Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes (ACP/AMT/GMD inter-journal SI)(ACP/AMT/GMD inter-journal SI)
Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes (ACP/AMT/GMD inter-journal SI)(ACP/AMT/GMD inter-journal SI)
Editor(s): GMD topic editors | Coordinators: Silke Troemel Special issue jointly organized between Atmospheric Chemistry and Physics, Atmospheric Measurement Techniques, and Geoscientific Model Development
In April 2017, the Senate of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) established the Priority Programme “Polarimetric Radar Observations meet Atmospheric Modelling (PROM)” (SPP 2115). The programme is designed to run for 6 years and is now in the third funding year. The overall motivation of the SPP PROM is a better understanding and representation of cloud and precipitation processes in numerical weather prediction and climate models. Since 2015 the whole atmosphere over Germany has been monitored by 17 state-of-the-art polarimetric Doppler weather radar observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Data assimilation merges observations and models for state estimation as a prerequisite for prediction and can be regarded as a smart interpolation between observations while exploiting the physical consistency of atmospheric models as mathematical constraints. However, considerable knowledge gaps exist both in radar polarimetry and atmospheric models, which impede the full exploitation of the triangle radar-polarimetry–atmospheric-models–data-assimilation. Objectives of SPP PROM and thus the envisioned publications within the special issue are (1) the exploitation of radar polarimetry for quantitative process detection in precipitating clouds and for model evaluation, (2) the improvement of cloud and precipitation schemes in atmospheric models based on process fingerprints detectable in polarimetric observations, (3) monitoring of the energy budget evolution due to phase changes in the cloudy, precipitating atmosphere for a better understanding of its dynamics, (4) the generation of precipitation system analyses by the assimilation of polarimetric radar observations into atmospheric models for weather forecasting, and (5) radar-based detection of the initiation of convection for the improvement of thunderstorm prediction.

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12 Feb 2024
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024,https://doi.org/10.5194/amt-17-999-2024, 2024
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15 Nov 2023
Assimilation of 3D polarimetric microphysical retrievals in a convective-scale NWP system
Lucas Reimann, Clemens Simmer, and Silke Trömel
Atmos. Chem. Phys., 23, 14219–14237, https://doi.org/10.5194/acp-23-14219-2023,https://doi.org/10.5194/acp-23-14219-2023, 2023
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24 Aug 2023
Numerical evidence that the impact of CCN and INP concentrations on mixed-phase clouds is observable with cloud radars
Junghwa Lee, Patric Seifert, Tempei Hashino, Maximilian Maahn, Fabian Senf, and Oswald Knoth
EGUsphere, https://doi.org/10.5194/egusphere-2023-1887,https://doi.org/10.5194/egusphere-2023-1887, 2023
Revised manuscript under review for ACP (discussion: final response, 4 comments)
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30 Jun 2023
Convective-gust nowcasting based on radar reflectivity and a deep learning algorithm
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628, https://doi.org/10.5194/gmd-16-3611-2023,https://doi.org/10.5194/gmd-16-3611-2023, 2023
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07 Jun 2023
Influence of cloud microphysics schemes on weather model predictions of heavy precipitation
Gregor Köcher, Tobias Zinner, and Christoph Knote
Atmos. Chem. Phys., 23, 6255–6269, https://doi.org/10.5194/acp-23-6255-2023,https://doi.org/10.5194/acp-23-6255-2023, 2023
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20 Apr 2023
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023,https://doi.org/10.5194/amt-16-2089-2023, 2023
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20 Dec 2022
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
Mathias Gergely, Maximilian Schaper, Matthias Toussaint, and Michael Frech
Atmos. Meas. Tech., 15, 7315–7335, https://doi.org/10.5194/amt-15-7315-2022,https://doi.org/10.5194/amt-15-7315-2022, 2022
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03 Nov 2022
Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022,https://doi.org/10.5194/acp-22-14095-2022, 2022
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13 Sep 2022
Ice microphysical processes in the dendritic growth layer: a statistical analysis combining multi-frequency and polarimetric Doppler cloud radar observations
Leonie von Terzi, José Dias Neto, Davide Ori, Alexander Myagkov, and Stefan Kneifel
Atmos. Chem. Phys., 22, 11795–11821, https://doi.org/10.5194/acp-22-11795-2022,https://doi.org/10.5194/acp-22-11795-2022, 2022
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05 Jul 2022
Retrievals of ice microphysical properties using dual-wavelength polarimetric radar observations during stratiform precipitation events
Eleni Tetoni, Florian Ewald, Martin Hagen, Gregor Köcher, Tobias Zinner, and Silke Groß
Atmos. Meas. Tech., 15, 3969–3999, https://doi.org/10.5194/amt-15-3969-2022,https://doi.org/10.5194/amt-15-3969-2022, 2022
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13 Jun 2022
Evaluation of modelled summertime convective storms using polarimetric radar observations
Prabhakar Shrestha, Silke Trömel, Raquel Evaristo, and Clemens Simmer
Atmos. Chem. Phys., 22, 7593–7618, https://doi.org/10.5194/acp-22-7593-2022,https://doi.org/10.5194/acp-22-7593-2022, 2022
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14 Mar 2022
Analytic characterization of random errors in spectral dual-polarized cloud radar observations
Alexander Myagkov and Davide Ori
Atmos. Meas. Tech., 15, 1333–1354, https://doi.org/10.5194/amt-15-1333-2022,https://doi.org/10.5194/amt-15-1333-2022, 2022
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01 Mar 2022
Evaluation of convective cloud microphysics in numerical weather prediction models with dual-wavelength polarimetric radar observations: methods and examples
Gregor Köcher, Tobias Zinner, Christoph Knote, Eleni Tetoni, Florian Ewald, and Martin Hagen
Atmos. Meas. Tech., 15, 1033–1054, https://doi.org/10.5194/amt-15-1033-2022,https://doi.org/10.5194/amt-15-1033-2022, 2022
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24 Jan 2022
Using artificial neural networks to predict riming from Doppler cloud radar observations
Teresa Vogl, Maximilian Maahn, Stefan Kneifel, Willi Schimmel, Dmitri Moisseev, and Heike Kalesse-Los
Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022,https://doi.org/10.5194/amt-15-365-2022, 2022
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17 Jan 2022
Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022,https://doi.org/10.5194/gmd-15-291-2022, 2022
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01 Dec 2021
Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021,https://doi.org/10.5194/acp-21-17291-2021, 2021
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25 Nov 2021
Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations
Markus Karrer, Axel Seifert, Davide Ori, and Stefan Kneifel
Atmos. Chem. Phys., 21, 17133–17166, https://doi.org/10.5194/acp-21-17133-2021,https://doi.org/10.5194/acp-21-17133-2021, 2021
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20 Aug 2021
Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756, https://doi.org/10.5194/amt-14-5735-2021,https://doi.org/10.5194/amt-14-5735-2021, 2021
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10 Mar 2021
Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07)
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021,https://doi.org/10.5194/gmd-14-1295-2021, 2021
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