Bojinski, S., Blaauboer, D., Calbet, X., de Coning, E., Debie, F., Montmerle, T., Nietosvaara, V., Norman, K., Bañón Peregrín, L., Schmid, F., Strelec Mahović, N., and Wapler, K.: Towards nowcasting in Europe in 2030, Meteorological Applications, 30, e2124,
https://doi.org/10.1002/met.2124, 2023.
a
Brenot, H., Neméghaire, J., Delobbe, L., Clerbaux, N., De Meutter, P., Deckmyn, A., Delcloo, A., Frappez, L., and Van Roozendael, M.: Preliminary signs of the initiation of deep convection by GNSS, Atmos. Chem. Phys., 13, 5425–5449,
https://doi.org/10.5194/acp-13-5425-2013, 2013.
a
Cimini, D., Nelson, M., Güldner, J., and Ware, R.: Forecast indices from a ground-based microwave radiometer for operational meteorology, Atmos. Meas. Tech., 8, 315–333,
https://doi.org/10.5194/amt-8-315-2015, 2015.
a
Crewell, S. and Löhnert, U.: Accuracy of cloud liquid water path from ground-based microwave radiometry 2. Sensor accuracy and synergy, Radio Science, 38,
https://doi.org/10.1029/2002RS002634, 2003.
a
Elgered, G., Ning, T., Diamantidis, P.-K., and Nilsson, T.: Assessment of GNSS stations using atmospheric horizontal gradients and microwave radiometry, Global Navigation Satellite Systems: Recent Scientific Advances, 74, 2583–2592,
https://doi.org/10.1016/j.asr.2023.05.010, 2024.
a
Elósegui, P., Davis, J. L., Gradinarsky, L. P., Elgered, G., Johansson, J. M., Tahmoush, D. A., and Rius, A.: Sensing atmospheric structure using small-scale space geodetic networks, Geophysical Research Letters, 26, 2445–2448,
https://doi.org/10.1029/1999GL900585, 1999.
a
Feister, U., Möller, H., Sattler, T., Shields, J., Görsdorf, U., and Güldner, J.: Comparison of macroscopic cloud data from ground-based measurements using VIS/NIR and IR instruments at Lindenberg, Germany, Atmospheric Research, 96, 395–407,
https://doi.org/10.1016/j.atmosres.2010.01.012, 2010.
a
Fuchsberger, J., Kirchengast, G., and Kabas, T.: WegenerNet high-resolution weather and climate data from 2007 to 2020, Earth Syst. Sci. Data, 13, 1307–1334,
https://doi.org/10.5194/essd-13-1307-2021, 2021.
a
Fuchsberger, J., Kirchengast, G., and Bichler, C.: WegenerNet climate station network Level 2 data version 8.0 (2007–2024), Wegener Center for Climate and Global Change [data set], University of Graz, Austria,
https://doi.org/10.25364/WEGC/WPS8.0-2025.1, 2025.
a,
b
Gartzke, J., Knuteson, R., Przybyl, G., Ackerman, S., and Revercomb, H.: Comparison of Satellite-, Model-, and Radiosonde-
Derived Convective Available Potential Energy in the Southern Great Plains Region, Journal of Applied Meteorology and Climatology, 56, 1499–1513,
https://doi.org/10.1175/JAMC-D-16-0267.1, 2017.
a
Haas, S. J., Kirchengast, G., and Fuchsberger, J.: Exploring possible climate change amplification of warm-season precipitation extremes in the southeastern Alpine forelands at regional to local scales, Journal of Hydrology: Regional Studies, 56, 101987,
https://doi.org/10.1016/j.ejrh.2024.101987, 2024.
a
Haslinger, K., Breinl, K., Pavlin, L., Pistotnik, G., Bertola, M., Olefs, M., Greilinger, M., Schöner, W., and Blöschl, G.: Increasing hourly heavy rainfall in Austria reflected in flood changes, Nature, 639, 667–672,
https://doi.org/10.1038/s41586-025-08647-2, 2025.
a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set],
https://doi.org/10.24381/cds.bd0915c6, 2023a.
a,
b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set],
https://doi.org/10.24381/cds.adbb2d47, 2023b.
a,
b
Hocking, T.: Improving WegenerNet temperature data products by advancing lapse rate and grid construction algorithms, Master's thesis, University of Graz, Graz, AT,
https://wegenernet.org/downloads/Hocking-2020-WegNet_lapserates.pdf (last access: 15 September 2025), 2020. a
IPCC: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, a Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change,
https://doi.org/10.13140/2.1.3117.9529, 2012.
a
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, vol. In Press, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA,
https://doi.org/10.1017/9781009157896, 2021.
a,
b
Kabas, T., Leuprecht, A., Bichler, C., and Kirchengast, G.: WegenerNet climate station network region Feldbach, Austria: network structure, processing system, and example results, Adv. Sci. Res., 6, 49–54,
https://doi.org/10.5194/asr-6-49-2011, 2011.
a
Kirchengast, G., Kabas, T., Leuprecht, A., Bichler, C., and Truhetz, H.: WegenerNet: A Pioneering High-Resolution Network for Monitoring Weather and Climate, Bulletin of the American Meteorological Society, 95, 227–242,
https://doi.org/10.1175/BAMS-D-11-00161.1, 2014.
a,
b
Kirsch, B., Hohenegger, C., and Ament, F.: Morphology and growth of convective cold pools observed by a dense station network in Germany, Quarterly Journal of the Royal Meteorological Society, 150, 857–876,
https://doi.org/10.1002/qj.4626, 2024.
a
Kvas, A., Fuchsberger, J., Kirchengast, G., and Scheidl, D.: WegenerNet 3D Open-Air Laboratory Level 2 Data, Version 1.0, Wegener Center for Climate and Global Change, University of Graz, Austria [data set],
https://doi.org/10.25364/WEGC/WPS3D-L2-10, 2024.
a,
b
Kvas, A., Kirchengast, G., and Fuchsberger, J.: High-resolution atmospheric data cubes from the WegenerNet 3D Open-Air Laboratory for Climate Change Research, Earth Syst. Sci. Data Discuss. [preprint],
https://doi.org/10.5194/essd-2025-176, in review, 2025.
a,
b
Laj, P., Lund Myhre, C., Riffault, V., Amiridis, V., Fuchs, H., Eleftheriadis, K., Petäjä, T., Salameh, T., Kivekäs, N., Juurola, E., Saponaro, G., Philippin, S., Cornacchia, C., Alados Arboledas, L., Baars, H., Claude, A., De Mazière, M., Dils, B., Dufresne, M., Evangeliou, N., Favez, O., Fiebig, M., Haeffelin, M., Herrmann, H., Höhler, K., Illmann, N., Kreuter, A., Ludewig, E., Marinou, E., Möhler, O., Mona, L., Eder Murberg, L., Nicolae, D., Novelli, A., O'Connor, E., Ohneiser, K., Petracca Altieri, R. M., Picquet-Varrault, B., van Pinxteren, D., Pospichal, B., Putaud, J.-P., Reimann, S., Siomos, N., Stachlewska, I., Tillmann, R., Voudouri, K. A., Wandinger, U., Wiedensohler, A., Apituley, A., Comerón, A., Gysel-Beer, M., Mihalopoulos, N., Nikolova, N., Pietruczuk, A., Sauvage, S., Sciare, J., Skov, H., Svendby, T., Swietlicki, E., Tonev, D., Vaughan, G., Zdimal, V., Baltensperger, U., Doussin, J.-F., Kulmala, M., Pappalardo, G., Sorvari Sundet, S., and Vana, M.: Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS): The European Research Infrastructure Supporting Atmospheric Science, Bulletin of the American Meteorological Society, 105, E1098–E1136,
https://doi.org/10.1175/BAMS-D-23-0064.1, 2024.
a
Löhnert, U. and Crewell, S.: Accuracy of cloud liquid water path from ground-based microwave radiometry 1. Dependency on cloud model statistics, Radio Science, 38,
https://doi.org/10.1029/2002RS002654, 2003.
a,
b,
c
Mateos, R. M., Sarro, R., Díez-Herrero, A., Reyes-Carmona, C., López-Vinielles, J., Ezquerro, P., Martínez-Corbella, M., Bru, G., Luque, J. A., Barra, A., Martín, P., Millares, A., Ortega, M., López, A., Galve, J. P., Azañón, J. M., Pereira, S., Santos, P. P., Zêzere, J. L., Reis, E., Garcia, R. A. C., Oliveira, S. C., Villatte, A., Chanal, A., Gasc-Barbier, M., and Monserrat, O.: Assessment of the Socio-Economic Impacts of Extreme Weather Events on the Coast of Southwest Europe during the Period 2009–2020, Applied Sciences, 13,
https://doi.org/10.3390/app13042640, 2023.
a
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., and Marsh, P. T.: MetPy: A Meteorological Python Library for Data Analysis and Visualization, Bulletin of the American Meteorological Society, 103, E2273–E2284,
https://doi.org/10.1175/BAMS-D-21-0125.1, 2022.
a
Männel, B., Zus, F., Dick, G., Glaser, S., Semmling, M., Balidakis, K., Wickert, J., Maturilli, M., Dahlke, S., and Schuh, H.: GNSS-based water vapor estimation and validation during the MOSAiC expedition, Atmos. Meas. Tech., 14, 5127–5138,
https://doi.org/10.5194/amt-14-5127-2021, 2021.
a
Niell, A. E., Coster, A. J., Solheim, F. S., Mendes, V. B., Toor, P. C., Langley, R. B., and Upham, C. A.: Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI, Journal of Atmospheric and Oceanic Technology, 18, 830–850,
https://doi.org/10.1175/1520-0426(2001)018<0830:COMOAW>2.0.CO;2, 2001.
a,
b
Ning, T., Wickert, J., Deng, Z., Heise, S., Dick, G., Vey, S., and Schöne, T.: Homogenized Time Series of the Atmospheric Water Vapor Content Obtained from the GNSS Reprocessed Data, Journal of Climate, 29, 2443–2456,
https://doi.org/10.1175/JCLI-D-15-0158.1, 2016.
a
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A network suitable microwave radiometer for operational monitoring of the cloudy atmosphere, CLIWA-NET: Observation and Modelling of Liquid Water Clouds, Atmospheric Research, 75, 183–200,
https://doi.org/10.1016/j.atmosres.2004.12.005, 2005.
a
Sapucci, L. F., Machado, L. A. T., de Souza, E. M., and Campos, T. B.: Global Positioning System precipitable water vapour (GPS-PWV) jumps before intense rain events: A potential application to nowcasting, Meteorological Applications, 26, 49–63,
https://doi.org/10.1002/met.1735, 2019.
a,
b,
c
Schroeer, K. and Tye, M. R.: Quantifying damage contributions from convective and stratiform weather types: How well do precipitation and discharge data indicate the risk?, Journal of Flood Risk Management, 12, e12491,
https://doi.org/10.1111/jfr3.12491, 2019.
a,
b
Solheim, F. S., Vivekanandan, J., Ware, R. H., and Rocken, C.: Propagation delays induced in GPS signals by dry air, water vapor, hydrometeors, and other particulates, Journal of Geophysical Research: Atmospheres, 104, 9663–9670,
https://doi.org/10.1029/1999JD900095, 1999.
a
Sun, J., Xue, M., Wilson, J. W., Zawadzki, I., Ballard, S. P., Onvlee-Hooimeyer, J., Joe, P., Barker, D. M., Li, P., Golding, B., Xu, M., and Pinto, J.: Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges, Bulletin of the American Meteorological Society, 95, 409–426,
https://doi.org/10.1175/BAMS-D-11-00263.1, 2014.
a
Taszarek, M., Allen, J., Púčik, T., Groenemeijer, P., Czernecki, B., Kolendowicz, L., Lagouvardos, K., Kotroni, V., and Schulz, W.: A climatology of thunderstorms across Europe from a synthesis of multiple data sources, Journal of Climate, 32, 1813–1837,
https://doi.org/10.1175/JCLI-D-18-0372.1, 2019.
a
Toporov, M. and Löhnert, U.: Synergy of Satellite- and Ground-Based Observations for Continuous Monitoring of Atmospheric Stability, Liquid Water Path, and Integrated Water Vapor: Theoretical Evaluations Using Reanalysis and Neural Networks, Journal of Applied Meteorology and Climatology, 59, 1153–1170,
https://doi.org/10.1175/JAMC-D-19-0169.1, 2020.
a
Walbröl, A., Crewell, S., Engelmann, R., Orlandi, E., Griesche, H., Radenz, M., Hofer, J., Althausen, D., Maturilli, M., and Ebell, K.: Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC, Scientific Data, 9, 534,
https://doi.org/10.1038/s41597-022-01504-1, 2022.
a
Walbröl, A., Griesche, H. J., Mech, M., Crewell, S., and Ebell, K.: Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products, Atmos. Meas. Tech., 17, 6223–6245,
https://doi.org/10.5194/amt-17-6223-2024, 2024.
a
Wang, W. and Hocke, K.: Atmospheric Effects and Precursors of Rainfall over the Swiss Plateau, Remote Sensing, 14,
https://doi.org/10.3390/rs14122938, 2022.
a,
b,
c,
d,
e,
f
Wang, W., Hocke, K., Nania, L., Cazorla, A., Titos, G., Matthey, R., Alados-Arboledas, L., Millares, A., and Navas-Guzmán, F.: Inter-relations of precipitation, aerosols, and clouds over Andalusia, southern Spain, revealed by the Andalusian Global ObseRvatory of the Atmosphere (AGORA), Atmos. Chem. Phys., 24, 1571–1585,
https://doi.org/10.5194/acp-24-1571-2024, 2024.
a,
b,
c,
d
