Abstract
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. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 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 in the model alters 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, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.
Highlights
Faced with the prospect of substantial future climate change, mitigation and adaptation strategies are increasingly paramount
The range across the ensemble members, which results from internal variability and its forced changes, spans the observed climate state much of the time, with a notable exception being Southern Ocean sea ice (Fig. 1e)
We find a substantial increase in land primary productivity (Fig. 1g), which contributes to the uptake of carbon in the terrestrial biosphere
Summary
Faced with the prospect of substantial future climate change, mitigation and adaptation strategies are increasingly paramount. While mitigation efforts are concerned with limiting mean state changes, successful adaptation will require understanding the potentially altered variability of the climate system (Sarachik, 2010). The way in which climate variability will change due to anthropogenic radiative forcing has not been extensively explored. Spectral peaks can emerge from a range of mechanisms, including astronomical forcings or internal climate instabilities such as for the El Niño–Southern Oscillation (ENSO). These distinct features can be further influenced by climate processes acting on different timescales. Examples of non-linear “timescale interactions” are multiplicative (state-dependent) noise (Müller, 1987; Majda et al, 2009; Sardeshmukh and Sura, 2009; Sardeshmukh and Penland, 2015; Jin et al, 2007, 2020; Levine and Jin, 2010) and combination mode dynam-
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