Evolution of the Internal Climate Modes under Future Warming

Abstract

Climate modes play an important role in weather and climate variability over multiple spatial and temporal scales. This research assesses Earth system model (ESM) projections of the spatiotemporal characteristics of key internal climate modes (NAM, SAM, PNA, ENSO, PDO, and AMO) under high (SSP585) and low (SSP126) radiative forcing scenarios and contextualizes those projections using historical fidelity. Time series analyses are used to assess trends and mode phase characteristics are summarized for the historical period and for the end of the twenty-first century. Spatial patterns are compared to infer morphological changes. Shifts in the power spectra are used to examine changes in variability at subannual, interannual, and interdecadal scales. Changes in time-lagged correlations are used to capture the evolution of first-order interactions. While differences in historical skill are predominantly ESM dependent, changing mode characteristics in a warmer climate also exhibit variability between individual ensemble realizations. NAM, SAM, and ENSO tend to evolve toward increased prevalence of the positive phase up to 2100 across the multimodel ensemble while the PNA and PDO exhibit little trend but increasing phase intensity. AMO characteristics are shown to depend on the method used to remove the external signal. ESMs that show higher historical fidelity tend to show more modest changes in those modes under global nonstationarity. Changes in mode interactions are found to be highly ESM dependent but exhibit broadly similar behavior to historical relationships. These findings have implications for our understanding of internal variability and make clear that the choice of ESM, and even the ESM realization, matters for applications of climate projections. Significance Statement Internal modes of variability are important to understand due to their impact on local, regional, and global weather and climate patterns. Future climate changes will not only be affected by the variability arising from these modes, but the modes will themselves change in response to the changing climate. Spatial and temporal aspects of the modes are assessed from projections of future climate and related to how well they are captured in the historical climate. This yields some measure of confidence in the changes exhibited by the models. In most cases, when historically skillful models exhibit changes that are different from those produced by less skillful models, they tend to produce more modest changes. These results, as well as the variability between model outcomes, mean decisions on which ESM to use for projections of the future climate matter significantly.

Stratospheric Aerosol Injection Can Reduce Risks to Antarctic Ice Loss Depending on Injection Location and Amount

“…The single‐latitude injection cases also reveal that the Equator and NH single‐latitude injections drive year‐round SLP reductions above Antarctica and westerly surface wind stress anomalies around the coastline consistent with a positive phase of SAM (Figure 3 and Figure S2 in Supporting Information ). These anomalies are similar in pattern and larger in magnitude as compared to the SSP2‐4.5 anomalies which also reflect a positive SAM and are consistent with previous studies projecting a positive trending SAM through the 21st century under greenhouse gas forcing (Coburn & Pryor, 2022; Zheng et al., 2013). Conversely, SH single‐latitude injections drive anomaly fields consistent with a negative SAM (pressure increases and easterly wind anomalies above and around Antarctica).…”

“…Figure 17 also shows in top left panel (a) the SLP difference between 40° and 65°S which represents the strength of the SAM (Gong & Wang, 1999; Marshall, 2003) relative to the GMT change for each of the simulation ensembles. Along the Historical‐to‐SSP2‐4.5 pathway the SLP difference increases with increasing GMT—this highlights the projected 21st century positive SAM trend (Coburn & Pryor, 2022; Zheng et al., 2013). This panel also illustrates that Polar+1.0 will result in a more robust positive SAM pattern than is projected along the Historical‐to‐SSP2‐4.5 pathway; and shows that for all the Global+ cases the SLP difference represents a negative SAM pattern relative to the Historical‐to‐SSP2‐4.5 pathway.…”

“…This mechanism may be responsible for the increased ice mass loss from this region observed this century (Greenbaum et al., 2015; Rignot et al., 2019; B. Smith et al., 2020). Furthermore, the SAM is projected to become more positive through the 21st century due to continued greenhouse gas emissions (Coburn & Pryor, 2022; Zheng et al., 2013), although an opposing effect from the long‐term stratospheric ozone recovery can significantly offset the positive SAM trend from greenhouse gas emissions, in particularly during the early part of the 21st century and during certain seasons (austral spring and summer, Perlwitz, 2011; D. W. J. Thompson et al., 2011). A positive SAM trend would lead to the Westerlies expanding southward, a weakening of the coastal easterlies, and subsequent Antarctic shelf warming, including warming around East Antarctica (Beadling et al., 2022; Goddard et al., 2017; Spence et al., 2014).…”

“…Smith et al, 2020). Furthermore, the SAM is projected to become more positive through the 21st century due to continued greenhouse gas emissions (Coburn & Pryor, 2022;Zheng et al, 2013), although an opposing effect from the long-term stratospheric ozone Figure 1. Ocean depth and Antarctic topography map with relevant geographic features labeled.…”

Comparative Analysis for Atmospheric Oscillations

“…Atmospheric oscillations may lead to zonal atmospheric variations and climatic conditions [36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51]. For example Arctic Oscillation led to precipitation increment [52].…”