Articles | Volume 5, issue 2
https://doi.org/10.5194/wcd-5-511-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-5-511-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying uncertainty in simulations of the West African monsoon with the use of surrogate models
Matthias Fischer
CORRESPONDING AUTHOR
Institute of Engineering Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
Peter Knippertz
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Roderick van der Linden
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Alexander Lemburg
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Gregor Pante
Deutscher Wetterdienst, Offenbach, Germany
Carsten Proppe
Institute of Engineering Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany
John H. Marsham
School of Earth and Environment, University of Leeds, Leeds, United Kingdom
Related authors
Matthias Fischer, Peter Knippertz, and Carsten Proppe
Weather Clim. Dynam., 6, 113–130, https://doi.org/10.5194/wcd-6-113-2025, https://doi.org/10.5194/wcd-6-113-2025, 2025
Short summary
Short summary
The West African monsoon is vital for millions but difficult to represent with numerical models. Our research aims at improving monsoon simulations by optimizing three model parameters – entrainment rate, ice fall speed, and soil moisture evaporation – using an advanced surrogate-based multi-objective optimization framework. Results show that tuning these parameters can sometimes improve certain monsoon characteristics, however at the expense of others, highlighting the power of our approach.
Tanguy Jonville, Maurus Borne, Cyrille Flamant, Juan Cuesta, Olivier Bock, Pierre Bosser, Christophe Lavaysse, Andreas Fink, and Peter Knippertz
Atmos. Chem. Phys., 25, 9765–9786, https://doi.org/10.5194/acp-25-9765-2025, https://doi.org/10.5194/acp-25-9765-2025, 2025
Short summary
Short summary
Tropical waves structure the atmosphere. Four types of tropical waves (equatorial Rossby – ER, Kelvin, MRG-TD1, and MRG-TD2 – mixed Rossby gravity–tropical depressions) are studied using filters, satellite measurements, and in situ data from the Clouds–Atmosphere Dynamics–Dust Interaction in West Africa (CADDIWA) campaign held in September 2021 in Cabo Verde. ER waves impact temperature and humidity above 2500 m, MRG-TD1 around 3500 m, and MRG-TD2 around 2000 m. Interactions between these waves favor tropical cyclone formation.
Ines Dillerup, Alexander Lemburg, Sebastian Buschow, and Joaquim G. Pinto
EGUsphere, https://doi.org/10.5194/egusphere-2025-3379, https://doi.org/10.5194/egusphere-2025-3379, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
We analyze the duration of large-scale weather patterns and their link to near-surface temperatures during heatwaves in Central Europe for 1950–2023. Compared to non-heatwave days, a stronger link between them is found on heatwave days from May to September. We relate our results to typical long-lasting weather patterns known as weather regimes. In July and August, weather patterns last longer as west winds are often blocked by Scandinavian and European blocking regimes, inducing hot extremes.
Lina Lucas, Christian Barthlott, Corinna Hoose, and Peter Knippertz
EGUsphere, https://doi.org/10.5194/egusphere-2025-3069, https://doi.org/10.5194/egusphere-2025-3069, 2025
Short summary
Short summary
We studied how climate change and cleaner air could affect severe storms in Central Europe. Using high-resolution weather simulations of past supercell storms under warmer and less polluted conditions, we found that storms may become more intense, with heavier rainfall and larger hailstones. These changes suggest an increased risk of damage in the future. Our findings help improve understanding of how extreme storms may evolve in a changing climate.
Christopher Johannes Diekmann, Matthias Schneider, Peter Knippertz, Tim Trent, Hartmut Boesch, Amelie Ninja Roehling, John Worden, Benjamin Ertl, Farahnaz Khosrawi, and Frank Hase
Atmos. Chem. Phys., 25, 5409–5431, https://doi.org/10.5194/acp-25-5409-2025, https://doi.org/10.5194/acp-25-5409-2025, 2025
Short summary
Short summary
The West African Monsoon is the main source of rainfall over West Africa, and understanding the development of the monsoon remains challenging due to complex interactions of atmospheric processes. We make use of new satellite datasets of isotopes in tropospheric water vapour to characterize processes controlling the monsoon convection. We find that comparing different water vapour isotopes reveals effects of rain–vapour interactions and air mass transport.
Hannah Meyer, Konrad Kandler, Sylvain Dupont, Jerónimo Escribano, Jessica Girdwood, George Nikolich, Andrés Alastuey, Vicken Etyemezian, Cristina González Flórez, Adolfo González-Romero, Tareq Hussein, Mark Irvine, Peter Knippertz, Ottmar Möhler, Xavier Querol, Chris Stopford, Franziska Vogel, Frederik Weis, Andreas Wieser, Carlos Pérez García-Pando, and Martina Klose
EGUsphere, https://doi.org/10.5194/egusphere-2025-1531, https://doi.org/10.5194/egusphere-2025-1531, 2025
Short summary
Short summary
Mineral dust particles emitted from dry soils are of various sizes, yet the abundance of very large particles is not well understood. Here we measured the dust size distribution from fine to giant particles at an emission source during a field campaign in Jordan (J-WADI) using multiple instruments. Our findings show that large particles make up a significant part of the total dust mass. This knowledge is essential to improve climate models and to predict dust impacts on climate and environment.
Matthias Fischer, Peter Knippertz, and Carsten Proppe
Weather Clim. Dynam., 6, 113–130, https://doi.org/10.5194/wcd-6-113-2025, https://doi.org/10.5194/wcd-6-113-2025, 2025
Short summary
Short summary
The West African monsoon is vital for millions but difficult to represent with numerical models. Our research aims at improving monsoon simulations by optimizing three model parameters – entrainment rate, ice fall speed, and soil moisture evaporation – using an advanced surrogate-based multi-objective optimization framework. Results show that tuning these parameters can sometimes improve certain monsoon characteristics, however at the expense of others, highlighting the power of our approach.
Selina M. Kiefer, Patrick Ludwig, Sebastian Lerch, Peter Knippertz, and Joaquim G. Pinto
EGUsphere, https://doi.org/10.5194/egusphere-2024-2955, https://doi.org/10.5194/egusphere-2024-2955, 2024
Preprint withdrawn
Short summary
Short summary
Weather forecasts 14 days in advance generally have a low skill but not always. We identify reasons thereof depending on the atmospheric flow, shown by Weather Regimes (WRs). If the WRs during the forecasts follow climatological patterns, forecast skill is increased. The forecast of a cold-wave day is better when the European Blocking WR (high pressure around the British Isles) is present a few days before a cold-wave day. These results can be used to assess the reliability of predictions.
Seraphine Hauser, Franziska Teubler, Michael Riemer, Peter Knippertz, and Christian M. Grams
Weather Clim. Dynam., 5, 633–658, https://doi.org/10.5194/wcd-5-633-2024, https://doi.org/10.5194/wcd-5-633-2024, 2024
Short summary
Short summary
Blocking over Greenland has substantial impacts on the weather and climate in mid- and high latitudes. This study applies a quasi-Lagrangian thinking on the dynamics of Greenland blocking and reveals two pathways of anticyclonic anomalies linked to the block. Moist processes were found to play a dominant role in the formation and maintenance of blocking. This emphasizes the necessity of the correct representation of moist processes in weather and climate models to realistically depict blocking.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
Short summary
Short summary
Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Maurus Borne, Peter Knippertz, Martin Weissmann, Benjamin Witschas, Cyrille Flamant, Rosimar Rios-Berrios, and Peter Veals
Atmos. Meas. Tech., 17, 561–581, https://doi.org/10.5194/amt-17-561-2024, https://doi.org/10.5194/amt-17-561-2024, 2024
Short summary
Short summary
This study assesses the quality of Aeolus wind measurements over the tropical Atlantic. The results identified the accuracy and precision of the Aeolus wind measurements and the potential source of errors. For instance, the study revealed atmospheric conditions that can deteriorate the measurement quality, such as weaker laser signal in cloudy or dusty conditions, and confirmed the presence of an orbital-dependant bias. These results can help to improve the Aeolus wind measurement algorithm.
Hyunju Jung, Peter Knippertz, Yvonne Ruckstuhl, Robert Redl, Tijana Janjic, and Corinna Hoose
Weather Clim. Dynam., 4, 1111–1134, https://doi.org/10.5194/wcd-4-1111-2023, https://doi.org/10.5194/wcd-4-1111-2023, 2023
Short summary
Short summary
A narrow rainfall belt in the tropics is an important feature for large-scale circulations and the global water cycle. The accurate simulation of this rainfall feature has been a long-standing problem, with the reasons behind that unclear. We present a novel diagnostic tool that allows us to disentangle processes important for rainfall, which changes due to modifications in model. Using our diagnostic tool, one can potentially identify sources of uncertainty in weather and climate models.
Lea Eisenstein, Benedikt Schulz, Joaquim G. Pinto, and Peter Knippertz
Weather Clim. Dynam., 4, 981–999, https://doi.org/10.5194/wcd-4-981-2023, https://doi.org/10.5194/wcd-4-981-2023, 2023
Short summary
Short summary
Mesoscale high-wind features within extratropical cyclones can cause immense damage. In Part 1 of this work, we introduced RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), an objective, flexible identification tool for these wind features based on a probabilistic random forest. Here, we use RAMEFI to compile a climatology of the features over 19 extended winter seasons over western and central Europe, focusing on relative occurrence, affected areas and further characteristics.
Valerian Hahn, Ralf Meerkötter, Christiane Voigt, Sonja Gisinger, Daniel Sauer, Valéry Catoire, Volker Dreiling, Hugh Coe, Cyrille Flamant, Stefan Kaufmann, Jonas Kleine, Peter Knippertz, Manuel Moser, Philip Rosenberg, Hans Schlager, Alfons Schwarzenboeck, and Jonathan Taylor
Atmos. Chem. Phys., 23, 8515–8530, https://doi.org/10.5194/acp-23-8515-2023, https://doi.org/10.5194/acp-23-8515-2023, 2023
Short summary
Short summary
During the DACCIWA campaign in West Africa, we found a 35 % increase in the cloud droplet concentration that formed in a polluted compared with a less polluted environment and a decrease of 17 % in effective droplet diameter. Radiative transfer simulations, based on the measured cloud properties, reveal that these low-level polluted clouds radiate only 2.6 % more energy back to space, compared with a less polluted cloud. The corresponding additional decrease in temperature is rather small.
Seraphine Hauser, Franziska Teubler, Michael Riemer, Peter Knippertz, and Christian M. Grams
Weather Clim. Dynam., 4, 399–425, https://doi.org/10.5194/wcd-4-399-2023, https://doi.org/10.5194/wcd-4-399-2023, 2023
Short summary
Short summary
Blocking describes a flow configuration in the midlatitudes where stationary high-pressure systems block the propagation of weather systems. This study combines three individual perspectives that capture the dynamics and importance of various processes in the formation of a major blocking in 2016 from a weather regime perspective. In future work, this framework will enable a holistic view of the dynamics and the role of moist processes in different life cycle stages of blocked weather regimes.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
Short summary
Short summary
Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Susanna Mohr, Uwe Ehret, Michael Kunz, Patrick Ludwig, Alberto Caldas-Alvarez, James E. Daniell, Florian Ehmele, Hendrik Feldmann, Mário J. Franca, Christian Gattke, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Marc Scheibel, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, https://doi.org/10.5194/nhess-23-525-2023, 2023
Short summary
Short summary
The flood event in July 2021 was one of the most severe disasters in Europe in the last half century. The objective of this two-part study is a multi-disciplinary assessment that examines the complex process interactions in different compartments, from meteorology to hydrological conditions to hydro-morphological processes to impacts on assets and environment. In addition, we address the question of what measures are possible to generate added value to early response management.
Moritz Zemann, Roderick van der Linden, Dan Trinh Cong, Duong Hoang Thai Vu, Nguyet Minh Nguyen, Frank Seidel, Peter Oberle, Franz Nestmann, and Andreas H. Fink
EGUsphere, https://doi.org/10.5194/egusphere-2022-1447, https://doi.org/10.5194/egusphere-2022-1447, 2023
Preprint withdrawn
Short summary
Short summary
The study investigates the possibility to predict wave heights close to the coast of the Mekong Delta based on long time climate model wave heights which are only availabe offshore. Due to severe coastal erosion in the Mekong Delta with average land loss rates of up to 10m per year, the coast needs to be protected from wave attacks e.g. by breakwaters. To design a breakwater in the right dimensions for the local conditions, the knowledge of wave heights is essential to the performing engineer.
Lea Eisenstein, Benedikt Schulz, Ghulam A. Qadir, Joaquim G. Pinto, and Peter Knippertz
Weather Clim. Dynam., 3, 1157–1182, https://doi.org/10.5194/wcd-3-1157-2022, https://doi.org/10.5194/wcd-3-1157-2022, 2022
Short summary
Short summary
Mesoscale high-wind features within extratropical cyclones can cause immense damage. Here, we present RAMEFI, a novel approach to objectively identify the wind features based on a probabilistic random forest. RAMEFI enables a wide range of applications such as probabilistic predictions for the occurrence or a multi-decadal climatology of these features, which will be the focus of Part 2 of the study, with the goal of improving wind and, specifically, wind gust forecasts in the long run.
Adrien Deroubaix, Laurent Menut, Cyrille Flamant, Peter Knippertz, Andreas H. Fink, Anneke Batenburg, Joel Brito, Cyrielle Denjean, Cheikh Dione, Régis Dupuy, Valerian Hahn, Norbert Kalthoff, Fabienne Lohou, Alfons Schwarzenboeck, Guillaume Siour, Paolo Tuccella, and Christiane Voigt
Atmos. Chem. Phys., 22, 3251–3273, https://doi.org/10.5194/acp-22-3251-2022, https://doi.org/10.5194/acp-22-3251-2022, 2022
Short summary
Short summary
During the summer monsoon in West Africa, pollutants emitted in urbanized areas modify cloud cover and precipitation patterns. We analyze these patterns with the WRF-CHIMERE model, integrating the effects of aerosols on meteorology, based on the numerous observations provided by the Dynamics-Aerosol-Climate-Interactions campaign. This study adds evidence to recent findings that increased pollution levels in West Africa delay the breakup time of low-level clouds and reduce precipitation.
Christopher J. Diekmann, Matthias Schneider, Benjamin Ertl, Frank Hase, Omaira García, Farahnaz Khosrawi, Eliezer Sepúlveda, Peter Knippertz, and Peter Braesicke
Earth Syst. Sci. Data, 13, 5273–5292, https://doi.org/10.5194/essd-13-5273-2021, https://doi.org/10.5194/essd-13-5273-2021, 2021
Short summary
Short summary
The joint analysis of different stable water isotopes in water vapour is a powerful tool for investigating atmospheric moisture pathways. This paper presents a novel global and multi-annual dataset of H2O and HDO in mid-tropospheric water vapour by using data from the satellite sensor Metop/IASI. Due to its unique combination of coverage and resolution in space and time, this dataset is highly promising for studying the hydrological cycle and its representation in weather and climate models.
Fabienne Dahinden, Franziska Aemisegger, Heini Wernli, Matthias Schneider, Christopher J. Diekmann, Benjamin Ertl, Peter Knippertz, Martin Werner, and Stephan Pfahl
Atmos. Chem. Phys., 21, 16319–16347, https://doi.org/10.5194/acp-21-16319-2021, https://doi.org/10.5194/acp-21-16319-2021, 2021
Short summary
Short summary
We use high-resolution numerical isotope modelling and Lagrangian backward trajectories to identify moisture transport pathways and governing physical and dynamical processes that affect the free-tropospheric humidity and isotopic variability over the eastern subtropical North Atlantic. Furthermore, we conduct a thorough isotope modelling validation with aircraft and remote-sensing observations of water vapour isotopes.
Alberto Caldas-Alvarez, Samiro Khodayar, and Peter Knippertz
Weather Clim. Dynam., 2, 561–580, https://doi.org/10.5194/wcd-2-561-2021, https://doi.org/10.5194/wcd-2-561-2021, 2021
Short summary
Short summary
The prediction capabilities of GPS, operational (low-resolution) and targeted (high-resolution) radiosondes for data assimilation in a Mediterranean heavy precipitation event at different model resolutions are investigated. The results show that even if GPS provides accurate observations, their lack of vertical information hampers the improvement, demonstrating the need for assimilating radiosondes, where the location and timing of release was more determinant than the vertical resolution.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
Short summary
Short summary
Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Gregor Pante, Peter Knippertz, Andreas H. Fink, and Anke Kniffka
Atmos. Chem. Phys., 21, 35–55, https://doi.org/10.5194/acp-21-35-2021, https://doi.org/10.5194/acp-21-35-2021, 2021
Short summary
Short summary
Seasonal rainfall amounts along the densely populated West African Guinea coast have been decreasing during the past 35 years, with recently accelerating trends. We find strong indications that this is in part related to increasing human air pollution in the region. Given the fast increase in emissions, the political implications of this work are significant. Reducing air pollution locally and regionally would mitigate an imminent health crisis and socio-economic damage from reduced rainfall.
Cited articles
Agustí-Panareda, A., Beljaars, A., Cardinali, C., Genkova, I., and Thorncroft, C.: Impacts of Assimilating AMMA Soundings on ECMWF Analyses and Forecasts, Weather Forecast., 25, 1142–1160, https://doi.org/10.1175/2010waf2222370.1, 2010. a
Brierley, C. M., Zhao, A., Harrison, S. P., Braconnot, P., Williams, C. J. R., Thornalley, D. J. R., Shi, X., Peterschmitt, J.-Y., Ohgaito, R., Kaufman, D. S., Kageyama, M., Hargreaves, J. C., Erb, M. P., Emile-Geay, J., D'Agostino, R., Chandan, D., Carré, M., Bartlein, P. J., Zheng, W., Zhang, Z., Zhang, Q., Yang, H., Volodin, E. M., Tomas, R. A., Routson, C., Peltier, W. R., Otto-Bliesner, B., Morozova, P. A., McKay, N. P., Lohmann, G., Legrande, A. N., Guo, C., Cao, J., Brady, E., Annan, J. D., and Abe-Ouchi, A.: Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations, Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, 2020. a
Burpee, R. W.: The Origin and Structure of Easterly Waves in the Lower Troposphere of North Africa, J. Atmos. Sci., 29, 77–90, https://doi.org/10.1175/1520-0469(1972)029<0077:toasoe>2.0.co;2, 1972. a
Cheng, K., Lu, Z., Ling, C., and Zhou, S.: Surrogate-assisted global sensitivity analysis: an overview, Struct. Multidiscip. Optimiz., 61, 1187–1213, https://doi.org/10.1007/s00158-019-02413-5, 2020. a, b
Claussen, M., Dallmeyer, A., and Bader, J.: Theory and Modeling of the African Humid Period and the Green Sahara, in: Oxford Research Encyclopedia of Climate Science, Oxford University Press, https://doi.org/10.1093/acrefore/9780190228620.013.532, 2017. a
Cook, K. H. and Vizy, E. K.: Coupled Model Simulations of the West African Monsoon System: Twentieth- and Twenty-First-Century Simulations, J. Climate, 19, 3681–3703, https://doi.org/10.1175/jcli3814.1, 2006. a
Diamond, M. S., Director, H. M., Eastman, R., Possner, A., and Wood, R.: Substantial Cloud Brightening From Shipping in Subtropical Low Clouds, AGU Adv., 1, e2019AV000111, https://doi.org/10.1029/2019av000111, 2020. a
DWD – Deutscher Wetterdienst: ICON Namelist Overview, Tech. rep., 2019. a
Fink, A. H. and Reiner, A.: Spatiotemporal variability of the relation between African easterly waves and West African squall lines in 1998 and 1999, J. Geophys. Res., 108, 4332, https://doi.org/10.1029/2002jd002816, 2003. a, b
Fink, A. H., Agustí-Panareda, A., Parker, D. J., Lafore, J.-P., Ngamini, J.-B., Afiesimama, E., Beljaars, A., Bock, O., Christoph, M., Didé, F., Faccani, C., Fourrié, N., Karbou, F., Polcher, J., Mumba, Z., Nuret, M., Pohle, S., Rabier, F., Tompkins, A. M., and Wilson, G.: Operational meteorology in West Africa: observational networks, weather analysis and forecasting, Atmos. Sci. Lett., 12, 135–141, https://doi.org/10.1002/asl.324, 2011. a
Fink, A. H., Engel, T., Ermert, V., van der Linden, R., Schneidewind, M., Redl, R., Afiesimama, E., Thiaw, W. M., Yorke, C., Evans, M., and Janicot, S.: Mean Climate and Seasonal Cycle, in: Meteorology of Tropical West Africa, John Wiley & Sons, Ltd, 1–39, https://doi.org/10.1002/9781118391297.ch1, 2017. a, b
Flaounas, E., Bastin, S., and Janicot, S.: Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF, Clim. Dynam., 36, 1083–1105, https://doi.org/10.1007/s00382-010-0785-3, 2011. a
Fletcher, C. G., Kravitz, B., and Badawy, B.: Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity, Atmos. Chem. Phys., 18, 17529–17543, https://doi.org/10.5194/acp-18-17529-2018, 2018. a, b, c
Flohn, H.: Investigations on the Tropical Easterly Jet, Bonner meteorologische Abhandlungen, Dümmlers, https://www2.meteo.uni-bonn.de/bibliothek/Flohn_Publikationen/K141-K190_1959-1965/K176.pdf (last access: 12 April 2024), 1964. a
Fotso-Nguemo, T. C., Vondou, D. A., Pokam, W. M., Djomou, Z. Y., Diallo, I., Haensler, A., Tchotchou, L. A. D., Kamsu-Tamo, P. H., Gaye, A. T., and Tchawoua, C.: On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa, Clim. Dynam., 49, 3813–3838, https://doi.org/10.1007/s00382-017-3547-7, 2017. a
Gbode, I. E., Dudhia, J., Ogunjobi, K. O., and Ajayi, V. O.: Sensitivity of different physics schemes in the WRF model during a West African monsoon regime, Theor. Appl. Climatol., 136, 733–751, https://doi.org/10.1007/s00704-018-2538-x, 2018. a
Gbode, I. E., Babalola, T. E., Diro, G. T., and Intsiful, J. D.: Assessment of ERA5 and ERA-Interim in Reproducing Mean and Extreme Climates over West Africa, Adv. Atmos. Sci., 40, 570–586, https://doi.org/10.1007/s00376-022-2161-8, 2023. a
Gill, A. E.: Some simple solutions for heat-induced tropical circulation, Q. J. Roy. Meteorol. Soc., 106, 447–462, https://doi.org/10.1002/qj.49710644905, 1980. a
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: An emulator approach to stratocumulus susceptibility, Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, 2019. a
Grist, J. P. and Nicholson, S. E.: A Study of the Dynamic Factors Influencing the Rainfall Variability in the West African Sahel, J. Climate, 14, 1337–1359, https://doi.org/10.1175/1520-0442(2001)014<1337:asotdf>2.0.co;2, 2001. a
Haile, M.: Weather patterns, food security and humanitarian response in sub-Saharan Africa, Philos. T. Roy. Soc. B, 360, 2169–2182, https://doi.org/10.1098/rstb.2005.1746, 2005. a
Hall, N. M. and Peyrillé, P.: Dynamics of the West African monsoon, Journal de Physique IV (Proceedings), 139, 81–99, https://doi.org/10.1051/jp4:2006139007, 2006. a
Hannak, L., Knippertz, P., Fink, A. H., Kniffka, A., and Pante, G.: Why Do Global Climate Models Struggle to Represent Low-Level Clouds in the West African Summer Monsoon?, J, of Climate, 30, 1665–1687, https://doi.org/10.1175/jcli-d-16-0451.1, 2017. a
Hastenrath, S.: Climate Dynamics of the Tropics, Springer Netherlands, https://doi.org/10.1007/978-94-011-3156-8, 1991. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Holden, P. B., Edwards, N. R., Oliver, K. I. C., Lenton, T. M., and Wilkinson, R. D.: A probabilistic calibration of climate sensitivity and terrestrial carbon change in GENIE-1, Clim. Dynam., 35, 785–806, https://doi.org/10.1007/s00382-009-0630-8, 2009. a
Hopcroft, P. O., Valdes, P. J., Harper, A. B., and Beerling, D. J.: Multi vegetation model evaluation of the Green Sahara climate regime, Geophys. Res. Lett., 44, 6804–6813, https://doi.org/10.1002/2017gl073740, 2017. a
Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., and Tan, J.: GPM IMERG final precipitation L3 half hourly 0.1 degree × 0.1 degree V06, GES DISC – Goddard Earth Sciences Data and Information Services Center [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/06, 2019. a, b
Iwanaga, T., Usher, W., and Herman, J.: Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses, Socio-Environ. Syst. Model., 4, 18155, https://doi.org/10.18174/sesmo.18155, 2022. a
Janicot, S., Lafore, J.-P., and Thorncroft, C.: The West African Monsoon, in: The Global Monsoon System, World Scientific, 111–135, https://doi.org/10.1142/9789814343411_0008, 2011. a
Kendon, E. J., Stratton, R. A., Tucker, S., Marsham, J. H., Berthou, S., Rowell, D. P., and Senior, C. A.: Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale, Nat. Commun., 10, 1794, https://doi.org/10.1038/s41467-019-09776-9, 2019. a
Kiladis, G. N., Thorncroft, C. D., and Hall, N. M. J.: Three-Dimensional Structure and Dynamics of African Easterly Waves. Part I: Observations, J. Atmos. Sci., 63, 2212–2230, https://doi.org/10.1175/jas3741.1, 2006. a
Klein, C., Heinzeller, D., Bliefernicht, J., and Kunstmann, H.: Variability of West African monsoon patterns generated by a WRF multi-physics ensemble, Clim. Dynam., 45, 2733–2755, https://doi.org/10.1007/s00382-015-2505-5, 2015. a
Kniffka, A., Knippertz, P., and Fink, A. H.: The role of low-level clouds in the West African monsoon system, Atmos. Chem. Phys., 19, 1623–1647, https://doi.org/10.5194/acp-19-1623-2019, 2019. a
Knippertz, P., Ansmann, A., Althausen, D., Müller, D., Tesche, M., Bierwirth, E., Dinter, T., Müller, T., Hoyningen-Huene, W. V., Schepanski, K., Wendisch, M., Heinold, B., Kandler, K., Petzold, A., Schütz, L., and Tegen, I.: Dust mobilization and transport in the northern Sahara during SAMUM 2006 – a meteorological overview, Tellus B, 61, 12–31, https://doi.org/10.1111/j.1600-0889.2008.00380.x, 2009. a
Kruskal, W. H. and Wallis, W. A.: Use of Ranks in One-Criterion Variance Analysis, J. Am. Stat. Assoc., 47, 583–621, https://doi.org/10.1080/01621459.1952.10483441, 1952. a
Lang, S. T. K., Lock, S.-J., Leutbecher, M., Bechtold, P., and Forbes, R. M.: Revision of the Stochastically Perturbed Parametrisations model uncertainty scheme in the Integrated Forecasting System, Q. J. Roy. Meteorol. Soc., 147, 1364–1381, https://doi.org/10.1002/qj.3978, 2021. a
Lavaysse, C., Flamant, C., Janicot, S., Parker, D. J., Lafore, J.-P., Sultan, B., and Pelon, J.: Seasonal evolution of the West African heat low: a climatological perspective, Clim. Dynam., 33, 313–330, https://doi.org/10.1007/s00382-009-0553-4, 2009. a
Lebel, T. and Ali, A.: Recent trends in the Central and Western Sahel rainfall regime (1990–2007), J. Hydrol., 375, 52–64, https://doi.org/10.1016/j.jhydrol.2008.11.030, 2009. a
Lebel, T., Diedhiou, A., and Laurent, H.: Seasonal cycle and interannual variability of the Sahelian rainfall at hydrological scales, J. Geophys. Res., 108, 8389, https://doi.org/10.1029/2001jd001580, 2003. a
Lee, L. A., Carslaw, K. S., Pringle, K. J., Mann, G. W., and Spracklen, D. V.: Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters, Atmos. Chem. Phys., 11, 12253–12273, https://doi.org/10.5194/acp-11-12253-2011, 2011. a, b, c
Lemburg, A., Bader, J., and Claussen, M.: Sahel Rainfall–Tropical Easterly Jet Relationship on Synoptic to Intraseasonal Time Scales, Mon. Weather Rev., 147, 1733–1752, https://doi.org/10.1175/mwr-d-18-0254.1, 2019. a, b, c
Loeppky, J. L., Sacks, J., and Welch, W. J.: Choosing the Sample Size of a Computer Experiment: A Practical Guide, Technometrics, 51, 366–376, https://doi.org/10.1198/tech.2009.08040, 2009. a
Lohou, F., Kalthoff, N., Adler, B., Babić, K., Dione, C., Lothon, M., Pedruzo-Bagazgoitia, X., and Zouzoua, M.: Conceptual model of diurnal cycle of low-level stratiform clouds over southern West Africa, Atmos. Chem. Phys., 20, 2263–2275, https://doi.org/10.5194/acp-20-2263-2020, 2020. a
Lu, D. and Ricciuto, D.: Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques, Geosci. Model Dev., 12, 1791–1807, https://doi.org/10.5194/gmd-12-1791-2019, 2019. a, b
Marsham, J. H., Dixon, N. S., Garcia-Carreras, L., Lister, G. M. S., Parker, D. J., Knippertz, P., and Birch, C. E.: The role of moist convection in the West African monsoon system: Insights from continental-scale convection-permitting simulations, Geophys. Res. Lett., 40, 1843–1849, https://doi.org/10.1002/grl.50347, 2013. a, b
Martin, G. M., Peyrillé, P., Roehrig, R., Rio, C., Caian, M., Bellon, G., Codron, F., Lafore, J.-P., Poan, D. E., and Idelkadi, A.: Understanding the West African Monsoon from the analysis of diabatic heating distributions as simulated by climate models, J. Adv. Model. Earth Syst., 9, 239–270, https://doi.org/10.1002/2016ms000697, 2017. a
Massoud, E. C.: Emulation of environmental models using polynomial chaos expansion, Environ. Model. Softw., 111, 421–431, https://doi.org/10.1016/j.envsoft.2018.10.008, 2019. a, b, c
Mathon, V., Laurent, H., and Lebel, T.: Mesoscale Convective System Rainfall in the Sahel, J. Appl. Meteorol., 41, 1081–1092, https://doi.org/10.1175/1520-0450(2002)041<1081:mcsrit>2.0.co;2, 2002. a
Matsui, T., Zhang, S. Q., Lang, S. E., Tao, W.-K., Ichoku, C., and Peters-Lidard, C. D.: Impact of radiation frequency, precipitation radiative forcing, and radiation column aggregation on convection-permitting West African monsoon simulations, Clim. Dynam., 55, 193–213, https://doi.org/10.1007/s00382-018-4187-2, 2018. a
Messager, C., Gallée, H., and Brasseur, O.: Precipitation sensitivity to regional SST in a regional climate simulation during the West African monsoon for two dry years, Clim. Dynam., 22, 249–266, https://doi.org/10.1007/s00382-003-0381-x, 2004. a
Morris, M. D. and Mitchell, T. J.: Exploratory designs for computational experiments, J. Stat. Plan. Infer., 43, 381–402, https://doi.org/10.1016/0378-3758(94)00035-t, 1995. a, b, c
Müller, J., Paudel, R., Shoemaker, C. A., Woodbury, J., Wang, Y., and Mahowald, N.: CH4 parameter estimation in CLM4.5bgc using surrogate global optimization, Geosci. Model Dev., 8, 3285–3310, https://doi.org/10.5194/gmd-8-3285-2015, 2015. a, b
Nicholson, S. E.: A revised picture of the structure of the “monsoon” and land ITCZ over West Africa, Clim. Dynam., 32, 1155–1171, https://doi.org/10.1007/s00382-008-0514-3, 2009. a
Oakley, J.: Estimating percentiles of uncertain computer code outputs, Appl. Stat.-J. Roy. C, 53, 83–93, https://doi.org/10.1046/j.0035-9254.2003.05044.x, 2004. a
Ollinaho, P., Lock, S.-J., Leutbecher, M., Bechtold, P., Beljaars, A., Bozzo, A., Forbes, R. M., Haiden, T., Hogan, R. J., and Sandu, I.: Towards process-level representation of model uncertainties: stochastically perturbed parametrizations in the ECMWF ensemble, Qu. J. Roy. Meteorol. Soc., 143, 408–422, https://doi.org/10.1002/qj.2931, 2017. a
Paeth, H., Capo-Chichi, A., and Endlicher, W.: Climate change and food security in tropical West Africa – a dynamic-statistical modelling approach, Erdkunde, 62, 101–115, https://doi.org/10.3112/erdkunde.2008.02.01, 2008. a
Pante, G. and Knippertz, P.: Resolving Sahelian thunderstorms improves mid-latitude weather forecasts, Nat. Commun., 10, 3487, https://doi.org/10.1038/s41467-019-11081-4, 2019. a, b, c
Parker, D. J., Fink, A., Janicot, S., Ngamini, J.-B., Douglas, M., Afiesimama, E., Agusti-Panareda, A., Beljaars, A., Dide, F., Diedhiou, A., Lebel, T., Polcher, J., Redelsperger, J.-L., Thorncroft, C., and Wilson, G. A.: The AMMA Radiosonde Program and its Implications for the Future of Atmospheric Monitoring Over Africa, B. Am. Meteorol. Soc., 89, 1015–1028, https://doi.org/10.1175/2008bams2436.1, 2008. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011. a
Quinn, G. P. and Keough, M. J.: Experimental Design and Data Analysis for Biologists, Cambridge University Press, ISBN 9780511806384, https://doi.org/10.1017/cbo9780511806384, 2002. a
Raschendorfer, M.: Operationelles NWV-System, hier: Verminderung der minimalen Diffusionskoeffizienten für COSMO-EU/DE/EPS, Tech. rep., https://www.dwd.de/DE/fachnutzer/forschung_lehre/numerische_wettervorhersage/nwv_aenderungen/_functions/DownloadBox_modellaenderungen/cosmo_de/pdf_2011_2015/pdf_cosmo_de_29_11_2012.pdf?__blob=publicationFile&v=4 (last access: 12 April 2024), 2012. a
Rasmussen, C. E. and Williams, C. K. I.: Gaussian Processes for Machine Learning, The MIT Press, https://doi.org/10.7551/mitpress/3206.001.0001, 2005. a, b, c
Ray, J., Hou, Z., Huang, M., Sargsyan, K., and Swiler, L.: Bayesian Calibration of the Community Land Model Using Surrogates, SIAM/ASA J. Uncertain. Quantif., 3, 199–233, https://doi.org/10.1137/140957998, 2015. a, b, c
Reed, R. J., Norquist, D. C., and Recker, E. E.: The Structure and Properties of African Wave Disturbances as Observed During Phase III of GATE, Mon. Weather Rev., 105, 317–333, https://doi.org/10.1175/1520-0493(1977)105<0317:tsapoa>2.0.co;2, 1977. a
Reinert, D., Prill, F., Frank, H., Denhard, M., and Zängl, G.: Database Reference Manual for ICON and ICON-EPS, Version 1.2.11, Tech. rep., Deutscher Wetterdienst, Offenbach am Main, https://doi.org/10.5676/DWD_pub/nwv/icon_1.2.11, 2019. a, b, c, d
Rosenblatt, M.: Remarks on a Multivariate Transformation, Ann. Math. Stat., 23, 470–472, https://doi.org/10.1214/aoms/1177729394, 1952. a
Saltelli, A., Tarantola, S., and Chan, K. P.-S.: A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output, Technometrics, 41, 39–56, https://doi.org/10.1080/00401706.1999.10485594, 1999. a
Stubenrauch, C. J., Caria, G., Protopapadaki, S. E., and Hemmer, F.: 3D radiative heating of tropical upper tropospheric cloud systems derived from synergistic A-Train observations and machine learning, Atmos. Chem. Phys., 21, 1015–1034, https://doi.org/10.5194/acp-21-1015-2021, 2021. a
Tchotchou, L. A. D. and Kamga, F. M.: Sensitivity of the simulated African monsoon of summers 1993 and 1999 to convective parameterization schemes in RegCM3, Theor. Appl. Climatol., 100, 207–220, https://doi.org/10.1007/s00704-009-0181-2, 2009. a
Thorncroft, C. D., Nguyen, H., Zhang, C., and Peyrillé, P.: Annual cycle of the West African monsoon: regional circulations and associated water vapour transport, Q. J. Roy. Meteorol. Soc., 137, 129–147, https://doi.org/10.1002/qj.728, 2011. a
van der Linden, R., Knippertz, P., Fink, A. H., Ingleby, B., Maranan, M., and Benedetti, A.: The influence of DACCIWA radiosonde data on the quality of ECMWF analyses and forecasts over southern West Africa, Q. J. Roy. Meteorol. Soc., 146, 1719–1739, https://doi.org/10.1002/qj.3763, 2020. a
Vellinga, M., Arribas, A., and Graham, R.: Seasonal forecasts for regional onset of the West African monsoon, Clim. Dynam., 40, 3047–3070, https://doi.org/10.1007/s00382-012-1520-z, 2013. a
Vogel, P., Knippertz, P., Fink, A. H., Schlueter, A., and Gneiting, T.: Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa, Weather Forecast., 33, 369–388, https://doi.org/10.1175/waf-d-17-0127.1, 2018. a
Vogel, P., Knippertz, P., Fink, A. H., Schlueter, A., and Gneiting, T.: Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall in the Tropics, Weather Forecast., 35, 2367–2385, https://doi.org/10.1175/waf-d-20-0082.1, 2020. a
Walz, E., Maranan, M., van der Linden, R., Fink, A. H., and Knippertz, P.: An IMERG-Based Optimal Extended Probabilistic Climatology (EPC) as a Benchmark Ensemble Forecast for Precipitation in the Tropics and Subtropics, Weather Forecast., 36, 1561–1573, https://doi.org/10.1175/waf-d-20-0233.1, 2021. a
Wan, H., Rasch, P. J., Zhang, K., Qian, Y., Yan, H., and Zhao, C.: Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models, Geosci. Model Dev., 7, 1961–1977, https://doi.org/10.5194/gmd-7-1961-2014, 2014. a
Wellmann, C., Barrett, A. I., Johnson, J. S., Kunz, M., Vogel, B., Carslaw, K. S., and Hoose, C.: Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail, Atmos. Chem. Phys., 20, 2201–2219, https://doi.org/10.5194/acp-20-2201-2020, 2020. a
Williamson, D.: Exploratory ensemble designs for environmental models using k-extended Latin Hypercubes, Environmetrics, 26, 268–283, https://doi.org/10.1002/env.2335, 2015. a
Xue, Y., Sales, F. D., Lau, W. K.-M., Boone, A., Feng, J., Dirmeyer, P., Guo, Z., Kim, K.-M., Kitoh, A., Kumar, V., Poccard-Leclercq, I., Mahowald, N., Moufouma-Okia, W., Pegion, P., Rowell, D. P., Schemm, J., Schubert, S. D., Sealy, A., Thiaw, W. M., Vintzileos, A., Williams, S. F., and Wu, M.-L. C.: Intercomparison and analyses of the climatology of the West African Monsoon in the West African Monsoon Modeling and Evaluation project (WAMME) first model intercomparison experiment, Clim. Dynam., 35, 3–27, https://doi.org/10.1007/s00382-010-0778-2, 2010. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteorol. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a, b
Zheng, X. and Eltahir, E. A. B.: The Role of Vegetation in the Dynamics of West African Monsoons, J. Climate, 11, 2078–2096, 1998. a
Short summary
Our research enhances the understanding of the complex dynamics within the West African monsoon system by analyzing the impact of specific model parameters on its characteristics. Employing surrogate models, we identified critical factors such as the entrainment rate and the fall velocity of ice. Precise definition of these parameters in weather models could improve forecast accuracy, thus enabling better strategies to manage and reduce the impact of weather events.
Our research enhances the understanding of the complex dynamics within the West African monsoon...