Linkage of future regional climate extremes to global warming intensity

2020 ◽  
Vol 81 ◽  
pp. 43-54
Author(s):  
X Wang ◽  
X Lang ◽  
D Jiang
Keyword(s):  
Global Warming ◽  
Temperature Increase ◽  
Regional Climate ◽  
Climate Extremes ◽  
Temperature Extremes ◽  
High Latitudes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Low Latitudes ◽  
Global Mean

Changes in extreme climate have caused widespread concern, and it is important to understand how climate extremes will link to global warming intensity at the regional scale. Based on the daily minimum and maximum temperature and precipitation outputs from 25 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models under the Representative Concentration Pathways 8.5 (RCP8.5) scenario, we project the linkage of future regional climate extremes to the global mean temperature increase above preindustrial levels. Results show that regionally averaged changes in absolute temperature extremes (the coldest night and the warmest day) scale linearly with global warming intensity. In contrast, changes in cold nights and cold days in all regions, warm nights in low latitudes, and warm days in Southeast Asia exhibit nonlinear relationships with the global mean temperature increase, which manifests rapid changes in early warming stages and weak changes in late warming stages. The percentile-based temperature extremes vary at large magnitudes as global warming intensifies in low latitudes, while large values are seen in middle and high latitudes for the coldest night and warmest day, respectively; large intermodel spread occurs in the strong scaling areas, except for cold days and cold nights. Regional mean changes in extreme precipitation show consistent linear trends with global warming, and different indices vary in magnitude with region. Extreme heavy precipitation events increase linearly with global warming in high latitudes with larger magnitudes. The intermodel spread is generally large in low latitudes and will increase with warming. The work presented here can provide effective support to decision makers for developing adaptation and mitigation measures.

scholarly journals Pacific variability reconciles observed and modelled global mean temperature increase since 1950

2020 ◽  
Author(s):  
Martin B. Stolpe ◽  
Kevin Cowtan ◽  
Iselin Medhaug ◽  
Reto Knutti
Keyword(s):  
Global Warming ◽  
Temperature Change ◽  
Temperature Increase ◽  
Global Temperature ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Pacific ◽  
Global Warming Hiatus ◽  
Warming Hiatus ◽  
Global Mean

Abstract Global mean temperature change simulated by climate models deviates from the observed temperature increase during decadal-scale periods in the past. In particular, warming during the ‘global warming hiatus’ in the early twenty-first century appears overestimated in CMIP5 and CMIP6 multi-model means. We examine the role of equatorial Pacific variability in these divergences since 1950 by comparing 18 studies that quantify the Pacific contribution to the ‘hiatus’ and earlier periods and by investigating the reasons for differing results. During the ‘global warming hiatus’ from 1992 to 2012, the estimated contributions differ by a factor of five, with multiple linear regression approaches generally indicating a smaller contribution of Pacific variability to global temperature than climate model experiments where the simulated tropical Pacific sea surface temperature (SST) or wind stress anomalies are nudged towards observations. These so-called pacemaker experiments suggest that the ‘hiatus’ is fully explained and possibly over-explained by Pacific variability. Most of the spread across the studies can be attributed to two factors: neglecting the forced signal in tropical Pacific SST, which is often the case in multiple regression studies but not in pacemaker experiments, underestimates the Pacific contribution to global temperature change by a factor of two during the ‘hiatus’; the sensitivity with which the global temperature responds to Pacific variability varies by a factor of two between models on a decadal time scale, questioning the robustness of single model pacemaker experiments. Once we have accounted for these factors, the CMIP5 mean warming adjusted for Pacific variability reproduces the observed annual global mean temperature closely, with a correlation coefficient of 0.985 from 1950 to 2018. The CMIP6 ensemble performs less favourably but improves if the models with the highest transient climate response are omitted from the ensemble mean.

scholarly journals Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

2017 ◽  
Author(s):  
Richard Wartenburger ◽  
Martin Hirschi ◽  
Markus G. Donat ◽  
Peter Greve ◽  
Andy J. Pitman ◽  
...  
Keyword(s):  
Water Cycle ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Projected Changes ◽  
Regional Analyses ◽  
Global Mean

Abstract. This article extends a previous study (Seneviratne et al., 2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global temperature targets, such as the 2 degree and 1.5 degree limits agreed within the 2015 Paris Agreement.

scholarly journals Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

2017 ◽  
Vol 10 (9) ◽  
pp. 3609-3634 ◽  
Author(s):  
Richard Wartenburger ◽  
Martin Hirschi ◽  
Markus G. Donat ◽  
Peter Greve ◽  
Andy J. Pitman ◽  
...  
Keyword(s):  
Water Cycle ◽  
Regional Climate ◽  
Coupled Model ◽  
Climate Extremes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Projected Changes ◽  
Regional Analyses ◽  
Global Mean

Abstract. This article extends a previous study Seneviratne et al. (2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global mean temperature targets, such as the 2 and 1.5° limits agreed within the 2015 Paris Agreement.

scholarly journals Trends in Thailand’s Extreme Temperature Indices during 1955-2018 and Their Relationship with Global Mean Temperature Change

2020 ◽  
pp. 94-107
Author(s):  
Atsamon Limsakul
Keyword(s):  
Global Warming ◽  
Extreme Temperature ◽  
Local Scale ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Global Mean Temperature ◽  
Temperature Distributions ◽  
Mean Temperature ◽  
Temperature Indices ◽  
Global Mean

Trends in Thailand’s extreme temperature indices and their relationship with global mean temperature (GMT) change are analyzed, based on longer quality controlled temperature data during 1955–2018. Widespread significant trends of extreme temperature indices with a clear warming evident in all indices are observed, consistent with the earlier results and general global warming. Changes associated with the upper tails of the minimum and maximum temperature distributions are the dominant feature of Thailand’s extreme temperature indices accounting for more than 65% of the total variance. Analysis of the probability distribution functions (PDFs) of combined extreme temperature indices further shows significant shifts in their distributions toward warmer conditions in the recent decades. The results suggest that daytime and nighttime temperatures in Thailand have become more extreme and that the changes are related to shifts in multiple aspects of the daily temperature distributions. With long-term temperature records, this study provides more confident and robust evidence of trends in Thailand’s temperature extremes occurred since the second half of 20th century. Another noteworthy finding is that most of Thailand’s extreme temperature indices show a distinct linear relationship with GMT, indicating that local-scale changes in temperatures and its extreme at local scale are related almost linearly to GMT change. The extrapolated values of the indices with strong linearity with GMT show substantial distinction with nearly 50% increase between 2 global warming levels set by Paris Agreement, highlighting that half a degree increase in GMT will lead to greatly increase in Thailand’s temperature extremes.

scholarly journals An Assessment of Global Macroeconomic Impacts Caused by Sea Level Rise Using the Framework of Shared Socioeconomic Pathways and Representative Concentration Pathways

2020 ◽  
Vol 12 (9) ◽  
pp. 3737
Author(s):  
Osamu Nishiura ◽  
Makoto Tamura ◽  
Shinichiro Fujimori ◽  
Kiyoshi Takahashi ◽  
Junya Takakura ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
Low Income ◽  
Temperature Increase ◽  
General Circulation ◽  
Economic Losses ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Coastal areas provide important services and functions for social and economic activities. Damage due to sea level rise (SLR) is one of the serious problems anticipated and caused by climate change. In this study, we assess the global economic impact of inundation due to SLR by using a computable general equilibrium (CGE) model that incorporates detailed coastal damage information. The scenario analysis considers multiple general circulation models, socioeconomic assumptions, and stringency of climate change mitigation measures. We found that the global household consumption loss proportion will be 0.045%, with a range of 0.027−0.066%, in 2100. Socioeconomic assumptions cause a difference in the loss proportion of up to 0.035% without greenhouse gas (GHG) emissions mitigation, the so-called baseline scenarios. The range of the loss proportion among GHG emission scenarios is smaller than the differences among the socioeconomic assumptions. We also observed large regional variations and, in particular, the consumption losses in low-income countries are, relatively speaking, larger than those in high-income countries. These results indicate that, even if we succeed in stabilizing the global mean temperature increase below 2 °C, economic losses caused by SLR will inevitably happen to some extent, which may imply that keeping the global mean temperature increase below 1.5 °C would be worthwhile to consider.

scholarly journals Scenarios towards limiting global mean temperature increase below 1.5 °C

2018 ◽  
Vol 8 (4) ◽  
pp. 325-332 ◽  
Author(s):  
Joeri Rogelj ◽  
Alexander Popp ◽  
Katherine V. Calvin ◽  
Gunnar Luderer ◽  
Johannes Emmerling ◽  
...  
Keyword(s):  
Temperature Increase ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

A new approach for assessing climate change impacts in ecotron experiments

2019 ◽  
Author(s):  
Inne Vanderkelen ◽  
Jakob Zschleischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
New Approach ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.

scholarly journals Climate Warming in Response to Emission Reductions Consistent with the Paris Agreement

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Fang Wang ◽  
Katarzyna B. Tokarska ◽  
Jintao Zhang ◽  
Quansheng Ge ◽  
Zhixin Hao ◽  
...  
Keyword(s):  
Climate Warming ◽  
Temperature Increase ◽  
Climate Model ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
The Arctic ◽  
Emission Reductions ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

To limit global warming to well below 2°C in accord with the Paris Agreement, countries throughout the world have submitted their Intended Nationally Determined Contributions (INDCs) outlining their greenhouse gas (GHG) mitigation actions in the next few decades. However, it remains unclear what the resulting climate change is in response to the proposed INDCs and subsequent emission reductions. In this study, the global and regional warming under the updated INDC scenarios was estimated from a range of comprehensive Earth system models (CMIP5) and a simpler carbon-climate model (MAGICC), based on the relationship of climate response to cumulative emissions. The global GHG emissions under the updated INDC pledges are estimated to reach 14.2∼15.0 GtC/year in 2030, resulting in a global mean temperature increase of 1.29∼1.55°C (median of 1.41°C) above the preindustrial level. By extending the INDC scenarios to 2100, global GHG emissions are estimated to be around 6.4∼9.0 GtC/year in 2100, resulting in a global mean temperature increase by 2.67∼3.74°C (median of 3.17°C). The Arctic warming is projected to be most profound, exceeding the global average by a factor of three by the end of this century. Thus, climate warming under INDC scenarios is projected to greatly exceed the long-term Paris Agreement goal of stabilizing the global mean temperature at to a low level of 1.5‐2.0°C above the pre-industrial. Our study suggests that the INDC emission commitments need to be adjusted and strengthened to bridge this warming gap.

Sign in / Sign up

Export Citation Format

Share Document