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Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change 1 – 3 . Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain 4 . This leads to low confidence in regional projections, especially for precipitation, over the coming decades 5 , 6 . The chaotic nature of the climate system 7 – 9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models 10 , and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. Current models are too noisy to predict climate usefully on decadal timescales, but two-stage post-processing of model outputs greatly improves predictions of decadal variations in North Atlantic winter climate.

A series of stationary wave model (SWM) experiments are performed in which the boreal summer atmosphere is forced, over a number of locations in the continental United States, with an idealized diabatic heating anomaly that mimics the atmospheric heating associated with a dry land surface. For localized heating within a large portion of the continental interior, regardless of the specific location of this heating, the spatial pattern of the forced atmospheric circulation anomaly (in terms of 250-hPa eddy streamfunction) is largely the same: a high anomaly forms over west-central North America and a low anomaly forms to the east. In supplemental atmospheric general circulation model (AGCM) experiments, similar results are found; imposing soil moisture dryness in the AGCM in different locations within the U.S. interior tends to produce the aforementioned pattern, along with an associated near-surface warming and precipitation deficit in the center of the continent. The SWM-based and AGCM-based patterns generally agree with composites generated using reanalysis and precipitation gauge data. The AGCM experiments also suggest that dry anomalies imposed in the lower Mississippi River valley have remote surface impacts of particularly large spatial extent, and a region along the eastern half of the U.S.–Canadian border is particularly sensitive to dry anomalies in a number of remote areas. Overall, the SWM and AGCM experiments support the idea of a positive feedback loop operating over the continent: dry surface conditions in many interior locations lead to changes in atmospheric circulation that act to enhance further the overall dryness of the continental interior.

During recent decades Arctic sea ice variability and retreat during winter have largely been a result of variable ocean heat transport (OHT). Here we use the Community Earth System Model (CESM) large ensemble simulation to disentangle internally and externally forced winter Arctic sea ice variability, and to assess to what extent future winter sea ice variability and trends are driven by Atlantic heat transport. We find that OHT into the Barents Sea has been, and is at present, a major source of internal Arctic winter sea ice variability and predictability. In a warming world (RCP8.5), OHT remains a good predictor of winter sea ice variability, although the relation weakens as the sea ice retreats beyond the Barents Sea. Warm Atlantic water gradually spreads downstream from the Barents Sea and farther into the Arctic Ocean, leading to a reduced sea ice cover and substantial changes in sea ice thickness. The future long-term increase in Atlantic heat transport is carried by warmer water as the current itself is found to weaken. The externally forced weakening of the Atlantic inflow to the Barents Sea is in contrast to a strengthening of the Nordic Seas circulation, and is thus not directly related to a slowdown of the Atlantic meridional overturning circulation (AMOC). The weakened Barents Sea inflow rather results from regional atmospheric circulation trends acting to change the relative strength of Atlantic water pathways into the Arctic. Internal OHT variability is associated with both upstream ocean circulation changes, including AMOC, and large-scale atmospheric circulation anomalies reminiscent of the Arctic Oscillation.

In recent decades, an increasing persistence of atmospheric circulation patterns has been observed. In the course of the associated long-lasting anticyclonic summer circulations, heatwaves and drought spells often coincide, leading to so-called hotter droughts. Previous hotter droughts caused a decrease in agricultural yields and an increase in tree mortality. Thus, they had a remarkable effect on carbon budgets and negative economic impacts. Consequently, a quantification of ecosystem responses to hotter droughts and a better understanding of the underlying mechanisms are crucial. In this context, the European hotter drought of the year 2018 may be considered a key event. As a first step towards the quantification of its causes and consequences, we here assess anomalies of atmospheric circulation patterns, maximum temperature, and climatic water balance as potential drivers of ecosystem responses which are quantified by remote sensing using the MODIS vegetation indices (VIs) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). To place the drought of 2018 within a climatological context, we compare its climatic features and remotely sensed ecosystem response with the extreme hot drought of 2003. The year 2018 was characterized by a climatic dipole, featuring extremely hot and dry weather conditions north of the Alps but comparably cool and moist conditions across large parts of the Mediterranean. Analysing the ecosystem response of five dominant land cover classes, we found significant positive effects of climatic water balance on ecosystem VI response. Negative drought impacts appeared to affect an area 1.5 times larger and to be significantly stronger in July 2018 compared to August 2003, i.e. at the respective peak of drought. Moreover, we found a significantly higher sensitivity of pastures and arable land to climatic water balance compared to forests in both years. We explain the stronger coupling and higher sensitivity of ecosystem response in 2018 by the prevailing climatic dipole: while the generally water-limited ecosystems of the Mediterranean experienced above-average climatic water balance, the less drought-adapted ecosystems of central and northern Europe experienced a record hot drought. In conclusion, this study quantifies the drought of 2018 as a yet unprecedented event, outlines hotspots of drought-impacted areas in 2018 which should be given particular attention in follow-up studies, and provides valuable insights into the heterogeneous responses of the dominant European ecosystems to hotter drought.

Annual precipitation anomalies over eastern China are characterized by a north–south dipole pattern, referred to as the “southern flooding and northern drought” pattern (SF/ND), fluctuating on decadal time scales. Previous research has suggested possible links with oceanic forcing, but the underlying physical mechanisms by which sea surface temperature (SST) variability impacts the dipole pattern remains unclear. Idealized atmospheric general circulation model experiments conducted by the U.S. CLIVAR Drought Working Group are used to investigate the role of historical SST anomalies associated with Pacific El Niño–Southern Oscillation (ENSO)-like and the Atlantic multidecadal oscillation (AMO) patterns in this dipole pattern. The results show that the Pacific SST pattern plays a dominant role in driving the decadal variability of this dipole pattern and the associated atmospheric circulation anomalies, whereas the Atlantic SST pattern contributes to a much lesser degree. The direct atmospheric response to the Pacific SST pattern is a large-scale cyclonic or anticyclonic circulation anomaly in the lower troposphere occupying the entire northern North Pacific. During the warm phase of the Pacific SST pattern, it is cyclonic with northwesterly wind anomalies over northern China pushing the monsoon front to the south and consequently SF/ND. During the cold phase of the Pacific SST pattern, the circulation anomaly reverses with southeasterly winds over northern China allowing the monsoon front and the associated rainband to migrate northward, resulting in southern drought and northern flooding. The Atlantic SST pattern plays a supplementary role, enhancing the dipole pattern when the Pacific SST and Atlantic SST patterns are in opposite phases and weakening it when the phases are the same.