Large-scale Atmospheric Circulation Research Articles

South Atlantic subtropical anticyclone responses to stratospheric aerosol injection

Abstract The South Atlantic Subtropical Anticyclone (SASA) is a key component of large-scale atmospheric circulation and is responsible for driving the climate in eastern Brazil and western Africa. Climate projections under warming scenarios suggest a strengthening, as well as a westward and southward expansion of this system. However, little is known about how the combination of global warming and climate intervention affects this system. To address this, SASA was identified from 2015 to 2099 in a set of projections with and without stratospheric aerosol injection (SAI). Projections were obtained from different initiatives: the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with SAI using Community Earth System Model version 2 (CESM2) global climate model, the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) using CESM1, and the Geoengineering Model Intercomparison Project (GeoMIP/G6sulfur) using Max Planck Institute Earth System Model. As each project has its own specific model, scenario, SAI location, etc, no intercomparison was carried out among them. Instead, there is an indication of what occurs in each project when comparing the near (2040–2059) and the far future (2080–2099) projections under SAI and no-SAI scenarios. SASA under no-SAI scenarios, compared to the reference period (2015–2024), follows the pattern described in the literature, i.e. a tendency to be stronger and wider. However, these features are more evident in the GLENS project. This same project suggests that SAI scenarios contribute to reducing the impact of global warming on the SASA climatology, as SASA in the future acquires characteristics similar to those of the reference period. One of the possibilities for it is that GLENS has the largest SAI forcing, given that the goal was to cancel out the strong greenhouse gas-induced warming in Representative Concentration Pathway 8.5.

Influence of large-scale atmospheric circulation and Mediterranean sea surface temperature to extreme land precipitation: the case of storm Alex

Abstract Extreme (greater than 500 mm) amount of rain fell in southeastern France and northern Italy on 2nd and 3rd October 2020 during a "Mediterranean episode" triggered by the powerful extratropical cyclone Alex. Here we use a dynamical adjustment methodology based on constructed analogues to assess the contributions of different drivers to the magnitude of this extreme precipitation event. We first show that the mean effect of the observed atmospheric circulation pattern, an intense low-pressure system centered over the coasts of Western Europe associated with a cold pool and a secondary low-pressure system, can explain about 80 percent of the precipitation event magnitude. By contrasting the effect of Alex atmospheric circulation with an anomalously warm Mediterranean sea and eastern Atlantic ocean versus neutral sea surface temperature conditions, we show that the influence of September 2020 positive sea surface temperature anomalies can explain a large fraction of the 20 percent residual precipitation over southeastern France and northern Italy. Finally, based on a storyline approach, we find that the dynamic component, the atmospheric circulation contribution to the extreme precipitation event, was more extreme than it would have been, had it occurred during the mid-20th century. The increase in the magnitude of the dynamic component since 1950 follows a Clausius-Clapeyron scaling, in agreement with previous studies about the intensity changes of Mediterranean extreme precipitation episodes. (limit =300 words)

Interannual Variability and Trends in Extreme Precipitation in Dronning Maud Land, East Antarctica

This study examines the trends and interannual variability of extreme precipitation in Antarctica, using six decades (1963–2023) of daily precipitation data from Russia’s Novolazarevskaya Station in East Antarctica. The results reveal declining trends in both the annual number of extreme precipitation days and the total amount of extreme precipitation, as well as a decreasing ratio of extreme to total annual precipitation. These trends are linked to changes in northward water vapor flux and enhanced downward atmospheric motion. The synoptic pattern driving extreme precipitation events is characterized by a dipole of negative and positive height anomalies to the west and east of the station, respectively, which directs southward water vapor flux into the region. Interannual variability in extreme precipitation days shows a significant correlation with the Niño 3.4 index during the austral winter semester (May–October). This relationship, weak before 1992, strengthened significantly afterward due to shifting wave patterns induced by tropical Pacific sea surface temperature anomalies. These findings shed light on how large-scale atmospheric circulation and tropical-extratropical teleconnections shape Antarctic precipitation patterns, with potential implications for ice sheet stability and regional climate variability.

Climatological Study on Cyclone Genesis and Tracks in Southern Brazil from 1979 to 2019

This study investigates cyclone dynamics and impacts in the Southwestern Atlantic, with a focus on their effects on southern Brazil. As climate change intensifies coastal vulnerability, understanding cyclone behavior has become essential. Using the TRACK and cycloTRACK algorithms, we examined cyclone trajectories and cyclogenesis densities from 1979 to 2019 to analyze seasonal and spatial patterns shaped by large-scale atmospheric circulations, including the Antarctic Oscillation (AAO). The analysis explores trends in cyclone activity across various temporal and spatial scales, identifying key regions of cyclogenesis and trajectory density. Results indicate that the cycloTRACK algorithm is more effective at tracking more intense and consistent cyclones, excluding weaker systems. Seasonal patterns suggest variability in cyclone formation, likely associated with atmospheric instability and ocean–atmosphere interactions. While trends reveal an increase in cyclone passages in southern Brazil, these systems are strongly associated with extreme climatic events in the region, including coastal storms, intense precipitation, strong winds, and high waves. By clarifying cyclone dynamics and seasonal patterns, this study enhances our understanding of cyclone behavior and contributes to improved assessments of regional climate resilience in southern Brazil.

Attribution of a record-breaking cold event in the historically warmest year of 2023 and assessing future risks

An unexpected record-breaking cold event struck eastern China in December 2023, causing widespread transportation shutdowns, power supply shortages, and agricultural crop damage. The manner in which such an extraordinary cold event was formed under global warming is unclear, as is the way in which anthropogenic climate change may affect the present and future frequency and intensity of similar cold events. Here, we show that the large-scale atmospheric circulation associated with the warm Arctic was the main event driver, explaining 83 ± 2% of the intensity of the 2023 cold event, whereas the thermodynamic effect of climate change suppressed the event intensity by −6 ± 3% in ERA5 and −22 ± 2% in HadGEM3-A-N216. An attribution analysis based on coupled model simulations shows that, due to anthropogenic climate change, the frequency and intensity of 2023-like events decrease by 92.5 ± 2.5% and 1.9 ± 0.2 °C, respectively, under the 2023 climate state. The thermodynamic effect of anthropogenic climate change outweighs its dynamic effect. Future projections indicate that the frequency and intensity of these 2023-like events will further decrease by 95 ± 3% and 2.05 ± 0.25 °C by the end of this century under an intermediate-emissions scenario compared with estimates made under the present climate. In contrast, 2023-like events will be similar to present events when the 1.5 °C target of the Paris Agreement is achieved. These findings highlight the dampening effect of anthropogenic climate change on cold events, but adaptation measures for future risks of 2023-like cold events will be needed by the end of the century if carbon neutrality is achieved.

Future large-scale atmospheric circulation changes and Greenland precipitation

In this work, we examine connections between patterns of future Greenland precipitation and large-scale atmospheric circulation changes over the Northern Hemisphere. In the last three decades of the 21st century, CMIP5 and CMIP6 ensemble mean precipitation significantly decreases over the northern part of the North Atlantic Ocean with respect to 1951–1980. This drying signal extends from the ocean to the southeastern margin of Greenland. The 500 hPa geopotential height change shows a clear pattern including a widespread increase across the Arctic with a negative anomaly centered over Iceland and surrounding regions. To identify the mechanisms linking atmospheric circulation variability with Greenland precipitation, we perform a singular value decomposition (SVD) and center of action (COA) analysis. We find that a northeastward shift of the Icelandic Low (IL) under the SSP5‐8.5 warming scenario leads to the drying signal found in southeast Greenland. This implies that the IL location will have a strong influence on precipitation changes over southeast Greenland in the future, impacting projections of Greenland ice sheet surface mass balance.

A long-term drought reconstruction based on oxygen isotope tree ring data for central and eastern parts of Europe (Romania)

Abstract. This study investigates the relationship between oxygen isotope ratios (δ18O) in oak tree ring cellulose and past drought variability in Letea Forest, Romania. A δ18O site chronology spanning 1803–2020 was compiled from seven individual time series. δ18O values exhibited a significant negative correlation with moisture-related variables (cloud cover, relative humidity, and precipitation) and a positive correlation with temperature and sunshine duration. This confirms that δ18O from tree rings can be a good proxy for moisture availability. The strongest correlation was found between δ18O and the August Standardized Precipitation Evapotranspiration Index for an accumulation period of 9 months (SPEI9) for central and eastern Europe. This highlights SPEI9 as a superior indicator of drought compared to individual parameters like temperature or precipitation. Using a linear regression model, we reconstructed August SPEI9 variability for the past 200 years. The reconstruction captured interannual and decadal variations, with distinct wet and dry periods. Analysis of large-scale atmospheric circulation patterns revealed a link between high δ18O values (indicating dry conditions) and a high-pressure system over the North Atlantic. Conversely, low δ18O values (indicating wet conditions) corresponded to negative pressure anomalies over Europe. Moreover, extreme values of δ18O are also associated with the prevalence of a hemispheric teleconnection pattern, namely wave number 4. This δ18O chronology and the corresponding August SPEI9 reconstruction offer valuable tools for understanding past climate variability and its relationship with large-scale atmospheric and oceanic circulation patterns.

Improving ozone estimation during rainy-warm seasons from the perspective of weather systems based on machine learning.

Surface ozone pollution in eastern China is increasingly serious during summer, coinciding with distinct stages of the rainy seasons in this region. This study focuses on the spatiotemporal distribution of ozone concentrations, their synoptic driving factors and estimation during the Meiyu periods from 2015 to 2022. Results show that high ozone levels mainly occur during the interval of Meiyu season (HOP), accounting for 15.1% of the total Meiyu period, with MDA8 O3 concentrations in HOP exceeding those in non-HOP (NHOP) by over 20μgm-3 at >60% of sites. Compared to NHOP, HOP is characterized by lower precipitation (-0.17mm), higher temperatures (0.25K), increased solar radiation (3.16kJm-2), and reduced relative humidity (-8.56%). Using the Lindeman, Merenda, and Gold method, it is found that the meteorological factors with the greatest impact on MDA8 O3 during the 2015-2022 Meiyu season are relative humidity (30.4%), surface 2m temperature (28.6%), and total precipitation (23.2%). These favorable conditions for ozone production are along with specific state synoptic-scale and large-scale atmospheric circulation systems. On a daily scale, the further south the position of the western Pacific subtropical high pressure ridge (72.2%) and the stronger the intensities of El Niño-Southern Oscillation and East Asian summer monsoon (19.0%) will lead to higher O3 concentration in the Meiyu-affected area. The results of machine learning prove that instead of conventional consideration of meteorological conditions, the introduction of daily atmospheric circulation indices can effectively improve the accuracy of ozone concentration estimation (R2: 0.72, NRMSE: 0.15). These findings provide valuable insights for predicting ozone pollution during the rainy interval period.

ВЛИЯНИЕ ЛОКАЛИЗАЦИИ ПОЛОЖИТЕЛЬНЫХ АНОМАЛИЙ ТЕМПЕРАТУРЫ ПОВЕРХНОСТИ ТИХОГО ОКЕАНА В ЭКВАТОРИАЛЬНОЙ ЗОНЕ НА ХАРАКТЕР РАСПРОСТРАНЕНИЯ ВОЛНОВОЙ АКТИВНОСТИ ИЗ ТРОПОСФЕРЫ В СТРАТОСФЕРУ В МОДЕЛЬНЫХ ЭКСПЕРИМЕНТАХ

During an El Niño event an area of intense convection is formed above the area of positive sea surface temperature (SST) anomalies in the equatorial Pacific Ocean. This leads to the formation of a Rossby wave, which propagates from low to high latitudes and can lead to changes in largescale atmospheric circulation in mid-latitudes and, as a consequence, to a change in the vertical wave activity flow from the troposphere to the stratosphere. In recent decades, a new type of El Niño – El Niño Modoki – has been increasingly observed. During El Niño Modoki positive SST anomalies are observed in the central part of the equatorial Pacific Ocean, in contrast to the anomalies of the canonical El Niño, which are observed in the east part. The paper shows differences in the nature of the propagation of wave activity in model experiments with SST anomalies located in areas corresponding to the events of the canonical El Niño (Nino 3 region) and El Niño Modoki (Nino 4 region). It was found that, with comparable amplitudes of SST anomalies, the stratospheric polar vortex is more weakened when the localization of the anomalies corresponds to the El Niño Modoki phenomenon. Statistically significant differences in the weakening of the intensity of the stratospheric polar vortex between experiments are observed at the beginning of the extended winter period (November–December) and in spring (March– April). When the anomalies are located in the central part of the equatorial Pacific Ocean, a doubling of the frequency of final sudden stratospheric warmings (SSWs) is observed compared to the experiment where the anomalies correspond to the localization of the canonical El Niño. The more frequent occurrence of SSWs, both final and intraseasonal, in the El Niño Modoki experiment compared to the canonical El Niño is explained by an increase in the meridional component of the three-dimensional flux of wave activity in case of more westerly position of the SST anomaly. This increase is recorded both immediately before the SSW and throughout the winter period (December–February).

Response of Larix sibirica Radial Growth to Climate Change in Kanas, Northern Xinjiang, China

Understanding how forest ecosystems respond to climate variability is critical for predicting the impacts of climate change on semi-arid and temperate regions. This study examines the climatic drivers of radial growth in Larix sibirica Ledeb in the Kanas Lake region, northern Xinjiang, China, to explore how climate change may alter forest growth patterns. Using tree-ring chronologies, we examine the relationships between temperature, precipitation, and drought conditions, as well as the influence of large-scale atmospheric circulation patterns on growth. Results indicate that high summer temperatures negatively affect tree growth, while adequate precipitation plays a crucial role in mitigating water stress, especially during key growth periods. Positive correlations with the Palmer Drought Severity Index further underscore the importance of long-term moisture availability. Moreover, the study highlights the role of the El Niño-Southern Oscillation in influencing moisture transport, with significant correlations between sea surface temperatures in the Niño 4 region and tree-ring growth. Future growth simulations under two climate scenarios suggest that moderate warming (SSP 2–4.5) may enhance growth, while more extreme warming (SSP 5–8.5) introduces greater uncertainty and potential growth instability. These findings provide critical guidance for forest management strategies in the face of climate change.

Concurrent trend turnings of drought severity across Afro-Eurasian continent since 1950

Rapidly intensifying global land drought poses severe threats to human societies, economies, and ecosystems. While previous studies have primarily investigated long-term drought trends, the frequency and concurrence of trend turnings have been largely neglected. In this study, we address this gap by employing the Running Slope Difference (RSD)-t-test to quantify trend turning frequency in Afro-Eurasian drought severity. Based on Palmer Drought Severity Index (PDSI), our analysis indicates that the PDSI trend in most parts of the Afro-Eurasian continent has experienced two turnings since 1950, although, the types of trend turnings vary regionally. The concurrence of these PDSI trending turnings is further investigated. Around 1985, a dipole pattern emerged - Eastern Europe experiences a drying trend turning, accompanied by decreased P-E and intensified drought, while Sahel exhibits a wetting trend turning, with increased P-E and mitigated drought. Around 2000, a tripole pattern is observed in Eastern Eurasia: The Russian Far East and South Asia experienced a drying trend turning, with reduced P-E and intensified drought, while Northeast Asia exhibited a further wetting trend, characterized by increased P-E and mitigated drought. We further investigate the influence of large-scale circulation changes. The enhanced Northern Hemisphere warming trend before and after 1985 contributes to increased land surface high pressure and an amplified meridional temperature gradient, favoring cross-equatorial water vapor transport. This mechanism potentially drives the dipole pattern of trend turning observed around 1985. Additionally, the North Pacific Ocean Sea Surface Temperature (SST) exhibited an enhanced North Pacific Gyre Oscillation (NPGO) pattern around 2000, which induced a tripole atmospheric circulation pattern over East Asia, corresponding to the observed tripole pattern of PDSI trend turnings. The identified dipole and tripole patterns of drought trend turnings, and their potential links to large-scale atmospheric circulation changes, provide insights into the complex dynamics of land drought variability across Afro-Eurasian.

Combined effects of ocean-land processes on spring precipitation variability in Mongolian Plateau

The Mongolian Plateau hosts one of the world's most fragile ecosystems, characterized by high volatility and frequent natural disasters due to rapid climate change and human activities in recent decades. Frequent dust storms notably mark spring in this region. Through observational analysis and numerical modeling, this study investigates the impacts of comprehensive ocean and land processes—including sea surface temperature (SST) in the North Atlantic and Pacific Oceans, as well as Eurasian land conditions—on the interannual fluctuations of spring precipitation in the Mongolian Plateau (SPMP) from 1979 to 2020. The ocean-land processes involve: a tripole pattern of North Atlantic SST anomalies triggers an eastward-propagating continental-scale wave train; Increased snow cover in Central Asia induces significant anomalous low pressure through the albedo effect; El Niño-Southern Oscillation initiate a teleconnection pattern over the upstream region of the Indian-western Pacific Ocean. These anomalous ocean and land conditions interact with large-scale atmospheric circulations, altering dynamical and hydrological conditions around the Mongolian Plateau, thereby contributing to SPMP variation. Further corroboration from numerical model experiments supports the observational analysis results. The combined effects of multiple ocean-land factors effectively explain precipitation variability across extensive areas of the Mongolian Plateau. A regression model constructed using these land-ocean factors captures the time evolution of the SPMP well.

Greater moisture impacts on radial growth of Larix sibirica in the eastern Altay Mountains since the 1990s.

Against the background of climate warming and humidification, the so-called 'divergence problem' reduces the stability of tree rings in response to climate, and affects the reliability of tree-ring reconstruction. Investigation of the divergence problem is crucial to improve our understanding of the response patterns of trees to climate warming, and provide a scientific basis for accurate climate reconstruction. Based on tree-ring width data for Siberian larch (Larix sibirica Ledeb.) growing at low elevations in the eastern Altay Mountains, we analyzed the relationship between radial growth of trees and climatic factors in the context of abrupt climate change in this region. We calculated the proportional contribution of five climatic factors to the radial growth of trees, and discussed the response mechanism of radial growth of L. sibirica in combination with large-scale atmospheric circulation patterns. The radial growth of L. sibirica was mainly constrained by water availability. Before climate warming (1961-1990), the radial growth of L. sibirica was mainly limited by temperature in the previous June. After abrupt climate warming (1991-2020), there was a significant positive correlation between growth and soil moisture in the previous winter, suggesting that high temperatures in the following spring would limit tree radial growth if water availability was low. The attribution analysis results revealed that, before 1990, the proportional of relative contribution of temperature to radial growth of trees exceeded 60%. Since 1990, the proportional of relative contribution of water (precipitation and volumetric soil water) to growth of L. sibirica increased. This might reflect the combined effects of local climatic conditions and changes in large-scale atmospheric circulation.

Westward Displacement of Atmospheric East–West Circulation Ameliorated Drought-Induced Conditions in Australia and India during the Major 2023–24 and 1997–98 El Niño Events

Abstract Based on a compilation of widely available climate analysis products, we show evidence for a significant variation in the spatial pattern of the large-scale vertical zonal atmospheric circulation patterns across the equatorial Indo-Australasian domain of the Eastern Hemisphere during the major 2023–24 El Niño event. The region of large-scale subsidence and its associated teleconnection patterns that are usually centered across Indonesia (the “Maritime Continent”) were displaced to the west over the equatorial Indian Ocean. In the record of El Niño events with readily available online dynamical tropospheric fields (one source from 1947 and the other from 1979), this has only been seen two other times, during the strong 1997–98 El Niño and the weaker 1977–78 event. These three events may well be consistent with internal variability, but at present, the reason for such occurrences has not been established.

Partitioning of Heavy Rainfall in the Taihang Mountains and Its Response to Atmospheric Circulation Factors

The spatial and temporal distribution of heavy rainfall across the Taihang Mountains exhibits significant variation. Due to the region’s unstable geological conditions, frequent heavy rainfall events can lead to secondary disasters such as landslides, debris flows, and floods, thus intensifying both the frequency and severity of extreme events. Understanding the spatiotemporal evolution of heavy rainfall and its response to atmospheric circulation patterns is crucial for effective disaster prevention and mitigation. This study utilized daily precipitation data from 13 meteorological stations in the Taihang Mountains spanning from 1973 to 2022, employing Rotated Empirical Orthogonal Function (REOF), the Mann–Kendall Trend Test, and Continuous Wavelet Transform (CWT) to examine the spatiotemporal characteristics of heavy rainfall and its relationship with large-scale atmospheric circulation patterns. The results reveal that: (1) Heavy rainfall in the Taihang Mountains can be categorized into six distinct regions, each demonstrating significant spatial heterogeneity. Region I, situated in the transition zone between the plains and mountains, experiences increased rainfall due to orographic lifting, while Region IV, located in the southeast, receives the highest rainfall, driven primarily by monsoon lifting. Conversely, Regions III and VI receive comparatively less precipitation, with Region VI, located in the northern hilly area, experiencing the lowest rainfall. (2) Over the past 50 years, all regions have experienced an upward trend in heavy rainfall, with Region II showing a notable increase at a rate of 14.4 mm per decade, a trend closely linked to the intensification of the hydrological cycle driven by global warming. (3) The CWT results reveal significant 2–3-year periodic fluctuations in rainfall across all regions, aligning with the quasi-biennial oscillation (QBO) characteristic of the East Asian summer monsoon, offering valuable insights for future climate predictions. (4) Correlation and wavelet coherence analyses indicate that rainfall in Regions II, III, and IV is positively correlated with the Southern Oscillation Index (SOI) and the Pacific Warm Pool (PWP), while showing a negative correlation with the Pacific Decadal Oscillation (PDO). Rainfall in Region I is negatively correlated with the Indian Ocean Dipole (IOD). These climatic factors exhibit a lag effect on rainfall patterns. Incorporating these climatic factors into future rainfall prediction models is expected to enhance forecast accuracy. This study integrates REOF analysis with large-scale circulation patterns to uncover the complex spatiotemporal relationships between heavy rainfall and climatic drivers, offering new insights into improving heavy rainfall event forecasting in the Taihang Mountains. The complex topography of the Taihang Mountains, combined with unstable geological conditions, leads to uneven spatial distribution of heavy rainfall, which can easily trigger secondary disasters such as landslides, debris flows, and floods. This, in turn, further increases the frequency and severity of extreme events.

Early emergence and determinants of human-induced Walker circulation weakening

The Walker circulation is projected to slow down in response to greenhouse gas warming. However, detecting the impact of human activities on changes in the Walker circulation is challenging due to the significant influence of internal variability. Here, based on ensembles of multiple climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we show evidence that the emergence of the human-induced weakening of Walker circulation tends to occur earlier in the middle-upper troposphere than at the surface. This earlier emergence is attributed to a more pronounced initial weakening response of the middle-upper tropospheric Walker circulation to atmospheric CO2 radiative forcing. We further reveal that the emergence time of a weaker Walker circulation varies across models. This intermodel spread is governed by an ocean thermostat that operates by modulating the zonal sea surface temperature gradient over the tropical Indo-Pacific region. Our findings address the key question of whether and how to detect human-induced large-scale atmospheric circulation changes and provide valuable insights for assessing the associated risks.

Основные особенности климатических условий зимнего сезона 2023/2024 гг. по данным мониторинга и прогнозов

The main results of the comprehensive analysis of the Northern Hemisphere large-scale atmospheric circulation features are presented for the 2023/2024 winter season. Skill scores of the consensus forecast for the 2023/2024 Northern Eurasia winter season are discussed in the context of reproducing the temperature and humidity regime. The qualitative analysis of the multimodel forecast from WMO’s Lead Center and the consensus forecast issued by NEACOF for seasonal anomalies in air temperature and precipitation for the winter of 2023/2024 resulted in the conclusion of the superior accuracy of the consensus forecast. This forecast was based on the data of three Russian models SL-AV, MGO, and INM with equal weighting coefficients.

Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changes

Abstract. Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage deep learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere–ocean–land-surface components. Large-scale circulation patterns can mediate the impact of the forcing on Arctic climate dynamics. We employed a DL-based clustering approach to classify large-scale atmospheric circulation patterns. To enhance the analysis of how these patterns impact the Arctic climate, the poleward moist static energy transport (PMSET) associated with the atmospheric circulation patterns was incorporated as an additional similarity metric in the clustering process. Furthermore, we developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative radiative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, our analysis revealed that while the regional radiative forcing alters the occurrence frequencies of the circulation patterns, these changes are not the primary drivers of the forcing's impact on the Arctic parameters. Instead, it is the shifts in the mean spatial characteristics of the atmospheric circulation patterns, induced by the forcing, that predominantly determine the effects on the Arctic climate. Our methodology facilitates the uncovering of complex, nonlinear interactions within the climate system, capturing nuances that are often obscured in broader seasonal anomaly analyses. This approach enables a deeper understanding of the dynamics driving observed climatic anomalies and their links to specific atmospheric circulation patterns.

Historical drivers and future streamflow variations of the Kura River in the Western Transcaucasia region of Georgia: Analysis of tree-ring chronologies from 1720 to 2021 CE

In this paper, we conduct a dendrochronological study in the Western Transcaucasia region of Georgia to elucidate the relationship between tree growth and climatic variables (temperature, precipitation, and streamflow) in order to reconstruct the paleohydrology of the Kura River and to assess the impacts of climate change on water resources. We analyzed tree-ring chronologies from 1720 to 2021 CE, and analysis of July–August streamflow revealed five wet phases (1739–1753, 1764–1807, 1811–1831, 1962–1988 and 2000–2019 CE ranging in duration from 11 to 49 years) when streamflow exceeded the long-term mean, and four dry phases (1720–1738, 1832–1881, 1936–1961 and 1989–1999 CE) when streamflow was below average. The most extreme wet and dry years were 1771 and 1851 CE, respectively. Spatial correlation patterns of Kura River reconstructed runoff against sea level pressure (SLP) are negative in the Arctic and positive in mid- to high-latitude Eurasia. The Arctic Oscillation (AO)/North Atlantic Oscillation (NAO), and solar activity are important drivers of hydroclimatic conditions in the Mediterranean region, by modifying the location of high-pressure areas and large-scale atmospheric circulations. Comparison of our Kura streamflow reconstructions and data in the Old World Drought Atlas (OWDA) reveals a moderately positive correlation (0.40) throughout the study period, being strongest over the Southern Caucasus and Eastern Turkey. This validates the drought signals and emphasizes the importance of using multi-proxy approaches, supported by spatially resolved data, to enhance understanding of regional hydroclimatic variability and drought patterns. We additionally conducted future streamflow scenarios, most notably under the high-emission SSP585 scenario, in line with global trends in CMIP6 projections. Our streamflow results indicate a trend towards increasing drought severity, which highlights the need for urgent adaptation and mitigation strategies in water resource management in this region. Ultimately, this study provides valuable information on historical hydroclimatic conditions in the Kura River Basin, which help to develop strategies to mitigate the hydrologic impacts of climate change in the Western Transcaucasia Caucasus region. We further highlight the importance of regional and global teleconnections for understanding regional hydrological dynamics.

Random Forests’ Postprocessing Capability of Enhancing Predictive Skill on Subseasonal Time Scales—A Flow-Dependent View on Central European Winter Weather

Abstract Weather predictions 2–4 weeks in advance, called the subseasonal time scale, are highly relevant for socioeconomic decision-makers. Unfortunately, the skill of numerical weather prediction models at this time scale is generally low. Here, we use probabilistic random forest (RF)-based machine learning models to postprocess the subseasonal to seasonal (S2S) reforecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF). We show that these models are able to improve the forecasts slightly in a 20-winter mean at lead times of 14, 21, and 28 days for wintertime central European mean 2-m temperatures compared to the lead-time-dependent mean bias-corrected ECMWF’s S2S reforecasts and RF-based models using only reanalysis data as input. Predictions of the occurrence of cold wave days are improved at lead times of 21 and 28 days. Thereby, forecasts of continuous temperatures show a better skill than forecasts of binary occurrences of cold wave days. Furthermore, we analyze if the skill depends on the large-scale flow configuration of the atmosphere at initialization, as represented by weather regimes (WRs). We find that the WR at the start of the forecast influences the skill and its evolution across lead times. These results can be used to assess the conditional improvement of forecasts initialized during one WR in comparison to forecasts initialized during another WR. Significance Statement Forecasts of winter temperatures and cold waves 2–4 weeks in advance done by numerical weather prediction (NWP) models are often unsatisfactory due to the chaotic characteristics of the atmosphere and limited predictive skill at this time range. Here, we use statistical methods, belonging to the so-called machine learning (ML) models, to improve forecast quality by postprocessing predictions of a state-of-the-art NWP model. We compare the forecasts of the NWP and ML models considering different weather regimes (WRs), which represent the large-scale atmospheric circulation such as the typical westerly winds in Europe. We find that the ML models generally yield better temperature forecasts for 14, 21, and 28 days in advance and better forecasts of cold wave days 21 and 28 days in advance. The quality of forecasts depends on the WR present at the forecast start. This information can be used to assess the conditional improvement of forecasts.