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Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation. [ABSTRACT FROM AUTHOR]

Interannual-to-decadal variability of Rhine River streamflow and their relationship with large-scale climate anomaly patterns for spring [March-May (MAM)] and autumn [September-November (SON)] are investigated through a statistical analysis of observed streamflow data and global climate anomaly fields. A wavelet analysis reveals that spring streamflow variability is nonstationary with enhanced variability in the 8-16-yr band from 1860 to 1900 and in the 2-8 and 16-30 yr after 1960. A composite analysis reveals that streamflow anomalies during spring are related to a sea surface temperature (SST) pattern that resembles the corresponding El Niño-Southern Oscillation (ENSO) SST pattern. The corresponding atmospheric circulation pattern favors enhanced moisture advection over the Rhine catchment area during positive streamflow anomalies. During autumn, the streamflow variability follows a distribution similar to spring streamflow, but with a strong peak in the 30-60-yr band. Autumn streamflow anomalies are significantly related only with the North Atlantic SST anomalies. The atmospheric circulation pattern associated with high streamflow during autumn, which is more regional than the corresponding spring pattern, shows a deep low pressure system over the British Isles and the northwestern part of Europe and a shift southward of the Atlantic jet axis. The orientation of the axis of the Atlantic and African jets, as well as the advection of the moist air from the ocean, plays a crucial role in the variability of Rhine streamflow both in spring and autumn. [ABSTRACT FROM AUTHOR]

The predictability of Elbe streamflow anomalies during spring is examined using previous winter sea surface temperature (SST), temperature over land (TT), and precipitation (PP) anomalies. Based on running correlation analysis, the authors identify several regions where the spring streamflow anomalies are stable correlated with SST, TT, and PP anomalies from the previous winter. During the period 1902–71 the Elbe spring streamflow is stable correlated with previous winter PP anomalies from its catchment area, with TT anomalies from the Black Sea–Caspian Sea region, northwestern Europe, and northern Canada as well as with SST anomalies from the tropical Pacific, the Indian Ocean, and several regions of the North Pacific and the North Atlantic. An index based on winter SST, TT, and PP anomalies from these regions is highly significantly correlated with spring streamflow anomalies during this period. Based on SST, TT, and PP anomalies from stable correlated regions, a forecast scheme is developed and applied to predict spring streamflow anomalies during the last decades. The prediction based on this statistical scheme represents a marked improvement relative to the forecast based on teleconnection indices that are traditionally used for streamflow prediction. [ABSTRACT FROM AUTHOR]

Winter climate variations in midlatitude regions have far-reaching effects on both natural and human systems worldwide. However, most climate reconstructions focus on either annual or summer climate conditions. Here we present a stalagmite stable isotope record from Urşilor Cave (Romania) where the δ 18O values are controlled by winter temperature. Because of its East-Central Europe (ECE) location, the cave site is well suited to capture variations in precipitation and temperature in response to changes in the North Atlantic region. Present day precipitation and temperature in this region are controlled by two teleconnection patterns, the Arctic Oscillation (AO) and the East Atlantic (EA). By analyzing composite maps for four different scenarios of AO and EA phase, we suggest that between 5.6 and 5.2 ka the positive phases of AO and EA became increasingly dominant. This shift led to generally warmer winters in northern Europe, but drier conditions in southern Europe and the Levant. Considering the compound effect of AO and EA on the hydroclimate of ECE, our study highlights the importance of examining the combined impact of teleconnection patterns on climate proxies influenced by various forcing mechanisms. • δ 18O values in calcite from stalagmite P from Urşilor Cave, Romania, are controlled by winter climate conditions. • Winter precipitation and air temperature are rature are controlled by the Arctic Oscillation (AO) and EAtlantic (EA)s and EA teleconnection patterns, respectively. • Comparing European speleothem δ 18O records reflecting winter climate, reveals important regional differences. • Between 5.6 and 5.2 ka, the dominance of AO+ oscillation and EA+ pattern gradually increased. [ABSTRACT FROM AUTHOR]

Recent evidence shows that wind‐driven ocean currents, like the western boundary currents, are strongly affected by global warming. However, due to insufficient observations both on temporal and spatial scales, the impact of climate change on large‐scale ocean gyres is still not clear. Here, based on satellite observations of sea surface height and sea surface temperature, we find a consistent poleward shift of the major ocean gyres. Due to strong natural variability, most of the observed ocean gyre shifts are not statistically significant, implying that natural variations may contribute to the observed trends. However, climate model simulations forced with increasing greenhouse gases suggest that the observed shift is most likely to be a response of global warming. The displacement of ocean gyres, which is coupled with the poleward shift of extratropical atmospheric circulation, has broad impacts on ocean heat transport, regional sea level rise, and coastal ocean circulation. Plain Language Summary: Ocean circulation plays a vital role in regulating the weather and climate and supporting marine life. Therefore, it is important to understand whether and how it responds to global warming. However, the available observations are currently sparse and short in duration, making it difficult to track the dynamic changes of large‐scale ocean circulation. Here, we show for the first time, independent satellite observational evidence demonstrating that the large‐scale ocean gyres are moving poleward during the past four decades. Further analysis based on climate models and various other data sets reveal that the poleward shifting of the ocean gyre circulation is most likely to be a consequence of global warming, which so far has not been well recognized by the public and the scientific community. Key Points: Satellite observations show a consistent poleward shift of the major ocean gyres during the past four decadesDue to strong natural variability, most of the observed ocean gyre shifts are not statistically significantClimate model simulations suggest that the observed shift is most likely to be a response to global warming [ABSTRACT FROM AUTHOR]

The Carpathian Mountains host several ice caves that preserve a large variety of geochemical information on past climate and environmental changes. In such caves, ice forms in winter by the freezing on infiltrating water, the later accumulating during the rainy season, between early summer and late autumn (depending on site-specific conditions). Here, we present the first reconstruction of summer temperature during the last 1000 years based on the d18O and d2H values measured in Focul Viu Ice Cave (Western Carpathian Mountains, Romania).Focul Viu (FV) is short (107 m long) descending cave, located at ca. 1165 m above sea level on the windward (western) side of the mountains. A stratified ice block, with a volume of ~25000 m3 and ~20 m thickness, occupies the floor of the cave. In May 2016 we have extracted a 4.86 m long ice core from the cave glacier and measured the stable isotope composition of ice in order to derive information on past climate variability. The chronology of the core is based on six 14C measurements on organic matter embedded in the ice. Monitoring of the stable isotope composition of precipitation in the vicinity of the cave shows that most of the summer precipitation is originating in the Atlantic Ocean, ca. 30 % percent of it being locally recycled during heavy summer storms.We have found a near-perfect correlation between d18O (and d2H) of the ice core and instrumental summer temperatures measurements at three local stations, located west, north and east of the cave's location and have used this correlation to reconstruct summer temperature variability during the past ~1100 years. Our results show little centennial-scale variability during this period, suggesting that summer temperatures were likely similar between the Medieval Warm Period (MWP) and the Little Ice Age (LIA). In contrast, winter temperatures reconstructed from the nearby Scărișoara Ice Cave clearly show lower temperatures during the LIA, compared to the MWP, suggesting that the well-known temperature contrast between the two periods was a the result of winter climatic conditions. On a decadal scale, both during the MWP and the LIA, summer temperatures fluctuated with a periodicity of ~20/30 years, the minima and the maxima matching the fluctuations recorded by the Atlantic Ocean sea surface temperatures. Both the periodicity and the observed variability are similar to those of the Atlantic Multidecadal Oscillation, suggesting the d18O and d2H values in FV cave ice are recording climatic changes at hemispheric scale, thus being an important new proxy for both past temperatures and large-scale circulation changes. [ABSTRACT FROM AUTHOR]

The variability of harsh winters is considered to be a sensitive indicator for climate change. As such, in this study we present a reconstruction of 2000 years of harsh winters in the Eastern Europe based on historical documents. In total, 360 harsh winters were extracted for the period from AD 0 to 2000, and it's the longest one, on record, over this area. Our investigations spans over five distinct periods: the Roman Warm Period (RWP), the Dark Age (DA), the Medieval Warm Period (MWP), the Little Ice Age (LIA) and the Modern Period (MD), respectively. The results obtained show that the number years of harsh winters has decreased considerably during the RWP (AD 0 – 550) and have an occurrence rate < 0.1/year. During the Dark Age is observed a small increase in the number of harsh winter and the occurrence rate is found to be > 0.15/year. The period which covers the MWP (AD 850 – 1250) shows very small variation in number of severe winters and a slight decline in occurrence rate (~ 0.05 to 0.08/year). Overall, the biggest changes have been observed during the LIA (AD 1400 – 1850), when the occurrence rate of harsh winters show an increasing trend of ~ 0.75/year, due to a decreasing in the winter mean temperature over the eastern part of Europe. During the MD (AD 1900 – 2000) the number of harsh winters is decreasing (0.4 – 0.3/year) due to an increasing the winter mean temperature. Based on these information we can reconstruct 2000 years of winter air temperature variability over the Eastern Europe, with warming winters during the RWP, cool during the Dark Age, warm and dry during the MWP, and very cold winters during the LIA. In conclusion the harsh winters reconstruction can be used as a proxy indicator for the air temperature variability in winter, over the eastern part of Europe. [ABSTRACT FROM AUTHOR]

• We provide fundamentals of climate seasonality and break it down into external and internal forcing, and regional and local and modulating factors. • We present a transdisciplinary overview on how seasonality is recorded in, and extracted from, different palaeonvironmental archives. • We propose a framework for transparent communication of seasonality-related research across different communities. The role of seasonality is indisputable in climate and ecosystem dynamics. Seasonal temperature and precipitation variability are of vital importance for the availability of food, water, shelter, migration routes, and raw materials. Thus, understanding past climatic and environmental changes at seasonal scale is equally important for unearthing the history and for predicting the future of human societies under global warming scenarios. Alas, in palaeoenvironmental research, the term ' seasonality change ' is often used liberally without scrutiny or explanation as to which seasonal parameter has changed and how. Here we provide fundamentals of climate seasonality and break it down into external (insolation changes) and internal (atmospheric CO 2 concentration) forcing, and regional and local and modulating factors (continentality, altitude, large-scale atmospheric circulation patterns). Further, we present a brief overview of the archives with potentially annual/seasonal resolution (historical and instrumental records, marine invertebrate growth increments, stalagmites, tree rings, lake sediments, permafrost, cave ice, and ice cores) and discuss archive-specific challenges and opportunities, and how these limit or foster the use of specific archives in archaeological research. Next, we address the need for adequate data-quality checks, involving both archive-specific nature (e.g., limited sampling resolution or seasonal sampling bias) and analytical uncertainties. To this end, we present a broad spectrum of carefully selected statistical methods which can be applied to analyze annually- and seasonally-resolved time series. We close the manuscript by proposing a framework for transparent communication of seasonality-related research across different communities. [ABSTRACT FROM AUTHOR]