CMIP5 Projections Research Articles

Early- and late-winter ENSO teleconnections to the Euro-Atlantic region in state-of-the-art seasonal forecasting systems

A number of recent studies have highlighted the differences in the northern extratropical response to the El Niño-Southern Oscillation (ENSO) during the early and late part of the boreal cold season, particularly over the North Atlantic/European (NAE) region. Diagnostic analyses of multi-decadal GCM simulations performed as a part of CMIP5 and CMIP6 projects have shown that early winter tropical teleconnections are usually simulated with lower fidelity than their late-winter equivalents. Although some results from individual seasonal forecasting systems have been published on this topic, it is still unclear to what extent the problems detected in multi-decadal simulations also affect initialised seasonal forecasts from state-of-the art models. In this study, we diagnose ENSO teleconnections from the re-forecast ensembles of nine models contributing (during winter 2021/22) to the multi-model seasonal forecasting system of the Copernicus Climate Change Service (C3S). The re-forecasts cover winters from 1993/94 to 2016/17, and are archived in the C3S Climate Data Store. Regression and composite patterns of 500-hPa height are computed separately for El Niño and La Niña winters, based on 2-month averages in November–December (ND) and January–February (JF). Model results are compared with the corresponding patterns derived from the ERA5 re-analysis. Signal-to-noise ratios are computed from time series of projections of individual winter anomalies onto the ENSO regression patterns. The results of this study indicate that initialised seasonal forecasts exhibit similar deficiencies to those already diagnosed in multi-decadal simulations, with a significant underestimation of the amplitude of early-winter teleconnections between ENSO and the NAE circulation, and of the signal-to-noise ratio in the early-winter response to El Niño. Further diagnostics highlight the impact of mis-representing the constructive interference of teleconnections from the Indian and Pacific Oceans in the early-winter ENSO response over the North Atlantic.

Updating the intensity-duration-frequency curves in major Canadian cities under changing climate using CMIP5 and CMIP6 model projections

Characteristics of extreme rainfall events are often presented using the Intensity-Duration-Frequency (IDF) curves. As Canada gets warmer, the credibility of using historical IDF curves for flood risk analysis and design of various urban infrastructure becomes questionable. This study aims at updating and intercomparing the IDF curves in 30 Canadian cities using the simulations of Climate Model Intercomparison Project Phase 6 (CMIP6) under Shared Socioeconomic Pathways 2–4.5 and 5–8.5 and their predecessor CMIP5 under Representative Concentration Pathways 4.5 and 8.5. Quantile-Quantile Downscaling is utilized to estimate extreme rainfall values at fine spatiotemporal scales. Overall, more frequent storms with an average increase of around 30%-40% in their intensity are projected in most cities based on both CMIP5 and CMIP6 models during 2071–2100. For instance, the fast-growing cities of Vancouver, Toronto, and Montreal could expect around 4–11 times more frequent 5-min storms with a 100-year return period during 2071–2100. Moreover, although IDF curves based on CMIP5 and CMIP6 individual models diverge, the expected IDF curves based on their multi-model ensemble mean are somewhat similar if models with a high climate sensitivity based on CMIP6 are excluded from the analysis. This study underlines the need to update IDF curves in Canadian cities.

Optimizing Soil Moisture Station Networks for Future Climates

AbstractSoil moisture is central to local climate on land. In situ soil moisture observations are vital for observing vegetation‐relevant root‐zone soil moisture. However, stations included in the International Soil Moisture Network are sparse in regions with strong land‐atmosphere coupling. We apply a machine‐learning‐based procedure for informing future station placement using virtual soil moisture stations in future CMIP6 projections. Stations are placed where the climate is currently most under‐represented. This strategy outperforms random station placement and station placement according to geographical distance. Doubling the current number of stations using this method alleviates the uneven global distribution of stations, increases the skill in the estimation of inter‐annual variability and trends in dry‐season soil moisture, and reduces its differences across climates in future projections. Stations are predominantly placed in tropical climates, especially when optimizing for drying trends. The results can inform future station placement to support climate change mitigation efforts.

Comparative assessment of future solar power potential based on CMIP5 and CMIP6 multi-model ensembles

While the popularity and feasibility of solar power have increased toward achieving a low-carbon and climate-resilient society, it is uncertain how changes in climate attributes will affect the future potential of solar power output. This study presents a comparative assessment of future changes in solar power in terms of the technology for harnessing energy from insolation (PVP vs CSP), climate projections (CMIP5 vs CMIP6), and emission scenarios. Both CMIP5 and CMIP6 multi-model projections capture the major characteristics of the global distribution seen in PVP and CSP calculated using the reanalysis data during the historical period. However, despite the general similarity to CMIP5-based results, CMIP6 models slightly outperform their CMIP5 counterparts regarding quantitative metrics and enhance the robustness of the future change signal estimated by the statistical significance and inter-model consistency. The future changes in PVP and CSP patterns are sensitive to the emission scenarios that can control the degree of warming. Under the fossil-fueled development scenarios, the greater increase in temperatures may lead to a high vulnerability of the solar power supply by reducing the output of both PVP and CSP. This study is timely and relevant to emphasizing the benefits of climate change mitigation, which can support the sustainable development of solar energy.

Projected decrease in trail access in the Arctic

Transportation systems in northern Canada are highly sensitive to climate change. We project how access to semi-permanent trails on land, water, and sea ice might change this century in Inuit Nunangat (the Inuit homeland in northern Canada), using CMIP6 projections coupled with trail access models developed with community members. Overall trail access is projected to diminish, with large declines in access for sea ice trails which play a central role for Inuit livelihoods and culture; limits to adaptation in southern regions of Inuit Nunangat within the next 40 years; a lengthening of the period when no trails are accessible; and an unequal distribution of impacts according to the knowledge, skills, equipment, and risk tolerance of trail users. There are opportunities for adaptation through efforts to develop skillsets and confidence in travelling in more marginal environmental conditions, which can considerably extend the envelope of days when trails are accessible and months when this is possible. Such actions could reduce impacts across emissions scenarios but their potential effectiveness declines at higher levels of global warming, and in southern regions only delays when sea ice trails become unusable.

Dynamic downscaling of wind speed over the North Atlantic Ocean using CMIP6 projections: Implications for offshore wind power density

Offshore wind energy is an important agent to fight climate change. However, it is simultaneously very sensitive to climate change. This study analyzes the future changes in wind speed of 10 m above sea surface (V10) in the North Atlantic Ocean and how these variations may affect offshore wind energy resources for three potential subregions (the United States (US) East Coast, western Iberian Peninsula, and the Caribbean Sea). Dynamic downscaling of three different future scenarios of the CESM2 global climate model (CMIP6 project) was performed using the WRF-ARW atmospheric model. V10 is expected to decrease in the winter and spring seasons but increase in summer and autumn, mainly in tropical regions up to 30 °N. Annually, it shows the maximum increase in the tropical region. For the Iberian Peninsula subregion, significant increases in summer are expected for wind power density (WPD) along the 21st century, but there is uncertainty for the other seasons. A WPD decrease in winter and increases in summer and autumn are expected along the 21st century for the US subregion. No significant changes were observed at annual scale. Finally, for the Caribbean Sea, a decrease is projected in the Yucatan Basin and considerable increases are foreseen for the Colombia and Venezuela basins.

Energy forecasting to benchmark for federal net-zero objectives under climate uncertainty

Climate variability creates energy demand uncertainty and complicates long-term asset management and budget planning. Without understanding future energy demand trends related to intensification of climate, changes to energy consumption could result in budget escalation. Energy demand trends can inform campus infrastructure repair and modernization plans, effective energy use reduction policies, or renewable energy resource implementation decisions, all of which are targeted at mitigating energy cost escalation and variability. To make these long-term management decisions, energy managers require unbiased and accurate energy use forecasts. This research uses a statistical, model-based forecast framework, calibrated retrospectively with open-source climate data, and run in a forecast mode with CMIP5 projections of temperature for RCPs 4.5 and 8.5 to predict total daily energy consumption and costs for a campus-sized community (population: 30 000) through the end of the century. The case study of Wright Patterson Air Force Base is contextualized within the existing executive orders directing net-zero emissions and carbon-free electricity benchmarks for the federal government. The model suggests that median annual campus electric consumption, based on temperature rise alone, could increase by 4.8% with RCP4.5 and 19.3% with RCP8.5 by the end of the century, with a current carbon footprint of 547 million kg CO2e. Monthly forecasts indicate that summer month energy consumption could significantly increase within the first decade (2020–2030), and nearly all months will experience significant increases by the end of the century. Therefore, careful planning is needed to meet net-zero emissions targets with significant increases in electricity demands under current conditions. Policies and projects to reduce the carbon footprint of federal agencies need to incorporate forecasting models to understand changes in demand to appropriately size electric infrastructure.

A Comparison Study of Observed and the CMIP5 Modelled Precipitation over Iraq 1941–2005

This paper presents an analysis of the annual precipitation observed by a network of 30 rain gauges in Iraq over a 65-year period (1941–2005). The simulated precipitation from 18 climate models in the CMIP5 project is investigated over the same area and time window. The Mann–Kendall test is used to assess the strength and the significance of the trends (if any) in both the simulations and the observations. Several exploratory techniques are used to identify the similarity (or disagreement) in the probability distributions that are fitted to both datasets. While the results show that large biases exist in the projected rainfall data compared with the observation, a clear agreement is also observed between the observed and modelled annual precipitation time series with respect to the direction of the trends of annual precipitation over the period.

Historical and Future Vegetation Changes in the Degraded Frozen Soil and the Entire Tibetan Plateau and Climate Drivers

AbstractAbout 99% of the Tibetan Plateau (TP) is covered by frozen soils and degradation of frozen soils will certainly impact TP's ecosystems. Here, we investigate decadal changes of frozen soils and net primary productivity (NPP, representing vegetation) in the degraded frozen soil zones and the TP during 1982–2014 and 2015–2100 using a dynamic vegetation model, historical records and the latest CMIP6 projections, as well as observation‐based soil temperature thresholds. In 1982–2014, degraded permafrost soil zones were in the range of 316,975–455,402 km2, with mean annual NPP staying around 84.9 gCm−2and annual NPP showing a significant reduction at −1.71 gCm−2/year due primarily to warming air. Seasonally frozen soil also degraded by 15,636 km2in the southeast TP, with mean annual NPP staying around 620.0 gCm−2and annual NPP showing a significant increase at 11.00 gCm−2/year. In the future, frozen soil continues to degrade and the degradation accelerates toward the end of the century such that only 2.7% of permafrost soil in 2014 is left by 2080–2100 under the shared socioeconomic pathway SSP5‐8.5. Mean annual NPP in the permafrost soil degraded zones in 2015–2100 is about half of that for 1982–2014, with spatially mixed decrease and increase trends in the near‐, mid‐, and long‐term periods. Over the seasonally frozen soil degraded zones and the entire TP, more positive than negative annual NPP changes are seen in 2015–2100, especially in the southeast of the TP, due to improved growing conditions and the expansion of primarily subtropical and temperate scrubland.

Changes in compound extremes of rainfall and temperature over West Africa using CMIP5 simulations

This study aims to characterize changes in compound extremes of rainfall and temperature over West Africa. For this purpose, data from CHIRPS observations, the ERA5 reanalysis, and twenty-four (24) climate models involved in the CMIP5 Project were analyzed. First, climate models were evaluated in terms of their capacity to simulate summer mean climatology and compound extremes during the historical period (1981–2005), and secondly, changes in compound extremes were examined under RCP8.5 emission scenario between the near future (2031–2055) and the far future (2071–2095) relative to the historical period. Despite the presence of some biases, the ensemble mean of the models well reproduces the compound extremes patterns over West Africa at the seasonal and intraseasonal timescales. The analysis over the historical period with CHIRPS/ERA5 dataset shows a strong occurrence of the dry/warm mode over the northern Sahel during the June-July-August-September period (JJAS; main rainy season) and over the Guinean region during the February-March-April-May season (FMAM; first and main rainy season). These strong occurrences are due to a weak and highly frequent precipitation recorded in these zones. The compound wet/warm mode is frequent in JJAS over the Sahel and the Sudanian zone (transition area between Sahel and Guinean regions), while in FMAM, its occurrence is maximum over the Guinean region. The study also shows that the dry/warm mode will increase in the whole Sahel (western and central) and in the Guinean zone in the near and far futures while the compound wet/warm mode will decrease in the whole region. This study suggests that the West Africa region will be prone to drought intensified by warmer temperatures and calls for climate action and adaptation strategies to mitigate the risks on rain-fed agriculture, energy, and on animals and human health.

Constraining CMIP6 Projections of an Ice‐Free Arctic Using a Weighting Scheme

AbstractEmploying a model democracy in which each model is equally weighted may lead to a poor estimation of the true uncertainty in climate projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The improvement and increase in number of CMIP6 models compared with previous phases of CMIP indicate that both model skill and independence need to be considered to provide convincing projections. In this study, we use a weighting scheme, which weights both the skill and independence of multi‐model simulations, to efficiently constrain the large uncertainty in the projection of the timing of an ice‐free Arctic. The uncertainty‐constrained projections of CMIP6 show that the multi‐model spread of the projected first year of an ice‐free Arctic can be reduced by about 29 years under the Shared Socioeconomic Pathway (SSP)3–7.0 scenario (a regional rivalry scenario), indicating a faster tendency to an ice‐free Arctic summer than projections based solely on model democracy. A fossil‐fuel‐based development scenario (i.e., SSP5‐8.5) leads to an ice‐free Arctic before the 2070s (ranging from 2038 to 2071), while an ice‐free Arctic occurs slightly later (by ∼10 years) under the SSP2‐4.5 scenario (i.e., intermediate scenario) and the SSP3‐7.0 scenario, but is inevitable this century. The sustainable development scenario (i.e., SSP1‐2.6) is likely to prevent the occurrence of an ice‐free Arctic. Internal variability strongly affects the projection estimated by the equally weighted ensemble; however, it has a negligible impact on the results obtained by the weighting scheme, thereby indicating that the results of this study are robust and convincing.

Diminishing seasonality of subtropical water availability in a warmer world dominated by soil moisture–atmosphere feedbacks

Global warming is expected to cause wet seasons to get wetter and dry seasons to get drier, which would have broad social and ecological implications. However, the extent to which this seasonal paradigm holds over land remains unclear. Here we examine seasonal changes in surface water availability (precipitation minus evaporation, P–E) from CMIP5 and CMIP6 projections. While the P–E seasonal cycle does broadly intensify over much of the land surface, ~20% of land area experiences a diminished seasonal cycle, mostly over subtropical regions and the Amazon. Using land–atmosphere coupling experiments, we demonstrate that 63% of the seasonality reduction is driven by seasonally varying soil moisture (SM) feedbacks on P–E. Declining SM reduces evapotranspiration and modulates circulation to enhance moisture convergence and increase P–E in the dry season but not in the wet season. Our results underscore the importance of SM–atmosphere feedbacks for seasonal water availability changes in a warmer climate.

Environmental Pressures at Dirre Sheikh Hussein Sanctuary

Dirre Sheikh Hussein is a religious complex in Ethiopia that dates from the 12th century or earlier. An important focus for pilgrimage, it lies in an isolated part of Oromia State on poorly drained semi-arid lowlands. Significant architecturally and culturally, recent expansion and refurbishment of the major buildings led to structural issues, though these are now largely overcome through consolidation of the prayer hall roof, laying a stone walkway, digging drainage ditches etc. Current deterioration of the buildings can be seen as: (i) fading of colours, (ii) cracks in walls, roofs, and festive places, (iii) deposits of sand around walls and (iv) staining and drainage marks on the white painted surfaces. Heavy falls of rain overwhelm drainage and overfill storage pools. Meteorological observations are infrequent locally, so those made some 70–100 km away were used, along with regridded historical data, reanalysis and CMIP6 projections. These revealed increases in temperature, precipitation and humidity, and provided indications of long-term climate pressures at the site. Changing patterns of future precipitation, particularly heavy rain, may threaten the site. The relative humidity changes are small, though an increasing Scheffer index suggests potentially enhanced wood decay. Changes in soil moisture have the potential to disrupt the foundations. Very hot days may become a problem for the two annual celebrations at the site.

Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios

The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070–2099 relative to 1971–2000. Under RCP8.5/SSP5-8.5 (2070–2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.

Assessing future runoff changes with different potential evapotranspiration inputs based on multi-model ensemble of CMIP5 projections

• Xinanjiang model performed well in runoff simulation in North Johnstone catchment. • Runoff projected with different ETp inputs showed similar changes in the future. • Runoff in spring and winter would decrease in the future. • GCMs and RCPs were major factors resulting in uncertainty in runoff projections. Runoff projection under future climate scenarios has been widely studied to investigate the impacts of climate change on regional water availability. However, uncertainty in runoff projection due to different ETp inputs has not been fully assessed. This study firstly adopted the physically-based Penman model, temperature-based Hargreaves model, and radiation-based Abtew, Jensen-Haise, and modified Makkink models to drive Xinanjiang (XAJ) model, thus investigating the influence of different potential evapotranspiration (ETp) inputs on runoff simulation. Then, we used the validated XAJ model to project runoff in North Johnstone catchment, northeast Australia. Lastly, we quantified the uncertainty caused by 34 global climate models (GCMs), different representative concentrative pathway (RCP) scenarios (RCP4.5 & RCP8.5), and different ETp models with the technique of three-way analysis of variance (ANOVA). We found that XAJ model performed well (R 2 ≥ 0.88, NSE ≥ 0.86) and showed low sensitivity to different ETp inputs in runoff simulation and projection. Under future climate scenarios, spring and winter runoff had a large decrease, which was mainly caused by the decrease in rainfall. The mean decreases in spring and winter runoff were 14.6% – 20.1% and 10.3% – 15.2% respectively by 2090s under RCP8.5. GCMs (50.9% – 67.4%) and their interaction with RCPs (35.4% – 46.6%) were the dominant factors resulting in uncertainty in runoff projection. Our study not only advanced the understanding of the impacts of different ETp inputs on runoff projection but also offered insights on the understanding of the roles different factors played in the uncertainty in runoff projection. We expect such knowledge can provide a way forward to narrow down the uncertainty in runoff projection, thus providing more robust information for policy makers in water management.

Comparison between CMIP5 and CMIP6 Models over MENA Region Using Historical Simulations and Future Projections

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.

Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia

Climate projections are essential for decision-making but contain non-negligible uncertainty. To reduce projection uncertainty over Asia, where half the world’s population resides, we develop emergent constraint relationships between simulated temperature (1970–2014) and precipitation (2015–2100) growth rates using 27 CMIP6 models under four Shared Socioeconomic Pathways. Here we show that, with uncertainty successfully narrowed by 12.1–31.0%, constrained future precipitation growth rates are 0.39 ± 0.18 mm year−1 (29.36 mm °C−1, SSP126), 0.70 ± 0.22 mm year−1 (20.03 mm °C−1, SSP245), 1.10 ± 0.33 mm year−1 (17.96 mm °C−1, SSP370) and 1.42 ± 0.35 mm year−1 (17.28 mm °C−1, SSP585), indicating overestimates of 6.0–14.0% by the raw CMIP6 models. Accordingly, future temperature and total evaporation growth rates are also overestimated by 3.4–11.6% and −2.1–13.0%, respectively. The slower warming implies a lower snow cover loss rate by 10.5–40.2%. Overall, we find the projected increase in future water availability is overestimated by CMIP6 over Asia.

How well have CMIP3, CMIP5 and CMIP6 future climate projections portrayed the recently observed warming

Despite the dire conclusions of the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports in terms of global warming and its impacts on Earth’s climate, ecosystems and human society, a skepticism claiming that the projected global warming is alarmist or, at least, overestimated, still persists. Given the years passed since the future climate projections that served as basis for the IPCC 4th, 5th and 6th Assessment Reports were released, it is now possible to answer this fundamental question if the projected global warming has been over or underestimated. This study presents a comparison between CMIP3, CMIP5 and CMIP6 future temperature projections and observations. The results show that the global warming projected by all CMIPs and future climate scenarios here analyzed project a global warming slightly lower than the observed one. The observed warming is closer to the upper level of the projected ones, revealing that CMIPs future climate scenarios with higher GHG emissions appear to be the most realistic ones. These results show that CMIPs future warming projections have been slightly conservative up to 2020, which could suggest a similar cold bias in their warming projections up to the end of the current century. However, given the short future periods here analyzed, inferences about warming at longer timescales cannot be done with confidence, since the models internal variability can play a relevant role on timescales of 20 years and less.

Comparison of Projections of Precipitation over Yangtze River Basin of China by Different Climate Models

Based on the observational dataset CN05.1 and the Coupled Model Intercomparison Project (CMIP), this study assesses the performance of CMIP5 and CMIP6 projects in projecting mean precipitation at annual and seasonal timescales in the Yangtze River Basin of China over the period 2015–2020 under medium emission scenarios (RCP4.5/SSP2-4.5). Results indicate that the multi-model ensemble (MME) of CMIP6 overall has lower relative bias and root-mean square error of both annual and seasonal mean than that of CMIP5, except for winter, but both of the two ensembles show the best projected accuracy in winter. Generally, CMIP6 outperformed CMIP5 in capturing spatial and temporal pattern over the YRB, especially in the midstream and downstream areas, which have high precipitation. Further analyses suggest that the CMIP6 GCMs have lower median normalized root-mean square error than CMIP5 GCMs. Based on the Taylor skill (TS) score, both CMIP6 and CMIP5 GCMs are ranked to evaluate relative model performance. CMIP6 GCMs have higher ranks than CMIP5 GCMs, with an average TS score of 0.68 (0.55) for CMIP6 (CMIP5), and three out of the five highest scored GCMs are CMIP6 GCMs. However, the CMIP6 precipitation projections are still quite uncertain, thus requiring further assessment and correction.

The Emerging Arctic Shipping Corridors

AbstractThe dramatic sea ice loss makes trans‐Arctic navigation possible. However, navigability assessments at high temporal resolution are still very limited. To bridge this gap, daily sea ice concentration and thickness from CMIP6 projections are applied to evaluate the future potential of Arctic shipping under multiple climate scenarios. The September navigable area will continue to increase through the 2050s for open‐water (OW) ships and the 2040s for Polar Class 6 (PC6) vessels across all scenarios. Quasi‐equilibrium states will then ensue for both OW and PC6 ships under SSP245 and SSP585. The sailing time will be shortened, especially for OW ships, while the navigable days for both types of vessels will increase dramatically. PC6 ships will be able to sail the Arctic shipping routes year‐round starting in the 2070s when the decadal‐averaged global mean surface temperature anomaly hits approximately +3.6°C (under SSP585) compared to pre‐industrial times (1850–1900).