TY - JOUR A1 - Weldeab, Syee A1 - Rühlemann, Carsten A1 - Bookhagen, Bodo A1 - Pausata, Francesco S. R. A1 - Perez-Lua, Fabiola M. T1 - Enhanced Himalayan glacial melting during YD and H1 recorded in the Northern Bay of Bengal JF - Geochemistry, geophysics, geosystems N2 - Ocean-land thermal feedback mechanisms in the Indian Summer Monsoon (ISM) domain are an important but not well understood component of regional climate dynamics. Here we present a O-18 record analyzed in the mixed-layer dwelling planktonic foraminifer Globigerinoides ruber (sensu stricto) from the northernmost Bay of Bengal (BoB). The O-18 time series provides a spatially integrated measure of monsoonal precipitation and Himalayan meltwater runoff into the northern BoB and reveals two brief episodes of anomalously low O-18 values between 16.30.4 and 160.5 and 12.60.4 and 12.30.4 thousand years before present. The timing of these events is centered at Heinrich event 1 and the Younger Dryas, well-known phases of weak northern hemisphere monsoon systems. Numerical climate model experiments, simulating Heinrich event-like conditions, suggest a surface warming over the monsoon-dominated Himalaya and foreland in response to ISM weakening. Corroborating the simulation results, our analysis of published moraine exposure ages in the monsoon-dominated Himalaya indicates enhanced glacier retreats that, considering age model uncertainties, coincide and overlap with the episodes of anomalously low O-18 values in the northernmost BoB. Our climate proxy and simulation results provide insights into past regional climate dynamics, suggesting reduced cloud cover, increased solar radiation, and air warming of the Himalaya and foreland areas and, as a result, glacier mass losses in response to weakened ISM. Plain Language Summary Indian Summer Monsoon rainfall and Himalayan glacier/snow melts constitute the main water source for the densely populated Indian subcontinent. Better understanding of how future climate changes will affect the monsoon rainfall and Himalayan glaciers requires a long climate record. In this study, we create a 13,000-year-long climate record that allows us to better understand the response of Indian Summer Monsoon rainfall and Himalayan glaciers to past climate changes. The focus of our study is the time window between 9,000 and 22,000 years ago, an episode where the global climate experienced large and rapid changes. Our sediment record from the northern Bay of Bengal and climate change simulation indicate that during episodes of weak monsoon, the melting of the Himalayan glaciers increases substantially significantly. This is because the weakening of the monsoon results in less cloud cover and, as a result, the surface receives more sunlight and causes glacier melting. KW - Bay of Bengal KW - Indian Summer Monsoon KW - Himalayan glacier meltwater KW - runoff KW - Younger Dryas KW - Heinrich event 1 Y1 - 2019 U6 - https://doi.org/10.1029/2018GC008065 SN - 1525-2027 VL - 20 IS - 5 SP - 2449 EP - 2461 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Merchel, Silke A1 - Gärtner, Andreas A1 - Beutner, Sabrina A1 - Bookhagen, Bodo A1 - Chabilan, Amelie T1 - Attempts to understand potential deficiencies in chemical procedures for AMS: Cleaning and dissolving quartz for Be-10 and Al-26 analysis JF - Nuclear instruments & methods in physics research : a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics, Section B, Beam interactions with materials and atoms N2 - The purity of the analysed samples (e.g. quartz) with respect to chemical composition and radionuclide contamination is essential for geomorphologic applications using so-called terrestrial cosmogenic nuclides (TCNs). To guarantee this, numerous cleaning and dissolution procedures have been developed. At the DREsden Accelerator Mass Spectrometry (DREAMS) facility, we also work on enhancing the chemical quartz-enrichment methodology from bulk rock and dissolution of quartz. Repeated exposure of the bulk material to acid mixtures (HCl/H2SiF6) at room temperature for cleaning and its monitoring by optical microscopy works for most quartz-rich samples. The quartz dissolution in HF under rather mild conditions (at room temperature on a shaker-table) has the advantage to leave difficult-to-dissolve minerals (e.g., tourmaline, zircon, rutile, sillimanite, kyanite, chromite, corundum), not separated by other physical methods before, as residue. Our comparison with a high-temperature dissolution method (in a microwave) indicates an additional amount of interfering elements, such as in average about 3 mg of Ti, more than 7 mg of Al, and about 22 mu g of Be (for 50 g SiO2), is added to the sample, hence showing the superiority of our mild method. This way, we reduce problems for chemistry and AMS, but also ensure better comparability to production rates of cleaner stoichiometric quartz from calibration sites. KW - Accelerator mass spectrometry KW - In-situ KW - Terrestrial cosmogenic nuclide KW - Residue KW - Quartz Y1 - 2019 U6 - https://doi.org/10.1016/j.nimb.2019.02.007 SN - 0168-583X SN - 1872-9584 VL - 455 SP - 293 EP - 299 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Clubb, Fiona J. A1 - Bookhagen, Bodo A1 - Rheinwalt, Aljoscha T1 - Clustering river profiles to classify geomorphic domains JF - Journal of geophysical research : Earth surface N2 - The structure and organization of river networks has been used for decades to investigate the influence of climate and tectonics on landscapes. The majority of these studies either analyze rivers in profile view by extracting channel steepness or calculate planform metrics such as drainage density. However, these techniques rely on the assumption of homogeneity: that intrinsic and external factors are spatially or temporally invariant over the measured profile. This assumption is violated for the majority of Earth's landscapes, where variations in uplift rate, rock strength, climate, and geomorphic process are almost ubiquitous. We propose a method for classifying river profiles to identify landscape regions with similar characteristics by adapting hierarchical clustering algorithms developed for time series data. We first test our clustering on two landscape evolution scenarios and find that we can successfully cluster regions with different erodibility and detect the transient response to sudden base level fall. We then test our method in two real landscapes: first in Bitterroot National Forest, Idaho, where we demonstrate that our method can detect transient incision waves and the topographic signature of fluvial and debris flow process regimes; and second, on Santa Cruz Island, California, where our technique identifies spatial patterns in lithology not detectable through normalized channel steepness analysis. By calculating channel steepness separately for each cluster, our method allows the extraction of more reliable steepness metrics than if calculated for the landscape as a whole. These examples demonstrate the method's ability to disentangle fluvial morphology in complex lithological and tectonic settings. KW - clustering KW - river networks KW - topographic analysis KW - landscape evolution modeling Y1 - 2019 U6 - https://doi.org/10.1029/2019JF005025 SN - 2169-9003 SN - 2169-9011 VL - 124 IS - 6 SP - 1417 EP - 1439 PB - American Geophysical Union CY - Hoboken ER - TY - JOUR A1 - Rheinwahlt, Aljoscha A1 - Goswami, Bedartha A1 - Bookhagen, Bodo T1 - A network-based flow accumulation algorithm for point clouds BT - Facet-Flow Networks (FFNs) JF - Journal of geophysical research : Earth surface N2 - Flow accumulation algorithms estimate the steady state of flow on real or modeled topographic surfaces and are crucial for hydrological and geomorphological assessments, including delineation of river networks, drainage basins, and sediment transport processes. Existing flow accumulation algorithms are typically designed to compute flows on regular grids and are not directly applicable to arbitrarily sampled topographic data such as lidar point clouds. In this study we present a random sampling scheme that generates homogeneous point densities, in combination with a novel flow path tracing approach-the Facet-Flow Network (FFN)-that estimates flow accumulation in terms of specific catchment area (SCA) on triangulated surfaces. The random sampling minimizes biases due to spatial sampling and the FFN allows for direct flow estimation from point clouds. We validate our approach on a Gaussian hill surface and study the convergence of its SCA compared to the analytical solution. Here, our algorithm outperforms the multiple flow direction algorithm, which is optimized for divergent surfaces. We also compute the SCA of a 6-km(2)-steep, vegetated catchment on Santa Cruz Island, California, based on airborne lidar point-cloud data. Point-cloud-based SCA values estimated by our method compare well with those estimated by the D-infinity or multiple flow direction algorithm on gridded data. The advantage of computing SCA from point clouds becomes relevant especially for divergent topography and for small drainage areas: These are depicted with much more detail due to the higher sampling density of point clouds. KW - point clouds KW - drainage networks KW - lidar KW - tin KW - surface runoff KW - spatial sampling Y1 - 2019 U6 - https://doi.org/10.1029/2018JF004827 SN - 2169-9003 SN - 2169-9011 VL - 124 IS - 7 SP - 2013 EP - 2033 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Smith, Taylor A1 - Bookhagen, Bodo T1 - Assessing Multi-Temporal Snow-Volume Trends in High Mountain Asia From 1987 to 2016 Using High-Resolution Passive Microwave Data JF - Frontiers in Earth Science N2 - High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances. KW - snow KW - glacier KW - climate change KW - passive microwave KW - special sensor microwave imager KW - special sensor microwave imager/sounder Y1 - 2020 U6 - https://doi.org/10.3389/feart.2020.559175 SN - 2296-6463 VL - 8 PB - Frontiers Media CY - Lausanne ER - TY - GEN A1 - Olen, Stephanie M. A1 - Bookhagen, Bodo T1 - Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series T2 - remote sensing N2 - The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 471 KW - Sentinel-1 KW - natural hazards KW - rapid damage mapping KW - coherence KW - potentially affected areas (PAA) Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-417766 ER - TY - JOUR A1 - Neely, Alexander B. A1 - Bookhagen, Bodo A1 - Burbank, Douglas W. T1 - An automated knickzone selection algorithm (KZ-Picker) to analyze transient landscapes: Calibration and validation JF - Journal of geophysical research : Earth surface N2 - Streams commonly respond to base-level fall by localizing erosion within steepened, convex knickzone reaches. Localized incision causes knickzone reaches to migrate upstream. Such migrating knickzones dictate the pace of landscape response to changes in tectonics or erosional efficiency and can help quantify the timing and source of base-level fall. Identification of knickzones typically requires individual selection of steepened reaches: a process that is tedious and subjective and has no efficient means to measure knickzone size. We construct an algorithm to automate this procedure by selecting the bounds of knickzone reaches in a -space (drainage-area normalized) framework. An automated feature calibrates algorithm parameters to a subset of knickzones handpicked by the user. The algorithm uses these parameters as consistent criteria to identify knickzones objectively, and then the algorithm measures the height, length, and slope of each knickzone reach. We test the algorithm on 1, 10, and 30m resolution digital elevation models (DEMs) of six catchments (trunk-stream lengths: 2.1-5.4km) on Santa Cruz Island, southern California. On the 1m DEM, algorithm-selected knickzones confirm 93% of handpicked knickzone positions (n=178) to a spatial accuracy of 100m, 88% to an accuracy within 50m, and 46% to an accuracy within 10m. Using 10 and 30m DEMs, accuracy is similar: 88-86% to 100m and 82% to 50m (n=38 and 36, respectively). The algorithm enables efficient regional comparison of the size and location of knickzones with geologic structures, mapped landforms, and hillslope morphology, thereby facilitating approaches to characterize the dynamics of transient landscapes. Plain Language Summary The shape of rivers reflects the environments that they flow through and the environments that they link together: mountains and oceans. Anywhere along the length of a river, changes in environmental conditions are propagated upstream and downstream as the river changes its morphology to match the new environmental conditions. Commonly, rivers steepen as land uplifts faster in regions of high tectonic convergence. The steepening of river gradients is propagated upstream and can be mapped to trace zones of high tectonic activity across landscapes and estimate the source and timing of environmental change. Such insights may indicate regions where earthquakes have become more frequent in the recent past and how rivers respond to these changes. In this submission, we detail an algorithm that can use digital topographic data (similar to google earth), to automatically map and measure anomalously steep river reaches across continental scales. This technology can highlight areas that have experienced recent sustained changes in environmental conditions, evident by changes in the morphology of rivers. Such environmental conditions could be changes in tectonic uplift and earthquake activity, changes in sea level, changes in land-use, or changes in climate, all factors that can produce measurable differences in river morphology over time. KW - knickpoint KW - transient KW - knickzone KW - incision KW - relict landscape KW - Santa Cruz Island Y1 - 2017 U6 - https://doi.org/10.1002/2017JF004250 SN - 2169-9003 SN - 2169-9011 VL - 122 SP - 1236 EP - 1261 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Smith, Taylor A1 - Bookhagen, Bodo A1 - Rheinwalt, Aljoscha T1 - identified with an automated snowmelt detection algorithm, 1987-2016 JF - The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union N2 - High Mountain Asia (HMA) – encompassing the Tibetan Plateau and surrounding mountain ranges – is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season – defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3–5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade−1 over the 29-year study period (5–25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002–2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers – such as the Karakoram and Kunlun Shan – see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous. Y1 - 2017 U6 - https://doi.org/10.5194/tc-11-2329-2017 SN - 1994-0416 SN - 1994-0424 VL - 11 SP - 2329 EP - 2343 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Bufe, Aaron A1 - Burbank, Douglas W. A1 - Liu, Langtao A1 - Bookhagen, Bodo A1 - Qin, Jintang A1 - Chen, Jie A1 - Li, Tao A1 - Jobe, Jessica Ann Thompson A1 - Yang, Huili T1 - Variations of Lateral Bedrock Erosion Rates Control Planation of Uplifting Folds in the Foreland of the Tian Shan, NW China JF - Journal of geophysical research : Earth surface N2 - Fluvial planation surfaces, such as straths, commonly serve as recorders of climatic and tectonic changes and are formed by the lateral erosion of rivers, a process that remains poorly understood. Here we present a study of kilometer-wide, fluvially eroded, low-relief surfaces on rapidly uplifting folds in the foreland of the southwestern Tian Shan. A combination of field work, digital elevation model analysis, and dating of fluvial deposits reveals that despite an arid climate and rapid average rock-uplift rates of 1-3mm/yr, rivers cut extensive (>1-2km wide) surfaces with typical height variations of <6m over periods of >2-6kyr. The extent of this beveling varies in space and time, such that different beveling episodes affect individual structures. Between times of planation, beveled surfaces are abandoned, incised, and deformed across the folds. In a challenge to models that link strath cutting and abandonment primarily to changes in river incision rates, we demonstrate that lateral erosion rates of antecedent streams crossing the folds have to vary by more than 1 order of magnitude to explain the creation of beveled platforms in the past and their incision at the present day. These variations do not appear to covary with climate variability and might be caused by relatively small (much less than an order of magnitude) changes in sediment or water fluxes. It remains uncertain in which settings variations in lateral bedrock erosion rates predominate over changes in vertical erosion rates. Therefore, when studying fluvial planation and strath terraces, variability of both lateral and vertical erosion rates should be considered. KW - strath terraces KW - lateral erosion KW - detachment folds KW - Quaternary geochronology Y1 - 2017 U6 - https://doi.org/10.1002/2016JF004099 SN - 2169-9003 SN - 2169-9011 VL - 122 SP - 2431 EP - 2467 PB - American Geophysical Union CY - Washington 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 -