Cold surges, or cold waves, are extreme weather events marked by abrupt drops in surface temperature and strong winds, making them some of the most impactful and concerning phenomena. Unlike cold air outbreaks, which are defined solely by sustained low temperatures, cold surges are characterized by both significant temperature drops and low temperatures. These events can severely disrupt societal activities, posing serious threats to human health, agricultural production, and economic stability. Despite their importance, there is no universally accepted definition of cold surges, and their tracks are often inferred indirectly, using proxies such as the movement of the Siberian High or air particle trajectories. In this study, we propose a unified definition of cold surges and introduce a novel method for their automatic identification and tracking. This algorithm detects cold surges and provides characteristics such as affected areas, duration, temperature drop, and temperature anomalies. Using this method, a Northern Hemisphere cold surge climatology is obtained.Based on the distribution of the frequency of affected areas, the entire Northern Hemisphere is divided into four regions: (1) Africa-Eurasia (AF-EA) ;(2) Pacific Ocean (PO);(3) North America (NA);(4) Atlantic Ocean (AtlO).The characteristics of cold surges in the Northern Hemisphere and these four regions are described. The frequency of cold surges in the Northern Hemisphere shows an increasing trend before 1970 and a decreasing trend after 1970, which is also observed in AF-EA, PO, NA, and AtlO. The duration shows a decreasing trend in the Northern Hemisphere and all four regions. The mean 24-hour temperature drop and the maximum 24-hour temperature show a slight negative (positive) trend in the Northern Hemisphere, AF-EA, and NA (AtlO). The mean and maximum temperature anomalies show a positive trend in the Northern Hemisphere, AF-EA, AtlO, and PO.

How to cite: Cui, W., Wang, L., and Gao, M.: A Climatology of Northern Hemisphere Cold Surge, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1901, https://doi.org/10.5194/egusphere-egu25-1901, 2025.

Previous studies suggested that fast-decay El Niño events are more favorable in generating the western North Pacific anticyclone (WNPAC) in the decaying summer. However, we found that this is not the case for all fast-decay El Niño events. By comparing two groups of fast-decay El Niño events with significant and insignificant WNPAC in the following summer, we found that the westward extension of the equatorial Pacific cold sea surface temperature anomalies (SSTA) and the subtropical central-north Pacific cold SSTA play important roles in the generation and intensification of the WNPAC during decaying summer. Further analyses indicated that the internal atmospheric mode—North Pacific Oscillation during boreal spring can affect the formation of the cold SSTA over the subtropical central-north Pacific and the westward extension of the equatorial Pacific cold SSTA during summer. Additional effects of tropical Indian and Atlantic forcing on the maintenance of the WNPAC are also shown.

How to cite: Jiang, L., Chen, H.-C., Li, T., and Chen, L.: Diverse Response of Western North Pacific Anticyclone to Fast-Decay El Niño During Decaying Summer, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5732, https://doi.org/10.5194/egusphere-egu25-5732, 2025.

Prior results from EGRIP (East Greenland Icesheet Project ice core) indicate that interannual-to-decadal variability in water isotopes lead abrupt Dansgaard-Oeschger event (D-O Events) warming by hundreds of years. As part of the U.S. National Science Foundation funded “Beyond Mean Climate” project, GISP2 (Greenland Ice Sheet Project 2 ice core) is being resampled at the NSF-Ice Core Facility and reanalyzed for high resolution water isotope measurements at INSTAAR, University of Colorado. GISP2 gives us the chance to verify those results from EGRIP and test whether the lead-lag may result from firn processes and diffusion, or from regional climate dynamics. Additionally, for part of this project we are creating a statistical database of climate variability and extremes in multiple Greenland and Antarctic ice cores. This database will include GISP2 and existing records of high-resolution water isotopes and impurities. The initial statistical database of climate indicators will include the mean, standard deviation, extreme values using the tail ends of probability distributions, and spectral analysis to determine the average amplitude in a given frequency band. We will present initial results on the first section of processed data from GISP2, as well as results from WDC (West Antarctic Ice Sheet Divide ice core), SPC (South Pole ice core), and EGRIP (East Greenland Icesheet Project ice core). In particular, we will focus on how the strength of interannual-to-decadal variability is different across geographies (Greenland, Antarctica, interhemispheric), analyze lead-lag between mean temperature and variability (e.g. for D-O Events in Greenland and their Antarctic counterparts, Antarctic Isotope Maxima (AIM) Events), and compare results across the deglaciation.

How to cite: Chase, B. M., Jones, T. R., Markle, B. R., Morris, V., León, R.-J., Rozmiarek, K. S., Johnson, E. H., Lunken, A., Rivas, T. J. L., and Vaughn, B. H.: Creating a Database of Climate Extremes and Variability in Polar Ice Cores, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13940, https://doi.org/10.5194/egusphere-egu25-13940, 2025.

Taking the principle that climate is what one expects, I suggest and illustrate with Sea Surface Temperature (SST) that it is desirable to represent the climatology as linear in time with the first few (3, it turns out) harmonics of the annual cycle. In many regions of the globe the trend is physically and statistically significant. We also expect the seasonal cycle to continue, though amplitude and phase of the harmonics do change — themselves matters of direct interest in climatology. In representing the SST climatology this way, rather than the common average over each month or for each day independently, the approach is similar to how slowly varying terms in astronomy, such as the earth’s eccentricity, are represented by an Epoch (date for time 0) and adjustments for secular changes while moving away in time.  

The Epoch-based climatology approach is shown in comparison to the traditional by developing a 30 year climatology for each and examining the departure from each climatology of the next 10 years observations. The Epoch climatology has markedly reduced anomalies compared to the traditional. A further comparison is to examine the autocorrelation of the anomalies in time. The traditional climatology has inflated times, including excess autocorrelation at annual time scale, meaning that there were things we could and should expect but which are not captured by that approach.

How to cite: Grumbine, R.: Epoch-based Sea Surface Temperature for Climate System Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5192, https://doi.org/10.5194/egusphere-egu25-5192, 2025.

Based on reanalysis data from 1968 to 2021, this study investigates the characteristics of Silk Road Pattern (SRP), a teleconnection pattern embedded in the Asian jet during summer, on the intraseasonal timescale. Results showed that the 10–30-day oscillations are the main component of SRP intraseasonal variability. The results of correlation for the base points along the jet axis indicate that the SRP on the 10–30-day timescale, hereafter referred to as the Bi-weekly Silk Road Pattern Oscillation (BSRP), is characterized by 3 alternatively-signed cells of 200-hPa meridional wind anomalies. The teleconnection patterns are highly consistent, no matter with the location of base points, suggesting that the BSRP is not geographically phase-locked, i.e., the BSRP has no preferred locations in the zonal direction, which is quite different with the SRP on the interannual timescale. Therefore, we “merge” the teleconnection patterns for the various base points into a composite pattern, and analyze the composite pattern to highlight the common features. The analyzed results demonstrate that the BSRP propagates eastwards of, and the speed of energy dispersion is estimated to be approximately 25° per day. In addition, the SRP obtains energy from the basic flows through the baroclinic energy conversion. On the other hand, barotropic energy conversion is weak and shows little variation with the change of longitude, failing to contribute to phase locking. Finally, we also explored the climatic impact of BSRP and found that the BSRP can induce remarkable precipitation and temperature anomalies.

How to cite: Yuan, Q. and Lu, R.: Silk Road Pattern on the Intraseasonal Time Scale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4983, https://doi.org/10.5194/egusphere-egu25-4983, 2025.

The summer North Atlantic Oscillation (SNAO) has been shown to exert a significant influence on downstream climate anomalies, primarily via the Silk Road teleconnection pattern (SRP). However, the linkage between the SNAO and the SRP is not consistently robust, and the SNAO does not invariably excite the SRP. The SRP itself is an upper-tropospheric teleconnection pattern traveling along the midlatitude Asian westerly jet, characterized by alternating southerly and northerly wind anomalies. In this study, we focus on the considerable variability of the SNAO’s southern branch and categorize the interannual SNAO–SRP relationship into two categories: a strongly linked category and a weakly linked category. Our results indicate that, under the strongly linked category, the SNAO’s southern branch retracts westward toward the Baltic Sea, whereas under the weakly linked category, it extends eastward beyond the Ural Mountains. When the southern branch retracts westward, a pronounced negative precipitation anomaly over Europe induces upper-level convergence, producing a strong positive Rossby wave source (RWS) anomaly, which effectively excites the downstream SRP wave train. In contrast, when the southern branch extends eastward, this process does not hold. These findings link the morphology of the SNAO to its capability to initiate the SRP, offering new insights into how the SNAO exerts remote impacts.

How to cite: Yuanxin, G., Riyu, L., and Xiaowei, H.: What type of summer North Atlantic Oscillation will trigger the downstream Silk Road teleconnection pattern, and how?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5054, https://doi.org/10.5194/egusphere-egu25-5054, 2025.

Understanding the relationship between vegetation and climatic drivers is essential for assessing terrestrial ecosystem patterns and managing future vegetation dynamics. This study examines the effects of local climatic factors and remote large-scale ocean–atmosphere circulations from the Pacific, Atlantic, and Arctic Oceans, as well as the East Asian and Indian summer monsoons, on the spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) in the karst region of southwest China (KRSC) using Mann-Kendall test, Sen’s slope, cross-correlation, and wavelet analysis. We observed a significant increase in NDVI over karst and non-karst regions from 1981 to 2019, with a notable abrupt shift from 2001 onwards, underscoring the importance of understanding the underlying drivers. The significant correlation and coherence of surface air (TMP) and soil temperatures (ST) with NDVI, especially when analyzed using wavelet methods, indicate their crucial role in vegetation dynamics. Additionally, the broad coherence patterns of AMO and WHWP with NDVI at annual and decadal cycles suggest that ocean–atmosphere interactions also play a significant part. At interannual periodicities, most large-scale indices displayed significant coherence with NDVI. These findings highlight the complexity of NDVI variability, which is better explained by the integration of multiple local and global factors rather than by single variables. The integrated local–global drivers, particularly TMP-ST-AMO-NP-WHWP and PCP-SM-AMO-NP-WHWP, with mean coherence of 0.90 and 0.89, respectively, showed the highest mean coherence, emphasizing the need for a multifaceted approach in understanding vegetation changes rather than a single local variable or atmospheric circulation index. These findings have significant implications for policy-makers, aiding in better planning and policy formulations considering climate change and atmospheric variability.

How to cite: Hussain, A., Cao, J., Abbas, H., Hussain, I., Zhou, J., Yang, H., Rezaei, A., Luo, Q., Ullah, W., and Liang, Z.: Characterizing the local and global climatic factors associated with vegetation dynamics in the karst region of southwest China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1955, https://doi.org/10.5194/egusphere-egu25-1955, 2025.

Eurasia is a sensitive and high-risk region for global climate changes, where climate anomalies significantly influence natural ecosystems, human health, and economic development. The North Atlantic tripole (NAT) sea surface temperature anomaly is crucial to interannual precipitation variations in Eurasia. Several studies have focused on the link between the NAT and climate anomalies in winter and spring. However, the mechanism by which the summer NAT impacts climate anomalies in Eurasia remains unclear. This study examines how the NAT impacts interannual variations of summer precipitation in mid–high-latitude Eurasia. Precipitation variations are associated with the atmospheric teleconnection triggered by the NAT. When the NAT is in its positive phase, the anomalous atmospheric diabatic heating over the North Atlantic excites an equivalent-barotropic Rossby wave train response that propagates eastward toward Eurasia, resulting in atmospheric circulation anomalies over the region. The combined effects of atmospheric circulation, radiative forcing, and water vapor transport anomalies lead to decreased precipitation across northern Europe and central Eurasia, with higher precipitation anomalies over northeast Asia. Finally, numerical experiments verify that the summer NAT excites atmospheric teleconnections propagating downstream, affecting precipitation anomalies in mid–high-latitude Eurasia. This study provides a scientific basis for predicting Eurasian summer precipitation and strengthening disaster management strategies.

How to cite: shangling, C. and haipeng, Y.: Impact of Summer North Atlantic Sea Surface Temperature Tripole on Precipitation over Mid–High-Latitude Eurasia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2349, https://doi.org/10.5194/egusphere-egu25-2349, 2025.

Teleconnections are crucial in shaping climate variability and regional climate change. The fidelity of teleconnections in climate models is important for reliable climate projections. As the observed sample size is limited, scientific judgment is required when models disagree with observed teleconnections. We illustrate this using the example of the relationship between El Ni.o‐Southern Oscillation (ENSO) and the northern stratospheric polar vortex (SPV), where the MIROC6 large ensemble exhibits an ENSO‐SPV correlation opposite in sign to observations. Yet the model well captures the upward planetary‐wave propagation pathway through which ENSO is known to affect the SPV. We show that the discrepancy arises from the model showing an additional linkage related to horizontal stratospheric wave propagation. Observations do not provide strong statistical evidence for or against the existence of this linkage. Thus, depending on the research purpose, a choice has to be made in how to use the model simulations. Under the assumption that the additional linkage is spurious, a physically‐based bias adjustment is applied to the SPV, which effectively aligns the modeled ENSO-SPV relationship with the observations, and thereby removes the model‐observations discrepancy in the surface air temperature response. However, if one believed that the additional linkage was genuine and was undersampled in the observations, a different approach could be taken. Our study emphasizes that caution is needed when concluding that a model is not suitable for studying teleconnections. We propose a forensic approach and argue that it helps to better understand model performance and utilize climate model data more effectively.

How to cite: Shen, X., Kretschmer, M., and Shepherd, T. G.: A Forensic Investigation of Climate Model Biases inTeleconnections: The Case of the Relationship BetweenENSO and the Northern Stratospheric Polar Vortex, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9462, https://doi.org/10.5194/egusphere-egu25-9462, 2025.

Dynamical storylines explore qualitatively different changes in climate driven by forced responses
in large-scale remote drivers, such as Arctic Amplification, tropical amplification, and the stratospheric
polar vortex. This approach helps address uncertainties in regional climate responses by using physical
understanding to link large-scale thermodynamic and dynamic climate responses to regional impacts and
present a small set of projections in a conditional way. By contextualizing events within broader climate
patterns, dynamical storylines aim to deepen understanding of the uncertainties associated with climate
change, particularly in relation to polar, tropical, and global warming.

Our project aims to make this advanced methodology accessible to a broader audience through a
user-friendly Python package and an intuitive interface. Our package, termed StoryPy, provides
a set of functions to analyze multi-model ensembles by focusing on the identification of dynamical
storylines. With customizable options for selecting remote drivers, target seasons, and climate variables
or climatic-impact drivers, the StoryPy provides flexibility and adaptability for various research
and policy applications. In this work we show the usability of the tool by applying it to the case of the
Mediterranean region and analyze regional climate uncertainty associated with drivers including Arctic
Amplification and the Stratospheric polar vortex.

By facilitating the technical complexity of identifying coherent narratives that bridge the gap between
complex climate dynamics and specific, actionable impacts, our hope is that in the long-run this tools
helps to facilitate dialogue among scientists, policymakers, and diverse stakeholder communities.

How to cite: Alawode, R., Mindlin, J., and Kretschmer, M.: StoryPy: A Python-based package to compute climate storylines, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5659, https://doi.org/10.5194/egusphere-egu25-5659, 2025.

Probabilistic lagged dependence (ranging from months to seasons) between atmospheric-oceanic variables, comes essentially from their linear and nonlinear statistical multivariate correlations. A new technique is presented to estimate the posterior conditional pdf of a scalar predictand y(t+lag) at lag tau, knowing a vector of predictor climatic indices X(t), taken at time t. For that, we apply a variant of the Kernel Canonical Correlation Analysis (KCCA) linking extended feature vectors f(Y) and g(X), filled with nonlinear and mixing functions (e.g. monomials, component products). The issued, leading canonical component pair (u,v) is then used to estimate the copula between X and Y, estimated as the Gaussian copula between Gaussian-anamorphed components ug, vg of u,v respectively. This copula works as a maximum-entropy copula, maximizing the Gaussian correlation Cor-g (Pearson correlation between ug, vg), captured by the feature vectors, and also maximizing the part  -0.5*log(1-cor-g^2) of the mutual information (MI) between X and Y. Moreover, Cor-g is much more outlier-resistant than the Pearson correlation. The above method is applied in two cases: 1) Y being a climatic index, (e.g. El-Niño index with lags tau in the range 0-48 months) and 2) Y being the local monthly temperature or precipitation for lags of 1-2 months. In both cases, X is taken as a set of climatic indices from the pool: El-Niño, NAO, AMO, PDO, IOD; QBO, TNA, TSA, SCAND, WE, EA-WR. The Gaussian-copula model improves the forecast of extreme situations, even beyond 1-2 standard deviations, providing a way of exploring probabilistic nonlinear forecasts and nonlinear lagged teleconnections. This work is supported by the Portuguese Fundação para a Ciência e Tecnologia, FCT, I.P./MCTES through national funds (PIDDAC): UID/50019/2025 and LA/P/0068/2020 https://doi.org/10.54499/LA/P/0068/2020).

How to cite: Pires, C., Hannachi, A., and Vannitsem, S.: Estimation of probabilistic copulas from nonlinear correlations: Application to lagged teleconnections and monthly atmospheric forecasting., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11798, https://doi.org/10.5194/egusphere-egu25-11798, 2025.