Ubiquity of human-induced changes in climate variability

Abstract

While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming will in particular alter variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, and for seasonal predictions.

Contributions to Polar Amplification in CMIP5 and CMIP6 Models

“…Figure 2 also shows the CMIP6 mean near-surface temperature trend with ± 2 standard deviations of trends calculated across the first 90 ensemble members of the Community Earth System Model version 2 Large Ensemble (CESM2-LE) as a reference for the range of internal variability within a single climate model in CMIP6. The CESM2-LE uses identical time-varying external forcing for its ensemble members, but begins each with a combination of different oceanic and atmospheric initial conditions (Rodgers et al, 2021). With the exception of the Southern Hemisphere mid-latitudes, zonal-mean warming trends in HadCRUT5 fall within the range of CMIP6 intermodel spread and the range of internal variability for CESM2-LE, suggesting that CMIP6 models may be largely consistent with observations when internal variability is taken into account.…”

Improvements in Wintertime Surface Temperature Variability in the Community Earth System Model Version 2 (CESM2) Related to the Representation of Snow Density

“…In LENS2, a mixture of micro and macro initializations are used, where "macro" refers to the initialization of members from different dates from the coupled pre-industrial control simulation. As detailed in Rogers et al (2021), some bug fixes and a change to the biomass burning emissions were introduced between the first and second 50 members of LENS2. However, since our focus here is primarily on sub-seasonal variability, we do not expect these changes to have a substantial impact and we consider both sets together.…”

“…To explore the change in present day temperature variability and future projections between CESM1 and CESM2 with fully coupled simulations we use the CESM1 large ensemble (LENS1, Kay et al (2014)) and the CESM2 large ensemble (LENS2, Rogers et al (2021)). LENS1 is a 40-member ensemble of coupled simulations using CESM1, initialized from 1920 and run under CMIP5 historical forcings to 2005 and forcings of the Representative Concentration Pathway 8.5 (RCP8.5), thereafter.…”

Widespread reductions in human labor capacity after 1.5°C warming

“…Overview of Modeling Framework. We use projections of historical and future climate from 37 with the LE documented in Rodgers et al (2021) 38 . Both models reproduce historical patterns and variation of surface conditions [37][38][39][40] , essential benchmarks for their utility in projecting future warming and humid heat.…”

“…We use projections of historical and future climate from 37 with the LE documented in Rodgers et al (2021) 38 . Both models reproduce historical patterns and variation of surface conditions [37][38][39][40] , essential benchmarks for their utility in projecting future warming and humid heat. We validate historical WBGT and summertime labor capacity projections of these models against reanalysis estimates and demonstrate agreement in their mean state, anthropogenic trend, and variance, both globally and on aggregate within the regions considered in this study (Supplementary Fig.…”