Letteratura scientifica selezionata sul tema "IPSL-CM6A-LR"
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Articoli di riviste sul tema "IPSL-CM6A-LR":
1
Din, Salah Ud. "Flow prediction in Kabul River: An artificial intelligence based technique". International Journal of Multidisciplinary Research and Growth Evaluation 5, n. 2 (2024): 854–57. http://dx.doi.org/10.54660/.ijmrge.2024.5.2.854-857.
Abstract (sommario):
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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Andrade-Velázquez, Mercedes, e Martín José Montero-Martínez. "Statistical Downscaling of Precipitation in the South and Southeast of Mexico". Climate 11, n. 9 (8 settembre 2023): 186. http://dx.doi.org/10.3390/cli11090186.
Abstract (sommario):
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 informed by a methodical approach grounded in previous research conducted within the southern–southeastern region of Mexico. Diverse performance evaluation metrics were employed, including root-mean-square difference (rmsd), normalized standard deviation (NSD), bias, and Pearson’s correlation (illustrated by Taylor diagrams). The study area was divided into two distinct domains: southern Mexico and the southeast region covering Tabasco and Chiapas, and the Yucatan Peninsula. The findings underscored the substantial improvement in model performance achieved through bias correction across the entire study area. The outcomes of rmsd and NSD not only exhibited variations among different climate models but also manifested sensitivity to the specific geographical region under examination. In the southern region, CNRM-ESM2-1 emerged as the most adept model following bias correction. In the southeastern domain, including only Tabasco and Chiapas, the optimal model was again CNRM-ESM2-1 after bias-correction. However, for the Yucatan Peninsula, the IPSL-CM6A-LR model yielded the most favorable results. This study emphasizes the significance of tailored bias-correction techniques in refining the performance of climate models and highlights the spatially nuanced responses of different models within the study area’s distinct geographical regions.
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Poletti, Alyssa N., Dargan M. W. Frierson, Travis Aerenson, Akshaya Nikumbh, Rachel Carroll, William Henshaw e Jack Scheff. "Atmosphere and ocean energy transport in extreme warming scenarios". PLOS Climate 3, n. 2 (1 febbraio 2024): e0000343. http://dx.doi.org/10.1371/journal.pclm.0000343.
Abstract (sommario):
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 determination of moisture and energy transports, and their relation to global atmosphere-ocean circulation. Three models performed simulations of SSP5-8.5 to 2300: MRI-ESM2-0, IPSL-CM6A-LR, and CanESM5. We analyze these simulations to improve understanding of climate dynamics, rather than as plausible futures. In the model with the most warming, CanESM5, the moisture content of the planet more than doubles, and the hydrologic cycle increases in intensity. In CanESM5 and IPSL-CM6A-LR nearly all sea ice is eliminated in both summer and winter in both hemispheres. In all three models, the Hadley circulation weakens, the tropopause height rises, and storm tracks shift poleward, to varying degrees. We analyze the moist static energy transports in the simulations using a diffusive framework. The dry static energy flux decreases to compensate for the increased moisture transport; however the compensation is imperfect. The total atmospheric transport increases but not as quickly as expected with a constant diffusivity. The decrease in eddy intensity plays an important role in determining the energy transports, as do the pattern of cloud feedbacks and the strength of ocean circulations.
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Üyük, Ayyüce, e Ömer K. Örücü. "Platanus orientalis L. (Doğu Çınarı) günümüz ve gelecek yayılış alanlarının CanESM5ve IPSL-CM6A-LR iklim modellerine göre karşılaştırılması". Ecological Perspective 2, n. 1 (6 luglio 2022): 137–50. http://dx.doi.org/10.53463/ecopers.20220146.
Abstract (sommario):
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 etkilendiğini anlamak için Kanada Modeli olan CanESM5 İklim modeli kullanılarak SSP2 4.5 VE SSP5 8.5 senaryolarına ait 2041-2060 ve 2081-2100 dönemlerine ait potansiyel dağıtım alanları belirlenmiştir. Diğer taraftan türlere ait üretilen günümüz ve gelecekteki dağılım alanlarına ait değişim analizleri oluşturulmuştur. Elde edilen çalışmalara göre şimdiki zaman dağılım alanı için çok uygun ve uygun görülen alanlar 208.092 km2 olarak elde edilmiştir. Sonuç olarak Platanus orientalis L.’in dağılım alanlarının yıllara göre giderek azalacağı ileride ülkemizde türe rastlanmayacağı tahmin edilmektedir.
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Sarikaya, Ayse Gul, e Almira Uzun. "Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning". Sustainability 16, n. 3 (1 febbraio 2024): 1230. http://dx.doi.org/10.3390/su16031230.
Abstract (sommario):
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 also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Türkiye for the periods 2041–2060 and 2081–2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species’ future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of Türkiye, and the very suitable areas encompassed 45,413.82 km2. However, when the SSP2 4.5 scenario was considered for the period 2041–2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km2, and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km2 in the 2081–2100 period. Considering the SSP5 8.5 scenario for the period 2041–2060, the area most suitable for the B. vulgaris species is 66,670.39 km2. In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km2 in the 2081–2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris—that is, areas with ecological niche potential—have been determined.
6
Xiao, Heng, Yue Zhuo, Hong Sun, Kaiwen Pang e Zhijia An. "Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations". Atmosphere 14, n. 9 (12 settembre 2023): 1429. http://dx.doi.org/10.3390/atmos14091429.
Abstract (sommario):
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 Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities.
7
Raila, Shiva Nath, Raju Acharya, Sudan Ghimire, Subash Adhikari, Saroj Khanal, Yogendra Mishra e Manoj Lamichhane. "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, n. 01 (25 agosto 2022): 165–72. http://dx.doi.org/10.3126/jacem.v7i01.47342.
Abstract (sommario):
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 data. Performance indicators (NSE, PBAIS, and RSR) are computed by comparing bias-corrected historical data with observed historical data. We found that GCM models EC-Earth3, NorESM2-MM, GDFL-ESM4, and IPSL-CM6A-LR showed a higher rating for maximum and minimum temperature, and GCM models EC-Earth3, NorESM2-MM, GDFLESM4, and MPI-ESM2-MM showed a higher rating for precipitation. Among the different bias correction functions power Xo transformation and Power transformed functions, Bernoulli’s Weibull showed the best performance for minimum temperature), maximum temperature, and precipitation, respectively. These models and bias correction could be used to project the climate variables of the surrounding basins.
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Babaousmail, Hassen, Rongtao Hou, Brian Ayugi, Moses Ojara, Hamida Ngoma, Rizwan Karim, Adharsh Rajasekar e Victor Ongoma. "Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa". Atmosphere 12, n. 4 (9 aprile 2021): 475. http://dx.doi.org/10.3390/atmos12040475.
Abstract (sommario):
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 utilized to assess models’ performance in reproducing annual and seasonal and monthly rainfall over the study domain. Results show that CMIP6 models satisfactorily reproduce mean annual climatology of dry/wet months. However, some models show a slight over/under estimation across dry/wet months. The models’ overall top ranking from all the performance analyses ranging from mean cycle simulation, trend analysis, inter-annual variability, ECDFs, and statistical metrics are as follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, and GFDL-ESM4. The mean model ensemble outperformed the individual CMIP6 models resulting in a TSS ratio (0.79). For future impact studies over the study domain, it is advisable to employ the multi-model ensemble of the best performing models.
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Smith, Christopher J., Ryan J. Kramer e Adriana Sima. "The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere". Earth System Science Data 12, n. 3 (13 settembre 2020): 2157–68. http://dx.doi.org/10.5194/essd-12-2157-2020.
Abstract (sommario):
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 to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).
10
Ragab, Sanad H., e Michael G. Tyshenko. "Predicting the potential worldwide distribution of Aedes aegypti under climate change scenarios". International Journal of Scientific Reports 9, n. 11 (23 ottobre 2023): 344–52. http://dx.doi.org/10.18203/issn.2454-2156.intjscirep20233163.
Abstract (sommario):
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 climate conditions. Methods: Data of Ae. aegypti was obtained from the global biodiversity information facility and used 19 bioclimatic layers (bio01-bio19) and elevation from the WorldClim database. The scenarios used are the Beijing climate center climate system model (BCC-CSM2-MR) and the institute Pierre-Simon Laplace, coupled model intercomparison project (IPSL-CM6A-LR) with two shared socio-economic pathways (SSPs) for each of the general circulation model (GCMs): SSP126 and SSP585. Results: The results revealed that altitude, temperature, seasonality (standard deviation *100) (bio4), and annual precipitation (bio12) were the most important environmental variables that affect the distribution of Ae. aegypti. Conclusions: The models showed that Africa and South America maintained very high and excellent habitat suitability for Ae. Aegypti under the current potential distribution map.
Tesi sul tema "IPSL-CM6A-LR":
1
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.
Abstract (sommario):
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 loin pour décrypter le mécanisme concernant différentes composantes radiatives du forçage volcanique (le refroidissement de la surface et le réchauffement du stratosphère). Le travail est axé sur trois 25-membres ensembles de simulation par IPSL-CM6A-LR suivant le protocole VolMIP sur l'éruption tropicale Mt. Pinatubo (Philippines, juin 1991), la meilleure observée. Les expériences de sensibilité indiquent que la signature d’ONA positive de surface dans nos expériences de modèle est principalement attribuée au réchauffement dans la basse stratosphère tropicale qui génère des vents zonaux subtropicaux plus forts à travers le bilan de vent thermique et accélère le vortex polaire. Les propagations d'ondes planétaires stationnaires jouent également des effets de modulations indispensablesThe PhD work aims at studying the role of volcanism in influencing winter climate variability (especially, NAO) over the North Atlantic-Mediterranean sector at inter-annual scale. The first part is devoted to characterizing the simulated NAO signal in winters following stratospheric volcanic eruptions using three long transient simulations of the past millennium (500-1849 CE) by IPSL-CM6A-LR in the frame of PMIP4. The robustness and sensitivity of the response related to the latitude, season and strength of the eruptions are also explored. The second part extends further to decrypt the physical mechanism regarding different components of volcanic radiative forcing (the surface cooling and stratospheric warming). The work focuses on three 25-members ensemble simulations by IPSL-CM6A-LR following the VolMIP protocol for the well observed Mt. Pinatubo tropical eruption (Philippines, June 1991). Sensitivity experiments indicate that the surface positive NAO signature in our model experiments is primarily attributable to heating in the lower tropical stratosphere which generates stronger subtropical zonal winds through the thermal wind balance and accelerates the polar vortex. Stationary planetary wave propagations are also playing indispensable modulations effects