74 citations as recorded by crossref.

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4. Extending the global high-resolution downscaled projections dataset to include CMIP6 projections at increased resolution coherent with the ERA5-Land reanalysis T. Noël et al. https://doi.org/10.1016/j.dib.2022.108669
5. Evaluation and improvement of tail behaviour in the cumulative distribution function transform downscaling method J. Lanzante et al. https://doi.org/10.1002/joc.5964
6. Multivariate Bias‐Correction of High‐Resolution Regional Climate Change Simulations for West Africa: Performance and Climate Change Implications D. Dieng et al. https://doi.org/10.1029/2021JD034836
7. Climate change impacts on floods in West Africa: new insight from two large-scale hydrological models S. Diop et al. https://doi.org/10.5194/nhess-25-3161-2025
8. Effects of Climate Variability on Malaria Transmission in Southern Côte d’Ivoire, West Africa M. Doumbia et al. https://doi.org/10.3390/ijerph20237102
9. Bias-Corrected CMIP5 Projections for Climate Change and Assessments of Impact on Malaria in Senegal under the VECTRI Model P. Fall et al. https://doi.org/10.3390/tropicalmed8060310
10. How might climate change affect river flows across West Africa? P. Rameshwaran et al. https://doi.org/10.1007/s10584-021-03256-0
11. Climate–yield interactions in West Africa: Machine learning insights for cocoa production in Ghana and Côte d’Ivoire S. Obahoundje et al. https://doi.org/10.1371/journal.pclm.0000970
12. Assessment of Climate Change Impact on Water Requirement and Rice Productivity K. N’guessan et al. https://doi.org/10.1016/j.rsci.2023.03.010
13. Stress-testing development pathways under a changing climate: water-energy-food security in the lake Malawi-Shire river system A. Bhave et al. https://doi.org/10.1098/rsta.2021.0134
14. Evaluating the sensitivity of robust water resource interventions to climate change scenarios R. Geressu et al. https://doi.org/10.1016/j.crm.2022.100442
15. Predicting crop yields in Senegal using machine learning methods A. Sarr & B. Sultan https://doi.org/10.1002/joc.7947
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17. ECHIDNA: Extreme Climate Historical and Future Indices Data under Numerous Approaches across Major Chinese River Basins Based on CMIP6 Multi-Model Ensemble L. Xinlong et al. https://doi.org/10.1038/s41597-026-07510-x
18. Migration response to drought in Mali. An analysis using panel data on Malian localities over the 1987-2009 period D. Defrance et al. https://doi.org/10.1017/S1355770X22000183
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21. Multivariate bias corrections of climate simulations: which benefits for which losses? B. François et al. https://doi.org/10.5194/esd-11-537-2020
22. A support vector machine-based method for improving real-time hourly precipitation forecast in Japan G. Yin et al. https://doi.org/10.1016/j.jhydrol.2022.128125
23. A Hybrid Statistical-Dynamical Downscaling of Air Temperature over Scandinavia Using the WRF Model J. Wang et al. https://doi.org/10.1007/s00376-019-9091-0
24. Future water resources and droughts in the Atlas Mountains of Morocco under a high-emission climate scenario O. Lahnik et al. https://doi.org/10.1016/j.ejrh.2025.102371
25. MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change T. Yokohata et al. https://doi.org/10.5194/gmd-13-4713-2020
26. Combining CMIP data with a regional convection-permitting model and observations to project extreme rainfall under climate change C. Klein et al. https://doi.org/10.1088/1748-9326/ac26f1
27. Adaptive policies balancing trade, productivity and cropland increases can support Zambia’s nutrition security under future climate shocks S. Jennings et al. https://doi.org/10.1038/s43016-026-01405-1
28. Tailored climate projections to assess site-specific vulnerability of tea production N. Mittal et al. https://doi.org/10.1016/j.crm.2021.100367
29. Lake Malawi’s threshold behaviour: A stakeholder-informed model to simulate sensitivity to climate change A. Bhave et al. https://doi.org/10.1016/j.jhydrol.2020.124671
30. Time of emergence of impacts of climate change on groundwater levels in sub-Saharan Africa M. Ascott et al. https://doi.org/10.1016/j.jhydrol.2022.128107
31. Effect of Climate Change on Staple Food Production: Empirical Evidence from a Structural Ricardian Analysis Y. Luh & Y. Chang https://doi.org/10.3390/agronomy11020369
32. ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1) F. Spuler et al. https://doi.org/10.5194/gmd-17-1249-2024
33. How could climate change affect the magnitude, duration and frequency of hydrological droughts and floods in West Africa during the 21st century? A storyline approach J. Ekolu et al. https://doi.org/10.1016/j.jhydrol.2025.133482
34. Change in Climate Indices Using Bias-Adjusted CMIP5 Models: The Case Study of the Fatick Region, Senegal I. Camara et al. https://doi.org/10.4236/ajcc.2022.114015
35. Impact of 1.5 and 2.0 °C global warming on the hydrology of the Faleme river basin M. Mbaye et al. https://doi.org/10.1016/j.ejrh.2020.100719
36. Impact of Climate Change in West Africa on Cereal Production Per Capita in 2050 D. Defrance et al. https://doi.org/10.3390/su12187585
37. Bias Correction for Climate Model Output (1) Method Characteristics and Classification S. WATANABE https://doi.org/10.3178/jjshwr.33.243
38. Ensemble bias correction of climate simulations: preserving internal variability P. Vaittinada Ayar et al. https://doi.org/10.1038/s41598-021-82715-1
39. A high-resolution downscaled CMIP5 projections dataset of essential surface climate variables over the globe coherent with the ERA5 reanalysis for climate change impact assessments T. Noël et al. https://doi.org/10.1016/j.dib.2021.106900
40. Impact of an accelerated melting of Greenland on malaria distribution over Africa A. Chemison et al. https://doi.org/10.1038/s41467-021-24134-4
41. Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations A. Dosio et al. https://doi.org/10.1007/s10584-022-03307-0
42. To bias correct or not to bias correct? An agricultural impact modelers’ perspective on regional climate model data P. Laux et al. https://doi.org/10.1016/j.agrformet.2021.108406
43. Impact of climate change on crop suitability in sub-Saharan Africa in parameterized and convection-permitting regional climate models S. Chapman et al. https://doi.org/10.1088/1748-9326/ab9daf
44. Millet and sorghum yield simulations under climate change scenarios in Senegal A. Faye et al. https://doi.org/10.1007/s10113-022-01940-0
45. How a typical West African day in the future-climate compares with current-climate conditions in a convection-permitting and parameterised convection climate model R. Fitzpatrick et al. https://doi.org/10.1007/s10584-020-02881-5
46. Adapting rainfed rice to climate change: a case study in Senegal E. Gérardeaux et al. https://doi.org/10.1007/s13593-021-00710-2
47. Impact of an acceleration of ice sheet melting on monsoon systems A. Chemison et al. https://doi.org/10.5194/esd-13-1259-2022
48. Heat waves in spring from Senegal to Sahel: Evolution under climate change M. Sambou et al. https://doi.org/10.1002/joc.7176
49. Systematic investigation of skill opportunities in decadal prediction of air temperature over Europe G. Sgubin et al. https://doi.org/10.1007/s00382-021-05863-0
50. Assessing the impacts of climate change on flooding under Coupled Model Intercomparison Project Phase 6 scenarios in the river Chenab, Pakistan S. Kiran et al. https://doi.org/10.1007/s11069-023-05892-4
51. A New Integrated Assessment Framework for Climate-Smart Nutrition Security in sub-Saharan Africa: The Integrated Future Estimator for Emissions and Diets (iFEED) S. Jennings et al. https://doi.org/10.3389/fsufs.2022.868189
52. Robust assessment of the time of emergence of precipitation change in West Africa M. Gaetani et al. https://doi.org/10.1038/s41598-020-63782-2
53. Teal-WCA: A Climate Services Platform for Planning Solar Photovoltaic and Wind Energy Resources in West and Central Africa in the Context of Climate Change S. Obahoundje et al. https://doi.org/10.3390/data9120148
54. On the application of rainfall projections from a convection-permitting climate model to lumped catchment models M. Ascott et al. https://doi.org/10.1016/j.jhydrol.2023.129097
55. Ranking of CMIP6 based High-resolution Global Climate Models for India using TOPSIS R. Thakur & V. Manekar https://doi.org/10.1080/09715010.2021.2015462
56. Spatiotemporal characteristics of future precipitation variability in the Tianshan Mountain region of China X. Lyu et al. https://doi.org/10.1016/j.ejrh.2024.102124
57. Comparing bias adjustment methods for CMIP6 extreme precipitation projections in the San-Pédro River Basin (Côte d’Ivoire, West Africa) F. Akaffou et al. https://doi.org/10.1007/s00704-026-06043-y
58. Climate data uncertainty for agricultural impact assessments in West Africa P. Romanovska et al. https://doi.org/10.1007/s00704-023-04430-3
59. Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa S. Kolusu et al. https://doi.org/10.1007/s10584-021-02991-8
60. Less negative impacts of climate change on crop yields in West Africa in the new CMIP6 climate simulations ensemble B. Sultan et al. https://doi.org/10.1371/journal.pclm.0000263
61. Projected Future Flooding Pattern of Wabash River in Indiana and Fountain Creek in Colorado: An Assessment Utilizing Bias-Corrected CMIP6 Climate Data S. Paudel et al. https://doi.org/10.3390/forecast5020022
62. Differential Impacts of 1.5 and 2 °C Warming on Extreme Events Over China Using Statistically Downscaled and Bias‐Corrected CESM Low‐Warming Experiment Y. Yang et al. https://doi.org/10.1029/2018GL079272
63. Integrating multi-model ensemble and spatiotemporal analysis for enhanced climate modelling in Nigeria D. Olasehinde et al. https://doi.org/10.1080/24749508.2026.2620210
64. Climate change will limit the potential for intensification in Senegal A. Mbengue et al. https://doi.org/10.1088/2515-7620/ae59f4
65. Impacts of Greenland and Antarctic Ice Sheet melt on future Köppen climate zone changes simulated by an atmospheric and oceanic general circulation model D. Defrance et al. https://doi.org/10.1016/j.apgeog.2020.102216
66. Stakeholder-driven transformative adaptation is needed for climate-smart nutrition security in sub-Saharan Africa S. Jennings et al. https://doi.org/10.1038/s43016-023-00901-y
67. Should We Use Quantile-Mapping-Based Methods in a Climate Change Context? A “Perfect Model” Experiment M. Vrac et al. https://doi.org/10.3390/cli13070137
68. Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century D. Defrance https://doi.org/10.1016/j.dib.2019.104585
69. Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle L. Teckentrup et al. https://doi.org/10.5194/esd-14-549-2023
70. High-Resolution Downscaled CMIP6 Projections dataset of Key Climate Variables for Senegal A. Mbengue et al. https://doi.org/10.1038/s41597-026-07059-9
71. Strong regional influence of climatic forcing datasets on global crop model ensembles A. Ruane et al. https://doi.org/10.1016/j.agrformet.2020.108313
72. Investigating the potential impact of 1.5, 2 and 3 °C global warming levels on crop suitability and planting season over West Africa T. Egbebiyi et al. https://doi.org/10.7717/peerj.8851
73. Regional climate model emulator based on deep learning: concept and first evaluation of a novel hybrid downscaling approach A. Doury et al. https://doi.org/10.1007/s00382-022-06343-9
74. Enhancing Understanding of the Impact of Climate Change on Malaria in West Africa Using the Vector-Borne Disease Community Model of the International Center for Theoretical Physics (VECTRI) and the Bias-Corrected Phase 6 Coupled Model Intercomparison Project Data (CMIP6) P. Fall et al. https://doi.org/10.3390/microbiolres14040145