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 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 Revisiting Whether Recent Surface Temperature Trends Agree with the CMIP5 Ensemble

2016 ◽  
Vol 29 (24) ◽  
pp. 8673-8687 ◽  
Author(s):  
Marena Lin ◽  
Peter Huybers
Keyword(s):  
Surface Temperature ◽  
Linear Trend ◽  
Coupled Model ◽  
Global Trends ◽  
Global Mean Temperature ◽  
Temperature Trends ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Slope Estimator ◽  
Global Mean

Abstract In an earlier study, a weaker trend in global mean temperature over the past 15 years relative to the preceding decades was characterized as significantly lower than those contained within the phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensemble. In this study, divergence between model simulations and observations is estimated using a fixed-intercept linear trend with a slope estimator that has one-third the noise variance compared to simple linear regression. Following the approach of the earlier study, where intermodel spread is used to assess the distribution of trends, but using the fixed-intercept trend metric demonstrates that recently observed trends in global mean temperature are consistent () with the CMIP5 ensemble for all 15-yr intervals of observation–model divergence since 1970. Significant clustering of global trends according to modeling center indicates that the spread in CMIP5 trends is better characterized using ensemble members drawn across models as opposed to using ensemble members from a single model. Despite model–observation consistency at the global level, substantial regional discrepancies in surface temperature trends remain.

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 Variability of surface climate in simulations of past and future

2020 ◽  
Author(s):  
Kira Rehfeld ◽  
Raphaël Hébert ◽  
Juan M. Lora ◽  
Marcus Lofverstrom ◽  
Chris M. Brierley
Keyword(s):  
Climate Variability ◽  
Temperature Change ◽  
Rainfall Variability ◽  
Coupled Model ◽  
Temperature Variability ◽  
Global Mean Temperature ◽  
Extreme Precipitation Events ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Global Mean

Abstract. It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios. Yet comparatively little is known about future changes in climate variability. We explore changes in climate variability over the large range of climates simulated by the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3). This consists of time slices of the Last Glacial Maximum, the Mid Holocene and idealized warming experiments (1 % CO2) and abrupt4×CO2), and encompasses climates with a range of 12 K of global mean temperature change. We examine climate variability from different perspectives: the local interannual change, coherent climate modes and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. Meanwhile only over tropical land is the change in the interannual temperature variability positively correlated to temperature change, and then weakly. In general, temperature variability is inversely related to mean temperature change – with analysis of power spectra demonstrating that this holds from intra-seasonal to multi-decadal timescales. We systematically investigate changes in the standard deviation of modes of climate variability, such as the North Atlantic Oscillation, with global mean temperature change. While several modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalisable pattern emerges. By compositing extreme precipitation events across the ensemble, we demonstrate that the atmospheric drivers dominating rainfall variability in Mediterranean climates persist throughout palaeoclimate and future simulations. The robust nature of the response of climate variability, between both cold and warm climates and across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.

scholarly journals Variability of surface climate in simulations of past and future

2020 ◽  
Author(s):  
Kira Rehfeld ◽  
Raphaël Hébert ◽  
Juan M. Lora ◽  
Marcus Lofverstrom ◽  
Chris M. Brierley
Keyword(s):  
Climate Variability ◽  
Temperature Change ◽  
Temperature Variability ◽  
Last Interglacial ◽  
Global Mean Temperature ◽  
Extreme Precipitation Events ◽  
Mean Temperature ◽  
Project Phases ◽  
Intercomparison Project ◽  
Global Mean

<p>It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios. Yet comparatively little is known about future changes in climate variability. We explore changes in climate variability over the large range of climates simulated in the framework the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phases 3 and 4 (PMIP3/4). <br>This consists of time slice simulations for the Pliocene, Last Interglacial, Last Glacial Maximum, the Mid Holocene and idealized warming experiments (1% CO<sub>2</sub> and abrupt 4xCO<sub>2</sub>), and encompasses climates with a range of 12°C of global mean temperature change. We examine climate variability from different perspectives: from local interannual change, to coherent climate modes and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. Meanwhile only over tropical land is the change in the interannual temperature variability positively correlated to temperature change, and then weakly. In general, temperature variability is inversely related to mean temperature change - with analysis of power spectra demonstrating that this holds from intra-seasonal to multi-decadal timescales. We systematically investigate changes in the standard deviation of modes of climate variability. Overall, no generalisable pattern emerges. Several modes do show, sometimes weak, increasing variability with global mean temperature change (most notably the Atlantic Zonal Mode), but also the El Niño/Southern Oscillation indices (NINO3.4 and NINO4). The annular modes in the Northern (Southern) hemisphere show only weakly increasing (decreasing) relationships. <br>By compositing extreme precipitation events across the ensemble, we demonstrate that the atmospheric drivers dominating rainfall variability in Mediterranean climates persist throughout palaeoclimate and future simulations. The robust nature of the response of climate variability in model simulations, between both cold and warm climates and across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.</p>

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 Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

2020 ◽  
Vol 13 (11) ◽  
pp. 5175-5190
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Phase 1 ◽  
Temperature Response ◽  
Earth System ◽  
Model Intercomparison ◽  
Radiative Forcings ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
Global Mean

Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

scholarly journals Variability of surface climate in simulations of past and future

2020 ◽  
Vol 11 (2) ◽  
pp. 447-468 ◽  
Author(s):  
Kira Rehfeld ◽  
Raphaël Hébert ◽  
Juan M. Lora ◽  
Marcus Lofverstrom ◽  
Chris M. Brierley
Keyword(s):  
Climate Variability ◽  
Temperature Change ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Temperature Variability ◽  
Climate Modes ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Global Mean

Abstract. It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios, yet comparatively little is known about future changes in climate variability. This study explores changes in climate variability over the large range of climates simulated by the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3), including time slices of the Last Glacial Maximum, the mid-Holocene, and idealized experiments (1 % CO2 and abrupt4×CO2). These states encompass climates within a range of 12 ∘C in global mean temperature change. We examine climate variability from the perspectives of local interannual change, coherent climate modes, and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. At the global scale, temperature variability is inversely related to mean temperature change on intra-seasonal to multidecadal timescales. This decrease is stronger over the oceans, while there is increased temperature variability over subtropical land areas (40∘ S–40∘ N) in warmer simulations. We systematically investigate changes in the standard deviation of modes of climate variability, including the North Atlantic Oscillation, the El Niño–Southern Oscillation, and the Southern Annular Mode, with global mean temperature change. While several climate modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalizable pattern emerges. By compositing extreme precipitation years across the ensemble, we demonstrate that the same large-scale modes influencing rainfall variability in Mediterranean climates persist throughout paleoclimate and future simulations. The robust nature of the response of climate variability, between cold and warm climates as well as across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.

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