![SIXTH ASSESSMENT REPORT
Working Group I – The Physical Science Basis
• Observed climatic changes since pre-industrial era at any spatial scale are a combination of long-term
human-caused changes and natural variations on time scales from days to decades.
Regardless of future levels of global warming, this combination will continue in the future.
• Natural variations consist of both natural radiatively-forced signals (due to volcanic eruptions or solar
variations) and internal fluctuations of the climate system, which occur spontaneously i.e. in the absence
of any radiative forcings.
• Natural climate variability has temporarily obscured/attenuated or
intensified human-caused climate change at decadal time scales
• Year-to-year variability on top of human-caused warming is mostly
controlled by internal variability
Observed global temperature changes
with respect to 1850-1900
Example of intensification
Example of attenuation
Year-to-year fingerprint of
internal variability
• The ratio between the long-term human-induced change
(signal) and the amplitude of year-to-year internal variability
(noise) [ = a metric that is attached to our perception of past
and future climate changes], differs from global to regional
scales and between regions.
Source: Figure SPM.1 AR6
How about Europe?
Background](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Similar to Climate change and internal variability in Europe
Similar to Climate change and internal variability in Europe (20)
More from ipcc-media
More from ipcc-media (20)
Recently uploaded
Recently uploaded (20)
Climate change and internal variability in Europe
- 1. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis 9 August 2021 #ClimateReport #IPCC SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Climate change and internal variability in EUROPE Christophe CASSOU Lead Author WGI Chapter 3 Centre National de Recherche Scientifique (France)
- 2. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis • Observed climatic changes since pre-industrial era at any spatial scale are a combination of long-term human-caused changes and natural variations on time scales from days to decades. Regardless of future levels of global warming, this combination will continue in the future. • Natural variations consist of both natural radiatively-forced signals (due to volcanic eruptions or solar variations) and internal fluctuations of the climate system, which occur spontaneously i.e. in the absence of any radiative forcings. • Natural climate variability has temporarily obscured/attenuated or intensified human-caused climate change at decadal time scales • Year-to-year variability on top of human-caused warming is mostly controlled by internal variability Observed global temperature changes with respect to 1850-1900 Example of intensification Example of attenuation Year-to-year fingerprint of internal variability • The ratio between the long-term human-induced change (signal) and the amplitude of year-to-year internal variability (noise) [ = a metric that is attached to our perception of past and future climate changes], differs from global to regional scales and between regions. Source: Figure SPM.1 AR6 How about Europe? Background
- 3. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis The year-to-year internal variability (noise) is stronger at midlatitudes than in the tropics. It is especially true over Europe. 1 Source: Fig 1.14 AR6 Regional properties of internal variability 1
- 4. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis In all European areas, the human-caused temperature rise (signal) is stronger than global mean temperature changes and than the rise over most tropical lands The year-to-year internal variability (noise) is stronger at midlatitudes than in the tropics. It is especially true over Europe. 2 1 Source: Fig 1.14 AR6 2 Observed annual temperature changes in 2020 Regional properties of internal variability and warming 1
- 5. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Emergence Source: Fig.TS24 AR6 1 2 Time of emergence = date from which the new mean climate corresponds to unfamiliar conditions in preindustrial period (unfamiliar=less than about 2% of chance of occurrence based on observed years over preindustrial time i.e. ratio signal/noise =2) • Emergence “delayed” over Europe with a latitudinal gradient due to greater weight of internal variability going north despite stronger warming 1981-1988 for Mediterranean (MED) 1997-2004 for WCE and EEU 2005-2012 for Northern Europe (NEU) • Emergence differs between regions, between climate variables and between seasons Weight of internal Variability: Regional >> global Mid-latitudes >> Tropics Precipitation >> Temperature Winter >> Annual >> Summer
- 6. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis • At oceanic- or continental-basin scales, internal variability is usually organized through so-called modes of variability, defined as recurrent space-time structures of variability with intrinsic spatial patterns, seasonality and timescales (see Technical Annex IV, AR6). • At oceanic- or continental-basin scales, the variability of the climate system on top of human-caused climate trends can be described to a large extent at seasonal-to-multidecadal timescales by the occurrence and often combination of several modes of climate variability which lead to local impacts and remote responses through teleconnection processes . • 7 modes of interannual variability + 2 modes of decadal variability have been assessed in AR6 NAM-NAO (North Atlantic Oscillation – Northern Annular Modes) SAM (Southern Annular mode) ENSO (El Nino Southern Oscillation) IOB (Indian Ocean Basin) & IOD (Indian Ocean Dipole) AZM (Atlantic Zonal Mode) & AMM (Atlantic Meridional Mode) AMV (Atlantic Multidecadal Variability) PDV (Pacific Decadal Variability) Modes of variability (MoVs) NAO Fraction of surface air temperature (SAT) and precipitation (pr) variance explained at interannual timescales for European regions Europe Source: Table TS.4 AR6
- 7. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis • Since preindustrial period, natural climate variability have temporarily obscured and intensified human-caused climate change on interannual to decadal time scales Internal variability as a modulator of past but also future human-caused changes • Natural drivers and internal variability WILL either amplify or attenuate projected human-caused changes in mean climate and climatic impact drivers(CIDs), including extremes, especially at regional scales and in the near-term [2020-2040], but with little effect on centennial global warming (high confidence) Near-term cooling at any particular location with respect to present climate could occur and would be consistent with the global surface temperature increase due to human influence (high confidence) • Modulations driven by internal variability are important to consider in planning for the full ranges of possible changes for risk assessment and regional adaptation
- 8. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis • Use of larger ensembles of Global Circulation Models to better explore and account for internal variability at near-term and at regional scale, and in particular the use of a collection of so-called single model initial condition large ensembles, a novelty in AR6. Source: Figure 1.21, AR6 Assessment of climate outcomes at near-term • Accounting better for internal variability strengthens the conclusion on the forced response. Different phasing of internal variability Range of internal variability Ensemble mean
- 9. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Source: Line et al. (2021), PC Full range of temperature outcome over Europe in winter @near-term Human-caused best estimate response: Warming [Europe] = +0.89o Difference of temperature between near-term [2020-2040] and historical [1995-2014] periods for 30 individual members One model: CNRM-CM6, one scenario : ssp2-4.5 Warmest Coldest Ensemble mean [30 members]
- 10. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Source: Line et al. (2021), PC Internal variability can partially mask human-caused warming @near-term (ex. North Europe region – NEU) Distribution of the temperature difference between near-term [2020-2040] and historical [1995-2014] periods averaged over NEU for ssp2-4.5 Human-caused best estimate NEU 10% 25% Mean 75% 90% NEU Warmest Coldest
- 11. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Source: Line et al. (2021), PC Internal variability partially masks discernible differences between scenarios over NEU @near-term Human-caused best estimate NEU NEU Distributions for the 4 illustrative scenarios are statistically undistinguishable over NEU @near-term Distribution of the temperature difference between near-term [2020-2040] and historical [1995-2014] periods averaged over NEU for ssp2-4.5 ssp1-2.6 ssp3-7.0 ssp5-8.5
- 12. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Modulations driven by internal variability are important to consider in planning for the full ranges of possible changes for risk assessment and regional adaptation strategies, especially @near-term because internal variability can significantly amplify or attenuate human caused changes Over Europe, accounting for internal variability is essential as its weight is large with respect to other regions. Summary
- 13. SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis 9 August 2021 #ClimateReport #IPCC SIXTH ASSESSMENT REPORT Working Group I – The Physical Science Basis Thank you. @IPCC @IPCC_CH linkedin.com/company/ipcc IPCC: www.ipcc.ch IPCC Secretariat: ipcc-sec@wmo.int IPCC Press Office: ipcc-media@wmo.int Interactive Atlas: interactive-atlas.ipcc.ch More Information: Follow Us: