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Brandi Newton
,
Diogo Sayanda
, and
Barrie Bonsal

Abstract

Most of the globe has experienced significant warming trends that have been attributed to anthropogenic climate change. However, these rates of warming are also influenced by short-term climate fluctuations driven by atmospheric circulation dynamics, resulting in inconsistent trend magnitudes in both time and space. This research evaluated winter (December–February) temperature trends over 1950–2020 at 91 climate stations across British Columbia (BC), Alberta (AB), and Saskatchewan (SK), Canada, and determined the components attributed to thermodynamic and dynamic (atmospheric circulation) factors. A synoptic climatological approach was used to classify atmospheric circulation patterns in the midtroposphere, relate those patterns to surface temperature, and evaluate changes in frequency. Moderate to high temperature increases over 71 years were found for most of the region, averaging 3.1°C in southern SK to 4.1°C in central-northern AB, and a maximum of 5.8°C in northern BC. Low to moderate increases were found for southern BC, averaging 1.2°C. Changes in atmospheric circulation accounted for 29% and 31% of observed temperature changes in central-northern BC and AB, respectively. Dynamic factors were a moderate driver in southern AB (18%) and central-northern SK (13%), and low in southern SK (5%). Negative dynamic contributions in southern BC (−6%), suggest that atmospheric circulation changes counteracted thermodynamically driven temperature changes. Results were consistent with trend analyses, indicating this method is well suited for trend detection and identification of thermodynamic and dynamic drivers. Results of this research improve our understanding of the magnitude of winter temperature changes critical for informing adaptation and climate-related policy decisions.

Significance Statement

Winter temperatures are strongly influenced by atmospheric circulation patterns, which move warm or cold air masses over large distances. We wanted to understand how changes in atmospheric circulation affect observed changes in winter temperatures in three provinces in western Canada. This also helps us to understand how much temperature change is due to anthropogenic (e.g., caused by greenhouse gases and land cover changes) and naturally occurring changes to Earth’s energy balance. Our results highlight the importance of understanding variability when selecting a time series for trend analyses or climate baselines for modeling studies. This study also helps to inform climate-related policies, decision-making, and adaptation strategies.

Open access
Minghao Yang
,
Yi Li
,
Wei Dong
,
Weilai Shi
,
Peilong Yu
, and
Xiong Chen

Abstract

With a particular focus on the Siberian storm track, this study provides new insights into variations in the warm Arctic–cold Eurasia (WACE) temperature anomaly pattern by using reanalysis data. The results show that the Siberian storm track has a significant out-of-phase relationship with both the WACE pattern and Ural blocking on the interannual time scale. The strengthened WACE pattern can weaken the Siberian storm track through a suppression of the low-level atmospheric baroclinicity over midlatitude Eurasia. The weakened Siberian storm track can contribute to the WACE pattern through feedback forcing from synoptic-scale eddies, which can also create favorable conditions for the development of Ural blocking. Composite temporal evolution reveals that the strongest cold Arctic–warm Eurasia pattern is preceded by the peak of the Siberian storm track. The Ural cyclonic circulation reaches its maximum amplitude on the peak day of the Siberian storm track strength and continues to persist for one day with the maximum amplitude due to the feedback forcing resulting from the Siberian storm track. On the intraseasonal time scale, the occurrence of the Siberian storm track activity can serve as an early indication of the diminished Ural blocking and WACE pattern.

Significance Statement

Because of the high impacts of the warm Arctic–cold Eurasia (WACE) pattern on public safety, socioeconomic development, and the economy, it is crucial to enhance our understanding of variations in the WACE pattern. This paper specifically investigates the impact of internal atmospheric variability on the WACE pattern, focusing on a pronounced negative correlation between the Siberian storm track and the WACE pattern. Daily composites also reveal that Siberian storm track activities can promote a strong cold Arctic–warm Eurasia pattern by maintaining the strength of the quasi-stationary Ural cyclonic circulation. As such, paying close attention to Siberian storm track activities may hold the promise to improve the prediction of the strength of the WACE pattern.

Open access
Ying Mei
,
Wenping He
,
Xiaoqiang Xie
,
Shiquan Wan
, and
Bin Gu

Abstract

In recent years, various early warning signals of critical transition have been presented, such as autocorrelation at lag 1 [AR(1)], variance, the propagator based on detrended fluctuation analysis (DFA-propagator), and so on. Many studies have shown that the climate system has the characteristics of long-term memory (LTM). Will the LTM characteristics of the climate system change as it approaches possible critical transition points? In view of this, the present paper first studies whether the LTM of several folding (folded bifurcation) models changes consistently as they approach their critical points slowly by the rescaled range (R/S) analysis. The results of numerical experiments show that when the control parameters of the folding model are close to its critical threshold, the Hurst exponent H exhibits an almost monotonic increase (significance level α = 0.05). We compare the performance of R/S with the existing indicators, including AR(1), variance, and DFA-propagator, and find that R/S is a perfectly valid alternative. When there is no extra false noise, AR(1) and variance have good early warning effects. After the addition of extra Gaussian white noise of different intensities, the values of AR(1) and variance change significantly. As a result, the DFA-propagator based on AR(1) calibration also changed significantly. Compared with the other three indicators, the early warning effect of H has stronger ability to resist the interference of external false signals. To further verify the validity of increasing H, paleoclimate reconstruction of Cariaco Basin sediment core grayscale record with long trends filtered out is studied by R/S analysis. The other three early warning signals are calculated in the same way. The data contain a well-known abrupt climate change: the transition between the Younger Dryas (YD) and the Holocene. We find that approximately 300 years before this abrupt climate change occurred, before 11.7 kyr BP, the LTM exponents for Cariaco Basin deglacial grayscale data present an obvious increasing trend at a significant level of α = 0.05. Meanwhile, the variation trend of H and DFA-propagator is basically similar. This shows that increasing H by R/S analysis is an effective early warning signal, which indicates that a dynamic system is approaching its possible critical transition points; H is a completely valid alternative signal for AR(1) and DFA-propagator. The main conclusion of this paper is based on numerical experiments. The precise relationship between H and the stability of the underlying state approaching the transition needs to be further studied.

Significance Statement

Dynamic systems have critical transition points, and these systems will suddenly change from a stable state to another alternative one beyond these points. Using several simple theoretical models and paleoclimate data, we study whether the characteristics of long-term memory, which are ubiquitous in complex systems in nature and society, change as a system approaches its critical transition point. The results show that the long-term memory of a dynamic system increases significantly with the approach of the critical point, whether in theoretical models or in paleoclimate data.

Open access
Prajvala Kurtakoti
,
Wilbert Weijer
,
Milena Veneziani
,
Philip J. Rasch
, and
Tarun Verma

Abstract

Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.

Open access
Shuheng Lin
,
Buwen Dong
,
Song Yang
,
Shan He
, and
Yamin Hu

Abstract

This study examines the fidelity of 47 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in representing the influence of El Niño–Southern Oscillation (ENSO) on the Southeast Asian summer monsoon (SEASM) during the ENSO decaying summer. The response of the SEASM to ENSO shows a large model spread among the models, some of which even simulate opposite signs of SEASM anomalies compared to the observed values. The bad-performance models (BPMs) are therefore selected to be compared with both the good-performance models (GPMs) and observations to explore the possible causes of the deficiency. Results show that in the BPMs, the ENSO-related warm sea surface temperature (SST) anomalies extend too far westward in the western equatorial Pacific (WEP) and they do not dissipate in the El Niño decaying summer in comparison with those in the GPMs and observations, interfering with the effect of ENSO on the SEASM. The slow decay of WEP SST anomalies from the El Niño mature winter to the decaying summer in the BPMs is mainly caused by a weak negative shortwave radiation feedback due to a low sensitivity of convection to local SST anomalies, which is related to the cold bias in climatological SST over this region. On the other hand, from the mature winter to the decaying summer of El Niño, the El Niño–related anomalous eastward current does not reverse to a westward current in the BPMs, which also contributes to the slow decay of WEP SST anomalies via inducing excessively persistent warm zonal advection.

Significance Statement

We investigate the possible causes of the diverse impacts of El Niño–Southern Oscillation (ENSO) on the Southeast Asian summer monsoon (SEASM) among 47 CMIP6 models. We find that a plausible reason for the deficiency of some models in simulating the influence of ENSO on the monsoon is that the sea surface temperature (SST) anomalies associated with ENSO are unrealistic in the western equatorial Pacific (WEP) in these models. Further diagnoses indicate that the unrealistic WEP SST anomalies are related to the cold bias of the climatological SST, which could lead to a weak negative shortwave radiation feedback and excessively persistent warm zonal advection. The information provided in this study is useful for improving the skill of the climate models in representing the ENSO–SEASM relationship.

Open access
Shaobo Zhang
,
Zuhao Zhou
,
Peiyi Peng
, and
Chongyu Xu

Abstract

Climate projections obtained by running global climate models (GCMs) are subject to multisource uncertainties. The existing framework based on analysis of variance (ANOVA) for decomposing such uncertainties is unable to include the interaction effect between GCM and internal climate variability, which ranks only second to the main effect of GCM in significance. In this study, a three-way ANOVA framework is presented, and all main effects and interaction effects are investigated. The results show that, although the overall uncertainty (O) is mainly contributed by main effects, interaction effects are considerable. Specifically, in the twenty-first century, the global mean (calculated at the grid-cell level and then averaged, and likewise below) relative contributions of all main effects are 54% for precipitation and 82% for temperature; those of all interaction effects are, respectively, 46% and 18%. As the three-way ANOVA cannot investigate the uncertainty components resulting from uncertainty sources, it is improved by deducing the relationship between uncertainty components resulting from uncertainty sources and those resulting from the main effects and interaction effects. By the improved three-way ANOVA, O is decomposed into uncertainty components resulting from the emission scenario (S), GCM (M), and internal climate variability (V). The results reveal that O is mainly contributed by M in the twenty-first century for precipitation, and by M before the 2060s whereas by S thereafter for temperature. The robustness of the V characterization is explored by investigating the variation of V on the number of included ensemble members. The extent of the underestimation of the V contribution is roughly an average of 4% for precipitation and 1% for temperature.

Open access
Yu-Chiao Liang
,
Young-Oh Kwon
,
Claude Frankignoul
,
Guillaume Gastineau
,
Karen L. Smith
,
Lorenzo M. Polvani
,
Lantao Sun
,
Yannick Peings
,
Clara Deser
,
Ruonan Zhang
, and
James Screen

Abstract

This study investigates the stratospheric response to Arctic sea ice loss and subsequent near-surface impacts by analyzing 200-member coupled experiments using the Whole Atmosphere Community Climate Model version 6 (WACCM6) with preindustrial, present-day, and future sea ice conditions specified following the protocol of the Polar Amplification Model Intercomparison Project. The stratospheric polar vortex weakens significantly in response to the prescribed sea ice loss, with a larger response to greater ice loss (i.e., future minus preindustrial) than to smaller ice loss (i.e., future minus present-day). Following the weakening of the stratospheric circulation in early boreal winter, the coupled stratosphere–troposphere response to ice loss strengthens in late winter and early spring, projecting onto a negative North Atlantic Oscillation–like pattern in the lower troposphere. To investigate whether the stratospheric response to sea ice loss and subsequent surface impacts depend on the background oceanic state, ensemble members are initialized by a combination of varying phases of Atlantic multidecadal variability (AMV) and interdecadal Pacific variability (IPV). Different AMV and IPV states combined, indeed, can modulate the stratosphere–troposphere responses to sea ice loss, particularly in the North Atlantic sector. Similar experiments with another climate model show that, although strong sea ice forcing also leads to tighter stratosphere–troposphere coupling than weak sea ice forcing, the timing of the response differs from that in WACCM6. Our findings suggest that Arctic sea ice loss can affect the stratospheric circulation and subsequent tropospheric variability on seasonal time scales, but modulation by the background oceanic state and model dependence need to be taken into account.

Significance Statement

This study uses new-generation climate models to better understand the impacts of Arctic sea ice loss on the surface climate in the midlatitudes, including North America, Europe, and Siberia. We focus on the stratosphere–troposphere pathway, which involves the weakening of stratospheric winds and its downward coupling into the troposphere. Our results show that Arctic sea ice loss can affect the surface climate in the midlatitudes via the stratosphere–troposphere pathway, and highlight the modulations from background mean oceanic states as well as model dependence.

Open access
Shunsuke Aoki
and
Shoichi Shige

Abstract

To understand how coastal precipitation is controlled by the low-level background wind, we performed comprehensive analysis using the 17-yr observations of the TRMM PR over the entire region of the tropics. We classified the data according to the direction (onshore or offshore) and strength of the cross-shore wind. Under weak winds, the contribution of the diurnal cycle to total precipitation is large, indicating that thermally forced precipitation with a symmetrical propagation pattern with opposite sign across the coastline is dominant. As the background wind strengthens, the contribution of the diurnal cycle reduces owing to the predominance of mechanical forcing; however, the effect of the diurnal cycle remains nonnegligible with an asymmetrical propagation pattern across the coastline. Using the linear theory of the sea–land-breeze circulation, we demonstrated that the difference in propagation is attributable to gravity waves excited by the land–ocean surface heating difference. Under weak winds, symmetrical diurnal phase propagation is caused by the two symmetrical modes of landward and seaward gravity waves. Under stronger background winds, in addition to the Doppler-shifted landward and seaward modes, waves propagating toward the upwind side in the flow-relative frame but with slow group velocity are advected to the downwind near the coastline, forming another mode that moves slowly in the downwind direction. The superposition of the three modes leads to asymmetrical propagation of precipitation with varying phase speed depending on the distance from the coastline.

Open access
Margaret L. Duffy
,
Brian Medeiros
,
Andrew Gettelman
, and
Trude Eidhammer

Abstract

The sensitivity of cloud feedbacks to atmospheric model parameters is evaluated using a CAM6 perturbed parameter ensemble (PPE). The CAM6 PPE perturbs 45 parameters across 262 simulations, 206 of which are used here. The spread in the total cloud feedback and its six components across the CAM6 PPE are comparable to the spread across the CMIP6 and AMIP ensembles, indicating that parametric uncertainty mirrors structural uncertainty. However, the high-cloud altitude feedback is generally larger in the CAM6 PPE than WCRP assessment, CMIP6, and AMIP values. We evaluate the influence of each of the 45 parameters on the total cloud feedback and each of the six cloud feedback components. We also explore whether the CAM6 PPE can be used to constrain the total cloud feedback, with inconclusive results. Further, we find that despite the large parametric sensitivity of cloud feedbacks in CAM6, a substantial increase in cloud feedbacks from CAM5 to CAM6 is not a result of changes in parameter values. Notably, the CAM6 PPE is run with a more recent version of CAM6 (CAM6.3) than was used for AMIP (CAM6.0) and has a smaller total cloud feedback (0.56 W m−2 K−1) as compared to CAM6.0 (0.81 W m−2 K−1) owing primarily to reductions in low clouds over the tropics and midlatitudes. The work highlights the large sensitivity of cloud feedbacks to both parameter values and structural details in CAM6.

Open access
Rachel Diamond
,
David Schroeder
,
Louise C. Sime
,
Jeff Ridley
, and
Danny Feltham

Abstract

The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments (“implicit” schemes) or prognostic melt-pond parameterizations (“explicit” schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere.

Significance Statement

This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change.

Open access