Heat stress indicators in CMIP6: Estimating future trends and exceedances of critical physiological thresholds

2020 ◽  
Author(s):  
Clemens Schwingshackl ◽  
Jana Sillmann ◽  
Marit Sandstad ◽  
Kristin Aunan
Keyword(s):  
Heat Stress ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Trends ◽  
Stress Indicators ◽  
Threshold Levels ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

<p>Global warming is leading to increased heat stress in many regions around the world. An extensive number of heat stress indicators has been developed to measure the associated impacts on human health. Here we calculate eight heat stress indicators for global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) and compare their future trends and exceedances of critical physiological thresholds with particular focus on highly populated regions. The heat stress indicators are selected to represent a range of different applications, such as extreme heat events, heat-related losses in worker productivity, heat warnings, and heat-related morbidity and mortality. Projections of the analyzed heat stress indicators reveal that they increase significantly in all considered regions as function of global mean temperature. Moreover, heat stress indicators reveal a substantial spread ranging from trends close to the rate of global mean temperature up to an amplification of more than a factor of two. Consistently, exceedances of critical physiological thresholds are strongly increasing globally, including in several densely populated regions, but also show substantial spread across the selected heat stress indicators. Additionally, the indicators with the highest exceedance vary for different threshold levels, suggesting that the large indicator spread is associated both to differences in trend magnitude and threshold levels. The usage of heat stress indicators that are suitable for each specific application is thus crucial for reliably assessing impacts of future heat stress, while inappropriate indicators might lead to substantial biases.</p>

Evidence of Decadal Climate Prediction Skill Resulting from Changes in Anthropogenic Forcing

2006 ◽  
Vol 19 (20) ◽  
pp. 5305-5318 ◽  
Author(s):  
Terry C. K. Lee ◽  
Francis W. Zwiers ◽  
Xuebin Zhang ◽  
Min Tsao
Keyword(s):  
Twentieth Century ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Spatial Scales ◽  
Global Climate Models ◽  
Anthropogenic Forcing ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract It is argued that simulations of the twentieth century performed with coupled global climate models with specified historical changes in external radiative forcing can be interpreted as climate hindcasts. A simple Bayesian method for postprocessing such simulations is described, which produces probabilistic hindcasts of interdecadal temperature changes on large spatial scales. Hindcasts produced for the last two decades of the twentieth century are shown to be skillful. The suggestion that skillful decadal forecasts can be produced on large regional scales by exploiting the response to anthropogenic forcing provides additional evidence that anthropogenic change in the composition of the atmosphere has influenced the climate. In the absence of large negative volcanic forcing on the climate system (which cannot presently be forecast), it is predicted that the global mean temperature for the decade 2000–09 will lie above the 1970–99 normal with a probability of 0.94. The global mean temperature anomaly for this decade relative to 1970–99 is predicted to be 0.35°C with a 5%–95% confidence range of 0.21°–0.48°C.

scholarly journals Mean precipitation change from a deepening troposphere

2018 ◽  
Vol 115 (45) ◽  
pp. 11465-11470 ◽  
Author(s):  
Nadir Jeevanjee ◽  
David M. Romps
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Precipitation Change ◽  
Global Climate Models ◽  
Simple Theory ◽  
Radiative Cooling ◽  
Free Troposphere ◽  
Global Mean

Global climate models robustly predict that global mean precipitation should increase at roughly 2–3%K−1, but the origin of these values is not well understood. Here we develop a simple theory to help explain these values. This theory combines the well-known radiative constraint on precipitation, which says that condensation heating from precipitation is balanced by the net radiative cooling of the free troposphere, with an invariance of radiative cooling profiles when expressed in temperature coordinates. These two constraints yield a picture in which mean precipitation is controlled primarily by the depth of the troposphere, when measured in temperature coordinates. We develop this theory in idealized simulations of radiative–convective equilibrium and also demonstrate its applicability to global climate models.

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 Uncertainty in the relationship between climate forcing and hydrological response in UK catchments

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals Intensification characteristics of hydroclimatic extremes in the Asia monsoon region under 1.5 and 2.0 °C of global warming

2020 ◽  
Author(s):  
Jeong-Bae Kim ◽  
Deg-Hyo Bae
Keyword(s):  
Global Warming ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Monsoon Region ◽  
Infiltration Capacity ◽  
Meteorological Forcing ◽  
Climate Zones ◽  
Global Mean Temperature

Abstract. The changes in hydroclimatic extremes are assessed over the Asia monsoon region under 1.5 and 2.0 °C warming targets of global mean temperature above preindustrial levels based on a representative concentration pathway (RCP) 4.5 scenario. The subregions in this domain are defined by the Köppen climate classification method to identify regional climate characteristics. The change patterns of long-term hydroclimatic mean and hydroclimatic extreme among subregions are compared based on the multimodel ensemble (MME) of selected five global climate models (GCMs). Each GCM is bias corrected and then used as a meteorological forcing for a hydrological model. To simulate how the hydrologic system responds to 1.5 and 2.0 °C global warming targets, we select the variable infiltration capacity (VIC) model. The results of temperature extremes show significant change patterns over all climate zones. As the globe warms, the increasing warm extremes and the decreasing cold extremes with a high robustness occur more frequently over Asia. Meanwhile, changes in precipitation and runoff averages (and low runoff extremes) show large spatial variations in change patterns with little robustness based on intermodel agreement. Global warming is expected to significantly intensify maximum precipitation extremes in all climate zones. Regardless of regional climate characteristics, this behavior is expected to be enhanced under 2.0 °C compare to 1.5 °C warming scenario and cause the likelihood of flood risk. The spatial extent and magnitude of change patterns in runoff are modulated by those of change patterns in precipitation. More importantly, an extra 0.5 °C of global warming also leads to amplified change signals and more robust change patterns in hydroclimatic extremes, especially in cold (and polar) climate zones. The results of this study demonstrate that the clear changes in regional hydroclimatic extremes under warmer conditions over Asia, and hydroclimatic sensitivities differ based on regional climate characteristics.

scholarly journals The relationship between climate forcing and hydrological response in UK catchments

2010 ◽  
Vol 7 (5) ◽  
pp. 7633-7667 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, it is likely that the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

2013 ◽  
Vol 4 (1) ◽  
pp. 95-108 ◽  
Author(s):  
B. B. B. Booth ◽  
D. Bernie ◽  
D. McNeall ◽  
E. Hawkins ◽  
J. Caesar ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temperature Change ◽  
Climate Sensitivity ◽  
Global Climate ◽  
Global Climate Model ◽  
Design Decision ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Atmospheric Feedbacks ◽  
Global Mean

Abstract. We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

scholarly journals A Stochastic Analysis of the Impact of Small-Scale Fluctuations on the Tropospheric Temperature Response to CO2 Doubling

2010 ◽  
Vol 23 (9) ◽  
pp. 2307-2319 ◽  
Author(s):  
Rita Seiffert ◽  
Jin-Song von Storch
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Small Scale ◽  
Tropospheric Temperature ◽  
Climate Response ◽  
Restoring Force ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Impact ◽  
Global Mean

Abstract The climate response to increased CO2 concentration is generally studied using climate models that have finite spatial and temporal resolutions. Different parameterizations of the effect of unresolved processes can result in different representations of small-scale fluctuations in the climate model. The representation of small-scale fluctuations can, on the other hand, affect the modeled climate response. In this study the mechanisms by which enhanced small-scale fluctuations alter the climate response to CO2 doubling are investigated. Climate experiments with preindustrial and doubled CO2 concentrations obtained from a comprehensive climate model [ECHAM5/Max Planck Institute Ocean Model (MPI-OM)] are analyzed both with and without enhanced small-scale fluctuations. By applying a stochastic model to the experimental results, two different mechanisms are found. First, the small-scale fluctuations can change the statistical behavior of the global mean temperature as measured by its statistical damping. The statistical damping acts as a restoring force that determines, according to the fluctuation–dissipation theory, the amplitude of the climate response to a change in external forcing (here, CO2 doubling). Second, the small-scale fluctuations can affect processes that occur only in response to the CO2 increase, thereby altering the change of the effective forcing on the global mean temperature.

scholarly journals Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

2012 ◽  
Vol 3 (2) ◽  
pp. 1055-1084 ◽  
Author(s):  
B. B. B. Booth ◽  
D. Bernie ◽  
D. McNeall ◽  
E. Hawkins ◽  
J. Caesar ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temperature Change ◽  
Climate Sensitivity ◽  
Global Climate ◽  
Global Climate Model ◽  
Design Decision ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Atmospheric Feedbacks ◽  
Global Mean

Abstract. We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10–90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon cycle range. These high end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real world climate sensitivity constraints which, if achieved, would lead to reductions on the uppper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present day observables and future changes while the large spread of future projected changes, highlights the ongoing need for such work.

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