Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3599-2024
© Author(s) 2024. 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-17-3599-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
03 May 2024
Development and technical paper |
| 03 May 2024
| 03 May 2024
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Rohith Thundathil
CORRESPONDING AUTHOR
Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Florian Zus
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Galina Dick
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Jens Wickert
Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
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Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
EGUsphere, https://doi.org/10.5194/egusphere-2025-19, https://doi.org/10.5194/egusphere-2025-19, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Tropospheric gradients provide information on the moisture distribution, whereas ZTDs provide the absolute amount of moisture through integrated water vapor. When TGs are assimilated with ZTDs, it helps the model actuate the moisture fields, correcting its dynamics. In our research, we show evidence that in particular regions with very few GNSS stations, the assimilation of gradients on top of ZTDs can provide the same impact as the assimilation of only ZTDs with dense coverage of GNSS stations.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
EGUsphere, https://doi.org/10.5194/egusphere-2025-19, https://doi.org/10.5194/egusphere-2025-19, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
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Tropospheric gradients provide information on the moisture distribution, whereas ZTDs provide the absolute amount of moisture through integrated water vapor. When TGs are assimilated with ZTDs, it helps the model actuate the moisture fields, correcting its dynamics. In our research, we show evidence that in particular regions with very few GNSS stations, the assimilation of gradients on top of ZTDs can provide the same impact as the assimilation of only ZTDs with dense coverage of GNSS stations.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Ladina Steiner, Holger Schmithüsen, Jens Wickert, and Olaf Eisen
The Cryosphere, 17, 4903–4916, https://doi.org/10.5194/tc-17-4903-2023, https://doi.org/10.5194/tc-17-4903-2023, 2023
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The present study illustrates the potential of a combined Global Navigation Satellite System reflectometry and refractometry (GNSS-RR) method for accurate, simultaneous, and continuous estimation of in situ snow accumulation, snow water equivalent, and snow density time series. The combined GNSS-RR method was successfully applied on a fast-moving, polar ice shelf. The combined GNSS-RR approach could be highly advantageous for a continuous quantification of ice sheet surface mass balances.
Karina Wilgan, Galina Dick, Florian Zus, and Jens Wickert
Atmos. Meas. Tech., 15, 21–39, https://doi.org/10.5194/amt-15-21-2022, https://doi.org/10.5194/amt-15-21-2022, 2022
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The assimilation of GNSS data in weather models has a positive impact on the forecasts. The impact is still limited due to using only the GPS zenith direction parameters. We calculate and validate more advanced tropospheric products from three satellite systems: the US American GPS, Russian GLONASS and European Galileo. The quality of all the solutions is comparable; however, combining more GNSS systems enhances the observations' geometry and improves the quality of the weather forecasts.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021, https://doi.org/10.5194/amt-14-5127-2021, 2021
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Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
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
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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.
Ankur Kepkar, Christina Arras, Jens Wickert, Harald Schuh, Mahdi Alizadeh, and Lung-Chih Tsai
Ann. Geophys., 38, 611–623, https://doi.org/10.5194/angeo-38-611-2020, https://doi.org/10.5194/angeo-38-611-2020, 2020
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The paper focuses on the analyses of the global occurrence of equatorial plasma bubble events using S4 data that were calculated from GPS radio occultation measurements of the FormoSat-3/COSMIC mission. The advantage in using radio occultation data is that we get information not only on the occurrence and intensity of the equatorial bubble events, but also on the altitude distribution. We analyzed a 10.5-year time series of COSMIC data and demonstrated a strong dependence on the solar cycle.
Michal Kačmařík, Jan Douša, Florian Zus, Pavel Václavovic, Kyriakos Balidakis, Galina Dick, and Jens Wickert
Ann. Geophys., 37, 429–446, https://doi.org/10.5194/angeo-37-429-2019, https://doi.org/10.5194/angeo-37-429-2019, 2019
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We provide an analysis of processing setting impacts on tropospheric gradients estimated from GNSS observation processing. These tropospheric gradients are related to water vapour distribution in the troposphere and therefore can be helpful in meteorological applications.
Fadwa Alshawaf, Kyriakos Balidakis, Galina Dick, Stefan Heise, and Jens Wickert
Atmos. Meas. Tech., 10, 3117–3132, https://doi.org/10.5194/amt-10-3117-2017, https://doi.org/10.5194/amt-10-3117-2017, 2017
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In this paper, we aimed at estimating climatic trends using precipitable water vapor time series and surface measurements of air temperature in Germany. We used GNSS, ERA-Interim, and synoptic data. The results show mainly a positive trend in precipitable water vapor and temperature with an increase in the trend when moving to northeastern Germany.
Michal Kačmařík, Jan Douša, Galina Dick, Florian Zus, Hugues Brenot, Gregor Möller, Eric Pottiaux, Jan Kapłon, Paweł Hordyniec, Pavel Václavovic, and Laurent Morel
Atmos. Meas. Tech., 10, 2183–2208, https://doi.org/10.5194/amt-10-2183-2017, https://doi.org/10.5194/amt-10-2183-2017, 2017
Georg Beyerle and Florian Zus
Atmos. Meas. Tech., 10, 15–34, https://doi.org/10.5194/amt-10-15-2017, https://doi.org/10.5194/amt-10-15-2017, 2017
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Ground-based observations of GPS satellites disappearing below the local horizon are analysed. Starting at +2 degree elevation angle the GPS signals are recorded in open-loop tracking mode down to −1.5 degrees. The open-loop Doppler model has negligible influence on the derived data products for strong signal-to-noise ratios; at lower signal levels, however, a notable bias is uncovered. These results may have implications for the design of future space-based GPS radio occultation missions.
Cuixian Lu, Florian Zus, Maorong Ge, Robert Heinkelmann, Galina Dick, Jens Wickert, and Harald Schuh
Atmos. Meas. Tech., 9, 5965–5973, https://doi.org/10.5194/amt-9-5965-2016, https://doi.org/10.5194/amt-9-5965-2016, 2016
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The recent dramatic development of multi-GNSS constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. In this contribution, we develop a numerical weather model (NWM) constrained PPP processing system to improve the multi-GNSS precise positioning. Compared to the standard PPP solution, significant improvements of both convergence time and positioning accuracy are achieved with the NWM-constrained PPP solution.
Guergana Guerova, Jonathan Jones, Jan Douša, Galina Dick, Siebren de Haan, Eric Pottiaux, Olivier Bock, Rosa Pacione, Gunnar Elgered, Henrik Vedel, and Michael Bender
Atmos. Meas. Tech., 9, 5385–5406, https://doi.org/10.5194/amt-9-5385-2016, https://doi.org/10.5194/amt-9-5385-2016, 2016
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Application of global navigation satellite systems (GNSSs) for atmospheric remote sensing (GNSS meteorology) is a well-established field in both research and operation in Europe. This review covers the state of the art in GNSS meteorology in Europe. It discusses 1) advances in GNSS processing techniques and tropospheric products, 2) use in numerical weather prediction and nowcasting, and 3) climate research.
Jan Douša, Galina Dick, Michal Kačmařík, Radmila Brožková, Florian Zus, Hugues Brenot, Anastasia Stoycheva, Gregor Möller, and Jan Kaplon
Atmos. Meas. Tech., 9, 2989–3008, https://doi.org/10.5194/amt-9-2989-2016, https://doi.org/10.5194/amt-9-2989-2016, 2016
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GNSS products provide observations of atmospheric water vapour. Advanced tropospheric products focus on ultra-fast and high-resolution zenith total delays (ZTDs), horizontal gradients and slant delays, all suitable for rapid-cycle numerical weather prediction (NWP) and severe weather event monitoring. The GNSS4SWEC Benchmark provides a complex data set for developing and assessing these products, with initial focus on reference ZTDs and gradients derived from several NWP and dense GNSS networks.
Fadwa Alshawaf, Galina Dick, Stefan Heise, Tzvetan Simeonov, Sibylle Vey, Torsten Schmidt, and Jens Wickert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-151, https://doi.org/10.5194/amt-2016-151, 2016
Revised manuscript not accepted
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In this work, we use time series from GNSS, European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data, and meteorological measurements to evaluate climate evolution in Central Europe. We monitor different atmospheric variables such as temperature, PWV, precipitation, and snow cover. The results show an increasing trend the water vapor time series that are correlated with the trend the temperature tme series. The average increase of water vapor is about 0.3–0.6 mm/decade .
T. Ning, J. Wang, G. Elgered, G. Dick, J. Wickert, M. Bradke, M. Sommer, R. Querel, and D. Smale
Atmos. Meas. Tech., 9, 79–92, https://doi.org/10.5194/amt-9-79-2016, https://doi.org/10.5194/amt-9-79-2016, 2016
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Integrated water vapour (IWV) obtained from GNSS is to be developed into a GRUAN data product. In addition to the actual measurement, this data product needs to provide an estimate of the measurement uncertainty at the same time resolution as the actual measurement. The method developed in the paper fulfils the requirement by assigning a specific uncertainty to each data point. The method is also valuable for all applications of GNSS IWV data in atmospheric research and weather forecast.
S. Steinke, S. Eikenberg, U. Löhnert, G. Dick, D. Klocke, P. Di Girolamo, and S. Crewell
Atmos. Chem. Phys., 15, 2675–2692, https://doi.org/10.5194/acp-15-2675-2015, https://doi.org/10.5194/acp-15-2675-2015, 2015
M. Shangguan, S. Heise, M. Bender, G. Dick, M. Ramatschi, and J. Wickert
Ann. Geophys., 33, 55–61, https://doi.org/10.5194/angeo-33-55-2015, https://doi.org/10.5194/angeo-33-55-2015, 2015
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We present validation results covering 184 days of SIWV (slant-integrated water vapor) observed by a ground-based GPS receiver and a WVR (water vapor radiometer). SIWV data from GPS and WVR generally show good agreement, and the relation between their differences and possible influential factors are analyzed. The differences in SIWV show a relative elevation dependence. Besides the elevation, dependencies between the atmospheric humidity conditions, temperature and differences in SIWV are found.
F. Zus, G. Beyerle, S. Heise, T. Schmidt, and J. Wickert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-7-12719-2014, https://doi.org/10.5194/amtd-7-12719-2014, 2014
Preprint withdrawn
M. Shangguan, M. Bender, M. Ramatschi, G. Dick, J. Wickert, A. Raabe, and R. Galas
Ann. Geophys., 31, 1491–1505, https://doi.org/10.5194/angeo-31-1491-2013, https://doi.org/10.5194/angeo-31-1491-2013, 2013
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely...
