@misc{AtmaniBookhagenSmith2022, author = {Atmani, Farid and Bookhagen, Bodo and Smith, Taylor}, title = {Measuring Vegetation Heights and Their Seasonal Changes in the Western Namibian Savanna Using Spaceborne Lidars}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1275}, issn = {1866-8372}, doi = {10.25932/publishup-56991}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-569915}, pages = {20}, year = {2022}, abstract = {The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.}, language = {en} } @article{AtmaniBookhagenSmith2022, author = {Atmani, Farid and Bookhagen, Bodo and Smith, Taylor}, title = {Measuring vegetation heights and their seasonal changes in the Western Namibian Savanna using spaceborne lidars}, series = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, volume = {14}, journal = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, number = {12}, edition = {12}, publisher = {MDPI}, address = {Basel, Schweiz}, issn = {2072-4292}, doi = {10.3390/rs14122928}, pages = {1 -- 20}, year = {2022}, abstract = {The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.}, language = {en} } @article{RegmiBookhagen2022, author = {Regmi, Shakil and Bookhagen, Bodo}, title = {The spatial pattern of extreme precipitation from 40 years of gauge data in the central Himalaya}, series = {Weather and climate extremes}, volume = {37}, journal = {Weather and climate extremes}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-0947}, doi = {10.1016/j.wace.2022.100470}, pages = {14}, year = {2022}, abstract = {The topography of the Himalaya exerts a substantial control on the spatial distribution of monsoonal rainfall, which is a vital water source for the regional economy and population. But the occurrence of short-lived and high-intensity precipitation results in socio-economic losses. This study relies on 40 years of daily data from 204 ground stations in Nepal to derive extreme precipitation thresholds, amounts, and days at the 95th percentile. We additionally determine the precipitation magnitude-frequency relation. We observe that extreme precipitation amounts follow an almost uniform band parallel to topographic contour lines in the southern Himalaya mountains in central and eastern Nepal but not in western Nepal. The relationship of extreme precipitation indices with topographic relief shows that extreme precipitation thresholds decrease with increasing elevation, but extreme precipitation days increase in higher elevation areas. Furthermore, stations above 1 km elevation exhibit a power-law relation in the rainfall magnitude-frequency framework. Stations at higher elevations generally have lower values of power-law exponents than low elevation areas. This suggests a fundamentally different behaviour of the rainfall distribution and an increased occurrence of extreme rainfall storms in the high elevation areas of Nepal.}, language = {en} } @article{ErbelloDoelessoMelnickZeilingeretal.2022, author = {Erbello Doelesso, Asfaw and Melnick, Daniel and Zeilinger, Gerold and Bookhagen, Bodo and Pingel, Heiko and Strecker, Manfred}, title = {Geomorphic expression of a tectonically active rift-transfer zone in southern Ethiopia}, series = {Geomorphology : an international journal on pure and applied geomorphology}, volume = {403}, journal = {Geomorphology : an international journal on pure and applied geomorphology}, publisher = {Elsevier Science}, address = {Amsterdam [u.a.]}, issn = {0169-555X}, doi = {10.1016/j.geomorph.2022.108162}, pages = {20}, year = {2022}, abstract = {The Gofa Province and the Chew Bahir Basin of southern Ethiopia constitute tectonically active regions, where the Southern Main Ethiopian Rift converges with the Northern Kenya Rift through a wide zone of extensional deformation with several north to northeast-trending, left-stepping en-e \& PRIME;chelon basins. This sector of the Southern Main Ethiopian Rift is characterized by a semi-arid climate and a largely uniform lithology, and thus provides ideal conditions for studying the different parameters that define the tectonic and geomorphic features of this complex kinematic transfer zone. In this study, the degree of tectonic activity, spatiotemporal variations in extension, and the nature of kinematic linkage between different fault systems of the transfer zone are constrained by detailed quantitative geomorphic analysis of river catchments and focused field work. We analyzed fluvial and landscape morphometric characteristics in combination with structural, seismicity, and climatic data to better evaluate the tectono-geomorphic history of this transfer zone. Our data reveal significant north-south variations in the degree of extension from the Sawula Basin in the north (mature) to the Chew Bahir Basin in the south (juvenile). First, normalized channel-steepness indices and the spatial arrangement of knickpoints in footwall-draining streams suggest a gradual, southward shift in extensional deformation and recent tectonic activity. Second, based on 1-k(m) radius local relief and mean-hillslope maximum values that are consistent with ksn anomalies, we confirm strain localization within zones of fault interaction. Third, morphometric indices such as hypsometry, basin asymmetry factor, and valley floor width to valley height ratio also indicate a north to south gradient in tectonic activity, highlighting the importance of such a wide transfer zone with diffuse extension linking different rift segments during the break-up of continental crust.}, language = {en} } @article{PenaMetzgerHeidbachetal.2022, author = {Pe{\~n}a, Carlos and Metzger, Sabrina and Heidbach, Oliver and Bedford, Jonathan and Bookhagen, Bodo and Moreno, Marcos and Oncken, Onno and Cotton, Fabrice}, title = {Role of poroelasticity during the early postseismic deformation of the 2010 Maule megathrust earthquake}, series = {Geophysical research letters}, volume = {49}, journal = {Geophysical research letters}, number = {9}, publisher = {Wiley}, address = {Hoboken, NJ}, issn = {0094-8276}, doi = {10.1029/2022GL098144}, pages = {11}, year = {2022}, abstract = {Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes. Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear. To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion. This model approach fits the geodetic data 14\% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations. If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40\%. Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled.}, language = {en} }