rlacombe/ClimateX huggingface dataset:
Ice-sheet model simulations indicate that Northern Hemisphere glaciation was limited to high-elevation regions in eastern and southern Greenland (IPCC AR6_WGI, confidence: medium)
Southern Hemisphere glaciation was characterized by an Antarctic Ice Sheet (AIS) reduced in volume from the present (IPCC AR6_WGI, confidence: medium)
In summary, under a past warming level of around 2.5°C–4°C, ice sheets in both hemispheres were reduced in extent compared to present (IPCC AR6_WGI, confidence: high)
Proxy-based evidence (Section 2.3.3.3) combined with numerical modelling indicates that, on millennial time scales, the GMSL contribution arising from ice sheets was >5 m (high confidence) or >10 m (IPCC AR6_WGI, confidence: medium)
The GMSL was 6–13 m above present (IPCC AR6_WGI, confidence: medium)
In summary, geological reconstructions and numerical simulations consistently show that past warming levels of <2°C (GMST) are sufficient to trigger multi- metre mass loss from both the Greenland and Antarctic ice sheets if maintained for millennia (IPCC AR6_WGI, confidence: high)
Since AR5, information has improved about the LIG, when GMST was about 0.5°C–1.5°C above 1850–1900 (IPCC AR6_WGI, confidence: medium)
It is virtually certain that GMSL was higher than today, likely by 5–10 m (IPCC AR6_WGI, confidence: medium)
Of the residual, up to about 1.4 m may be ascribed to groundwater, leaving a shortfall of 16 ± 10 m yet to be allocated among land ice reservoirs or lakes.9.6.2.5 Last Deglacial Transition: Meltwater pulse 1A During Meltwater pulse 1A (MWP-1A), GMSL very likely (IPCC AR6_WGI, confidence: medium)
In summary, MWP-1A appears to have been driven by a combination of melt in North America (high confidence), Eurasia (low confidence), and Antarctica (IPCC AR6_WGI, confidence: low)
At 6 ka, GMSL was –3.5 to +0.5 m (IPCC AR6_WGI, confidence: medium)
Geochronological and numerical modelling studies indicate that it is likely (IPCC AR6_WGI, confidence: medium)
In summary, higher-than-pre-industrial GMST during the mid-Holocene coincided with recession of the Greenland Ice Sheet to a smaller-than-present extent (IPCC AR6_WGI, confidence: high)
In summary, both proxies and model simulations indicate that GMSL changes during the early to mid-Holocene were the result of episodic pulses, due to drainage of meltwater lakes, superimposed on a trend of steady rise due to continued ice-sheet retreat (IPCC AR6_WGI, confidence: high)
The combination of tide gauge observations and geological reconstructions indicates that a sustained increase of GMSL began between 1820–1860 and led to a 20th-century GMSL rise that was very likely (IPCC AR6_WGI, confidence: high)
In summary, rates of RSL rise exceeding the pre-industrial background rate of rise are apparent in parts of the North Atlantic in the 19th century (medium confidence), and in most of the world in the 20th century (IPCC AR6_WGI, confidence: high)
Considering also projections incorporating MICI or SEJ (IPCC AR6_WGI, confidence: low)
RSL rise associated with GRD is very likely to be largest in the Pacific, due to the combined effects of projected GrIS, AIS and glacier mass loss (IPCC AR6_WGI, confidence: high)
In parts of north-eastern North America and north-western Europe, GRD effects associated with mass loss from southern Greenland will lead to an RSL fall, whereas mass loss from northern Greenland will lead to an RSL rise (IPCC AR6_WGI, confidence: high)
In particular, under SSP5-8.5, low-confidence processes could lead to a total GMSL rise of 0.6–1.6 m over this time period (17th–83rd percentile range of p-box, including SEJ- and MICI-based projections), with 5th–95th percentile projections extending to 0.5–2.3 m (IPCC AR6_WGI, confidence: low)
Approximately 60% (SSP1-1.9) to 70% (SSP5-8.5) of the global coastline has a projected median 21st century regional RSL rise within ±20% of the global mean m 1950 2000 2050 2100 2150 00.511.522.5 SSP5-8.5 SSP3-7.0 SSP2-4.5 SSP1-2.6 SSP1-1.9 HistoricalMedian (medium confidence) Likely range (IPCC AR6_WGI, confidence: medium)
Consistent with AR5, loss of land ice mass will be an important contributor to spatial patterns in RSL change (high confidence), with ocean dynamic sea level being particularly important as a dipolar contributor in the north-west Atlantic, a positive contributor in the Arctic Ocean, and a negative contributor in the Southern Ocean south of the Antarctic Circumpolar Current (IPCC AR6_WGI, confidence: medium)
As today, VLM will remain a major driver of RSL change (IPCC AR6_WGI, confidence: high)
Uncertainty in RSL projections is greatest in tectonically active areas in which VLM varies over short distances (e.g., Alaska) and in areas potentially subject to large ocean dynamic sea level change (e.g., the north-western Atlantic) (IPCC AR6_WGI, confidence: high)
The SROCC projected 0.6–1.0 m under RCP2.6 and 2.3–5.3 m under RCP8.5 (IPCC AR6_WGI, confidence: low)
Under SSP5-8.5, GMSL will rise between 1.7 and 6.8 m by 2300 in the absence of MICI and by up to 16 m considering MICI, a wider range than AR5 or SROCC assessments, but consistent with published projections (IPCC AR6_WGI, confidence: low)
On the basis of modelling studies, paleo constraints, single-ice-sheet studies finding multimillennial nonlinear responses from both the Greenland and Antarctic ice sheets (Sections 9.4.1.4 and 9.4.2.6), and the underlying physics, we conclude that GMSL commitment is nonlinear in peak warming on time scales of both 2,000 and 10,000 years (IPCC AR6_WGI, confidence: medium)
Although thermosteric sea level will start to decline slowly about 2,000 years after emissions cease, the slower responses from the Greenland and Antarctic ice sheets mean that GMSL will continue to rise for 10,000 years under most scenarios (IPCC AR6_WGI, confidence: medium)
Carbon dioxide removal, solar radiation modification, and local ice-shelf engineering may be effective at reducing the yet-to-be- realized sea level commitment, but ineffective at reversing GMSL rise (IPCC AR6_WGI, confidence: low)
In doing so, we note upfront that the main uncertainty related to high-end sea level rise is ‘when’ rather than ‘if’ it arises: the upper limit of 1.01 m of likely sea level range by 2100 for the SSP5-8.5 scenario will be exceeded in any future warming scenario on time scales of centuries to millennia (IPCC AR6_WGI, confidence: high)
As in AR5 and SROCC, tide gauge observations show that RSL rise (Section 9.6.1.3) is the primary driver of changes in ESWL at most locations and, across tide gauges, has led to a median 165% increase in high-tide flooding over 1995–2014 relative to those over 1960–1980 (IPCC AR6_WGI, confidence: high)
Some locations exhibit substantial differences between long-term RSL trends and ESWL (IPCC AR6_WGI, confidence: high)
Failing to consider the non-linear interactions between tide, surge and RSL may overestimate trends in ESWL (IPCC AR6_WGI, confidence: low)
Combined, observations and models indicate RSL rise and direct anthropogenic factors are the primary drivers of observed tidal changes at tide gauge stations (IPCC AR6_WGI, confidence: medium)
On the basis of satellite altimeter observations, SROCC reported increasing extreme wave heights in the Southern and North Atlantic oceans of around 1.0 and 0.8 cm yr –1, respectively, over the period 1985–2018 (IPCC AR6_WGI, confidence: medium)
The SROCC (Collins et al., 2019) also identified sea ice loss in the Arctic as leading to increased wave heights over the period 1992–2014 (IPCC AR6_WGI, confidence: medium)
However, sensitivity of processing techniques, inadequate spatial distribution of observations, and homogeneity issues in available records limit confidence in reported trends (IPCC AR6_WGI, confidence: medium)
Detection and attribution of the human influence on climatic changes in surges, and waves remains a challenge (Ceres et al., 2017), with limited evidence to suggest in some instances – for example, poleward migration of tropical cyclones in the Western North Pacific (Section 11.7.1.2), changes in surges and waves can be attributed to anthropogenic climate change (IPCC AR6_WGI, confidence: low)
The close relationship between local ESL and long-term RSL change, combined with the robust attribution of GMSL change (Section 9.6.1.4), implies that observed global changes in ESL can be attributed, at least in part, to human-caused climate change (IPCC AR6_WGI, confidence: medium)
The SROCC showed that currently rare ESL events (e.g., with an average return period of 100 years) will occur annually or more frequently at most available locations for RCP4.5 by the end of the century (IPCC AR6_WGI, confidence: high)
By 2100, the median frequency amplification factor is projected to be 163 for SSP1-2.6, 325 for SSP2-4.5, and 532 for SSP5-8.5, with respectively 60%, 71%, and 82% of the stations experiencing a currently 1% annual probability event at least yearly (IPCC AR6_WGI, confidence: medium)
In summary, despite waves and surges being non-negligible contributors to projected ETWL and ECWL changes (Vousdoukas et al., 2018; Melet et al., 2020), RSL change is expected to be the main driver in changes in future ESL return periods in most areas (IPCC AR6_WGI, confidence: medium)
At local and regional scales, anthropogenic factors such as major land reclamation efforts, as in the East China Sea (Song et al., 2013) or differing national coastal management strategies (maintaining the present coastline position or managed retreat) will locally modulate the influence of GMSL rise on tidal amplitude (IPCC AR6_WGI, confidence: medium)
Thus, projections of ESL that do not consider correlations between and among sea level forced and atmospherically forced drivers can differ strongly from coupled projections (IPCC AR6_WGI, confidence: medium)
The SROCC (Collins et al., 2019) highlighted compound events, or coincident occurrence of multiple hazards, as an example of deep uncertainty, and noted that failing to account for multiple factors contributing to extreme events will lead to underestimation of the probabilities of occurrence (IPCC AR6_WGI, confidence: high)
Distilling regional climate information from multiple lines of evidence and taking the user context into account will increase the fitness, usefulness and relevance for decision-making and enhances the trust users will have in applying it (IPCC AR6_WGI, confidence: high)
Taking the values of the relevant actors into account when co-producing climate information, and translating this information into the broader user context, improves the usefulness and uptake of this information (IPCC AR6_WGI, confidence: high)
The availability of multiple observational records, including reanalyses, that are fit for evaluating the phenomena of interest and account for observational uncertainty, are fundamental for both understanding past regional climate change and assessing climate model performance at regional scales (IPCC AR6_WGI, confidence: high)
Employing tailored, process-oriented and potentially multivariate diagnostics to evaluate whether a climate model realistically simulates relevant aspects of present-day regional climate increases trust in future projections of these aspects (IPCC AR6_WGI, confidence: high)
Precipitation measurements in mountainous areas, especially of solid precipitation, are strongly affected by gauge location and setup (IPCC AR6_WGI, confidence: very high)
Regional reanalyses represent the distributions of precipitation, surface air temperature, and surface wind, including the frequency of extremes, better than global reanalyses (IPCC AR6_WGI, confidence: high)
Global models by themselves provide a useful line of evidence for the construction of regional climate information through the attribution or projection of forced changes or the quantification of the role of the internal variability (IPCC AR6_WGI, confidence: high)
Dynamical downscaling using regional climate models adds value in representing many regional weather and climate phenomena, especially over regions of complex orography or with heterogeneous surface characteristics (IPCC AR6_WGI, confidence: very high)
Increasing climate model resolution improves some aspects of model performance (IPCC AR6_WGI, confidence: high)
Some local-scale phenomena such as land–sea breezes and mountain wind systems can only be realistically represented by simulations at a resolution of the order of 10 km or finer (IPCC AR6_WGI, confidence: high)
Simulations at kilometre-scale resolution add value in particular to the representation of convection, sub-daily precipitation extremes (high confidence) and soil-moisture– precipitation feedbacks (IPCC AR6_WGI, confidence: medium)
Including the relevant forcings (e.g., aerosols, land-use change and stratospheric ozone concentrations) and representing the relevant feedbacks (e.g., snow–albedo, soil-moisture–temperature, soil-moisture–precipitation) in global and regional models is a prerequisite for reproducing historical regional trends and ensuring fitness for future projections (IPCC AR6_WGI, confidence: high)
The sign of projected regional changes of variables such as precipitation and wind speed is in some cases only simulated in a trustworthy manner if relevant regional processes are represented (IPCC AR6_WGI, confidence: medium)
Statistical downscaling methods with carefully chosen predictors and an appropriate model structure for a given application realistically represent many statistical aspects of present-day daily temperature and precipitation (IPCC AR6_WGI, confidence: high)
Bias adjustment has proven beneficial as an interface between climate model projections and impact modelling in many different contexts (IPCC AR6_WGI, confidence: high)
Weather generators realistically simulate many statistical characteristics of present-day daily temperature and precipitation, such as extreme temperatures and wet- and dry-day transition probabilities (IPCC AR6_WGI, confidence: high)
Bias adjustment cannot overcome all consequences of unresolved or strongly misrepresented physical processes, such as large-scale circulation biases or local feedbacks, and may instead introduce other biases and implausible climate change signals (IPCC AR6_WGI, confidence: medium)
Using bias adjustment as a method for statistical downscaling, particularly for coarse-resolution global models, may lead to substantial misrepresentations of regional climate and climate change (IPCC AR6_WGI, confidence: medium)
The performance of statistical approaches and their fitness for future projections depends on predictors and change factors taken from the driving dynamical models (IPCC AR6_WGI, confidence: high)
Multi-model ensembles enable the assessment of regional climate response uncertainty (IPCC AR6_WGI, confidence: very high)
Discarding models that fundamentally misrepresent processes relevant for a given purpose improves the fitness of multi-model ensembles for generating regional climate information (IPCC AR6_WGI, confidence: high)
At the regional scale, multi-model mean and ensemble spread are not sufficient to characterize low-likelihood, high-impact changes or situations where different models simulate substantially different or even opposing changes (IPCC AR6_WGI, confidence: high)
Since AR5, the availability of multiple single-model initial-condition large ensembles (SMILEs) allows for a more robust separation of model uncertainty and internal variability in regional-scale projections and provides a more comprehensive spectrum of possible changes associated with internal variability (IPCC AR6_WGI, confidence: high)
Multiple attribution approaches, including optimal fingerprinting, grid-point detection, pattern recognition and dynamical adjustment methods, as well as multi-model, single-forcing large ensembles and multi-centennial paleoclimate records, support the contribution of human influence to several regional multi-decadal mean precipitation changes (IPCC AR6_WGI, confidence: high)
Multiple lines of evidence, combining multi-model ensemble global projections with those coming from SMILEs, show that internal variability is largely contributing to the delayed or absent emergence of the anthropogenic signal in long-term regional mean precipitation changes (IPCC AR6_WGI, confidence: high)
Annual mean daily minimum temperature is more affected by urbanization than annual mean daily maximum temperature (IPCC AR6_WGI, confidence: very high)
The global annual mean surface air temperature response to urbanization is, however, negligible (IPCC AR6_WGI, confidence: very high)
A large effect is expected from the combination of future urban development and more frequent occurrence of extreme climatic events, such as heatwaves (IPCC AR6_WGI, confidence: very high)
For example, the apparent contradiction between the observed decrease in Indian monsoon rainfall over the second half of the 20th century and the projected long-term increase is explained by attribution of the trends to different forcings, with aerosols dominating recently and greenhouse gases in the future (IPCC AR6_WGI, confidence: high)
Further, the chapter identified that the regional climate information was limited by the paucity of comprehensive observations and their analysis along with the different levels of confidence in projections (IPCC AR6_WGI, confidence: high)
Part of the projected increase in heatwaves and droughts can be attributed to soil moisture feedbacks in regions where evapotranspiration is limited by moisture availability (IPCC AR6_WGI, confidence: medium)
Vegetation changes can also amplify or dampen extreme events through changes in albedo and evapotranspiration, which will influence future trends in extreme events (IPCC AR6_WGI, confidence: medium)
Urbanization increases the risks associated with extreme events (IPCC AR6_WGI, confidence: high)
Urbanization suppresses evaporative cooling and amplifies heatwave intensity (high confidence) with a strong influence on minimum temperatures (IPCC AR6_WGI, confidence: high)
The SROCC assessed that it is virtually certain that Antarctica and Greenland have lost mass over the past decade and observed glacier mass loss over the last decades is attributable to anthropogenic climate change (IPCC AR6_WGI, confidence: high)
Averaged over the decade 2010–2019, monthly average sea ice area in August, September and October has been about 25% smaller than during 1979–1988 (IPCC AR6_WGI, confidence: high)
Availability of active sensors on LEO satellites enables measurement of microphysical properties of aerosol, cloud and precipitation, which can advance regional climate studies and process evaluation studies to improve regional climate models (IPCC AR6_WGI, confidence: high)
The regional reanalyses represent the frequencies of extremes and the distributions of precipitation, surface air temperature, and surface wind better than global reanalyses (IPCC AR6_WGI, confidence: high)
Regional reanalyses can provide estimates that are more consistent with observations than dynamical downscaling approaches, due to the assimilation of additional local observations (IPCC AR6_WGI, confidence: high)
Quality-controlled, high-resolution observational datasets are especially needed at regional and local scales to assess models as their resolution increases (Di Luca et al., 2016; Zittis and Hadjinicolaou, 2017), although the awareness and appropriate use of the QC information is challenging (Tapiador et al., 2017) when generating regional climate information (IPCC AR6_WGI, confidence: high)
Gridded products of climate variables, including temperature and precipitation, are strongly affected (IPCC AR6_WGI, confidence: high)
This technological trend could prove very useful (IPCC AR6_WGI, confidence: high)
Realistically representing local-scale phenomena such as land–sea breezes requires simulations at a resolution of the order of 10 km (IPCC AR6_WGI, confidence: high)
Simulations at kilometre-scale resolution add value in particular to the representation of convection, sub-daily summer precipitation extremes (high confidence) and soil-moisture–precipitation feedbacks (IPCC AR6_WGI, confidence: medium)
Resolving regional processes may be required to correctly represent the sign of regional climate change (IPCC AR6_WGI, confidence: medium)
Weather generators realistically simulate many statistical aspects of present-day daily temperature and precipitation (IPCC AR6_WGI, confidence: high)
The performance of these approaches and their fitness for future projections also depends on predictors and change factors taken from the driving dynamical models (IPCC AR6_WGI, confidence: high)
An accurate estimation of the delay in regional-scale emergence caused by internal variability remains challenging due to global model biases in their representation of internal variability as well as methodological difficulties to precisely estimate these biases (IPCC AR6_WGI, confidence: high)
This process enhances trust in the information as well its usefulness, relevance, and uptake, especially when the communication involves complex, contextual details (IPCC AR6_WGI, confidence: high)
Drawing upon multiple lines of evidence in the construction of climate information increases the fitness of this information and creates a stronger foundation (IPCC AR6_WGI, confidence: high)
Projections There is high confidence that by the end of century most regions in South America will undergo extreme heat stress conditions much more often than in the recent past, with about 50–100 more days per year under SSP1-2.6 and more than 200 additional days per year under SSP5-8.5 (IPCC AR6_WGI, confidence: high)
There is an increase in probability and intensity of agricultural and ecological droughts (medium confidence) and there is an increase in frequency and severity of hydrological droughts (IPCC AR6_WGI, confidence: high)
Attribution Global warming has contributed to drying in dry summer climates including the Mediterranean (IPCC AR6_WGI, confidence: high)
Multiple lines of evidence suggest that anthropogenic forcings are causing increased aridity and drought severity in the Mediterranean region (IPCC AR6_WGI, confidence: high)
These factors contribute to attribution of historical climate change signals (Section 10.4), recognizing that attribution must account for the interplay between externally forced Cross-Chapter Box 10.3 (continued) An increasing trend towards agricultural and ecological droughts has been attributed to human-induced climate change in the Mediterranean (IPCC AR6_WGI, confidence: medium)
Increased evapotranspiration due to growing atmospheric water demand will decrease soil moisture (IPCC AR6_WGI, confidence: high)
The seasonality of runoff and streamflow (the annual difference between the wettest and driest months of the year) is expected to increase with global warming (IPCC AR6_WGI, confidence: high)
The paleoclimate record provides context for these future expected changes: climate change will shift soil moisture outside the range of observed and reconstructed values spanning the last millennium (IPCC AR6_WGI, confidence: high)
In summary, long-term future scenarios dominated by GHG increases (such as the RCPs) suggest increases in Indian summer monsoon rainfall (IPCC AR6_WGI, confidence: high)
The SROCC assessed that HKH (named High Mountain Asia) surface-air temperature has warmed more rapidly than the global mean over recent decades (IPCC AR6_WGI, confidence: high)
Glacier trends The SROCC assessed that snow cover has declined in duration, depth and accumulated mass at lower elevations in mountain regions, including the HKH (IPCC AR6_WGI, confidence: high)
Glaciers are losing mass (very high confidence) and permafrost is warming (IPCC AR6_WGI, confidence: high)
The SR1.5 (IPCC, 2018b) stated that heavy precipitation risk in high-elevation regions is projected to be higher at 2°C compared to 1.5°C of global warming (IPCC AR6_WGI, confidence: medium)
The SROCC assessed that glaciers will lose substantial mass (high confidence) and permafrost will undergo increasing thaw and degradation (IPCC AR6_WGI, confidence: very high)
Glacier mass in HKH will decline through the 21st century (IPCC AR6_WGI, confidence: high)