INM INM-CM5-0 model output prepared for CMIP6 ScenarioMIP

Volodin, Evgeny; Mortikov, Evgeny; Gritsun, Andrey; Lykossov, Vasily; Galin, Vener; Diansky, Nikolay; Gusev, Anatoly; Kostrykin, Sergey; Iakovlev, Nikolay; Shestakova, Anna; Emelina, Svetlana

doi:10.22033/esgf/cmip6.12322

Cited by 8 publications

(2 citation statements)

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“…All CMIP6 data used in this study are freely available via DOI links provided in the references section: ACCESS-CM2 (Dix et al, 2019); ACCESS-ESM1-5 (Ziehn et al, 2019); AWI-CM-1-1-MR (Semmler et al, 2019); CNRM-CM6-1 (Voldoire, 2019); CNRM-ESM2-1 (Seferian, 2019); CanESM5 (Swart et al, 2019); EC-Earth3 (EC-Earth, 2019a); EC-Earth3-Veg (EC-Earth, 2019b); FGOALS-g3 (Li, 2019); GISS-E2-1-G (NASA/GISS, 2020a); GISS-E2-1-H (NASA/GISS, 2020b); INM-CM5-0 (Volodin et al, 2019); IPSL-CM6A-LR (Boucher et al, 2019); MIROC-ES2L (Tachiiri et al, 2019); MPI-ESM1-2-HR (Schupfner et al, 2019); MPI-ESM1-2-LR (Wieners et al, 2019); MRI-ESM2-0 (Yukimoto et al, 2019); and UKESM1-0-LL (Good et al, 2019).…”

Section: Data Availability Statementmentioning

confidence: 99%

Variability in Projected North American Mean and Extreme Temperature and Precipitation Trends for the 21st Century: Model‐To‐Model Differences Versus Internal Variability

2023

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While climate change is expected to alter mean and extreme temperature and precipitation over the 21st century, regional changes in these fields remain difficult to project. For a given future emissions scenario, the uncertainty in future projections can be attributed to either model‐to‐model differences, which can presumably be reduced if models are improved, or internal variability, which cannot be constrained to a single outcome but can be used to quantify a range of plausible outcomes. This study examines the range of possible trends in North American mean and extreme temperature and precipitation across phase 6 of the Coupled Model Intercomparison Project models under the SSP3‐7.0 emissions scenario. While model‐to‐model differences primarily govern the spread in mean and extreme temperature trends across these model simulations, the spread in mean and extreme precipitation trends is dominated by internal variability in many regions. A storylines approach—a type of regression‐based analysis—is used to identify key dynamical drivers that explain the variance in future trends across model simulations. The dynamical drivers considered include trends in global mean surface temperature (GMST) and four common modes of climate variability. Combinations of these drivers can reinforce each other to create high‐impact storylines. For example, model simulations with large positive GMST and El Niño‐Southern Oscillation trends are associated with a large reduction in the annual maximum number of consecutive dry days in the American Southwest. However, limiting these storylines to only models with climate sensitivities consistent with observational constraints reduces the likelihood of a large reduction of consecutive dry days in this region.

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Section: Data Availability Statementmentioning

confidence: 99%

Variability in Projected North American Mean and Extreme Temperature and Precipitation Trends for the 21st Century: Model‐To‐Model Differences Versus Internal Variability

2023

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“…The solar radiation data for driving Carnegie-Ames-Stanford approach (CASA) are acquired from the Global Land Surface Satellite Downward Shortwave Radiation data set (GLASS DSR), which are available at https:// www.geodata.cn/thematicView/GLASS.html. The future meteorological conditions were acquired from 16 Earth system models (ESMs) which simulated four different future climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) as part of CMIP6, which are available in Boucher et al (2019), Dix et al (2019), EC-Earth (2019), Good et al (2019), Lovato et al (2021; Schupfner et al (2021), Schupfner et al (2019), Seferian (2019), Swart et al (2019), Tachiiri et al (2019), Voldoire (2019aVoldoire ( , 2019b, Volodin et al (2019aVolodin et al ( , 2019b, Xin et al (2019), andZiehn et al (2019). The RF was built according to scikit-learn 1.3.0 (Pedregosa et al, 2011), available at https:// scikit-learn.org/stable/.…”

Section: Data Availability Statementmentioning

confidence: 99%

Natural Vegetation Succession Under Climate Change and the Combined Effects on Net Primary Productivity

Zhang,

Hao,

Zhao

et al. 2023

Earth's Future

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Climate change and the resulting natural vegetation succession can alter vegetation productivity. However, the mechanisms underlying future productivity changes under the two influences remain unclear. Here, we used the comprehensive sequence classification system to simulate changes in global potential natural vegetation under different climate scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5), and combined the Carnegie–Ames–Stanford Approach model with random forest to assess the response of net primary productivity (NPP) to climate change and vegetation succession from 2020 to 2100. Except for SSP126, terrestrial NPP in 2100 decreased by 0.86, 2.39, and 2.54 Pg C·a−1 versus 2020 under SSP2‐4.5, SSP5‐8.5, and SSP3‐7.0, respectively. Forest was the primary contributor to terrestrial NPP changes. The total forest area was projected to increase under all scenarios, with SSP2‐4.5 showing the largest increase (358.57 × 104 km2). However, expanding forest regions exhibited a relatively low mean NPP, while stable regions demonstrated a declining pattern. Consequently, forest NPP increased under SSP1‐2.6 but decreased by 4.03, 3.43, and 0.82 Pg C·a−1 in 2100 versus 2020 under SSP5‐8.5, SSP3‐7.0, and SSP2‐4.5, respectively. In comparison, grassland and desert exerted minor influence on terrestrial NPP changes, their total NPP decreased only under the SSP1‐2.6 scenario. The grassland area decreased, but the mean NPP increased, whereas the desert area expanded, resulting in consistent changes in both total and mean NPP. Our results analyzed the effects of climate change and vegetation distribution under its influence on the change of NPP, which can deepen our understanding of their relationship.

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Exploring the impact of a frontal ablation parameterization on projected 21st-century mass change for Northern Hemisphere glaciers

et al. 2023

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Marine-terminating glaciers cover more than one-fourth of the total glacierized area in the Northern Hemisphere outside the Greenland ice sheet. It is therefore crucial to ensure an adequate representation of these glaciers when projecting large-scale glacier mass changes. We investigate how the introduction of marine frontal processes in the modeling chain influences the results of mass change projections, compared to projections neglecting such processes. We find that including frontal processes reduces the projected glacier mass loss, since incorporating frontal ablation in the model's mass-balance calibration results in a decrease in marine-terminating glaciers’ sensitivity to atmospheric temperatures. We also find that retrograde bed slopes lead to increased frontal ablation as the atmosphere warms, while frontal ablation decreases if bed slopes are prograde. These opposing effects have the potential to partly cancel each other when considering large glacier ensembles. Although we do not account for potential future changes in oceanic climate yet, any effect of these would be moderated by around half of today's marine-terminating glaciers becoming land-terminating in the course of the 21st century. While we find a significant influence of ice flow parameters on our results, boundary conditions remain the largest source of uncertainty in our projections.

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INM INM-CM5-0 model output prepared for CMIP6 ScenarioMIP

Cited by 8 publications

References 0 publications

Variability in Projected North American Mean and Extreme Temperature and Precipitation Trends for the 21st Century: Model‐To‐Model Differences Versus Internal Variability

Variability in Projected North American Mean and Extreme Temperature and Precipitation Trends for the 21st Century: Model‐To‐Model Differences Versus Internal Variability

Natural Vegetation Succession Under Climate Change and the Combined Effects on Net Primary Productivity

Exploring the impact of a frontal ablation parameterization on projected 21st-century mass change for Northern Hemisphere glaciers

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