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Статті в журналах з теми "CMIP6 simulations":
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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.
Анотація:
Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled according to a multi-site statistical downscaling method for the Hanjiang River Basin (HRB), China. Downscaled precipitation accuracy was assessed using data collected from 14 meteorological stations in the HRB. The spatial performances, temporal performances, and seasonal variations of the downscaled CMIP5-MME and CMIP6-MME were evaluated and compared with observed data from 1970–2005. We found that the multi-site downscaling method accurately downscaled the CMIP5-MME and CMIP6-MME precipitation simulations. The downscaled precipitation of CMIP5-MME and CMIP6-MME captured the spatial pattern, temporal pattern, and seasonal variations; however, precipitation was slightly overestimated in the western and central HRB and precipitation was underestimated in the eastern HRB. The precipitation simulation ability of the downscaled CMIP6-MME relative to the downscaled CMIP5-MME improved because of reduced biases. The downscaled CMIP6-MME better simulated precipitation for most stations compared to the downscaled CMIP5-MME in all seasons except for summer. Both the downscaled CMIP5-MME and CMIP6-MME exhibit poor performance in simulating rainy days in the HRB.
2
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.
Анотація:
The study evaluated the ability of 11 global climate models of the latest two versions of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) to simulate observed (1965–2005) rainfall, maximum (Tmax) and minimum (Tmin) temperatures, mean eastward (uas) and northward (vas) wind speed, and mean surface pressure. It also evaluated relative uncertainty in projections of climate variables using those two CMIPs. The European reanalysis (ERA5) data were used as the reference to evaluate the performance of the GCMs and their mean and median multimodel ensembles (MME). The study revealed less bias in CMIP6 GCMs than CMIP5 GCMs in simulating most climate variables. The biases in rainfall, Tmax, Tmin, uas, vas, and surface pressure were −55 mm, 0.28 °C, −0.11 °C, −0.25 m/s, −0.06 m/s, and −0.038 Kpa for CMIP6 compared to −65 mm, 0.07 °C, −0.87 °C, −0.41 m/s, −0.05 m/s, and 0.063 Kpa for CMIP5. The uncertainty in CMIP6 projections of rainfall, Tmax, Tmin, uas, vas, and wind speed was relative more narrow than those for CMIP5. The projections showed a higher increase in Tmin than Tmax by 0.64 °C, especially in the central region. Besides, rainfall in most parts of MENA would increase; however, it might decrease by 50 mm in the coastal regions. The study revealed the better ability of CMIP6 GCMs for a wide range of climatic studies.
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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.
Анотація:
Abstract. The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.
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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.
Анотація:
Abstract. This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and future (2015–2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder-minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical one (NRLTSI2–NRLSSI2) and a semi-empirical one (SATIRE). A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m−2. The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m−2. In the 200–400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %).We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using time-slice experiments of two chemistry–climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day−1 at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day−1 at the stratopause), temperatures ( ∼ 1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset.CMIP6 models with a well-resolved shortwave radiation scheme are encouraged to prescribe SSI changes and include solar-induced stratospheric ozone variations, in order to better represent solar climate variability compared to models that only prescribe TSI and/or exclude the solar-ozone response. We show that monthly-mean solar-induced ozone variations are implicitly included in the SPARC/CCMI CMIP6 Ozone Database for historical simulations, which is derived from transient chemistry–climate model simulations and has been developed for climate models that do not calculate ozone interactively. CMIP6 models without chemistry that perform a preindustrial control simulation with time-varying solar forcing will need to use a modified version of the SPARC/CCMI Ozone Database that includes solar variability. CMIP6 models with interactive chemistry are also encouraged to use the particle forcing datasets, which will allow the potential long-term effects of particles to be addressed for the first time. The consideration of particle forcing has been shown to significantly improve the representation of reactive nitrogen and ozone variability in the polar middle atmosphere, eventually resulting in further improvements in the representation of solar climate variability in global models.
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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.
Анотація:
Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.
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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.
Анотація:
Abstract. By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.
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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.
Анотація:
Abstract. The enhanced warming trend and precipitation decline in the Mediterranean region make it a climate change hotspot. We compare projections of multiple Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) historical and future scenario simulations to quantify the impacts of the already changing climate in the region. In particular, we investigate changes in temperature and precipitation during the 21st century following scenarios RCP2.6, RCP4.5 and RCP8.5 for CMIP5 and SSP1-2.6, SSP2-4.5 and SSP5-8.5 from CMIP6, as well as for the HighResMIP high-resolution experiments. A model weighting scheme is applied to obtain constrained estimates of projected changes, which accounts for historical model performance and inter-independence in the multi-model ensembles, using an observational ensemble as reference. Results indicate a robust and significant warming over the Mediterranean region during the 21st century over all seasons, ensembles and experiments. The temperature changes vary between CMIPs, CMIP6 being the ensemble that projects a stronger warming. The Mediterranean amplified warming with respect to the global mean is mainly found during summer. The projected Mediterranean warming during the summer season can span from 1.83 to 8.49 ∘C in CMIP6 and 1.22 to 6.63 ∘C in CMIP5 considering three different scenarios and the 50 % of inter-model spread by the end of the century. Contrarily to temperature projections, precipitation changes show greater uncertainties and spatial heterogeneity. However, a robust and significant precipitation decline is projected over large parts of the region during summer by the end of the century and for the high emission scenario (−49 % to −16 % in CMIP6 and −47 % to −22 % in CMIP5). While there is less disagreement in projected precipitation than in temperature between CMIP5 and CMIP6, the latter shows larger precipitation declines in some regions. Results obtained from the model weighting scheme indicate larger warming trends in CMIP5 and a weaker warming trend in CMIP6, thereby reducing the difference between the multi-model ensemble means from 1.32 ∘C before weighting to 0.68 ∘C after weighting.
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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.
Анотація:
AbstractThis paper presents the changes in projected temperature and precipitation over the Arabian Peninsula for the twenty-first century using the Coupled Model Intercomparison Project phase 6 (CMIP6) dataset. The changes are obtained by analyzing the multimodel ensemble from 31 CMIP6 models for the near (2030–2059) and far (2070–2099) future periods, with reference to the base period 1981–2010, under three future Shared Socioeconomic Pathways (SSPs). Observations show that the annual temperature is rising at the rate of 0.63 ˚C decade–1 (significant at the 99% confidence level), while annual precipitation is decreasing at the rate of 6.3 mm decade–1 (significant at the 90% confidence level), averaged over Saudi Arabia. For the near (far) future period, the 66% likely ranges of annual-averaged temperature is projected to increase by 1.2–1.9 (1.2–2.1) ˚C, 1.4–2.1 (2.3–3.4) ˚C, and 1.8–2.7 (4.1–5.8) ˚C under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. Higher warming is projected in the summer than in the winter, while the Northern Arabian Peninsula (NAP) is projected to warm more than Southern Arabian Peninsula (SAP), by the end of the twenty-first century. For precipitation, a dipole-like pattern is found, with a robust increase in annual mean precipitation over the SAP, and a decrease over the NAP. The 66% likely ranges of annual-averaged precipitation over the whole Arabian Peninsula is projected to change by 5 to 28 (–3 to 29) %, 5 to 31 (4 to 49) %, and 1 to 38 (12 to 107) % under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively, in the near (far) future. Overall, the full ranges in CMIP6 remain higher than the CMIP5 models, which points towards a higher climate sensitivity of some of the CMIP6 climate models to greenhouse gas (GHG) emissions as compared to the CMIP5. The CMIP6 dataset confirmed previous findings of changes in future climate over the Arabian Peninsula based on CMIP3 and CMIP5 datasets. The results presented in this study will be useful for impact studies, and ultimately in devising future policies for adaptation in the region.
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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.
Анотація:
Abstract. As the number of models in Coupled Model Intercomparison Project (CMIP) archives increase from generation to generation, there is a pressing need for guidance on how to interpret and best use the abundance of newly available climate information. Users of the latest CMIP6 seeking to draw conclusions about model agreement must contend with an “ensemble of opportunity” containing similar models that appear under different names. Those who used the previous CMIP5 as a basis for downstream applications must filter through hundreds of new CMIP6 simulations to find several best suited to their region, season, and climate horizon of interest. Here we present methods to address both issues, model dependence and model subselection, to help users previously anchored in CMIP5 to navigate CMIP6 and multi-model ensembles in general. In Part I, we refine a definition of model dependence based on climate output, initially employed in Climate model Weighting by Independence and Performance (ClimWIP), to designate discrete model families within CMIP5 and CMIP6. We show that the increased presence of model families in CMIP6 bolsters the upper mode of the ensemble's bimodal effective equilibrium climate sensitivity (ECS) distribution. Accounting for the mismatch in representation between model families and individual model runs shifts the CMIP6 ECS median and 75th percentile down by 0.43 ∘C, achieving better alignment with CMIP5's ECS distribution. In Part II, we present a new approach to model subselection based on cost function minimization, Climate model Selection by Independence, Performance, and Spread (ClimSIPS). ClimSIPS selects sets of CMIP models based on the relative importance a user ascribes to model independence (as defined in Part I), model performance, and ensemble spread in projected climate outcome. We demonstrate ClimSIPS by selecting sets of three to five models from CMIP6 for European applications, evaluating the performance from the agreement with the observed mean climate and the spread in outcome from the projected mid-century change in surface air temperature and precipitation. To accommodate different use cases, we explore two ways to represent models with multiple members in ClimSIPS, first, by ensemble mean and, second, by an individual ensemble member that maximizes mid-century change diversity within the CMIP overall. Because different combinations of models are selected by the cost function for different balances of independence, performance, and spread priority, we present all selected subsets in ternary contour “subselection triangles” and guide users with recommendations based on further qualitative selection standards. ClimSIPS represents a novel framework to select models in an informed, efficient, and transparent manner and addresses the growing need for guidance and simple tools, so those seeking climate services can navigate the increasingly complex CMIP landscape.
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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.
Анотація:
AbstractRadiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. This study investigates intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the west Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.
Дисертації з теми "CMIP6 simulations":
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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.
Анотація:
L'Afrique centrale occidentale abrite les forêts les plus denses du bassin du Congo, deuxième plus grand massif forestier tropical après l’Amazonie. Elle se caractérise par un climat équatorial avec des températures élevées, un régime pluviométrique bimodal et surtout une longue saison sèche nuageuse, de juin à septembre. Malgré son importance écologique, la variabilité climatique de cette région a été peu étudiée par rapport à d'autres régions du continent africain, principalement en raison de la rareté des observations in-situ.Reconnaissant ces défis posés par le manque de données in situ, cette étude explore la variabilité climatique en Afrique centrale occidentale sous l’angle du rayonnement solaire en surface, paramètre clef pour le fonctionnement des forêts tropicales. Dans ce contexte, cette thèse s’attache à établir une première climatologie du rayonnement solaire en surface pour la région, à en documenter la variabilité, en particulier durant la saison sèche nuageuse de juin à septembre, et à évaluer la performance des produits satellitaires, des réanalyses et des simulations des modèles climatiques CMIP6.Dans une première partie, une évaluation de huit produits satellitaires d’estimation du rayonnement solaire (CERES-EBAF, CERES-SYN1deg, TPDC, CMSAF SARAH-2, CMSAF CLARA-A2, CAMS-JADE, WorldClim 2 et les réanalyses ERA5), révèle des différences dans les champs spatiotemporels. Tout en capturant avec succès les cycles annuels moyens de rayonnement solaire, les produits présentent des variations régionales, soulignant l'impact des paramètres atmosphériques sur l'estimation précise du rayonnement solaire. En outre, tous les produits à l’exception de WorldClim 2 s’accordent sur le fait que la façade atlantique reçoit moins de rayonnement solaire que les autres régions d’Afrique Centrale. La performance de ces produits est également évaluée par rapport aux observations in-situ sur la base de quatre types de cycle diurne de rayonnement solaire - les jours Obscurs, Obscurs AM (matin), Obscurs PM (après-midi) et Lumineux. Les produits représentent correctement la forme de ces quatre types, mais avec une amplitude plus grande.La deuxième partie se concentre sur l’étude de la variabilité interannuelle et les tendances du rayonnement solaire pendant la saison sèche nuageuse juin-septembre, mettant en évidence des différences marquées entre le produit satellitaire CMSAF SARAH-2 et la réanalyse climatique ERA5. Dans cette partie, l’étude a également permis d’identifier les dates de début et de fin de la saison sèche à partir du rayonnement solaire, et en établissant une relation significative entre les températures de surface de l'océan Atlantique équatorial et le début de la saison sèche.Dans la dernière partie, la capacité des modèles climatiques globaux CMIP6 à reproduire les niveaux moyens de rayonnement solaire dans la région a été évaluée. Les résultats soulignent des disparités sous-régionales dans la performance des modèles. Les modèles utilisés dans cette étude sous-estiment le rayonnement solaire au sud-ouest du Gabon-Congo tandis qu’ils le surestiment au nord-est, principalement d’avril à décembre. Les différences les plus importantes étant observées pendant la saison des pluies octobre-novembre. Ces disparités semblent provenir de la nébulosité, en particulier des nuages de basse et moyenne altitude, qui influencent de manière significative le rayonnement solaire mais avec des relations variables selon les modèles. Cette partie met également en évidence la téléconnexion entre la température de surface de l’océan Atlantique équatorial et le rayonnement solaire dans les modèles, mais qui varie entre le littoral et l’intérieur du Gabon, soulignant la nécessité de travailler avec des modèles climatiques régionaux mieux résolusWestern 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
2
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.
Анотація:
Sur les effets du changement climatique aux échelles globale et régionale. Il montre en particulierqu'aucun consensus ne peut être trouvé pour ce qui concerne l'évolution future de lapluviométrie -- et de la dynamique atmosphérique associée -- en région de mousson africaine.Ce mémoire revisite cette question à la lumière des nouvelles données disponibles et selon uneapproche évitant toute surreprésentation du nombre de simulations disponibles pour un type demodèle donné, tout en prenant en compte la diversité des modèles ainsi que leur évolution dansle temps : sorties de vingt modèles de circulation générale (MCGs) ayant participé aux exercicesCMIP3 (douze MCGs) et CMIP5 (huit MCGs) sous les scénarios d'émissions A1B et rcp4.5,respectivement. Les sorties sont analysées principalement sur deux fenêtres de quarante ans --périodes actuelle (1960-1999) et future (2031-2070) -- et les résultats discutés au regard de leurvraisemblance selon une approche permettant à la fois de quantifier les différences futur moinsactuel, de mesurer les significativités et les robustesses statistiques et d'associer une probabilitémesurant le consensus des modèles en fonction des échelles et des variables considérées.Les analyses menées sur CMIP3 et CMIP5 montrent qu'un consensus sur l'effet du changementclimatique en Afrique de l'Ouest peut être obtenu si l'on ne fait pas de l'ensemble de labande sahélienne une entité homogène et qu'on raisonne à des échelles spatiales inférieures. Lesrésultats révèlent une évolution contrastée entre le centre et l'ouest du Sahel avec, pour le futur(i) une hausse des précipitations au centre s'expliquant surtout par une plus grande convergencedes flux dans les basses couches, ainsi qu'une pénétration plus au nord de la mousson ;(ii) une baisse des précipitations à l'ouest s'expliquant par le renforcement de la circulation detype Walker, du Jet d'Est Africain (JEA) et de la subsidence dans les couches moyennes. Parailleurs, on peut s'attendre à une modification du cycle annuel moyen avec un retrait retardé dela mousson. Ce retard est notamment lié aux apports supplémentaires d'humidité depuis l'Atlantique,dus au renforcement des contrastes thermiques et d'humidité entre océan et continent,mais aussi et surtout aux apports tardifs d'humidité depuis la Méditerranée et au renforcementdes flux de nord en septembre et octobre en direction du Sahel
3
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.
Анотація:
The 11 year solar-cycle component of climate variability is assessed in historical simulations of models taken from the Coupled Model Intercomparison Project, phase 5 (CMIP-5). Multiple linear regression is applied to estimate the zonal temperature, wind and annular mode responses to a typical solar cycle, with a focus on both the stratosphere and the stratospheric influence on the surface over the period ∼1850–2005. The analysis is performed on all CMIP-5 models but focuses on the 13 CMIP-5 models that resolve the stratosphere (high-top models) and compares the simulated solar cycle signature with reanalysis data. The 11 year solar cycle component of climate variability is found to be weaker in terms of magnitude and latitudinal gradient around the stratopause in the models than in the reanalysis. The peak in temperature in the lower equatorial stratosphere (∼70 hPa) reported in some studies is found in the models to depend on the length of the analysis period, with the last 30 years yielding the strongest response.
A modification of the Polar Jet Oscillation (PJO) in response to the 11 year solar cycle is not robust across all models, but is more apparent in models with high spectral resolution in the short-wave region. The PJO evolution is slower in these models, leading to a stronger response during February, whereas observations indicate it to be weaker. In early winter, the magnitude of the modelled response is more consistent with observations when only data from 1979–2005 are considered. The observed North Pacific high-pressure surface response during the solar maximum is only simulated in some models, for which there are no distinguishing model characteristics. The lagged North Atlantic surface response is reproduced in both high- and low-top models, but is more prevalent in the former. In both cases, the magnitude of the response is generally lower than in observations.
4
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.
Анотація:
Accurate assessments of future climate impacts require realistic simulation of interannual-century-scale temperature and precipitation variability. Here, well-constrained paleoclimate data and the latest generation of Earth system model data are used to evaluate the magnitude and spatial consistency of climate variance distributions across interannual to centennial frequencies. It is found that temperature variance generally increases with time scale in patterns that are spatially consistent among models, especially over the mid-and high-latitude oceans. However, precipitation is similar to white noise across much of the globe. When Earth system model variance is compared to variance generated by simple autocorrelation, it is found that tropical temperature variability in Earth system models is difficult to distinguish from variability generated by simple autocorrelation. By contrast, both forced and unforced Earth system models produce variability distinct from a simple autoregressive process over most high-latitude oceans. This new analysis of tropical paleoclimate records suggests that low-frequency variance dominates the temperature spectrum across the tropical Pacific and Indian Oceans, but in many Earth system models, interannual variance dominates the simulated central and eastern tropical Pacific temperature spectrum, regardless of forcing. Tropical Pacific model spectra are compared to spectra from the instrumental record, but the short instrumental record likely cannot provide accurate multidecadal-centennial-scale variance estimates. In the coming decades, both forced and natural patterns of decade-century-scale variability will determine climate-related risks. Underestimating low-frequency temperature and precipitation variability may significantly alter our understanding of the projections of these climate impacts.
5
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.
Анотація:
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.
6
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.
Анотація:
La neige est une composante essentielle du système climatique arctique. Au nord de l'Eurasie et de l'Amérique du Nord, la couverture neigeuse est présente de 7 à 10 mois par an et son extension saisonnière maximale représente plus de 40% de la surface terrestre de l'hémisphère nord. La neige affecte une variété de processus climatiques et de rétroactions aux hautes latitudes. Sa forte réflectivité et sa faible conductivité thermique ont un effet de refroidissement et modulent la rétroaction neige-albédo. Sa contribution au bilan radiatif de la Terre est comparable à celle de la banquise. De plus, en empêchant d'importantes pertes d'énergie du sol sous-jacent, la neige limite la progression de la glace et le développement du pergélisol saisonnier. Réserve d'eau naturelle, la neige joue un rôle essentiel dans le cycle hydrologique aux hautes latitudes, notamment en ce qui concerne l'évaporation et le ruissellement. La neige est l'une des composantes du système climatique présentant la plus forte variabilité. Le réchauffement de l'Arctique étant deux fois plus rapide que celui du reste du globe, la variabilité présente et future des caractéristiques de la neige est cruciale pour une meilleure compréhension des processus et des changements climatiques.Cependant, notre capacité à observer l'Arctique terrestre étant limitée, les modèles climatiques jouent un rôle clé dans notre aptitude à comprendre les processus liés à la neige. À cet égard, la représentation des rétroactions associées à la neige dans les modèles climatiques, en particulier pendant les saisons intermédiaires (lorsque la couverture neigeuse de l'Arctique présente la plus forte variabilité), est primordiale.Notre étude porte principalement sur la représentation de la neige terrestre arctique dans les modèles de circulation générale issus du projet CMIP5 (Coupled Model Intercomparison Project) au cours du printemps (mars-avril) et de l’automne (octobre-novembre) de 1979 à 2005. Les caractéristiques de la neige des modèles de circulation générale ont été validées par rapport aux mesures de neige in situ, ainsi qu’à des produits satellitaires et à des réanalyses.Nous avons constaté que les caractéristiques de la neige dans les modèles ont un biais plus marqué au printemps qu'en automne. Le cycle annuel de la couverture neigeuse est bien reproduit par les modèles. Cependant, les cycles annuels d'équivalent en eau de la neige et de sa profondeur sont largement surestimés par les modèles, notamment en Amérique du Nord. Il y a un meilleur accord entre les modèles et les observations dans la position de la marge de neige au printemps plutôt qu'en automne. Les amplitudes de variabilité interannuelle pour toutes les variables de la neige sont nettement sous-estimées par la plupart des modèles CMIP5. Pour les deux saisons, les tendances des variables de la neige dans les modèles sont principalement négatives, mais plus faibles et moins significatives que celles observées. Les distributions spatiales des tendances de la couverture neigeuse sont relativement bien reproduites par les modèles, toutefois, la distribution spatiale des tendances en équivalent-eau et en profondeur de la neige présente de fortes hétérogénéités régionales.Enfin, nous concluons que les modèles CMIP5 fournissent des informations précieuses sur les caractéristiques de la neige en Arctique terrestre, mais qu’ils présentent encore des limites. Il y a un manque d’accord entre l’ensemble des modèles sur la distribution spatiale de la neige par rapport aux observations et aux réanalyses. Ces écarts sont particulièrement marqués dans les régions où la variabilité de la neige est la plus forte. Notre objectif dans cette étude était d'identifier les circonstances dans lesquelles ces modèles reproduisent ou non les caractéristiques observées de la neige en Arctique. Nous attirons l’attention de la communauté scientifique sur la nécessité de prendre compte nos résultats pour les futures études climatiquesSnow 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
7
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.
Анотація:
Dans la plupart des études, on s'intéresse au changement climatique futur en analysant l'évolution du climat entre une référence actuelle fixée et une période future. Le réchauffement est de plus en plus fort au fil du 21ème siècle. Dans un contexte où les conditions climatiques sont toujours en train d'évoluer, les écosystèmes doivent continuellement s'adapter à des modifications diverses du climat. Dans le cadre de cette thèse, je propose d'analyser les projections climatiques sous un angle alternatif. Afin d’être caractéristique des représentations des populations urbaines et rurales, je définis et analyse des indicateurs liés à la vitesse des changements de température, de précipitations et de végétation. Un ensemble de simulations CMIP5 de 18 modèles de climat est sélectionné. La vitesse est représentée par des différences entre deux périodes successives de 20 ans. Cette notion de vitesse pourrait offrir de nouveaux outils pour interagir avec les communautés scientifiques travaillant sur les impacts et l'adaptation.Sans politiques d’atténuation du changement (scénario RCP8.5), le réchauffement global sera au moins deux fois plus rapide à la fin du siècle qu’actuellement, et même trois fois dans certaines régions. Près de la moitié des surfaces continentales, principalement les zones tropicales, seront touchées par des décalages significatifs de la distribution de la température entre deux périodes de 20 ans d’ici à 2060, i.e. au moins 4 fois plus qu’actuellement. Dans ces régions, des années extrêmement chaudes ayant un temps de retour de 50 ans deviendront habituelles en l’espace de 20 ans seulement. La fraction de la population mondiale étant exposée à ces changements pourrait atteindre environ 60% (i.e. 6 milliards de personnes et 7 fois plus qu’actuellement). Il suffit de relativement légères mesures d’atténuation (RCP6.0) pour que la vitesse du réchauffement ne dépasse pas les valeurs actuelles et que 3 fois moins de personnes soient exposées à des décalages significatifs de température.Les vitesses d’humidification et d’assèchement en termes de précipitations augmenteront de 30 à 40%. Leur répartition géographique deviendra plus stable spatialement et les tendances tendront à persister sur les mêmes régions, et ce malgré l’accélération du réchauffement global. Cette stabilisation résulte de la contribution grandissante des processus thermodynamiques par rapport à ceux contrôlés par la circulation générale. La combinaison de l’accélération des tendances et de leur persistance peut avoir un impact sur l’adaptation des sociétés et des écosystèmes, particulièrement sur le bassin méditerranéen, en Amérique centrale, en Inde et dans les régions arctiques. Une telle évolution est déjà visible actuellement, mais pourrait disparaître avec de fortes mesures d’atténuation (RCP2.6).Les changements de la végétation peuvent être des repères visuels du changement climatique. Dans les moyennes et hautes latitudes Nord, le cycle saisonnier des arbres et des herbacées suit la vitesse du réchauffement. Sans politiques d’atténuation, le début de la saison foliaire avance et sa durée augmente plus rapidement au fil du siècle. La couverture de la végétation se densifie quelque soit le scénario proportionnellement à l’augmentation de la température. Le cycle saisonnier des cultures des moyennes latitudes dépend directement de la température et celui des cultures tropicales de l’évolution des caractéristiques de la saison des pluies. Sous les autres latitudes, aucune évolution robuste du cycle saisonnier n’est projetée. La vitesse des changements de répartition de la végétation a déjà doublé entre 1880 et 1950 correspondant à un changement marqué de l'utilisation des sols. Elle est stable tout au long du siècle si la végétation interagit dynamiquement avec le climat dans les modèles, traduisant un ralentissement du changement de l'utilisation des sols et l'accélération des changements de végétation sous l'effet du changement climatiqueIn 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
8
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.
Анотація:
Hydro-climate extreme analysis helps understanding the process of spatio-temporal variation of extreme events due to climate change, and it is an important aspect in designing hydrological structures, forecasting floods and an effective decision making in the field of water resources design and management. The study evaluates extreme precipitation events over the Columbia River Basin (CRB), the fourth largest basin in the U.S., by simulating four CMIP5 global climate models (GCMs) for the historical period (1970-1999) and future period (2041-2070) under RCP85 GHG scenario.
We estimated the intensity of extreme and average precipitation for both winter (DJF) and summer (JJA) seasons by using the GEV distribution and multi-model ensemble average over the domain of the Columbia River Basin. The four CMIP5 models performed very well at simulating precipitation extremes in the winter season. The CMIP5 climate models showed heterogeneous spatial pattern of summer extreme precipitation over the CRB for the future period. It was noticed that multi-model ensemble mean outperformed compared to the individual performance of climate models for both seasons.
We have found that the multi-model ensemble shows a consistent and significant increase in the extreme precipitation events in the west of the Cascades Range, Coastal Ranges of Oregon and Washington State, the Canadian portion of the basin and over the Rocky Mountains. However, the mean precipitation is projected to decrease in both winter and summer seasons in the future period.
The Columbia River is dominated by the glacial snowmelt, so the increase in the intensity of extreme precipitation and decrease in mean precipitation in the future period, as simulated by four CMIP5 models, is expected to aggravate the earlier snowmelt and contribute to the flooding in the low lying areas especially in the west of the Cascades Range. In addition, the climate change shift could have serious implications on transboundary water issues in between the United States and Canada. Therefore, adaptation strategies should be devised to cope the possible adverse effects of the changing the future climate so that it could have minimal influence on hydrology, agriculture, aquatic species, hydro-power generation, human health and other water related infrastructure.
9
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.
Анотація:
Dans la plupart des études, on s'intéresse au changement climatique futur en analysant l'évolution du climat entre une référence actuelle fixée et une période future. Le réchauffement est de plus en plus fort au fil du 21ème siècle. Dans un contexte où les conditions climatiques sont toujours en train d'évoluer, les écosystèmes doivent continuellement s'adapter à des modifications diverses du climat. Dans le cadre de cette thèse, je propose d'analyser les projections climatiques sous un angle alternatif. Afin d’être caractéristique des représentations des populations urbaines et rurales, je définis et analyse des indicateurs liés à la vitesse des changements de température, de précipitations et de végétation. Un ensemble de simulations CMIP5 de 18 modèles de climat est sélectionné. La vitesse est représentée par des différences entre deux périodes successives de 20 ans. Cette notion de vitesse pourrait offrir de nouveaux outils pour interagir avec les communautés scientifiques travaillant sur les impacts et l'adaptation.Sans politiques d’atténuation du changement (scénario RCP8.5), le réchauffement global sera au moins deux fois plus rapide à la fin du siècle qu’actuellement, et même trois fois dans certaines régions. Près de la moitié des surfaces continentales, principalement les zones tropicales, seront touchées par des décalages significatifs de la distribution de la température entre deux périodes de 20 ans d’ici à 2060, i.e. au moins 4 fois plus qu’actuellement. Dans ces régions, des années extrêmement chaudes ayant un temps de retour de 50 ans deviendront habituelles en l’espace de 20 ans seulement. La fraction de la population mondiale étant exposée à ces changements pourrait atteindre environ 60% (i.e. 6 milliards de personnes et 7 fois plus qu’actuellement). Il suffit de relativement légères mesures d’atténuation (RCP6.0) pour que la vitesse du réchauffement ne dépasse pas les valeurs actuelles et que 3 fois moins de personnes soient exposées à des décalages significatifs de température.Les vitesses d’humidification et d’assèchement en termes de précipitations augmenteront de 30 à 40%. Leur répartition géographique deviendra plus stable spatialement et les tendances tendront à persister sur les mêmes régions, et ce malgré l’accélération du réchauffement global. Cette stabilisation résulte de la contribution grandissante des processus thermodynamiques par rapport à ceux contrôlés par la circulation générale. La combinaison de l’accélération des tendances et de leur persistance peut avoir un impact sur l’adaptation des sociétés et des écosystèmes, particulièrement sur le bassin méditerranéen, en Amérique centrale, en Inde et dans les régions arctiques. Une telle évolution est déjà visible actuellement, mais pourrait disparaître avec de fortes mesures d’atténuation (RCP2.6).Les changements de la végétation peuvent être des repères visuels du changement climatique. Dans les moyennes et hautes latitudes Nord, le cycle saisonnier des arbres et des herbacées suit la vitesse du réchauffement. Sans politiques d’atténuation, le début de la saison foliaire avance et sa durée augmente plus rapidement au fil du siècle. La couverture de la végétation se densifie quelque soit le scénario proportionnellement à l’augmentation de la température. Le cycle saisonnier des cultures des moyennes latitudes dépend directement de la température et celui des cultures tropicales de l’évolution des caractéristiques de la saison des pluies. Sous les autres latitudes, aucune évolution robuste du cycle saisonnier n’est projetée. La vitesse des changements de répartition de la végétation a déjà doublé entre 1880 et 1950 correspondant à un changement marqué de l'utilisation des sols. Elle est stable tout au long du siècle si la végétation interagit dynamiquement avec le climat dans les modèles, traduisant un ralentissement du changement de l'utilisation des sols et l'accélération des changements de végétation sous l'effet du changement climatiqueIn 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
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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.
Анотація:
La neige peut couvrir jusqu'à 40% des terres immergées de l'hémisphère Nord en hiver. De par son influence sur le bilan d'énergie en surface, elle constitue donc une source potentielle de variabilité et de prévisibilité climatique aux échelles mensuelles à saisonnières. Au-delà de ses effets locaux, la couverture neigeuse peut, à l'instar des surfaces océaniques, engendrer des téléconnexions et ainsi moduler le climat de régions plus lointaines. Cette thèse revisite plusieurs aspects des liens neige-climat en utilisant à la fois les jeux de données observées, les simulations réalisées pour le 4ème rapport du Groupe Intergouvernemental d'experts sur l'Evolution du Climat (GIEC), ainsi que le modèle atmosphérique ARPEGE-Climat pour réaliser des tests de sensibilité. L'influence de la neige eurasiatique/himalayenne sur la mousson indienne d'été, largement évoquée dans la littérature, est remise en cause par l'analyse des données observées étendues à la période 1967-2006. Toutefois, un prédicteur lié à la circulation atmosphérique de grande échelle sur le Pacifique Nord est proposé pour améliorer les prévisions saisonnières statistiques de la mousson indienne. L'influence des étendues de neige sibériennes en automne sur la variabilité atmosphérique hivernale de l'hémisphère Nord semble quant à elle plus robuste dans les observations. Si les modèles couplés du GIEC sont incapables de reproduire cette téléconnexion, les expériences de sensibilité réalisées avec ARPEGE-Climat confirment le mécanisme physique proposé dans la littérature, à condition que la perturbation en surface soit importante et que l'état moyen de la circulation extratropicale simulé soit suffisamment réaliste. Finalement, la prévisibilité de l'atmosphère associée à l'enneigement est quantifiée de façon plus systématique avec ARPEGE-Climat. Si les résultats montrent un impact mitigé sur la circulation de grande échelle, la relaxation/initialisation du modèle vers/avec des masses de neige plus réalistes permet une meilleure prévisibilité des températures de surface sur l'Europe et l'Amérique du Nord. La neige représente donc une source de prévisibilité climatique non négligeable à l'échelle locale et peut influencer à distance la circulation atmosphérique extratropicale. Les téléconnexions neige-climat doivent être cependant être confirmées dans les années qui viennent, et constituent encore un exercice difficile pour l'état de l'art des modèles de climat.
Частини книг з теми "CMIP6 simulations":
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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.
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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.
3
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.
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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.
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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.
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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.
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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.
Анотація:
Climate has a strong influence on agriculture, which is considered the most dependent human activity on climate variations. The future performance of the Senegalese agricultural sector will depend on its ability to adapt to the negative impacts of climate change. This study demonstrated that the impact of three climate change scenarios (ssp126, ssp245 and ssp585) on the evolution of 14 agro-climatic indicators is already evident in Senegal in the near and distant future. Indeed, the results obtained show a generalized decrease over the whole country in seasonal rainfall totals of about −10% in the near future (2020–2049; PSE horizon) up to −40% in the distant future (2070–2099) for the ssp585 scenario. This decrease in precipitation will be associated with two phenomena, namely a shortening of the rainy season due to increasingly late starts and an increase in dry spells, particularly the DSl and DSxl. The other trend observed is an increase in the frequency and intensity of extreme rainfall events (R99 and R20), which illustrates an increasingly chaotic distribution of rain in the future. Finally, this characterization of agroclimatic indicators made it possible to evaluate and classify the sensitivity of four global models corrected by the CFD-t method in order to run agronomic simulations and to explore adaptation strategies for farmer management in the future.
Тези доповідей конференцій з теми "CMIP6 simulations":
1
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.
Анотація:
The main source of data about possible future climate change over the Czech Republic studied within the project PERUN is a series of Aladin-CLIMATE/CZ model simulations driven by the global climate model CNRM-ESM2-1. Other available model simulations, in particular the CMIP5 and CMIP6 global climate models, Euro-CORDEX regional climate models, and other new simulations at high horizontal resolution, will be used to estimate the uncertainties in the climate change scenarios. This paper presents examples of such uncertainty analysis.
2
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.
3
"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.
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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.
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"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.
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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.
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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.
Анотація:
Planning is essential to navigate the challenges and uncertainties posed by climate change as offshore marine energy development proceeds over the coming decades. This paper introduces the prototype version of the Canadian Coastal Zone Information System (CCZIS), a pioneering initiative developed jointly by ASL Environmental Sciences Inc. and Trailmark Systems Inc. through the Innovative Solutions Canada Challenge administered by Public Services and Procurement Canada (ISC, 2020). The core functionality of CCZIS lies in its ability to provide spatial-statistical representations of key metocean parameters such as water levels, waves, sea ice conditions, vertical allowances, and marine winds. One of CCZIS's ground-breaking features is its integration of regional model-based projections derived from coupled atmosphere-ocean models such as The Coupled Model Intercomparison Project Phase 5 (CMIP5). CMIP5 is a collaborative international effort that involves a collection of climate models used to simulate and project the Earth's climate system (Taylor et al., 2012; IPCC, 2013). CMIP5 was coordinated by the World Climate Research Programme (WCRP) and facilitated the comparison of climate models from different global institutions. It served as a framework for assessing the performance of these models, advancing our understanding of climate processes, and providing projections for future climate conditions. CMIP5 models simulate a range of climate variables, including temperature, precipitation, sea ice extent, and atmospheric circulation. These simulations help scientists and policymakers explore potential future climate scenarios under different greenhouse gas emission scenarios. CMIP-5 model realizations for different relative concentration pathway scenarios (RCP) contributed to the Intergovernmental Panel on Climate Change (IPCC) assessments, providing valuable data and insights that inform climate research, impact assessments, and policy decisions. Spanning a variety of greenhouse gas emission scenarios, from the conservative RCP 2.0 to the more extreme RCP 8.5, these projections enable users to toggle between different climate change scenarios with the number representing the increase in net surface radiative forcing. This functionality allows for comparative analysis against metocean design criteria used in past projects against different potential future climate change scenarios, thereby allowing for the assessment of expected metocean extremes under each RCP scenario. A variety of other data sources were reviewed such as the Canadian Extreme Water Level Adaptation Tool (CAN-EWLAT) (Greenan, 2022), MSC-50 (Swail et. al., 2007), etc., and are described further in the analysis section. CCZIS displays three-dimensional bathymetric and infrastructure data together, through the combination of several data sources: high-resolution Canadian Hydrographic Service (CHS) Non-Navigational (NONNA) bathymetry (CHS, 2023) dredging survey data, seabed properties (borehole data), and its support for the geo-referenced three-dimensional display of present and future coastal and offshore infrastructure. In addition, CCZIS has a built-in user input-driven computational tool for computing nearshore waves, for large marine wind events, at any selected location. The integration of hydrographic data, seabed properties, and existing infrastructure with hindcast and future-looking metocean conditions offers a unified data fusion platform to ensure resilient engineering of offshore marine energy installations, including wind farms, energy platforms, transmission infrastructure, as well as ports and small craft harbors where support vessel operations will be based.
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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.
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"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.
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"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.
Звіти організацій з теми "CMIP6 simulations":
1
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.
Анотація:
In this deliverable, we perform Earth system model (ESM) simulations to assess the role of land-based and ocean-based negative emission technologies (NETs) for achieving the temperature target set by the 2015 Paris Agreement. The dataset provided from this work package will be used for investigating carbon sequestration potential, side-effects and potential constraints of combining oceanic and terrestrial NETs with the help of an earth system model, NorESM2. Two long NorESM2 coupled simulations with SSP5-3.4-OS scenario are conducted to check the CDR potential of terrestrial CDR, and terrestrial and marine CDR together by combining land-based Bioenergy for Carbon Capture and Storage (BECCS) and Ocean Alkalinization Enhancement (OAE) scenarios together. For the terrestrial BECCS simulation, the default land use distribution in the original CMIP6 SSP5-3.4 land use dataset is modified to accommodate more bioenergy crop in the future while keeping the total crop area of 2015 for food throughout the century and combining it with a bio-CCS system. For the second simulation we combined the above terrestrial BECCS simulation with 2030-high OAE scenario from Deliverable 4.6. A higher amount of carbon captured by making use of the carbon sequestration potential of land and ocean together. (OceanNets Deliverable ; D4.7)
2
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.
Анотація:
In this report, we have evaluated the performance of nearly 40 global climate models (GCMs) participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). The focus is on the northern European area, but the ability to simulate southern European and global climate is discussed as well. Model evaluation was started with a technical control; completely unrealistic values in the GCM output files were identified by seeking the absolute minimum and maximum values. In this stage, one GCM was rejected totally, and furthermore individual output files from two other GCMs. In evaluating the remaining GCMs, the primary tool was the Model Climate Performance Index (MCPI) that combines RMS errors calculated for the different climate variables into one index. The index takes into account both the seasonal and spatial variations in climatological means. Here, MCPI was calculated for the period 1981—2010 by comparing GCM output with the ERA-Interim reanalyses. Climate variables explored in the evaluation were the surface air temperature, precipitation, sea level air pressure and incoming solar radiation at the surface. Besides MCPI, we studied RMS errors in the seasonal course of the spatial means by examining each climate variable separately. Furthermore, the evaluation procedure considered model performance in simulating past trends in the global-mean temperature, the compatibility of future responses to different greenhouse-gas scenarios and the number of available scenario runs. Daily minimum and maximum temperatures were likewise explored in a qualitative sense, but owing to the non-existence of data from multiple GCMs, these variables were not incorporated in the quantitative validation. Four of the 37 GCMs that had passed the initial technical check were regarded as wholly unusable for scenario calculations: in two GCMs the responses to the different greenhouse gas scenarios were contradictory and in two other GCMs data were missing from one of the four key climate variables. Moreover, to reduce inter-GCM dependencies, no more than two variants of any individual GCM were included; this led to an abandonment of one GCM. The remaining 32 GCMs were divided into three quality classes according to the assessed performance. The users of model data can utilize this grading to select a subset of GCMs to be used in elaborating climate projections for Finland or adjacent areas. Annual-mean temperature and precipitation projections for Finland proved to be nearly identical regardless of whether they were derived from the entire ensemble or by ignoring models that had obtained the lowest scores. Solar radiation projections were somewhat more sensitive.
3
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.
Анотація:
In part one of this deliverable, an ensemble of 14 CMIP6 Earth System Models is evaluated regarding their performance in simulating alkalinity and related parameters. The majority of the models and the multi-model-mean underestimate surface alkalinity compared to climatological observations. Alkalinity biases stemming from the parametrization of calcium carbonate formation and dissolution can be as big as biases stemming from model physics. In part two, we test the sensitivity of parametrizations concerning the carbonate chemistry in the FESOM2.1-REcoM3 and give recommendations for addressing alkalinity biases.
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.
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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.
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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.