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

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 31 de julio de 2025

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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11

Xiao, Heng, Yue Zhuo, Hong Sun, Kaiwen Pang, and Zhijia An. "Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations." Atmosphere 14, no. 9 (2023): 1429. http://dx.doi.org/10.3390/atmos14091429.

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The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Scienc
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12

Lamichhane, Shankar. "Assessment and Selection of CMIP6 Climate Models: Application to the Budhigandaki River Basin (BGRB), Nepal." Himalayan Journal of Applied Science and Engineering 6, no. 1 (2025): 90–109. https://doi.org/10.3126/hijase.v6i1.81072.

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The most representative CMIP6 Global Climate Models for predicting future climate conditions in the Budhigandaki River Basin (BGRB) are found using an advanced envelope selection method. For each scenario (SSP2-4.5 and SSP5-8.5), four GCMs that best replicate the basin's historical climate and forecast future changes were selected by combining envelope-based range coverage, historical performance assessment, and climate extreme analysis. EC-Earth3-CC, MIROC6, MPI-ESM1-2-LR, and MRI-ESM2-0, representing the Warm-Wet, Warm-Dry, Cold-Dry, and Cold-Wet extremes for SSP2-4.5. For the corresponding
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13

Raila, Shiva Nath, Raju Acharya, Sudan Ghimire, et al. "Out-Performing Bias-Corrected GCM Models and CMIP6-Based Precipitation and Temperature Projections for the Bagmati Irrigation Area." Journal of Advanced College of Engineering and Management 7, no. 01 (2022): 165–72. http://dx.doi.org/10.3126/jacem.v7i01.47342.

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The selection of General circulation models (GCMs) and suitable bias correction methods for any particular study area in very crucial for the projection of precipitation and temperature using climate models which can be used for estimating the future crop water requirement. The results of a General Circulation Model (GCM) are being downscaled and compared to a baseline climatology for two IPCC scenarios (ssp245 and ssp585) based on Coupled Model Inter-comparison Project Phase 6 (CMIP6) climate model. We choose four GCMs models out of ten by evaluating their performance to observe historical da
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14

Babaousmail, Hassen, Rongtao Hou, Brian Ayugi, et al. "Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa." Atmosphere 12, no. 4 (2021): 475. http://dx.doi.org/10.3390/atmos12040475.

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This study assesses the performance of historical rainfall data from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the spatial and temporal rainfall variability over North Africa. Datasets from Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets to examine the capability of 15 CMIP6 models’ and their ensemble in simulating rainfall during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), and Taylor skill score (TSS) are uti
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15

Smith, Christopher J., Ryan J. Kramer, and Adriana Sima. "The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere." Earth System Science Data 12, no. 3 (2020): 2157–68. http://dx.doi.org/10.5194/essd-12-2157-2020.

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Abstract. We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable
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16

Ragab, Sanad H., Shatha I. Alqurashi, Mohammad M. Aljameeli, Michael G. Tyshenko, Ahmed H. Abdelwahab, and Tharwat A. Selim. "Predicting the Global Distribution of Gryllus bimaculatus Under Climate Change: Implications for Biodiversity and Animal Feed Production." Sustainability 16, no. 23 (2024): 10278. http://dx.doi.org/10.3390/su162310278.

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The potential range and distribution of insects are greatly impacted by climate change. This study evaluates the potential global shifts in the range of Gryllus bimaculatus (Orthoptera: Gryllidae) under several climate change scenarios. The Global Biodiversity Information Facility provided the location data for G. bimaculatus, which included nineteen bioclimatic layers (bio01–bio19), elevation data from the WorldClim database, and land cover data. For the near future (2021–2040) and far future (2081–2100) under low (SSP1-2.6) and high (SSP5-8.5) emission scenarios, the Beijing Climate Center C
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17

Acarer, Ahmet. "Role of climate change on Oriental spruce (Picea orientalis L.): Modeling and mapping." BioResources 19, no. 2 (2024): 3845–56. http://dx.doi.org/10.15376/biores.19.2.3845-3856.

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Global climate change is a process with dramatic consequences for ecosystems, and changes that may occur in the potential distribution of plant communities especially draw attention. This study aimed to reveal the potential distribution modeling and mapping of the Oriental spruce (Picea orientalis L.), distributed in a limited area, using current and future (year 2100) climate scenarios in Turkey. The maximum entropy method for potential distribution and Chelsa V2.1 technical specification IPSL-CM6A-LR scenarios (SSP126-SSP370-SSP585) were preferred to reveal the effect of climate change. Resu
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18

Ragab, Sanad H., and Michael G. Tyshenko. "Predicting the potential worldwide distribution of Aedes aegypti under climate change scenarios." International Journal of Scientific Reports 9, no. 11 (2023): 344–52. http://dx.doi.org/10.18203/issn.2454-2156.intjscirep20233163.

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Background: Climate change is one of the most important factors associated with medically important insect pests such as mosquitoes (Diptera: Culicidae). Diseases spread by mosquitoes are increasing due to changes in global temperature and weather patterns that are altering vector host ranges allowing spread into new regions. Zika, dengue fever, chikungunya and yellow fever are arboviral infections that are spread by Aedes aegypti (Culicidae). The objective of the current research is to study the potential geographic distribution habitats of Ae. aegypti in the world under current and future cl
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19

Casagrande, Fernanda, Ronald Buss de Souza, Paulo Nobre, and Andre Lanfer Marquez. "An inter-hemispheric seasonal comparison of polar amplification using radiative forcing of a quadrupling CO<sub>2</sub> experiment." Annales Geophysicae 38, no. 5 (2020): 1123–38. http://dx.doi.org/10.5194/angeo-38-1123-2020.

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Abstract. The numerical climate simulations from the Brazilian Earth System Model (BESM) are used here to investigate the response of the polar regions to a forced increase in CO2 (Abrupt-4×CO2) and compared with Coupled Model Intercomparison Project phase 5 (CMIP5) and 6 (CMIP6) simulations. The main objective here is to investigate the seasonality of the surface and vertical warming as well as the coupled processes underlying the polar amplification, such as changes in sea ice cover. Polar regions are described as the most climatically sensitive areas of the globe, with an enhanced warming o
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20

Anil, Suram, and P. Anand Raj. "Deciphering the projected changes in CMIP-6 based precipitation simulations over the Krishna River Basin." Journal of Water and Climate Change 13, no. 3 (2022): 1389–407. http://dx.doi.org/10.2166/wcc.2022.399.

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Abstract The impact of climate change on the Krishna River Basin (KRB) is significant due to the semi-arid nature of the basin. Herein, 21 global climate models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) were examined to simulate the historical monthly precipitation over the 1951–2014 period in the KRB. The symmetrical uncertainty (SU) method and the multi-criteria decision method (MCDM) were employed to select the suitable GCMs for projecting possible changes in precipitation over the KRB. The biases in the climate projections were removed by using the empirical quantile
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21

Cruz-Baltuano, Ana, Raúl Huarahuara-Toma, Arlette Silva-Borda, et al. "Assessment of Observed and Projected Extreme Droughts in Perú—Case Study: Candarave, Tacna." Atmosphere 16, no. 1 (2024): 18. https://doi.org/10.3390/atmos16010018.

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Droughts have always been one of the most dangerous hazards for civilizations, especially when they impact the headwaters of a watershed, as their effects can spread downstream. In this context, observed droughts (1981–2015) and projected droughts (2016–2100) were assessed in Candarave, the headwaters of the Locumba basin. Regarding observed droughts, SPI-3 and SPEI-3 detected seven extreme droughts (1983, 1992, 1996, 1998, 2010, 2011, and 2012), with the most intense occurring in 1992 and 1998. SPI-6 and SPEI-6 identified the same extreme drought events, highlighting 1992 as the most intense.
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22

Lézine, Anne-Marie, Maé Catrain, Julián Villamayor, and Myriam Khodri. "Using data and models to infer climate and environmental changes during the Little Ice Age in tropical West Africa." Climate of the Past 19, no. 1 (2023): 277–92. http://dx.doi.org/10.5194/cp-19-277-2023.

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Abstract. Here we present hydrological and vegetation paleo-data extracted from 28 sites in West Africa from 5∘ S to 19∘ N and the past1000/PMIP4 IPSL-CM6A-LR climate model simulations covering the 850–1850 CE period to document the environmental and climatic changes that occurred during the Little Ice Age (LIA). The comparison between paleo-data and model simulations shows a clear contrast between the area spanning the Sahel and the savannah in the north, characterized by widespread drought, and the equatorial sites in the south, where humid conditions prevailed. Particular attention was paid
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23

Andrade-Velázquez, Mercedes, and Martín José Montero-Martínez. "Historical and Projected Trends of the Mean Surface Temperature in South-Southeast Mexico Using ERA5 and CMIP6." Climate 11, no. 5 (2023): 111. http://dx.doi.org/10.3390/cli11050111.

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This study aimed to determine the mean temperature trends in the south-southeast region of Mexico during the historical period of 1980–2014, as well as during the future periods of 2021–2040, 2041–2060, and 2081–2100, as recommended by the IPCC. Additionally, the study sought to identify the climate change scenario that is most closely aligned with the socio-environmental conditions of the south-southeast zone of Mexico and that has the greatest impact on the region’s average temperature. The downscaling method of bias correction was conducted at a spatial resolution of 0.25° × 0.25°, and an a
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24

Flack, David L. A., Gwendal Rivière, Ionela Musat, et al. "Representation by two climate models of the dynamical and diabatic processes involved in the development of an explosively deepening cyclone during NAWDEX." Weather and Climate Dynamics 2, no. 1 (2021): 233–53. http://dx.doi.org/10.5194/wcd-2-233-2021.

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Abstract. The dynamical and microphysical properties of a well-observed cyclone from the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX), called the Stalactite cyclone and corresponding to intensive observation period 6, is examined using two atmospheric components (ARPEGE-Climat 6.3 and LMDZ6A) of the global climate models CNRM-CM6-1 and IPSL-CM6A, respectively. The hindcasts are performed in “weather forecast mode”, run at approximately 150–200 km (low resolution, LR) and approximately 50 km (high resolution, HR) grid spacings, and initialised during the initiation stage o
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25

Zanchettin, Davide, Claudia Timmreck, Myriam Khodri, et al. "Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment." Geoscientific Model Development 15, no. 5 (2022): 2265–92. http://dx.doi.org/10.5194/gmd-15-2265-2022.

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Abstract. This paper provides initial results from a multi-model ensemble analysis based on the volc-pinatubo-full experiment performed within the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The volc-pinatubo-full experiment is based on an ensemble of volcanic forcing-only climate simulations with the same volcanic aerosol dataset across the participating models (the 1991–1993 Pinatubo period from the CMIP6-GloSSAC dataset). The simulations are conducted within an idealized
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Dunkl, István, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin. "Gross primary productivity and the predictability of CO2: more uncertainty in what we predict than how well we predict it." Biogeosciences 20, no. 16 (2023): 3523–38. http://dx.doi.org/10.5194/bg-20-3523-2023.

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Abstract. The prediction of atmospheric CO2 concentrations is limited by the high interannual variability (IAV) in terrestrial gross primary productivity (GPP). However, there are large uncertainties in the drivers of GPP IAV among Earth system models (ESMs). Here, we evaluate the impact of these uncertainties on the predictability of atmospheric CO2 in six ESMs. We use regression analysis to determine the role of environmental drivers in (i) the patterns of GPP IAV and (ii) the predictability of GPP. There are large uncertainties in the spatial distribution of GPP IAV. Although all ESMs agree
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Ferreiro-Lera, Giovanni-Breogán, Ángel Penas, and Sara del Río. "Unveiling Deviations from IPCC Temperature Projections through Bayesian Downscaling and Assessment of CMIP6 General Circulation Models in a Climate-Vulnerable Region." Remote Sensing 16, no. 11 (2024): 1831. http://dx.doi.org/10.3390/rs16111831.

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The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, the proficiency of GCMs in replicating reanalyzed 1981–2010 temperature data sourced from the ERA5 Land was assessed. Initially, the least data-modifying interpolation method for achieving a resolution match of 0.1° was ascertained. Subsequently, a pixel-by-pixel evaluation was conducted, employing five goodness-of-fit metrics. From the
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Simon, Amélie, Guillaume Gastineau, Claude Frankignoul, Vladimir Lapin, and Pablo Ortega. "Pacific Decadal Oscillation modulates the Arctic sea-ice loss influence on the midlatitude atmospheric circulation in winter." Weather and Climate Dynamics 3, no. 3 (2022): 845–61. http://dx.doi.org/10.5194/wcd-3-845-2022.

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Abstract. The modulation of the winter impacts of Arctic sea-ice loss by the Pacific Decadal Oscillation (PDO) is investigated in the IPSL-CM6A-LR ocean–atmosphere general circulation model. Ensembles of simulations are performed with constrained sea-ice concentration following the Polar Amplification Model Intercomparison Project (PAMIP) and initial conditions sampling warm and cold phases of the PDO. Using a general linear model, we estimate the simulated winter impact of sea-ice loss, PDO and their combined effects. On the one hand, a negative North Atlantic Oscillation (NAO)-like pattern a
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Dufatanye Umwali, Edovia, Xi Chen, Brian Odhiambo Ayugi, et al. "Estimating the Effects of Climate Fluctuations on Precipitation and Temperature in East Africa." Atmosphere 15, no. 12 (2024): 1455. https://doi.org/10.3390/atmos15121455.

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This study evaluated the effectiveness of the NASA Earth Exchange Global Daily Downscaled models from CMIP6 experiments (hereafter; NEX-GDDP-CMIP6) in reproducing observed precipitation and temperature across East Africa (EA) from 1981 to 2014. Additionally, climate changes were estimated under various emission scenarios, namely low (SSP1-2.6), medium (SSP2-4.5), and high (SSP5-8.5) scenarios. Multiple robust statistics metrics, the Taylor diagram, and interannual variability skill (IVS) were employed to identify the best-performing models. Significant trends in future precipitation and temper
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Melnikova, Irina, Philippe Ciais, Katsumasa Tanaka, et al. "Carbon cycle and climate feedbacks under CO2 and non-CO2 overshoot pathways." Earth System Dynamics 16, no. 1 (2025): 257–73. https://doi.org/10.5194/esd-16-257-2025.

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Abstract. Reducing emissions of non-carbon dioxide (CO2) greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), complements CO2 mitigation in limiting global warming. However, estimating carbon–climate feedback for these gases remains fraught with uncertainties, especially under overshoot scenarios. This study investigates the impact of CO2 and non-CO2 gases with nearly equal levels of effective radiative forcing on the climate and carbon cycle, using the Earth system model (ESM) IPSL-CM6A-LR. We first present a method to recalibrate methane and nitrous oxide concentrations to
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Rivera, Paris, Eduardo Herrera, and Werner Ochoa. "Comparación de series mensuales de precipitación y temperaturas de los Modelos CMIP6 para Guatemala." Ciencia, Tecnologí­a y Salud 9, no. 2 (2022): 132–49. http://dx.doi.org/10.36829/63cts.v9i2.1285.

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Se comparan las métricas de 37 modelos climáticos globales (GCMs, por sus siglas en inglés) de la Fase 6 del Proyecto de Intercomparación de Modelos Acoplados (CMIP6) con el objetivo de simular el clima de Guatemala del periodo de 1971 al 2014. La temperatura y precipitación mensual fue comparada con los datos de observación de la Unidad De Investigación Climática de la Universidad del este de Anglia (CRU). Se generó un ranquin de modelos basado en la menor distancia entre tres dimisiones basado en tres métricas; Coeficiente de Correlación de Pearson (CCP), Error medio cuadrático (RMSE) y Desv
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32

Tian, Peizhi, Binyang Jian, Jianrui Li, Xitian Cai, Jiangfeng Wei, and Guo Zhang. "Land-Use-Change-Induced Cooling and Precipitation Reduction in China: Insights from CMIP6 Models." Sustainability 15, no. 16 (2023): 12191. http://dx.doi.org/10.3390/su151612191.

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In the 21st century, the effect of land use/land cover change (LULCC) on climate has become an area of active research. To explore the effects of LULCC on temperature and precipitation in China, we used outputs from the BCC-CSM2-MR, CESM2, IPSL-CM6A-LR, and UKESM1 models, which participated in the Land Use Model Intercomparison Project (LUMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on these models, we identified temporal variations in precipitation and near-surface air temperature (hereinafter temperature) with and without historical land use changes and their rela
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33

Zhao, Siyi, Jiankai Zhang, Chongyang Zhang, et al. "Evaluating Long-Term Variability of the Arctic Stratospheric Polar Vortex Simulated by CMIP6 Models." Remote Sensing 14, no. 19 (2022): 4701. http://dx.doi.org/10.3390/rs14194701.

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The Arctic stratospheric polar vortex is a key component of the climate system, which has significant impacts on surface temperatures in the mid-latitudes and polar regions. Therefore, understanding polar vortex variability is helpful for extended-range weather forecasting. The present study evaluates long-term changes in the position and strength of the polar vortex in the Arctic lower stratosphere during the winters from 1980/81 to 2013/14. Simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models are compared with Modern-Era Retrospective analysis for Research and Appl
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34

Li, Xiuping, Peiqing Xiao, Shilong Hao, and Zhihui Wang. "Rainfall Erosivity Characteristics during 1961–2100 in the Loess Plateau, China." Remote Sensing 16, no. 4 (2024): 661. http://dx.doi.org/10.3390/rs16040661.

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Rainfall erosivity, which signifies the inherent susceptibility of soil erosion induced by precipitation, plays a fundamental role in formulating a comprehensive soil loss equation (RUSLE). It stands as a crucial determinant among the foundational factors considered in a comprehensive soil loss equation’s establishment. Nonetheless, the prediction and quantification of future alterations in rainfall erosivity under the influence of global warming have been relatively limited. In this study, climate change was widely evaluated and 10 preferred global climate models in the Loess Plateau were sel
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35

Li, Hui, Hongxu Mu, Shengqi Jian, and Xinan Li. "Assessment of Rainfall and Temperature Trends in the Yellow River Basin, China from 2023 to 2100." Water 16, no. 10 (2024): 1441. http://dx.doi.org/10.3390/w16101441.

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China’s Yellow River Basin (YRB) is sensitive to climate change due to its delicate ecosystem and complex geography. Water scarcity, soil erosion, and desertification are major challenges. To mitigate the YRB’s ecological difficulties, climate change must be predicted. Based on the analysis of the evolution features of hydro-meteorological elements, the CMIP6 climate model dataset with Delta downscaling and the Empirical Orthogonal Function (EOF) is utilized to quantitatively explore the future variations in precipitation and temperature in the YRB. The following results are drawn: The spatial
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36

Silvy, Yona, Clément Rousset, Eric Guilyardi, et al. "A modeling framework to understand historical and projected ocean climate change in large coupled ensembles." Geoscientific Model Development 15, no. 20 (2022): 7683–713. http://dx.doi.org/10.5194/gmd-15-7683-2022.

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Abstract. The ocean responds to climate change through modifications of heat, freshwater and momentum fluxes at its boundaries. Disentangling the specific role of each of these contributors in shaping the changes of the thermohaline structure of the ocean is central for our process understanding of climate change and requires the design of specific numerical experiments. While it has been partly addressed by modeling studies using idealized CO2 forcings, the time evolution of these individual contributions during historical and projected climate change is however lacking. Here, we propose a no
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37

Prathom, Chotirose, and Paskorn Champrasert. "General Circulation Model Downscaling Using Interpolation—Machine Learning Model Combination—Case Study: Thailand." Sustainability 15, no. 12 (2023): 9668. http://dx.doi.org/10.3390/su15129668.

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Climate change, a global problem, is now impacting human life and nature in many sectors. To reduce the severity of the impacts, General Circulation Models (GCMs) are used for predicting future climate. The prediction output of a GCM requires a downscaling process to increase its spatial resolution before projecting on local area. In order to downscale the output to a higher spatial resolution (less than 20 km), a statistical method is typically considered. By using this method, a large amount of historical observed data, up to 30 years, is essential. In some areas, the historical data is insu
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38

Sicard, Marie, Masa Kageyama, Sylvie Charbit, Pascale Braconnot, and Jean-Baptiste Madeleine. "An energy budget approach to understand the Arctic warming during the Last Interglacial." Climate of the Past 18, no. 3 (2022): 607–29. http://dx.doi.org/10.5194/cp-18-607-2022.

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Abstract. The Last Interglacial period (129–116 ka) is characterised by a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the pre-industrial period. In particular, these changes amplify the seasonality of the insolation in the high latitudes of the Northern Hemisphere. Here, we investigate the Arctic climate response to this forcing by comparing the CMIP6 lig127k and piControl simulations performed with the IPSL-CM6A-LR (the global climate model developed at Institut Pierre-Simon Laplace) model. Using an energy budget framework,
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39

Liu, Tao, Zhenjiang Si, Yan Liu, Longfei Wang, Yusu Zhao, and Jing Wang. "Runoff and Drought Responses to Land Use Change and CMIP6 Climate Projections." Water 17, no. 11 (2025): 1696. https://doi.org/10.3390/w17111696.

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Climate and land use changes significantly affect runoff and hydrological drought, presenting challenges for water resource management. This study focuses on the Naoli River Basin, utilizing the SWAT model integrated with PLUS land use projections under the CMIP6 SSP245 and SSP585 scenarios to assess trends in runoff and drought characteristics from 2025 to 2100. The Standardized Runoff Index (SRI) and run theory are applied to analyze drought frequency and duration. Key findings include the following: (1) Under the SSP585 scenario (2061–2100), land use changes—specifically, a reduction in cro
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40

Yang, Mingjie, Lianqing Xue, Tao Lin, Peng Zhang, and Yuanhong Liu. "Assessing Extreme Precipitation in Northwest China’s Inland River Basin Under a Novel Low Radiative Forcing Scenario." Water 17, no. 13 (2025): 2009. https://doi.org/10.3390/w17132009.

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Accelerating climate change poses significant risks to water security and ecological stability in arid regions due to the increasing frequency and intensity of extreme precipitation events. As a climate-sensitive area, the inland river basin (IRB) of Northwest China—a critical water source for local ecosystems and socioeconomic activities—remains insufficiently studied in terms of future extreme precipitation dynamics. This study evaluated the spatiotemporal evolution of extreme precipitation in the IRB under a new low radiative forcing scenario (SSP1-1.9) by employing four global climate mode
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41

Beridze, Berika, Katarzyna Sękiewicz, Łukasz Walas, et al. "Niche modelling suggests low feasibility of assisted gene flow for a Neogene relict tree, Castanea sativa Mill." Dendrobiology 90 (October 11, 2023): 58–75. http://dx.doi.org/10.12657/denbio.090.005.

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Abstract: As many tree species populations are being degraded by climate change, adaptive conservation, and forest management, such as assisted gene flow (AGF), can provide the genetic variation needed to adapt to climate change. The core of this strategy is to assist the adaptation process in populations at risk of climate maladaptation by introducing individuals with beneficial alleles to cope with expected climate changes. Castanea sativa Mill. (sweet chestnut) is an essential component of natural forests in the Mediterranean and Caucasian regions, with a long history of cultivation. Curren
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42

Caillet, Justine, Nicolas C. Jourdain, Pierre Mathiot, et al. "Uncertainty in the projected Antarctic contribution to sea level due to internal climate variability." Earth System Dynamics 16, no. 1 (2025): 293–315. https://doi.org/10.5194/esd-16-293-2025.

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Abstract. Identifying and quantifying irreducible and reducible uncertainties in the Antarctic Ice Sheet (AIS) response to future climate change is essential for guiding mitigation and adaptation policy decision. However, the impact of the irreducible internal climate variability, resulting from processes intrinsic to the climate system, remains poorly understood and quantified. Here, we characterise both the atmospheric and oceanic internal climate variability in a selection of three Coupled Model Intercomparison Project Phase 6 (CMIP6) models (UKESM1-0-LL, IPSL-CM6A-LR, and MPI-ESM1.2-HR) an
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43

Li, Yan, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust. "Investigating the global and regional response of drought to idealized deforestation using multiple global climate models." Hydrology and Earth System Sciences 29, no. 6 (2025): 1637–58. https://doi.org/10.5194/hess-29-1637-2025.

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Abstract. Land use change, particularly deforestation, significantly influences the global climate system. While various studies have explored how deforestation affects temperature and precipitation, its impact on drought remains less explored. Understanding these effects across different climate zones and timescales is crucial for crafting effective land use policies aimed at mitigating climate change. This study investigates how changes in forest cover affect drought across different timescales and climate zones using simulated deforestation scenarios, where forests are converted to grasslan
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44

Li, Zhenjie, Hui Tao, Heike Hartmann, Buda Su, Yanjun Wang, and Tong Jiang. "Variation of Projected Atmospheric Water Vapor in Central Asia Using Multi-Models from CMIP6." Atmosphere 11, no. 9 (2020): 909. http://dx.doi.org/10.3390/atmos11090909.

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Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021–2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986–2005). Results showed that the annual mean TCWV from IGRA2 was c
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45

Mignot, Juliette, Frédéric Hourdin, Julie Deshayes, et al. "The Tuning Strategy of IPSL‐CM6A‐LR." Journal of Advances in Modeling Earth Systems 13, no. 5 (2021). http://dx.doi.org/10.1029/2020ms002340.

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46

Lézine, Anne-Marie, Maé Catrain, Julián Villamayor, and Myriam Khodri. "Using data and model to infer climate and environmental changes during the Little Ice Age in tropical West Africa." August 17, 2022. https://doi.org/10.5281/zenodo.7003853.

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Datasets and processed datasets of the&nbsp;publication &nbsp;&quot;Using data and model to infer climate and environmental changes during the Little Ice Age in tropical West Africa&quot;:&nbsp;IPSL-CM6A-LR model rainfall (pr)&nbsp;raw dataset for the past millennium (3 members) over the&nbsp;10&ordm;S-35&ordm;N and 50&ordm;W-50&ordm;E region, pre-processed IPSL-CM6A-LR model rainfall&nbsp;and&nbsp;pre-processed pollen and hydroclimate proxies datasets.
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47

Boucher, Olivier, Jérôme Servonnat, Anna Lea Albright, et al. "Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model." Journal of Advances in Modeling Earth Systems 12, no. 7 (2020). http://dx.doi.org/10.1029/2019ms002010.

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48

UZUN, Almira, and Ömer K. ÖRÜCÜ. "Modeling of potential distribution areas of Spartium junceum L. (Spanish broom) under the impact of global climate change." Ağaç ve Orman, December 11, 2023. http://dx.doi.org/10.59751/agacorman.1383004.

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İklimin canlılar üzerindeki yaşamsal etkileri ve bu etkilerin sebepleri yaşamın varlığı boyunca bilinmekte ve araştırılmaya devam etmektedir. İklim değişikliğinin bitkiler üzerinde de birçok farklı etkisi bulunmakta ve çoğu zaman da bu etkiler olumsuz sonuçlar doğurmaktadır. Bu çalışmada, parlak sarı çiçekleri ile dikkat çeken ve özellikle toprak tutma kabiliyeti olan Spartium junceum L.’nin günümüz yayılış alanı ve gelecekte iklim değişikliği etkisi altında potansiyel yayılış alanları MaxEnt algoritması ile modellenmiştir. Modelde, örnek noktalar ve biyoklimatik değişkenlerle birlikte IPSL CM
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49

Langehaug, Helene Reinertsen, Hanne Sagen, A. Stallemo, et al. "Constraining CMIP6 estimates of Arctic Ocean temperature and salinity in 2025-2055." Frontiers in Marine Science 10 (October 24, 2023). http://dx.doi.org/10.3389/fmars.2023.1211562.

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Global climate models (CMIP6 models) are the basis for future predictions and projections, but these models typically have large biases in their mean state of the Arctic Ocean. Considering a transect across the Arctic Ocean, with a focus on the depths between 100-700m, we show that the model spread for temperature and salinity anomalies increases significantly during the period 2025-2045. The maximum model spread is reached in the period 2045-2055 with a standard deviation 10 times higher than in 1993-2010. The CMIP6 models agree that there will be warming, but do not agree on the degree of wa
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50

CONSTRAIN, archive. "Journal Article: Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model." May 28, 2020. https://doi.org/10.1029/2019MS002010.

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Abstract: This study presents the global climate model IPSL‐CM6A‐LR developed at Institut Pierre‐Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from
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