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(top) The time series of global-mean, monthly mean surface temperature anomalies based on the HadCRUT3 combined SST and land surface air temperature data (T g ). (second from top) The component of T g that is linearly congruent with T ENSO . (second from bottom) The component of T g that is linearly congruent with T dyn . (bottom) The residual global-mean surface temperature time series found by removing the linear contributions of T ENSO and T dyn from T g . The vertical lines denote the month of August 1945 and volcano eruption dates (from left to right) of Santa María, Mount Agung, El Chichó n, and Mount Pinatubo. The horizontal lines denote the mean for the period 1961–90 (i.e., the base period for the temperature data).
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Global-mean surface temperature is affected by both natural variability and anthropogenic forcing. This study is concerned with identifying and removing from global-mean temperatures the signatures of natural climate variability over the period January 1900-March 2009. A series of simple, physically based methodologies are developed and applied to...
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... 4 and 5 show the effects of removing the T ENSO and T dyn time series from all three global-mean time se- ries. The T dyn time series evidently accounts for a com- ponent of the month-to-month variability in T g and T Land (Figs. 4 and 5b), whereas T ENSO accounts for much of the interannual variability in all three time series (Figs. 4, 5a, and 5b). The T ENSO and T dyn residual time series (bottom time series in all panels) provide a comparatively smooth rendition of the global-mean temperature variability, and they also serve to highlight a number of sudden drops in surface temperatures over the past century. ...
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... 4 and 5 show the effects of removing the T ENSO and T dyn time series from all three global-mean time se- ries. The T dyn time series evidently accounts for a com- ponent of the month-to-month variability in T g and T Land (Figs. 4 and 5b), whereas T ENSO accounts for much of the interannual variability in all three time series (Figs. 4, 5a, and 5b). The T ENSO and T dyn residual time series (bottom time series in all panels) provide a comparatively smooth rendition of the global-mean temperature variability, and they also serve to highlight a number of sudden drops in surface temperatures over the past century. The drop in late 1945, which is largely restricted to the T ...
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... obfuscation of the volcanic cooling by dynam- ically induced variability is exemplified in the response of global-mean temperatures to the June 1991 eruption of Mount Pinatubo. The left and middle panels in Fig. 6 are excerpts from the combined land and ocean global- mean temperature time series (T g ) and residual T g time series from Fig. 4 but focused on the period surrounding the June 1991 eruption of Mount Pinatubo. The right panel in Fig. 6 shows the residual T g time series after the 30-yr trend centered on the June 1991 eruption date has been removed from the data. The cooling following the eruption of Mount Pinatubo is barely discernible in T g (Fig. 6, left) ...
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... and dynamically induced variability in the record. The vol- canic signal is evidently much clearer in the residual global-mean time series (Fig. 6, middle) but is distorted by the pronounced global warming trend of the past few decades. The volcanic signal is most clearly isolated when the low-frequency global-scale warming of the FIG. 5. As in Fig. 4, but for (a) global-mean SSTs from the HadSST2 dataset and (b) the global-mean surface land data from the CRUTEM3 dataset. Note that T dyn is not significantly corre- lated with the global-mean SST time series and hence is not filtered from the SST data. past decades has been removed from the residual time series (Fig. 6, right). The ...
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... provide a re- markably clean rendition of twentieth-century global- mean temperature variability. When the ENSO and dynamically induced variability are removed from the global-mean temperature time series, the analyses highlight the spurious drop in SSTs in 1945 and draw out the signal of major volcanic eruptions in surface tem- peratures (Figs. 4 and 5). When the signal of volcanic eruptions is subsequently removed from the data, the time series are dominated by century-long warming that is punctuated primarily by 1) the step in global-mean temperatures in ;1945 and 2) a brief cooling in the 1970s (Fig. 10). In this section we discuss three aspects of twentieth-century temperature ...
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... The factors affecting ENSO are complex, including volcanic, orbital, and solar forcing, unforced internal climate oscillations, human activities, etc. Volcanic eruptions can impact atmospheric composition and surface temperature (Thompson et al., 2009), and several studies have demonstrated that volcanic eruptions potentially modulate the magnitude of ENSO (e.g., Emile-Geay et al., 2008;McGregor and Timmermann, 2011). Coupled general circulation model simulations and proxy reconstructions indicate that large tropical volcanic eruptions may raise the probability of El Niño phases in the year after an eruption (McGregor et al., 2010). ...
The behavior of the global climate system on scales from years to centuries is related to several mechanisms, including solar forcing and the El Niño-Southern Oscillation (ENSO). However, due to limited stratigraphic resolution and the accuracy of dating methods, pre-Quaternary archives are rare. A middle Eocene lacustrine shale in the Bohai Bay Basin of East China contains annual laminae which provides a site to study the astronomical and varve chronology of the basin. Principal component analysis of the sediments in the cored material, their magnetic susceptibility and grayscale scans as well as analysis of the varve thickness in thin sections, jointly reveal variations between a warm/dry and cold/wet climate on the scale of centuries (∼200−240 years and ∼350 years, respectively), probably corresponding with cycles in solar activity. In situ δ13C and δ18O values of the light carbonate laminae indicate, in combination with varve-thickness data, that algal blooming and carbonate production occurred at ∼2.1−8.7-year cycles, which could be ascribed to ENSO activity. Our finding of the ENSO variability during this notably warm interval indicates that evident interannual variability will likely continue to exist in our future greenhouse planet.
... Volcanic eruptions that inject sulfate aerosols into the stratosphere can also impact climate, not only on annual timescales but also on decadal timescales, depending upon the sequence of eruptions (Solomon et al., 2011;Marshall et al., 2022). The eruption of Mount Pinatubo injected nearly 20 Tg of SO2 into the stratosphere (Bluth et al., 1992), which led to a reduction in global mean surface temperature (GMST) between about 0.1 and 0.4°C (Santer et al., 2001;Thompson et al., 2009;Canty et al., 2013;Fujiwara, Martineau and Wright, 2020). In contrast, the Hunga eruption injected between 0.5 and 0.7 Tg of SO2 into the stratosphere (Carn et al., 2022;Sellitto et al., 2022;Duchamp et al., 2023) and is estimated to have resulted in a cooling of less than about 0.04°C of Earth's surface in the SH in 2022 (Schoeberl et al., 2023). ...
The Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) on SCISAT-1 and Microwave Limb Sounder (MLS) on NASA’s Aura satellite have contributed significantly to understanding the impacts of human activities on the stratospheric ozone layer. The two-decade-long data record from these instruments has allowed quantification of ozone depletion caused by human-released ozone-depleting substances, the effects of extreme natural events like major volcanic eruptions including Hunga in 2022, as well as events amplified by human-caused climate change such as wildfires that inject material into the stratosphere, as happened over Australia in early 2020. Both platforms are nearing the end of their operational lifetimes, and their decommissioning will cause a substantial gap in the measurement of critical atmospheric components, including water vapor, inorganic chlorine species, and tracers of stratospheric transport. This upcoming “data desert” poses significant challenges for monitoring the recovery of the ozone layer and assessing the effects on stratospheric composition of future extreme events, threats posed by increases in space debris from satellite burn-up, and the possible injection of stratospheric aerosol to mitigate global warming. The lack of confirmed future missions that can provide daily near-global profile measurements of stratospheric composition highlights the need for observational strategies to bridge this impending gap. This paper discusses the essential role of ACE-FTS and MLS in advancing our understanding of the stratosphere, the impact of data loss after the cessation of one or both instruments, and the urgency of developing strategies for mitigating the impact of these observational losses at a time marked by dramatic changes in the stratosphere due to human and natural factors.
... To understand permafrost climate zones, we examined climate variations by dividing climate records into distinct intervals. To detect changes in climate time series graphs, stepchange models were used, incorporating quasi-stationary development periods and climatic shifts [26][27][28][29]. The mean annual air temperature showed a clear change in variability around 1987-1988 and again around 2004-2005, indicating important developmental climate shifts. ...
... To better illustrate the use of climatic transitions, such as the transition from a stable climate to modern warming, it is more effective to use periods rather than a single trend. Studies by Litzow [26], Tompson et al. [27,28], and Lobanov [29] analyzing homogeneous periods while accounting for climate shifts have revealed the stages of modern climate warming across the vast northern region of Yakutia. Our research indicates that the Arctic and Subarctic experienced a dramatic transition from a cold climate to a pre-warming period in 1988, followed by a sensitive warming phase starting in 2005 (see Figures 4-15, Tables 1-3 and 5-7). ...
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... We utilized ENSO to depict internal variability, as it exerts a greater impact on global ΔT compared to other modes of variability 3,11,26,65 . The total sum of the DDT of individual factors converged on the observation (Fig. 2m) Tables 4-7). ...
... Statistical model ENSO has larger influences on the global ΔT than other internal variabilities 3,11,26,65 . We used ENSO to reflect the main changes due to internal variability. ...
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... Similarly, it is impossible to isolate a single event from observational data. Advanced methods that could better capture the multiple sources of natural variability such as the El Niño Southern Oscillation, could further draw out the signal from the noise (e.g Thompson et al., 2009). This could be addressed through an alternate basis function representation or additional data processing steps. ...
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Cold extremes have large impacts on human society. Understanding the physical processes dominating the changes in cold extremes is crucial for a reliable projection of future climate change. The observed cold extremes have decreased during the last several decades, and this trend will continue under future global warming. Here, we quantitatively identify the contributions of dynamic (changes in large-scale atmospheric circulation) and thermodynamic (rising temperatures resulting from global warming) effects to East Asian cold extremes in the past several decades and in a future warm climate by using two sets of large-ensemble simulations of climate models. We show that the dynamic component accounts for over 80 % of the cold-month (coldest 5 % boreal winter months) surface air temperature (SAT) anomaly over the past 5 decades. However, in a future warm climate, the thermodynamic change is the main contributor to the decreases in the intensity and occurrence probability of East Asian cold extremes, while the dynamic change is also contributive. The intensity of East Asian cold extremes will decrease by around 5 °C at the end of the 21st century, in which the thermodynamic (dynamic) change contributes approximately 75 % (25 %). The present-day (1986–2005) East Asian cold extremes will almost never occur after around 2035, and this will happen 10 years later due solely to thermodynamic change. The upward trend of a positive Arctic Oscillation-like sea level pressure pattern dominates the changes in the dynamic component. The finding provides a useful reference for policymakers in climate change adaptation activities.
... These results suggest that the primary driver of the wetting trend is atmospheric internal variability, while the role of oceanic conditions, if any, is limited. This conclusion is consistent with previous analyses conducted over North America, where it was found that internal variability in the large-scale atmospheric circulation played a substantial role in explaining variations in precipitation [28][29][30] . Collectively, these findings provide compelling support for attributing the observed wetting trend to internal variability in the atmosphere. ...
The Taklamakan and Gobi Desert (TGD) region has experienced a pronounced increase in summer precipitation, including high-impact extreme events, over recent decades. Despite identifying large-scale circulation changes as a key driver of the wetting trend, understanding the relative contributions of internal variability and external forcings remains limited. Here, we approach this problem by using a hierarchy of numerical simulations, complemented by diverse statistical analysis tools. Our results offer strong evidence that the atmospheric internal variations primarily drive this observed trend. Specifically, recent changes in the North Atlantic Oscillation have redirected the storm track, leading to increased extratropical storms entering TGD and subsequently more precipitation. A clustering analysis further demonstrates that these linkages predominantly operate at the synoptic scale, with larger contributions from large precipitation events. Our analysis highlights the crucial role of internal variability, in addition to anthropogenic forcing, when seeking a comprehensive understanding of future precipitation trends in TGD.
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... • Global decrease of almost 0.4 K [3] Simulated Pathway (HSW++) 5 • Sulfur dioxide injected into the tropopause using a Gaussian injection profile at the same rate and location as Mt. Pinatubo ...
... All the above functions are supposed to be anomalies relative to t 0 = 1850, that is, it is assumed that T(t 0 ) = 0°C and F(t 0 ) = 0 W/m 2 . T A (t) is expected to be monotonically increasing, T V (t) is expected to be made of spikes that occasionally cool the climate for a few years (Thompson et al., 2009;Marshall et al., 2020), and T S (t) should presents a complex modulation that is also trending upward. ...
The role of the Sun in climate change is hotly debated. Some studies suggest its impact is significant, while others suggest it is minimal. The Intergovernmental Panel on Climate Change (IPCC) supports the latter view and suggests that nearly 100% of the observed surface warming from 1850–1900 to 2020 is due to anthropogenic emissions. However, the IPCC’s conclusions are based solely on computer simulations made with global climate models (GCMs) forced with a total solar irradiance (TSI) record showing a low multi-decadal and secular variability. The same models also assume that the Sun affects the climate system only through radiative forcing – such as TSI – even though the climate could also be affected by other solar processes. In this paper I propose three “balanced” multi-proxy models of total solar activity (TSA) that consider all main solar proxies proposed in scientific literature. Their optimal signature on global and sea surface temperature records is assessed together with those produced by the anthropogenic and volcanic radiative forcing functions adopted by the CMIP6 GCMs. This is done by using a basic energy balance model calibrated with a differential multi-linear regression methodology, which allows the climate system to respond to the solar input differently than to radiative forcings alone, and to evaluate the climate’s characteristic time-response as well. The proposed methodology reproduces the results of the CMIP6 GCMs when their original forcing functions are applied under similar physical conditions, indicating that, in such a scenario, the likely range of the equilibrium climate sensitivity (ECS) could be 1.4 °C to 2.8 °C, with a mean of 2.1 °C (using the HadCRUT5 temperature record), which is compatible with the low-ECS CMIP6 GCM group. However, if the proposed solar records are used as TSA proxies and the climatic sensitivity to them is allowed to differ from the climatic sensitivity to radiative forcings, a much greater solar impact on climate change is found, along with a significantly reduced radiative effect. In this case, the ECS is found to be 0.9–1.8 °C, with a mean of around 1.3 °C. Lower ECS ranges (up to 20%) are found using HadSST4, HadCRUT4, and HadSST3. The result also suggests that at least about 80% of the solar influence on the climate may not be induced by TSI forcing alone, but rather by other Sun-climate processes (e.g., by a solar magnetic modulation of cosmic ray and other particle fluxes, and/or others), which must be thoroughly investigated and physically understood before trustworthy GCMs can be created. This result explains why empirical studies often found that the solar contribution to climate changes throughout the Holocene has been significant, whereas GCM-based studies, which only adopt radiative forcings, suggest that the Sun plays a relatively modest role. Appendix A (Supplementary Data Text) includes the proposed TSA records.
