scholarly journals Responsibility of major emitters for country-level warming and extreme hot years

2022 ◽  
Vol 3 (1) ◽  
Author(s):  
Lea Beusch ◽  
Alexander Nauels ◽  
Lukas Gudmundsson ◽  
Johannes Gütschow ◽  
Carl-Friedrich Schleussner ◽  
...  

AbstractThe contributions of single greenhouse gas emitters to country-level climate change are generally not disentangled, despite their relevance for climate policy and litigation. Here, we quantify the contributions of the five largest emitters (China, US, EU-27, India, and Russia) to projected 2030 country-level warming and extreme hot years with respect to pre-industrial climate using an innovative suite of Earth System Model emulators. We find that under current pledges, their cumulated 1991–2030 emissions are expected to result in extreme hot years every second year by 2030 in twice as many countries (92%) as without their influence (46%). If all world nations shared the same fossil CO2 per capita emissions as projected for the US from 2016–2030, global warming in 2030 would be 0.4 °C higher than under actual current pledges, and 75% of all countries would exceed 2 °C of regional warming instead of 11%. Our results highlight the responsibility of individual emitters in driving regional climate change and provide additional angles for the climate policy discourse.

2010 ◽  
Vol 36 ◽  
pp. 7-21 ◽  
Author(s):  
Katharine Hayhoe ◽  
Jeff VanDorn ◽  
Thomas Croley ◽  
Nicole Schlegal ◽  
Donald Wuebbles

2013 ◽  
Vol 6 (1) ◽  
pp. 2213-2248 ◽  
Author(s):  
E. Monier ◽  
J. R. Scott ◽  
A. P. Sokolov ◽  
C. E. Forest ◽  
C. A. Schlosser

Abstract. This paper describes an integrated assessment modelling framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyse uncertainties in emissions resulting from both uncertainties in the economic model parameters and uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change associated with uncertainty in the climate response and projected emissions. This study presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century global climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, especially when it comes to changes in precipitation.


2021 ◽  
Author(s):  
Lea Beusch ◽  
Alexander Nauels ◽  
Lukas Gudmundsson ◽  
Carl-Friedrich Schleussner ◽  
Sonia I. Seneviratne

<p>Human influence on climate is not usually disentangled in the contribution of single emitters, especially when assessing changes and impacts in individual countries. However, such information could help individual countries understand their role in driving climate change and thus aid them in committing to fair and evidence-based emission reduction targets. Here, we quantify the contribution of single emitters to country-level median warming and extremes based on historical emissions and currently pledged policy targets. Thereby, we focus on the five largest historical emitters – China, the United States of America, the European Union, India, and Russia. While large ensembles are needed for this task, the computational burden of running full Earth System Models (ESMs) renders it impossible to answer our question with actual ESMs. Instead, we combine a physical global mean temperature emulator (Meinshausen et al., 2009) with a statistical spatially-resolved ESM emulator (Beusch et al., 2020) to create millions of temperature field time series. Our setup accounts for three major sources of uncertainty: (i) uncertainty in the global temperature response to greenhouse gas emissions, (ii) uncertainty in the regional response to global warming, (iii) uncertainty due to internal climate variability. </p><p>We find that historically rare hot years (occurring about once every 100 years in pre-industrial times) are expected at least every second year in 89 % (likely range: 71 – 100 %) of all countries by 2030. Without the emissions of the top five emitters over the time period during which policy makers had been informed about the looming anthropogenic climate crisis, i.e., after the first IPCC report of 1990, it would be 40 % (10 – 64 %) of all countries instead. Furthermore, when considering all current and projected emissions until 2030, 8 % (0 – 54 %) of countries are headed towards surpassing 2.0 °C of warming since pre-industrial times by 2030. If all nations followed the same per capita emissions as the USA since the 2015 Paris Agreement, the percentage of countries surpassing 2.0 °C by 2030 would amount to 78 % (24 – 96 %). Generally, northern high latitude countries experience the largest changes in median warming and tropical Africa the largest changes in extremes. Our results emphasize the relevance of individual emitters, and in particular the top five emitters, in driving regional climate change across different time periods.</p><p>Beusch, L., Gudmundsson, L., and Seneviratne, S. I. (ESD, 2020): https://doi.org/10.5194/esd-11-139-2020</p><p>Meinshausen, M., Meinshausen, N., Hare, W. et al. (Nature, 2009): https://doi.org/10.1038/nature08017</p>


2013 ◽  
Vol 6 (6) ◽  
pp. 2063-2085 ◽  
Author(s):  
E. Monier ◽  
J. R. Scott ◽  
A. P. Sokolov ◽  
C. E. Forest ◽  
C. A. Schlosser

Abstract. This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap – but display similar size – over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.


2010 ◽  
Vol 6 (5) ◽  
pp. 674-677 ◽  
Author(s):  
Michael R. Kearney ◽  
Natalie J. Briscoe ◽  
David J. Karoly ◽  
Warren P. Porter ◽  
Melanie Norgate ◽  
...  

There is strong correlative evidence that human-induced climate warming is contributing to changes in the timing of natural events. Firm attribution, however, requires cause-and-effect links between observed climate change and altered phenology, together with statistical confidence that observed regional climate change is anthropogenic. We provide evidence for phenological shifts in the butterfly Heteronympha merope in response to regional warming in the southeast Australian city of Melbourne. The mean emergence date for H. merope has shifted −1.5 days per decade over a 65-year period with a concurrent increase in local air temperatures of approximately 0.16°C per decade. We used a physiologically based model of climatic influences on development, together with statistical analyses of climate data and global climate model projections, to attribute the response of H. merope to anthropogenic warming. Such mechanistic analyses of phenological responses to climate improve our ability to forecast future climate change impacts on biodiversity.


2020 ◽  
Vol 11 (6-2) ◽  
pp. 755-770
Author(s):  
Jungi Moon ◽  
Changsub Shim ◽  
OkJin Jung ◽  
Je-Woo Hong ◽  
Jihyun Han ◽  
...  

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.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3704
Author(s):  
Agnieszka Karman ◽  
Andrzej Miszczuk ◽  
Urszula Bronisz

The article deals with the competitiveness of regions in the face of climate change. The aim was to present the concept of measuring the Regional Climate Change Competitiveness Index. We used a comparative and logical analysis of the concept of regional competitiveness and heuristic conceptual methods to construct the index and measurement scale. The structure of the index includes six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, Social, and 89 indicators. A practical application of the model was presented for the Mazowieckie province in Poland. This allowed the region’s performance in the context of climate change to be presented, and regional weaknesses in the process of adaptation to climate change to be identified. The conclusions of the research confirm the possibility of applying the Regional Climate Change Competitiveness Index in the economic analysis and strategic planning. The presented model constitutes one of the earliest tools for the evaluation of climate change competitiveness at a regional level.


2017 ◽  
Author(s):  
Chunlüe Zhou ◽  
Yanyi He ◽  
Kaicun Wang

Abstract. Reanalyses have been widely used because they add value to the routine observations by generating physically/dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies have extensively discussed their temporal suitability in global change study. This study moves forward on their suitability for regional climate change study where land–atmosphere interactions play a more important role. Here, surface air temperature (Ta) from 12 current reanalysis products were investigated, focusing on spatial patterns of Ta trends, using homogenized Ta from 1979 to 2010 at ~ 2200 meteorological stations in China. Results show that ~ 80 % of the Ta mean differences between reanalyses and in-situ observations are attributed to station and model-grid elevation differences, denoting good skill in Ta climatology and rebutting the previously reported Ta biases. However, the Ta trend biases in reanalyses display spatial divergence (standard deviation = 0.15–0.30 °C/decade at 1° × 1° grids). The simulated Ta trend biases correlate well with those of precipitation frequency, surface incident solar radiation (Rs), and atmospheric downward longwave radiation (Ld) among the reanalyses (r = −0.83, 0.80 and 0.77, p 


Sign in / Sign up

Export Citation Format

Share Document