Articles | Volume 12, issue 5
https://doi.org/10.5194/gmd-12-2139-2019
© 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-12-2139-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
29 May 2019
Model description paper |
| 29 May 2019
| 29 May 2019
Atmospheric boundary layer dynamics from balloon soundings worldwide: CLASS4GL v1.0
Laboratory of Hydrology and Water Management, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
Irina Y. Petrova
Laboratory of Hydrology and Water Management, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
Chiel C. van Heerwaarden
Meteorology and Air Quality Group, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Jordi Vilà-Guerau de Arellano
Meteorology and Air Quality Group, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Adriaan J. Teuling
Hydrology and Quantitative Water Management Group, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Vicky Meulenberg
Meteorology and Air Quality Group, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Joseph A. Santanello
Hydrological Sciences Laboratory (617), Goddard Space Flight Center, National Aeronautics and Space Administration, Greenbelt, MD, USA
Diego G. Miralles
Laboratory of Hydrology and Water Management, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
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Mirjam Tijhuis, Bart J. H. van Stratum, and Chiel C. van Heerwaarden
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Hydrol. Earth Syst. Sci., 28, 3495–3518, https://doi.org/10.5194/hess-28-3495-2024, https://doi.org/10.5194/hess-28-3495-2024, 2024
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Biogeosciences, 21, 2425–2445, https://doi.org/10.5194/bg-21-2425-2024, https://doi.org/10.5194/bg-21-2425-2024, 2024
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Gaoyun Wang, Rong Fu, Yizhou Zhuang, Paul A. Dirmeyer, Joseph A. Santanello, Guiling Wang, Kun Yang, and Kaighin McColl
Atmos. Chem. Phys., 24, 3857–3868, https://doi.org/10.5194/acp-24-3857-2024, https://doi.org/10.5194/acp-24-3857-2024, 2024
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Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
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Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 15, 265–291, https://doi.org/10.5194/esd-15-265-2024, https://doi.org/10.5194/esd-15-265-2024, 2024
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Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We analyzed measurements with the aim of finding relations between the surface atmosphere exchange of NH3 and the CO2 uptake and transpiration by vegetation. We found a high correlation of daytime NH3 emissions with both latent heat flux and photosynthetically active radiation. Very few simultaneous measurements of NH3, CO2 fluxes and meteorological variables exist at sub-diurnal timescales. This study paves the way to finding more robust relations between the NH3 exchange flux and CO2 uptake.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Robbert P. J. Moonen, Getachew A. Adnew, Oscar K. Hartogensis, Jordi Vilà-Guerau de Arellano, David J. Bonell Fontas, and Thomas Röckmann
Atmos. Meas. Tech., 16, 5787–5810, https://doi.org/10.5194/amt-16-5787-2023, https://doi.org/10.5194/amt-16-5787-2023, 2023
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Isotope fluxes allow for net ecosystem gas exchange fluxes to be partitioned into sub-components like plant assimilation, respiration and transpiration, which can help us better understand the environmental drivers of each partial flux. We share the results of a field campaign isotope fluxes were derived using a combination of laser spectroscopy and eddy covariance. We found lag times and high frequency signal loss in the isotope fluxes we derived and present methods to correct for both.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023, https://doi.org/10.5194/hess-27-4057-2023, 2023
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Using a new approach based on a combination of modeling and Earth observation, useful information about the filling of the Grand Ethiopian Renaissance Dam can be obtained with limited data and proper rainfall selection. While the monthly streamflow into Sudan has decreased significantly (1.2 × 109–5 × 109 m3) with respect to the non-dam scenario, the negative impact has been masked due to higher-than-average rainfall. We reveal that the dam will need 3–5 more years to complete filling.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
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There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Bert G. Heusinkveld, Wouter B. Mol, and Chiel C. van Heerwaarden
Atmos. Meas. Tech., 16, 3767–3785, https://doi.org/10.5194/amt-16-3767-2023, https://doi.org/10.5194/amt-16-3767-2023, 2023
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This paper presents a new instrument for fast measurements of solar irradiance in 18 wavebands (400–950 nm): GPS perfectly synchronizes 10 Hz measurement speed to universal time, low-cost (< EUR 200) complete standalone solution for realizing dense measurement grids to study cloud-shading dynamics, 940 nm waveband reveals atmospheric moisture column information, 11 wavebands to study photosynthetic active radiation and light interaction with vegetation, and good reflection spectra performance.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
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We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Wouter B. Mol, Wouter H. Knap, and Chiel C. van Heerwaarden
Earth Syst. Sci. Data, 15, 2139–2151, https://doi.org/10.5194/essd-15-2139-2023, https://doi.org/10.5194/essd-15-2139-2023, 2023
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We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a rate of one measurement per second for 10 years. The dataset includes detailed information on direct and scattered sunlight; classifications and statistics of variability; and observations of clouds, atmospheric composition, and wind. The dataset can be used to study how the atmosphere influences sunlight variability and to validate models that aim to predict this variability with greater accuracy.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2023-953, https://doi.org/10.5194/egusphere-2023-953, 2023
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Land cover and management changes can affect the climate and water availability. In this study we use climate model simulations of extreme global land cover changes (afforestation, deforestation) and land management changes (irrigation) to understand the effects on the global water cycle and local to continental water availability. We show that cropland expansion generally leads to higher evaporation and lower amounts of precipitation and afforestation and irrigation expansion to the opposite.
Kim A. P. Faassen, Linh N. T. Nguyen, Eadin R. Broekema, Bert A. M. Kers, Ivan Mammarella, Timo Vesala, Penelope A. Pickers, Andrew C. Manning, Jordi Vilà-Guerau de Arellano, Harro A. J. Meijer, Wouter Peters, and Ingrid T. Luijkx
Atmos. Chem. Phys., 23, 851–876, https://doi.org/10.5194/acp-23-851-2023, https://doi.org/10.5194/acp-23-851-2023, 2023
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The exchange ratio (ER) between atmospheric O2 and CO2 provides a useful tracer for separately estimating photosynthesis and respiration processes in the forest carbon balance. This is highly relevant to better understand the expected biosphere sink, which determines future atmospheric CO2 levels. We therefore measured O2, CO2, and their ER above a boreal forest in Finland and investigated their diurnal behaviour for a representative day, and we show the most suitable way to determine the ER.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, https://doi.org/10.5194/hess-26-5647-2022, 2022
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A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
Luuk D. van der Valk, Adriaan J. Teuling, Luc Girod, Norbert Pirk, Robin Stoffer, and Chiel C. van Heerwaarden
The Cryosphere, 16, 4319–4341, https://doi.org/10.5194/tc-16-4319-2022, https://doi.org/10.5194/tc-16-4319-2022, 2022
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Most large-scale hydrological and climate models struggle to capture the spatially highly variable wind-driven melt of patchy snow cover. In the field, we find that 60 %–80 % of the total melt is wind driven at the upwind edge of a snow patch, while it does not contribute at the downwind edge. Our idealized simulations show that the variation is due to a patch-size-independent air-temperature reduction over snow patches and also allow us to study the role of wind-driven snowmelt on larger scales.
Micael Amore Cecchini, Marco de Bruine, Jordi Vilà-Guerau de Arellano, and Paulo Artaxo
Atmos. Chem. Phys., 22, 11867–11888, https://doi.org/10.5194/acp-22-11867-2022, https://doi.org/10.5194/acp-22-11867-2022, 2022
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Shallow clouds (vertical extent up to 3 km height) are ubiquitous throughout the Amazon and are responsible for redistributing the solar heat and moisture vertically and horizontally. They are a key component of the water cycle because they can grow past the shallow phase to contribute significantly to the precipitation formation. However, they need favourable environmental conditions to grow. In this study, we analyse how changing wind patterns affect the development of such shallow clouds.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Felipe Lobos-Roco, Oscar Hartogensis, Francisco Suárez, Ariadna Huerta-Viso, Imme Benedict, Alberto de la Fuente, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 26, 3709–3729, https://doi.org/10.5194/hess-26-3709-2022, https://doi.org/10.5194/hess-26-3709-2022, 2022
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This research brings a multi-scale temporal analysis of evaporation in a saline lake of the Atacama Desert. Our findings reveal that evaporation is controlled differently depending on the timescale. Evaporation is controlled sub-diurnally by wind speed, regulated seasonally by radiation and modulated interannually by ENSO. Our research extends our understanding of evaporation, contributing to improving the climate change assessment and efficiency of water management in arid regions.
Alessandro Montemagno, Christophe Hissler, Victor Bense, Adriaan J. Teuling, Johanna Ziebel, and Laurent Pfister
Biogeosciences, 19, 3111–3129, https://doi.org/10.5194/bg-19-3111-2022, https://doi.org/10.5194/bg-19-3111-2022, 2022
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We investigated the biogeochemical processes that dominate the release and retention of elements (nutrients and potentially toxic elements) during litter degradation. Our results show that toxic elements are retained in the litter, while nutrients are released in solution during the first stages of degradation. This seems linked to the capability of trees to distribute the elements between degradation-resistant and non-degradation-resistant compounds of leaves according to their chemical nature.
Ruben B. Schulte, Margreet C. van Zanten, Bart J. H. van Stratum, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 22, 8241–8257, https://doi.org/10.5194/acp-22-8241-2022, https://doi.org/10.5194/acp-22-8241-2022, 2022
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We present a fine-scale simulation framework, utilizing large-eddy simulations, to assess NH3 measurements influenced by boundary-layer dynamics and turbulent dispersion of a nearby emission source. The minimum required distance from an emission source differs for concentration and flux measurements, from 0.5–3.0 km and 0.75–4.5 km, respectively. The simulation framework presented here proves to be a powerful and versatile tool for future NH3 research at high spatio-temporal resolutions.
Linqi Zhang, Yi Liu, Liliang Ren, Adriaan J. Teuling, Ye Zhu, Linyong Wei, Linyan Zhang, Shanhu Jiang, Xiaoli Yang, Xiuqin Fang, and Hang Yin
Hydrol. Earth Syst. Sci., 26, 3241–3261, https://doi.org/10.5194/hess-26-3241-2022, https://doi.org/10.5194/hess-26-3241-2022, 2022
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In this study, three machine learning methods displayed a good detection capacity of flash droughts. The RF model was recommended to estimate the depletion rate of soil moisture and simulate flash drought by considering the multiple meteorological variable anomalies in the adjacent time to drought onset. The anomalies of precipitation and potential evapotranspiration exhibited a stronger synergistic but asymmetrical effect on flash droughts compared to slowly developing droughts.
Anja Ražnjević, Chiel van Heerwaarden, and Maarten Krol
Atmos. Meas. Tech., 15, 3611–3628, https://doi.org/10.5194/amt-15-3611-2022, https://doi.org/10.5194/amt-15-3611-2022, 2022
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We evaluate two widely used observational techniques (Other Test Method (OTM) 33A and car drive-bys) that estimate point source gas emissions. We performed our analysis on high-resolution plume dispersion simulation. For car drive-bys we found that at least 15 repeated measurements were needed to get within 40 % of the true emissions. OTM 33A produced large errors in estimation (50 %–200 %) due to its sensitivity to dispersion coefficients and underlying simplifying assumptions.
Femke A. Jansen, Remko Uijlenhoet, Cor M. J. Jacobs, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 26, 2875–2898, https://doi.org/10.5194/hess-26-2875-2022, https://doi.org/10.5194/hess-26-2875-2022, 2022
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We studied the controls on open water evaporation with a focus on Lake IJssel, the Netherlands, by analysing eddy covariance observations over two summer periods at two locations at the borders of the lake. Wind speed and the vertical vapour pressure gradient can explain most of the variation in observed evaporation, which is in agreement with Dalton's model. We argue that the distinct characteristics of inland waterbodies need to be taken into account when parameterizing their evaporation.
Anja Ražnjević, Chiel van Heerwaarden, Bart van Stratum, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, and Maarten Krol
Atmos. Chem. Phys., 22, 6489–6505, https://doi.org/10.5194/acp-22-6489-2022, https://doi.org/10.5194/acp-22-6489-2022, 2022
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Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify and quantify individual sources of greenhouse gases. Due to road restrictions, those observations are often sparse (temporally and spatially). We performed high-resolution simulations of plume dispersion, with realistic weather conditions encountered in the field, to reproduce the measurement process of a methane plume emitted from an oil well and provide additional information about the plume.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, https://doi.org/10.5194/gmd-15-1875-2022, 2022
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Air transports moisture and heat, shaping the weather we experience. When and where was this air moistened and warmed by the surface? To address this question, atmospheric models trace the history of air parcels in space and time. However, their uncertainties remain unexplored, which hinders their utility and application. Here, we present a framework that sheds light on these uncertainties. Our approach sets a new standard in the assessment of atmospheric moisture and heat trajectories.
Charles Nduhiu Wamucii, Pieter R. van Oel, Arend Ligtenberg, John Mwangi Gathenya, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 25, 5641–5665, https://doi.org/10.5194/hess-25-5641-2021, https://doi.org/10.5194/hess-25-5641-2021, 2021
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East African water towers (WTs) are under pressure from human influences within and without, but the water yield (WY) is more sensitive to climate changes from within. Land use changes have greater impacts on WY in the surrounding lowlands. The WTs have seen a strong shift towards wetter conditions while, at the same time, the potential evapotranspiration is gradually increasing. The WTs were identified as non-resilient, and future WY may experience more extreme variations.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
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Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Carlos Román-Cascón, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jordi Vila-Guerau de Arellano, David Pino, Carlos Yagüe, and Eric R. Pardyjak
Geosci. Model Dev., 14, 3939–3967, https://doi.org/10.5194/gmd-14-3939-2021, https://doi.org/10.5194/gmd-14-3939-2021, 2021
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The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land cover databases in models to improve their predictions.
Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021, https://doi.org/10.5194/gmd-14-3769-2021, 2021
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Turbulent flows are often simulated with the large-eddy simulation (LES) technique, which requires subgrid models to account for the smallest scales. Current subgrid models often require strong simplifying assumptions. We therefore developed a subgrid model based on artificial neural networks, which requires fewer assumptions. Our data-driven SGS model showed high potential in accurately representing the smallest scales but still introduced instability when incorporated into an actual LES.
Felipe Lobos-Roco, Oscar Hartogensis, Jordi Vilà-Guerau de Arellano, Alberto de la Fuente, Ricardo Muñoz, José Rutllant, and Francisco Suárez
Atmos. Chem. Phys., 21, 9125–9150, https://doi.org/10.5194/acp-21-9125-2021, https://doi.org/10.5194/acp-21-9125-2021, 2021
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We investigate the influence of regional atmospheric circulation on the evaporation of a saline lake in the Altiplano region of the Atacama Desert through a field experiment and regional modeling. Our results show that evaporation is controlled by two regimes: (1) in the morning by local conditions with low evaporation rates and low wind speed and (2) in the afternoon with high evaporation rates and high wind speed. Afternoon winds are connected to the regional Pacific Ocean–Andes flow.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
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Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Joost Buitink, Lieke A. Melsen, and Adriaan J. Teuling
Earth Syst. Dynam., 12, 387–400, https://doi.org/10.5194/esd-12-387-2021, https://doi.org/10.5194/esd-12-387-2021, 2021
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Higher temperatures influence both evaporation and snow processes. These two processes have a large effect on discharge but have distinct roles during different seasons. In this study, we study how higher temperatures affect the discharge via changed evaporation and snow dynamics. Higher temperatures lead to enhanced evaporation but increased melt from glaciers, overall lowering the discharge. During the snowmelt season, discharge was reduced further due to the earlier depletion of snow.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech., 14, 1099–1110, https://doi.org/10.5194/amt-14-1099-2021, https://doi.org/10.5194/amt-14-1099-2021, 2021
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Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.
Jolijn van Engelenburg, Erik van Slobbe, Adriaan J. Teuling, Remko Uijlenhoet, and Petra Hellegers
Drink. Water Eng. Sci., 14, 1–43, https://doi.org/10.5194/dwes-14-1-2021, https://doi.org/10.5194/dwes-14-1-2021, 2021
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This study analysed the impact of extreme weather events, water quality deterioration, and a growing drinking water demand on the sustainability of drinking water supply in the Netherlands. The results of the case studies were compared to sustainability issues for drinking water supply that are experienced worldwide. This resulted in a set of sustainability characteristics describing drinking water supply on a local scale in terms of hydrological, technical, and socio-economic characteristics.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Theresa C. van Hateren, Marco Chini, Patrick Matgen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-583, https://doi.org/10.5194/hess-2020-583, 2020
Manuscript not accepted for further review
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Agricultural droughts occur when the water content of the soil diminishes to such a level that vegetation is negatively impacted. Here we show that, although they are classified as the same type of drought, substantial differences between soil moisture and vegetation droughts exist. This duality is not included in the term agricultural drought, and thus is a potential issue in drought research. We argue that a distinction should be made between soil moisture and vegetation drought events.
Joost Buitink, Anne M. Swank, Martine van der Ploeg, Naomi E. Smith, Harm-Jan F. Benninga, Frank van der Bolt, Coleen D. U. Carranza, Gerbrand Koren, Rogier van der Velde, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 24, 6021–6031, https://doi.org/10.5194/hess-24-6021-2020, https://doi.org/10.5194/hess-24-6021-2020, 2020
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The amount of water stored in the soil is critical for the productivity of plants. Plant productivity is either limited by the available water or by the available energy. In this study, we infer this transition point by comparing local observations of water stored in the soil with satellite observations of vegetation productivity. We show that the transition point is not constant with soil depth, indicating that plants use water from deeper layers when the soil gets drier.
Joost Buitink, Lieke A. Melsen, James W. Kirchner, and Adriaan J. Teuling
Geosci. Model Dev., 13, 6093–6110, https://doi.org/10.5194/gmd-13-6093-2020, https://doi.org/10.5194/gmd-13-6093-2020, 2020
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This paper presents a new distributed hydrological model: the distributed simple dynamical systems (dS2) model. The model is built with a focus on computational efficiency and is therefore able to simulate basins at high spatial and temporal resolution at a low computational cost. Despite the simplicity of the model concept, it is able to correctly simulate discharge in both small and mesoscale basins.
Jasper Foets, Carlos E. Wetzel, Núria Martínez-Carreras, Adriaan J. Teuling, Jean-François Iffly, and Laurent Pfister
Hydrol. Earth Syst. Sci., 24, 4709–4725, https://doi.org/10.5194/hess-24-4709-2020, https://doi.org/10.5194/hess-24-4709-2020, 2020
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Diatoms (microscopic algae) are regarded as useful tracers in catchment hydrology. However, diatom analysis is labour-intensive; therefore, only a limited number of samples can be analysed. To reduce this number, we explored the potential for a time-integrated mass-flux sampler to provide a representative sample of the diatom assemblage for a whole storm run-off event. Our results indicate that the Phillips sampler did indeed sample representative communities during two of the three events.
Caspar T. J. Roebroek, Lieke A. Melsen, Anne J. Hoek van Dijke, Ying Fan, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 24, 4625–4639, https://doi.org/10.5194/hess-24-4625-2020, https://doi.org/10.5194/hess-24-4625-2020, 2020
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Vegetation is a principal component in the Earth system models that are used for weather, climate and other environmental predictions. Water is one of the main drivers of vegetation; however, the global distribution of how water influences vegetation is not well understood. This study looks at spatial patterns of photosynthesis and water sources (rain and groundwater) to obtain a first understanding of water access and limitations for the growth of global forests (proxy for natural vegetation).
Brecht Martens, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles
Geosci. Model Dev., 13, 4159–4181, https://doi.org/10.5194/gmd-13-4159-2020, https://doi.org/10.5194/gmd-13-4159-2020, 2020
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Climate reanalyses are widely used in different fields and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets. In this study, we show the improvements of ECMWF's latest climate reanalysis (ERA5) upon its predecessor (ERA-Interim) in partitioning the available energy at the land surface.
Anne J. Hoek van Dijke, Kaniska Mallick, Martin Schlerf, Miriam Machwitz, Martin Herold, and Adriaan J. Teuling
Biogeosciences, 17, 4443–4457, https://doi.org/10.5194/bg-17-4443-2020, https://doi.org/10.5194/bg-17-4443-2020, 2020
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We investigated the link between the vegetation leaf area index (LAI) and the land–atmosphere exchange of water, energy, and carbon fluxes. We show that the correlation between the LAI and water and energy fluxes depends on the vegetation type and aridity. For carbon fluxes, however, the correlation with the LAI was strong and independent of vegetation and aridity. This study provides insight into when the vegetation LAI can be used to model or extrapolate land–atmosphere fluxes.
Jordi Vilà-Guerau de Arellano, Patrizia Ney, Oscar Hartogensis, Hugo de Boer, Kevin van Diepen, Dzhaner Emin, Geiske de Groot, Anne Klosterhalfen, Matthias Langensiepen, Maria Matveeva, Gabriela Miranda-García, Arnold F. Moene, Uwe Rascher, Thomas Röckmann, Getachew Adnew, Nicolas Brüggemann, Youri Rothfuss, and Alexander Graf
Biogeosciences, 17, 4375–4404, https://doi.org/10.5194/bg-17-4375-2020, https://doi.org/10.5194/bg-17-4375-2020, 2020
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The CloudRoots field experiment has obtained an open comprehensive observational data set that includes soil, plant, and atmospheric variables to investigate the interactions between a heterogeneous land surface and its overlying atmospheric boundary layer, including the rapid perturbations of clouds in evapotranspiration. Our findings demonstrate that in order to understand and represent diurnal variability, we need to measure and model processes from the leaf to the landscape scales.
Pleun N. J. Bonekamp, Chiel C. van Heerwaarden, Jakob F. Steiner, and Walter W. Immerzeel
The Cryosphere, 14, 1611–1632, https://doi.org/10.5194/tc-14-1611-2020, https://doi.org/10.5194/tc-14-1611-2020, 2020
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Drivers controlling melt of debris-covered glaciers are largely unknown. With a 3D turbulence-resolving model the impact of surface properties of debris on micrometeorological variables and the conductive heat flux is shown. Also, we show ice cliffs are local melt hot spots and that turbulent fluxes and local heat advection amplify spatial heterogeneity on the surface.This work is important for glacier mass balance modelling and for the understanding of the evolution of debris-covered glaciers.
Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
Earth Syst. Sci. Data, 12, 753–769, https://doi.org/10.5194/essd-12-753-2020, https://doi.org/10.5194/essd-12-753-2020, 2020
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Africa has been severely influenced by intense drought events, which has led to crop failure, food shortages, famine, epidemics and even mass migration. The current study developed a high spatial resolution drought dataset entirely from satellite-based products. The dataset has been comprehensively inter-compared with other drought indicators and may contribute to an improved characterization of drought risk and vulnerability and minimize drought's impact on water and food security in Africa.
Xabier Pedruzo-Bagazgoitia, Stephan R. de Roode, Bianca Adler, Karmen Babić, Cheikh Dione, Norbert Kalthoff, Fabienne Lohou, Marie Lothon, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 20, 2735–2754, https://doi.org/10.5194/acp-20-2735-2020, https://doi.org/10.5194/acp-20-2735-2020, 2020
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Using a high-resolution model we simulate the transition from night to day clouds on southern West Africa using observations from the DACCIWA project. We find that the radiative effects of clouds help mantain a thick cloud layer in the night, while the mixing of cloud air with air above during the day, aided by moisture and heat fluxes at the surface, thins this layer and promotes its transition to other clouds. The effect of changing wind with height accelerates the transition.
Femke A. Jansen and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 24, 1055–1072, https://doi.org/10.5194/hess-24-1055-2020, https://doi.org/10.5194/hess-24-1055-2020, 2020
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We characterized the (dis)agreement between six evaporation methods from hourly to decadal timescales, focussing on the IJsselmeer region in the Netherlands. The projected changes in mean yearly water losses through evaporation between the years 2000 and 2100 range from 4 mm to 94 mm among the methods. We therefore stress that the choice of method is of great importance for water managers in their decision making.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
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Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Jeroen Claessen, Annalisa Molini, Brecht Martens, Matteo Detto, Matthias Demuzere, and Diego G. Miralles
Biogeosciences, 16, 4851–4874, https://doi.org/10.5194/bg-16-4851-2019, https://doi.org/10.5194/bg-16-4851-2019, 2019
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Bidirectional interactions between vegetation and climate are unraveled over short (monthly) and long (inter-annual) temporal scales. Analyses use a novel causal inference method based on wavelet theory. The performance of climate models at representing these interactions is benchmarked against satellite data. Climate models can reproduce the overall climate controls on vegetation at all temporal scales, while their performance at representing biophysical feedbacks on climate is less adequate.
Marco de Bruine, Maarten Krol, Jordi Vilà-Guerau de Arellano, and Thomas Röckmann
Geosci. Model Dev., 12, 5177–5196, https://doi.org/10.5194/gmd-12-5177-2019, https://doi.org/10.5194/gmd-12-5177-2019, 2019
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An aerosol scheme with multiple aerosol species is introduced in the Dutch Atmospheric Large-Eddy Simulation model (DALES) and focused to simulate the feedback of aerosol–cloud interaction (ACI) on the aerosol population. Cloud aerosol processing is found to be sensitive to the numerical method, while removal by precipitation is more stable. How ACI increases or decreases the mean aerosol size depends on the balance between the evaporation of clouds/rain and ultimate removal by precipitation.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
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Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Adriaan J. Teuling, Emile A. G. de Badts, Femke A. Jansen, Richard Fuchs, Joost Buitink, Anne J. Hoek van Dijke, and Shannon M. Sterling
Hydrol. Earth Syst. Sci., 23, 3631–3652, https://doi.org/10.5194/hess-23-3631-2019, https://doi.org/10.5194/hess-23-3631-2019, 2019
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Over the past decades, changes in land use and climate over Europe have impacted the average flow of water flowing through rivers and reservoirs (the so-called
water yield). We quantify these changes using a simple but widely tested modelling approach constrained by observations of lysimeters across Europe. Results show that the contribution of land use to changes in water yield are of the same order as changes in climate, showing that impacts of land use changes cannot be neglected.
Sven Boese, Martin Jung, Nuno Carvalhais, Adriaan J. Teuling, and Markus Reichstein
Biogeosciences, 16, 2557–2572, https://doi.org/10.5194/bg-16-2557-2019, https://doi.org/10.5194/bg-16-2557-2019, 2019
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This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration. We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation. Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
Anne J. Hoek van Dijke, Kaniska Mallick, Adriaan J. Teuling, Martin Schlerf, Miriam Machwitz, Sibylle K. Hassler, Theresa Blume, and Martin Herold
Hydrol. Earth Syst. Sci., 23, 2077–2091, https://doi.org/10.5194/hess-23-2077-2019, https://doi.org/10.5194/hess-23-2077-2019, 2019
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Satellite images are often used to estimate land water fluxes over a larger area. In this study, we investigate the link between a well-known vegetation index derived from satellite data and sap velocity, in a temperate forest in Luxembourg. We show that the link between the vegetation index and transpiration is not constant. Therefore we suggest that the use of vegetation indices to predict transpiration should be limited to ecosystems and scales where the link has been confirmed.
Jon Ander Arrillaga, Carlos Yagüe, Carlos Román-Cascón, Mariano Sastre, Maria Antonia Jiménez, Gregorio Maqueda, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 19, 4615–4635, https://doi.org/10.5194/acp-19-4615-2019, https://doi.org/10.5194/acp-19-4615-2019, 2019
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Thermally driven downslope winds develop in mountainous areas under a weak large-scale forcing and clear skies. In this work, we find that their onset time and intensity are closely connected with both the large-scale wind and soil moisture. We also show how the distinct downslope intensities shape the turbulent and thermal features of the nocturnal atmosphere. The analysis concludes that the downslope–turbulence interaction and the horizontal transport explain the important CO2 variability.
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci., 23, 1779–1800, https://doi.org/10.5194/hess-23-1779-2019, https://doi.org/10.5194/hess-23-1779-2019, 2019
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The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This model study examines the benefits of a very high-resolution GCM and GHM in representing the hydrological cycle in the Rhine and Mississippi basins. We find that a higher-resolution GCM results in an improved precipitation budget, and therefore an improved hydrological cycle for the Rhine. For the Mississippi, no substantial improvements are found with increased resolution.
Joost Buitink, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 23, 1593–1609, https://doi.org/10.5194/hess-23-1593-2019, https://doi.org/10.5194/hess-23-1593-2019, 2019
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This study describes how the spatial resolution of hydrological models affects the model results. The high-resolution model allowed for more spatial variability than the low-resolution model. As a result, the low-resolution model failed to capture most variability that was simulated with the high-resolution model. This has implications for the interpretation of results carried out at coarse resolutions, as they may fail to represent the local small-scale variability.
Ashley M. Broadbent, Andrew M. Coutts, Kerry A. Nice, Matthias Demuzere, E. Scott Krayenhoff, Nigel J. Tapper, and Hendrik Wouters
Geosci. Model Dev., 12, 785–803, https://doi.org/10.5194/gmd-12-785-2019, https://doi.org/10.5194/gmd-12-785-2019, 2019
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We present a simple model for assessing the cooling impacts of vegetation and water features (green and blue infrastructure) in urban environments. This model is designed to be computationally efficient so that those without technical knowledge or access to high-performance computers can use it. TARGET can be used to model average street-level air temperature at canyon to block scales (e.g. 100 m resolution). The model is carefully designed to provide reliable and accurate cooling estimates.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
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Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
Juhi Nagori, Ruud H. H. Janssen, Juliane L. Fry, Maarten Krol, Jose L. Jimenez, Weiwei Hu, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 19, 701–729, https://doi.org/10.5194/acp-19-701-2019, https://doi.org/10.5194/acp-19-701-2019, 2019
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Secondary organic aerosol (SOA) is produced through a complex interaction of sunlight, volatile organic compounds emitted from trees, anthropogenic emissions, and atmospheric chemistry. We are able to successfully model the formation and diurnal evolution of SOA using a model that takes into consideration the surface and boundary layer dynamics (1–2 km from the surface) and photochemistry above the southeastern US with data collected during the SOAS campaign to constrain the model.
Tjitske J. Geertsema, Adriaan J. Teuling, Remko Uijlenhoet, Paul J. J. F. Torfs, and Antonius J. F. Hoitink
Hydrol. Earth Syst. Sci., 22, 5599–5613, https://doi.org/10.5194/hess-22-5599-2018, https://doi.org/10.5194/hess-22-5599-2018, 2018
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This study investigate the processes and effects of simultaneous flood peaks at a lowland confluence. The flood peaks are analyzed with the relatively new dynamic time warping method, which offers a robust means of tracing flood waves in discharge time series at confluences. The time lag between discharge peaks in the main river and its lowland tributaries is small compared to the wave duration; therefore the exact timing of discharge peaks may be little relevant to flood risk.
Christina Papagiannopoulou, Diego G. Miralles, Matthias Demuzere, Niko E. C. Verhoest, and Willem Waegeman
Geosci. Model Dev., 11, 4139–4153, https://doi.org/10.5194/gmd-11-4139-2018, https://doi.org/10.5194/gmd-11-4139-2018, 2018
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Common global land cover and climate classifications are based on vegetation–climatic characteristics derived from observational data, ignoring the interaction between the local climate and biome. Here, we model the interplay between vegetation and local climate by discovering spatial relationships among different locations. The resulting global
hydro-climatic biomescorrespond to regions of coherent climate–vegetation interactions that agree well with traditional global land cover maps.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
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Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
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Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
Marit Van Tiel, Adriaan J. Teuling, Niko Wanders, Marc J. P. Vis, Kerstin Stahl, and Anne F. Van Loon
Hydrol. Earth Syst. Sci., 22, 463–485, https://doi.org/10.5194/hess-22-463-2018, https://doi.org/10.5194/hess-22-463-2018, 2018
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Glaciers are important hydrological reservoirs. Short-term variability in glacier melt and also glacier retreat can cause droughts in streamflow. In this study, we analyse the effect of glacier changes and different drought threshold approaches on future projections of streamflow droughts in glacierised catchments. We show that these different methodological options result in different drought projections and that these options can be used to study different aspects of streamflow droughts.
Joost Buitink, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-629, https://doi.org/10.5194/hess-2017-629, 2017
Revised manuscript not accepted
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We compared the hydrological response simulated at two different spatial resolutions. The low resolution model was not able to simulate the complex response as was simulated with the high resolution model. The low resolution model underestimated the anomalies when compared with the high resolution model. This has implications on the interpretation of global scale impact studies (low resolution) on local or regional scales (high resolution).
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-473, https://doi.org/10.5194/hess-2017-473, 2017
Revised manuscript not accepted
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The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This study examines the benefits of a very high resolution GCM and GHM on representing the hydrological cycle in the Rhine and Mississippi basin. We conclude that increasing the resolution of a GCM is the most straightforward route to better precipitation and thereby discharge results, although this is depending on the climatic drivers of the basin.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Chiel C. van Heerwaarden, Bart J. H. van Stratum, Thijs Heus, Jeremy A. Gibbs, Evgeni Fedorovich, and Juan Pedro Mellado
Geosci. Model Dev., 10, 3145–3165, https://doi.org/10.5194/gmd-10-3145-2017, https://doi.org/10.5194/gmd-10-3145-2017, 2017
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MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is made to simulate atmospheric flows up to the finest detail levels at very high resolution. It has been designed from scratch in C++ in order to use a modern design that allows the code to run on more than 10 000 cores, as well as on a graphical processing unit.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Patricia M. Lawston, Joseph A. Santanello Jr., Trenton E. Franz, and Matthew Rodell
Hydrol. Earth Syst. Sci., 21, 2953–2966, https://doi.org/10.5194/hess-21-2953-2017, https://doi.org/10.5194/hess-21-2953-2017, 2017
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Irrigation can affect the weather by making the air cooler and more humid, potentially causing changes to clouds and rainfall. This study uses new datasets to test how well irrigation is simulated in a model. We find the model applies more water than farmers' data show, but the water is applied at the right time in the growing season and improves the modeled wetness of the soil. These results will help improve irrigation modeling and thus understanding of human impacts on the water cycle.
Hidayat Hidayat, Adriaan J. Teuling, Bart Vermeulen, Muh Taufik, Karl Kastner, Tjitske J. Geertsema, Dinja C. C. Bol, Dirk H. Hoekman, Gadis Sri Haryani, Henny A. J. Van Lanen, Robert M. Delinom, Roel Dijksma, Gusti Z. Anshari, Nining S. Ningsih, Remko Uijlenhoet, and Antonius J. F. Hoitink
Hydrol. Earth Syst. Sci., 21, 2579–2594, https://doi.org/10.5194/hess-21-2579-2017, https://doi.org/10.5194/hess-21-2579-2017, 2017
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Hydrological prediction is crucial but in tropical lowland it is difficult, considering data scarcity and river system complexity. This study offers a view of the hydrology of two tropical lowlands in Indonesia. Both lowlands exhibit the important role of upstream wetlands in regulating the flow downstream. We expect that this work facilitates a better prediction of fire-prone conditions in these regions.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
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Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Guillaume Nord, Brice Boudevillain, Alexis Berne, Flora Branger, Isabelle Braud, Guillaume Dramais, Simon Gérard, Jérôme Le Coz, Cédric Legoût, Gilles Molinié, Joel Van Baelen, Jean-Pierre Vandervaere, Julien Andrieu, Coralie Aubert, Martin Calianno, Guy Delrieu, Jacopo Grazioli, Sahar Hachani, Ivan Horner, Jessica Huza, Raphaël Le Boursicaud, Timothy H. Raupach, Adriaan J. Teuling, Magdalena Uber, Béatrice Vincendon, and Annette Wijbrans
Earth Syst. Sci. Data, 9, 221–249, https://doi.org/10.5194/essd-9-221-2017, https://doi.org/10.5194/essd-9-221-2017, 2017
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A high space–time resolution dataset linking hydrometeorological forcing and hydro-sedimentary response in a mesoscale catchment (Auzon, 116 km2) of the Ardèche region (France) is presented. This region is subject to precipitating systems of Mediterranean origin, which can result in significant rainfall amount. The data presented cover a period of 4 years (2011–2014) and aim at improving the understanding of processes triggering flash floods.
Metodija M. Shapkalijevski, Huug G. Ouwersloot, Arnold F. Moene, and Jordi Vilà-Guerau de Arrellano
Atmos. Chem. Phys., 17, 1623–1640, https://doi.org/10.5194/acp-17-1623-2017, https://doi.org/10.5194/acp-17-1623-2017, 2017
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Hendrik Wouters, Matthias Demuzere, Ulrich Blahak, Krzysztof Fortuniak, Bino Maiheu, Johan Camps, Daniël Tielemans, and Nicole P. M. van Lipzig
Geosci. Model Dev., 9, 3027–3054, https://doi.org/10.5194/gmd-9-3027-2016, https://doi.org/10.5194/gmd-9-3027-2016, 2016
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A methodology is presented for translating three-dimensional information of urban areas into land-surface parameters that can be easily employed in atmospheric modelling. As demonstrated with the COSMO-CLM model for a Belgian summer, it enables them to represent urban heat islands and their dependency on urban design with a low computational cost. It allows for efficiently incorporating urban information systems (e.g., WUDAPT) into climate change assessment and numerical weather prediction.
Luping Su, Edward G. Patton, Jordi Vilà-Guerau de Arellano, Alex B. Guenther, Lisa Kaser, Bin Yuan, Fulizi Xiong, Paul B. Shepson, Li Zhang, David O. Miller, William H. Brune, Karsten Baumann, Eric Edgerton, Andrew Weinheimer, Pawel K. Misztal, Jeong-Hoo Park, Allen H. Goldstein, Kate M. Skog, Frank N. Keutsch, and John E. Mak
Atmos. Chem. Phys., 16, 7725–7741, https://doi.org/10.5194/acp-16-7725-2016, https://doi.org/10.5194/acp-16-7725-2016, 2016
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
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In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Rohini Kumar, Jude L. Musuuza, Anne F. Van Loon, Adriaan J. Teuling, Roland Barthel, Jurriaan Ten Broek, Juliane Mai, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 20, 1117–1131, https://doi.org/10.5194/hess-20-1117-2016, https://doi.org/10.5194/hess-20-1117-2016, 2016
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In a maiden attempt, we performed a multiscale evaluation of the widely used SPI to characterize local- and regional-scale groundwater (GW) droughts using observations at 2040 groundwater wells in Germany and the Netherlands. From this data-based exploratory analysis, we provide sufficient evidence regarding the inability of the SPI to characterize GW drought events, and stress the need for more GW observations and accounting for regional hydrogeological characteristics in GW drought monitoring.
Lieke A. Melsen, Adriaan J. Teuling, Paul J. J. F. Torfs, Remko Uijlenhoet, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 20, 1069–1079, https://doi.org/10.5194/hess-20-1069-2016, https://doi.org/10.5194/hess-20-1069-2016, 2016
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A meta-analysis on 192 peer-reviewed articles reporting applications of a land surface model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
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In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
S. V. Kumar, C. D. Peters-Lidard, J. A. Santanello, R. H. Reichle, C. S. Draper, R. D. Koster, G. Nearing, and M. F. Jasinski
Hydrol. Earth Syst. Sci., 19, 4463–4478, https://doi.org/10.5194/hess-19-4463-2015, https://doi.org/10.5194/hess-19-4463-2015, 2015
C. Darbieu, F. Lohou, M. Lothon, J. Vilà-Guerau de Arellano, F. Couvreux, P. Durand, D. Pino, E. G. Patton, E. Nilsson, E. Blay-Carreras, and B. Gioli
Atmos. Chem. Phys., 15, 10071–10086, https://doi.org/10.5194/acp-15-10071-2015, https://doi.org/10.5194/acp-15-10071-2015, 2015
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A case study of the BLLAST experiment is considered to explore the decay of turbulence that occurs in the convective boundary layer over land during the afternoon. Based on observations and on a large-eddy simulation, the analysis reveals two phases in the afternoon: a first quasi-stationary phase when the turbulent kinetic energy slowly decays without significant change in the turbulence structure and a second phase of more rapid decay with a change in spectral turbulence characteristics.
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
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Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
H. P. Pietersen, J. Vilà-Guerau de Arellano, P. Augustin, A. van de Boer, O. de Coster, H. Delbarre, P. Durand, M. Fourmentin, B. Gioli, O. Hartogensis, F. Lohou, M. Lothon, H. G. Ouwersloot, D. Pino, and J. Reuder
Atmos. Chem. Phys., 15, 4241–4257, https://doi.org/10.5194/acp-15-4241-2015, https://doi.org/10.5194/acp-15-4241-2015, 2015
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
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Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
M. Combe, J. Vilà-Guerau de Arellano, H. G. Ouwersloot, C. M. J. Jacobs, and W. Peters
Biogeosciences, 12, 103–123, https://doi.org/10.5194/bg-12-103-2015, https://doi.org/10.5194/bg-12-103-2015, 2015
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This study investigates the interactions among the carbon, water and heat cycles above a maize field at the diurnal scale. We couple two land-surface schemes, corresponding to two different modelling approaches, to the same atmospheric boundary-layer (ABL) model. We find the simpler meteorological approach best reproduces the surface and upper-air observations. Finally, we show that the interaction of subsidence with ABL dynamics is key to explain the daytime atmospheric CO2 budget.
C. C. van Heerwaarden and A. J. Teuling
Biogeosciences, 11, 6159–6171, https://doi.org/10.5194/bg-11-6159-2014, https://doi.org/10.5194/bg-11-6159-2014, 2014
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This study disentangles the response of forest and grassland to heatwaves, to interpret the findings of Teuling et al. (2010), who found systematically higher temperatures over forests than over grasslands in European heatwaves. By means of a study with a simple coupled land–atmosphere model, we show that the increase in stomatal resistance of vegetation under high values of vapor pressure deficit explains most of the differences and that this increase is enhanced by boundary layer feedbacks.
M. Lothon, F. Lohou, D. Pino, F. Couvreux, E. R. Pardyjak, J. Reuder, J. Vilà-Guerau de Arellano, P Durand, O. Hartogensis, D. Legain, P. Augustin, B. Gioli, D. H. Lenschow, I. Faloona, C. Yagüe, D. C. Alexander, W. M. Angevine, E Bargain, J. Barrié, E. Bazile, Y. Bezombes, E. Blay-Carreras, A. van de Boer, J. L. Boichard, A. Bourdon, A. Butet, B. Campistron, O. de Coster, J. Cuxart, A. Dabas, C. Darbieu, K. Deboudt, H. Delbarre, S. Derrien, P. Flament, M. Fourmentin, A. Garai, F. Gibert, A. Graf, J. Groebner, F. Guichard, M. A. Jiménez, M. Jonassen, A. van den Kroonenberg, V. Magliulo, S. Martin, D. Martinez, L. Mastrorillo, A. F. Moene, F. Molinos, E. Moulin, H. P. Pietersen, B. Piguet, E. Pique, C. Román-Cascón, C. Rufin-Soler, F. Saïd, M. Sastre-Marugán, Y. Seity, G. J. Steeneveld, P. Toscano, O. Traullé, D. Tzanos, S. Wacker, N. Wildmann, and A. Zaldei
Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, https://doi.org/10.5194/acp-14-10931-2014, 2014
C. C. Brauer, A. J. Teuling, P. J. J. F. Torfs, and R. Uijlenhoet
Geosci. Model Dev., 7, 2313–2332, https://doi.org/10.5194/gmd-7-2313-2014, https://doi.org/10.5194/gmd-7-2313-2014, 2014
C. C. Brauer, P. J. J. F. Torfs, A. J. Teuling, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 18, 4007–4028, https://doi.org/10.5194/hess-18-4007-2014, https://doi.org/10.5194/hess-18-4007-2014, 2014
A. I. Gevaert, A. J. Teuling, R. Uijlenhoet, S. B. DeLong, T. E. Huxman, L. A. Pangle, D. D. Breshears, J. Chorover, J. D. Pelletier, S. R. Saleska, X. Zeng, and P. A. Troch
Hydrol. Earth Syst. Sci., 18, 3681–3692, https://doi.org/10.5194/hess-18-3681-2014, https://doi.org/10.5194/hess-18-3681-2014, 2014
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
J. A. Adame, M. Martínez, M. Sorribas, P. J. Hidalgo, H. Harder, J.-M. Diesch, F. Drewnick, W. Song, J. Williams, V. Sinha, M. A. Hernández-Ceballos, J. Vilà-Guerau de Arellano, R. Sander, Z. Hosaynali-Beygi, H. Fischer, J. Lelieveld, and B. De la Morena
Atmos. Chem. Phys., 14, 2325–2342, https://doi.org/10.5194/acp-14-2325-2014, https://doi.org/10.5194/acp-14-2325-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
Z. Tao, J. A. Santanello, M. Chin, S. Zhou, Q. Tan, E. M. Kemp, and C. D. Peters-Lidard
Atmos. Chem. Phys., 13, 6207–6226, https://doi.org/10.5194/acp-13-6207-2013, https://doi.org/10.5194/acp-13-6207-2013, 2013
Related subject area
Atmospheric sciences
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
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Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
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Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
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
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of 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 models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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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 rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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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 new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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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 at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
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
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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
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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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
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Short summary
The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic atmospheric boundary layer (ABL) with weather balloons. It mines observational data from global radio soundings, satellite and reanalysis data from the last 40 years to constrain and initialize an ABL model and automizes multiple experiments in parallel. CLASS4GL aims at fostering a better understanding of land–atmosphere feedbacks and the drivers of extreme weather.
The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic...
