scholarly journals Rapid attribution analysis of the extraordinary heatwave on the Pacific Coast of the US and Canada June 2021

2021 ◽  
Author(s):  
Sjoukje Y. Philip ◽  
Sarah F. Kew ◽  
Geert Jan van Oldenborgh ◽  
Faron S. Anslow ◽  
Sonia I. Seneviratne ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Pacific Northwest ◽  
Industrial Revolution ◽  
Climate Models ◽  
Well Being ◽  
Daily Maximum ◽  
Attribution Analysis ◽  
The Pacific ◽  
Temperature Records

Abstract. Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific northwest areas of the U.S. and Canada, leading to spikes in sudden deaths, and sharp increases in hospital visits for heat-related illnesses and emergency calls. Here we present a multi-model, multi-method attribution analysis to investigate to what extent human-induced climate change has influenced the probability and intensity of extreme heatwaves in this region. Based on observations and modeling, the occurrence of a heatwave with maximum daily temperatures (TXx) as observed in the area 45° N–52° N, 119° W–123° W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lie far outside the range of historically observed temperatures. This makes it hard to quantify with confidence how rare the event was. In the most realistic statistical analysis, which uses the assumption that the heatwave was a very low probability event that was not caused by new nonlinearities, the event is estimated to be about a 1 in 1000 year event in today’s climate. With this assumption and combining the results from the analysis of climate models and weather observations, an event, defined as daily maximum temperatures (TXx) in the heatwave region, as rare as 1 in a 1000 years would have been at least 150 times rarer without human-induced climate change. Also, this heatwave was about 2 °C hotter than a 1 in 1000-year heatwave that at the beginning of the industrial revolution would have been (when global mean temperatures were 1.2 °C cooler than today). Looking into the future, in a world with 2 °C of global warming (0.8 °C warmer than today), a 1000-year event would be another degree hotter. It would occur roughly every 5 to 10 years in such global warming conditions. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being, and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

scholarly journals Creating the Healthiest Nation: Climate Change and Environmental Health Impacts in Nigeria: A Narrative Review

2021 ◽  
Vol 6 (1) ◽  
pp. p61
Author(s):  
Morufu Olalekan Raimi ◽  
Tonye Vivien Odubo ◽  
Adedoyin Oluwatoyin Omidiji
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
21St Century ◽  
Industrial Revolution ◽  
Environmental Changes ◽  
Heat Waves ◽  
Human Life ◽  
Well Being ◽  
Intergovernmental Panel ◽  
Mitigation And Adaptation

Climate change is a “threat multiplier and a prime cause of universal threat to health in the 21st century, including 4th industrial revolution. The health effects of climate change will increase dramatically over the next few years and pose a risk to human life and the well-being of billions of people. As we all know, the milieu is fundamental to our sustained earth survival and environmental changes (natural and artificial) affect it either to the benefit or detriment of humans. Climate change is one of such changes in the physical environment which has grave consequences for the existence of mankind. Climate change is interestingly, no longer a speculative subject. There is a good international scientific consensus existing to show that this phenomenon is real and if recent global warming movements continue, temperature rise, ocean levels and more frequently weather conditions that is extreme (storms, heat-waves, droughts, floods, cyclones, etc.) may perhaps cause severe food shortages, loss of shelter, water, livelihoods, extinction of flora and fauna species. In the recent past, the earth has witnessed devastating weather-related events in different portions of the globe including hurricanes (e.g., Katrina and Rita in USA), tsunamis, typhoons, flooding especially in the Asian Continent, wild fires especially in Australia, USA, etc. Currently, the on-going flood incident in Pakistan that has so far claimed about 1,600 lives and rendered another four million people homeless is a sad reminder of the ugly and devastating consequences of global warming on the environment. There is no gainsaying the fact that humankind is paying dearly for the massive alterations in the environment that have induced changes in climate. This is because of frequent incidence of changes in climate related disasters in the world today. There is hardly any month that passes without an incident occurring in one part of the globe or another since the advent of the 21st century. Changes in climate has significant and potentially devastating health consequences, whether through direct actions (e.g., deaths resulting from heat wave and weather disasters) or disruption of complex biological methods (e.g., changes in infectious diseases patterns, supplies in fresh water and production of food).The report of the fourth assessment of the United Nations Intergovernmental Panel on Climate Change (IPCC) have globally submitted that “it is estimated that the health of millions of people is affected, for instance, malnutrition increases; deaths increase, diseases and injury; burden of increase diarrheal diseases; frequency of increased cardio-respiratory diseases caused by high levels of ground-level ozone in cities due to climate change; besides altered spatial distribution of some communicable diseases”. The association amongst changes in climate, its drivers, systemic effects, health and socioeconomic growth, mitigation and adaptation has been specified.

scholarly journals Snowfall and snowpack in the Western U.S. as captured by convection permitting climate simulations: current climate and pseudo global warming future climate

2021 ◽  
Author(s):  
Kyoko Ikeda ◽  
Roy Rasmussen ◽  
Changhai Liu ◽  
Andrew Newman ◽  
Fei Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Pacific Northwest ◽  
Climate Model ◽  
Future Climate ◽  
Climate Simulation ◽  
Climate Change Signal ◽  
Mountain Ranges ◽  
The Pacific ◽  
Climate Simulations

AbstractThis study examines current and future western U.S. snowfall and snowpack through current and future climate simulations with a 4-km horizontal grid spacing cloud permitting regional climate model over the entire CONtinental U.S. for a 13-year period between 2001 and 2013. At this horizontal resolution, the spatiotemporal distribution of the orographic snowfall and snowpack is well captured partly due to the ability of the model to realistically simulate mesoscale and microphysical features such as orographically induced updrafts driving clouds and precipitation. The historical simulation well captures the observed snowfall and snowpack amounts and pattern in the western U.S. The future climate simulation uses the Pseudo-Global Warming approach, taking the climate change signal from CMIP5 multi-model ensemble-mean difference between 2070–2099 and 1976–2005. The results show that the thermodynamic impacts of climate change in the western U.S. can be characterized considering mountain ranges in two distinct geographic regions: the mountain ranges close to the Pacific Ocean (coastal ranges) and those in the inter-mountain west. Climate change out to 2100 significantly impacts all aspects of the water cycle, with pronounced climate change response in the coastal ranges. A notable result is that the snowpack in the Pacific Northwest is predicted to decrease by ~ 70% by 2100. Trends of this magnitude have already been observed in the historical data and in previous studies. The current Pseudo Global Warming future climate simulation and previous global climate simulations all suggest that these trends will continue to the point that most snowpack will be gone by 2100 in the Pacific Northwest for the most aggressive RCP8.5 climate scenario, even if annual precipitation increases by 10%. Future work will focus on extending the current convective permitting results to a full climate change simulation allowing for dynamical changes in the flow.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

Projected sea-level changes in the marginal seas near China based on dynamical downscaling

2021 ◽  
pp. 1-52
Author(s):  
Yi Jin ◽  
Xuebin Zhang ◽  
John A. Church ◽  
Xianwen Bao
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate Models ◽  
Open Boundary ◽  
Open Boundary Conditions ◽  
Sea Level Changes ◽  
Marginal Seas ◽  
The Pacific

AbstractProjections of future sea-level changes are usually based on global climate models (GCMs). However, the changes in shallow coastal regions, like the marginal seas near China, cannot be fully resolved in GCMs. To improve regional sea-level simulations, a high-resolution (~8 km) regional ocean model is set up for the marginal seas near China for both the historical (1994-2015) and future (2079-2100) periods under representative concentration pathways (RCPs) 4.5 and 8.5. The historical ocean simulations are evaluated at different spatiotemporal scales, and the model is then integrated for the future period, driven by projected monthly climatological climate change signals from 8 GCMs individually via both surface and open boundary conditions. The downscaled ocean changes derived by comparing historical and future experiments reveal greater spatial details than those from GCMs, e.g., a low dynamic sea level (DSL) centre of -0.15 m in the middle of the South China Sea (SCS). As a novel test, the downscaled results driven by the ensemble mean forcings are almost identical with the ensemble average results from individually downscaled cases. Forcing of the DSL change and increased cyclonic circulation in the SCS are dominated by the climate change signals from the Pacific, while the DSL change in the East China marginal seas is caused by both local atmosphere forcing and signals from the Pacific. The method of downscaling developed in this study is a useful modelling protocol for adaptation and mitigation planning for future oceanic climate changes.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

scholarly journals Quantification of impact of climate uncertainty on regional air quality

2008 ◽  
Vol 8 (2) ◽  
pp. 7781-7804 ◽  
Author(s):  
K.-J. Liao ◽  
E. Tagaris ◽  
K. Manomaiphiboon ◽  
C. Wang ◽  
J.-H. Woo ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Urban Areas ◽  
Climate Models ◽  
Global Climate Models ◽  
Base Case ◽  
Daily Maximum ◽  
Climate Scenarios ◽  
Extreme Climate ◽  
Regional Air Quality

Abstract. Impacts of uncertain climate forecasts on future regional air quality are investigated using downscaled MM5 meteorological fields from the NASA GISS and MIT IGSM global climate models and the CMAQ model in 2050 in the continental US. Three future climate scenarios: high-extreme, low-extreme and base, are developed for regional air quality simulations. GISS, with the IPCC A1B scenario, is used for the base case. IGSM results, in the form of probabilistic distributions, are used to perturb the base case climate to provide 0.5th and 99.5th percentile climate scenarios. Impacts of the extreme climate scenarios on concentrations of summertime fourth-highest daily maximum 8-h average ozone are predicted to be up to 10 ppbv (about one-eighth of the current NAAQS of ozone) in some urban areas, though average differences in ozone concentrations are about 1–2 ppbv on a regional basis. Differences between the extreme and base scenarios in annualized PM2.5 levels are very location dependent and predicted to range between −1.0 and +1.5 μg m−3. Future annualized PM2.5 is less sensitive to the extreme climate scenarios than summertime peak ozone since precipitation scavenging is only slightly affected by the extreme climate scenarios examined. Relative abundances of biogenic VOC and anthropogenic NOx lead to the areas that are most responsive to climate change. Such areas may find that climate change can significantly offset air quality improvements from emissions reductions, particularly during the most severe episodes.

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

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