John C. Fyfe’s research while affiliated with Environment Canada and other places

How global warming is impacting winter cold extremes is uncertain. Previous work has found decreasing winter temperature variability over North America which suggests a reduction in frequency and intensity of cold extremes relative to mean changes. However, others argue that cold air outbreaks are becoming more likely because of Arctic-induced changes in atmospheric circulation. Here we show that cold extremes over North America have warmed substantially faster than the winter mean temperature since 1980. This amplified warming is linked to both decreasing variance and changes in higher moments of the temperature distributions. Climate model simulations with historical forcings robustly capture the observed trends in extremes and variability. A pattern-based detection and attribution analysis shows that the changes in variability are detectable in observations and can be attributed to human influence. Our results highlight that human emissions are warming North American extreme cold temperatures beyond only shifting the winter mean temperature.

Human influence has been robustly detected throughout many parts of the climate system. Pattern-based methods have been used extensively to estimate the strength of model-predicted “fingerprints,” both human and natural, in observational data. However, individual studies using different analysis methods and time periods yield inconsistent estimates of the magnitude of the influence of anthropogenic aerosols, depending on whether they examined the troposphere, surface, or ocean. Reducing the uncertainty of the impact of aerosols on the climate system is crucial for understanding past climate change and obtaining more reliable estimates of climate sensitivity. To reconcile divergent estimates of aerosol effects obtained in previous studies, we apply the same regression-based detection and attribution method to three different variables: mid-to-upper-tropospheric temperature, surface temperature, and ocean heat content. We find that quantitative estimates of human influence in observations are consistent across these three independently monitored components of the climate system. Combining the troposphere, surface, and ocean data into a single multivariate fingerprint results in a small (∼10%) reduction of uncertainty of the magnitude of the greenhouse gas fingerprint, but a large (∼40%) reduction for the anthropogenic aerosol fingerprint. This reduction in uncertainty results in a substantially earlier time of detection of the multivariate aerosol fingerprint when compared to aerosol fingerprint detection time in each of the three individual variables. Our results highlight the benefits of analyzing data across the troposphere, surface, and ocean in detection and attribution studies, and motivate future work to further constrain uncertainties in aerosol effects on climate. Significance Statement Fingerprints of human influence have been detected separately across the troposphere, surface, and ocean. Previous studies examining the different parts of the climate system are difficult to compare quantitatively, however, because they use different methods and cover differ timespans. Here we find consistent estimates of the human influence on the troposphere, surface, and ocean over recent decades when the same fingerprint method and analysis period is used. When we combine the three variables into a single fingerprint, the uncertainty of the influence of anthropogenic aerosols is substantially reduced and the signal is detectable considerably earlier in the observational record. Our results highlight the benefits of performing analysis across different variables instead of focusing on one variable only.

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II (WGII) to categorize, assess and communicate a wide range of regional and sectoral key risks from climate change. These are risks expected to become severe due to the potentially detrimental convergence of changing climate conditions with the exposure and vulnerability of human and natural systems. Other papers in this special issue treat each of eight RKRs holistically by assessing their current status and future evolution as a result of this convergence. However, in these papers, such assessment cannot always be organized according to a systematic gradation of climatic changes. Often the big-picture evolution of risk has to be extrapolated from either qualitative effects of “low”, “medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C), together with consideration of the socio-economic context and possible adaptation choices.In this study we offer a representation – as systematic as possible given current literature and assessments – of the future evolution of the hazard components of RKRs.We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels (GWLs) to the extent possible. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group I supplemented when needed by more recent literature.For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with increasing GWLs has been identified. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - that link can only be described qualitatively. For some processes - like the behavior of ice sheets, or changes in circulation dynamics - large uncertainties about the effects of different GWLs remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems, in the absence of compensating changes in these systems’ exposure and vulnerability, and in the absence of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in their often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future potential evolution, an important component – if never the only one – of the future evolution of risk severity.

Plain Language Summary Ozone‐depleting substances (ODSs) are chemicals developed in the 1920s and 1930s for use in spray cans, refrigerators and plastic foams. Their commercial use increased rapidly in the 1950s and 1960s, but their phase out is underway since the signing of the Montreal Protocol in the 1987, following the identification of their devastating impact on the stratospheric ozone layer. It is well known that ODSs are powerful greenhouse gases, with the second largest warming effect between 1955 and 2005. However, their relative contribution to past global warming has not been quantified previously using comprehensive climate models. Here we show that ODSs were responsible for roughly a third of late 20th Century global warming, Arctic warming and Arctic sea ice decline. In addition, we find that the impact of ODSs on global temperatures is about 20% larger than expected based on the impacts they have on the radiative balance. The impacts of ODSs peak in the Arctic, while their radiative forcing peaks in the tropics, and thus opposes Arctic warming amplification. These findings enhance our understanding of drivers of past climate change, and highlight the importance of the Montreal Protocol for future climate change mitigation.

Projections of wintertime surface climate over Europe depend on reliable simulations of the North Atlantic atmospheric circulation from climate models. However, it is unclear whether these models capture the long-term observed trends in the North Atlantic circulation. Here, we show that over the period from 1951 to 2020, the wintertime North Atlantic jet has strengthened, while model trends are, on average, only very weakly positive. The observed strengthening is greater than in any one of the 303 simulations from 44 climate models considered in our study. This divergence between models and observations is now much more apparent because of a very strong jet observed over the past decade. The models similarly have difficulty capturing the observed precipitation trends over Europe. Our results suggest that projections of winter atmospheric circulation and associated precipitation over Europe may be unreliable because they fail to capture the response to human emissions or underestimate the magnitude of multidecadal-to-centennial time scale internal variability.

How do ocean initial states impact historical and future climate projections in Earth system models? To answer this question, we use the 50-member Canadian Earth System Model (CanESM2) large ensemble, in which individual ensemble members are initialized using a combination of different oceanic initial states and atmospheric micro-perturbations. We show that global ocean heat content anomalies associated with the different ocean initial states, particularly differences in deep ocean heat content due to ocean drift, persist from initialization at year 1950 through the end of the simulations at year 2100. We also find that these anomalies most readily impact surface climate over the Southern Ocean. Differences in ocean initial states affect Southern Ocean surface climate because persistent deep ocean temperature anomalies upwell along sloping isopycnal surfaces that delineate neighboring branches of the Upper and Lower Cells of the Global Meridional Overturning Circulation. As a result, up to a quarter of the ensemble variance in Southern Ocean turbulent heat fluxes, heat uptake, and surface temperature trends can be traced to variance in the ocean initial state, notably deep ocean temperature differences of order 0.1K due to model drift. Such a discernible impact of varying ocean initial conditions on ensemble variance over the Southern Ocean is evident throughout the full 150 simulation years of the ensemble, even though upper ocean temperature anomalies due to varying ocean initial conditions rapidly dissipate over the first two decades of model integration over much of the rest of the globe.

The Southern Ocean is a primary heat sink that buffers atmospheric warming and has warmed substantially, accounting for an outsized portion of global warming-induced excess heat in the climate system. However, its projected warming is highly uncertain and varies substantially across climate models. Here, using outputs from Coupled Model Intercomparison Project phase six models, we show that Southern Ocean warming during the twenty-first century is linked to the change in amplitude of the El Niño–Southern Oscillation (ENSO). Models simulating a larger increase in ENSO amplitude systematically produce a slower Southern Ocean warming; conversely, a smaller increase in ENSO amplitude sees a stronger warming. The asymmetry in amplitude and teleconnection between El Niño and La Niña produce cumulative surface wind anomalies over the southern high latitudes, impacting Southern Ocean heat uptake. The magnitude of inter-model ENSO variations accounts for about 50% of the uncertainty in the projected Southern Ocean warming.

Previous work identified an anthropogenic fingerprint pattern in T AC ( x,t ), the amplitude of the seasonal cycle of mid- to upper tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T AC ( x,t ) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their T AC ( x,t ) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3-4) inter-model and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal T AC ( x,t ) variability associated with the Atlantic Multidecadal Oscillation and the El Niño~Southern Oscillation. The robustness of the seasonal cycle D&A results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced T AC ( x,t ) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.

As the leading mode of Pacific variability, El Niño–Southern Oscillation (ENSO) causes vast and widespread climatic impacts, including in the stratosphere. Following discovery of a stratospheric pathway of ENSO to the Northern Hemisphere surface, here we aim to investigate if there is a substantial Southern Hemisphere (SH) stratospheric pathway in relation to austral winter ENSO events. Large stratospheric anomalies connected to ENSO occur on average at high SH latitudes as early as August, peaking at around 10 hPa. An overall colder austral spring Antarctic stratosphere is generally associated with the warm phase of the ENSO cycle, and vice versa. This behavior is robust among reanalysis and six separate model ensembles encompassing two different model frameworks. A stratospheric pathway is identified by separating ENSO events that exhibit a stratospheric anomaly from those that do not and comparing to stratospheric extremes that occur during neutral ENSO years. The tropospheric eddy-driven jet response to the stratospheric ENSO pathway is the most robust in the spring following a La Niña, but extends into summer, and is more zonally symmetric compared to the tropospheric ENSO teleconnection. The magnitude of the stratospheric pathway is weaker compared to the tropospheric pathway and therefore, when it is present, has a secondary role. For context, the magnitude is approximately half that of the eddy-driven jet modulation due to austral spring ozone depletion in the model simulations. This work establishes that the stratospheric circulation acts as an intermediary in coupling ENSO variability to variations in the austral spring and summer tropospheric circulation.

Sahel summertime precipitation declined from the 1950s to 1970s and recovered from the 1970s to 2000s. Anthropogenic aerosol contributions to this evolution are typically attributed to interhemispheric gradient changes of Atlantic Ocean sea surface temperature (SST). However recent work by Hirasawa et al. indicates a more complex picture, with the response being a combination of “fast” direct atmospheric (DA) processes and “slow” ocean-mediated (OM) processes. Here, we extend this understanding using the Community Atmosphere Model 5 to determine the role of regional ocean-basin perturbations and regional aerosol emission changes in the overall aerosol-driven OM and DA responses, respectively. From the 1950s to 1970s, there was an OM Sahel wetting response due to Pacific Ocean cooling that was offset by drying due to Atlantic cooling. By contrast, from the 1970s to 2000s, Atlantic trends reversed and amplified the Pacific cooling-induced wetting. This wetting was partially offset by drying driven by Indian Ocean cooling. Thus, the OM Sahel precipitation response to aerosol crucially depends on the balance of responses to Atlantic, Pacific, and Indian Ocean SST anomalies. From the 1950s to 1970s, there is DA Sahel drying that was principally due to North American aerosol emissions, with negligible effect from European emissions. DA drying from the 1970s to 2000s was mainly due to African aerosol emissions. Thus, the shifting roles of regional OM and DA effects reveal a complex interplay of direct driving and remote teleconnections in determining the time evolution of Sahel precipitation due to aerosol forcing in the late twentieth century. Significance Statement Studies of global climate models consistently indicate that anthropogenic aerosol emissions were a significant contributor to a severe drought that occurred in the Sahel region of Africa in the late twentieth century. The drying influence of aerosol forcing is the combined result of rapid atmospheric responses directly due to the forcing and slower responses due to forced ocean temperature changes. Using a set of simulations targeted at determining the influences from different ocean basins and different emission regions for two periods in the late twentieth century, we find there is a surprising range of mechanisms through which aerosol emissions affect the Sahel. This results in a complex interplay of at times competing and at times complementary regional influences.