TY - JOUR A1 - Boers, Niklas A1 - Goswami, Bedartha A1 - Ghil, Michael T1 - A complete representation of uncertainties in layer-counted paleoclimatic archives JF - Climate of the past : an interactive open access journal of the European Geosciences Union N2 - 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. Y1 - 2017 U6 - https://doi.org/10.5194/cp-13-1169-2017 SN - 1814-9324 SN - 1814-9332 VL - 13 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Boers, Niklas A1 - Goswami, Bedartha A1 - Ghil, Michael T1 - A complete representation of uncertainties in layer-counted paleoclimatic archives T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 641 KW - Greenland ice-core KW - late-glacial chronology KW - high-resolution record KW - Lake Suigetsu KW - proxy records KW - age models KW - climate KW - events KW - Japan KW - period Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418030 SN - 1866-8372 IS - 641 ER - TY - GEN A1 - Goswami, Bedartha A1 - Boers, Niklas A1 - Rheinwalt, Aljoscha A1 - Marwan, Norbert A1 - Heitzig, Jobst A1 - Breitenbach, Sebastian Franz Martin A1 - Kurths, Jürgen T1 - Abrupt transitions in time series with uncertainties T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - 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 Nino-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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 576 KW - North-Atlantic climate KW - Indian monsoon KW - Holocene KW - teleconnections KW - variability KW - periods KW - records Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-423111 SN - 1866-8372 IS - 576 ER - TY - JOUR A1 - Goswami, Bedartha A1 - Boers, Niklas A1 - Rheinwalt, Aljoscha A1 - Marwan, Norbert A1 - Heitzig, Jobst A1 - Breitenbach, Sebastian Franz Martin A1 - Kurths, Jürgen T1 - Abrupt transitions in time series with uncertainties JF - Nature Communications N2 - 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 Niño-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. Y1 - 2018 U6 - https://doi.org/10.1038/s41467-017-02456-6 SN - 2041-1723 VL - 9 PB - Nature Publ. Group CY - London ER - TY - GEN A1 - Ciemer, Catrin A1 - Rehm, Lars A1 - Kurths, Jürgen A1 - Donner, Reik Volker A1 - Winkelmann, Ricarda A1 - Boers, Niklas T1 - An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1207 KW - complex networks KW - droughts KW - prediction KW - Amazon rainforest Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-525863 SN - 1866-8372 IS - 9 ER - TY - JOUR A1 - Ciemer, Catrin A1 - Rehm, Lars A1 - Kurths, Jürgen A1 - Donner, Reik Volker A1 - Winkelmann, Ricarda A1 - Boers, Niklas T1 - An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures JF - Environmental Research Letters N2 - 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. KW - complex networks KW - droughts KW - prediction KW - Amazon rainforest Y1 - 2019 VL - 15 IS - 9 PB - IOP - Institute of Physics Publishing CY - Bristol ER - TY - JOUR A1 - Boers, Niklas A1 - Goswami, Bedartha A1 - Rheinwalt, Aljoscha A1 - Bookhagen, Bodo A1 - Hoskins, Brian A1 - Kurths, Jürgen T1 - Complex networks reveal global pattern of extreme-rainfall teleconnections JF - Nature : the international weekly journal of science N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1038/s41586-018-0872-x SN - 0028-0836 SN - 1476-4687 VL - 566 IS - 7744 SP - 373 EP - 377 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Smith, Taylor A1 - Traxl, Dominik A1 - Boers, Niklas T1 - Empirical evidence for recent global shifts in vegetation resilience JF - Nature climate change N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1038/s41558-022-01352-2 SN - 1758-678X SN - 1758-6798 VL - 12 IS - 5 SP - 477 EP - 484 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Boers, Niklas A1 - Bookhagen, Bodo A1 - Marengo, Jose A1 - Marwan, Norbert A1 - von Storch, Jin-Song A1 - Kurths, Jürgen T1 - Extreme Rainfall of the South American Monsoon System: A Dataset Comparison Using Complex Networks JF - Journal of climate N2 - 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. Y1 - 2015 U6 - https://doi.org/10.1175/JCLI-D-14-00340.1 SN - 0894-8755 SN - 1520-0442 VL - 28 IS - 3 SP - 1031 EP - 1056 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Ciemer, Catrin A1 - Boers, Niklas A1 - Hirota, Marina A1 - Kurths, Jürgen A1 - Müller-Hansen, Finn A1 - Oliveira, Rafael S. A1 - Winkelmann, Ricarda T1 - Higher resilience to climatic disturbances in tropical vegetation exposed to more variable rainfall JF - Nature geoscience N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1038/s41561-019-0312-z SN - 1752-0894 SN - 1752-0908 VL - 12 IS - 3 SP - 174 EP - 179 PB - Nature Publ. Group CY - New York ER - TY - JOUR A1 - Rheinwalt, Aljoscha A1 - Boers, Niklas A1 - Marwan, Norbert A1 - Kurths, Jürgen A1 - Hoffmann, Peter A1 - Gerstengarbe, Friedrich-Wilhelm A1 - Werner, Peter T1 - Non-linear time series analysis of precipitation events using regional climate networks for Germany JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - 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. KW - Rainfall KW - Complex networks KW - Precipitation events KW - Anisotropy KW - Dominant link directions KW - Isochrones KW - Event synchronization Y1 - 2016 U6 - https://doi.org/10.1007/s00382-015-2632-z SN - 0930-7575 SN - 1432-0894 VL - 46 SP - 1065 EP - 1074 PB - Springer CY - New York ER - TY - JOUR A1 - Boers, Niklas A1 - Barbosa, Henrique M. J. A1 - Bookhagen, Bodo A1 - Marengo, Jose A. A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes JF - Journal of climate N2 - 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. KW - Cold air surges KW - Extreme events KW - Precipitation KW - Subtropical cyclones KW - Convective storms KW - Mesoscale systems Y1 - 2015 U6 - https://doi.org/10.1175/JCLI-D-15-0137.1 SN - 0894-8755 SN - 1520-0442 VL - 28 IS - 19 SP - 7641 EP - 7658 PB - American Meteorological Soc. CY - Boston ER - TY - GEN A1 - Smith, Taylor A1 - Zotta, Ruxandra-Maria A1 - Boulton, Chris A. A1 - Lenton, Timothy M. A1 - Dorigo, Wouter A1 - Boers, Niklas T1 - Reliability of resilience estimation based on multi-instrument time series T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1322 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589120 SN - 1866-8372 IS - 1322 SP - 173 EP - 183 ER - TY - JOUR A1 - Smith, Taylor A1 - Zotta, Ruxandra-Maria A1 - Boulton, Chris A. A1 - Lenton, Timothy M. A1 - Dorigo, Wouter A1 - Boers, Niklas T1 - Reliability of resilience estimation based on multi-instrument time series JF - Earth System Dynamics N2 - 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. Y1 - 2023 U6 - https://doi.org/10.5194/esd-14-173-2023 SN - 2190-4987 VL - 14 SP - 173 EP - 183 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Boers, Niklas A1 - Bookhagen, Bodo A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Spatiotemporal characteristics and synchronization of extreme rainfall in South America with focus on the Andes Mountain range JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - 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. KW - Extreme rainfall KW - Synchronization KW - Complex networks KW - South American monsoon system Y1 - 2016 U6 - https://doi.org/10.1007/s00382-015-2601-6 SN - 0930-7575 SN - 1432-0894 VL - 46 SP - 601 EP - 617 PB - Springer CY - New York ER - TY - JOUR A1 - Traxl, Dominik A1 - Boers, Niklas A1 - Rheinwalt, Aljoscha A1 - Goswami, Bedartha A1 - Kurths, Jürgen T1 - The size distribution of spatiotemporal extreme rainfall clusters around the globe JF - Geophysical research letters N2 - 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. Y1 - 2016 U6 - https://doi.org/10.1002/2016GL070692 SN - 0094-8276 SN - 1944-8007 VL - 43 SP - 9939 EP - 9947 PB - American Geophysical Union CY - Washington ER -