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1
Gier, Bettina K., Manuel Schlund, Pierre Friedlingstein, et al. "Representation of the terrestrial carbon cycle in CMIP6." Biogeosciences 21, no. 22 (2024): 5321–60. http://dx.doi.org/10.5194/bg-21-5321-2024.
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Abstract. Simulation of the carbon cycle in climate models is important due to its impact on climate change, but many weaknesses in its reproduction were found in previous models. Improvements in the representation of the land carbon cycle in Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) include the interactive treatment of both the carbon and nitrogen cycles, improved photosynthesis, and soil hydrology. To assess the impact of these model developments on aspects of the global carbon cycle, the Earth System Model Evaluation Tool (ESMValTool) is expanded to compare CO2-concentration- and CO2-emission-driven historical simulations from CMIP5 and CMIP6 to observational data sets. A particular focus is on the differences in models with and without an interactive terrestrial nitrogen cycle. Overestimations of photosynthesis (gross primary productivity (GPP)) in CMIP5 were largely resolved in CMIP6 for participating models with an interactive nitrogen cycle but remaining for models without one. This points to the importance of including nutrient limitation. Simulating the leaf area index (LAI) remains challenging, with a large model spread in both CMIP5 and CMIP6. In ESMs, the global mean land carbon uptake (net biome productivity (NBP)) is well reproduced in the CMIP5 and CMIP6 multi-model means. However, this is the result of an underestimation of NBP in the Northern Hemisphere, which is compensated by an overestimation in the Southern Hemisphere and the tropics. Carbon stocks remain a large uncertainty in the models. While vegetation carbon content is slightly better represented in CMIP6, the inter-model range of soil carbon content remains the same between CMIP5 and CMIP6. Overall, a slight improvement in the simulation of land carbon cycle parameters is found in CMIP6 compared to CMIP5, but with many biases remaining, further improvements of models in particular for LAI and NBP is required. Models from modeling groups participating in both CMIP phases generally perform similarly or better in their CMIP6 compared to their CMIP5 models. This improvement is not as significant in the multi-model means due to more new models in CMIP6, especially those using older versions of the Community Land Model (CLM). Emission-driven simulations perform just as well as the concentration-driven models, despite the added process realism. Due to this, we recommend that ESMs in future Coupled Model Intercomparison Project (CMIP) phases perform emission-driven simulations as the standard so that climate–carbon cycle feedbacks are fully active. The inclusion of the nitrogen limitation led to a large improvement in photosynthesis compared to models not including this process, suggesting the need to view the nitrogen cycle as a necessary part of all future carbon cycle models. Possible benefits when including further limiting nutrients such as phosphorus should also be considered.
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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 (2021): 867. http://dx.doi.org/10.3390/atmos12070867.
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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.
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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 (2022): 10375. http://dx.doi.org/10.3390/su141610375.
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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, et al. "Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations." Climate of the Past 16, no. 5 (2020): 1847–72. http://dx.doi.org/10.5194/cp-16-1847-2020.
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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, et al. "Solar forcing for CMIP6 (v3.2)." Geoscientific Model Development 10, no. 6 (2017): 2247–302. http://dx.doi.org/10.5194/gmd-10-2247-2017.
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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 (2021): e2016549118. http://dx.doi.org/10.1073/pnas.2016549118.
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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, et al. "Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization." Geoscientific Model Development 9, no. 5 (2016): 1937–58. http://dx.doi.org/10.5194/gmd-9-1937-2016.
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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 (2022): 321–40. http://dx.doi.org/10.5194/esd-13-321-2022.
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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 (2020): 611–30. http://dx.doi.org/10.1007/s41748-020-00183-5.
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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 (2023): 4715–47. http://dx.doi.org/10.5194/gmd-16-4715-2023.
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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, et al. "Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models." Journal of Climate 33, no. 18 (2020): 7755–75. http://dx.doi.org/10.1175/jcli-d-19-1011.1.
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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.
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Vennapu, Lakshmana Rao, Krishna Dora Babu Kotti, Sravani Alanka, and Pavan Krishnudu Badireddi. "Analysis of CMIP6 Simulations in the Indian Summer Monsoon Period 1979-2014." Nature Environment and Pollution Technology 24, no. 1 (2025): B4215. https://doi.org/10.46488/nept.2025.v24i01.b4215.
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The monsoon system in India plays a pivotal role in shaping the country’s climate. Recent studies have indicated that the increasing variability of monsoons is attributable to climate change, resulting in prolonged periods of drought and excessive rainfall. Understanding, analyzing, and forecasting monsoons is crucial for socioeconomic sustainability and communities’ overall well-being. Climate forecasts, which project future Earth climates typically up to 2100, rely on models such as the Couple Model Intercomparison Project (CMIP). However, confidence in these forecasts remains low due to the limitations of global climate models, particularly in terms of capturing the intricacies of monsoon dynamics, notably from June to September. To address this issue, researchers have examined precipitation simulations under various future scenarios using both CMIP5 and the latest CMIP6 models. Evaluating the performance of these models from 1979 to 2014, particularly in simulating mean precipitation and temperature, has revealed improvements in multi-model ensembles (MME), highlighting advancements in monsoon characteristics. By comparing the CMIP5 and CMIP6 models, researchers have identified the most reliable models for climate downscaling research, which can provide more accurate predictions of regional climate changes, thereby offering valuable insights for enhancing climate modeling in the Indian subcontinent.
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Eyring, V., S. Bony, G. A. Meehl, et al. "Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation." Geoscientific Model Development Discussions 8, no. 12 (2015): 10539–83. http://dx.doi.org/10.5194/gmdd-8-10539-2015.
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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 experiments) and the CMIP Historical Simulation (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 the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on 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: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given 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 the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.
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Shen, Zili, Anmin Duan, Dongliang Li, and Jinxiao Li. "Assessment and Ranking of Climate Models in Arctic Sea Ice Cover Simulation: From CMIP5 to CMIP6." Journal of Climate 34, no. 9 (2021): 3609–27. http://dx.doi.org/10.1175/jcli-d-20-0294.1.
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AbstractThe capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.
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Jiang, Wenping, Ping Huang, Gang Huang, and Jun Ying. "Origins of the Excessive Westward Extension of ENSO SST Simulated in CMIP5 and CMIP6 Models." Journal of Climate 34, no. 8 (2021): 2839–51. http://dx.doi.org/10.1175/jcli-d-20-0551.1.
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AbstractAn excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.
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Maycock, Amanda C., Katja Matthes, Susann Tegtmeier, et al. "The representation of solar cycle signals in stratospheric ozone – Part 2: Analysis of global models." Atmospheric Chemistry and Physics 18, no. 15 (2018): 11323–43. http://dx.doi.org/10.5194/acp-18-11323-2018.
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Abstract. The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate simulations to aid in capturing the atmospheric response to solar cycle variability. This study presents the first systematic comparison of the representation of the 11-year solar cycle ozone response (SOR) in chemistry–climate models (CCMs) and in pre-calculated ozone databases specified in climate models that do not include chemistry, with a special focus on comparing the recommended protocols for the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6). We analyse the SOR in eight CCMs from the Chemistry–Climate Model Initiative (CCMI-1) and compare these with results from three ozone databases for climate models: the Bodeker Scientific ozone database, the SPARC/Atmospheric Chemistry and Climate (AC&amp;C) ozone database for CMIP5 and the SPARC/CCMI ozone database for CMIP6. The peak amplitude of the annual mean SOR in the tropical upper stratosphere (1–5 hPa) decreases by more than a factor of 2, from around 5 to 2 %, between the CMIP5 and CMIP6 ozone databases. This substantial decrease can be traced to the CMIP5 ozone database being constructed from a regression model fit to satellite and ozonesonde measurements, while the CMIP6 database is constructed from CCM simulations. The SOR in the CMIP6 ozone database therefore implicitly resembles the SOR in the CCMI-1 models. The structure in latitude of the SOR in the CMIP6 ozone database and CCMI-1 models is considerably smoother than in the CMIP5 database, which shows unrealistic sharp gradients in the SOR across the middle latitudes owing to the paucity of long-term ozone measurements in polar regions. The SORs in the CMIP6 ozone database and the CCMI-1 models show a seasonal dependence with enhanced meridional gradients at mid- to high latitudes in the winter hemisphere. The CMIP5 ozone database does not account for seasonal variations in the SOR, which is unrealistic. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess the atmospheric impacts of changes in the representation of the SOR and solar spectral irradiance (SSI) forcing between CMIP5 and CMIP6. The larger amplitude of the SOR in the CMIP5 ozone database compared to CMIP6 causes a likely overestimation of the modelled tropical stratospheric temperature response between 11-year solar cycle minimum and maximum by up to 0.55 K, or around 80 % of the total amplitude. This effect is substantially larger than the change in temperature response due to differences in SSI forcing between CMIP5 and CMIP6. The results emphasize the importance of adequately representing the SOR in global models to capture the impact of the 11-year solar cycle on the atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been identified, we recommend that CMIP6 models without chemistry use the CMIP6 ozone database and the CMIP6 SSI dataset to better capture the climate impacts of solar variability. The SOR coefficients from the CMIP6 ozone database are published with this paper.
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Lu, Zhichao, Tianbao Zhao, and Weican Zhou. "Evaluation of the Antarctic Circumpolar Wave Simulated by CMIP5 and CMIP6 Models." Atmosphere 11, no. 9 (2020): 931. http://dx.doi.org/10.3390/atmos11090931.
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As a coupled large-scale oceanic and atmospheric pattern in the Southern Ocean, the Antarctic circumpolar wave (ACW) has substantial impacts on the global climate. In this study, using the European Centre for Medium-Range Weather Forecasts ERA5 dataset and historical experiment outputs from 24 models of the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5/CMIP6) spanning the 1980s and 1990s, the simulation capability of models for sea-level pressure (SLP) and sea surface temperature (SST) variability of the ACW is evaluated. It is shown that most models can capture well the 50-month period of the ACW. However, many simulations show a weak amplitude, but with various phase differences. Selected models can simulate SLP better than SST, and CMIP6 models generally perform better than the CMIP5 models. The best model for SLP simulation is the CanESM5 model from CMIP6, whereas the best model for SST simulation is the ACCESS1.3 model from CMIP5. It seems that the SST simulation benefits from the inclusion of both a carbon cycle process and a chemistry module, while the SLP simulation benefits from only the chemistry module. When both SLP and SST are taken into consideration, the CanESM5 model performs the best among all the selected models.
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Karypidou, Maria Chara, Eleni Katragkou, and Stefan Pieter Sobolowski. "Precipitation over southern Africa: is there consensus among global climate models (GCMs), regional climate models (RCMs) and observational data?" Geoscientific Model Development 15, no. 8 (2022): 3387–404. http://dx.doi.org/10.5194/gmd-15-3387-2022.
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Abstract. The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modeling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behavior of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (October–March), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensembles exhibited improved performance compared to their forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher-resolution regional climate simulations. The CMIP6 ensemble displayed a similar behavior to CMIP5, but reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angola Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic processes that take place. Improvements in observational networks (both in situ and satellite) as well as continued advancements in high-resolution modeling will be critical, in order to develop a robust assessment of climate change for southern Africa.
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Kageyama, Masa, Sandy P. Harrison, Marie-L. Kapsch, et al. "The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations." Climate of the Past 17, no. 3 (2021): 1065–89. http://dx.doi.org/10.5194/cp-17-1065-2021.
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Abstract. The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.
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Mostue, Idunn Aamnes, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis. "Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5." Cryosphere 18, no. 1 (2024): 475–88. http://dx.doi.org/10.5194/tc-18-475-2024.
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Abstract. The Greenland Ice Sheet (GrIS) has been losing mass since the 1990s as a direct consequence of rising temperatures and has been projected to continue to lose mass at an accelerating pace throughout the 21st century, making it one of the largest contributors to future sea-level rise. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models produce a greater Arctic amplification signal and therefore also a notably larger mass loss from the GrIS when compared to the older CMIP5 projections, despite similar forcing levels from greenhouse gas emissions. However, it is also argued that the strength of regional factors, such as melt–albedo feedbacks and cloud-related feedbacks, will partly impact future melt and sea-level rise contribution, yet little is known about the role of these regional factors in producing differences in GrIS surface melt projections between CMIP6 and CMIP5. In this study, we use high-resolution (15 km) regional climate model simulations over the GrIS performed using the Modèle Atmosphérique Régional (MAR) to physically downscale six CMIP5 Representative Concentration Pathway (RCP) 8.5 and five CMIP6 Shared Socioeconomic Pathway (SSP) 5-8.5 extreme high-emission-scenario simulations. Here, we show a greater annual mass loss from the GrIS at the end of the 21st century but also for a given temperature increase over the GrIS, when comparing CMIP6 to CMIP5. We find a greater sensitivity of Greenland surface mass loss in CMIP6 centred around summer and autumn, yet the difference in mass loss is the largest during autumn with a reduction of 27.7 ± 9.5 Gt per season for a regional warming of +6.7 ∘C and 24.6 Gt per season more mass loss than in CMIP5 RCP8.5 simulations for the same warming. Assessment of the surface energy budget and cloud-related feedbacks suggests a reduction in high clouds during summer and autumn – despite enhanced cloud optical depth during autumn – to be the main driver of the additional energy reaching the surface, subsequently leading to enhanced surface melt and mass loss in CMIP6 compared to CMIP5. Our analysis highlights that Greenland is losing more mass in CMIP6 due to two factors: (1) a (known) greater sensitivity to greenhouse gas emissions and therefore warmer temperatures and (2) previously unnotified cloud-related surface energy budget changes that enhance the GrIS sensitivity to warming.
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Wang, Zhenchao, Lin Han, Jiayu Zheng, et al. "Evaluation of the Performance of CMIP5 and CMIP6 Models in Simulating the Victoria Mode–El Niño Relationship." Journal of Climate 34, no. 18 (2021): 7625–44. http://dx.doi.org/10.1175/jcli-d-20-0927.1.
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AbstractThe Victoria mode (VM) is the second dominant sea surface temperature mode in the North Pacific, forced by North Pacific Oscillation–like extratropical atmospheric variability. Observational studies have shown that the boreal spring VM is closely connected to the following winter El Niño, with the VM efficiently acting as a precursor signal to El Niño events. This study evaluates the relationship of the spring VM with subsequent winter El Niño in the preindustrial simulations of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). We found that most CMIP5 and CMIP6 models can simulate the basic characteristics of the VM reasonably well. The current CMIP6 models simulate the VM–El Niño connections more realistically as compared to the earlier CMIP5 models. The analysis further suggests that the improved capability of the CMIP6 models to simulate the VM–El Niño relationship is because the CMIP6 models are better able to capture the VM-related surface air–sea thermodynamic coupling process over the subtropical/tropical Pacific and the seasonal evolution of VM-related anomalous subsurface ocean temperature in the equatorial Pacific.
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Arora, Vivek K., Anna Katavouta, Richard G. Williams, et al. "Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models." Biogeosciences 17, no. 16 (2020): 4173–222. http://dx.doi.org/10.5194/bg-17-4173-2020.
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Abstract. Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
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Schiemann, Reinhard, Panos Athanasiadis, David Barriopedro, et al. "Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution." Weather and Climate Dynamics 1, no. 1 (2020): 277–92. http://dx.doi.org/10.5194/wcd-1-277-2020.
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Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.
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Döscher, Ralf, Mario Acosta, Andrea Alessandri, et al. "The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6." Geoscientific Model Development 15, no. 7 (2022): 2973–3020. http://dx.doi.org/10.5194/gmd-15-2973-2022.
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Abstract. The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
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Bracegirdle, Thomas J., Hua Lu, and Jon Robson. "Early-winter North Atlantic low-level jet latitude biases in climate models: implications for simulated regional atmosphere-ocean linkages." Environmental Research Letters 17, no. 1 (2021): 014025. http://dx.doi.org/10.1088/1748-9326/ac417f.
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Abstract Climate model biases in the North Atlantic (NA) low-level tropospheric westerly jet are a major impediment to reliably representing variability of the NA climate system and its wider influence, in particular over western Europe. A major aspect of the biases is the occurrence of a prominent early-winter equatorward jet bias in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models that has implications for NA atmosphere-ocean coupling. Here we assess whether this bias is reduced in the new CMIP6 models and assess implications for model representation of NA atmosphere-ocean linkages, in particular over the sub-polar gyre (SPG) region. Historical simulations from the CMIP5 and CMIP6 model datasets were compared against reanalysis data over the period 1861–2005. The results show that the early-winter equatorward bias remains present in CMIP6 models, although with an approximately one-fifth reduction compared to CMIP5. The equatorward bias is mainly associated with a weaker-than-observed frequency of poleward excursions of the jet to its northern position. A potential explanation is provided through the identification of a strong link between NA jet latitude bias and systematically too-weak model-simulated low-level baroclinicity over eastern North America in early-winter. CMIP models with larger equatorward jet biases exhibit weaker correlations between temporal variability in speed of the jet and sea surface conditions (sea surface temperatures and turbulent heat fluxes) over the SPG. The results imply that the early-winter equatorward bias in jet latitude in CMIP models could partially explain other known biases, such as the weaker-than-observed seasonal-decadal predictability of the NA climate system.
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Fabiano, Federico, Virna L. Meccia, Paolo Davini, Paolo Ghinassi, and Susanna Corti. "A regime view of future atmospheric circulation changes in northern mid-latitudes." Weather and Climate Dynamics 2, no. 1 (2021): 163–80. http://dx.doi.org/10.5194/wcd-2-163-2021.
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Abstract. Future wintertime atmospheric circulation changes in the Euro–Atlantic (EAT) and Pacific–North American (PAC) sectors are studied from a weather regimes perspective. The Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6) historical simulation performance in reproducing the observed regimes is first evaluated, showing a general improvement in the CMIP6 models, which is more evident for EAT. The circulation changes projected by CMIP5 and CMIP6 scenario simulations are analysed in terms of the change in the frequency and persistence of the regimes. In the EAT sector, significant positive trends are found for the frequency and persistence of NAO+ (North Atlantic Oscillation) for SSP2–4.5, SSP3–7.0 and SSP5–8.5 scenarios with a concomitant decrease in the frequency of the Scandinavian blocking and Atlantic Ridge regimes. For PAC, the Pacific Trough regime shows a significant increase, while the Bering Ridge is predicted to decrease in all scenarios analysed. The spread among the model responses is linked to different levels of warming in the polar stratosphere, the tropical upper troposphere, the North Atlantic and the Arctic.
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Paola, A. Arias, Ortega Geusep, D. Villegas Laura, and Alejandro Martínez J. "Colombian climatology in CMIP5/CMIP6 models: Persistent biases and improvements." Revista Facultad de Ingeniería, Universidad de Antioquia, no. 100 (May 3, 2021): 75–96. https://doi.org/10.17533/udea.redin.20210525.
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Northern South America is among the regions with the highest vulnerability to climate change. General Circulation Models (GCMs) are among the different tools considered to analyze the impacts of climate change. In particular, GCMs have been proved to provide useful information, although they exhibit systematic biases and fail in reproducing regional climate, particularly in terrains with complex topography. This work evaluates the performance of GCMs included in the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP), representing the annual cycle of precipitation and air surface temperature in Colombia. To evaluate this, we consider different observational and reanalysis datasets, including in situ gauges from the Colombian Meteorological Institute. Our results indicate that although the most recent generation of GCMs (CMIP6) show improvements with respect to the previous generation (CMIP5), they still have systematic biases in representing the Intertropical Convergence Zone and elevation-dependent processes, which highly determine intra-annual precipitation and air surface temperature in Colombia. In addition, CMIP6 models have larger biases in temperature over the Andes than CMIP5. We also analyze climate projections by the end of the 21st century according to the CMIP5/CMIP6 simulations under the highest greenhouse gases emission scenarios. Models show projections toward warmer air surface temperatures and mixed changes of precipitation, with decreases of precipitation over the Orinoco and Colombian Amazon in September-November and increases over the eastern equatorial Pacific during the entire year.
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Sultan, Benjamin, Aicha Ilmi Ahmed, Babacar Faye, and Yves Tramblay. "Less negative impacts of climate change on crop yields in West Africa in the new CMIP6 climate simulations ensemble." PLOS Climate 2, no. 12 (2023): e0000263. http://dx.doi.org/10.1371/journal.pclm.0000263.
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Food insecurity is among one of the greatest risks posed by climate change in Africa, where 90 to 95% of African food production is rainfed and a large proportion of the population already faces chronic hunger and malnutrition. Although, several studies have found robust evidence of future crop yield losses under climate change scenarios, there is wide variation among crops and regions as well as large modeling uncertainties. A large part of this uncertainty stems from climate projections, as climate models may differ in simulating future changes in precipitation and temperature, which could lead to different future crop production scenarios. This work examines the impacts of climate change on crop yields of maize, millet and sorghum in West Africa using climate change projections from the Coupled Model Intercomparison Project 5th Phase (CMIP5) and from the new generation of climate models from the Coupled Model Intercomparison Project 6th Phase (CMIP6). We use the SIMPLACE crop modeling framework to simulate historical and future crop yields, and bootstrap techniques to evaluate projected changes in crop productivity between the CMIP5 and CMIP6 ensembles. Using the new generation of climate models CMIP6, we find that the negative crop yield projections shown by CMIP5 simulations are largely reduced, with even large increases in crop yields when the effect of atmospheric CO2 concentration is considered in the crop model. These differences in crop yield impacts between the CMIP5 and CMIP6 simulations are mainly due to different climate projections of temperature and precipitation in West Africa; CMIP6 projections being significantly wetter and cooler by mid-century and to a lesser extent by the end of the century. Such results highlight the large uncertainties that remain in assessing the impacts of climate change in the region and the consequent difficulty for end-users to anticipate adaptation strategies.
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Xie, Bo, Hui Guo, Fanhao Meng, Chula Sa, and Min Luo. "Historical Evolution and Future Trends of Precipitation based on Integrated Datasets and Model Simulations of Arid Central Asia." Remote Sensing 15, no. 23 (2023): 5460. http://dx.doi.org/10.3390/rs15235460.
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Earth system models (ESMs) are important tools for assessing the historical characteristics and predicting the future characteristics of precipitation, yet the quantitative understanding of how these land–atmospheric coupling models perform in simulating precipitation characteristics remains limited. This study conducts a comprehensive evaluation of precipitation changes simulated by 43 ESMs in CMIP5 and 32 ESMs in CMIP6 in Arid Central Asia (ALL) and its two sub-regions for 1959–2005 with reference to Climate Research Unit (CRU) data, and predicts precipitation changes for 2054–2100. Our analyses suggest the following: (a) no single model consistently outperformed the others in all aspects of simulated precipitation variability (annual averages, long-term trends, and climatological monthly patterns); (b) the CMIP5 and CMIP6 model simulations tended to overestimate average annual precipitation for most of the ALL region, especially in the Xinjiang Uygur Autonomous Region of China (XJ); (c) most model simulations projected a stronger increasing trend in average annual precipitation; (d) although all the model simulations reasonably captured the climatological monthly precipitation, there was an underestimation; (e) compared to CMIP5, most CMIP6 model simulations exhibited an enhanced capacity to simulate precipitation across all aspects, although discrepancies persisted in individual sub-regions; (f) it was confirmed that the multi-model ensemble mean (MME) provides a more accurate representation of the three aspects of precipitation compared to the majority of single-model simulations. Lastly, the values of precipitation predicted by the more efficient models across the ALL region and its sub-regions under the different scenarios showed an increasing trend in most seasons. Notably, the strongest increasing trend in precipitation was seen under the high-emission scenarios.
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Li, Fang, Xiang Song, Sandy P. Harrison, et al. "Evaluation of global fire simulations in CMIP6 Earth system models." Geoscientific Model Development 17, no. 23 (2024): 8751–71. https://doi.org/10.5194/gmd-17-8751-2024.
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Abstract. Fire is the primary form of terrestrial ecosystem disturbance on a global scale and an important Earth system process. Most Earth system models (ESMs) have incorporated fire modeling, with 19 of them submitting model outputs of fire-related variables to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study provides the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based historical reconstructions. Our results show that most CMIP6 models simulate the present-day global burned area and fire carbon emissions within the range of satellite-based products. They also capture the major features of observed spatial patterns and seasonal cycles, the relationship of fires with precipitation and population density, and the influence of the El Niño–Southern Oscillation (ENSO) on the interannual variability of tropical fires. Regional fire carbon emissions simulated by the CMIP6 models from 1850 to 2010 generally align with the charcoal-based reconstructions, although there are regional mismatches, such as in southern South America and eastern temperate North America prior to the 1910s and in temperate North America, eastern boreal North America, Europe, and boreal Asia since the 1980s. The CMIP6 simulations have addressed three critical issues identified in CMIP5: (1) the simulated global burned area being less than half of that of the observations, (2) the failure to reproduce the high burned area fraction observed in Africa, and (3) the weak fire seasonal variability. Furthermore, the CMIP6 models exhibit improved accuracy in capturing the observed relationship between fires and both climatic and socioeconomic drivers and better align with the historical long-term trends indicated by charcoal-based reconstructions in most regions worldwide. However, the CMIP6 models still fail to reproduce the decline in global burned area and fire carbon emissions observed over the past 2 decades, mainly attributed to an underestimation of anthropogenic fire suppression, and the spring peak in fires in the Northern Hemisphere mid-latitudes, mainly due to an underestimation of crop fires. In addition, the model underestimates the fire sensitivity to wet–dry conditions, indicating the need to improve fuel wetness estimation. Based on these findings, we present specific guidance for fire scheme development and suggest a post-processing methodology for using CMIP6 multi-model outputs to generate reliable fire projection products.
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Wei, Ning, Jianyang Xia, Jian Zhou, et al. "Evolution of Uncertainty in Terrestrial Carbon Storage in Earth System Models from CMIP5 to CMIP6." Journal of Climate 35, no. 17 (2022): 5483–99. http://dx.doi.org/10.1175/jcli-d-21-0763.1.
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Abstract The spatial and temporal variations in terrestrial carbon storage play a pivotal role in regulating future climate change. However, Earth system models (ESMs), which have coupled the terrestrial biosphere and atmosphere, show great uncertainty in simulating the global land carbon storage. Here, based on multiple global datasets and a traceability analysis, we diagnosed the uncertainty source of terrestrial carbon storage in 22 ESMs that participated in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). The modeled global terrestrial carbon storage has converged among ESMs from CMIP5 (1936.9 ± 739.3 PgC) to CMIP6 (1774.4 ± 439.0 PgC) but is persistently lower than the observation-based estimates (2285 ± 669 PgC). By further decomposing terrestrial carbon storage into net primary production (NPP) and ecosystem carbon residence time (τE), we found that the decreased intermodel spread in land carbon storage primarily resulted from more accurate simulations on NPP among ESMs from CMIP5 to CMIP6. The persistent underestimation of land carbon storage was caused by the biased τE. In CMIP5 and CMIP6, the modeled τE was far shorter than the observation-based estimates. The potential reasons for the biased τE could be the lack of or incomplete representation of nutrient limitation, vertical soil biogeochemistry, and the permafrost carbon cycle. Moreover, the modeled τE became the key driver for the intermodel spread in global land carbon storage in CMIP6. Overall, our study indicates that CMIP6 models have greatly improved the terrestrial carbon cycle, with a decreased model spread in global terrestrial carbon storage and less uncertain productivity. However, more efforts are needed to understand and reduce the persistent data–model disagreement on carbon storage and residence time in the terrestrial biosphere.
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Juckes, Martin, Karl E. Taylor, Paul J. Durack, et al. "The CMIP6 Data Request (DREQ, version 01.00.31)." Geoscientific Model Development 13, no. 1 (2020): 201–24. http://dx.doi.org/10.5194/gmd-13-201-2020.
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Abstract. The data request of the Coupled Model Intercomparison Project Phase 6 (CMIP6) defines all the quantities from CMIP6 simulations that should be archived. This includes both quantities of general interest needed from most of the CMIP6-endorsed model intercomparison projects (MIPs) and quantities that are more specialized and only of interest to a single endorsed MIP. The complexity of the data request has increased from the early days of model intercomparisons, as has the data volume. In contrast with CMIP5, CMIP6 requires distinct sets of highly tailored variables to be saved from each of the more than 200 experiments. This places new demands on the data request information base and leads to a new requirement for development of software that facilitates automated interrogation of the request and retrieval of its technical specifications. The building blocks and structure of the CMIP6 Data Request (DREQ), which have been constructed to meet these challenges, are described in this paper.
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Pinheiro, Henri R., Tercio Ambrizzi, Kevin I. Hodges, and Manoel A. Gan. "Understanding the El Niño Southern Oscillation Effect on Cut-Off Lows as Simulated in Forced SST and Fully Coupled Experiments." Atmosphere 13, no. 8 (2022): 1167. http://dx.doi.org/10.3390/atmos13081167.
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In this study, we show that changes in the 250 hPa vorticity cut-off low (COL) activity may possibly be driven by sea surface temperature (SST) variations in the tropical Pacific. Using ERA5 reanalysis, the existence of different large-scale circulation patterns is identified that work to enhance the COL activity with a weakened jet stream, while COLs are suppressed with strengthened westerlies. The present-day simulations of AMIP-CMIP6 models reproduce realistic features of the El Niño Southern Oscillation (ENSO)–COL teleconnection, but biases exist, especially in coupled models. The differences are a priori due to the inability of the models to accurately predict the time-mean zonal flow, which may be in part due to systematic biases in the predicted SST. The underestimation of warm SST anomalies over the eastern Pacific is a common problem in CMIP3 and CMIP5 models and remains a major uncertainty in CMIP6. We find that a reduced bias in the predicted SST by coupled models is most likely to produce more skillful simulations in the Southern Hemisphere, but the same evidence does not hold for the Northern Hemisphere. The study suggests the potential for seasonal prediction of COLs and the benefits that would result using accurate initialization and consistent model coupling.
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Zhang, Jie, Tongwen Wu, Fang Zhang, et al. "BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP)." Advances in Atmospheric Sciences 38, no. 2 (2021): 317–28. http://dx.doi.org/10.1007/s00376-020-0151-2.
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AbstractBCC-ESM1 is the first version of the Beijing Climate Center’s Earth System Model, and is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is the only CMIP6-endorsed MIP in which BCC-ESM1 is involved. All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted. The DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations have also been run as the entry card of CMIP6. The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies. To facilitate the use of the BCC-ESM1 datasets, this study describes the experiment settings and summarizes the model outputs in detail. Preliminary evaluations of BCC-ESM1 are also presented, revealing that: the climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5; the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured, despite some common precipitation biases as in CMIP5 and CMIP6 models; a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1, as in most other ESMs; and the mean states of surface sulfate concentrations can also be reasonably reproduced, as well as their temporal evolution at regional scales. These datasets have been archived on the Earth System Grid Federation (ESGF) node for atmospheric chemistry studies.
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Gier, Bettina K., Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring. "Spatially resolved evaluation of Earth system models with satellite column-averaged CO<sub>2</sub>." Biogeosciences 17, no. 23 (2020): 6115–44. http://dx.doi.org/10.5194/bg-17-6115-2020.
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Abstract. Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO2 concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate emission-driven CMIP5 and CMIP6 simulations with satellite data of column-average CO2 mole fractions (XCO2). XCO2 time series show a large spread among the model ensembles both in CMIP5 and CMIP6. Compared to the satellite observations, the models have a bias of +25 to −20 ppmv in CMIP5 and +20 to −15 ppmv in CMIP6, with the multi-model mean biases at +10 and +2 ppmv, respectively. The derived mean atmospheric XCO2 growth rate (GR) of 2.0 ppmv yr−1 is overestimated by 0.4 ppmv yr−1 in CMIP5 and 0.3 ppmv yr−1 in CMIP6 for the multi-model mean, with a good reproduction of the interannual variability. All models capture the expected increase of the seasonal cycle amplitude (SCA) with increasing latitude, but most models underestimate the SCA. Any SCA derived from data with missing values can only be considered an “effective” SCA, as the missing values could occur at the peaks or troughs. The satellite data are a combined data product covering the period 2003–2014 based on the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat (2003–2012) and Thermal And Near infrared Sensor for carbon Observation Fourier transform spectrometer/Greenhouse Gases Observing Satellite (TANSO-FTS/GOSAT) (2009–2014) instruments. While the combined satellite product shows a strong negative trend of decreasing effective SCA with increasing XCO2 in the northern midlatitudes, both CMIP ensembles instead show a non-significant positive trend in the multi-model mean. The negative trend is reproduced by the models when sampling them as the observations, attributing it to sampling characteristics. Applying a mask of the mean data coverage of each satellite to the models, the effective SCA is higher for the SCIAMACHY/Envisat mask than when using the TANSO-FTS/GOSAT mask. This induces an artificial negative trend when using observational sampling over the full period, as SCIAMACHY/Envisat covers the early period until 2012, with TANSO-FTS/GOSAT measurements starting in 2009. Overall, the CMIP6 ensemble shows better agreement with the satellite data than the CMIP5 ensemble in all considered quantities (XCO2, GR, SCA and trend in SCA). This study shows that the availability of column-integral CO2 from satellite provides a promising new way to evaluate the performance of Earth system models on a global scale, complementing existing studies that are based on in situ measurements from single ground-based stations.
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Haarsma, Reindert J., Malcolm J. Roberts, Pier Luigi Vidale, et al. "High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6." Geoscientific Model Development 9, no. 11 (2016): 4185–208. http://dx.doi.org/10.5194/gmd-9-4185-2016.
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Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.
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Nowicki, Sophie, Heiko Goelzer, Hélène Seroussi, et al. "Experimental protocol for sea level projections from ISMIP6 stand-alone ice sheet models." Cryosphere 14, no. 7 (2020): 2331–68. http://dx.doi.org/10.5194/tc-14-2331-2020.
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Abstract. Projection of the contribution of ice sheets to sea level change as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the form of simulations from coupled ice sheet–climate models and stand-alone ice sheet models, overseen by the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). This paper describes the experimental setup for process-based sea level change projections to be performed with stand-alone Greenland and Antarctic ice sheet models in the context of ISMIP6. The ISMIP6 protocol relies on a suite of polar atmospheric and oceanic CMIP-based forcing for ice sheet models, in order to explore the uncertainty in projected sea level change due to future emissions scenarios, CMIP models, ice sheet models, and parameterizations for ice–ocean interactions. We describe here the approach taken for defining the suite of ISMIP6 stand-alone ice sheet simulations, document the experimental framework and implementation, and present an overview of the ISMIP6 forcing to be used by participating ice sheet modeling groups.
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Kittel, Christoph, Charles Amory, Cécile Agosta, et al. "Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet." Cryosphere 15, no. 3 (2021): 1215–36. http://dx.doi.org/10.5194/tc-15-1215-2021.
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Abstract. The future surface mass balance (SMB) will influence the ice dynamics and the contribution of the Antarctic ice sheet (AIS) to the sea level rise. Most of recent Antarctic SMB projections were based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5). However, new CMIP6 results have revealed a +1.3 ∘C higher mean Antarctic near-surface temperature than in CMIP5 at the end of the 21st century, enabling estimations of future SMB in warmer climates. Here, we investigate the AIS sensitivity to different warmings with an ensemble of four simulations performed with the polar regional climate model Modèle Atmosphérique Régional (MAR) forced by two CMIP5 and two CMIP6 models over 1981–2100. Statistical extrapolation enables us to expand our results to the whole CMIP5 and CMIP6 ensembles. Our results highlight a contrasting effect on the future grounded ice sheet and the ice shelves. The SMB over grounded ice is projected to increase as a response to stronger snowfall, only partly offset by enhanced meltwater run-off. This leads to a cumulated sea-level-rise mitigation (i.e. an increase in surface mass) of the grounded Antarctic surface by 5.1 ± 1.9 cm sea level equivalent (SLE) in CMIP5-RCP8.5 (Relative Concentration Pathway 8.5) and 6.3 ± 2.0 cm SLE in CMIP6-ssp585 (Shared Socioeconomic Pathways 585). Additionally, the CMIP6 low-emission ssp126 and intermediate-emission ssp245 scenarios project a stabilized surface mass gain, resulting in a lower mitigation to sea level rise than in ssp585. Over the ice shelves, the strong run-off increase associated with higher temperature is projected to decrease the SMB (more strongly in CMIP6-ssp585 compared to CMIP5-RCP8.5). Ice shelves are however predicted to have a close-to-present-equilibrium stable SMB under CMIP6 ssp126 and ssp245 scenarios. Future uncertainties are mainly due to the sensitivity to anthropogenic forcing and the timing of the projected warming. While ice shelves should remain at a close-to-equilibrium stable SMB under the Paris Agreement, MAR projects strong SMB decrease for an Antarctic near-surface warming above +2.5 ∘C compared to 1981–2010 mean temperature, limiting the warming range before potential irreversible damages on the ice shelves. Finally, our results reveal the existence of a potential threshold (+7.5 ∘C) that leads to a lower grounded-SMB increase. This however has to be confirmed in following studies using more extreme or longer future scenarios.
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Zhu, Yuchao, Rong-Hua Zhang, and Jichang Sun. "North Pacific Upper-Ocean Cold Temperature Biases in CMIP6 Simulations and the Role of Regional Vertical Mixing." Journal of Climate 33, no. 17 (2020): 7523–38. http://dx.doi.org/10.1175/jcli-d-19-0654.1.
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AbstractSubstantial model biases are still prominent even in the latest CMIP6 simulations; attributing their causes is defined as one of the three main scientific questions addressed in CMIP6. In this paper, cold temperature biases in the North Pacific subtropics are investigated using simulations from the newly released CMIP6 models, together with other related modeling products. In addition, ocean-only sensitivity experiments are performed to characterize the biases, with a focus on the role of oceanic vertical mixing schemes. Based on the Argo-derived diffusivity, idealized vertical diffusivity fields are designed to mimic the seasonality of vertical mixing in this region, and are employed in ocean-only simulations to test the sensitivity of this cold bias to oceanic vertical mixing. It is demonstrated that the cold temperature biases can be reduced when the mixing strength is enhanced within and beneath the surface boundary layer. Additionally, the temperature simulations are rather sensitive to the parameterization of static instability, and the cold biases can be reduced when the vertical diffusivity for convection is increased. These indicate that the cold temperature biases in the North Pacific can be largely attributed to biases in oceanic vertical mixing within ocean-only simulations, which likely contribute to the even larger biases seen in coupled simulations. This study therefore highlights the need for improved oceanic vertical mixing in order to reduce these persistent cold temperature biases seen across several CMIP models.
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Liang, Ziling, Fangrui Zhu, Tian Liang, Fuhai Luo, and Jiali Luo. "Spatiotemporal Distribution of CO in the UTLS Region in the Asian Summer Monsoon Season: Analysis of MLS Observations and CMIP6 Simulations." Remote Sensing 15, no. 2 (2023): 367. http://dx.doi.org/10.3390/rs15020367.
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In this study, CO is used as a tracer to evaluate the chemical field related to the Asian summer monsoon anticyclone (ASMA) in the upper troposphere and lower stratosphere (UTLS) region simulated by Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models from a multi-spatiotemporal perspective. The results show that the simulations of the six selected CMIP6 global climate models are well correlated with the MLS observations, while each model has its own advantages and disadvantages in the simulation of the ASMA and related chemical and geopotential height fields. Compared with MLS data, all six CMIP6 models can reasonably simulate the high CO values and the corresponding anticyclone, although certain biases exist in the simulations. Each model output has certain degrees of deviation in the simulation of the ASMA center position. In terms of time series, the six CMIP6 global models all exhibit an interannual variation CO mixing ratio over the ASM region while the interannual variation features are different from that in MLS. In general, it is impossible to identify a single determined model that can well reproduce the observations. In future work to assess the development trend and location of the ASMA, simulations of CESM2-WACCM and GFDL-ESM4 might be used due to their better performance than other models.
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Griffiths, Paul T., Lee T. Murray, Guang Zeng, et al. "Tropospheric ozone in CMIP6 simulations." Atmospheric Chemistry and Physics 21, no. 5 (2021): 4187–218. http://dx.doi.org/10.5194/acp-21-4187-2021.
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Abstract. The evolution of tropospheric ozone from 1850 to 2100 has been studied using data from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). We evaluate long-term changes using coupled atmosphere–ocean chemistry–climate models, focusing on the CMIP Historical and ScenarioMIP ssp370 experiments, for which detailed tropospheric-ozone diagnostics were archived. The model ensemble has been evaluated against a suite of surface, sonde and satellite observations of the past several decades and found to reproduce well the salient spatial, seasonal and decadal variability and trends. The multi-model mean tropospheric-ozone burden increases from 247 ± 36 Tg in 1850 to a mean value of 356 ± 31 Tg for the period 2005–2014, an increase of 44 %. Modelled present-day values agree well with previous determinations (ACCENT: 336 ± 27 Tg; Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP: 337 ± 23 Tg; Tropospheric Ozone Assessment Report, TOAR: 340 ± 34 Tg). In the ssp370 experiments, the ozone burden increases to 416 ± 35 Tg by 2100. The ozone budget has been examined over the same period using lumped ozone production (PO3) and loss (LO3) diagnostics. Both ozone production and chemical loss terms increase steadily over the period 1850 to 2100, with net chemical production (PO3-LO3) reaching a maximum around the year 2000. The residual term, which contains contributions from stratosphere–troposphere transport reaches a minimum around the same time before recovering in the 21st century, while dry deposition increases steadily over the period 1850–2100. Differences between the model residual terms are explained in terms of variation in tropopause height and stratospheric ozone burden.
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Holland, Marika M., Cecile Hannay, John Fasullo, et al. "New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model." Geoscientific Model Development 17, no. 4 (2024): 1585–602. http://dx.doi.org/10.5194/gmd-17-1585-2024.
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Abstract. Climate simulation uncertainties arise from internal variability, model structure, and external forcings. Model intercomparisons (such as the Coupled Model Intercomparison Project; CMIP) and single-model large ensembles have provided insight into uncertainty sources. Under the Community Earth System Model (CESM) project, large ensembles have been performed for CESM2 (a CMIP6-era model) and CESM1 (a CMIP5-era model). We refer to these as CESM2-LE and CESM1-LE. The external forcing used in these simulations has changed to be consistent with their CMIP generation. As a result, differences between CESM2-LE and CESM1-LE ensemble means arise from changes in both model structure and forcing. Here we present new ensemble simulations which allow us to separate the influences of these model structural and forcing differences. Our new CESM2 simulations are run with CMIP5 forcings equivalent to those used in the CESM1-LE. We find a strong influence of historical forcing uncertainty due to aerosol effects on simulated climate. For the historical period, forcing drives reduced global warming and ocean heat uptake in CESM2-LE relative to CESM1-LE that is counteracted by the influence of model structure. The influence of the model structure and forcing vary across the globe, and the Arctic exhibits a distinct signal that contrasts with the global mean. For the 21st century, the importance of scenario forcing differences (SSP3–7.0 for CESM2-LE and RCP8.5 for CESM1-LE) is evident. The new simulations presented here allow us to diagnose the influence of model structure on 21st century change, despite large scenario forcing differences, revealing that differences in the meridional distribution of warming are caused by model structure. Feedback analysis reveals that clouds and their impact on shortwave radiation explain many of these structural differences between CESM2 and CESM1. In the Arctic, albedo changes control transient climate evolution differences due to structural differences between CESM2 and CESM1.
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Davini, Paolo, and Fabio D’Andrea. "From CMIP3 to CMIP6: Northern Hemisphere Atmospheric Blocking Simulation in Present and Future Climate." Journal of Climate 33, no. 23 (2020): 10021–38. http://dx.doi.org/10.1175/jcli-d-19-0862.1.
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AbstractA comprehensive analysis of the representation of winter and summer Northern Hemisphere atmospheric blocking in global climate simulations in both present and future climate is presented. Three generations of climate models are considered: CMIP3 (2007), CMIP5 (2012), and CMIP6 (2019). All models show common and extended underestimation of blocking frequencies, but a reduction of the negative biases in successive model generations is observed. However, in some specific regions and seasons such as the winter European sector, even CMIP6 models are not yet able to achieve the observed blocking frequency. For future decades the vast majority of models simulate a decrease of blocking frequency in both winter and summer, with the exception of summer blocking over the Urals and winter blocking over western North America. Winter predicted decreases may be even larger than currently estimated considering that models with larger blocking frequencies, and hence generally smaller errors, show larger reduction. Nonetheless, trends computed over the historical period are weak and often contrast with observations: this is particularly worrisome for summer Greenland blocking where models and observations significantly disagree. Finally, the intensity of global warming is related to blocking changes: wintertime European and North Pacific blocking are expected to decrease following larger global mean temperatures, while Ural summer blocking is expected to increase.
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Rackow, Thomas, Dmitry V. Sein, Tido Semmler, et al. "Sensitivity of deep ocean biases to horizontal resolution in prototype CMIP6 simulations with AWI-CM1.0." Geoscientific Model Development 12, no. 7 (2019): 2635–56. http://dx.doi.org/10.5194/gmd-12-2635-2019.
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Abstract. Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show substantial biases in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. Here, we analyze the influence of horizontal resolution in a hierarchy of five multi-resolution simulations with the AWI Climate Model (AWI-CM), the climate model used at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, which employs a sea ice–ocean model component formulated on unstructured meshes. The ocean grid sizes considered range from a nominal resolution of ∼1∘ (CMIP5 type) up to locally eddy resolving. We show that increasing ocean resolution locally to resolve ocean eddies leads to reductions in deep ocean biases, although these improvements are not strictly monotonic for the five different ocean grids. A detailed diagnosis of the simulations allows to identify the origins of the biases. We find that two key regions at the surface are responsible for the development of the deep bias in the Atlantic Ocean: the northeastern North Atlantic and the region adjacent to the Strait of Gibraltar. Furthermore, the Southern Ocean density structure is equally improved with locally explicitly resolved eddies compared to parameterized eddies. Part of the bias reduction can be traced back towards improved surface biases over outcropping regions, which are in contact with deeper ocean layers along isopycnal surfaces. Our prototype simulations provide guidance for the optimal choice of ocean grids for AWI-CM to be used in the final runs for phase 6 of CMIP (CMIP6) and for the related flagship simulations in the High Resolution Model Intercomparison Project (HighResMIP). Quite remarkably, retaining resolution only in areas of high eddy activity along with excellent scalability characteristics of the unstructured-mesh sea ice–ocean model enables us to perform the multi-centennial climate simulations needed in a CMIP context at (locally) eddy-resolving resolution with a throughput of 5–6 simulated years per day.
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Bock, Lisa, and Axel Lauer. "Cloud properties and their projected changes in CMIP models with low to high climate sensitivity." Atmospheric Chemistry and Physics 24, no. 3 (2024): 1587–605. http://dx.doi.org/10.5194/acp-24-1587-2024.
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Abstract. Since the release of the first Coupled Model Intercomparison Project version 6 (CMIP6) simulations, one of the most discussed topics is the higher effective climate sensitivity (ECS) of some of the models, resulting in an increased range of ECS values in CMIP6 compared to previous CMIP phases. An important contribution to ECS is the cloud climate feedback. Although climate models have continuously been developed and improved over the last few decades, a realistic representation of clouds remains challenging. Clouds contribute to the large uncertainties in modeled ECS, as projected changes in cloud properties and cloud feedbacks also depend on the simulated present-day fields. In this study, we investigate the representation of both cloud physical and radiative properties from a total of 51 CMIP5 and CMIP6 models. ECS is used as a simple metric to group the models, as the sensitivity of the physical cloud properties to warming is closely related to cloud feedbacks, which in turn are known to have a large contribution to ECS. Projected changes in the cloud properties in future scenario simulations are analyzed by the ECS group. In order to help with interpreting the projected changes, model results from historical simulations are also analyzed. The results show that differences in the net cloud radiative effect as a reaction to warming among the three model groups are driven by changes in a range of cloud regimes rather than individual regions. In polar regions, high-ECS models show a weaker increase in the net cooling effect of clouds, due to warming, than the low-ECS models. At the same time, high-ECS models show a decrease in the net cooling effect of clouds over the tropical ocean and the subtropical stratocumulus regions, whereas low-ECS models show either little change or even an increase in the cooling effect. Over the Southern Ocean, the low-ECS models show a higher sensitivity of the net cloud radiative effect to warming than the high-ECS models.
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Jones, Chris D., Vivek Arora, Pierre Friedlingstein, et al. "C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6." Geoscientific Model Development 9, no. 8 (2016): 2853–80. http://dx.doi.org/10.5194/gmd-9-2853-2016.
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Abstract. Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate–carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate–carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.
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Zhao, Siyi, Jiankai Zhang, Chongyang Zhang, et al. "Evaluating Long-Term Variability of the Arctic Stratospheric Polar Vortex Simulated by CMIP6 Models." Remote Sensing 14, no. 19 (2022): 4701. http://dx.doi.org/10.3390/rs14194701.
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The Arctic stratospheric polar vortex is a key component of the climate system, which has significant impacts on surface temperatures in the mid-latitudes and polar regions. Therefore, understanding polar vortex variability is helpful for extended-range weather forecasting. The present study evaluates long-term changes in the position and strength of the polar vortex in the Arctic lower stratosphere during the winters from 1980/81 to 2013/14. Simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models are compared with Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2) reanalysis dataset. Overall, the CMIP6 models well capture the spatial characteristics of the polar vortex with spatial correlation coefficients between the potential vorticity (PV) in the lower stratosphere from simulations and MERRA2 products generally greater than 0.85 for all CMIP6 models during winter. There is a good agreement in the position and shape of the polar vortex between the CMIP6 multi-model mean and MERRA2, although there exist differences between simulations of individual CMIP6 models. However, most CMIP6 models underestimate the strength of polar vortex in the lower stratosphere, with the largest negative bias up to about −20%. The present study further reveals that there is an anticorrelation between the polar vortex strength bias and area bias simulated by CMIP6 models. In addition, there is a positive correlation between the trend of EP-flux divergence for wavenumber one accumulated in early winter and the trend in zonal mean zonal wind averaged in late winter. As for the long-term change in polar vortex position, CanESM5, IPSL-CM5A2-INCA, UKESM1-0-LL, and IPSL-CM6A-LR well capture the persistent shift of polar vortex towards the Eurasian continent and away from North America in February, which has been reported in observations. These models reproduce the positive trend of wavenumber-1 planetary waves since the 1980s seen in the MERRA2 dataset. This suggests that realistic wave activity processes in CMIP6 models play a key role not only in the simulation of the strength of the stratospheric polar vortex but also in the simulation of the polar vortex position shift.
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Priestley, Matthew D. K., Duncan Ackerley, Jennifer L. Catto, Kevin I. Hodges, Ruth E. McDonald, and Robert W. Lee. "An Overview of the Extratropical Storm Tracks in CMIP6 Historical Simulations." Journal of Climate 33, no. 15 (2020): 6315–43. http://dx.doi.org/10.1175/jcli-d-19-0928.1.
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AbstractThe representation of the winter and summer extratropical storm tracks in both hemispheres is evaluated in detail for the available models in phase 6 of the Coupled Model intercomparison Project (CMIP6). The state of the storm tracks from 1979 to 2014 is compared to that in ERA5 using a Lagrangian objective cyclone tracking algorithm. It is found that the main biases present in the previous generation of models (CMIP5) still persist, albeit to a lesser extent. The equatorward bias around the SH is much reduced and there appears to be some improvement in mean biases with the higher-resolution models, such as the zonal tilt of the North Atlantic storm track. Low-resolution models have a tendency to underestimate the frequency of high-intensity cyclones with all models simulating a peak intensity that is too low for cyclones in the SH. Explosively developing cyclones are underestimated across all ocean basins and in both hemispheres. In particular the models struggle to capture the rapid deepening required for these cyclones. For all measures, the CMIP6 models exhibit an overall improvement compared to the previous generation of CMIP5 models. In the NH most improvements can be attributed to increased horizontal resolution, whereas in the SH the impact of resolution is less apparent and any improvements are likely a result of improved model physics.
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Graffino, Giorgio, Riccardo Farneti, and Fred Kucharski. "Low-frequency variability of the Pacific Subtropical Cells as reproduced by coupled models and ocean reanalyses." Climate Dynamics 56, no. 9-10 (2021): 3231–54. http://dx.doi.org/10.1007/s00382-021-05639-6.
Full textAbstract:
AbstractLow-frequency variability of the Pacific Subtropical Cells (STCs) is investigated using outputs from several models included in the two latest phases of Coupled Model Intercomparison Project (CMIP), CMIP5 and CMIP6, as well as ocean reanalysis products. Our analysis focuses on historical simulations and an idealised future scenario integration. Mass and heat transport diagnostics are employed to assess how coupled models and ocean reanalyses reproduce Pacific STCs total and interior transport convergence at the equator and their relationship with equatorial Pacific sea surface temperature (SST). Trends of mass and heat transport are also evaluated, in order to study how the STCs are expected to change in a warming climate. A large spread is obtained across models in simulated mass transports, confirming that coupled models do not agree on reproducing observed Pacific STCs dynamics, with very limited improvement by CMIP6 models. Compared to ocean reanalysis products, coupled models tend to underestimate the STCs interior transport convergence, and are less efficient on propagating the signal generated by the subtropical wind stress towards the equator. Also, mass transport obtained from ocean reanalyses exhibit larger variability, and these products also better reproduce the STCs-SST relationship. Future scenario simulations suggest a weakening (strengthening) of the heat transport by the North (South) Pacific cell under warmer conditions, with a general agreement across models. Equatorward mass transport trends do not confirm this for total and interior components, but they do for the western boundary component.
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Zhao, Yaodi, and De-Zheng Sun. "ENSO Asymmetry in CMIP6 Models." Journal of Climate 35, no. 17 (2022): 5555–72. http://dx.doi.org/10.1175/jcli-d-21-0835.1.
Full textAbstract:
Abstract An interesting aspect of the El Niño–Southern Oscillation (ENSO) phenomenon is the asymmetry between its two phases. This paper evaluates the simulations of this property of ENSO by the Coupled Model Intercomparison Project phase 6 (CMIP6) models. Both the surface and subsurface signals of ENSO are examined for this purpose. The results show that the models still underestimate ENSO asymmetry as shown in the SST field, but do a better job in the subsurface. A much weaker negative feedback from the net surface heat flux during La Niña in the models is identified as a factor causing the degradation of the ENSO asymmetry at the surface. The simulated asymmetry in the subsurface is still weaker than the observations owing to a weaker dynamic coupling between the atmosphere and ocean. Consistent with the finding of a weaker dynamic coupling strength, the precipitation response to the SST changes is also found to be weaker in the models. The results underscore that a more objective assessment of the simulation of ENSO by climate models may have to involve the examination of the subsurface signals. Future improvements in simulating ENSO will likely require a better simulation of the surface heat flux feedback from the atmosphere as well as the dynamical coupling strength between the atmosphere and ocean. Significance Statement The ENSO phenomenon affects weather and climate worldwide. An interesting aspect of this phenomenon is the asymmetry between its two phases. Previous studies have reported a weaker asymmetry in the simulations by climate models. But these studies have focused on the ENSO asymmetry at the surface. Here by examining the ENSO asymmetry at the surface and the subsurface, we have found that ENSO asymmetry is better simulated in the subsurface than at the surface. We have also identified factors that are responsible for the degradation of the ENSO asymmetry at the surface as well as the remaining weakness in the subsurface, pointing out specific pathways to take to further improve ENSO simulations by coupled climate models.