Articles | Volume 16, issue 2
https://doi.org/10.5194/esd-16-497-2025
© Author(s) 2025. 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-16-497-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Apr 2025
Research article |
| 03 Apr 2025
| 03 Apr 2025
Changes in extreme precipitation patterns over the Greater Antilles and teleconnection with large-scale sea surface temperature
Carlo Destouches
CORRESPONDING AUTHOR
Faculté des Sciences, Université d'Etat d'Haïti, LMI CARIBACT, URGéo, Port-au-Prince, Haiti
Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
Arona Diedhiou
Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
Sandrine Anquetin
Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
Benoit Hingray
Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
Armand Pierre
Faculté des Sciences, Université d'Etat d'Haïti, LMI CARIBACT, URGéo, Port-au-Prince, Haiti
Dominique Boisson
Faculté des Sciences, Université d'Etat d'Haïti, LMI CARIBACT, URGéo, Port-au-Prince, Haiti
Adermus Joseph
Faculté des Sciences, Université d'Etat d'Haïti, LMI CARIBACT, URGéo, Port-au-Prince, Haiti
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Léo Clauzel, Sandrine Anquetin, Christophe Lavaysse, Gilles Bergametti, Christel Bouet, Guillaume Siour, Rémy Lapere, Béatrice Marticorena, and Jennie Thomas
Atmos. Chem. Phys., 25, 997–1021, https://doi.org/10.5194/acp-25-997-2025, https://doi.org/10.5194/acp-25-997-2025, 2025
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Solar energy production in West Africa is set to rise and needs accurate solar radiation estimates which are affected by desert dust. This work analyses a March 2021 dust event using a modelling strategy incorporating desert dust. Results show that considering desert dust cuts errors in solar radiation estimates by 75 % and reduces surface solar radiation by 18 %. This highlights the importance of incorporating dust aerosols into solar forecasting for better accuracy.
Camille Crapart, Sandrine Anquetin, Juliette Blanchet, and Arona Diedhiou
EGUsphere, https://doi.org/10.5194/egusphere-2024-3710, https://doi.org/10.5194/egusphere-2024-3710, 2025
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Our study investigates global dryland dynamics and aridification under future climate scenarios. By employing the FAO Aridity Index and an ensemble of 13 CMIP6 models, we provide projections for dryland distribution and aridity index across three socio-economic pathways (SSP2-4.5, SSP3-7.0, and SSP5-8.5), for the near-term (2030–2060) and for the long-term (2070–2100) future. Our findings give insights on the future distribution of the world water resources and climatic conditions.
Maria Staudinger, Martina Kauzlaric, Alexandre Mas, Guillaume Evin, Benoit Hingray, and Daniel Viviroli
Nat. Hazards Earth Syst. Sci., 25, 247–265, https://doi.org/10.5194/nhess-25-247-2025, https://doi.org/10.5194/nhess-25-247-2025, 2025
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Various combinations of antecedent conditions and precipitation result in floods of varying degrees. Antecedent conditions played a crucial role in generating even large ones. The key predictors and spatial patterns of antecedent conditions leading to flooding at the basin's outlet were distinct. Precipitation and soil moisture from almost all sub-catchments were important for more frequent floods. For rarer events, only the predictors of specific sub-catchments were important.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384, https://doi.org/10.5194/nhess-22-3361-2022, https://doi.org/10.5194/nhess-22-3361-2022, 2022
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We present a new landslide inventory for the 2021, M 7.2, Haiti, earthquake. We compare characteristics of this inventory with those of the 2010 seismically induced landslides, highlighting the much larger total area of 2021 landslides. This fact could be related to the larger earthquake magnitude in 2021, to the more central location of the fault segment ruptured in 2021 with respect to coastal zones, and/or to possible climatic preconditioning of slope failures in the 2021 affected area.
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022, https://doi.org/10.5194/nhess-22-2891-2022, 2022
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Estimating the magnitude of rare to very rare floods is a challenging task due to a lack of sufficiently long observations. The challenge is even greater in large river basins, where precipitation patterns and amounts differ considerably between individual events and floods from different parts of the basin coincide. We show that a hydrometeorological model chain can provide plausible estimates in this setting and can thus inform flood risk and safety assessments for critical infrastructure.
Eva Boisson, Bruno Wilhelm, Emmanuel Garnier, Alain Mélo, Sandrine Anquetin, and Isabelle Ruin
Nat. Hazards Earth Syst. Sci., 22, 831–847, https://doi.org/10.5194/nhess-22-831-2022, https://doi.org/10.5194/nhess-22-831-2022, 2022
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We present the database of Historical Impacts of Floods in the Arve Valley (HIFAVa). It reports flood occurrences and impacts (1850–2015) in a French Alpine catchment. Our results show an increasing occurrence of impacts from 1920 onwards, which is more likely related to indirect source effects and/or increasing exposure rather than hydrological changes. The analysis reveals that small mountain streams caused more impacts (67 %) than the main river.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anne-Sophie Mreyen, Sophia Ulysse, Anika Braun, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-83, https://doi.org/10.5194/nhess-2022-83, 2022
Preprint withdrawn
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First analyses of landslide distribution and triggering factors are presented for the region affected by the Mw = 7.2 earthquake, 2021, in Haiti. The landslide inventory created for the 2021 event is compared with catalogues compiled by others both for the 2021 and 2010 events. Related analyses show that the larger total area of landslides triggered in 2021, can be explained, e.g., by (a) the stronger shaking intensity in 2021, (b) a climatic influence on slope stability in the 2021-affected area.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 711–730, https://doi.org/10.5194/hess-26-711-2022, https://doi.org/10.5194/hess-26-711-2022, 2022
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The impact of initial soil moisture anomalies can persist for up to 3–4 months and is greater on temperature than on precipitation over West Africa. The strongest homogeneous impact on temperature is located over the Central Sahel, with a peak change of −1.5 and 0.5 °C in the wet and dry experiments, respectively. The strongest impact on precipitation in the wet and dry experiments is found over the West and Central Sahel, with a peak change of about 40 % and −8 %, respectively.
Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea
Hydrol. Earth Syst. Sci., 26, 731–754, https://doi.org/10.5194/hess-26-731-2022, https://doi.org/10.5194/hess-26-731-2022, 2022
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The impact of initial soil moisture is more significant on temperature extremes than on precipitation extremes. A stronger impact is found on maximum temperature than on minimum temperature. The impact on extreme precipitation indices is homogeneous, especially over the Central Sahel, and dry (wet) experiments tend to decrease (increase) the number of precipitation extreme events but not their intensity.
Guillaume Evin, Samuel Somot, and Benoit Hingray
Earth Syst. Dynam., 12, 1543–1569, https://doi.org/10.5194/esd-12-1543-2021, https://doi.org/10.5194/esd-12-1543-2021, 2021
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This research paper proposes an assessment of mean climate change responses and related uncertainties over Europe for mean seasonal temperature and total seasonal precipitation. An advanced statistical approach is applied to a large ensemble of 87 high-resolution EURO-CORDEX projections. For the first time, we provide a comprehensive estimation of the relative contribution of GCMs and RCMs, RCP scenarios, and internal variability to the total variance of a very large ensemble.
Derrick K. Danso, Sandrine Anquetin, Arona Diedhiou, Kouakou Kouadio, and Arsène T. Kobea
Earth Syst. Dynam., 11, 1133–1152, https://doi.org/10.5194/esd-11-1133-2020, https://doi.org/10.5194/esd-11-1133-2020, 2020
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The atmospheric and surface conditions that exist during the occurrence of daytime low-level clouds (LLCs) and their influence on solar radiation were investigated in West Africa. During the monsoon season, these LLCs are linked to high moisture flux driven by strong southwesterly winds from the Gulf of Guinea and significant background moisture levels. Their occurrence leads to a strong reduction in the incoming solar radiation and has large impacts on the surface energy budget.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
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The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Damien Raynaud, Benoit Hingray, Guillaume Evin, Anne-Catherine Favre, and Jérémy Chardon
Hydrol. Earth Syst. Sci., 24, 4339–4352, https://doi.org/10.5194/hess-24-4339-2020, https://doi.org/10.5194/hess-24-4339-2020, 2020
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This research paper proposes a weather generator combining two sampling approaches. A first generator recombines large-scale atmospheric situations. A second generator is applied to these atmospheric trajectories in order to simulate long time series of daily regional precipitation and temperature. The method is applied to daily time series in Switzerland. It reproduces adequately the observed climatology and improves the reproduction of extreme precipitation values.
Florian Raymond, Bruno Wilhelm, and Sandrine Anquetin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-100, https://doi.org/10.5194/hess-2019-100, 2019
Manuscript not accepted for further review
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We focus on the role of precipitation on the high magnitude flood generation to explore in what extent such events could be explained by only atmospheric variables. The role of the precipitation accumulations prior to the flood day progressively decreases when considering floods of weaker magnitude, suggesting a higher diversity of processes involved in the generation of e.g. annual flooding. Our results open new perspectives for flood hazard assessments directly based on climate model outputs.
Brahima Koné, Arona Diedhiou, N'datchoh Evelyne Touré, Mouhamadou Bamba Sylla, Filippo Giorgi, Sandrine Anquetin, Adama Bamba, Adama Diawara, and Arsene Toka Kobea
Earth Syst. Dynam., 9, 1261–1278, https://doi.org/10.5194/esd-9-1261-2018, https://doi.org/10.5194/esd-9-1261-2018, 2018
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Simulations of regional climate are very sensitive to physical parameterization schemes, particularly over the tropics where convection plays a major role in monsoon dynamics. The latest version of RegCM4 was used to assess the performance and sensitivity of the simulated West African climate system to different convection schemes. The configuration of RegCM4 with CLM4.5 as a land surface model and the Emanuel convective scheme is recommended for the study of the West African climate.
Guillaume Evin, Anne-Catherine Favre, and Benoit Hingray
Hydrol. Earth Syst. Sci., 22, 655–672, https://doi.org/10.5194/hess-22-655-2018, https://doi.org/10.5194/hess-22-655-2018, 2018
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This research paper proposes a multi-site daily precipitation model, named GWEX, which aims to reproduce the statistical features of extremely rare events at different temporal and spatial scales. Recent advances and various statistical methods (regionalization, disaggregation) are considered in order to obtain a robust and appropriate representation of the most extreme precipitation fields. Performances are shown with an application to 105 stations, covering a large region in Switzerland.
Jérémy Chardon, Benoit Hingray, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 22, 265–286, https://doi.org/10.5194/hess-22-265-2018, https://doi.org/10.5194/hess-22-265-2018, 2018
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We present a two-stage statistical downscaling model for the probabilistic prediction of local precipitation, where the downscaling statistical link is estimated from atmospheric circulation analogs of the current prediction day.
The model allows for a day-to-day adaptive and tailored downscaling. It can reveal specific predictors for peculiar and non-frequent weather configurations. This approach noticeably improves the skill of the prediction for both precipitation occurrence and quantity.
Saif Shabou, Isabelle Ruin, Céline Lutoff, Samuel Debionne, Sandrine Anquetin, Jean-Dominique Creutin, and Xavier Beaufils
Nat. Hazards Earth Syst. Sci., 17, 1631–1651, https://doi.org/10.5194/nhess-17-1631-2017, https://doi.org/10.5194/nhess-17-1631-2017, 2017
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This study describes the development of a model, called MobRISK, for assessing motorists' exposure to road flooding. MobRISK combines sociodemographic, travel-activity and hydrometeorological data in order to simulate the number and the profile of exposed persons to road flooding. The first application of MobRISK in a case study in southern France enabled the identification of the most dangerous road sections based on a spatiotemporal exposure index and the profile of most exposed people.
Jean-Philippe Vidal, Benoît Hingray, Claire Magand, Eric Sauquet, and Agnès Ducharne
Hydrol. Earth Syst. Sci., 20, 3651–3672, https://doi.org/10.5194/hess-20-3651-2016, https://doi.org/10.5194/hess-20-3651-2016, 2016
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Possible transient futures of winter and summer low flows for two snow-influenced catchments in the southern French Alps show a strong decrease signal. It is however largely masked by the year-to-year variability, which should be the main target for defining adaptation strategies. Responses of different hydrological models strongly diverge in the future, suggesting to carefully check the robustness of evapotranspiration and snowpack components under a changing climate.
A. Kuentz, T. Mathevet, J. Gailhard, and B. Hingray
Hydrol. Earth Syst. Sci., 19, 2717–2736, https://doi.org/10.5194/hess-19-2717-2015, https://doi.org/10.5194/hess-19-2717-2015, 2015
B. François, B. Hingray, F. Hendrickx, and J. D. Creutin
Hydrol. Earth Syst. Sci., 18, 3787–3800, https://doi.org/10.5194/hess-18-3787-2014, https://doi.org/10.5194/hess-18-3787-2014, 2014
I. Braud, P.-A. Ayral, C. Bouvier, F. Branger, G. Delrieu, J. Le Coz, G. Nord, J.-P. Vandervaere, S. Anquetin, M. Adamovic, J. Andrieu, C. Batiot, B. Boudevillain, P. Brunet, J. Carreau, A. Confoland, J.-F. Didon-Lescot, J.-M. Domergue, J. Douvinet, G. Dramais, R. Freydier, S. Gérard, J. Huza, E. Leblois, O. Le Bourgeois, R. Le Boursicaud, P. Marchand, P. Martin, L. Nottale, N. Patris, B. Renard, J.-L. Seidel, J.-D. Taupin, O. Vannier, B. Vincendon, and A. Wijbrans
Hydrol. Earth Syst. Sci., 18, 3733–3761, https://doi.org/10.5194/hess-18-3733-2014, https://doi.org/10.5194/hess-18-3733-2014, 2014
Related subject area
Topics: Climate change | Interactions: Ocean/atmosphere interactions | Methods: Other methods
Are physiological and ecosystem-level tipping points caused by ocean acidification? A critical evaluation
Christopher E. Cornwall, Steeve Comeau, and Ben P. Harvey
Earth Syst. Dynam., 15, 671–687, https://doi.org/10.5194/esd-15-671-2024, https://doi.org/10.5194/esd-15-671-2024, 2024
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Ocean acidification will cause profound shifts in many marine ecosystems by impairing the ability of calcareous taxa to grow and by influencing the photophysiology of many others. Physiological tipping points will likely be reached in the next 20 years. Small changes in organism physiology result in larger ecological tipping points being crossed. Ecosystems will shift from having higher abundances of calcifying taxa and towards increased abundances of non-calcareous species under elevated CO2.
Cited articles
Agudelo, P. A., Hoyos, C. D., Curry, J. A., and Webster, P. J.: Probabilistic discrimination between large-scale environments of intensifying and decaying African easterly waves, Clim. Dynam., 36, 1379–1401, https://doi.org/10.1007/s00382-010-0851-x, 2011. a
Almazroui, M., Islam, M. N., Saeed, F., Saeed, S., Ismail, M., Ehsan, M. A., Diallo, I., O'Brien, E., Ashfaq, M., Martínez-Castro, D., Cavazos, T., Cerezo-Mota, R., Tippett, M. K., Gutowski, W. J., Alfaro, E. J., Hidalgo, H. G., Vichot-Llano, A., Campbell, J. D., Kamil, S., Rashid, I. U., Sylla, M. B., Stephenson, T., Taylor, M., and Barlow, M.: Projected Changes in Temperature and Precipitation Over the United States, Central America, and the Caribbean in CMIP6 GCMs, Earth Syst. Environ., 5, 1–24, https://doi.org/10.1007/s41748-021-00199-5, 2021. a
An, D., Eggeling, J., Zhang, L., He, H., Sapkota, A., Wang, Y.-C., and Gao, C.: Extreme precipitation patterns in the Asia–Pacific region and its correlation with El Niño-Southern Oscillation (ENSO), Sci. Rep., 13, 11068, https://doi.org/10.1038/s41598-023-38317-0, 2023. a
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Ribbe, L., Nauditt, A., Giraldo-Osorio, J. D., and Thinh, N. X.: Temporal and spatial evaluation of satellite rainfall estimates over different regions in Latin-America, Atmos. Res., 213, 34–50, https://doi.org/10.1016/j.atmosres.2018.05.011, 2018. a
Bathelemy R., Brigode P., Boisson D., and Tric, E.: Rainfall in the Greater and Lesser Antilles: Performance of five gridded datasets on a daily timescale, J. Hydrol.: Regional Studies, 43, 101203, https://doi.org/10.1016/j.ejrh.2022.101203, 2022. a
Beharry, S. L., Clarke, R. M., and Kumarsingh, K.: Variations in extreme temperature and precipitation for a Caribbean island: Trinidad, Theor. Appl. Climatol., 122, 783–797, https://doi.org/10.1007/s00704-014-1330-9, 2015. a
Burgess, C. P., Taylor, M. A., Spencer, N., Jones, J., and Stephenson, T. S.: Estimating damages from climate-related natural disasters for the Caribbean at 1.5 °C and 2 °C global warming above preindustrial levels, Reg. Environ. Change, 18, 2297–2312, https://doi.org/10.1007/s10113-018-1423-6, 2018. a
Cantet, P.: Mapping the mean monthly precipitation of a small island using kriging with external drifts, Theor. Appl. Climatol., 127, 31–44, https://doi.org/10.1007/s00704-015-1610-z, 2017. a
Centella-Artola, A., Bezanilla-Morlot, A., Taylor, M. A., Herrera, D. A., Martinez-Castro, D., Gouirand, I., Sierra-Lorenzo, M., Vichot-Llano, A., Stephenson, T., Fonseca, C., Campbell, J., and Alpizar, M.: Evaluation of Sixteen Gridded Precipitation Datasets over the Caribbean Region Using Gauge Observations, Atmosphere, 11, 1334, https://doi.org/10.3390/atmos11121334, 2020. a
Climate Hazards Group: Index of /products/CHIRPS-2.0, Climate Hazards Group [data set], https://data.chc.ucsb.edu/products/CHIRPS-2.0/, last access: February 2023. a
Cook, K. H. and Vizy, E. K.: Hydrodynamics of the Caribbean low-level jet and its relationship to precipitation, J. Climate, 23, 1477–1494, https://doi.org/10.1175/2009JCLI3210.1, 2010. a
Curtis, S. and Gamble, D. W.: Regional Variations of the Caribbean Mid-Summer Drought, Theor. Appl. Climatol., 94, 25–34, https://doi.org/10.1007/s00704-007-0342-0, 2008. a
Daly, C., Helmer, E. H., and Quiñones, M.: Mapping the climate of Puerto Rico. Vieques Culebra, Int. J. Climate, 23, 1359–1381, https://doi.org/10.1002/joc.937, 2003. a
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. a
De Giorgi, A., Solarna, D., Moser, G., Tapete, D., Cigna, F., Boni, G., Rudari, R., Serpico, S. B., Pisani, A. R., Montuori, A., and Zoffoli, S.: Monitoring the Recovery after 2016 Hurricane Matthew in Haiti via Markovian Multitemporal Region-Based Modeling, Remote Sens., 13, 3509, https://doi.org/10.3390/rs13173509, 2021. a
Deopersad, C., Persaud, C., Chakalall, Y., Bello, O., Masson, M., Perroni, A., Carrera-Marquis, D., Fontes de Meira, L., Gonzales, C., Peralta, L., Skerette, N., Marcano, B., Pantin, M., Vivas, G., Espiga, C., Allen, E., Ruiz, E., Ibarra, F., Espiga, F., and Nelson, M.: Assessment of the Effects and Impacts of Hurricane Dorian in the Bahamas, IDB Publications, https://doi.org/10.18235/0002582, 2020. a
Dookie, N., Chadee, X. T., and Clarke, R. M.: Trends in extreme temperature and precipitation indices for the Caribbean small islands: Trinidad and Tobago, Theor. Appl. Climatol., 136, 31–44, https://doi.org/10.1007/s00704-018-2463-z, 2019. a
Enfield, D. B., Mestas-Nunez, A. M., and Trimble, P. J.: The Atlantic Multidecadal Oscillation and Its Relation to Rainfall and River Flows in the Continental U.S., Geophys. Res. Lett., 28, 2077–2080, https://doi.org/10.1029/2000GL012745, 2001. a, b
Frich P., Alexander, L. V., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A. M. G., and Peterson, T.: Observed Coherent Changes in Climatic Extremes during the Second Half of the Twentieth Century, Clim. Res., 19, 193–212, https://doi.org/10.3354/cr019193, 2002. a
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015a. a, b
Funk, C., Verdin, A., Michaelsen, J., Peterson, P., Pedreros, D., and Husak, G.: A global satellite-assisted precipitation climatology, Earth Syst. Sci. Data, 7, 275–287, https://doi.org/10.5194/essd-7-275-2015, 2015b. a
Gauthier, T. D.: Detecting trends using Spearman's rank correlation coefficient, Environ. Forensic, 2, 359–362, https://doi.org/10.1006/enfo.2001.0061, 2001. a
Giannini, A., Kushnir, Y., and Cane, M. A.: Interannual Variability of Caribbean Rainfall, ENSO, and the Atlantic Ocean, J. Climate, 13, 297–311, https://doi.org/10.1175/1520-0442(2000)013<0297:IVOCRE>2.0.CO;2, 2000. a, b, c
Giannini, A., Cane, M. A., and Kushnir, Y.: Interdecadal Changes in the ENSO Teleconnection to the Caribbean Region and the North Atlantic Oscillation, J. Climate, 14, 2867–2879, https://doi.org/10.1175/1520-0442(2001)014<2867:ICITET>2.0.CO;2, 2001a. a
Giannini, A., Kushnir, Y., and Cane, M. A.: Seasonality in the impact of ENSO and the North Atlantic High on Caribbean Rainfall, Phys. Chem. Earth B, 28, 143–147, https://doi.org/10.1016/S1464-1909(00)00231-8, 2001b. a
Gimeno, L., Magaña, V., and Enfield, D. B.: Introduction to special section on the role of the Atlantic warm pool in the climate of the Western Hemisphere, J. Geophys. Res., 116, D00Q01, https://doi.org/10.1029/2011JD016699, 2011. a, b
Griffiths, J. F. and Driscoll, J. M.: Survey of climatology, Charles Merril, Columbus, OH, ISBN 9780675099943, 1982. a
Hall, T. C., Sealy, A. M., Stephenson, T. S., Kusunoki, S., Taylor, M. A., Chen, A. A., and Kitoh, A.: Future climate of the Caribbean from a super-high-resolution atmospheric general circulation model, Theor. Appl. Climatol., 113, 271–287, https://doi.org/10.1007/s00704-012-0779-7, 2013. a
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Mise à jour des grilles à haute résolution des observations climatiques mensuelles – l'ensemble de données CRU TS3.10, J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hastenrath, S.: The intertropical convergence zone of the eastern Pacific revisited. Int. J. Climatol. 22, 347–356, https://doi.org/10.1002/joc.739, 2002. a
Huang, B., Liu, C., Banzon, V., Freeman, E., Graham, G., Hankins, B., Smith, T., and Zhang, H.: Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1, J. Climate, 34, 2923–2939, https://doi.org/10.1175/JCLI-D-20-0166.1, 2021a. a
Huang, B., Liu, C., Freeman, E., Graham, G., Smith, T., and Zhang, H.: Assessment and Intercomparison of NOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1, J. Climate, 34, 7421–7441, https://doi.org/10.1175/JCLI-D-21-0001.1, 2021b. a
Hurrell, J. W.: Decadal trends in the north Atlantic oscillation: regional temperatures and precipitation, Science, 269, 676–679, https://doi.org/10.1126/science.269.5224.676, 1995. a
Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M.: An Overview of the North Atlantic Oscillation, in: The North Atlantic Oscillation: climatic significance and environmental impact, edited by: Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M., Geophysical Monograph Series, 134, AGU (American Geophysical Union), Washington, DC, 1–36, https://doi.org/10.1029/134GM01, 2003. a
IPCC: Climate Change 2007, Synthesis Report, Working Group, I, II and III contributions to the Fourth Assessment Report, http://www.ipcc.ch (last access: June 2023), 2007. a
IPCC: Climate Change: The Physical Science Basis, in: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, 1535 pp., ISBN 978-92-9169-138-8, 2013. a
Jones, P. D., Jónsson, T., and Wheeler, D.: Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and South-West Iceland, Int. J. Climatol., 17, 1433–1450, https://doi.org/10.1002/(SICI)1097-0088(19971115)17:13<1433::AID-JOC203>3.0.CO;2-P, 1997. a
Joseph, P.: La Caraïbe, données environnementales. Coordonné par Joseph P. Karthala, Paris, et Géode (Groupe de recherche Géographie, développement, environnement de la Caraïbe), ÉÉditions KARTHALA, 458 pp., ISBN 978-2845867567, 2006. a
Jury, M., Malmgren, B. A., and Winter, A.: Subregional precipitation climate of the Caribbean and relationships with ENSO and NAO, J. Geophys. Res., 112, D16107, https://doi.org/10.1029/2006JD007541, 2007. a
Khadgarai, S., Kumar, V., and Pradhan, P. K.: The Connection between Extreme Precipitation Variability over Monsoon Asia and Large-Scale Circulation Patterns, Atmosphere, 12, 1492, https://doi.org/10.3390/atmos12111492, 2021. a
Klotzbach, P. J.: The influence of El Niño–Southern Oscillation and the Atlantic multidecadal oscillation on Caribbean tropical cyclone activity, J. Climate, 24, 721–731, https://doi.org/10.1175/2010JCLI3705.1, 2011. a
Lewis-Beck, M. S.: Data Analysis: An Introduction, Sage Publications, Thousand Oaks, CA, ISBN 9780803957725, 1995. a
Love, T. B., Kumar, V., Xie, P., and Thiaw, W.: A 20-year daily Africa precipitation climatology using satellite and gauge data, 14th Conf. on Applied Meteorology, Seattle, WA, Amer. Meteor. Soc., P5.4, 2004, http://ams.confex.com/ams/pdfpapers/67484.pdf (last access: December 2023), 2004. a
Mariani, M., Holz, A., Veblen, T. T., Williamson, G., Fletcher, M.-S., and Bowman, D. M. J. S.: Climate change amplifications of climate-fire teleconnections in the Southern Hemisphere, Geophys. Res. Lett., 45, 5071–5081, https://doi.org/10.1029/2018GL078294, 2018. a, b
Martens, B., Waegeman, W., Dorigo, W. A., Verhoest, N. E. C., and Miralles, D. G.: Terrestrial evaporation response to modes of climate variability, npj Climate and Atmospheric Science, 1, 43, https://doi.org/10.1038/s41612-018-0053-5, 2018. a
Marto, R., Alvarez, L., and Suarez, D.: Background Paper: LAC Small Island Development States, IDB Publications, https://doi.org/10.18235/0009228, 2014. a
McLean, N. M., Stephenson, T. S., Taylor, M. A., and Campbell, J. D.: Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones, Adv. Meteorol., 2015, 1–18, https://doi.org/10.1155/2015/425987, 2015. a, b, c
Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S., and Donlon, C.: Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI), Geosci. Data J., 1, 179–191, https://doi.org/10.1002/gdj3.20, 2014. a
Mo, K. C., Chelliah, M., Carrera, M. L., Higgins, R. W., and Ebisuzaki, W.: Atmospheric Moisture Transport over the United States and Mexico as Evaluated in the NCEP Regional Reanalysis, J. Hydrometeor., 6, 710–728, https://doi.org/10.1175/JHM452.1, 2005. a, b
Moron, V., Frelat, R., Jean-Jeune, P. K., and Gaucherel, C.: Interannual and intra-annual variability of rainfall in Haiti (1905–2005), Clim. Dynam., 45, 915–932, https://doi.org/10.1007/s00382-014-2326-y, 2015. a
Naciones Unidades, Comision economica para America Latima y el Caribe: Repuplica Dominica: evaluacion de los danos ocasionados por el huracan Georges, sus implicaciones para el desarrollo del pais, 91 pp., https://hdl.handle.net/11362/25344 (last access: June 2023), 1988. a
Nobre, P. and Shukla, J.: Variation of Sea Surface Temperature, Wind Stress and Rainfall over the Tropical Atlantic and South America, J. Climate, 9, 2464–2479, https://doi.org/10.1175/1520-0442(1996)009<2464:VOSSTW>2.0.CO;2, 1996. a
North Atlantic Oscillation: NOAA's Climate Prediction Center, https://www.climate.gov/news-features/understanding-climate/climate-variability-north-atlantic-oscillation, last access: 8 December 2023. a
Nurse, M.: Droughts, hurricanes, pandemic, and hope: Current realities im- pacting Caribbean agriculture. CARICOM Today, 5 June, https://www.caricomstats.org/E-CISTAR/2020/06/03/droughts-hurricanes-pandemic-and-hope-current-realities-impacting-caribbean-agriculture/ (last access: 19 March 2023), 2023. a
Peterson, T. C., Taylor, M. A., Demeritte, R., Duncombe, D. L., Burton, S., Thompson, F., Porter, A., Mercedes, M., Villegas, E., Semexant Fils, R., Klein Tank, A., Martis, A., Warner, R., Joyette, A., Mills, W., Alexander, L., and Gleason, B.: Recent changes in climate extremes in the Caribbean region: RECENT CHANGES IN CLIMATE EXTREMES IN THE CARIBBEAN REGION, J. Geophys. Res., 107, ACL 16-1–ACL 16-9, https://doi.org/10.1029/2002JD002251, 2002. a, b, c
Philander, S. G. H., Gu, D. D., Lambert, G., Li, T., Halpern, D., Lau, N., and Pacanowski, R. C.: Why the ITCZ Is Mostly North of the Equator, J. Climate, 9, 2958–2972, https://doi.org/10.1175/1520-0442(1996)009<2958:WTIIMN>2.0.CO;2, 1996. a
Physical Sciences Laboratory: NOAA OI SST V2 High Resolution Dataset, Physical Sciences Laboratory [data set], https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html, last access: July 2023. a
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003. a
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and Schlax, M. G.: Daily high-resolution blended analyses for sea surface temperature, J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1, 2007. a, b
Ríos-Cornejo, D., Penas, A., Álvarez-Esteban, R., and del Río, S.: Links between teleconnection patterns and precipitation in Spain, Atmos. Res., 156, 14–28, https://doi.org/10.1016/j.atmosres.2014.12.012, 2015. a
Rivera, J. A., Hinrichs, S., and Marianetti, G.: Using CHIRPS dataset to assess wet and dry conditions along the semiarid central-western Argentina, Adv. Meteor., 18, 8413964, https://doi.org/10.1155/2019/8413964, 2019. a
Rodrigues, M., Peña-Angulo, D., Russo, A., Zúñiga-Antón, M., and Cardil, A.: Do climate teleconnections modulate wildfire-prone conditions over the Iberian Peninsula?, Environ. Res. Lett., 16, 044050, https://doi.org/10.1088/1748-9326/abe25d, 2021. a
Rodriguez-Vera, G., Romero-Centeno, R., Castro, C. L., and Castro, V. M.: Coupled Interannual Variability of Wind and Sea Surface Temperature in the Caribbean Sea and the Gulf of Mexico, J. Climate, 32, 4263–4280, https://doi.org/10.1175/JCLI-D-18-0573.1, 2019. a
Ropelewski C. F. and Halpert, M. S.: Global and regional scale precipitation and temperature patterns associated with El Niño–Southern Oscillation, Mon. Weather Rev., 115, 1606–1626, https://doi.org/10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2, 1987. a
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, Jiande, Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, Jun, Hou, Y.-T., Chuang, H., Juang, H.-M. H., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: The NCEP Climate Forecast System Reanalysis, B. Am. Meteorol. Soc., 91, 1015–1058, https://doi.org/10.1175/2010BAMS3001.1, 2010. a
Sheskin, D. J.: Handbook of Parametric and Nonparametric Statistical Procedures, 4th edn., Boca Raton, FL, Chapman & Hall/CRC, ISBN 978-1439858011, 2007. a
Smith, T. M., Reynolds, R. W., Livezey, R. E., and Stokes, D. C.: Reconstruction of Historical Sea Surface Temperatures Using Empirical Orthogonal Functions, J. Climate, 9, 1403–1420, https://doi.org/10.1175/1520-0442(1996)009<1403:ROHSST>2.0.CO;2, 1996. a
Stephenson, T. S., Vincent, L. A., Allen, T., Van Meerbeeck, C. J., McLean, N., Peterson, T. C., Taylor, M. A., Aaron-Morrison, A. P., Auguste, T., Bernard, D., Boekhoudt, J. R. I., Blenman, R. C., Braithwaite, G. C., Brown, G., Butler, M., Cumberbatch, C. J. M., Etienne-Leblanc, S., Lake, D. E., Martin, D. E., McDonald, J. L., Ozoria Zaruela, M., Porter, A. O., Santana Ramirez, M., Tamar, G. A., Roberts, B. A., Sallons Mitro, S., Shaw, A., Spence, J. M., Winter, A., and Trotman, A. R.: Changes in extreme temperature and precipitation in the Caribbean region, 1961–2010, Int. J. Climatol., 34, 2957–2971, https://doi.org/10.1002/joc.3889, 2014. a, b, c, d
Taylor, M. A. and Enfield, D. B.: Chen, Influence of the tropical Atlantic versus the tropical Pacific on Caribbean rainfall, J. Geophys. Res., 107, 3127, https://doi.org/10.1029/2001JC001097, 2002. a
Taylor, M. A., Clarke, L. A., Cantella, A., Bezanilla, A., Stephenson, T. S., Jones, J., Campbell, J. D., Vichot, A., and Charlery, J.: Future Caribbean Climates in a World of Rising Temperatures: The 1.5 vs 2.0 Dilemma, J. Climate, 31, 2907–2926, https://doi.org/10.1175/JCLI-D-17-0074.1, 2018. a
Thompson, D. W. J. and Wallace, J. M.: Annular modes in the extratropical circulation Part I: Month-to-month variability, J. Climate, 13, 1000–1016, https://doi.org/10.1175/1520-0442(2000)013<1000:AMITEC>2.0.CO;2, 2000. a
Thorncroft, C. and Hodges, K.: African easterly wave variability and its relationship to Atlantic tropical cyclone activity, J. Climate, 14, 1166–1179, https://doi.org/10.1175/1520-0442(2001)014<1166:AEWVAI>2.0.CO;2, 2001. a
Utida, G., Cruz, F. W., Etourneau, J., Bouloubassi, I., Schefuß, E., Vuille, M., Novello, V. F., Prado, L. F., Sifeddine, A., Klein, V., Zular, A., Viana, J. C. C., and Turcq, B.: Tropical South Atlantic influence on Northeastern Brazil precipitation and ITCZ displacement during the past 2300 years, Sci. Rep., 9, 1698, https://doi.org/10.1038/s41598-018-38003-6, 2019. a, b
Vichot‐Llano, A., Martinez‐Castro, D., Bezanilla‐Morlot, A., Centella‐Artola, A., and Giorgi, F.: Projected changes in precipitation and temperature regimes and extremes over the Caribbean and Central America using a multiparameter ensemble of RegCM4, Int. J. Climatol., 41, 1328–1350, https://doi.org/10.1002/joc.6811, 2021. a
Visbeck, M. H., Hurrell, J. W., Polvani, L., and Cullen, H. M.: The North Atlantic Oscillation: Past, present, and future, P. Natl. Acad. Sci. USA, 98, 12876–12877, https://doi.org/10.1073/pnas.231391598, 2001. a
Von Storch, H. and Zwiers, F. C.: Statistical Analysis in Climate Research. Cambridge University Press, Cambridge, 0 521 45071 3, 1999. a
Wallace, J. M. and Gutzler, D. S.: Teleconnections in the Geopotential Height Field during the Northern Hemisphere Winter, Mon. Weather Rev., 109, 784–812, https://doi.org/10.1175/1520-0493(1981)109<0784:TITGHF>2.0.CO;2, 1981. a
Wang, C., Enfield, D. B., Lee, S., and Landsea, C. W.: Influences of the Atlantic Warm Pool on Western Hemisphere Summer Rainfall and Atlantic Hurricanes, J. Climate, 19, 3011–3028, https://doi.org/10.1175/JCLI3770.1, 2006. a
Wang, C., Lee, S., and Enfield, D. B.: Impact of the Atlantic Warm Pool on the Summer Climate of the Western Hemisphere, J. Climate, 20, 5021–5040, https://doi.org/10.1175/JCLI4304.1, 2007. a
Wu, R. and Kirtman, B. P.: Caribbean Sea rainfall variability during the rainy season and relationship to the equatorial Pacific and tropical Atlantic SST, Clim. Dynam., 37, 1533–1550, https://doi.org/10.1007/s00382-010-0927-7, 2011. a
Short summary
This work provides a relevant analysis of changes in extreme precipitation over the Caribbean and their link with warming in different ocean basins. It also improves our understanding of the impact of warming on extreme precipitation events, which can cause devastating damage to economic sectors such as agriculture, biodiversity, health, and energy.
This work provides a relevant analysis of changes in extreme precipitation over the Caribbean...
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