Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-2855-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-2855-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
11 Jul 2019
Model evaluation paper |
| 11 Jul 2019
| 11 Jul 2019
A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain
Christoph Schlager
CORRESPONDING AUTHOR
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Gottfried Kirchengast
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Juergen Fuchsberger
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Alexander Kann
Department of Forecasting Models, Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria
Heimo Truhetz
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Related authors
Christoph Schlager, Gottfried Kirchengast, and Juergen Fuchsberger
Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, https://doi.org/10.5194/amt-11-5607-2018, 2018
Short summary
Short summary
In this work we further developed and evaluated an operational weather diagnostic application, the WegenerNet Wind Product Generator (WPG), and applied it to the WegenerNet Johnsbachtal (JBT), a dense meteorological station network located in a mountainous Alpine region. The WPG automatically generates gridded high-resolution wind fields in near-real time with a temporal resolution of 30 min and a spatial resolution of 100 m x 100 m.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech., 18, 265–286, https://doi.org/10.5194/amt-18-265-2025, https://doi.org/10.5194/amt-18-265-2025, 2025
Short summary
Short summary
Due to the shortcomings of available observations, having accurate global 3D wind fields remains a challenge. A promising option is radio occultation (RO) satellite data, which enable the derivation of winds based on wind approximations. We test how well RO winds describe the ERA5 winds. We separate the total wind difference into the approximation bias and the systematic difference between the two datasets. The results show the utility of RO winds for climate monitoring and analyses.
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024, https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Short summary
We investigated the potential of radio occultation (RO) data for climate-oriented wind field monitoring, focusing on the equatorial band within ±5° latitude. In this region, the geostrophic balance breaks down, and the equatorial balance approximation takes over. The study encourages the use of RO wind fields for mesoscale climate monitoring for the equatorial region, showing a small improvement in the troposphere when including the meridional wind in the zonal-mean total wind speed.
Josef Innerkofler, Gottfried Kirchengast, Marc Schwärz, Christian Marquardt, and Yago Andres
Atmos. Meas. Tech., 16, 5217–5247, https://doi.org/10.5194/amt-16-5217-2023, https://doi.org/10.5194/amt-16-5217-2023, 2023
Short summary
Short summary
Atmosphere remote sensing using GNSS radio occultation provides a highly valuable basis for atmospheric and climate science. For the highest-quality demands, the Wegener Center set up a rigorous system for processing low-level measurement data. This excess-phase processing setup includes integrated quality control and uncertainty estimation. It was successfully evaluated and inter-compared, ensuring the capability of producing reliable long-term data records for climate applications.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-100, https://doi.org/10.5194/amt-2023-100, 2023
Revised manuscript not accepted
Short summary
Short summary
As global wind measurements are limited by low spatial coverage or lack of vertical profile information, radio occultation (RO) satellite data might be of help. Wind fields are indirectly retrieved using the geostrophic approximation. We first test how well the method performs, finding agreement better than 2 m/s in wind speed. In a second step, we investigate how good RO and reanalysis data compare. The results suggest that RO-derived wind fields provide added value for climate monitoring.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Ying Li, Gottfried Kirchengast, Marc Schwaerz, and Yunbin Yuan
Atmos. Chem. Phys., 23, 1259–1284, https://doi.org/10.5194/acp-23-1259-2023, https://doi.org/10.5194/acp-23-1259-2023, 2023
Short summary
Short summary
We develop a new approach to monitor sudden stratospheric warming (SSW) events since 1980 and develop a 42-year SSW event climatology. Detection and evaluation results suggest that the new method is robust for SSW monitoring. We also found an increase in the duration of SSW main-phase warmings of about 5(±2) d over the three decades from the 1980s to the 2010s, raising the average duration from about 10 to 15 d, and the warming strength is also found increased.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Esmail Ghaemi, Ulrich Foelsche, Alexander Kann, and Jürgen Fuchsberger
Hydrol. Earth Syst. Sci., 25, 4335–4356, https://doi.org/10.5194/hess-25-4335-2021, https://doi.org/10.5194/hess-25-4335-2021, 2021
Short summary
Short summary
We assess an operational merged gauge–radar precipitation product over a period of 12 years, using gridded precipitation fields from a dense gauge network (WegenerNet) in southeastern Austria. We analyze annual data, seasonal data, and extremes using different metrics. We identify individual events using a simple threshold based on the interval between two consecutive events and evaluate the events' characteristics in both datasets.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
Short summary
Short summary
We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Jürgen Fuchsberger, Gottfried Kirchengast, and Thomas Kabas
Earth Syst. Sci. Data, 13, 1307–1334, https://doi.org/10.5194/essd-13-1307-2021, https://doi.org/10.5194/essd-13-1307-2021, 2021
Short summary
Short summary
The paper describes the most recent weather and climate data from the WegenerNet station networks, providing hydrometeorological measurements since 2007 at very high spatial and temporal resolution for long-term observation in two regions in southeastern Austria: the WegenerNet Feldbach Region, in the Alpine forelands, comprising 155 stations with 1 station about every 2 km2, and the WegenerNet Johnsbachtal, in a mountainous region, with 14 stations at altitudes from about 600 m to 2200 m.
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech., 14, 853–867, https://doi.org/10.5194/amt-14-853-2021, https://doi.org/10.5194/amt-14-853-2021, 2021
Short summary
Short summary
Currently, the canonical transform (CT) approach to the processing of radio occultation observations is widely used. For the spherically symmetric atmosphere, the applicability of this method can be strictly proven. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a generalization of the CT method in order to reduce the errors due to horizontal gradients.
Pierre-Yves Tournigand, Valeria Cigala, Elzbieta Lasota, Mohammed Hammouti, Lieven Clarisse, Hugues Brenot, Fred Prata, Gottfried Kirchengast, Andrea K. Steiner, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 3139–3159, https://doi.org/10.5194/essd-12-3139-2020, https://doi.org/10.5194/essd-12-3139-2020, 2020
Short summary
Short summary
The detection and monitoring of volcanic clouds are important for aviation management, climate and weather forecasts. We present in this paper the first comprehensive archive collecting spatial and temporal information about volcanic clouds generated by the 11 largest eruptions of this century. We provide a complete set of state-of-the-art data allowing the development and testing of new algorithms contributing to improve the accuracy of the estimation of fundamental volcanic cloud parameters.
Elżbieta Lasota, Andrea K. Steiner, Gottfried Kirchengast, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 2679–2693, https://doi.org/10.5194/essd-12-2679-2020, https://doi.org/10.5194/essd-12-2679-2020, 2020
Short summary
Short summary
In this work, we provide a comprehensive archive of tropical cyclone vertical structure for the period 2001–2018. The tropical cyclone best tracks are co-located in time and space with high-vertical-resolution atmospheric profiles (temperature, pressure, humidity and refractivity) from radio occultations and with climatological profiles. This dataset can be used to analyze the inner vertical thermodynamic structure of tropical cyclones and the pre-cyclone environment.
Clara Hohmann, Gottfried Kirchengast, Sungmin O, Wolfgang Rieger, and Ulrich Foelsche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-453, https://doi.org/10.5194/hess-2020-453, 2020
Manuscript not accepted for further review
Short summary
Short summary
Heavy precipitation events are still feeding with a large uncertainty into hydrological models. Based on the highly dense station network WegenerNet (one station per 2 km2) we analyzed the sensitivity of runoff simulations to different rain network densities and interpolation methods in small catchments. We find, and quantify relevant characteristics, that runoff curves especially from
short-duration convective rainfall events are strongly influenced by gauge station density and distribution.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Andrea K. Steiner, Florian Ladstädter, Chi O. Ao, Hans Gleisner, Shu-Peng Ho, Doug Hunt, Torsten Schmidt, Ulrich Foelsche, Gottfried Kirchengast, Ying-Hwa Kuo, Kent B. Lauritsen, Anthony J. Mannucci, Johannes K. Nielsen, William Schreiner, Marc Schwärz, Sergey Sokolovskiy, Stig Syndergaard, and Jens Wickert
Atmos. Meas. Tech., 13, 2547–2575, https://doi.org/10.5194/amt-13-2547-2020, https://doi.org/10.5194/amt-13-2547-2020, 2020
Short summary
Short summary
High-quality observations are critically important for monitoring the Earth’s changing climate. We provide information on the consistency and long-term stability of observations from GPS radio occultation (RO). We assess, for the first time, RO records from multiple RO missions and all major RO data providers. Our results quantify where RO can be used for reliable trend assessment and confirm its climate quality.
Yueqiang Sun, Weihua Bai, Congliang Liu, Yan Liu, Qifei Du, Xianyi Wang, Guanglin Yang, Mi Liao, Zhongdong Yang, Xiaoxin Zhang, Xiangguang Meng, Danyang Zhao, Junming Xia, Yuerong Cai, and Gottfried Kirchengast
Atmos. Meas. Tech., 11, 5797–5811, https://doi.org/10.5194/amt-11-5797-2018, https://doi.org/10.5194/amt-11-5797-2018, 2018
Short summary
Short summary
The GNSS Occultation Sounder (GNOS) is one of the new-generation payloads on board the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth’s neutral atmosphere and ionosphere. FY-3C GNOS, on board the FY-3 series C satellite launched in September 2013, was designed to acquire setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BDS and the US GPS. This paper reviews the FY-3C GNOS mission.
Christian Reszler, Matthew Blaise Switanek, and Heimo Truhetz
Nat. Hazards Earth Syst. Sci., 18, 2653–2674, https://doi.org/10.5194/nhess-18-2653-2018, https://doi.org/10.5194/nhess-18-2653-2018, 2018
Short summary
Short summary
Small-scale floods are a consequence of high rainfall rates in small areas that can occur along frontal activity and convective storms. This situation is expected to become more severe due to a warming climate. This study shows the test of fine-gridded (~ 3 km spacing) climate models combined with error-correction techniques for flood modelling in small- and medium-sized catchments. Results are promising, but further research is needed so these models can be applied in climate change studies.
Christoph Schlager, Gottfried Kirchengast, and Juergen Fuchsberger
Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, https://doi.org/10.5194/amt-11-5607-2018, 2018
Short summary
Short summary
In this work we further developed and evaluated an operational weather diagnostic application, the WegenerNet Wind Product Generator (WPG), and applied it to the WegenerNet Johnsbachtal (JBT), a dense meteorological station network located in a mountainous Alpine region. The WPG automatically generates gridded high-resolution wind fields in near-real time with a temporal resolution of 30 min and a spatial resolution of 100 m x 100 m.
Congliang Liu, Gottfried Kirchengast, Yueqiang Sun, Kefei Zhang, Robert Norman, Marc Schwaerz, Weihua Bai, Qifei Du, and Ying Li
Atmos. Meas. Tech., 11, 2427–2440, https://doi.org/10.5194/amt-11-2427-2018, https://doi.org/10.5194/amt-11-2427-2018, 2018
Short summary
Short summary
In this study, we focused on investigating the causes of the higher-order residual ionospheric error (RIE) in the GNSS RO events, by employing detailed along-ray-path analyses of atmospheric and ionospheric refractivities, impact parameter changes, and bending angles and RIEs under asymmetric and symmetric ionospheric structures. We found that the main causes of the high RIEs are a combination of physics-based effects, where asymmetric ionospheric conditions play the primary role.
Weihua Bai, Congliang Liu, Xiangguang Meng, Yueqiang Sun, Gottfried Kirchengast, Qifei Du, Xianyi Wang, Guanglin Yang, Mi Liao, Zhongdong Yang, Danyang Zhao, Junming Xia, Yuerong Cai, Lijun Liu, and Dongwei Wang
Atmos. Meas. Tech., 11, 819–833, https://doi.org/10.5194/amt-11-819-2018, https://doi.org/10.5194/amt-11-819-2018, 2018
Short summary
Short summary
In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing. From the statistics, average bias (and standard deviation) of the bending angle and refractivity profiles were found to be as small as about 0.05–0.2 % (and 0.7–1.6 %) over the upper troposphere and lower stratosphere, including for the GEO, IGSO, and MEO subsets. Zero differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise.
Michael E. Gorbunov and Gottfried Kirchengast
Atmos. Meas. Tech., 11, 111–125, https://doi.org/10.5194/amt-11-111-2018, https://doi.org/10.5194/amt-11-111-2018, 2018
Short summary
Short summary
We study the systematic discreapancies between atmospheric refractivity derived from radio occulation (RO) sounding of the Earth's atmosphere and the reanalyses of the European Centre for Medium-Range Weather Forecasts. We construct a regression-based bias model. The model can be used for the RO data propagation in the new reference occultation processing system (rOPS) including the uncertainty propagation through the retrieval chain.
Sungmin O, Ulrich Foelsche, Gottfried Kirchengast, Juergen Fuchsberger, Jackson Tan, and Walter A. Petersen
Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, https://doi.org/10.5194/hess-21-6559-2017, 2017
Short summary
Short summary
We evaluate gridded satellite rainfall estimates, from GPM IMERG, through a direct grid-to-grid comparison with gauge data from the WegenerNet Feldbach (WEGN) network in southeastern Austria. As the WEGN data are independent of the IMERG gauge adjustment process, we could analyze the IMERG estimates across its three different runs. Our results show the effects of additional retrieval processes on the final rainfall estimates, and consequently provide IMERG accuracy information for data users.
Barbara Angerer, Florian Ladstädter, Barbara Scherllin-Pirscher, Marc Schwärz, Andrea K. Steiner, Ulrich Foelsche, and Gottfried Kirchengast
Atmos. Meas. Tech., 10, 4845–4863, https://doi.org/10.5194/amt-10-4845-2017, https://doi.org/10.5194/amt-10-4845-2017, 2017
Short summary
Short summary
We present a detailed analysis of the latest Wegener Center GPS radio occultation reprocessing (OPSv5.6) output. Knowledge of differences in data quality, as well as of data consistency, is essential when combining data from different missions to a long-term climate record. We compare quality aspects of the various processed satellite missions and present satellite-dependent variations. Temperature data from various satellites are found to be highly consistent within 8 to 25 km.
Theresa Schellander-Gorgas, Yong Wang, Florian Meier, Florian Weidle, Christoph Wittmann, and Alexander Kann
Geosci. Model Dev., 10, 35–56, https://doi.org/10.5194/gmd-10-35-2017, https://doi.org/10.5194/gmd-10-35-2017, 2017
Short summary
Short summary
Ensemble forecasting offers a useful method to simulate the uncertainty of a numerical forecast model for each individual forecast run. This study compares ALADIN-LAEF, a 16-member ensemble with a resolution of 11 km that combines several perturbation methods, with AROME-EPS, which downscales the members of ALADIN-LAEF to 2.5 km resolution. The verification shows that there are benefits of a higher-resolution ensemble, especially for highly localized precipitation and for mountainous terrain.
Ingo Meirold-Mautner, Alexander Kann, and Florian Meier
Adv. Sci. Res., 13, 27–35, https://doi.org/10.5194/asr-13-27-2016, https://doi.org/10.5194/asr-13-27-2016, 2016
Short summary
Short summary
In this study a precipitation nowcasting method is developed which relies on satellite products and automatic weather station data only. It thus omits ground based radar observations which are not readily available in large parts of the world. The system shows improved skill when compared to numerical weather prediction models for analysis and for lead times up to one hour. This type of nowcasting could be valuable in data sparse regions where radar observations are lacking or of poor quality.
Riccardo Biondi, Andrea Steiner, Gottfried Kirchengast, Hugues Brenot, and Therese Rieckh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2015-974, https://doi.org/10.5194/acp-2015-974, 2016
Revised manuscript not accepted
Short summary
Short summary
Cloud structure and cloud top height are key parameters for the monitoring of volcanic cloud movement and for characterizing eruptive processes and understanding the impact on short-term climate variability.
We have studied the eruption of Nabro volcano, which has been recognized as the largest stratospheric sulfur injection since Pinatubo (1991) and we have found a clear warming signature after the eruption of Nabro persisting for a few months.
Y. Li, G. Kirchengast, B. Scherllin-Pirscher, R. Norman, Y. B. Yuan, J. Fritzer, M. Schwaerz, and K. Zhang
Atmos. Meas. Tech., 8, 3447–3465, https://doi.org/10.5194/amt-8-3447-2015, https://doi.org/10.5194/amt-8-3447-2015, 2015
Short summary
Short summary
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System-based radio occultation measurements. The new algorithm is evaluated against the OPSv5.6 algorithm developed by the Wegener Center using both simulated and real observed data. It is found that the algorithm can significantly reduce the random errors of optimized bending angles. The retrieved refractivity and temperature profiles are also benefited.
V. Proschek, G. Kirchengast, S. Schweitzer, J. S. A. Brooke, P. F. Bernath, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher
Atmos. Meas. Tech., 8, 3315–3336, https://doi.org/10.5194/amt-8-3315-2015, https://doi.org/10.5194/amt-8-3315-2015, 2015
C. L. Liu, G. Kirchengast, K. Zhang, R. Norman, Y. Li, S. C. Zhang, J. Fritzer, M. Schwaerz, S. Q. Wu, and Z. X. Tan
Atmos. Meas. Tech., 8, 2999–3019, https://doi.org/10.5194/amt-8-2999-2015, https://doi.org/10.5194/amt-8-2999-2015, 2015
A. Plach, V. Proschek, and G. Kirchengast
Atmos. Meas. Tech., 8, 2813–2825, https://doi.org/10.5194/amt-8-2813-2015, https://doi.org/10.5194/amt-8-2813-2015, 2015
Short summary
Short summary
This paper discusses simulation results of a newly developed line-of-sight wind retrieval algorithm expanding an existing simulation framework that includes the retrieval of thermodynamic variables and greenhouse gases in the upper troposphere/lower stratosphere region. The underlying mission concept further develops the radio occultation technique (i.e. satellite remote sensing technique scanning the atmosphere with high vertical resolution) employing microwave and infrared-laser signals.
R. Biondi, A. K. Steiner, G. Kirchengast, and T. Rieckh
Atmos. Chem. Phys., 15, 5181–5193, https://doi.org/10.5194/acp-15-5181-2015, https://doi.org/10.5194/acp-15-5181-2015, 2015
F. Ladstädter, A. K. Steiner, M. Schwärz, and G. Kirchengast
Atmos. Meas. Tech., 8, 1819–1834, https://doi.org/10.5194/amt-8-1819-2015, https://doi.org/10.5194/amt-8-1819-2015, 2015
M. Suklitsch, A. Kann, and B. Bica
Adv. Sci. Res., 12, 51–55, https://doi.org/10.5194/asr-12-51-2015, https://doi.org/10.5194/asr-12-51-2015, 2015
Short summary
Short summary
Ensemble prediction systems are becoming of more and more interest for various applications. They are used to account for uncertainties that exist from the very beginning of a forecast due to the chaotic behavior of atmospheric processes as well as approximations in numerical models. Ensemble nowcasting systems are therefore increasingly requested by end users. In this study we show that En-INCA, an integrated probabilistic nowcasting system, is able to improve existing state-of-the-art LAM-EPS.
A. Kann, I. Meirold-Mautner, F. Schmid, G. Kirchengast, J. Fuchsberger, V. Meyer, L. Tüchler, and B. Bica
Hydrol. Earth Syst. Sci., 19, 1547–1559, https://doi.org/10.5194/hess-19-1547-2015, https://doi.org/10.5194/hess-19-1547-2015, 2015
Short summary
Short summary
The paper introduces a high resolution precipitation analysis system which operates on 1 km x 1 km resolution with high frequency updates of 5 minutes. The ability of such a system to adequately assess the convective precipitation distribution is evaluated by means of an independant, high resolution station network. This dense station network allows for a thorough evaluation of the analyses under different convective situations and of the representativeness error of raingaue measurements.
A. K. Steiner, D. Hunt, S.-P. Ho, G. Kirchengast, A. J. Mannucci, B. Scherllin-Pirscher, H. Gleisner, A. von Engeln, T. Schmidt, C. Ao, S. S. Leroy, E. R. Kursinski, U. Foelsche, M. Gorbunov, S. Heise, Y.-H. Kuo, K. B. Lauritsen, C. Marquardt, C. Rocken, W. Schreiner, S. Sokolovskiy, S. Syndergaard, and J. Wickert
Atmos. Chem. Phys., 13, 1469–1484, https://doi.org/10.5194/acp-13-1469-2013, https://doi.org/10.5194/acp-13-1469-2013, 2013
Related subject area
Atmospheric sciences
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
Short summary
Short summary
Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
Short summary
Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
Short summary
Short summary
Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
Short summary
Short summary
Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
Short summary
Short summary
Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
Short summary
Short summary
Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
Short summary
Short summary
Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Cited articles
Abdel-Aal, R., Elhadidy, M., and Shaahid, S.: Modeling and forecasting the mean
hourly wind speed time series using GMDH-based abductive networks, Renew.
Ener., 34, 1686–1699, https://doi.org/10.1016/j.renene.2009.01.001, 2009. a
Awan, N. K., Truhetz, H., and Gobiet, A.: Parameterization-induced error
characteristics of MM5 and WRF operated in climate mode over the alpine
region: An ensemble-based analysis, J. Climate, 24, 3107–3123,
https://doi.org/10.1175/2011JCLI3674.1, 2011. a
Bartalev, S., Belward, A., Ershov, D., and S. Isaev, A.: A new SPOT4-VEGETATION
derived land cover map of Northern Eurasia, Int. J. Remote Sens., 24,
1977–1982, https://doi.org/10.1080/0143116031000066297, 2003. a
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell,
M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric
variability with the ECMWF model: From synoptic to decadal time-scales,
Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008. a
Bellasio, R., Maffeis, G., Scire, J. S., Longoni, M. G., Bianconi, R., and
Quaranta, N.: Algorithms to Account for Topographic Shading Effects and
Surface Temperature Dependence on Terrain Elevation in Diagnostic
Meteorological Models, Bound.-Lay. Meteor., 114, 595–614,
https://doi.org/10.1007/s10546-004-1670-6, 2005. a, b
Böhm, U., Kücken, M., Ahrens, W., Block, A., Hauffe, D., Keuler, B., Rockel,
B., and Will, A.: CLM-The Climate Version of LM: Brief Description and
Long-Term Applications, 225–236, Deutscher Wetterdienst (DWD), 6 Edn.,
available at:
http://www.cosmo-model.org/content/model/documentation/newsLetters/newsLetter06/newsLetter_06.pdf (last access: 2 July 2019),
2006. a
Bubnová, R., Hello, G., Bénard, P., and Geleyn, J.-F.: Integration of the
Fully Elastic Equations Cast in the Hydrostatic Pressure Terrain-Following
Coordinate in the Framework of the ARPEGE/Aladin NWP System, Mon. Weather Rev., 123, 515–535, https://doi.org/10.1175/1520-0493(1995)123<0515:IOTFEE>2.0.CO;2,
1995. a
Cox, R. M., Sontowski, J., and Dougherty, C. M.: An evaluation of three
diagnostic wind models (CALMET, MCSCIPUF, and SWIFT) with wind data from the
Dipole Pride 26 field experiments, Meteor. Appl., 12, 329–341,
https://doi.org/10.1017/S1350482705001908, 2005. a, b
Davies, H. C.: A lateral boundary formulation for multi-level prediction
models, Q. J. Roy. Meteor. Soc., 102, 405–418,
https://doi.org/10.1002/qj.49710243210, 1976. a
Deutscher Wetterdienst: Climate Limited-area Modelling Community, available at: https://www.clm-community.eu, last access: 2 July 2019. a
Exponent, Inc.: CALPUFF Modeling System, Exponent Engineering and Scientific Consulting, available at: http://www.src.com (last access: 2 July 2019), 2018. a
Gal-Chen, T. and Somerville, R. C.: On the use of a coordinate transformation
for the solution of the Navier-Stokes equations, J. Comput. Phys., 17, 209–228, https://doi.org/10.1016/0021-9991(75)90037-6, 1975. a
Gerard, L. and Geleyn, J.-F.: Evolution of a subgrid deep convection
parametrization in a limited-area model with increasing resolution, Q. J. Roy. Meteor. Soc., 131, 2293–2312, https://doi.org/10.1256/qj.04.72, 2005. a
Giard, D. and Bazile, E.: Implementation of a New Assimilation Scheme for Soil
and Surface Variables in a Global NWP Model, Mon. Weather Rev., 128,
997–1015, https://doi.org/10.1175/1520-0493(2000)128<0997:IOANAS>2.0.CO;2, 2000. a
Gilleland, E., Ahijevych, D. A., Brown, B. G., and Ebert, E. E.: Verifying
Forecasts Spatially, B. Am. Meteor. Soc., 91, 1365–1376,
https://doi.org/10.1175/2010BAMS2819.1, 2010. a
Gilleland, E: SpatialVx: Spatial Forecast Verification, The Comprehensive R Archive Network, available at: https://cran.r-project.org/package=SpatialVx, last access: 2 July 2019. a
Gómez-Navarro, J. J., Raible, C. C., and Dierer, S.: Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain, Geosci. Model Dev., 8, 3349–3363, https://doi.org/10.5194/gmd-8-3349-2015, 2015. a, b
Gross, G.: On the applicability of numerical mass-consistent wind field models,
Bound.-Lay. Meteor., 77, 379–394, https://doi.org/10.1007/BF00123533, 1996. a
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J. Geophys. Res., 113,
D20119, https://doi.org/10.1029/2008JD010201, 2008. a
Hewer, F.: Non-Linear Numerical Model Predictions of Flow Over an Isolated Hill
of Moderate Slope, Bound.-Lay. Meteor., 87, 381–408,
https://doi.org/10.1023/A:1000944817965, 1998. a
Hiebl, J. and Frei, C.: Daily temperature grids for Austria since
1961 – concept, creation and applicability, Theor. Appl. Climatol., 124,
161–178, https://doi.org/10.1007/s00704-015-1411-4, 2016. a
Hohmann, C., Kirchengast, G., and Birk, S.: Alpine foreland running drier?
Sensitivity of a drought vulnerable catchment to changes in climate, land
use, and water management, Clim. Change, 147, 179–193,
https://doi.org/10.1007/s10584-017-2121-y, 2018. a
Kabas, T.: WegenerNet climate station network region Feldbach: Experimental
setup and high resolution data for weather and climate research (in German),
Scientific Rep. 47-2012, Wegener Center Verlag, Graz, Austria, available
at:
http://wegcwww.uni-graz.at/publ/wegcreports/2012/WCV-WissBer-No47-TKabas-Jan2012.pdf (last access: 2 July 2019),
2012. a
Kabas, T., Foelsche, U., and Kirchengast, G.: Seasonal and annual trends of
temperature and precipitation within 1951/1971–2007 in south-eastern Styria,
Austria, Meteor. Z., 20, 277–289, https://doi.org/10.1127/0941-2948/2011/0233, 2011. a
Kann, A., Meirold-Mautner, I., Schmid, F., Kirchengast, G., Fuchsberger, J., Meyer, V., Tüchler, L., and Bica, B.: Evaluation of high-resolution precipitation analyses using a dense station network, Hydrol. Earth Syst. Sci., 19, 1547–1559, https://doi.org/10.5194/hess-19-1547-2015, 2015a. a
Kann, A., Wittmann, C., Bica, B., and Wastl, C.: On the Impact of NWP Model
Background on Very High–Resolution Analyses in Complex Terrain, Weather Forecast., 30, 1077–1089, https://doi.org/10.1175/WAF-D-15-0001.1,
2015b. a
Kendon, E. J., Ban, N., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan,
S. C., Evans, J. P., Fosser, G., and Wilkinson, J. M.: Do
convection-permitting regional climate models improve projections of future
precipitation change?, B. Am. Meteor. Soc., 98, 79–93,
https://doi.org/10.1175/BAMS-D-15-0004.1, 2017. a
Kida, H., Koide, T., Sasaki, H., and Chiba, M.: A New Approach for Coupling a
Limited Area Model to a GCM for Regional Climate Simulations, J. Meteor. Soc. JPN, 69, 723–728, https://doi.org/10.2151/jmsj1965.69.6_723, 1991. a
Kirchengast, G., Kabas, T., Leuprech, A., Bichler, C., and Truhetz, H.:
WegenerNet: A pioneering high-resolution network for monitoring weather and
climate, B. Am. Meteor. Soc., 95, 227–242,
https://doi.org/10.1175/BAMS-D-11-00161.1, 2014. a, b, c, d
Land Steiermark: Das Land Steiermark, Geoinformation aus dem Land für das Land, available at: http://www.landesentwicklung.steiermark.at/cms/ziel/141976122/DE/, last access: 2 July 2019. a
Leutwyler, D., Fuhrer, O., Lapillonne, X., Lüthi, D., and Schär, C.: Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19, Geosci. Model Dev., 9, 3393–3412, https://doi.org/10.5194/gmd-9-3393-2016, 2016. a
Lugauer, M. and Winkler, P.: Thermal circulation in South Bavaria –
climatology and synoptic aspects, Meteor. Z., 14, 15–30,
https://doi.org/10.1127/0941-2948/2005/0014-0015, 2005. a
Morales, L., Lang, F., and Mattar, C.: Mesoscale wind speed simulation using
CALMET model and reanalysis information: An application to wind potential,
Renew. Energ., 48, 57–71, https://doi.org/10.1016/j.renene.2012.04.048, 2012. a
Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface
Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549,
https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989. a
O, S., Foelsche, U., Kirchengast, G., Fuchsberger, J., Tan, J., and Petersen, W. A.: Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria, Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, 2017. a
O, S., Foelsche, U., Kirchengast, G., and Fuchsberger, J.: Validation and
correction of rainfall data from the WegenerNet high density network in
southeast Austria, J. Hydrol., 556, 1110–1122,
https://doi.org/10.1016/j.jhydrol.2016.11.049, 2018. a
Ogaja, J. and Will, A.: Fourth order, conservative discretization of horizontal
Euler equations in the COSMO model and regional climate simulations, Meteor. Z., 25, 577–605, https://doi.org/10.1127/metz/2016/0645, 2016. a, b, c
Osborn, T. J. and Hulme, M.: Evaluation of the European daily precipitation
characteristics from the atmospheric model intercomparison project, Int. J. Climatol., 18, 505–522,
https://doi.org/10.1002/(SICI)1097-0088(199804)18:5<505::AID-JOC263>3.0.CO;2-7, 1998. a
Prein, A. F., Gobiet, A., Suklitsch, M., Truhetz, H., Awan, N. K., Keuler, K.,
and Georgievski, G.: Added value of convection permitting seasonal
simulations, Clim. Dynam., 41, 2655–2677, https://doi.org/10.1007/s00382-013-1744-6,
2013a. a, b
Prein, A. F., Holland, G. J., Rasmussen, R. M., Done, J., Ikeda, K., Clark,
M. P., and Liu, C. H.: Importance of regional climate model grid spacing for
the simulation of heavy precipitation in the colorado headwaters, J. Climate, 26, 4848–4857, https://doi.org/10.1175/JCLI-D-12-00727.1, 2013b. a, b
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Toelle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., Van Lipzig, N. P., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015. a, b
Raschendorfer, M.: The New Turbulence Parameterization of LM, 89–97,
Deutscher Wetterdienst (DWD), 1 Edn., available at:
http://www.cosmo-model.org/content/model/documentation/newsLetters/newsLetter01/newsLetter_01.pdf
(last access: 2 July 2019),
2001. a
Ratto, C., Festa, R., Romeo, C., Frumento, O., and Galluzzi, M.:
Mass-consistent models for wind fields over complex terrain: The state of the
art, Environ. Softw., 9, 247–268, 1994. a
Raymond, W. H.: High-Order Low-Pass Implicit Tangent Filters for Use in Finite
Area Calculations, Mon. Weather Rev., 116, 2132–2141,
https://doi.org/10.1175/1520-0493(1988)116<2132:HOLPIT>2.0.CO;2, 1988. a
Ritter, B. and Geleyn, J.-F.: A Comprehensive Radiation Scheme for Numerical
Weather Prediction Models with Potential Applications in Climate Simulations,
Mon. Weather Rev., 120, 303–325,
https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2, 1992. a
Roberts, N.: Assessing the spatial and temporal variation in the skill of
precipitation forecasts from an NWP model, Meteor. Appl., 15, 163–169,
https://doi.org/10.1002/met.57, 2008. a, b, c, d
Rockel, B., Will, A., and Hense, A.: The Regional Climate Model COSMO-CLM
(CCLM), Meteor. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309, 2008. a, b
Schättler, U., Doms, G. U., and Baldauf, M.: A Description of the
Nonhydrostatic Regional COSMO Model, Part VII: User's Guide, Deutscher
Wetterdienst, 3004 Offenbach, Germany, 2016. a
Schlager, C., Kirchengast, G., and Fuchsberger, J.: Empirical high-resolution wind field and gust model in mountainous and hilly terrain based on the dense WegenerNet station networks, Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, 2018. a, b, c, d, e, f, g, h, i, j, k, l
Schroeer, K. and Kirchengast, G.: Sensitivity of extreme precipitation to
temperature: the variability of scaling factors from a regional to local
perspective, Clim. Dynam., 50, 3981–3994, 2018. a
Scire, J. S., Robe, F. R., Fernau, M. E., and Roberto, Y. J.: A User`s Guide
for the CALMET Meteorological Model (Version 5), Earth Tech, Inc, 196 Baker
Avenue, Concord, MA 01742, 1998. a
Seaman, N. L.: Meteorological modeling for air-quality assessments, Appl. Energ., 34, 2231–2259, https://doi.org/10.1016/S1352-2310(99)00466-5, 2000. a, b
Sfetsos, A.: A novel approach for the forecasting of mean hourly wind speed
time series, Renew. Energ., 27, 163–174,
https://doi.org/10.1016/S0960-1481(01)00193-8, 2002. a
Strasser, U., Marke, T., Sass, O., Birk, S., and Winkler, G.: John's creek
valley: A mountainous catchment for long-term interdisciplinary
human-environment system research in Upper Styria (Austria), Environ. Earth
Sci., 69, 695–705, https://doi.org/10.1007/s12665-013-2318-y, 2013. a, b
Suklitsch, M., Gobiet, A., Truhetz, H., Awan, N. K., Göttel, H., and
Jacob, D.: Error characteristics of high resolution regional climate models
over the Alpine area, Clim. Dynam., 37, 377–390,
https://doi.org/10.1007/s00382-010-0848-5, 2011. a, b
Taylor, P. A., Mason, P. J., and Bradley, E. F.: Boundary-layer flow over low hills, Bound.-Lay. Meteorol., 39, 107–132, https://doi.org/10.1007/BF00121870, 1987. a
Termonia, P., Fischer, C., Bazile, E., Bouyssel, F., Brožková, R., Bénard, P., Bochenek, B., Degrauwe, D., Derková, M., El Khatib, R., Hamdi, R., Mašek, J., Pottier, P., Pristov, N., Seity, Y., Smolíková, P., Španiel, O., Tudor, M., Wang, Y., Wittmann, C., and Joly, A.: The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1, Geosci. Model Dev., 11, 257–281, https://doi.org/10.5194/gmd-11-257-2018, 2018. a
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization in
Large-Scale Models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Truhetz, H.: High resolution wind field modelling over complex topography:
analysis and future scenarios, Scientific Rep. 32-2010, Wegener Center
Verlag, Graz, Austria, available at:
http://wegcwww.uni-graz.at/publ/wegcreports/2010/WCV-SciRep-No32-HTruhetz-Apr2010.pdf (last access: 2 July 2019),
2010. a
Wang, Y., Haiden, T., and Kann, A.: The operational Limited Area Modelling
system at ZAMG: ALADIN-AUSTRIA, Vol. 37, Österreichische Beiträge zu
Meteorologie und Geophysik, Wien, 2006. a
Wegener Center: WegenerNet Data portal, WegenerNet – New data for research and society, available at: https://wegenernet.org/portal/, last access: 2 July 2019. a
Whiteman, C.: Mountain Meteorology: Fundamentals and Applications, Oxford
University Press, Graz, 2000. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models
Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
Short summary
Empirical high-resolution surface wind fields from two study areas, automatically generated by a weather diagnostic application, were intercompared with wind fields of different modeling approaches. The focus is on evaluating spatial differences and displacements between the different datasets. In general, the spatial verification indicates a better statistical agreement for the first study area (hilly WegenerNet Feldbach Region), than for the second one (mountainous WegenerNet Johnsbachtal).
Empirical high-resolution surface wind fields from two study areas, automatically generated by a...
