rlacombe/ClimateX huggingface dataset:
Changes to the coincident atmospheric water cycle and ocean-atmosphere fluxes (evaporation and precipitation) are the primary drivers of the observed basin-scale salinity changes (IPCC AR6_WGI, confidence: high)
The basin-scale changes are consistent across models and intensify through the historical period (IPCC AR6_WGI, confidence: high)
The structure of the biases in the multi-model mean has not changed substantially between CMIP5 and CMIP6 (IPCC AR6_WGI, confidence: medium)
However, biases are apparent in the modelled circulation strengths (high confidence) and their variability (IPCC AR6_WGI, confidence: medium)
Earth system models simulate globally averaged land carbon sinks within the range of observation-based estimates (IPCC AR6_WGI, confidence: high)
The influence of ozone forcing on the SAM trend has been small since the early 2000s compared to earlier decades, contributing to a weaker SAM trend observed over 2000–2019 (IPCC AR6_WGI, confidence: medium)
Climate models reproduce the summertime SAM trend well, with CMIP6 models outperforming CMIP5 models (IPCC AR6_WGI, confidence: medium)
Models reproduce the observed spatial features and variance of the SAM and NAM very well (IPCC AR6_WGI, confidence: high)
Further assessment since AR5 confirms that climate and Earth system models are able to reproduce most aspects of the spatial structure and variance of the El Niño–Southern Oscillation and Indian Ocean Basin and Dipole modes (IPCC AR6_WGI, confidence: medium)
Uncertainties remain in quantification of the human influence on AMV and PDV due to brevity of the observational records, limited model performance in reproducing related sea surface temperature (SST) anomalies despite improvements from CMIP5 to CMIP6 (IPCC AR6_WGI, confidence: medium)
Simulated GMST anomalies are well within the uncertainty range of temperature reconstructions (IPCC AR6_WGI, confidence: medium)
Before the year 1300, larger disagreements between models and temperature reconstructions are expected because forcing and temperature reconstructions are increasingly uncertain further back in time, but specific causes have not been identified conclusively (Ljungqvist et al., 2019; PAGES 2k Consortium, 2019) (IPCC AR6_WGI, confidence: medium)
CMIP6 models also reproduce historical GSAT changes similarly to their CMIP5 counterparts (IPCC AR6_WGI, confidence: medium)
In summary, based on the latest updates to satellite observations of stratospheric temperature, we assess that simulated and observed trends in global mean temperature through the depth of the stratosphere are more consistent than based on previous datasets, but some differences remain (IPCC AR6_WGI, confidence: medium)
Therefore, the observed 1998–2012 trend is consistent with both the CMIP5 or CMIP6 multi-model ensemble of trends over the same period (IPCC AR6_WGI, confidence: high)
Although there is noticeable uncertainty among observational products (H. Su et al., 2017) and observation quality changes through time, global ocean heat content continued to increase during the slower surface warming period (IPCC AR6_WGI, confidence: very high)
Nonetheless, the heating of the climate system continued during this period, as reflected in the continued warming of the global ocean (very high confidence) and in the continued rise of hot extremes over land (IPCC AR6_WGI, confidence: medium)
The past five-year period (2016–2020) is the hottest five-year period in the instrumental record up to 2020 (IPCC AR6_WGI, confidence: high)
Records of tree ring width have provided evidence that recent prolonged dry spells in the Levant and Chile are unprecedented in the last millennium (IPCC AR6_WGI, confidence: high)
Likewise, tree rings indicate that the 2012–2014 drought in the south-western United States was exceptionally severe in the context of natural variability over the last millennium, and may have been exacerbated by the contribution of anthropogenic temperature rise (IPCC AR6_WGI, confidence: medium)
Nonetheless, tree rings also indicate the presence of prolonged megadroughts in western North America throughout the last millennium that were more severe than 20th and 21st century events (IPCC AR6_WGI, confidence: high)
However, prescribing changes in vegetation and dust was found to improve the match to the paleoclimate record (Pausata et al., 2016; Tierney et al., 2017) suggesting that vegetation feedbacks in the CMIP5 models may be too weak (IPCC AR6_WGI, confidence: low)
Based on these results we assess that despite some improvements, CMIP6 models still have deficiencies in simulating precipitation patterns, particularly over the tropical ocean (IPCC AR6_WGI, confidence: high)
Global land precipitation has likely increased since the middle of the 20th century (IPCC AR6_WGI, confidence: medium)
New attribution studies strengthen previous findings of a detectable increase in mid to high latitude land precipitation over the Northern Hemisphere (IPCC AR6_WGI, confidence: high)
Moreover, human interventions and water withdrawals, while affecting streamflow, cannot explain the observed spatio-temporal trends (IPCC AR6_WGI, confidence: medium)
The overall performance of CMIP6 models in simulating extreme precipitation intensity and frequency is similar to that of CMIP5 models (IPCC AR6_WGI, confidence: high)
For the strong ozone depletion period of 1981–2000, human influence is detectable in the summertime poleward expansion in the Southern Hemisphere (IPCC AR6_WGI, confidence: medium)
The causes of the observed strengthening of the Pacific Walker circulation over the 1980–2014 period are not well understood, since the observed strengthening trend is outside the range of variability simulated in the coupled models (IPCC AR6_WGI, confidence: medium)
AR5 assessed that CMIP5 models simulated monsoons better than CMIP3 models but that biases remained in domains and intensity (IPCC AR6_WGI, confidence: high)
In summary, while greenhouse gas increases acted to enhance the global land monsoon precipitation over the 20th century (medium confidence), consistent with projected future enhancement (Section 4.5.1.5), this tendency was overwhelmed by anthropogenic aerosols from the 1950s to the 1980s, which contributed to weakening of global land summer monsoon precipitation intensity for this period (IPCC AR6_WGI, confidence: medium)
While CMIP5 models can capture the domain and precipitation intensity of the global monsoon, biases remain in their regional representations, and they are unsuccessful in quantitatively reproducing changes in paleo reconstructions (IPCC AR6_WGI, confidence: high)
CMIP6 models reproduce the domain and precipitation intensity of the global monsoon observed over the instrumental period better than CMIP5 models (IPCC AR6_WGI, confidence: medium)
Section 2.3.1.4.3 assesses that the total number of extratropical cyclones has likely increased since the 1980s in the Northern Hemisphere (IPCC AR6_WGI, confidence: low)
Section 2.3.1.4.3 assesses that the extratropical jets and cyclone tracks have likely shifted poleward in both hemispheres since the 1980s with marked seasonality in trends (IPCC AR6_WGI, confidence: medium)
The recent Arctic sea ice loss during summer is unprecedented since 1850 (IPCC AR6_WGI, confidence: high)
Sea ice thermodynamic considerations indicate that the magnitude of sea ice variability and loss depends on ice thickness (Bitz, 2008; Massonnet et al., 2018) and hence the climatology simulated by different models may influence their simulated sea ice trends (IPCC AR6_WGI, confidence: medium)
An important consideration in comparing Arctic sea ice loss in models and observations is the role of internal variability (IPCC AR6_WGI, confidence: medium)
Increases in anthropogenic aerosols have offset part of the greenhouse gas induced Arctic sea ice loss since the 1950s (IPCC AR6_WGI, confidence: medium)
CMIP6 models better represent the seasonality and geographical distribution of snow cover than CMIP5 simulations (IPCC AR6_WGI, confidence: high)
Section 2.3.2.4.1 assesses that Greenland Ice Sheet mass loss began in the latter half of the 19th century and that the rate of loss has increased substantially since the turn of the 21st century (IPCC AR6_WGI, confidence: high)
It further assessed that Antarctic ice loss is dominated by acceleration, retreat and rapid thinning of the major West Antarctic Ice Sheet outlet glaciers (very high confidence), driven by melting of ice shelves by warm ocean waters (IPCC AR6_WGI, confidence: high)
Nevertheless, the CMIP6 models show a somewhat more realistic pattern of SST trends (IPCC AR6_WGI, confidence: low)
The multi-model means of both CMIP5 and CMIP6 historical simulations forced with time varying natural and anthropogenic forcing shows robust increases in ocean heat content in the upper (0–700 m) and intermediate (700–2000 m) ocean (IPCC AR6_WGI, confidence: high)
It is extremely likely that human influence was the main driver of the ocean heat content increase observed since the 1970s, which extends into the deeper ocean (IPCC AR6_WGI, confidence: very high)
Updated observations, like model simulations, show that warming extends throughout the entire water column (IPCC AR6_WGI, confidence: high)
The structure of the salinity biases in the multi-model mean has not changed substantially between CMIP5 and CMIP6 (IPCC AR6_WGI, confidence: medium)
All available multi-decadal assessments have confirmed that the associated pattern of change corresponds to fresh regions becoming fresher and salty regions becoming saltier (IPCC AR6_WGI, confidence: high)
CMIP5 and CMIP6 models are only able to reproduce these patterns in simulations that include greenhouse gas increases (IPCC AR6_WGI, confidence: medium)
Changes to the coincident atmospheric water cycle and ocean-atmosphere fluxes (evaporation and precipitation) are the primary drivers of the basin-scale observed salinity changes (IPCC AR6_WGI, confidence: high)
The basin-scale changes are consistent across models and intensify on centennial scales from the historical period through to the projections of future climate (IPCC AR6_WGI, confidence: high)
As reported in Section 2.3.3.4.1, estimates of AMOC since at least 1950, which are generated from observed surface temperatures or sea surface height, suggest the AMOC weakened through the 20th century (IPCC AR6_WGI, confidence: low)
In summary, while there have been improvements across successive CMIP phases (from CMIP3 to CMIP6) in the representation of the Southern Ocean circulation, such that the mean zonal and overturning circulations of the Southern Ocean are now broadly reproduced, substantial observational uncertainty and climate model challenges preclude attribution of Southern Ocean circulation changes (IPCC AR6_WGI, confidence: high)
That increase was attributed to direct land use and management changes, as well as to CO 2 fertilization, nitrogen deposition, increased diffuse radiation and climate change (IPCC AR6_WGI, confidence: high)
In summary, Earth system models simulate globally averaged land carbon sinks within the range of observation-based estimates (IPCC AR6_WGI, confidence: high)
The decrease in ocean oxygen content in the upper 1000 m, between 1970 and 2010, is further confirmed in SROCC (IPCC AR6_WGI, confidence: medium)
Section 5.2.1.3 assesses that both observational reconstructions based on the partial pressure of CO 2 and ocean biogeochemical models show a quasi-linear increase in the ocean sink of anthropogenic CO 2 from 1.0 ± 0.3 PgC yr–1 to 2.5 ± 0.6 PgC yr–1 between 1960–1969 and 2010–2019 in response to global CO 2 emissions (IPCC AR6_WGI, confidence: high)
CMIP5 and CMIP6 models are skilful in simulating the spatial features and the variance of the NAM/NAO and associated teleconnections (IPCC AR6_WGI, confidence: high)
However, despite the aforementioned limitations of the reconstructions, Section 2.4.1.2 assesses that the recent positive trend in the SAM is likely unprecedented in at least the past millennium (IPCC AR6_WGI, confidence: medium)
While ozone depletion contributed to the trend from the 1970s to the 1990s (medium confidence), its influence has been small since 2000, leading to a weaker summertime SAM trend over 2000–2019 (IPCC AR6_WGI, confidence: medium)
Climate models reproduce the spatial structure of the summertime SAM observed since the late 1970s well (IPCC AR6_WGI, confidence: high)
CMIP6 models reproduce the spatiotemporal features and recent multi-decadal trend of the summertime SAM better than CMIP5 models (IPCC AR6_WGI, confidence: medium)
However, there is a large spread in the intensity of the SAM response to ozone and greenhouse gas changes in both CMIP5 and CMIP6 models (IPCC AR6_WGI, confidence: high)
CMIP5 and CMIP6 models do not capture multicentennial variability of the SAM found in proxy reconstructions (IPCC AR6_WGI, confidence: low)
As assessed in Section 2.4.2, ENSO amplitude since 1950 is higher than over the pre-industrial period from 1850 as far back as 1400 (IPCC AR6_WGI, confidence: medium)
Nevertheless, CMIP5 models have medium overall performance in reproducing both the interannual IOB and IOD modes, with an apparently good performance in reproducing the IOB magnitude arising from compensation of biases in the formation process, and overly high IOD magnitude due to the mean state bias (IPCC AR6_WGI, confidence: high)
As such, PDV is an important driver of decadal internal climate variability which limits detection of human influence on various aspects of decadal climate change on global to regional scales (IPCC AR6_WGI, confidence: high)
Despite the limitations of these model-observation comparisons, CMIP5 models, on average, simulate broadly realistic spatial structures of the PDV, but with a clear bias in the South Pacific (IPCC AR6_WGI, confidence: medium)
In particular, anthropogenic and volcanic aerosols are thought to have played a role in the timing and intensity of the negative (cold) phase of AMV recorded from the mid-1960s to mid-1990s and subsequent warming (IPCC AR6_WGI, confidence: medium)
The pattern of ocean salinity changes indicate that fresh regions are becoming fresher and that salty regions are becoming saltier as a result of changes in ocean-atmosphere fluxes through evaporation and precipitation (IPCC AR6_WGI, confidence: high)
Earth System models characterized by additional biogeochemical feedbacks often perform at least as well as related more constrained, lower-complexity models lacking these feedbacks (IPCC AR6_WGI, confidence: medium)
In many cases, the models score similarly against both observational references, indicating that model errors are usually larger than observational uncertainties (IPCC AR6_WGI, confidence: high)
Moreover, synthesizing across Sections 3.3–3.7, we assess that the CMIP6 multi-model mean captures most aspects of observed climate change well (IPCC AR6_WGI, confidence: high)
Overall, the PMIP multi-model means agree very well (within 0.5°C of the assessed range) with GSAT reconstructed from proxies across multiple time periods, spanning a range from 6°C colder than pre-industrial (Last Glacial Maximum) to 14°C warmer than pre-industrial (Early Eocene Climate Optimum) (IPCC AR6_WGI, confidence: high)
During the orbitally-forced mid-Holocene, the CMIP6 multi-model mean captures the sign of the regional changes in temperature and precipitation in most regions assessed, and there have been some regional improvements compared to AR5 (IPCC AR6_WGI, confidence: medium)
The limited number of CMIP6 simulations of the LGM hinders model evaluation of the multi-model mean, but for both LGM and mid-Holocene, models tend to underestimate the magnitude of large changes (IPCC AR6_WGI, confidence: high)
Some long-standing model-data discrepancies, such as a dry bias in North Africa in the mid-Holocene, have not improved in CMIP6 compared with PMIP3 (IPCC AR6_WGI, confidence: high)
In comparison with standard resolution CMIP6 models, higher resolution probed under the HighResMIP activity (Haarsma et al., 2016) improves aspects of the simulation of climate (particularly concerning sea surface temperature) but discrepancies remain and there are some regions, such as parts of the Southern Ocean, where currently attainable resolution produces inferior performance (IPCC AR6_WGI, confidence: high)
The other half arises because for central estimates of climate sensitivity, most scenarios show stronger warming over the near term than was assessed as ‘current’ in SR1.5 (IPCC AR6_WGI, confidence: medium)
If climate sensitivity lies near the lower end of the assessed very likely range, crossing the 1.5°C warming threshold is avoided in scenarios SSP1-1.9 and SSP1-2.6 (IPCC AR6_WGI, confidence: medium)
Uncertainty in near-term projections of annual GSAT arises in roughly equal measure from natural internal variability and model uncertainty (IPCC AR6_WGI, confidence: high)
Forecasts initialized from recent observations simulate annual GSAT changes for the period 2019–2028 relative to the recent past that are consistent with the assessed very likely range (IPCC AR6_WGI, confidence: high)
The uncertainty ranges for the period 2081–2100 continue to be dominated by the uncertainty in ECS and TCR (IPCC AR6_WGI, confidence: very high)
Emissions-driven simulations for SSP5-8.5 show that carbon-cycle uncertainty is too small to change the assessment of GSAT projections (IPCC AR6_WGI, confidence: high)
In SSP1-2.6 and SSP2-4.5, ERF changes also explain about half of the changes in the range of warming (IPCC AR6_WGI, confidence: medium)
For SSP5-8.5, higher climate sensitivity is the primary reason behind the upper end of the warming being higher than in CMIP5 (IPCC AR6_WGI, confidence: medium)
For SSP1-2.6, such a high-warming storyline implies long-term (2081–2100) warming well above, rather than well below, 2°C (IPCC AR6_WGI, confidence: high)
Irrespective of scenario, high-warming storylines imply changes in many aspects of the climate system that exceed the patterns associated with the central estimate of GSAT changes by up to more than 50% (IPCC AR6_WGI, confidence: high)
The warming pattern likely varies across seasons, with northern high latitudes warming more during boreal winter than summer (IPCC AR6_WGI, confidence: medium)
As warming increases, a larger land area will experience statistically significant increases or decreases in precipitation (IPCC AR6_WGI, confidence: medium)
Interannual variability of precipitation over many land regions will increase with global warming (IPCC AR6_WGI, confidence: medium)
In the near term, no discernible differences in precipitation changes are projected between different SSPs (IPCC AR6_WGI, confidence: high)
The anthropogenic aerosol forcing decreases in most scenarios, contributing to increases in GSAT (medium confidence) and global mean land precipitation (IPCC AR6_WGI, confidence: low)
In the long term (2081–2100), monsoon rainfall change will feature a north–south asymmetry characterized by a greater increase in the Northern Hemisphere than in the Southern Hemisphere and an east–west asymmetry characterized by an increase in Asian-African monsoon regions and a decrease in the North American monsoon region (IPCC AR6_WGI, confidence: medium)
Near-term changes in global monsoon precipitation and circulation are uncertain due to model uncertainty and internal variability such as Atlantic Multi-decadal Variability and Pacific Decadal Variability (IPCC AR6_WGI, confidence: medium)
This is because of the opposing influence in the near- to mid-term from stratospheric ozone recovery and increases in other greenhouse gases on the Southern Hemisphere summertime mid-latitude circulation (IPCC AR6_WGI, confidence: high)
One exception is the expected decrease in frequency of atmospheric blocking events over Greenland and the North Pacific in boreal winter in SSP3-7.0 and SSP5-8.5 scenarios (IPCC AR6_WGI, confidence: medium)
AMV influences on the nearby regions can be predicted over lead times of 5–8 years (IPCC AR6_WGI, confidence: medium)
There is no model consensus for a systematic change in intensity of ENSO sea surface temperature variability over the 21st century in any of the SSP scenarios assessed (IPCC AR6_WGI, confidence: medium)
Arctic sea ice area in March, the month of annual maximum sea ice area, also decreases in the future under each of the considered scenarios, but to a much lesser degree (in percentage terms) than in September (IPCC AR6_WGI, confidence: high)
For the period 2081–2100 relative to 1995–2014, GMSL is likely to rise by 0.46–0.74 m under SSP3-7.0 and by 0.30–0.54 m under SSP1-2.6 (IPCC AR6_WGI, confidence: medium)
The fraction of emissions absorbed by land and ocean sinks will be smaller under high emissions scenarios than under low emissions scenarios (IPCC AR6_WGI, confidence: high)
Ocean surface pH will decrease steadily through the 21st century, except for SSP1-1.9 and SSP1-2.6 where values decrease until around 2070 and then increase slightly to 2100 (IPCC AR6_WGI, confidence: high)
However, the response of many other climate quantities to mitigation would be largely masked by internal variability during the near term, especially on the regional scale (IPCC AR6_WGI, confidence: high)
The mitigation benefits for these quantities would emerge only later during the 21st century (IPCC AR6_WGI, confidence: high)
During the near term, a small fraction of the surface can show cooling under all scenarios assessed here, so near-term cooling at any given location is fully consistent with GSAT increase (IPCC AR6_WGI, confidence: high)
Events of reduced and increased GSAT trends at decadal time scales will continue to occur in the 21st century but will not affect the centennial warming (IPCC AR6_WGI, confidence: very high)
The climate effect of a sudden and sustained CDR termination would depend on the amount of CDR-induced cooling prior to termination and the rate of background CO 2 emissions at the time of termination (IPCC AR6_WGI, confidence: high)
A sudden and sustained termination of SRM in a high-emissions scenario such as SSP5-8.5 would cause a rapid climate change (IPCC AR6_WGI, confidence: high)
Overshooting specific global warming levels such as 2°C has effects on the climate system that persist beyond 2100 (IPCC AR6_WGI, confidence: medium)
Under one scenario including a peak and decline in atmospheric CO 2 concentration (SSP5-3.4-OS), some climate metrics such as GSAT begin to decline but do not fully reverse by 2100 to levels prior to the CO 2 peak (IPCC AR6_WGI, confidence: medium)
GSAT projected for the end of the 23rd century under SSP5-8.5 (likely 6.6°C–14.1°C higher than over the period 1850–1900) overlaps with the range estimated for the Miocene Climatic Optimum (5°C–10°C higher) and Early Eocene Climatic Optimum (10°C–18°C higher), about 15 and 50 million years ago, respectively (IPCC AR6_WGI, confidence: medium)
The warming has increased in part because of models with higher ECS in CMIP6, compared to CMIP5 (IPCC AR6_WGI, confidence: high)
The AR5 further assessed that GSAT averaged over the period 2081–2100 are projected to likely exceed 1.5°C above 1850–1900 for RCP4.5, RCP6.0 and RCP8.5 (high confidence) and are likely to exceed 2°C above 1850–1900 for RCP6.0 and RCP8.5 (IPCC AR6_WGI, confidence: high)
Global surface temperature changes above 2°C under RCP2.6 were deemed unlikely (IPCC AR6_WGI, confidence: medium)
In summary, the CMIP6 models show a general tendency toward larger long-term globally averaged surface warming than did the CMIP5 models, for nominally comparable scenarios (IPCC AR6_WGI, confidence: very high)
In SSP1-2.6 and SSP2-4.5, the 5–95% ranges have remained similar to the ranges in RCP2.6 and RCP4.5, respectively, but the distributions have shifted upward by about 0.3°C (IPCC AR6_WGI, confidence: high)
For SSP5-8.5 compared to RCP8.5, the 5% bound of the distribution has hardly changed, but the 95% bound and the range have increased by about 20% and 40%, respectively (IPCC AR6_WGI, confidence: high)
This means that the CMIP6 spread in GSAT response to CO 2 emissions is dominated by climate sensitivity differences between ESMs more than by carbon cycle differences (IPCC AR6_WGI, confidence: high)