Articles | Volume 15, issue 6
https://doi.org/10.5194/esd-15-1401-2024
© 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/esd-15-1401-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dakar Niño under global warming investigated by a high-resolution regionally coupled model
Geophysical Institute, University of Bergen, 5007 Bergen, Norway
Bjerknes Centre for Climate Research, 5007 Bergen, Norway
Rubén Vázquez
Departamento de Física y Matemáticas, Universidad de Alcalá, 28801 Alcalá de Henares, Spain
Instituto Universitario de Investigación Marina (INMAR), Universidad de Cádiz, 11510 Cádiz, Spain
William Cabos
Departamento de Física y Matemáticas, Universidad de Alcalá, 28801 Alcalá de Henares, Spain
Claudia Gutiérrez
Departamento de Física y Matemáticas, Universidad de Alcalá, 28801 Alcalá de Henares, Spain
Dmitry V. Sein
Alfred Wegener Institute for Polar and Marine Research, 27570 Bremerhaven, Germany
Shirshov Institute of Oceanography, Russian Academy of Sciences, Moscow, 117218, Russia
Moscow Institute of Physics and Technology, Moscow, 141701, Russia
Marie-Lou Bachèlery
Geophysical Institute, University of Bergen, 5007 Bergen, Norway
CMCC Foundation – Euro-Mediterranean Center on Climate Change, 40127 Bologna, Italy
Bjerknes Centre for Climate Research, 5007 Bergen, Norway
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Shunya Koseki, Lander R. Crespo, Jerry Tjiputra, Filippa Fransner, Noel S. Keenlyside, and David Rivas
Biogeosciences, 21, 4149–4168, https://doi.org/10.5194/bg-21-4149-2024, https://doi.org/10.5194/bg-21-4149-2024, 2024
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We investigated how the physical biases of an Earth system model influence the marine biogeochemical processes in the tropical Atlantic. With four different configurations of the model, we have shown that the versions with better SST reproduction tend to better represent the primary production and air–sea CO2 flux in terms of climatology, seasonal cycle, and response to climate variability.
Shunya Koseki, Priscilla A. Mooney, William Cabos, Miguel Ángel Gaertner, Alba de la Vara, and Juan Jesus González-Alemán
Nat. Hazards Earth Syst. Sci., 21, 53–71, https://doi.org/10.5194/nhess-21-53-2021, https://doi.org/10.5194/nhess-21-53-2021, 2021
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This study investigated one case of a tropical-like cyclone over the Mediterranean Sea under present and future climate conditions with a regional climate model. A pseudo global warming (PGW) technique is employed to simulate the cyclone under future climate, and our simulation showed that the cyclone is moderately strengthened by warmer climate. Other PGW simulations where only ocean and atmosphere are warmed reveal the interesting results that both have counteracting effects on the cyclone.
Shunya Koseki and Priscilla A. Mooney
Hydrol. Earth Syst. Sci., 23, 2795–2812, https://doi.org/10.5194/hess-23-2795-2019, https://doi.org/10.5194/hess-23-2795-2019, 2019
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This study revealed that Lake Malawi plays an important role for local precipitation in terms of spatial distribution and diurnal cycle in boreal summer (November to March). The diurnal cycle is detected by harmonics analysis and empirical orthogonal function analysis. An idealized simulation of WRF without Lake Malawi clearly showed that Lake Malawi is a source of local precipitation.
Shunya Koseki, Hervé Giordani, and Katerina Goubanova
Ocean Sci., 15, 83–96, https://doi.org/10.5194/os-15-83-2019, https://doi.org/10.5194/os-15-83-2019, 2019
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With an ocean frontogenetic function, the frontogenesis of the Angola–Benguela Frontal Zone (ABFZ) is investigated. On an annual-mean timescale, the meridional confluence of Angola and Benguela currents and tilting effect due to the upwelling are the main sources to generate the ABFZ. The annual cycle of the ABFZ is also mainly driven by these two effects.
Shunya Koseki, Lander R. Crespo, Jerry Tjiputra, Filippa Fransner, Noel S. Keenlyside, and David Rivas
Biogeosciences, 21, 4149–4168, https://doi.org/10.5194/bg-21-4149-2024, https://doi.org/10.5194/bg-21-4149-2024, 2024
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We investigated how the physical biases of an Earth system model influence the marine biogeochemical processes in the tropical Atlantic. With four different configurations of the model, we have shown that the versions with better SST reproduction tend to better represent the primary production and air–sea CO2 flux in terms of climatology, seasonal cycle, and response to climate variability.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2491, https://doi.org/10.5194/egusphere-2024-2491, 2024
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Based on a series of storm-resolving greenhouse warming simulations conducted with the AWI-CM3 model at 9 km global atmosphere, 4–25 km ocean resolution, we present new projections of regional climate change, modes of climate variability and extreme events. The 10-year-long high resolution simulations for the 2000s, 2030s, 2060s, 2090s were initialized from a coarser resolution transient run (31 km atmosphere) which follows the SSP5-8.5 greenhouse gas emission scenario from 1950–2100 CE.
Iván M. Parras-Berrocal, Rubén Vázquez, William Cabos, Dimitry V. Sein, Oscar Álvarez, Miguel Bruno, and Alfredo Izquierdo
Ocean Sci., 19, 941–952, https://doi.org/10.5194/os-19-941-2023, https://doi.org/10.5194/os-19-941-2023, 2023
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Global warming may strongly affect dense water formation in the eastern Mediterranean, potentially impacting basin circulation and water properties. We find that at the end of the century dense water formation is reduced by 75 % for the Adriatic, 84 % for the Aegean, and 83 % for the Levantine Sea. This reduction is caused by changes in the temperature and salinity of surface and intermediate waters, which strengthen the vertical stratification, hampering deep convection.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022, https://doi.org/10.5194/esd-13-809-2022, 2022
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The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. When the biogeochemical coupling is included, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.
Matthias Gröger, Christian Dieterich, Cyril Dutheil, H. E. Markus Meier, and Dmitry V. Sein
Earth Syst. Dynam., 13, 613–631, https://doi.org/10.5194/esd-13-613-2022, https://doi.org/10.5194/esd-13-613-2022, 2022
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Atmospheric rivers transport high amounts of water from subtropical regions to Europe. They are an important driver of heavy precipitation and flooding. Their response to a warmer future climate in Europe has so far been assessed only by global climate models. In this study, we apply for the first time a high-resolution regional climate model that allow to better resolve and understand the fate of atmospheric rivers over Europe.
Alba de la Vara, Iván M. Parras-Berrocal, Alfredo Izquierdo, Dmitry V. Sein, and William Cabos
Earth Syst. Dynam., 13, 303–319, https://doi.org/10.5194/esd-13-303-2022, https://doi.org/10.5194/esd-13-303-2022, 2022
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We study with the regionally coupled climate model ROM the impact of climate change on the Tyrrhenian Sea circulation, as well as the possible mechanisms and consequences in the NW Mediterranean Sea. Our results show a shift towards the summer circulation pattern by the end of the century. Also, water flowing via the Corsica Channel is more stratified and smaller in volume. Both factors may contribute to the interruption of deep water formation in the Gulf of Lions in the future.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
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Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Shunya Koseki, Priscilla A. Mooney, William Cabos, Miguel Ángel Gaertner, Alba de la Vara, and Juan Jesus González-Alemán
Nat. Hazards Earth Syst. Sci., 21, 53–71, https://doi.org/10.5194/nhess-21-53-2021, https://doi.org/10.5194/nhess-21-53-2021, 2021
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This study investigated one case of a tropical-like cyclone over the Mediterranean Sea under present and future climate conditions with a regional climate model. A pseudo global warming (PGW) technique is employed to simulate the cyclone under future climate, and our simulation showed that the cyclone is moderately strengthened by warmer climate. Other PGW simulations where only ocean and atmosphere are warmed reveal the interesting results that both have counteracting effects on the cyclone.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
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This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Ivan M. Parras-Berrocal, Ruben Vazquez, William Cabos, Dmitry Sein, Rafael Mañanes, Juan Perez-Sanz, and Alfredo Izquierdo
Ocean Sci., 16, 743–765, https://doi.org/10.5194/os-16-743-2020, https://doi.org/10.5194/os-16-743-2020, 2020
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This work presents high-resolution simulations of a coupled regional model in the Mediterranean basin. The approach allows us to assess the role of ocean feedbacks in the downscaled climate. Our results show good skills in simulating present climate; the model's robustness introduces improvements in reproducing physical processes at local scales. Our climate projections reveal that by the end of the 21st century the Mediterranean Sea will be warmer and saltier although not in a homogeneous way.
Reinhard Schiemann, Panos Athanasiadis, David Barriopedro, Francisco Doblas-Reyes, Katja Lohmann, Malcolm J. Roberts, Dmitry V. Sein, Christopher D. Roberts, Laurent Terray, and Pier Luigi Vidale
Weather Clim. Dynam., 1, 277–292, https://doi.org/10.5194/wcd-1-277-2020, https://doi.org/10.5194/wcd-1-277-2020, 2020
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In blocking situations the westerly atmospheric flow in the midlatitudes is blocked by near-stationary high-pressure systems. Blocking can be associated with extremes such as cold spells and heat waves. Climate models are known to underestimate blocking occurrence. Here, we assess the latest generation of models and find improvements in simulated blocking, partly due to increases in model resolution. These new models are therefore more suitable for studying climate extremes related to blocking.
Torben Koenigk, Ramon Fuentes-Franco, Virna Meccia, Oliver Gutjahr, Laura C. Jackson, Adrian L. New, Pablo Ortega, Christopher Roberts, Malcolm Roberts, Thomas Arsouze, Doroteaciro Iovino, Marie-Pierre Moine, and Dmitry V. Sein
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-41, https://doi.org/10.5194/os-2020-41, 2020
Revised manuscript not accepted
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The mixing of water masses into the deep ocean in the North Atlantic is important for the entire global ocean circulation. We use seven global climate models to investigate the effect of increasing the model resolution on this deep ocean mixing. The main result is that increased model resolution leads to a deeper mixing of water masses in the Labrador Sea but has less effect in the Greenland Sea. However, most of the models overestimate the deep ocean mixing compared to observations.
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
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This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice-Ocean Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor, FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases but with a remarkable performance speedup with a 3 times higher throughput.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
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Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Shunya Koseki and Priscilla A. Mooney
Hydrol. Earth Syst. Sci., 23, 2795–2812, https://doi.org/10.5194/hess-23-2795-2019, https://doi.org/10.5194/hess-23-2795-2019, 2019
Short summary
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This study revealed that Lake Malawi plays an important role for local precipitation in terms of spatial distribution and diurnal cycle in boreal summer (November to March). The diurnal cycle is detected by harmonics analysis and empirical orthogonal function analysis. An idealized simulation of WRF without Lake Malawi clearly showed that Lake Malawi is a source of local precipitation.
Shunya Koseki, Hervé Giordani, and Katerina Goubanova
Ocean Sci., 15, 83–96, https://doi.org/10.5194/os-15-83-2019, https://doi.org/10.5194/os-15-83-2019, 2019
Short summary
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With an ocean frontogenetic function, the frontogenesis of the Angola–Benguela Frontal Zone (ABFZ) is investigated. On an annual-mean timescale, the meridional confluence of Angola and Benguela currents and tilting effect due to the upwelling are the main sources to generate the ABFZ. The annual cycle of the ABFZ is also mainly driven by these two effects.
Anton Y. Dvornikov, Stanislav D. Martyanov, Vladimir A. Ryabchenko, Tatjana R. Eremina, Alexey V. Isaev, and Dmitry V. Sein
Earth Syst. Dynam., 8, 265–282, https://doi.org/10.5194/esd-8-265-2017, https://doi.org/10.5194/esd-8-265-2017, 2017
N. Sudarchikova, U. Mikolajewicz, C. Timmreck, D. O'Donnell, G. Schurgers, D. Sein, and K. Zhang
Clim. Past, 11, 765–779, https://doi.org/10.5194/cp-11-765-2015, https://doi.org/10.5194/cp-11-765-2015, 2015
Related subject area
Topics: Oceans | Interactions: Ocean/atmosphere interactions | Methods: Earth system and climate modeling
Generalized stability landscape of the Atlantic Meridional Overturning Circulation
Multi-centennial evolution of the climate response and deep-ocean heat uptake in a set of abrupt stabilization scenarios with EC-Earth3
Diagnosing the causes of AMOC slowdown in a coupled model: a cautionary tale
Extremely warm European summers preceded by sub-decadal North Atlantic ocean heat accumulation
Matteo Willeit and Andrey Ganopolski
EGUsphere, https://doi.org/10.5194/egusphere-2024-1482, https://doi.org/10.5194/egusphere-2024-1482, 2024
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Using a fast Earth system model we trace the stability landscape of the Atlantic Meridional Overturning Circulation (AMOC) in the combined freshwater forcing – atmospheric CO2 space. We find four different AMOC states that are stable under different conditions and a generally increasing equilibrium AMOC strength with increasing CO2 concentrations.
Federico Fabiano, Paolo Davini, Virna L. Meccia, Giuseppe Zappa, Alessio Bellucci, Valerio Lembo, Katinka Bellomo, and Susanna Corti
Earth Syst. Dynam., 15, 527–546, https://doi.org/10.5194/esd-15-527-2024, https://doi.org/10.5194/esd-15-527-2024, 2024
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Even after the concentration of greenhouse gases is stabilized, the climate will continue to adapt, seeking a new equilibrium. We study this long-term stabilization through a set of 1000-year simulations, obtained by suddenly "freezing" the atmospheric composition at different levels. If frozen at the current state, global warming surpasses 3° in the long term with our model. We then study how climate impacts will change after various centuries and how the deep ocean will warm.
Justin Gérard and Michel Crucifix
Earth Syst. Dynam., 15, 293–306, https://doi.org/10.5194/esd-15-293-2024, https://doi.org/10.5194/esd-15-293-2024, 2024
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We used cGENIE, a climate model, to investigate the Atlantic Meridional Overturning Circulation (AMOC) slowdown under a warming scenario. We apply a diagnostic that was used in a previous study (Levang and Schmitt, 2020) to separate the temperature from salinity contribution to this slowdown. We find that, in our model, the initial slowdown of the AMOC was driven by temperature and that salinity takes the lead for the termination of the circulation.
Lara Wallberg, Laura Suarez-Gutierrez, Daniela Matei, and Wolfgang A. Müller
Earth Syst. Dynam., 15, 1–14, https://doi.org/10.5194/esd-15-1-2024, https://doi.org/10.5194/esd-15-1-2024, 2024
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European summer temperatures are influenced by mechanisms on different timescales. We find that timescales of 5 to 10 years dominate the changes in summer temperature over large parts of the continent. Further, we find that specific processes within the North Atlantic, affecting the storage and transport of heat, cause changes in the atmosphere and extremely warm European summers. Our findings could be used for better forecasts of extremely warm European summers several years ahead.
Cited articles
Aristegui, J., Barton, E. D., Alvarez-Salgado, X. A., Santos, A. M. P., Figueiras, F. G., Kifani, S., Hernandez-Leon, S., Mason, E., Machu, E., and Demarcq, H.: Sub-regional ecosystem variability in the Canary Current upwelling, Prog. Oceanogr., 83, 33–48, https://doi.org/10.1016/j.pocean.2009.07.031, 2009.
Arrasate-Lopez, M., Tuset, V. M., Santana, J. I., Garcia-Mederos, A., Ayza, O., and Gonzalez, J. A.: Fishing methods for sustainable shrimp fisheries in the Canary Islands (North-West Africa), Afr. J. Mar. Sci., 34, 331–339, https://doi.org/10.2989/1814232x.2012.725281, 2012.
Bachelery, M. L., Illig, S., and Rouault, M.: Interannual Coastal Trapped Waves in the Angola-Benguela Upwelling System and Benguela Nino and Nina events, J. Marine Syst., 203, 103262, https://doi.org/10.1016/j.jmarsys.2019.103262, 2020.
Bakun, A.: Global Climate Change and Intensification of Coastal Ocean Upwelling, Science, 247, 198–201, https://doi.org/10.1126/science.247.4939.198, 1990.
Barton, E. D., Aristegui, J., Tett, P., Canton, M., Garcia-Braun, J., Hernandez-Leon, S., Nykjaer, L., Almeida, C., Almunia, J., Ballesteros, S., Basterretxea, G., Escanez, J., Garcia-Weill, L., Hernandez-Guerra, A., Lopez-Laatzen, F., Molina, R., Montero, M. F., Navarro-Perez, E., Rodriguez, J. M., van Lenning, K., Velez, H., and Wild, K.: The transition zone of the Canary Current upwelling region, Prog. Oceanogr., 41, 455–504, https://doi.org/10.1016/S0079-6611(98)00023-8, 1998.
Becognee, P., Almeida, C., Barrera, A., Hernandez-Guerra, A., and Hernandez-Leon, S.: Annual cycle of clupeiform larvae around Gran Canaria Island, Canary Islands, Fish. Oceanogr., 15, 293–300, https://doi.org/10.1111/j.1365-2419.2005.00390.x, 2006.
Block, K. and Mauritsen, T.: Forcing and feedback in the MPI-ESM-LR coupled model under abruptly quadrupled CO2, J. Adv. Model. Earth Sy., 5, 676–691, https://doi.org/10.1002/jame.20041, 2013.
Bracegirdle, T. J., Holmes, C. R., Hosking, J. S., Marshall, G. J., Osman, M., Patterson, M., and Rackow, T.: Improvements in Circumpolar Southern Hemisphere Extratropical Atmospheric Circulation in CMIP6 Compared to CMIP5, Earth Space Sci., 7, e2019EA001065, https://doi.org/10.1029/2019EA001065, 2020.
Brandimarte, L., Di Baldassarre, G., Bruni, G., D'Odorico, P., and Montanari, A.: Relation Between the North-Atlantic Oscillation and Hydroclimatic Conditions in Mediterranean Areas, Water Resour. Manag., 25, 1269–1279, https://doi.org/10.1007/s11269-010-9742-5, 2011.
Cabos, W., Sein, D. V., Pinto, J. G., Fink, A. H., Koldunov, N. V., Alvarez, F., Izquierdo, A., Keenlyside, N., and Jacob, D.: The South Atlantic Anticyclone as a key player for the representation of the tropical Atlantic climate in coupled climate models, Clim. Dynam., 48, 4051–4069, https://doi.org/10.1007/s00382-016-3319-9, 2017.
Cabos, W., de la Vara, A., Alvarez-Garcia, F. J., Sanchez, E., Sieck, K., Perez-Sanz, J. I., Limareva, N., and Sein, D. V.: Impact of ocean-atmosphere coupling on regional climate: the Iberian Peninsula case, Clim. Dynam., 54, 4441–4467, https://doi.org/10.1007/s00382-020-05238-x, 2020.
Chang, P., Xu, G. P., Kurian, J., Small, R. J., Danabasoglu, G., Yeager, S., Castruccio, F., Zhang, Q. Y., Rosenbloom, N., and Chapman, P.: Uncertain future of sustainable fisheries environment in eastern boundary upwelling zones under climate change, Commun. Earth Environ., 4, 19, https://doi.org/10.1038/s43247-023-00681-0, 2023.
Chen, S. H., Huang, C. C., Kuo, Y. C., Tseng, Y. H., Gu, Y., Earl, K., Chen, C. Y., Choi, Y., and Liou, K. N.: Impacts of Saharan Mineral Dust on Air-Sea Interaction over North Atlantic Ocean Using a Fully Coupled Regional Model, J. Geophys. Res.-Atmos., 126, e2020JD033586, https://doi.org/10.1029/2020JD033586, 2021.
Choudhury, B. A., Rajesh, P. V., Zahan, Y., and Goswami, B. N.: Evolution of the Indian summer monsoon rainfall simulations from CMIP3 to CMIP6 models, Clim. Dynam., 58, 2637–2662, https://doi.org/10.1007/s00382-021-06023-0, 2022.
Colberg, F. and Reason, C. J. C.: A model study of the Angola Benguela Frontal Zone: Sensitivity to atmospheric forcing, Geophys. Res. Lett., 33, L19608, https://doi.org/10.1029/2006gl027463, 2006.
Cook, K. H. and Vizy, E. K.: Detection and Analysis of an Amplified Warming of the Sahara Desert, J. Climate, 28, 6560–6580, https://doi.org/10.1175/Jcli-D-14-00230.1, 2015.
Counillon, F., Keenlyside, N. S., Wang, S., Devilliers, M., Gupta, A., Koseki, S., and Shen, M.-L.: Framework for an ocean-connected supermodel of the Earth System, J. Adv. Model. Earth Sy., 15, e2022MS003310, https://doi.org/10.1029/2022MS003310, 2023.
Crespo, L. R., Prigent, A., Keenlyside, N., Koseki, S., Svendsen, L., Richter, I., and Sanchez-Gomez, E.: Weakening of the Atlantic Nino variability under global warming, Nat. Clim. Change, 12, 822–827, https://doi.org/10.1038/s41558-022-01453-y, 2022.
Cropper, T. E., Hanna, E., and Bigg, G. R.: Spatial and temporal seasonal trends in coastal upwelling off Northwest Africa, 1981–2012, Deep-Sea Res. Pt. I, 86, 94–111, https://doi.org/10.1016/j.dsr.2014.01.007, 2014.
Davis, R. E., Hayden, B. P., Gay, D. A., Phillips, W. L., and Jones, G. V.: The North Atlantic subtropical anticyclone, J. Climate, 10, 728–744, https://doi.org/10.1175/1520-0442(1997)010<0728:Tnasa>2.0.Co;2, 1997.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
de la Vara, A., Cabos, W., Sein, D. V., Sidorenko, D., Koldunov, N. I. V., Koseki, S., Soares, P. M. M., and Danilov, S.: On the impact of atmospheric vs oceanic resolutions on the representation of the sea surface temperature in the South Eastern Tropical Atlantic, Clim. Dynam., 54, 4733–4757, https://doi.org/10.1007/s00382-020-05256-9, 2020.
Deppenmeier, A. L., Haarsma, R. J., LeSager, P., and Hazeleger, W.: The effect of vertical ocean mixing on the tropical Atlantic in a coupled global climate model, Clim. Dynam., 54, 5089–5109, https://doi.org/10.1007/s00382-020-05270-x, 2020.
Dippe, T., Greatbatch, R. J., and Ding, H.: On the relationship between Atlantic Nio variability and ocean dynamics, Clim. Dynam., 51, 597–612, https://doi.org/10.1007/s00382-017-3943-z, 2018.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Bottinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H. D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K. H., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Sy., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013.
Giorgi, F. and Lionello, P.: Climate change projections for the Mediterranean region, Global Planet. Change, 63, 90–104, https://doi.org/10.1016/j.gloplacha.2007.09.005, 2008.
Gomez-Letona, M., Ramos, A. G., Coca, J., and Aristegui, J.: Trends in Primary Production in the Canary Current Upwelling System-A Regional Perspective Comparing Remote Sensing Models, Front. Mar. Sci., 4, 370, https://doi.org/10.3389/fmars.2017.00370, 2017.
Good, S. A., Embury, O., Bulgin, C. E., and Mittaz, J.: ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record, version 2.0, Centre for Environmental Data Analysis [data set], 22 August 2019, https://doi.org/10.5285/aced40d7cb964f23a0fd3e85772f2d48, 2019.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horanyi, A., Munoz-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., De 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., Holm, E., Janiskova, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thepaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hurrell, J. W., Kushnir, Y., and Visbeck, M.: Climate – The North Atlantic oscillation, Science, 291, 603–605, https://doi.org/10.1126/science.1058761, 2001.
Jacob, D.: A note to the simulation of the annual and inter-annual variability of the water budget over the Baltic Sea drainage basin, Meteorol. Atmos. Phys., 77, 61–73, https://doi.org/10.1007/s007030170017, 2001.
Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., Matei, D., Mikolajewicz, U., Notz, D., and von Storch, J. S.: Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model, J. Adv. Model. Earth Sy., 5, 422–446, https://doi.org/10.1002/jame.20023, 2013.
Klenz, T., Dengler, M., and Brandt, P.: Seasonal Variability of the Mauritania Current and Hydrography at 18° N, J. Geophys. Res.-Oceans, 123, 8122–8137, https://doi.org/10.1029/2018jc014264, 2018.
Koseki, S. and Koungue, R. A. I.: Regional atmospheric response to the Benguela Ninas, Int. J. Climatol., 41, E1483–E1497, https://doi.org/10.1002/joc.6782, 2021.
Koseki, S., Giordani, H., and Goubanova, K.: Frontogenesis of the Angola–Benguela Frontal Zone, Ocean Sci., 15, 83–96, https://doi.org/10.5194/os-15-83-2019, 2019.
Koseki, S., Vázquez, R., Cabos, W., Gutierrez, C., Sein, D., and Bacherery, M.-L.: ROM data and code for Dakar Niño variability under global warming investigated by a high-resolution regionally coupled model, Zenodo [data set], https://doi.org/10.5281/zenodo.10244334, 2023.
Koungue, R. A. I., Rouault, M., Illig, S., Brandt, P., and Jouanno, J.: Benguela Ninos and Benguela Ninas in Forced Ocean Simulation From 1958 to 2015, J. Geophys. Res.-Oceans, 124, 5923–5951, https://doi.org/10.1029/2019jc015013, 2019.
Koungue, R. A. I., Brandt, P., Luebbecke, J., Prigent, A., Martins, M. S., and Rodrigues, R. R.: The 2019 Benguela Nino, Front. Mar. Sci., 8, 800103, https://doi.org/10.3389/fmars.2021.800103, 2021.
Lazaro, C., Fernandes, M. J., Santos, A. M. P., and Oliveira, P.: Seasonal and interannual variability of surface circulation in the Cape Verde region from 8 years of merged T/P and ERS-2 altimeter data, Remote Sens. Environ., 98, 45–62, https://doi.org/10.1016/j.rse.2005.06.005, 2005.
Lopez-Moreno, J. I., Vicente-Serrano, S. M., Moran-Tejeda, E., Lorenzo-Lacruz, J., Kenawy, A., and Beniston, M.: Effects of the North Atlantic Oscillation (NAO) on combined temperature and precipitation winter modes in the Mediterranean mountains: Observed relationships and projections for the 21st century, Global Planet. Change, 77, 62–76, https://doi.org/10.1016/j.gloplacha.2011.03.003, 2011.
Lopez-Parages, J., Auger, P. A., Rodriguez-Fonseca, B., Keenlyside, N., Gaetan, C., Rubino, A., Arisido, M. W., and Brochier, T.: El Nino as a predictor of round sardinella distribution along the northwest African coast, Prog. Oceanogr., 186, 102341, https://doi.org/10.1016/j.pocean.2020.102341, 2020.
Marsland, S. J., Haak, H., Jungclaus, J. H., Latif, M., and Roske, F.: The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates, Ocean Model., 5, 91–127, https://doi.org/10.1016/S1463-5003(02)00015-X, 2003.
Martin-Rey, M. and Lazar, A.: Is the boreal spring tropical Atlantic variability a precursor of the Equatorial Mode?, Clim. Dynam., 53, 2339–2353, https://doi.org/10.1007/s00382-019-04851-9, 2019.
Mittelstaedt, E.: The Ocean Boundary Along the Northwest African Coast – Circulation and Oceanographic Properties at the Sea-Surface, Prog. Oceanogr., 26, 307–355, https://doi.org/10.1016/0079-6611(91)90011-A, 1991.
Ndoye, S., Capet, X., Estrade, P., Sow, B., Dagorne, D., Lazar, A., Gaye, A., and Brehmer, P.: SST patterns and dynamics of the southern Senegal-Gambia upwelling center, J. Geophys. Res.-Oceans, 119, 8315–8335, https://doi.org/10.1002/2014jc010242, 2014.
Oettli, P., Yuan, C., and Richter, I.: 10 – The other coastal Niño/Niña – the Benguela, California, and Dakar Niños/Niñas, in: Tropical and Extratropical Air-Sea Interactions. Modes of Climate Variations, Elsevier, 237–266, https://doi.org/10.1016/B978-0-12-818156-0.00010-1, 2021.
Oettli, P., Morioka, Y., and Yamagata, T.: A Regional Climate Mode Discovered in the North Atlantic: Dakar Nino/Nina, Sci. Rep.-UK, 6, 18782, https://doi.org/10.1038/srep18782, 2016.
Pardo, P. C., Padin, X. A., Gilcoto, M., Farina-Busto, L., and Perez, F. F.: Evolution of upwelling systems coupled to the long-term variability in sea surface temperature and Ekman transport, Clim. Res., 48, 231–246, https://doi.org/10.3354/cr00989, 2011.
Pastor, M. V., Pelegri, J. L., Hernandez-Guerra, A., Font, J., Salat, J., and Emellanov, M.: Water and nutrient fluxes off Northwest Africa, Cont. Shelf Res., 28, 915–936, https://doi.org/10.1016/j.csr.2008.01.011, 2008.
Perez-Hernandez, M. D., Hernandez-Guerra, A., Fraile-Nuez, E., Comas-Rodriguez, I., Benitez-Barrios, V. M., Dominguez-Yanes, J. F., Velez-Belchi, P., and De Armas, D.: The source of the Canary current in fall 2009, J. Geophys. Res.-Oceans, 118, 2874–2891, https://doi.org/10.1002/jgrc.20227, 2013.
Pietikäinen, J.-P., O'Donnell, D., Teichmann, C., Karstens, U., Pfeifer, S., Kazil, J., Podzun, R., Fiedler, S., Kokkola, H., Birmili, W., O'Dowd, C., Baltensperger, U., Weingartner, E., Gehrig, R., Spindler, G., Kulmala, M., Feichter, J., Jacob, D., and Laaksonen, A.: The regional aerosol-climate model REMO-HAM, Geosci. Model Dev., 5, 1323–1339, https://doi.org/10.5194/gmd-5-1323-2012, 2012.
Priestley, M. D. K., Ackerley, D., Catto, J. L., Hodges, K. I., McDonald, R. E., and Lee, R. W.: An Overview of the Extratropical Storm Tracks in CMIP6 Historical Simulations, J. Climate, 33, 6315–6343, https://doi.org/10.1175/Jcli-D-19-0928.1, 2020.
Prigent, A., Koungue, R. A. I., Lübbecke, J. F., Brandt, P., Harlass, J., and Latif, M.: Future weakening of southeastern tropical Atlantic Ocean interannual sea surface temperature variability in a global climate model, Clim. Dynam., 62, 1997–2016, https://doi.org/10.1007/s00382-023-07007-y, 2023.
Richter, I. and Tokinaga, H.: An overview of the performance of CMIP6 models in the tropical Atlantic: mean state, variability, and remote impacts, Clim. Dynam., 55, 2579–2601, https://doi.org/10.1007/s00382-020-05409-w, 2020.
Richter, I. and Xie, S. P.: On the origin of equatorial Atlantic biases in coupled general circulation models, Clim. Dynam., 31, 587–598, https://doi.org/10.1007/s00382-008-0364-z, 2008.
Rouault, M., Illig, S., Lubbecke, J., and Koungue, R. A. I.: Origin, development and demise of the 2010-2011 Benguela Nino, J. Marine Syst., 188, 39–48, https://doi.org/10.1016/j.jmarsys.2017.07.007, 2018.
Santana-Falcon, Y., Mason, E., and Aristegui, J.: Offshore transport of organic carbon by upwelling filaments in the Canary Current System, Prog. Oceanogr., 186, 102322, https://doi.org/10.1016/j.pocean.2020.102322, 2020.
Sein, D. V., Mikolajewicz, U., Groger, M., Fast, I., Cabos, W., Pinto, J. G., Hagemann, S., Semmler, T., Izquierdo, A., and Jacob, D.: Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation, J. Adv. Model. Earth Sy., 7, 268–304, https://doi.org/10.1002/2014ms000357, 2015.
Sein, D. V., Groger, M., Cabos, W., Alvarez-Garcia, F. J., Hagemann, S., Pinto, J. G., Izquierdo, A., de la Vara, A., Koldunov, N. V., Dvornikov, A. Y., Limareva, N., Alekseeva, E., Martinez-Lopez, B., and Jacob, D.: Regionally Coupled Atmosphere-Ocean-Marine Biogeochemistry Model ROM: 2. Studying the Climate Change Signal in the North Atlantic and Europe, J. Adv. Model. Earth Sy., 12, e2019MS001646, https://doi.org/10.1029/2019MS001646, 2020.
Shen, M. L., Keenlyside, N., Selten, F., Wiegerinck, W., and Duane, G. S.: Dynamically combining climate models to “supermodel” the tropical Pacific, Geophys. Res. Lett., 43, 359–366, https://doi.org/10.1002/2015gl066562, 2016.
Soares, P. M. M., Lima, D. C. A., Semedo, A., Cardoso, R. M., Cabos, W., and Sein, D.: The North African coastal low level wind jet: a high resolution view (vol 53, pg 1211, 2019), Clim. Dynam., 53, 1231–1231, https://doi.org/10.1007/s00382-018-4475-x, 2019.
Sylla, A., Mignot, J., Capet, X., and Gaye, A. T.: Weakening of the Senegalo-Mauritanian upwelling system under climate change, Clim. Dynam., 53, 4447–4473, https://doi.org/10.1007/s00382-019-04797-y, 2019.
Sylla, A., Sanchez Gomez, E., Mignot, J., and López-Parages, J.: Impact of increased resolution on the representation of the Canary upwelling system in climate models, Geosci. Model Dev., 15, 8245–8267, https://doi.org/10.5194/gmd-15-8245-2022, 2022.
Toniazzo, T. and Koseki, S.: A Methodology for Anomaly Coupling in Climate Simulation, J. Adv. Model. Earth Sy., 10, 2061–2079, https://doi.org/10.1029/2018ms001288, 2018.
Vázquez, R., Parras-Berrocal, I., Cabos, W., Sein, D. V., Mananes, R., and Izquierdo, A.: Assessment of the Canary current upwelling system in a regionally coupled climate model, Clim. Dynam., 58, 69–85, https://doi.org/10.1007/s00382-021-05890-x, 2022.
Vázquez, R., Parras-Berrocal, I., Koseki, S., Cabos, W., Sein, D. V., and Izquierdo, A.: Seasonality of coastal upwelling trends in the Mauritania-Senegalese region under RCP8.5 climate change scenarios, Sci. Total Environ., 898, 166391, https://doi.org/10.1016/j.scitotenv.2023.166391, 2023.
Vázquez, R., Parras-Berrocal, I. M., Cabos, W., Sein, D., Mañanes, R., Bolado-Penagos, M., and Izquierdo, A.: Climate change in the Canary/Iberia upwelling region: the role of ocean stratification and wind, Environ. Res. Lett., 19, 074064, https://doi.org/10.1088/1748-9326/ad5ab4, 2024.
Vijith, V., Vinayachandran, P. N., Webber, B. G. M., Matthews, A. J., George, J. V., Kannaujia, V. K., Lotliker, A. A., and Amol, P.: Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE, Sci. Rep.-UK, 10, 7062, https://doi.org/10.1038/s41598-020-63320-0, 2020.
Voldoire, A., Exarchou, E., Sanchez-Gomez, E., Demissie, T., Deppenmeier, A. L., Frauen, C., Goubanova, K., Hazeleger, W., Keenlyside, N., Koseki, S., Prodhomme, C., Shonk, J., Toniazzo, T., and Traore, A. K.: Role of wind stress in driving SST biases in the Tropical Atlantic, Clim. Dynam., 53, 3481–3504, https://doi.org/10.1007/s00382-019-04717-0, 2019.
Yang, Y., Wu, L. X., Cai, W. J., Jia, F., Ng, B., Wang, G. J., and Geng, T.: Suppressed Atlantic Nino/Nina variability under greenhouse warming, Nat. Clim. Change, 12, 814–821, https://doi.org/10.1038/s41558-022-01444-z, 2022.
Yang, Y., Wu, L. X., Guo, Y., Gan, B. L., Cai, W. J., Huang, G., Li, X. C., Geng, T., Jing, Z., Li, S. J., Liang, X., and Xie, S. P.: Greenhouse warming intensifies north tropical Atlantic climate variability, Sci. Adv., 7, eabg9690, https://doi.org/10.1126/sciadv.abg9690, 2021.
Zhou, L. M.: Desert Amplification in a Warming Climate, Sci. Rep.-UK, 6, 31065, https://doi.org/10.1038/srep31065, 2016.
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M.: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment, Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, 2019.
Short summary
Using a high-resolution regionally coupled model, we suggest that Dakar Niño variability will be reinforced under the Representative Concentration Pathway (RCP) 8.5 scenario. This may be induced by intensified surface heat flux anomalies and, secondarily, by anomalies in horizontal and vertical advection. Increased sea surface temperature (SST) variability can be associated with stronger wind variability, attributed to amplified surface temperature anomalies between ocean and land.
Using a high-resolution regionally coupled model, we suggest that Dakar Niño variability will be...
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