scholarly journals Detection and Attribution of Multivariate Climate Change Signals Using Discriminant Analysis and Bayesian Theorem

2017 ◽  
Vol 30 (19) ◽  
pp. 7757-7776
Author(s):  
Heiko Paeth ◽  
Felix Pollinger ◽  
Christoph Ring

Abstract Detection and attribution methods in climatological research aim at assessing whether observed climate anomalies and trends are still consistent with the range of natural climate variations or rather an indication of anthropogenic climate change. In this study, the authors pursue a novel approach by using discriminant analysis to enhance the distinction between past and future climates from state-of-the-art climate model simulations. The method is based on multivariate fingerprints that are defined in the space of several prominent climate indices representing the thermal, dynamical, and hygric aspects of climate change. Attribution is carried out by means of a Bayesian classification approach. The leading discriminant function accounts for more than 99% of total discriminability, with temperature variables, extratropical precipitation, and extratropical circulation modes mainly contributing to the discriminant power. The misclassification probability between probability density functions of past and future climates is substantially reduced by the discriminant analysis: from >50% to <15%. Since the mid-1980s, the observed anomalies of the considered climate indices are more or less consistently attributed to a climate under strong radiative forcing, projected for the first half of the twenty-first century. The authors also assess the sensitivity of their results to different emissions scenarios from the CMIP3 and CMIP5 multimodel ensembles, seasons, prior probabilities for the early twenty-first-century climate, estimates of the observational error, low-pass filters, variable compositions, group numbers, and reference data.

2018 ◽  
Vol 31 (20) ◽  
pp. 8281-8303 ◽  
Author(s):  
Kieran Bhatia ◽  
Gabriel Vecchi ◽  
Hiroyuki Murakami ◽  
Seth Underwood ◽  
James Kossin

As one of the first global coupled climate models to simulate and predict category 4 and 5 (Saffir–Simpson scale) tropical cyclones (TCs) and their interannual variations, the High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model at the Geophysical Fluid Dynamics Laboratory (GFDL) represents a novel source of insight on how the entire TC intensification distribution could be transformed because of climate change. In this study, three 70-yr HiFLOR experiments are performed to identify the effects of climate change on TC intensity and intensification. For each of the experiments, sea surface temperature (SST) is nudged to different climatological targets and atmospheric radiative forcing is specified, allowing us to explore the sensitivity of TCs to these conditions. First, a control experiment, which uses prescribed climatological ocean and radiative forcing based on observations during the years 1986–2005, is compared to two observational records and evaluated for its ability to capture the mean TC behavior during these years. The simulated intensification distributions as well as the percentage of TCs that become major hurricanes show similarities with observations. The control experiment is then compared to two twenty-first-century experiments, in which the climatological SSTs from the control experiment are perturbed by multimodel projected SST anomalies and atmospheric radiative forcing from either 2016–35 or 2081–2100 (RCP4.5 scenario). The frequency, intensity, and intensification distribution of TCs all shift to higher values as the twenty-first century progresses. HiFLOR’s unique response to climate change and fidelity in simulating the present climate lays the groundwork for future studies involving models of this type.


2020 ◽  
Vol 33 (9) ◽  
pp. 3431-3447
Author(s):  
Tobias Spiegl ◽  
Ulrike Langematz

AbstractSatellite measurements over the last three decades show a gradual decrease in solar output, which can be indicative as a precursor to a modern grand solar minimum (GSM). Using a chemistry–climate model, this study investigates the potential of two GSM scenarios with different magnitude to counteract the climate change by projected anthropogenic greenhouse gas (GHG) emissions through the twenty-first century. To identify regions showing enhanced vulnerability to climate change (hot spots) and to estimate their response to a possible modern GSM, a multidimensional metric is applied that accounts for—in addition to changes in mean quantities—seasonal changes in the variability and occurrence of extreme events. We find that a future GSM in the middle of the twenty-first century would temporarily mitigate the global mean impact of anthropogenic climate change by 10%–23% depending on the GSM scenario. A future GSM would, however, not be able to stop anthropogenic global warming. For the GHG-only scenario, our hot-spot analysis suggests that the midlatitudes show a response to rising GHGs below global average, while in the tropics, climate change hot spots with more frequent extreme hot seasons will develop during the twenty-first century. A GSM would reduce the climate change warming in all regions. The GHG-induced warming in Arctic winter would be dampened in a GSM due to the impact of reduced solar irradiance on Arctic sea ice. However, even an extreme GSM could only mitigate a fraction of the tropical hot-spot pattern (up to 24%) in the long term.


Author(s):  
Richard A. Betts ◽  
Matthew Collins ◽  
Deborah L. Hemming ◽  
Chris D. Jones ◽  
Jason A. Lowe ◽  
...  

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate–carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with ‘FI’ standing for ‘fossil intensive’. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC’s ‘likely range’.


2012 ◽  
Vol 26 (21) ◽  
pp. 8269-8288 ◽  
Author(s):  
Alvaro Semedo ◽  
Ralf Weisse ◽  
Arno Behrens ◽  
Andreas Sterl ◽  
Lennart Bengtsson ◽  
...  

Abstract Wind-generated waves at the sea surface are of outstanding importance for both their practical relevance in many aspects, such as coastal erosion, protection, or safety of navigation, and for their scientific relevance in modifying fluxes at the air–sea interface. So far, long-term changes in ocean wave climate have been studied mostly from a regional perspective with global dynamical studies emerging only recently. Here a global wave climate study is presented, in which a global wave model [Wave Ocean Model (WAM)] is driven by atmospheric forcing from a global climate model (ECHAM5) for present-day and potential future climate conditions represented by the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. It is found that changes in mean and extreme wave climate toward the end of the twenty-first century are small to moderate, with the largest signals being a poleward shift in the annual mean and extreme significant wave heights in the midlatitudes of both hemispheres, more pronounced in the Southern Hemisphere and most likely associated with a corresponding shift in midlatitude storm tracks. These changes are broadly consistent with results from the few studies available so far. The projected changes in the mean wave periods, associated with the changes in the wave climate in the middle to high latitudes, are also shown, revealing a moderate increase in the equatorial eastern side of the ocean basins. This study presents a step forward toward a larger ensemble of global wave climate projections required to better assess robustness and uncertainty of potential future wave climate change.


Author(s):  
Nathan P. Gillett

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081–2100 relative to 1986–2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5–95% warming range of 0.8–2.5 K is somewhat lower than the unweighted range of 1.1–2.6 K reported in the IPCC AR5.


2012 ◽  
Vol 69 (8) ◽  
pp. 2608-2618 ◽  
Author(s):  
Daniel M. Mitchell ◽  
Scott M. Osprey ◽  
Lesley J. Gray ◽  
Neal Butchart ◽  
Steven C. Hardiman ◽  
...  

Abstract With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.


2012 ◽  
Vol 25 (8) ◽  
pp. 2696-2710 ◽  
Author(s):  
Stephen J. Vavrus ◽  
Marika M. Holland ◽  
Alexandra Jahn ◽  
David A. Bailey ◽  
Benjamin A. Blazey

Abstract The authors summarize the twenty-first-century Arctic climate simulated by NCAR’s Community Climate System Model, version 4 (CCSM4). Under a strong radiative forcing scenario, the model simulates a much warmer, wetter, cloudier, and stormier Arctic climate with considerably less sea ice and a fresher Arctic Ocean. The high correlation among the variables composing these changes—temperature, precipitation, cloudiness, sea level pressure (SLP), and ice concentration—suggests that their close coupling collectively represents a fingerprint of Arctic climate change. Although the projected changes in CCSM4 are generally consistent with those in other GCMs, several noteworthy features are identified. Despite more global warming in CCSM4, Arctic changes are generally less than under comparable greenhouse forcing in CCSM3, as represented by Arctic amplification (16% weaker) and the date of a seasonally ice-free Arctic Ocean (20 years later). Autumn is the season of the most pronounced Arctic climate change among all the primary variables. The changes are very similar across the five ensemble members, although SLP displays the largest internal variability. The SLP response exhibits a significant trend toward stronger extreme Arctic cyclones, implying greater wave activity that would promote coastal erosion. Based on a commonly used definition of the Arctic (the area encompassing the 10°C July air temperature isotherm), the region shrinks by about 40% during the twenty-first century, in conjunction with a nearly 10-K warming trend poleward of 70°N. Despite this pronounced long-term warming, CCSM4 simulates a hiatus in the secular Arctic climate trends during a decade-long stretch in the 2040s and to a lesser extent in the 2090s. These pauses occur despite averaging over five ensemble members and are remarkable because they happen under the most extreme greenhouse-forcing scenario and in the most climatically sensitive region of the world.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.


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