@article{SmithTraxlBoers2022, author = {Smith, Taylor and Traxl, Dominik and Boers, Niklas}, title = {Empirical evidence for recent global shifts in vegetation resilience}, series = {Nature climate change}, volume = {12}, journal = {Nature climate change}, number = {5}, publisher = {Nature Publ. Group}, address = {London}, issn = {1758-678X}, doi = {10.1038/s41558-022-01352-2}, pages = {477 -- 484}, year = {2022}, abstract = {The authors demonstrate that a vegetation system's ability to recover from disturbances-its resilience-can be estimated from its natural variability. Global patterns of resilience loss and gains since the early 1990s reveal shifts towards widespread resilience loss since the early 2000s. The character and health of ecosystems worldwide is tightly coupled to changes in Earth's climate. Theory suggests that ecosystem resilience-the ability of ecosystems to resist and recover from external shocks such as droughts and fires-can be inferred from their natural variability. Here, we quantify vegetation resilience globally with complementary metrics based on two independent long-term satellite records. We first empirically confirm that the recovery rates from large perturbations can be closely approximated from internal vegetation variability across vegetation types and climate zones. On the basis of this empirical relationship, we quantify vegetation resilience continuously and globally from 1992 to 2017. Long-term vegetation resilience trends are spatially heterogeneous, with overall increasing resilience in the tropics and decreasing resilience at higher latitudes. Shorter-term trends, however, reveal a marked shift towards a global decline in vegetation resilience since the early 2000s, particularly in the equatorial rainforest belt.}, language = {en} } @article{SmithZottaBoultonetal.2023, author = {Smith, Taylor and Zotta, Ruxandra-Maria and Boulton, Chris A. and Lenton, Timothy M. and Dorigo, Wouter and Boers, Niklas}, title = {Reliability of resilience estimation based on multi-instrument time series}, series = {Earth System Dynamics}, volume = {14}, journal = {Earth System Dynamics}, publisher = {Copernicus Publications}, address = {G{\"o}ttingen}, issn = {2190-4987}, doi = {10.5194/esd-14-173-2023}, pages = {173 -- 183}, year = {2023}, abstract = {Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process - rather than actual changes in the dynamical properties of the system - is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.}, language = {en} } @article{GoswamiBoersRheinwaltetal.2018, author = {Goswami, Bedartha and Boers, Niklas and Rheinwalt, Aljoscha and Marwan, Norbert and Heitzig, Jobst and Breitenbach, Sebastian Franz Martin and Kurths, J{\"u}rgen}, title = {Abrupt transitions in time series with uncertainties}, series = {Nature Communications}, volume = {9}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-017-02456-6}, pages = {10}, year = {2018}, abstract = {Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Ni{\~n}o-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.}, language = {en} } @article{CiemerRehmKurthsetal.2020, author = {Ciemer, Catrin and Rehm, Lars and Kurths, J{\"u}rgen and Donner, Reik Volker and Winkelmann, Ricarda and Boers, Niklas}, title = {An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures}, series = {Environmental Research Letters}, volume = {15}, journal = {Environmental Research Letters}, number = {9}, publisher = {IOP - Institute of Physics Publishing}, address = {Bristol}, pages = {10}, year = {2020}, abstract = {Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.}, language = {en} } @article{BoersGoswamiRheinwaltetal.2019, author = {Boers, Niklas and Goswami, Bedartha and Rheinwalt, Aljoscha and Bookhagen, Bodo and Hoskins, Brian and Kurths, J{\"u}rgen}, title = {Complex networks reveal global pattern of extreme-rainfall teleconnections}, series = {Nature : the international weekly journal of science}, volume = {566}, journal = {Nature : the international weekly journal of science}, number = {7744}, publisher = {Nature Publ. Group}, address = {London}, issn = {0028-0836}, doi = {10.1038/s41586-018-0872-x}, pages = {373 -- 377}, year = {2019}, abstract = {Climatic observables are often correlated across long spatial distances, and extreme events, such as heatwaves or floods, are typically assumed to be related to such teleconnections(1,2). Revealing atmospheric teleconnection patterns and understanding their underlying mechanisms is of great importance for weather forecasting in general and extreme-event prediction in particular(3,4), especially considering that the characteristics of extreme events have been suggested to change under ongoing anthropogenic climate change(5-8). Here we reveal the global coupling pattern of extreme-rainfall events by applying complex-network methodology to high-resolution satellite data and introducing a technique that corrects for multiple-comparison bias in functional networks. We find that the distance distribution of significant connections (P < 0.005) around the globe decays according to a power law up to distances of about 2,500 kilometres. For longer distances, the probability of significant connections is much higher than expected from the scaling of the power law. We attribute the shorter, power-law-distributed connections to regional weather systems. The longer, super-power-law-distributed connections form a global rainfall teleconnection pattern that is probably controlled by upper-level Rossby waves. We show that extreme-rainfall events in the monsoon systems of south-central Asia, east Asia and Africa are significantly synchronized. Moreover, we uncover concise links between south-central Asia and the European and North American extratropics, as well as the Southern Hemisphere extratropics. Analysis of the atmospheric conditions that lead to these teleconnections confirms Rossby waves as the physical mechanism underlying these global teleconnection patterns and emphasizes their crucial role in dynamical tropical-extratropical couplings. Our results provide insights into the function of Rossby waves in creating stable, global-scale dependencies of extreme-rainfall events, and into the potential predictability of associated natural hazards.}, language = {en} } @article{CiemerBoersHirotaetal.2019, author = {Ciemer, Catrin and Boers, Niklas and Hirota, Marina and Kurths, J{\"u}rgen and M{\"u}ller-Hansen, Finn and Oliveira, Rafael S. and Winkelmann, Ricarda}, title = {Higher resilience to climatic disturbances in tropical vegetation exposed to more variable rainfall}, series = {Nature geoscience}, volume = {12}, journal = {Nature geoscience}, number = {3}, publisher = {Nature Publ. Group}, address = {New York}, issn = {1752-0894}, doi = {10.1038/s41561-019-0312-z}, pages = {174 -- 179}, year = {2019}, abstract = {With ongoing global warming, the amount and frequency of precipitation in the tropics is projected to change substantially. While it has been shown that tropical forests and savannahs are sustained within the same intermediate mean annual precipitation range, the mechanisms that lead to the resilience of these ecosystems are still not fully understood. In particular, the long-term impact of rainfall variability on resilience is as yet unclear. Here we present observational evidence that both tropical forest and savannah exposed to a higher rainfall variability-in particular on interannual scales-during their long-term past are overall more resilient against climatic disturbances. Based on precipitation and tree cover data in the Brazilian Amazon basin, we constructed potential landscapes that enable us to systematically measure the resilience of the different ecosystems. Additionally, we infer that shifts from forest to savannah due to decreasing precipitation in the future are more likely to occur in regions with a precursory lower rainfall variability. Long-term rainfall variability thus needs to be taken into account in resilience analyses and projections of vegetation response to climate change.}, language = {en} } @article{BoersGoswamiGhil2017, author = {Boers, Niklas and Goswami, Bedartha and Ghil, Michael}, title = {A complete representation of uncertainties in layer-counted paleoclimatic archives}, series = {Climate of the past : an interactive open access journal of the European Geosciences Union}, volume = {13}, journal = {Climate of the past : an interactive open access journal of the European Geosciences Union}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1814-9324}, doi = {10.5194/cp-13-1169-2017}, pages = {12}, year = {2017}, abstract = {Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5-52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval.}, language = {en} } @article{BoersBookhagenMarwanetal.2016, author = {Boers, Niklas and Bookhagen, Bodo and Marwan, Norbert and Kurths, J{\"u}rgen}, title = {Spatiotemporal characteristics and synchronization of extreme rainfall in South America with focus on the Andes Mountain range}, series = {Climate dynamics : observational, theoretical and computational research on the climate system}, volume = {46}, journal = {Climate dynamics : observational, theoretical and computational research on the climate system}, publisher = {Springer}, address = {New York}, issn = {0930-7575}, doi = {10.1007/s00382-015-2601-6}, pages = {601 -- 617}, year = {2016}, abstract = {The South American Andes are frequently exposed to intense rainfall events with varying moisture sources and precipitation-forming processes. In this study, we assess the spatiotemporal characteristics and geographical origins of rainfall over the South American continent. Using high-spatiotemporal resolution satellite data (TRMM 3B42 V7), we define four different types of rainfall events based on their (1) high magnitude, (2) long temporal extent, (3) large spatial extent, and (4) high magnitude, long temporal and large spatial extent combined. In a first step, we analyze the spatiotemporal characteristics of these events over the entire South American continent and integrate their impact for the main Andean hydrologic catchments. Our results indicate that events of type 1 make the overall highest contributions to total seasonal rainfall (up to 50\%). However, each consecutive episode of the infrequent events of type 4 still accounts for up to 20\% of total seasonal rainfall in the subtropical Argentinean plains. In a second step, we employ complex network theory to unravel possibly non-linear and long-ranged climatic linkages for these four event types on the high-elevation Altiplano-Puna Plateau as well as in the main river catchments along the foothills of the Andes. Our results suggest that one to two particularly large squall lines per season, originating from northern Brazil, indirectly trigger large, long-lasting thunderstorms on the Altiplano Plateau. In general, we observe that extreme rainfall in the catchments north of approximately 20 degrees S typically originates from the Amazon Basin, while extreme rainfall at the eastern Andean foothills south of 20 degrees S and the Puna Plateau originates from southeastern South America.}, language = {en} } @article{RheinwaltBoersMarwanetal.2016, author = {Rheinwalt, Aljoscha and Boers, Niklas and Marwan, Norbert and Kurths, J{\"u}rgen and Hoffmann, Peter and Gerstengarbe, Friedrich-Wilhelm and Werner, Peter}, title = {Non-linear time series analysis of precipitation events using regional climate networks for Germany}, series = {Climate dynamics : observational, theoretical and computational research on the climate system}, volume = {46}, journal = {Climate dynamics : observational, theoretical and computational research on the climate system}, publisher = {Springer}, address = {New York}, issn = {0930-7575}, doi = {10.1007/s00382-015-2632-z}, pages = {1065 -- 1074}, year = {2016}, abstract = {Synchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We propose a novel standardization of this number that results in synchronization scores which are not biased by the number of events in the respective time series. Additionally, we introduce a new version of the network measure directionality that measures the spatial directionality of weighted links by also taking account of the effects of the spatial embedding of the network. This measure provides an estimate of heavy precipitation isochrones by pointing out directions along which rainfall events synchronize. We propose a climatological interpretation of this measure in terms of propagating fronts or event traces and confirm it for Germany by comparing our results to known atmospheric circulation patterns.}, language = {en} } @article{TraxlBoersRheinwaltetal.2016, author = {Traxl, Dominik and Boers, Niklas and Rheinwalt, Aljoscha and Goswami, Bedartha and Kurths, J{\"u}rgen}, title = {The size distribution of spatiotemporal extreme rainfall clusters around the globe}, series = {Geophysical research letters}, volume = {43}, journal = {Geophysical research letters}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1002/2016GL070692}, pages = {9939 -- 9947}, year = {2016}, abstract = {The scaling behavior of rainfall has been extensively studied both in terms of event magnitudes and in terms of spatial extents of the events. Different heavy-tailed distributions have been proposed as candidates for both instances, but statistically rigorous treatments are rare. Here we combine the domains of event magnitudes and event area sizes by a spatiotemporal integration of 3-hourly rain rates corresponding to extreme events derived from the quasi-global high-resolution rainfall product Tropical Rainfall Measuring Mission 3B42. A maximum likelihood evaluation reveals that the distribution of spatiotemporally integrated extreme rainfall cluster sizes over the oceans is best described by a truncated power law, calling into question previous statements about scale-free distributions. The observed subpower law behavior of the distribution's tail is evaluated with a simple generative model, which indicates that the exponential truncation of an otherwise scale-free spatiotemporal cluster size distribution over the oceans could be explained by the existence of land masses on the globe.}, language = {en} } @article{BoersBookhagenMarengoetal.2015, author = {Boers, Niklas and Bookhagen, Bodo and Marengo, Jose and Marwan, Norbert and von Storch, Jin-Song and Kurths, J{\"u}rgen}, title = {Extreme Rainfall of the South American Monsoon System: A Dataset Comparison Using Complex Networks}, series = {Journal of climate}, volume = {28}, journal = {Journal of climate}, number = {3}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {0894-8755}, doi = {10.1175/JCLI-D-14-00340.1}, pages = {1031 -- 1056}, year = {2015}, abstract = {In this study, the authors compare six different rainfall datasets for South America with a focus on their representation of extreme rainfall during the monsoon season (December February): the gauge-calibrated TRMM 3B42 V7 satellite product; the near-real-time TRMM 3B42 V7 RT, the GPCP 1 degrees daily (1DD) V1.2 satellite gauge combination product, the Interim ECMWF Re-Analysis (ERA-Interim) product; output of a high-spatial-resolution run of the ECHAM6 global circulation model; and output of the regional climate model Eta. For the latter three, this study can be understood as a model evaluation. In addition to statistical values of local rainfall distributions, the authors focus on the spatial characteristics of extreme rainfall covariability. Since traditional approaches based on principal component analysis are not applicable in the context of extreme events, they apply and further develop methods based on complex network theory. This way, the authors uncover substantial differences in extreme rainfall patterns between the different datasets: (i) The three model-derived datasets yield very different results than the satellite gauge combinations regarding the main climatological propagation pathways of extreme events as well as the main convergence zones of the monsoon system. (ii) Large discrepancies are found for the development of mesoscale convective systems in southeastern South America. (iii) Both TRMM datasets and ECHAM6 indicate a linkage of extreme rainfall events between the central Amazon basin and the eastern slopes of the central Andes, but this pattern is not reproduced by the remaining datasets. The authors' study suggests that none of the three model-derived datasets adequately captures extreme rainfall patterns in South America.}, language = {en} } @article{BoersBarbosaBookhagenetal.2015, author = {Boers, Niklas and Barbosa, Henrique M. J. and Bookhagen, Bodo and Marengo, Jose A. and Marwan, Norbert and Kurths, J{\"u}rgen}, title = {Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes}, series = {Journal of climate}, volume = {28}, journal = {Journal of climate}, number = {19}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {0894-8755}, doi = {10.1175/JCLI-D-15-0137.1}, pages = {7641 -- 7658}, year = {2015}, abstract = {Based on high-spatiotemporal-resolution data, the authors perform a climatological study of strong rainfall events propagating from southeastern South America to the eastern slopes of the central Andes during the monsoon season. These events account for up to 70\% of total seasonal rainfall in these areas. They are of societal relevance because of associated natural hazards in the form of floods and landslides, and they form an intriguing climatic phenomenon, because they propagate against the direction of the low-level moisture flow from the tropics. The responsible synoptic mechanism is analyzed using suitable composites of the relevant atmospheric variables with high temporal resolution. The results suggest that the low-level inflow from the tropics, while important for maintaining sufficient moisture in the area of rainfall, does not initiate the formation of rainfall clusters. Instead, alternating low and high pressure anomalies in midlatitudes, which are associated with an eastward-moving Rossby wave train, in combination with the northwestern Argentinean low, create favorable pressure and wind conditions for frontogenesis and subsequent precipitation events propagating from southeastern South America toward the Bolivian Andes.}, language = {en} }