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 - Teshebaeva, Kanayim A1 - Echtler, Helmut A1 - Bookhagen, Bodo A1 - Strecker, Manfred T1 - Deep-seated gravitational slope deformation (DSGSD) and slow-moving landslides in the southern Tien Shan Mountains: new insights from InSAR, tectonic and geomorphic analysis JF - Earth surface processes and landforms : the journal of the British Geomorphological Research Group N2 - We investigated deep-seated gravitational slope deformation (DSGSD) and slow mass movements in the southern Tien Shan Mountains front using synthetic aperture radar (SAR) time-series data obtained by the ALOS/PALSAR satellite. DSGSD evolves with a variety of geomorphological changes (e.g. valley erosion, incision of slope drainage networks) over time that affect earth surfaces and, therefore, often remain unexplored. We analysed 118 interferograms generated from 20 SAR images that covered about 900 km(2). To understand the spatial pattern of the slope movements and to identify triggering parameters, we correlated surface dynamics with the tectono-geomorphic processes and lithologic conditions of the active front of the Alai Range. We observed spatially continuous, constant hillslope movements with a downslope speed of approximately 71 mm year(-1) velocity. Our findings suggest that the lithological and structural framework defined by protracted deformation was the main controlling factor for sustained relief and, consequently, downslope mass movements. The analysed structures revealed integration of a geological/structural setting with the superposition of Cretaceous-Paleogene alternating carbonatic and clastic sedimentary structures as the substratum for younger, less consolidated sediments. This type of structural setting causes the development of large-scale, gravity-driven DSGSD and slow mass movement. Surface deformations with clear scarps and multiple crest lines triggered planes for large-scale deep mass creeps, and these were related directly to active faults and folds in the geologic structures. Our study offers a new combination of InSAR techniques and structural field observations, along with morphometric and seismologic correlations, to identify and quantify slope instability phenomena along a tectonically active mountain front. These results contribute to an improved natural risk assessment in these structures. KW - interferometric SAR (InSAR) KW - small baseline subset (SBAS) KW - gravity-driven slope deformation KW - landslide KW - tectonic geomorphology KW - Tien Shan Mountains Y1 - 2019 U6 - https://doi.org/10.1002/esp.4648 SN - 0197-9337 SN - 1096-9837 VL - 44 IS - 12 SP - 2333 EP - 2348 PB - Wiley CY - Hoboken ER - TY - GEN A1 - Smith, Taylor A1 - Rheinwalt, Aljoscha A1 - Bookhagen, Bodo T1 - Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect. Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies. Using lidar data with point density of ∼10 pts m−2 covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1 m dataset are on average 0.3∘ (0.9∘) from TE and 5.5∘ (14.5∘) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4 m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4 m DEM are 0.25∘ (0.75∘) from TE and 5∘ (12.5∘) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 725 KW - Digital Elevation Model KW - River Incision Model KW - Accuracy Asseessment KW - Landscape Response KW - Error KW - Slope KW - Uncertainties KW - Extraction KW - Expression KW - Patterns Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-430165 SN - 1866-8372 IS - 725 SP - 475 EP - 489 ER - TY - JOUR A1 - Smith, Taylor A1 - Rheinwalt, Aljoscha A1 - Bookhagen, Bodo T1 - Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset JF - Earth Surface Dynamics N2 - Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect. Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies. Using lidar data with point density of ∼10 pts m−2 covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1 m dataset are on average 0.3∘ (0.9∘) from TE and 5.5∘ (14.5∘) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4 m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4 m DEM are 0.25∘ (0.75∘) from TE and 5∘ (12.5∘) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions. KW - Digital Elevation Model KW - River Incision Model KW - Accuracy Asseessment KW - Landscape Response KW - Error KW - Slope KW - Uncertainties KW - Extraction KW - Expression KW - Patterns Y1 - 2019 U6 - https://doi.org/10.5194/esurf-7-475-2019 SN - 2196-6311 SN - 2196-632X VL - 7 SP - 475 EP - 489 PB - Copernicus Publ. CY - Göttingen 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 - GEN A1 - Ramezani Ziarani, Maryam A1 - Bookhagen, Bodo A1 - Schmidt, Torsten A1 - Wickert, Jens A1 - de la Torre, Alejandro A1 - Hierro, Rodrigo T1 - Using Convective Available Potential Energy (CAPE) and Dew-Point Temperature to Characterize Rainfall-Extreme Events in the South-Central Andes T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 771 KW - eastern south–central Andes KW - extreme rainfall KW - deep convection KW - convective available potential energy KW - dew-point temperature Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-438865 SN - 1866-8372 IS - 771 ER - TY - JOUR A1 - Ramezani Ziarani, Maryam A1 - Bookhagen, Bodo A1 - Schmidt, Torsten A1 - Wickert, Jens A1 - de la Torre, Alejandro A1 - Hierro, Rodrigo T1 - Using Convective Available Potential Energy (CAPE) and Dew-Point Temperature to Characterize Rainfall-Extreme Events in the South-Central Andes JF - Atmosphere N2 - The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes. KW - eastern south–central Andes KW - extreme rainfall KW - deep convection KW - convective available potential energy KW - dew-point temperature Y1 - 2019 U6 - https://doi.org/10.3390/atmos10070379 SN - 2073-4433 VL - 10 IS - 7 PB - MDPI CY - Basel ER - TY - JOUR A1 - Purinton, Benjamin A1 - Bookhagen, Bodo T1 - Introducing PebbleCounts BT - a grain-sizing tool for photo surveys of dynamic gravel-bed rivers JF - Earth Surface Dynamics N2 - Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms. Y1 - 2019 U6 - https://doi.org/10.5194/esurf-7-859-2019 SN - 2196-6311 SN - 2196-632X VL - 2019 IS - 7 SP - 859 EP - 877 PB - Copernicus Publ CY - Göttingen ER - TY - GEN A1 - Purinton, Benjamin A1 - Bookhagen, Bodo T1 - Introducing PebbleCounts BT - a grain-sizing tool for photo surveys of dynamic gravel-bed rivers T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 783 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-439468 SN - 1866-8372 IS - 783 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 -