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The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon (EAWM), as well as the associated atmospheric circulation, was investigated using the hindcast data from Global Seasonal Forecast System version 5 (GloSea5), with a focus on the evolution of model bias among different forecast lead times. While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well, systematic biases exist, including a cold bias for most of China's mainland, especially for North and Northeast China. GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead, which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation. GloSea5 realistically reproduces the synergistic effect of El Niño—Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the EAWM, especially for the western North Pacific anticyclone (WNPAC). Compared with the North Pacific and North America, the representation of circulation anomalies over Eurasia is poor, especially for sea level pressure (SLP), which limits the prediction skill for surface air temperature over East Asia. The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions. [ABSTRACT FROM AUTHOR]

This paper studies the spatiotemporal variability of the IRt index (defined as the difference between the percentage of precipitation corresponding to warm days and cold days in year t) calculated at 35 stations in the Iberian Peninsula during 1951–2019. Spatial variability is estimated using cluster analysis (Euclidean distance, Ward's method), which allows regionalization of the data set for each year's season. For each cluster, the < IR > index is defined as the average of the indexes corresponding to each cluster element. The temporal evolution of the < IR > indices is analyzed by studying the appearance of trends using the Mann–Kendall test and the possible existence of various subperiods using the cumulative sum of deviations and the t-test for the difference between the means. The role of EA, EA/WR, NAO, SCAN and WeMO teleconnection patterns in modulating the relationship between temperature and precipitation is analyzed by applying multiple regression analysis. The results show a trend towards positive (or less negative) values in the relationship between temperatures and precipitation (of varying magnitude depending on the region and season) and the contribution of atmospheric dynamics to these changes. [ABSTRACT FROM AUTHOR]

Climate change affects atmospheric circulation patterns and intensifies recurrent extreme weather events across the globe. It has resulted in increasing air temperatures, rising sea levels, and alterations in precipitation patterns, which will immensely influence the hydro-environment regime in semi-enclosed water bodies (e.g., gulfs and estuaries). The Persian Gulf (PG), the world's hottest sea, is a regional hotspot for climate change. This study investigates how the interplay between climate change and the meteorological variables affects salinity, temperature, and density of water mass concerning water circulation patterns (WCPs) in PG. It contributes to representing a perspective of meteorological conditions over the region and projecting expected seasonal variations of PG hydro-physical properties at the beginning of the next decade. For these purposes, we used the downscaled data of 2030 under RCP2.6, RCP4.5, and RCP8.5 (representative concentration pathway) scenarios to run the hydrodynamic model and also used a 54-year time series (1948–2002) for reference model representing the historical state (HS). The findings project distinguishable temperature rise (reaching 37 °C in summer over vast areas), salinity rise in most parts (up to +5.4 practical salinity units relative to HS at the northwestern head in spring), and an increase in vertical density gradients leading to an increase in speeds of surface currents. These alterations in physical properties significantly influence chemical and biological processes in PG, potentially resulting in aquatic degradation and ecological issues. Therefore, the findings are remarkable for policymakers to develop adaptation management plans in the PG region in line with sustainable development goals. [ABSTRACT FROM AUTHOR]

European climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase. [ABSTRACT FROM AUTHOR]

Record-breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier-than-usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record-breaking heatwaves in Siberia in the spring of 2020. [ABSTRACT FROM AUTHOR]

To better understand the dynamics and impacts of blocking events, their 3D structure needs to be further investigated. We present a comprehensive composite analysis of the 3D structure of blocks and its response to future climate change over the North Pacific, the North Atlantic, and Russia in summers and winters using reanalysis and two large-ensemble datasets from CESM1 and GFDL-CM3. In reanalysis, over both ocean and land, the anomalous winds are equivalent-barotropic in the troposphere and stratosphere, and temperature anomalies are positive throughout the troposphere and negative in the lower stratosphere. The main seasonal and regional differences are that blocks are larger and/or stronger in winters; over oceans, the temperature anomaly is shifted westward due to latent heating. Analyzing the temperature tendency equation shows that in all three sectors, adiabatic warming due to subsidence is the main driver of the positive temperature anomaly; however, depending on season and region, meridional thermal advection and latent heating might have leading-order contributions too. Both GCMs are found to reproduce the climatological 3D structure remarkably well, but sometimes disagree on future changes. Overall, the future summertime response is weakening of all fields (except for specific humidity), although the impact on near-surface temperature is not necessarily weakened; for example, the blocking-driven near-surface warming over Russia intensifies. The wintertime response is strengthening of all fields, except for temperature in some cases. Responses of geopotential height and temperature are shifted westward in winters, most likely due to latent heating. Results highlight the importance of process-level analyses of blocks' 3D structure for improved understanding of the resulting temperature extremes and their future changes. [ABSTRACT FROM AUTHOR]

This study explores the teleconnection between the boreal summer precipitation for the central highlands of Eritrea, with respect to global sea‐surface temperature (SST) and atmospheric parameters (winds, pressure, humidity, and vertical velocity) as indirect indicators of atmospheric circulation. The central‐highland summer (Jul–Aug) precipitation (1914–2015) is significantly negatively correlated with the Atlantic Niño (ATL3) index. Similarly, with a 2‐month (May) or 1‐month lead (Jun), SSTs over the equatorial Atlantic (Gulf of Guinea) are inversely correlated with the central‐highland summer precipitation. Moreover, the regional atmospheric circulation reveals that the boreal summer precipitation series has a significant positive correlation with the westerly wind over the Gulf of Guinea at 700 hPa and a negative correlation with the Tropical Easterly Jet (TEJ) at 200 hPa. Overall, these findings depict the African Walker circulation cell, whereby a low‐level westerly wind flows from the Gulf of Guinea across central Africa, coupled with a rising branch over north‐eastern Africa, and reverses as an easterly wind at a higher level. These significant correlations between Atlantic Ocean SST as the precipitation‐driving factor enabled the development and validation of an area‐specific seasonal precipitation prediction model, as precipitation in this region is temporally and spatially highly variable. [ABSTRACT FROM AUTHOR]

The East Asian winter monsoon in 2018 winter is characterized by below-normal surface air temperature (SAT) over central Siberia and eastern China when the winter mean is considered and by three cold waves when the intraseasonal variability, whose timescale is shorter than a season, is concerned. The three cold waves only consist of approximately 2 weeks, but they play a primary role in shaping the SAT pattern in the winter mean field. Nevertheless, the atmospheric circulation anomalies that shape the SAT pattern during the cold waves cannot be reflected well in the winter mean fields. It leads to insufficiencies to explain the winter mean SAT pattern by examining the winter mean circulation alone. In contrast, the SAT pattern formation can be better interpreted when the role of cold waves is considered. These results suggest that the common approach in climate science to examine the seasonal mean variables alone in understanding the seasonal behaviors of climate misses some crucial aspects, at least for this particular winter, and that the intraseasonal variability should be taken into account to supplement these missing aspects. It is recommended that the influences of intraseasonal variability on the climatic behavior of the East Asian winter monsoon be studied comprehensively in the future to portrait a complete picture of this issue. [ABSTRACT FROM AUTHOR]

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue "windows of forecast opportunity" in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated. [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis. [ABSTRACT FROM AUTHOR]

The Arctic polar vortex (APV) system plays an important role in controlling winter and spring atmospheric circulation pattern in China. Here, we evaluate the anomalous APV-induced spring vegetation variability and lagged productivity responses in China. We found that both strong and weak APV conditions have almost equally negative impacts on spring vegetation growth in China, e.g., negative NDVI anomalies occurred in 48.6 and 53.2% of China's vegetated areas under strong and weak APV conditions, respectively. However, large seasonal compensation effects were associated with weak APV conditions, and beneficial lagged vegetation productivity responses occurred in 67.2% of China's vegetated areas, whereas adverse responses occurred in only 32.8% of vegetated areas. Under a strong APV, adverse lagged vegetation productivity responses occurred in 54.5% of China's vegetated areas, whereas beneficial responses occurred in only 45.5% of vegetated areas. The temperature, precipitation, and solar radiation changes caused by anomalous APV-induced changes in circulation patterns are the main reasons for spring vegetation variability. The lagged vegetation productivity responses were attributed to anomalous APV-related precipitation and air temperature anomalies in the following summer and autumn. This improved understanding of the strong links between APV anomalies and vegetation dynamics in China should facilitate early warning of vegetation productivity reductions under anomalous APV conditions. [ABSTRACT FROM AUTHOR]

The persistence of atmospheric circulation anomalies over East Asia shows a winter to winter recurrence (WTWR) phenomenon. Seasonal variations in sea level pressure anomalies and surface wind anomalies display significantly different characteristics between WTWR and non-WTWR years. The WTWR years are characterized by the recurrence of both a strong (weak) anomalous Siberian High and an East Asian winter monsoon over two successive winters without persistence through the intervening summer. However, anomalies during the non-WTWR years have the opposite sign between the current and ensuing winters. The WTWR of circulation anomalies contributes to that of surface air temperature anomalies (SATAs), which is useful information for improving seasonal and interannual climate predictions over East Asia and China. In the positive (negative) WTWR years, SATAs are cooler (warmer) over East Asia in two successive winters, but the signs of the SATAs are opposite in the preceding and subsequent winters during the non-WTWR years. [ABSTRACT FROM AUTHOR]

The Last Interglacial warm period, the Eemian (ca. 130–116 thousand years ago), serves as a reference for projected future climate in a warmer world. However, there is a limited understanding of the seasonal characteristics of interglacial climate dynamics, especially in high latitude regions. In this study, we aim to provide new insights into seasonal trends in temperature and moisture source location, linked to shifts in atmospheric circulation patterns, for northern Fennoscandia during the Eemian. Our study is based on the distribution and stable hydrogen isotope composition (δD) of n -alkanes in a lake sediment sequence from the Sokli paleolake in NE Finland, placed in a multi-proxy framework. The δD values of predominantly macrophyte-derived mid-chain n -alkanes are interpreted to reflect lake water δD variability influenced by winter precipitation δD (δD prec), ice cover duration and deuterium (D)-depleted meltwater. The δD values of terrestrial plant-derived long-chain n -alkanes primarily reflect soil water δD variability modulated by summer δD prec and by the evaporative enrichment of soil and leaf water. The δD prec variability in our study area is mostly attributed to the temperature effect and the moisture source location linked to the relative dominance between D-depleted continental and polar air masses and D-enriched North Atlantic air masses. The biomarker signal further corroborates earlier diatom-based studies and pollen-inferred January and July temperature reconstructions from the same sediment sequence. Three phases of climatic changes can be identified that generally follow the secular variations in seasonal insolation: (i) an early warming trend succeeded by a period of strong seasonality (ii) a mid-optimum phase with gradually decreased seasonality and cooler summers, and (iii) a late climatic instability with a cooling trend. Superimposed on this trend, two abrupt cooling events occur in the early and late Eemian. The Sokli δD variability is generally in good agreement with other North Atlantic and Siberian records, reflecting major changes in the atmospheric circulation patterns during the Eemian as a response to orbital and oceanic forcings. • Terrestrial and aquatic n -alkanes δD reflect temperature and moisture source seasonality. • Orbital-driven changes in atmospheric circulation influence the δD variability. • δD records reveal changes in the dominance between oceanic and polar/continental air masses. • Colder winters occur in the early Eemian and colder summers in the late Eemian. • Two abrupt cooling events are linked to disturbances in the North Atlantic. [ABSTRACT FROM AUTHOR]