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Literatura académica sobre el tema "IPSL-CM6A-LR"

Autor: Grafiati

Publicado: 25 de mayo de 2024

Última modificación: 19 de julio de 2025

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Artículos de revistas sobre el tema "IPSL-CM6A-LR"

Din, Salah Ud. "Flow prediction in Kabul River: An artificial intelligence based technique." International Journal of Multidisciplinary Research and Growth Evaluation 5, no. 2 (2024): 854–57. http://dx.doi.org/10.54660/.ijmrge.2024.5.2.854-857.

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This study employs random forest regressor to forecast future flow in Kabul River. Utilizing CMIP6 projected climate data for the SSP585 scenario from the IPSL-CM6A-LR climate model. The random forest regressor demonstrate efficacy in predicting flow, achieving an R2 of 0.77. The study highlights the importance of modern artificial intelligence-based techniques for precise flow and flood predictions and suggests an increase in flash flood events in Kabul River in response to a warming climate.

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Zeraatkar, Zahra, Ali Shahidi, and Hadi Memarian. "Assessment and efficiency of CMIP6 models in simulation and prediction of climatic parameters of precipitation and temperature in the Samalghan basin, Iran." Időjárás 128, no. 1 (2024): 59–74. http://dx.doi.org/10.28974/idojaras.2024.1.4.

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In the present study, four global climate models MRI-ESM2-0, IPSL-CM6A-LR, CanESM5, and GFDL-ESM4 from the set of CMIP6 models are assessed to select the best model and determine the effects of climate change on temperature and precipitation parameters under three shared socioeconomic pathway scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the base period (1988–2017) and a future period (2020–2049) in the Samalghan basin. Statistical measures such as mean absolute error, root mean square error, mean bias error are applied to test the models, and the correlation coefficient is used to compare

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Ndiaye, Cassien Diabe, Elsa Mohino, Juliette Mignot, and Dr MOHAMADOU SAIDOU SALL. "On the Detection of Externally Forced Decadal Modulations of the Sahel Rainfall over the Whole Twentieth Century in the CMIP6 Ensemble." Journal of Climate 35, no. 21 (2022): 6939–54. https://doi.org/10.1175/JCLI-D-21-0585.1.

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Abstract The Sahel semiarid region was marked during the twentieth century by significant modulations of its rainfall regime at the decadal time scale. Part of these modulations have been associated with the internal variability of the climate system, linked to changes in oceanic sea surface temperature. More recently, several studies have highlighted the influence of external forcings during the dry period in the 1980s and the recovery around the 2000s. In this work we evaluate the internally and externally driven decadal modulations of Sahel rainfall during the entire twentieth century using

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Andrade-Velázquez, Mercedes, and Martín José Montero-Martínez. "Statistical Downscaling of Precipitation in the South and Southeast of Mexico." Climate 11, no. 9 (2023): 186. http://dx.doi.org/10.3390/cli11090186.

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The advancements in global climate modeling achieved within the CMIP6 framework have led to notable enhancements in model performance, particularly with regard to spatial resolution. However, the persistent requirement for refined techniques, such as dynamically or statistically downscaled methods, remains evident, particularly in the context of precipitation variability. This study centered on the systematic application of a bias-correction technique (quantile mapping) to four designated CMIP6 models: CNRM-ESM2-6A, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0. The selection of these models was inform

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Poletti, Alyssa N., Dargan M. W. Frierson, Travis Aerenson, et al. "Atmosphere and ocean energy transport in extreme warming scenarios." PLOS Climate 3, no. 2 (2024): e0000343. http://dx.doi.org/10.1371/journal.pclm.0000343.

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Extreme scenarios of global warming out to 2300 from the SSP5-8.5 extension scenario are analyzed in three state-of-the-art climate models, including two models with climate sensitivity greater than 4.5°C. The result is some of the largest warming amounts ever seen in simulations run over the historical record and into the future. The simulations exhibit between 9.3 and 17.5°C global mean temperature change between pre-Industrial and the end of the 23rd century. The extremely large changes in global temperature allow exploration of fundamental questions in climate dynamics, such as the determi

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Hamid, H., S. N. Rahmat, H. Kasmin, and N. N. Tukimat. "Rainfall projection using CIMP6 models of extreme area in Johor." IOP Conference Series: Earth and Environmental Science 1347, no. 1 (2024): 012013. http://dx.doi.org/10.1088/1755-1315/1347/1/012013.

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Abstract This paper explores the impact of climate change on rainfall patterns, particularly extreme intensity, in Johor, Malaysia. The study focuses on addressing uncertainties in climate change projections by selecting suitable Global Climate Models (GCMs) based on location and topography. Four CMIP6 models (GFDL-ESM4, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0) were chosen for analysis. The research employs statistical downscaling, using historical observed data (1988-2020) and GCM output data, with a bias correction through linear scaling. The performance of the GCMs is assessed using various me

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Almeida, Débora de Melo, Sara Sebastiana Nogueira, Emanuel Araújo Silva, João Matheus Ferreira de Souza, Antonio Leandro Chaves Gurgel, and Alex Nascimento de Sousa. "Climate change is expected to reduce the potential distribution of Ceiba glaziovii in Caatinga, the largest area of dry tropical forest in South America." Bioscience Journal 40 (October 30, 2024): e40051. http://dx.doi.org/10.14393/bj-v40n0a2024-72663.

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Ecological niche modeling is a widely used tool to predict species distribution considering current, past, or future climate change scenarios across different geographic areas. Modeling scenarios allow researchers to assess the impacts of climate change on species distribution and identify priority areas for conservation. This study aimed to model the current and future potential distribution of Ceiba glaziovii under different climate change scenarios in Brazil. The MaxEnt algorithm was used to correlate species occurrence points with bioclimatic variables in current and future climate scenari

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Üyük, Ayyüce, and Ömer K. Örücü. "Platanus orientalis L. (Doğu Çınarı) günümüz ve gelecek yayılış alanlarının CanESM5ve IPSL-CM6A-LR iklim modellerine göre karşılaştırılması." Ecological Perspective 2, no. 1 (2022): 137–50. http://dx.doi.org/10.53463/ecopers.20220146.

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Peyzaj Mimarlığı meslek disiplininin başlıca tasarım öğesi olan bitki materyalinin iklim değişikliğinden nasıl etkileneceğini analiz etmek, bu türlerin bitkilendirme çalışmalarında gelecekteki kullanımlarının planlanması açısından çok önemlidir. Çalışma için ilk olarak Platanus orientalis L. Türün günümüz koşullarındaki potansiyel yayılış alanı, türün mevcudiyet verileri ve 2,5 dakikalık (yaklaşık 20 km2) uzamsal çözünürlüğe sahip WorldClim 2.1 versiyon 19 biyoiklimsel değişkenler kullanılarak tahmin edilmektedir. Platanus orientalis L. dağıtım alanlarının iklim değişikliğinden nasıl etkilendi

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Sarikaya, Ayse Gul, and Almira Uzun. "Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning." Sustainability 16, no. 3 (2024): 1230. http://dx.doi.org/10.3390/su16031230.

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Species of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently

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Ruiz-Diaz, Raquel, Mariano Koen-Alonso, Frédéric Cyr, et al. "Climate models drive variation in projections of species distribution on the Grand Banks of Newfoundland." PLOS Climate 3, no. 11 (2024): e0000520. http://dx.doi.org/10.1371/journal.pclm.0000520.

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Species Distribution Models (SDMs) are tools for understanding climate-induced habitat changes, yet their outcomes depend heavily on climate model selection. This study compares biomass projections for three key species on the Grand Banks of Newfoundland that are known to be sensitive to warming—snow crab, yellowtail flounder, and Atlantic cod. We use Earth system models (GFDL-ESM4, IPSL-CM6A-LR) and a regional ocean model system (Atlantic Climate Model (ACM)) under varying climate change emissions scenarios to assess long-term biomass trends and distributional shifts driven by future ocean wa

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Tesis sobre el tema "IPSL-CM6A-LR"

Feng, Yang. "Study of the climate variability and the role of volcanism in the North Atlantic-Mediterranean sector during the last millennium." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS038.

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La thèse vise à étudier le rôle du volcanisme ainsi ses impacts sur la variabilité climatique hivernale (spécialement l'ONA) dans le secteur Atlantique Nord-Méditerranée à l'échelle interannuelle. La première partie est consacrée à la caractérisation du signal d'ONA en hiver à la suite d'éruptions volcaniques stratosphériques grâce à trois simulations transitoires du dernier millénaire (500-1849 CE) par IPSL-CM6A-LR dans le cadre de PMIP4. La robustesse et la sensibilité de réponse liée à la latitude, la saison et la magnitude des éruptions sont ainsi explorées. La deuxième partie étend plus l

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Barthélemy, Léonard. "« Rivières Atmosphériques » en Antarctique : caractéristiques et impacts, du passé au futur." Electronic Thesis or Diss., Sorbonne université, 2025. http://www.theses.fr/2025SORUS008.

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Dans le contexte du changement climatique, le suivi de l'évolution du bilan de masse (BM) de la calotte de glace Antarctique est essentiel pour prédire sa contribution potentielle à la hausse du niveau des mers. En effet, l'augmentation de la vapeur d'eau dans l'atmosphère, conséquence de la hausse des températures (selon la relation de Clausius-Clapeyron), entraîne une hausse des précipitations en Antarctique, notamment sous forme d'accumulation de neige, stockant ainsi de l'eau sur le continent. Toutefois, les cumuls annuels de neige proviennent principalement d'événements hydrologiques rare

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