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Wei Dong
,
XiaoJing Jia
, and
Renguang Wu

Abstract

This study revealed a significant interdecadal change in the impact of spring western Tibetan Plateau (TP) snow cover (TPSC) on subsequent summer compound heat waves (CHWs) in western Europe (WE) after 1998. This interdecadal change is attributed to a change in a western Europe high–western TP low (WEH–TPL) atmospheric circulation pattern. This pattern arises due to both the inherent variability of TPSC and the phase transition of the Atlantic multidecadal oscillation (AMO) after 1998. The increased magnitude and persistence of western TPSC from spring to summer after 1998 enhanced the snow–atmosphere coupling effect, intensifying ascent and decent motion over the TP and WE, respectively, and strengthening the WEH–TPL pattern. In addition, the post-1998 positive AMO phase favors continuous and stable downstream Rossby wave propagation, enhancing the WEH–TPL pattern and the TPSC–CHWs relationship. Further analyses reveal that the interdecadal changes in the TPSC and the AMO around 1998 contribute to the presence of “double jets” over the North Atlantic–central Eurasian sectors. The TPSC–related anomalous atmospheric circulation and AMO phase shift contribute to the southern and northern branches of the intensified westerly jet, respectively. These conditions create a favorable environment for the formation and persistence of summer CHWs in WE. Numerical modeling experiments with a linear baroclinic model confirm these findings. Our findings suggest that in the context of a changing climate, TPSC plays a pivotal role in the genesis of summer CHWs in WE and may serve as a valuable predictor for CHWs.

Significance Statement

This study discovered that starting from 1998 there was a significant change in how spring snow cover on the western Tibetan Plateau affects summer compound heat waves in western Europe. After 1998, the snow cover on the western Tibetan Plateau increased in size and lasted longer from spring to summer, intensifying the interaction between the snow and the atmosphere. This led to more rising and sinking air over the Tibetan Plateau and western Europe, respectively. Also, after 1998 a positive phase of the Atlantic multidecadal oscillation (AMO) was favorable for the circulation connection between western Europe and the Tibetan Plateau. Further analysis showed that these changes in snow cover and the AMO after 1998 caused “double jets” in the North Atlantic and central Eurasia that created better conditions for summer heat waves in western Europe. Numerical models are used to confirm these findings. Our research indicates that, in a changing climate, the snow cover on the western Tibetan Plateau plays a crucial role in the development of summer heat waves in western Europe and can be a useful predictor for these heat waves.

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Claudia Timmreck
,
Dirk Olonscheck
,
Andrew P. Ballinger
,
Roberta D’Agostino
,
Shih-Wei Fang
,
Andrew P. Schurer
, and
Gabriele C. Hegerl

Abstract

Large explosive volcanic eruptions cause short-term climatic impacts on both regional and global scales. Their impact on tropical climate variability, in particular El Niño–Southern Oscillation (ENSO), is still uncertain, as is their combined and separate effect on tropical and global precipitation. Here, we investigate the relationship between large-scale temperature and precipitation and tropical volcanic eruption strength, using 100-member MPI-ESM ensembles for idealized equatorial symmetric Northern Hemisphere summer eruptions of different sulfur emission strengths. Our results show that for idealized tropical eruptions, global and hemispheric mean near-surface temperature and precipitation anomalies are negative and linearly scalable for sulfur emissions between 10 and 40 Tg S. We identify 20 Tg S emission as a threshold where the global ensemble-mean near-surface temperature and precipitation signals exceed the range of internal variability, even though some ensemble members emerge from variability for lower eruption strengths. Seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are highly correlated across eruption strengths, in particular for larger emission strengths in the tropics, and strongly modulated by ENSO. There is a tendency to shift toward a warm ENSO phase for the first postvolcanic year as the emission strength increases. Volcanic cooling emerges on a hemisphere-wide scale, while the precipitation response is more localized, and emergence is mainly confined to the tropics and subtropics.

Significance Statement

The purpose of this study is to investigate at which strength the climate responses of volcanic forcing can be distinguished from the internal climate variability and whether the responses will linearly increase as the emission strengths become stronger. We ran 100-member MPI-ESM ensembles of idealized equatorial volcanic eruptions of different sulfur emission strengths and find that seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are distinguishable and linearly scalable for sulfur emissions from 10 to 40 Tg S if their forcing patterns are similar. The identification of volcanic fingerprints is important for seasonal to decadal forecasts in the case of potential future eruptions and could help to prepare society for the regional climatic consequences of such an event.

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Igor V. Polyakov
,
Thomas J. Ballinger
,
Rick Lader
, and
Xiangdong Zhang

Abstract

Strengthened by polar amplification, Arctic warming provides direct evidence for global climate change. This analysis shows how Arctic surface air temperature (SAT) extremes have changed throughout time. Using ERA5, we demonstrate a pan-Arctic (>60°N) significant upward SAT trend of +0.62°C decade−1 since 1979. Due to this warming, the warmest days of each month in the 1980s to 1990s would be considered average today, while the present coldest days would be regarded as normal in the 1980s to 1990s. Over 1979–2021, there was a 2°C (or 7%) reduction of pan-Arctic SAT seasonal cycle, which resulted in warming of the cold SAT extremes by a factor of 2 relative to the SAT trend and dampened trends of the warm SAT extremes by roughly 25%. Since 1979, autumn has seen the strongest increasing trends in daily maximum and minimum temperatures, as well as counts of days with SAT above the 90th percentile and decreasing trends in counts of days with SAT below the 10th percentile, consistent with rapid Arctic sea ice decline and enhanced air–ocean heat fluxes. The modulated SAT seasonal signal has a significant impact on the timing of extremely strong monthly cold and warm spells. The dampening of the SAT seasonal fluctuations is likely to continue to increase as more sea ice melts and upper-ocean warming persists. As a result, the Arctic winter cold SAT extremes may continue to exhibit a faster rate of change than that of the summer warm SAT extremes as the Arctic continues to warm.

Significance Statement

As a result of global warming, the Arctic Ocean’s sea ice is receding, exposing more and more areas to air–sea interactions. This reduces the range of seasonal changes in Arctic surface air temperatures (SAT). Since 1979, the reduced seasonal SAT signal has decreased the trend of warm SAT extremes by 25% over the background warming trend and doubled the trend of cold SAT extremes relative to SAT trends. A substantial number of warm and cold spells would not have been identified as exceptional if the reduction of the Arctic SAT seasonal amplitudes had not been taken into account. As the Arctic continues to warm and sea ice continues to diminish, seasonal SAT fluctuations will become more dampened, with the rate of decreasing winter SAT extremes exceeding the rate of increasing summer SAT extremes.

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Robert H. Nazarian
,
Noel G. Brizuela
,
Brody J. Matijevic
,
James V. Vizzard
,
Carissa P. Agostino
, and
Nicholas J. Lutsko

Abstract

Northern Mexico is home to more than 32 million people and is of significant agricultural and economic importance for the country. The region includes three distinct hydroclimatic regions, all of which regularly experience severe dryness and flooding and are highly susceptible to future changes in precipitation. To date, little work has been done to characterize future trends in either mean or extreme precipitation over northern Mexico. To fill this gap, we investigate projected precipitation trends over the region in the NA-CORDEX ensemble of dynamically downscaled simulations. We first verify that these simulations accurately reproduce observed precipitation over northern Mexico, as derived from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, demonstrating that the NA-CORDEX ensemble is appropriate for studying precipitation trends over the region. By the end of the century, simulations forced with a high-emissions scenario project that both mean and extreme precipitation will decrease to the west and increase to the east of the Sierra Madre highlands, decreasing the zonal gradient in precipitation. We also find that the North American monsoon, which is responsible for a substantial fraction of the precipitation over the region, is likely to start later and last approximately three weeks longer. The frequency of extreme precipitation events is expected to double throughout the region, exacerbating the flood risk for vulnerable communities in northern Mexico. Collectively, these results suggest that the extreme precipitation-related dangers that the region faces, such as flooding, will increase significantly by the end of the century, with implications for the agricultural sector, economy, and infrastructure.

Significance Statement

Northern Mexico regularly experiences severe flooding and its important agricultural sector can be heavily impacted by variations in precipitation. Using high-resolution climate model simulations that have been tested against observations, we find that these hydroclimate extremes are likely to be exacerbated in a warming climate; the dry (wet) season is projected to receive significantly less (more) precipitation (approximately ±10% by the end of the century). Simulations suggest that some of the changes in precipitation over the region can be related to the North American monsoon, with the monsoon starting later in the year and lasting several weeks longer. Our results also suggest that the frequency of extreme precipitation will increase, although this increase is smaller than that projected for other regions, with the strongest storms becoming 20% more frequent per degree of warming. These results suggest that this region may experience significant changes to its hydroclimate through the end of the century that will require significant resilience planning.

Open access
Dong Wan Kim
,
Sukyoung Lee
,
Joseph P. Clark
, and
Steven B. Feldstein

Abstract

A thermodynamic energy budget analysis is applied to the lowest model level of the ERA5 dataset to investigate the mechanisms that drive the growth and decay of extreme positive surface air temperature (SAT) events. Regional and seasonal variation of the mechanisms are investigated. For each grid point on Earth’s surface, a separate composite analysis is performed for extreme SAT events, which are days when temperature anomaly exceeds the 95th percentile. Among the dynamical terms, horizontal temperature advection of the climatological temperature by the anomalous wind dominates SAT anomaly growth over the extratropics, while nonlinear horizontal temperature advection is a major factor over high-latitude regions and the adiabatic warming is important over major mountainous regions. During the decay period, advection of the climatological temperature by the anomalous wind sustains the warming while nonlinear advection becomes the dominant decay mechanism. Among diabatic heating processes, vertical mixing contributes to the SAT anomaly growth over most locations while longwave radiative cooling hinders SAT anomaly growth, especially over the ocean. However, over arid regions during summer, longwave heating largely contributes to SAT anomaly growth while the vertical mixing dampens the SAT anomaly growth. During the decay period, both longwave cooling and vertical mixing contribute to SAT anomaly decay with more pronounced effects over the ocean and land, respectively. These regional and seasonal characteristics of the processes that drive extreme SAT events can serve as a benchmark for understanding the future behavior of extreme weather.

Open access
Duo Chan
,
Geoffrey Gebbie
, and
Peter Huybers

Abstract

Land surface air temperatures (LSAT) inferred from weather station data differ among major research groups. The estimate by NOAA’s monthly Global Historical Climatology Network (GHCNm) averages 0.02°C cooler between 1880 and 1940 than Berkeley Earth’s and 0.14°C cooler than the Climate Research Unit estimates. Such systematic offsets can arise from differences in how poorly documented changes in measurement characteristics are detected and adjusted. Building upon an existing pairwise homogenization algorithm used in generating the fourth version of NOAA’s GHCNm(V4), PHA0, we propose two revisions to account for autocorrelation in climate variables. One version, PHA1, makes minimal modification to PHA0 by extending the threshold used in breakpoint detection to be a function of LSAT autocorrelation. The other version, PHA2, uses penalized likelihood to detect breakpoints through optimizing a model-selection problem globally. To facilitate efficient optimization for series with more than 1000 time steps, a multiparent genetic algorithm is proposed for PHA2. Tests on synthetic data generated by adding breakpoints to CMIP6 simulations and realizations from a Gaussian process indicate that PHA1 and PHA2 both similarly outperform PHA0 in recovering accurate climatic trends. Applied to unhomogenized GHCNmV4, both revised algorithms detect breakpoints that correspond with available station metadata. Uncertainties are estimated by perturbing algorithmic parameters, and an ensemble is constructed by pooling 50 PHA1- and 50 PHA2-based members. The continental-mean warming in this new ensemble is consistent with that of Berkeley Earth, despite using different homogenization approaches. Relative to unhomogenized data, our homogenization increases the 1880–2022 trend by 0.16 [0.12, 0.19]°C century−1 (95% confidence interval), leading to continental-mean warming of 1.65 [1.62, 1.69]°C over 2010–22 relative to 1880–1900.

Significance Statement

Accurately correcting for systematic errors in observational records of land surface air temperature (LSAT) is critical for quantifying historical warming. Existing LSAT estimates are subject to systematic offsets associated with processes including changes in instrumentation and station movement. This study improves a pairwise homogenization algorithm by accounting for the fact that climate signals are correlated over time. The revised algorithms outperform the original in identifying discontinuities and recovering accurate warming trends. Applied to monthly station temperatures, the revised algorithms adjust trends in continental mean LSAT since the 1880s to be 0.16°C century−1 greater relative to raw data. Our estimate is most consistent with that from Berkeley Earth and indicates lesser and greater warming than estimates from NOAA and the Met Office, respectively.

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Sandrine Trotechaud
,
Bruno Tremblay
,
James Williams
,
Joy Romanski
,
Anastasia Romanou
,
Mitchell Bushuk
,
William Merryfield
, and
Rym Msadek

Abstract

Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous offshore ice drift along the Eurasian coastline, leading to local ice thickness anomalies at the onset of the melt season—a signal then amplified by the ice–albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE; a proxy for Eurasian coastal divergence) is present in global climate model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counterintuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large, or late in the simulation when the sea ice is thin, and/or when internal variability increases. More important, periods with weak correlation between winter FSIAE and the following Sept SIE dominate, suggesting that summer melt processes generally dominate over late-winter preconditioning and May SIT anomalies. In general, we find that the coupling between the winter FSIAE and ice thickness anomalies along the Eurasian coastline at the onset of the melt season is a ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness.

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Zunya Wang
,
Xingwen Jiang
,
Zongjian Ke
, and
Yafang Song

Abstract

The related atmospheric and oceanic factors are investigated in this analysis to understand the natural attributes responsible for the significant increase of the high temperature extremes (HTEs) on the Tibetan Plateau (TP) in summer. It is found that a stronger-than-normal South Asian high (SAH) and corresponding weaker-than-normal East Asian jet, an anomalous anticyclone and intensified midlevel westerly wind over the TP, and a more extensive, stronger, farther westward- and northward-stretching western Pacific subtropical high motivate more occurrences of HTEs over the TP on the interannual time scale. From 1961 to 2021, these crucial circulation patterns show a significant changing trend favorable for the occurrence of HTEs and thus contribute to its great increase. Further, the significant warmings of sea surface temperature (SST) in the tropical western Indian, northern North Pacific, and western North Atlantic Oceans make great contributions through different air–sea interactive processes as the Matsuno–Gill response, zonal vertical circulation cell, and mid- to high-latitude teleconnection wave train, respectively. Meanwhile, the interdecadal variability plays an important role. A breakpoint at the early twenty-first century is detected in the occurrence of summer HTEs on the TP. Both the crucial circulation patterns and the SST anomalies in the key oceanic regions experienced significant interdecadal transition to favor the occurrence of HTEs. In particular, the Atlantic multidecadal oscillation (AMO) is significantly and positively correlated with the interdecadal variation of summer HTEs on the TP. The zonal teleconnection wave train triggered by AMO forms a stronger-than-normal SAH and strengthened midlevel westerly airflow over the TP, conducive to the increase of summer HTEs on the TP.

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Tong Shen
and
Riyu Lu

Abstract

This study investigates the relationship between the uncertainty of empirical orthogonal function (EOF) modes and sampling size in climate models, using simulated results of preindustrial control (piControl) experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6), and taking the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) as examples. The results indicate that this relationship can be quantified by a concise fitting function [i.e., y = a/(xb)]. Here, y is the 5%–95% confidence interval of congruence coefficient, x is the sampling size, and a and b are two parameters depending on models or observations. As compared with b, which modulates the sampling size in the fitting function, the parameter a scales the sampling size and thus plays a much more important role. Further analysis indicates that the parameter a, or the uncertainty of EOF1 mode, decreases dramatically with the increase of the difference between variance fractions of EOF1 and EOF2 modes, approximately in the form of a power function. The minimum sampling size to ensure a reliable EOF mode can also be estimated by the fitting function and shows a great diversity among models both for the NAO and ENSO. The diversity suggests the importance of estimating the minimum sampling size before model evaluations on climate variability modes and projections on the future change in modes, particularly when the EOF2 mode explains the variance close to EOF1 mode.

Significance Statement

Empirical orthogonal function (EOF) analysis, principal component analysis, or eigenvector analysis has been widely used in various research fields. However, it remains as an open question as to how large the sampling size is required to be to obtain reliable modes through the EOF method. In this study, we investigate the relationship between the uncertainty of EOF results and sampling size in current climate models, using adequately long simulated data, and we find that this relationship can be depicted by the fitting function y = a/(xb). Here, y represents the uncertainty, x is the sampling size, and a and b are parameters. The parameter a is closely related to the difference between variance fractions of first and second EOF modes and plays a more important role in the fitting function. The minimum sampling sizes that are required to obtain reliable EOF modes can also be estimated by the fitting function and vary greatly from model to model. The results provide a basis for judging the reliability of EOF modes, particularly when the first and second EOF modes explain similar variance fractions.

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Sizhuo Wei
,
Pang-Chi Hsu
, and
Jinhui Xie

Abstract

The time of rainy season onset is crucial information for policymakers, especially in densely populated regions such as the Yangtze River basin (YRB) in China. In this study, we proposed a new grid-based index to objectively detect mei-yu onset timing using reanalysis data and model predictions, and then we identified the key processes via which intraseasonal oscillation (ISO) affects the YRB mei-yu onset and its subseasonal predictability based on scale-decomposed moisture analysis. Climatologically, propagation of an ISO anticyclonic anomaly toward East China supports the moisture convergence required for rainy season onset over the YRB via interaction with the seasonal-mean moisture component. In the years of early mei-yu onset, the ISO was enhanced earlier in May and favored the moisture convergence anomaly in late May–early June, when the mei-yu started. In contrast, the enhanced ISO and associated moistening processes were observed later in June–early July in the years with delayed onset. The European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction models show skillful prediction of mei-yu onset at forecast lead times of 5–6 pentads, whereas the China Meteorological Administration model has limited skill of 3 pentads. The differences in model prediction skill are related to the accuracy of predicted moisture convergence anomalies induced by the ISO. The prediction bias in mei-yu onset timing (early or delayed) is also connected to bias in the occurrence timing of enhanced intraseasonal perturbations, suggesting the vital role of ISO in YRB mei-yu onset on the subseasonal time scale.

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