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Abstract AimPrevious work demonstrated the global variability of synchrony in tree growth within populations, that is, the covariance of the year‐to‐year variability in growth of individual neighbouring trees. However, there is a lack of knowledge about the causes of this variability and its trajectories through time. Here, we examine whether climate can explain variation in within‐population synchrony (WPS) across space but also through time and we develop models capable of explaining this variation. These models can be applied to the global tree cover under current and future climate change scenarios. LocationGlobal. Time period1901–2012. Major taxa studiedTrees. MethodsWe estimated WPS values from a global tree‐ring width database consisting of annual growth increment measurements from multiple trees at 3,579 sites. We used generalized linear mixed effects models to infer the drivers of WPS variability and temporal trends of global WPS. We then predicted WPS values across the global extent of tree cover. Finally, we applied our model to predict future WPS based on the RCP 8.5 (2045–2065 period) emission scenario. ResultsAreas with the highest WPS are characterized by a combination of environments with both high mean annual temperature (>10°C) and low precipitation (<300 mm). Average WPS across all temperate forests has decreased historically and will continue to decrease. Potential implications of these patterns include changes in forest dynamics, such as higher tree growth and productivity and an increase in carbon sequestration. In contrast, the WPS of tropical forests of Central and South America will increase in the near future owing to reduced annual precipitation. Main conclusionsClimate explains WPS variability in space and time. We suggest that WPS might have value as an integrative ecological measure of the level of environmental stress to which forests are subjected and therefore holds potential for diagnosing effects of global climate change on tree growth. 

Abstract Hydroclimate variability in tropical South America is strongly regulated by the South American Summer Monsoon (SASM). However, past precipitation changes are poorly constrained due to limited observations and high‐resolution paleoproxies. We found that summer precipitation and the El Niño‐Southern Oscillation (ENSO) variability are well registered in tree‐ring stable oxygen isotopes (δ¹⁸O_TR) ofPolylepis tarapacanain the Chilean and Bolivian Altiplano in the Central Andes (18–22°S, ∼4,500 m a.s.l.) with the northern forests having the strongest climate signal. More enrichedδ¹⁸O_TRvalues were found at the southern sites likely due to the increasing aridity toward the southwest of the Altiplano. The climate signal ofP. tarapacana δ¹⁸O_TRis the combined result of moisture transported from the Amazon Basin, modulated by the SASM, ENSO, and local evaporation, and emerges as a novel tree‐ring climate proxy for the southern tropical Andes. 

Abstract Large volcanic eruptions are one of the dominant perturbations to global and regional atmospheric temperatures on timescales of years to decades. Discrepancies remain, however, in the estimated magnitude and persistence of the surface temperature cooling caused by volcanic eruptions, as characterized by paleoclimatic proxies and climate models. We investigate these discrepancies in the context of large tropical eruptions over the Last Millennium using two state‐of‐the‐art data assimilation products, the Paleo Hydrodynamics Data Assimilation product (PHYDA) and the Last Millennium Reanalysis (LMR), and simulations from the National Center for Atmospheric Research Community Earth System Model‐Last Millennium Ensemble (NCAR CESM‐LME). We find that PHYDA and LMR estimate mean global and hemispheric cooling that is similar in magnitude and persistence once effects from eruptions occurring in short succession are removed. The estimates also compare well to Northern‐Hemisphere reconstructions based solely or partially on tree‐ring density, which have been proposed as the most accurate proxy estimates of surface cooling due to volcanism. All proxy‐based estimates also agree well with the magnitude of the mean cooling simulated by the CESM‐LME. Differences remain, however, in the spatial patterns of the temperature responses in the PHYDA, LMR, and the CESM‐LME. The duration of cooling anomalies also persists for several years longer in the PHYDA and LMR relative to the CESM‐LME. Our results demonstrate progress in resolving discrepancies between proxy‐ and model‐based estimates of temperature responses to volcanism, but also indicate these estimates must be further reconciled to better characterize the risks of future volcanic eruptions. 

Abstract The long‐term hydroclimatic variability in Santiago (Chile) was analysed by means of a new 481‐year (1536–2016 CE) tree‐ring reconstruction of the Standardized Precipitation Evapotranspiration Index (SPEI) of August, integrating the hydroclimatic conditions during the preceding 14 months. Results show a high frequency of extreme drought events in the late 20th and early 21st centuries, while the frequency of extreme wet events was higher in the 17th–18th centuries. The mid‐20th century represents a breaking point for the hydroclimatic history in the region, including some significant changes: (a) the interannual variability increased; (b) the wet events became less intense; (c) the extreme dry events became more frequent; and (d) the most intense dry event of the entire period was identified, coinciding with the so‐called Megadrought (2006–2016). A correlation analysis between the reconstructed SPEI and three climate indices (PDO, SOI and Niño3.4) was performed at monthly scale, considering different multi‐annual aggregations. The analysis shows diverse impacts on the hydroclimatic variability, with positive correlations between SPEI and PDO as well as Niño3.4, and negative correlations between SPEI and SOI. The most significant correlations were, overall, found at multi‐annual time scales (>7 years). Results help to better understand the current hydroclimatic changes (Megadrought) in a long‐term context. 

Abstract Theδ¹⁸O signal in ice cores from the Quelccaya Ice Cap (QIC), Peru, corresponds with and has been used to reconstruct Niño region sea surface temperatures (SSTs), but the physical mechanisms that tie El Niño–Southern Oscillation (ENSO)‐related equatorial Pacific SSTs to snowδ¹⁸O at 5,680 m in the Andes have not been fully established. We use a proxy system model to simulate how QIC snowδ¹⁸O varies by ENSO phase. The model accurately simulates higher and lowerδ¹⁸O values during El Niño and La Niña, respectively. We then explore the relative roles of ENSO forcing on different components of the forward model: (i) the seasonality and amount of snow gain and loss at the QIC, (ii) the initial water vaporδ¹⁸O values, and (iii) regional temperature. Most (more than two thirds) of the ENSO‐related variability in the QICδ¹⁸O can be accounted for by ENSO's influence on South American summer monsoon (SASM) activity and the resulting change in the initial water vapor isotopic composition. The initial water vaporδ¹⁸O values are affected by the strength of upstream convection associated with the SASM. Since convection over the Amazon is enhanced during La Niña, the water vapor over the western Amazon Basin—which serves as moisture source for snowfall on QIC—is characterized by more negativeδ¹⁸O values. In the forward model, higher initial water vaporδ‐values during El Niño yield higher snowδ¹⁸O at the QIC. Our results clarify that the ENSO‐related isotope signal on Quelccaya should not be interpreted as a simple temperature response. 

Abstract South American climate is influenced by both Atlantic multidecadal variability (AMV) and Pacific multidecadal variability (PMV). But how they jointly affect South American precipitation and surface air temperature is not well understood. Here we analyze composite anomalies to quantify their combined impacts using observations and reanalysis data. During an AMV warm (cold) phase, PMV-induced JJA precipitation anomalies are more positive (negative) over 0°-10°S and southeastern South America, but more negative (positive) over the northern Amazon and central Brazil. PMV-induced precipitation anomalies in DJF are more positive (negative) over Northeast Brazil and southeastern South America during the warm (cold) AMV phase, but more negative (positive) over the central Amazon Basin and central-eastern Brazil. PMV’s impact on AMV-induced precipitation anomalies shows similar dipole patterns. The precipitation changes result from perturbations of the local Hadley and Walker Circulations. In JJA, PMV- and AMV-induced temperature anomalies are more positive (negative) over entire South America when the other basin is in a warm (cold) phase, but in DJF temperature anomalies are more positive (negative) only over the central Andes and central-eastern Brazil and more negative (positive) over southeastern South America and Patagonia. Over central Brazil in JJA and southern Bolivia and northern Argentina in DJF, the temperature and precipitation anomalies are negatively correlated. Our results show that the influence of Pacific and Atlantic multidecadal variability need to be considered jointly, as significant departures from the mean AMV or PMV fingerprint can occur during a cold or warm phase of the other basin’s mode. 

Large tropical volcanic eruptions can affect the climate of many regions on Earth, yet it is uncertain how the largest eruptions over the past millennium may have altered Earth’s hydroclimate. Here, we analyze the global hydroclimatic response to all the tropical volcanic eruptions over the past millennium that were larger than the Mount Pinatubo eruption of 1991. Using the Paleo Hydrodynamics Data Assimilation product (PHYDA), we find that these large volcanic eruptions tended to produce dry conditions over tropical Africa, Central Asia and the Middle East and wet conditions over much of Oceania and the South American monsoon region. These anomalies are statistically significant, and they persisted for more than a decade in some regions. The persistence of the anomalies is associated with southward shifts in the Intertropical Convergence Zone and sea surface temperature changes in the Pacific and Atlantic oceans. We compare the PHYDA results with the stand-alone model response of the Community Earth System Model (CESM)-Last Millennium Ensemble. We find that the proxy-constrained PHYDA estimates are larger and more persistent than the responses simulated by CESM. Understanding which of these estimates is more realistic is critical for accurately characterizing the hydroclimate risks of future volcanic eruptions. 

Abstract Precipitation is one of the most difficult variables to estimate using large-scale predictors. Over South America (SA), this task is even more challenging, given the complex topography of the Andes. Empirical–statistical downscaling (ESD) models can be used for this purpose, but such models, applicable for all of SA, have not yet been developed. To address this issue, we construct an ESD model using multiple-linear-regression techniques for the period 1982–2016 that is based on large-scale circulation indices representing tropical Pacific Ocean, Atlantic Ocean, and South American climate variability, to estimate austral summer [December–February (DJF)] precipitation over SA. Statistical analyses show that the ESD model can reproduce observed precipitation anomalies over the tropical Andes (Ecuador, Colombia, Peru, and Bolivia), the eastern equatorial Amazon basin, and the central part of the western Argentinian Andes. On a smaller scale, the ESD model also shows good results over the Western Cordillera of the Peruvian Andes. The ESD model reproduces anomalously dry conditions over the eastern equatorial Amazon and the wet conditions over southeastern South America (SESA) during the three extreme El Niños: 1982/83, 1997/98, and 2015/16. However, it overestimates the observed intensities over SESA. For the central Peruvian Andes as a case study, results further show that the ESD model can correctly reproduce DJF precipitation anomalies over the entire Mantaro basin during the three extreme El Niño episodes. Moreover, multiple experiments with varying predictor combinations of the ESD model corroborate the hypothesis that the interaction between the South Atlantic convergence zone and the equatorial Atlantic Ocean provoked the Amazon drought in 2015/16.