the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Observation based precipitation life cycle analysis of heavy rainfall events in the southeastern Alpine forelands
Abstract. Heavy thunderstorms are a typical weather phenomenon during summer in southeast Austria. These fast-developing high-impact rainfall events often result in serious damage and are hard to predict. A profound understanding of the life cycle of these events, from formation to dissipation, is therefore crucial to increase resilience and improve forecasting skills. High-resolution observation datasets, like the one of the WegenerNet 3D Open-Air Laboratory for Climate Change Research (WEGN3D) in Feldbach (Austria), provide unique insights and are especially well suited for these important use cases. Consisting of 156 ground stations, an X-band radar, two radiometers, and 6 global navigation satellite system (GNSS) stations, the WEGN3D delivers highly resolved data, in both space and time, of key atmospheric parameters that enable a detailed investigation of small-scale weather phenomena, such as heavy rainfall events. Here we follow the different stages of the life cycle of 94 heavy rainfall events by investigating multiple atmospheric parameters in WEGN3D and global reanalysis data. Beginning with the event formation stage (i.e., the 8 h before the event), where temperatures are usually already quite high and continue to rise, while the first clouds begin to form, before wind speeds pick up and the sky darkens. Connected to these characteristics, we find an increase in \unit[2]{m} air temperature anomaly, integrated water vapor (IWV) anomaly, liquid water path (LWP), convective available potential energy (CAPE), and wind speed. Also, a decrease of cloud base height (CBH) can be observed, in accordance with the deepening of the convective cloud system. During the precipitation stage, we find an increase in the spatial variability of precipitation amount, temperature, LWP, and cloud cover, which represents the highly localized character of these events. After a few minutes to hours of intense rainfall, the event is over and has reached the dissipation stage. The parameters that increased during the event formation stage experience a drop during this last stage (i.e., the 16 h after the event), while CBH again reaches its pre-event levels. Our study gives insights into the physical processes connected to the life cycle of heavy rainfall events, by using the WEGN3D's distinct capability to capture characteristic features of such small-scale events, which illustrates the dataset's high potential for improving and verifying weather and climate models.
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RC1: 'Comment on egusphere-2025-1819', Anonymous Referee #1, 08 May 2025
The brief article of Haas et al. analyses 94 heavy precipitation events in southeastern Alpine forelands. The authors well describe their datasets and methods. The results of their study are reasonable and interesting showing a clear average behavior of the atmospheric parameters before, during and after convective rainfall events. This research area is of high interest for progress in nowcasting of extreme weather events. Thus, I recommend a publication of this study after a minor revision.
Major comments:1) The Introduction should provide a short overview of related studies, e.g., Cimini et al. 2015: Forecast indices from a ground-based microwave radiometer for operational meteorology , Atmospheric Measurement Techniques , DOI: 10.5194/amt-8-315-2015
2) line 101: a more detailed description or a reference for derivation of CAPE would be interesting.
3) Discussion: it might be interesting if you could discuss the potential of near realtime WEGN3D data for nowcasting of precipitation events
Minor comments:line 24 sentence is not complete. I think it should be:
These short and highly localized (convective) events which strongly influence ....Or divide this long sentence into two sentences.
line 94 missing end of the sentence (roughly ????line 192 in how far are the IWV measurements biased by water films on the antenna (or do you just take GNSS IWV and not radiometer IWV?)
line 242 might be "strong rise" better than "stark rise" ?
Citation: https://doi.org/10.5194/egusphere-2025-1819-RC1 -
AC1: 'Reply on RC1', Stephanie Haas, 15 May 2025
We thank the reviewer for the thorough assessment, comments, and constructive feedback.
In response to your major comments:- Thank you for suggesting adding a short description of related studies to the introduction. We added such a paragraph at the end of the introduction:
Finding precursors of rainfall and forecast indices in observation data has been the focus of numerous previous studies. While Cimini et al. (2015) used microwave radiometer profiler data to calculate multiple forecast indices, Wang and Hocke (2022) relied on data from a dual-channel microwave radiometer to investigate local precursors of rainfall events. Data from the Global Positioning System (GPS) and weather station data have been used for the same purpose (Sapucci et al., 2019; Wang et al., 2024). In this study, we leverage the different instruments available in the WEGN3D Open-Air Lab to investigate local HPE precursors in an unprecedented holistic way. - In our study, CAPE is calculated from radiometer-derived T and RH profiles by using the MetPy python package. To clarify this also in the manuscript, we added this information:
All parameters are directly available in the WEGN3D dataset except for the CAPE index, which we calculate from air pressure profiles, and radiometer-derived T and RH profiles using the MetPy Python package (May et al. 2022, version 1.6.3, https://unidata.github.io/MetPy/latest/index.html).
[May, R. M., Goebbert, K. H., Thielen, J. E., Leeman, J. R., Camron, M. D., Bruick, Z., Bruning, E. C., Manser, R. P., Arms, S. C., & Marsh, P. T. (2022). MetPy: A Meteorological Python Library for Data Analysis and Visualization. Bulletin of the American Meteorological Society, 103(10), E2273-E2284. https://doi.org/10.1175/BAMS-D-21-0125.1] - To discuss the potential of near realtime WEGN3D data for nowcasting of precipitation events, we added the following sentences to the discussion:
The WEGN3D’s capability to adequately capture very characteristic features of high-intensity small-scale rainfall events while being solely observation-based (i.e., generated without any models) illustrates the high potential for applications of this dataset in the improvement and verification of weather and climate models. Specifically, the data could be used to develop an experimental nowcasting model for the region. Of particular interest could be the investigation of using atmospheric precursors of (heavy) precipitation in addition to extrapolation-based nowcasting methods (cf. Wang et al., 2024; Bojinski et al., 2023). Given the holistic setup of the instruments, such a model can be adjusted and verified in a very fine-grained manner, potentially serving as a blueprint for improving larger-scale models.
In response to your minor comments:
- Line 24: We see that the sentence was indeed a bit confusing. Thus we changed it according to your suggestions, thank you for bringing that to our attention.
- Incomplete sentences: Apparently there was a problem with the file upload, the sentences you refer to are complete in our local version of the manuscript. We are sorry for that and will make sure that the revised manuscript will not have the same issues.
- Bias of IWV measurements: As mentioned in the manuscript (Data section and Table 1), we only use IWV data from GNSS measurements for this study. The IWV is therefore not biased by the water films on the radiometer housing.
- Line 242: Thank you for that suggestion, we changed “stark rise” to “strong rise”.
Citation: https://doi.org/10.5194/egusphere-2025-1819-AC1 - Thank you for suggesting adding a short description of related studies to the introduction. We added such a paragraph at the end of the introduction:
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AC1: 'Reply on RC1', Stephanie Haas, 15 May 2025
-
RC2: 'Comment on egusphere-2025-1819', Anonymous Referee #2, 06 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1819/egusphere-2025-1819-RC2-supplement.pdf
- AC2: 'Reply on RC2', Stephanie Haas, 07 Jul 2025
Status: closed
-
RC1: 'Comment on egusphere-2025-1819', Anonymous Referee #1, 08 May 2025
The brief article of Haas et al. analyses 94 heavy precipitation events in southeastern Alpine forelands. The authors well describe their datasets and methods. The results of their study are reasonable and interesting showing a clear average behavior of the atmospheric parameters before, during and after convective rainfall events. This research area is of high interest for progress in nowcasting of extreme weather events. Thus, I recommend a publication of this study after a minor revision.
Major comments:1) The Introduction should provide a short overview of related studies, e.g., Cimini et al. 2015: Forecast indices from a ground-based microwave radiometer for operational meteorology , Atmospheric Measurement Techniques , DOI: 10.5194/amt-8-315-2015
2) line 101: a more detailed description or a reference for derivation of CAPE would be interesting.
3) Discussion: it might be interesting if you could discuss the potential of near realtime WEGN3D data for nowcasting of precipitation events
Minor comments:line 24 sentence is not complete. I think it should be:
These short and highly localized (convective) events which strongly influence ....Or divide this long sentence into two sentences.
line 94 missing end of the sentence (roughly ????line 192 in how far are the IWV measurements biased by water films on the antenna (or do you just take GNSS IWV and not radiometer IWV?)
line 242 might be "strong rise" better than "stark rise" ?
Citation: https://doi.org/10.5194/egusphere-2025-1819-RC1 -
AC1: 'Reply on RC1', Stephanie Haas, 15 May 2025
We thank the reviewer for the thorough assessment, comments, and constructive feedback.
In response to your major comments:- Thank you for suggesting adding a short description of related studies to the introduction. We added such a paragraph at the end of the introduction:
Finding precursors of rainfall and forecast indices in observation data has been the focus of numerous previous studies. While Cimini et al. (2015) used microwave radiometer profiler data to calculate multiple forecast indices, Wang and Hocke (2022) relied on data from a dual-channel microwave radiometer to investigate local precursors of rainfall events. Data from the Global Positioning System (GPS) and weather station data have been used for the same purpose (Sapucci et al., 2019; Wang et al., 2024). In this study, we leverage the different instruments available in the WEGN3D Open-Air Lab to investigate local HPE precursors in an unprecedented holistic way. - In our study, CAPE is calculated from radiometer-derived T and RH profiles by using the MetPy python package. To clarify this also in the manuscript, we added this information:
All parameters are directly available in the WEGN3D dataset except for the CAPE index, which we calculate from air pressure profiles, and radiometer-derived T and RH profiles using the MetPy Python package (May et al. 2022, version 1.6.3, https://unidata.github.io/MetPy/latest/index.html).
[May, R. M., Goebbert, K. H., Thielen, J. E., Leeman, J. R., Camron, M. D., Bruick, Z., Bruning, E. C., Manser, R. P., Arms, S. C., & Marsh, P. T. (2022). MetPy: A Meteorological Python Library for Data Analysis and Visualization. Bulletin of the American Meteorological Society, 103(10), E2273-E2284. https://doi.org/10.1175/BAMS-D-21-0125.1] - To discuss the potential of near realtime WEGN3D data for nowcasting of precipitation events, we added the following sentences to the discussion:
The WEGN3D’s capability to adequately capture very characteristic features of high-intensity small-scale rainfall events while being solely observation-based (i.e., generated without any models) illustrates the high potential for applications of this dataset in the improvement and verification of weather and climate models. Specifically, the data could be used to develop an experimental nowcasting model for the region. Of particular interest could be the investigation of using atmospheric precursors of (heavy) precipitation in addition to extrapolation-based nowcasting methods (cf. Wang et al., 2024; Bojinski et al., 2023). Given the holistic setup of the instruments, such a model can be adjusted and verified in a very fine-grained manner, potentially serving as a blueprint for improving larger-scale models.
In response to your minor comments:
- Line 24: We see that the sentence was indeed a bit confusing. Thus we changed it according to your suggestions, thank you for bringing that to our attention.
- Incomplete sentences: Apparently there was a problem with the file upload, the sentences you refer to are complete in our local version of the manuscript. We are sorry for that and will make sure that the revised manuscript will not have the same issues.
- Bias of IWV measurements: As mentioned in the manuscript (Data section and Table 1), we only use IWV data from GNSS measurements for this study. The IWV is therefore not biased by the water films on the radiometer housing.
- Line 242: Thank you for that suggestion, we changed “stark rise” to “strong rise”.
Citation: https://doi.org/10.5194/egusphere-2025-1819-AC1 - Thank you for suggesting adding a short description of related studies to the introduction. We added such a paragraph at the end of the introduction:
-
AC1: 'Reply on RC1', Stephanie Haas, 15 May 2025
-
RC2: 'Comment on egusphere-2025-1819', Anonymous Referee #2, 06 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1819/egusphere-2025-1819-RC2-supplement.pdf
- AC2: 'Reply on RC2', Stephanie Haas, 07 Jul 2025
Data sets
Preprocessed WegenerNet 3D Open-Air Lab data Stephanie J. Haas et al. https://cloud.uni-graz.at/s/cXMi33bfTNHQA8S
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