term katabatic wind be enough?
line255: " sub-km resolution is advantageous or even crucial (e.g. Wang et al., 2013)." - this is in agreement with the findings of Goger and Dipankar (2024), who conducted real-case simulations across the hectometric range of thermally-induced flows
line261: Where do you see in your data the occurrence of "glacier fronts"?
Figures 2 and 3: Please add the variable name to the units.References
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Cuxart, J.: When Can a High-Resolution Simulation Over Complex Terrain be Called LES?, Front. Earth Sci., 3, 6, https://doi.org/10.3389/feart.2015.00087, 2015
Goger, B., Stiperski, I., Nicholson, L., and Sauter, T.: Large-eddy simulations of the atmospheric boundary layer over an Alpine glacier: Impact of synoptic flow direction and governing processes, Q. J. Roy. Meteor. Soc, 148, 1319–1343, https://doi.org/10.1002/qj.4263, 2022
Goger, B. and Dipankar, A.: The impact of mesh size, turbulence parameterization, and land-surface-exchange scheme on simulations of the mountain boundary layer in the hectometric range, Q. J. Roy. Meteor. Soc., 150, 3853–3873, https://doi.org/10.1002/qj.4799, 2024
Graf M, Kossmann M, Trusilova K, Mühlbacher G: Identification and climatology of Alpine pumping from a regional climate simulation. Front Earth Sci 4:1–11. https://doi.org/10.3389/feart.2016.00005, 2016
Haualand, K. F., Sauter, T., Abermann, J., de Villiers, S. D., Georgi, A., Goger, B., Dawson, I., Nerhus, S. D., Robson, B., Hauknes Sjursen, K., Thomas, D., Thomaser, M., and Yde, J. C.: Micro-Meteorological Impact of Glacier Retreat and Proglacial Lake Temperature in Western Norway, ESS Open Archive, https://doi.org/10.22541/essoar.172926901.19613096/v1, 2024
Langhans W, Schmidli J, Fuhrer O, Bieri S, Schär C: Long-term simulations of thermally driven flows and orographic convection at convection-parameterizing and cloud-resolving resolutions. J Appl Meteorol Climatol 52(6):1490–1510, 2013
Mikkola, J., Sinclair, V. A., Bister, M., and Bianchi, F.: Daytime along-valley winds in the Himalayas as simulated by the Weather Research and Forecasting (WRF) model, Atmos. Chem. Phys., 23, 821–842, https://doi.org/10.5194/acp-23-821-2023, 2023
Schmidli, J., S. Böing, and O. Fuhrer, 2018: Accuracy of simulated diurnal valley winds in the Swiss Alps: Influence of grid resolution, topography filtering, and land surface datasets. Atmosphere, 9, 196, https://doi.org/10.3390/atmos9050196, 2018
Wagner, J. S., Gohm, A., and Rotach, M. W.: The Impact of Horizontal Model Grid Resolution on the Boundary Layer Structure over an Idealized Valley, Mon. Weather Rev., 142, 3446–3465, https://doi.org/10.1175/MWR-D-14-00002.1, 2014
Zardi, D. and Whiteman, C. D.: Diurnal Mountain Wind Systems, in: Mountain Weather Research and Forecasting, edited by: Chow, F. K., De Wekker, S. F. J., and Snyder, B. J., Springer Atmospheric Sciences, Springer Netherlands, 35–119, ISBN 978-94-007-4097-6 978-94-007-4098-3, https://doi.org/10.1007/978-94-007-4098-3, 2013Citation: https://doi.org/10.5194/egusphere-2025-1281-RC2
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