Academic literature on the topic 'Simulations CMIP6'
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Journal articles on the topic "Simulations CMIP6":
Wang, Dong, Jiahong Liu, Weiwei Shao, Chao Mei, Xin Su, and Hao Wang. "Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin." Atmosphere 12, no. 7 (July 3, 2021): 867. http://dx.doi.org/10.3390/atmos12070867.
Hamed, Mohammed Magdy, Mohamed Salem Nashwan, Mohammed Sanusi Shiru, and Shamsuddin Shahid. "Comparison between CMIP5 and CMIP6 Models over MENA Region Using Historical Simulations and Future Projections." Sustainability 14, no. 16 (August 20, 2022): 10375. http://dx.doi.org/10.3390/su141610375.
Brierley, Chris M., Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, et al. "Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations." Climate of the Past 16, no. 5 (October 1, 2020): 1847–72. http://dx.doi.org/10.5194/cp-16-1847-2020.
Matthes, Katja, Bernd Funke, Monika E. Andersson, Luke Barnard, Jürg Beer, Paul Charbonneau, Mark A. Clilverd, et al. "Solar forcing for CMIP6 (v3.2)." Geoscientific Model Development 10, no. 6 (June 22, 2017): 2247–302. http://dx.doi.org/10.5194/gmd-10-2247-2017.
Fyfe, John C., Viatcheslav V. Kharin, Benjamin D. Santer, Jason N. S. Cole, and Nathan P. Gillett. "Significant impact of forcing uncertainty in a large ensemble of climate model simulations." Proceedings of the National Academy of Sciences 118, no. 23 (June 1, 2021): e2016549118. http://dx.doi.org/10.1073/pnas.2016549118.
Eyring, Veronika, Sandrine Bony, Gerald A. Meehl, Catherine A. Senior, Bjorn Stevens, Ronald J. Stouffer, and Karl E. Taylor. "Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization." Geoscientific Model Development 9, no. 5 (May 26, 2016): 1937–58. http://dx.doi.org/10.5194/gmd-9-1937-2016.
Cos, Josep, Francisco Doblas-Reyes, Martin Jury, Raül Marcos, Pierre-Antoine Bretonnière, and Margarida Samsó. "The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections." Earth System Dynamics 13, no. 1 (February 8, 2022): 321–40. http://dx.doi.org/10.5194/esd-13-321-2022.
Almazroui, Mansour, M. Nazrul Islam, Sajjad Saeed, Fahad Saeed, and Muhammad Ismail. "Future Changes in Climate over the Arabian Peninsula based on CMIP6 Multimodel Simulations." Earth Systems and Environment 4, no. 4 (November 11, 2020): 611–30. http://dx.doi.org/10.1007/s41748-020-00183-5.
Merrifield, Anna L., Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti. "Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications." Geoscientific Model Development 16, no. 16 (August 23, 2023): 4715–47. http://dx.doi.org/10.5194/gmd-16-4715-2023.
Dong, Yue, Kyle C. Armour, Mark D. Zelinka, Cristian Proistosescu, David S. Battisti, Chen Zhou, and Timothy Andrews. "Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models." Journal of Climate 33, no. 18 (September 15, 2020): 7755–75. http://dx.doi.org/10.1175/jcli-d-19-1011.1.
Dissertations / Theses on the topic "Simulations CMIP6":
Ouhechou, Amine. "Analyse de la variabilité multi-échelles du rayonnement solaire incident sur la façade atlantique de l'Afrique Centrale : observations in-situ, estimations satellitaires, et simulations climatiques CMIP6." Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALU007.
Western Central Africa, home to the densest forests of the Congo Basin - the second largest tropical forest massif after Amazonia - is characterized by an equatorial climate with high temperatures, a bimodal rainfall pattern and, a long and cloudy dry season from June to September. Despite its ecological importance, the climate variability of this region has been less studied compared with other parts of the African continent, mainly because of the scarcity of in-situ observations.Recognizing these challenges posed by the lack of in-situ data, this study explores the climate variability in Western Central Africa through the lens of surface solar radiation, a key parameter for the functioning of tropical forests. In this context, this thesis aims to establish an initial climatology of surface solar radiation for the region, to document its variability, particularly during the cloudy dry season from June to September, and to assess the performance of satellite products, reanalyses and CMIP6 climate model simulations.In the first part, an evaluation of eight satellite products for estimating solar radiation (CERES-EBAF, CERES-SYN1deg, TPDC, CMSAF SARAH-2, CMSAF CLARA-A2, CAMS-JADE, WorldClim 2 and ERA5 reanalysis) reveals differences in the spatiotemporal fields. While successfully capturing mean annual solar radiation cycles, the products show regional variations, highlighting the impact of atmospheric parameters on the accurate estimation of solar radiation. In addition, all the products except WorldClim 2 agree that the Atlantic coast receives less solar radiation than the other regions of Central Africa. The performance of these products is also assessed against in-situ measurements based on four types of solar radiation diurnal cycle - Obscure, Obscure AM (morning), Obscure PM (afternoon) and Bright days. The products correctly represent the shape of these four types, but with a larger amplitude.The second part focuses on studying the interannual variability and trends in solar radiation during the June-September cloudy dry season, highlighting notable differences between CMSAF SARAH-2 satellite product and ERA5 reanalysis. The study also made it possible to identify the onset and cessation dates of the dry season based on solar radiation, and establishing a significant relationship between surface temperatures of the equatorial Atlantic ocean and the onset of the dry season.In the final part, the capacity of CMIP6 global climate models to reproduce average levels of solar radiation in the region was assessed. The results highlight sub-regional disparities in model performance. The models used in this study underestimate solar radiation in the south-west of Gabon-Congo, while they overestimate it in the north-east, mainly from april to december. The largest differences were observed during the october-november rainy season. These disparities seem to be caused by cloud cover, in particular low- and medium-level clouds, which have a significant influence on solar radiation, although the relationship varies according to the models. This section also highlights the teleconnection between the surface temperature of the equatorial Atlantic ocean and solar radiation in the models, which varies between the coastal and inland areas of Gabon, underlining the need to use regional climate models
Monerie, Paul-Arthur. "Le changement climatique en région de mousson africaine : évolution des champs pluviométriques et atmosphériques dans les simulations CMIP3 et CMIP5 sous scénario A1B et rcp45 (1960-1999, 2031-2070)." Phd thesis, Université de Bourgogne, 2013. http://tel.archives-ouvertes.fr/tel-00955371.
Mitchell, D. M., S. Misios, L. J. Gray, K. Tourpali, K. Matthes, L. Hood, H. Schmidt, et al. "Solar signals in CMIP-5 simulations: the stratospheric pathway." Royal Meteorological Society, 2015. http://hdl.handle.net/10150/623311.
Parsons, Luke A., Garrison R. Loope, Jonathan T. Overpeck, Toby R. Ault, Ronald Stouffer, and Julia E. Cole. "Temperature and Precipitation Variance in CMIP5 Simulations and Paleoclimate Records of the Last Millennium." AMER METEOROLOGICAL SOC, 2017. http://hdl.handle.net/10150/626270.
Sumi, Selina Jahan. "Eco-Hydrology Driven Evaluation of Statistically Downscaled Precipitation CMIP5 Climate Model Simulations over Louisiana." Thesis, University of Louisiana at Lafayette, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1594512.
Statistically downscaled CMIP5 precipitation data are available at higher spatial resolution compared to global climate models. The downscaled climate models have been used in many hydrological applications. However, limited numbers of studies focused on downscaled CMIP5 precipitation data for Louisiana. Statistically downscaled precipitation data for Louisiana is critically needed for various water resources engineering, planning and design purposes. This study has focused on assessing the skill of CMIP5 climate models in reproducing observed precipitation of Louisiana and application of CMIP5 precipitation data to analyze the impact of precipitation on hydrology (salinity and water level). Assessment of CMIP5 precipitation showed that statistically downscaled and bias corrected precipitation data reproduce observed average annual precipitation. But for other statistics (standard deviation), model data are not the same as observation data. The bias correction procedure ensured that models would reproduce the observed average precipitation. The maps of correlation distance for the models do not match with that of observation. This may be an indication that bias correction does not force the model to perform better in all statistics except annual average. Based on the analysis over climate divisions, it can be stated that spatial and temporal aggregation enables the models to perform better than gridded dataset. Application of CMIP5 precipitation data indicates that precipitation has a significant effect on salinity and almost zero effect on water level. Different salinity variables control the hydrologic and habitat suitability indices in coastal Louisiana. The cell-based analysis shows that different variables have different degrees of effect on vegetation and species (brown shrimp and oyster). Some species thrive in a high salinity environment while some others in low salinity. The uncertainty in the salinity and water level may occur due to insufficient data and boundary conditions provided in the Eco-hydrology model environment.
Santolaria, Otín María. "Le rôle de la couverture de neige de l'Arctique dans le cycle hydrologique de hautes latitudes révélé par les simulations des modèles climatiques." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAU027/document.
Snow is a critical component of the Arctic climate system. Over Northern Eurasia and North America the duration of snow cover is 7 to 10 months per year and a maximum snow extension is over 40% of the Northern Hemisphere land each year. Snow affects a variety of high latitude climate processes and feedbacks. High reflectivity of snow and low thermal conductivity have a cooling effect and modulates the snow-albedo feedback. A contribution from terrestrial snow to the Earth’s radiation budget at the top of the atmosphere is close to that from the sea ice. Snow also prevents large energy losses from the underlying soil and notably the ice growth and the development of seasonal permafrost. Being a natural water storage, snow plays a critical role in high latitude hydrological cycle, including evaporation and run-off. Snow is also one of the most variable components of climate system. With the Arctic warming twice as fast as the globe, the present and future variability of snow characteristics are crucially important for better understanding of the processes and changes undergoing with climate. However, our capacity to observe the terrestrial Arctic is limited compared to the mid-latitudes and climate models play very important role in our ability to understand the snow-related processes especially in the context of a warming cryosphere. In this respect representation of snow-associated feedbacks in climate models, especially during the shoulder seasons (when Arctic snow cover exhibits the strongest variability) is of a special interest.The focus of this study is on the representation of the Arctic terrestrial snow in global circulation models from Coupled Model Intercomparison Project (CMIP5) ensemble during the melting (March-April) and the onset (October-November) season for the period from 1979 to 2005. Snow characteristics from the general circulation models have been validated against in situ snow measurements, different satellite-based products and reanalyses.We found that snow characteristics in models have stronger bias in spring than in autumn. The annual cycle of snow cover is well captured by models in comparison with observations, however, the annual cycles of snow water equivalent and snow depth are largely overestimated by models, especially in North America. There is better agreement between models and observations in the snow margin position in spring rather than in autumn. Magnitudes of interannual variability for all snow characteristics are significantly underestimated in most CMIP5 models compared to observations. For both seasons, trends of snow characteristics in models are primarily negative but weaker and less significant than those from observations. The patterns of snow cover trends are relatively well reproduced in models, however, the spatial distribution of trends for snow water equivalent and snow depth display strong regional heterogeneities.Finally, we have concluded CMIP5 general circulation models provides valuable information about the snow characteristics in the terrestrial Arctic, however, they have still limitations. There is a lack of agreement among the ensemble of models in the spatial distribution of snow compared to the observations and reanalysis. And these discrepancies are accentuated in regions where variability of snow is higher in areas with complex terrain such as Canada and Alaska and during the melting and the onset season. Our goal in this study was to identify where and when these models are or are not reproducing the real snow characteristics in the Arctic, thus we hope that our results should be considered when using these snow-related variables from CMIP5 historical output in future climate studies
Chavaillaz, Yann. "La vitesse du changement climatique et ses implications sur la perception des générations futures." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLV021/document.
In most climate studies, climate change is approached by focusing on the evolution between a fixed current baseline and a future period, emphasizing stronger warming as we move further over the 21st century. Under climate conditions that are continuously evolving, human and natural systems might have to constantly adapt to a changing climate. This thesis proposes an alternative approach to climate projections. Here, I consider and analyze indicators of the pace of changes relative to temperature, precipitation and vegetation in order to be relevant for both urban and rural populations. An ensemble of CMIP5 simulations from 18 climate models is selected. The pace is represented by differences between two subsequent 20-year periods. Considering the pace of change would be beneficial for climate impacts and adaptation analyses.The models predict that the warming rate strongly increases without any mitigation policies (RCP8.5 scenario). It is twice as high by the end of the century compared to the current period, and even three times higher in some regions. Significant shifts in temperature distributions between two subsequent 20-year periods are projected to involve almost half of all land surfaces and most tropical areas by 2060 onwards (i.e. at least four times as many regions than currently). In these regions, an extremely warm year with a return period of about 50 years would become quite common only 20 years later. The fraction of the world population exposed to such shifts might reach about 60% (6 billion people, i.e. seven times more than currently). Low mitigation measures (RCP6.0) allow the warming rate to be kept at current values, and reduce the fraction of the world population exposed to significant shifts of temperature distributions by one third.Under RCP8.5, rainfall moistening and drying rates both increase by 30-40% above current levels. As we move further over the century, their patterns become geographically stationary and the trends become persistent. The stabilization of the geographical rate patterns that occurs despite the acceleration of global warming can be physically explained: it results from the increasing contribution of thermodynamic processes compared to dynamic processes in the control of precipitation change. The combination of intensification and increasing persistence of precipitation rate patterns may affect the way human societies and ecosystems adapt to climate change, especially in the Mediterranean basin, Central America, South Asia and the Arctic. Such an evolution in precipitation has already become noticeable over the last few decades, but it could be reversed if strong mitigation policies were quickly implemented (RCP2.6).Changes in vegetation could be visual landmarks of climate change. In mid- and high-latitudes of the Northern Hemisphere, the phenology of grass and trees follows the warming rate. Without any mitigation policies, the start of spring occurs earlier, and its duration is extended faster as we move over the century. The vegetation cover becomes denser, regardless of the selected pathway, in proportion to the temperature rise. The seasonal cycle of mid-latitude crops also depends on the temperature, and the seasonal cycle of tropical crops directly follows the features of the wet season. In all other latitudes, no robust evolution of the seasonal cycle is projected. The pace of change of vegetation cover since 1880 already doubled before 1950, mainly due to a strong change in land use. This pace is then projected to be stable over the entire 21st century if the vegetation dynamically interacts with the climate system in the models. This corresponds to a reduction of land-use change and to the acceleration of changes of vegetation cover under climate change
Dars, Ghulam Hussain. "Climate Change Impacts on Precipitation Extremes over the Columbia River Basin Based on Downscaled CMIP5 Climate Scenarios." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/979.
Chavaillaz, Yann. "La vitesse du changement climatique et ses implications sur la perception des générations futures." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLV021.
In most climate studies, climate change is approached by focusing on the evolution between a fixed current baseline and a future period, emphasizing stronger warming as we move further over the 21st century. Under climate conditions that are continuously evolving, human and natural systems might have to constantly adapt to a changing climate. This thesis proposes an alternative approach to climate projections. Here, I consider and analyze indicators of the pace of changes relative to temperature, precipitation and vegetation in order to be relevant for both urban and rural populations. An ensemble of CMIP5 simulations from 18 climate models is selected. The pace is represented by differences between two subsequent 20-year periods. Considering the pace of change would be beneficial for climate impacts and adaptation analyses.The models predict that the warming rate strongly increases without any mitigation policies (RCP8.5 scenario). It is twice as high by the end of the century compared to the current period, and even three times higher in some regions. Significant shifts in temperature distributions between two subsequent 20-year periods are projected to involve almost half of all land surfaces and most tropical areas by 2060 onwards (i.e. at least four times as many regions than currently). In these regions, an extremely warm year with a return period of about 50 years would become quite common only 20 years later. The fraction of the world population exposed to such shifts might reach about 60% (6 billion people, i.e. seven times more than currently). Low mitigation measures (RCP6.0) allow the warming rate to be kept at current values, and reduce the fraction of the world population exposed to significant shifts of temperature distributions by one third.Under RCP8.5, rainfall moistening and drying rates both increase by 30-40% above current levels. As we move further over the century, their patterns become geographically stationary and the trends become persistent. The stabilization of the geographical rate patterns that occurs despite the acceleration of global warming can be physically explained: it results from the increasing contribution of thermodynamic processes compared to dynamic processes in the control of precipitation change. The combination of intensification and increasing persistence of precipitation rate patterns may affect the way human societies and ecosystems adapt to climate change, especially in the Mediterranean basin, Central America, South Asia and the Arctic. Such an evolution in precipitation has already become noticeable over the last few decades, but it could be reversed if strong mitigation policies were quickly implemented (RCP2.6).Changes in vegetation could be visual landmarks of climate change. In mid- and high-latitudes of the Northern Hemisphere, the phenology of grass and trees follows the warming rate. Without any mitigation policies, the start of spring occurs earlier, and its duration is extended faster as we move over the century. The vegetation cover becomes denser, regardless of the selected pathway, in proportion to the temperature rise. The seasonal cycle of mid-latitude crops also depends on the temperature, and the seasonal cycle of tropical crops directly follows the features of the wet season. In all other latitudes, no robust evolution of the seasonal cycle is projected. The pace of change of vegetation cover since 1880 already doubled before 1950, mainly due to a strong change in land use. This pace is then projected to be stable over the entire 21st century if the vegetation dynamically interacts with the climate system in the models. This corresponds to a reduction of land-use change and to the acceleration of changes of vegetation cover under climate change
Peings, Yannick. "Influence de la couverture de neige de l'hémisphère nord sur la variabilité interannuelle du climat." Phd thesis, Université Paul Sabatier - Toulouse III, 2010. http://tel.archives-ouvertes.fr/tel-00562496.
Book chapters on the topic "Simulations CMIP6":
Doumbia, Boubacar, Elijah Adefisan, Jerome Omotosho, Boris Thies, and Joerg Bendix. "Evaluation of CMIP5 and CMIP6 Performance in Simulating West African Precipitation." In Digital Technologies and Applications, 84–96. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-29857-8_9.
Dong, Wenjie, Fumin Ren, Jianbin Huang, and Yan Guo. "Climate Change Simulation and Projection Based on CMIP5." In The Atlas of Climate Change: Based on SEAP-CMIP5, 7–142. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31773-6_2.
Zhang, Jing, Jeremy Krieger, Uma Bhatt, Chuhan Lu, and Xiangdong Zhang. "Alaskan Regional Climate Changes in Dynamically Downscaled CMIP5 Simulations." In Proceedings of the 2013 National Conference on Advances in Environmental Science and Technology, 47–60. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-19923-8_5.
Adigun, Paul, Koji Dairaku, and Precious Ebiendele. "Aerosol Forcing Dominating Late-Summer Precipitation Change Over East Asia's Transitional Climatic Zone in CMIP6 Model Simulation." In Advances in Science, Technology & Innovation, 245–50. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47079-0_55.
Shkolnik, Igor M. "Climate in the Late Twentieth and Twenty-First Centuries over the Northern Eurasia: RCM and CMIP3 Simulations." In Regional Aspects of Climate-Terrestrial-Hydrologic Interactions in Non-boreal Eastern Europe, 47–54. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2283-7_6.
Bachelet, D., T. Sheehan, K. Ferschweiler, and J. Abatzoglou. "Simulating Vegetation Change, Carbon Cycling, and Fire Over the Western United States Using CMIP5 Climate Projections." In Natural Hazard Uncertainty Assessment, 257–75. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119028116.ch17.
Modou Noreyni Fall, Cheikh, Adama Faye, Mbaye Diop, Babacar Faye, and Amadou Thierno Gaye. "Evolution of Agroclimatic Indicators in Senegal Using CMIP6 Simulations." In Natural Hazards - New Insights. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.109895.
Conference papers on the topic "Simulations CMIP6":
Holtanová, Eva, and Tomáš Halenka. "Assessment of uncertainty of the PERUN climate change scenarios." In První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.04.
Chatzopoulou, Anthi, Kleareti Tourpali, and Alkiviadis Bais. "Projections of biologically weighted solar irradiance doses based on simulations of CMIP6 models." In RADIATION PROCESSES IN THE ATMOSPHERE AND OCEAN. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0183113.
"Evaluating downscaled CMIP5 and CMIP6 for rainfall erosivity projections." In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.bulovic428.
Logothetis, Ioannis, Kleareti Tourpali, and Dimitrios Melas. "Projected Changes in Etesians Regime over Eastern Mediterranean in CMIP6 Simulations According to SSP2-4.5 and SSP5-8.5 Scenarios." In ECAS 2023. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/ecas2023-15129.
"CMIP6 projections indicate more erosive events across Australia." In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.zhu596.
Xu, Min, and Forrest Hoffman. "Evaluations of CMIP5 simulations over cropland." In SPIE Optical Engineering + Applications, edited by Wei Gao, Ni-Bin Chang, and Jinnian Wang. SPIE, 2015. http://dx.doi.org/10.1117/12.2192586.
Asplin, Matthew, Ed Ross, David Fissel, Peter Willis, Dawn Sadowy, Randy Kerr, Dave Billenness, Keath Borg, and Todd Mudge. "The Canada Coastal Zone Information System for Model-Based Projections of Future Metocean Parameters from Coupled Atmosphere-Ocean Models Under Different Greenhouse Gas Emission Scenarios for Offshore Marine Energy Development in Canada." In Offshore Technology Conference. OTC, 2024. http://dx.doi.org/10.4043/35435-ms.
Hayden, Lindsey, and Zaitao Pan. "ISCCP cloud based verification of CMIP5 climate simulations." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729140.
"A snapshot of climate change impacts for Queensland and regions using high-resolution downscaled CMIP6 projections." In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.toombs.
"CMIP5 climate change projections for hydrological modelling in South Asia." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.l13.zheng.
Reports on the topic "Simulations CMIP6":
Sathyanadh, Anusha, and Helene Muri. Open access dataset of ESM simulations of combined land- and ocean-based NETs. OceanNets, 2024. http://dx.doi.org/10.3289/oceannets_d4.7.
Ruosteenoja, Kimmo. Applicability of CMIP6 models for building climate projections for northern Europe. Finnish Meteorological Institute, September 2021. http://dx.doi.org/10.35614/isbn.9789523361416.
Hinrichs, Claudia, and Judith Hauck. Report on skill of CMIP6 models to simulate alkalinity and improved parameterizations for large scale alkalinity distribution. OceanNets, June 2022. http://dx.doi.org/10.3289/oceannets_d4.4.
Chervenkov, Hristo, and Kiril Slavov. Historical Climate Assessment of Temperature-based ETCCDI Climate Indices Derived from CMIP5 Simulations. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, June 2020. http://dx.doi.org/10.7546/crabs.2020.06.05.
Chervenkov, Hristo, and Kiril Slavov. Historical Climate Assessment of Precipitation-based ETCCDI Climate Indices Derived from CMIP5 Simulations. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, July 2020. http://dx.doi.org/10.7546/crabs.2020.07.06.
Huang, Huei-Ping. Final Report for "Interdecadal climate regime transition and its interaction with climate change in CMIP5 simulations" (DOE Grant DE-SC0005344). Office of Scientific and Technical Information (OSTI), December 2013. http://dx.doi.org/10.2172/1109482.