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In this study, the spatial and temporal impacts of the Ataturk Dam on agro-meteorological aspects of the Southeastern Anatolia region have been investigated. Change detection and environmental impacts due to water-reserve changes in Ataturk Dam Lake have been determined and evaluated using multi-temporal Landsat satellite imageries and meteorological datasets within a period of 1984-2011. These time series have been evaluated for three time periods. Dam construction period constitutes the first part of the study. Land cover/use changes especially on agricultural fields under the Ataturk Dam Lake and its vicinity have been identified between the periods of 1984-1992. The second period comprises the 10-year period after the completion of filling up the reservoir in 1992. At this period, Landsat and meteorological time-series analyses are examined to assess the impact of the Ataturk Dam Lake on selected irrigated agricultural areas. For the last 9-year period from 2002 to 2011, the relationships between seasonal water-reserve changes and irrigated plains under changing climatic factors primarily driving vegetation activity (monthly, seasonal, and annual fluctuations of rainfall rate, air temperature, humidity) on the watershed have been investigated using a 30-year meteorological time series. The results showed that approximately 368 km(2) of agricultural fields have been affected because of inundation due to the Ataturk Dam Lake. However, irrigated agricultural fields have been increased by 56.3% of the total area (1552 of 2756 km(2)) on Harran Plain within the period of 1984-2011.
Integration of digital elevation models and satellite images to investigate geological processes.
(2006)
In order to better understand the geological boundary conditions for ongoing or past surface processes geologists face two important questions: 1) How can we gain additional knowledge about geological processes by analyzing digital elevation models (DEM) and satellite images and 2) Do these efforts present a viable approach for more efficient research. Here, we will present case studies at a variety of scales and levels of resolution to illustrate how we can substantially complement and enhance classical geological approaches with remote sensing techniques. Commonly, satellite and DEM based studies are being used in a first step of assessing areas of geologic interest. While in the past the analysis of satellite imagery (e.g. Landsat TM) and aerial photographs was carried out to characterize the regional geologic characteristics, particularly structure and lithology, geologists have increasingly ventured into a process-oriented approach. This entails assessing structures and geomorphic features with a concept that includes active tectonics or tectonic activity on time scales relevant to humans. In addition, these efforts involve analyzing and quantifying the processes acting at the surface by integrating different remote sensing and topographic data (e.g. SRTM-DEM, SSM/I, GPS, Landsat 7 ETM, Aster, Ikonos…). A combined structural and geomorphic study in the hyperarid Atacama desert demonstrates the use of satellite and digital elevation data for assessing geological structures formed by long-term (millions of years) feedback mechanisms between erosion and crustal bending (Zeilinger et al., 2005). The medium-term change of landscapes during hundred thousands to millions years in a more humid setting is shown in an example from southern Chile. Based on an analysis of rivers/watersheds combined with landscapes parameterization by using digital elevation models, the geomorphic evolution and change in drainage pattern in the coastal Cordillera can be quantified and put into the context of seismotectonic segmentation of a tectonically active region. This has far-reaching implications for earthquake rupture scenarios and hazard mitigation (K. Rehak, see poster on IMAF Workshop). Two examples illustrate short-term processes on decadal, centennial and millennial time scales: One study uses orogen scale precipitation gradients derived from remotely sensed passive microwave data (Bookhagen et al., 2005a). They demonstrate how debris flows were triggered as a response of slopes to abnormally strong rainfall in the interior parts of the Himalaya during intensified monsoons. The area of the orogen that receives high amounts of precipitation during intensified monsoons also constitutes numerous landslide deposits of up to 1km<sup>3 volume that were generated during intensified monsoon phase at about 27 and 9 ka (Bookhagen et al., 2005b). Another project in the Swiss Alps compared sets of aerial photographs recorded in different years. By calculating high resolution surfaces the mass transport in a landslide could be reconstructed (M. Schwab, Universität Bern). All these examples, although representing only a short and limited selection of projects using remote sense data in geology, have as a common approach the goal to quantify geological processes. With increasing data resolution and new sensors future projects will even enable us to recognize more patterns and / or structures indicative of geological processes in tectonically active areas. This is crucial for the analysis of natural hazards like earthquakes, tsunamis and landslides, as well as those hazards that are related to climatic variability. The integration of remotely sensed data at different spatial and temporal scales with field observations becomes increasingly important. Many of presently highly populated places and increasingly utilized regions are subject to significant environmental pressure and often constitute areas of concentrated economic value. Combined remote sensing and ground-truthing in these regions is particularly important as geologic, seismicity and hydrologic data may be limited here due to the recency of infrastructural development. Monitoring ongoing processes and evaluating the remotely sensed data in terms of recurrence of events will greatly enhance our ability to assess and mitigate natural hazards. <hr> Dokument 1: Foliensatz | Dokument 2: Abstract <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
We document Quaternary fluvial incision driven by fault-controlled surface deformation in the inverted intermontane Gökirmak Basin in the Central Pontide mountains along the northern margin of the Central Anatolian Plateau. In-situ-produced Be-10, Ne-21, and Cl-36 concentrations from gravel-covered fluvial terraces and pediment surfaces along the trunk stream of the basin (the Gökirmak River) yield model exposure ages ranging from 71ka to 34645ka and average fluvial incision rates over the past similar to 350ka of 0.280.01mm a(-1). Similarities between river incision rates and coastal uplift rates at the Black Sea coast suggest that regional uplift is responsible for the river incision. Model exposure ages of deformed pediment surfaces along tributaries of the trunk stream range from 605ka to 110 +/- 10ka, demonstrating that the thrust faults responsible for pediment deformation were active after those times and were likely active earlier as well as explaining the topographic relief of the region. Together, our data demonstrate cumulative incision that is linked to active internal shortening and uplift of similar to 0.3mm a(-1) in the Central Pontide orogenic wedge, which may ultimately contribute to the lateral growth of the northern Anatolian Plateau.
Rivers draining the southern Himalaya provide most of the water supply for the densely populated Indo-Gangetic plains. Despite the importance of water resources in light of climate change, the relative contributions of rainfall, snow and glacier melt to discharge are not well understood, due to the scarcity of ground-based data in this complex terrain. Here, we quantify discharge sources in the Sutlej Valley, western Himalaya, from 2000 to 2012 with a distributed hydrological model that is based on daily, ground-calibrated remote-sensing observation. Based on the consistently good model performance, we analyzed the spatiotemporal distribution of hydrologic components and quantified their contribution to river discharge. Our results indicate that the Sutlej River's annual discharge at the mountain front is sourced to 55% by effective rainfall (rainfall reduced by evapotranspiration), 35% by snow melt and 10% by glacier melt. In the high-elevation orogenic interior glacial runoff contributes ∼30% to annual river discharge. These glacier melt contributions are especially important during years with substantially reduced rainfall and snowmelt runoff, as during 2004, to compensate for low river discharge and ensure sustained water supply and hydropower generation. In 2004, discharge of the Sutlej River totaled only half the maximum annual discharge; with 17.3% being sourced by glacier melt. Our findings underscore the importance of calibrating remote-sensing data with ground-based data to constrain hydrological models with reasonable accuracy. For instance, we found that TRMM (Tropical Rainfall Measuring Mission) product 3B42 V7 systematically overestimates rainfall in arid regions of our study area by a factor of up to 5. By quantifying the spatiotemporal distribution of water resources we provide an important assessment of the potential impact of global warming on river discharge in the western Himalaya. Given the near-global coverage of the utilized remote-sensing datasets this hydrological modeling approach can be readily transferred to other data-sparse regions.
The sediment flux through Himalayan rivers directly impacts water quality and is important for sustaining agriculture as well as maintaining drinking-water and hydropower generation. Despite the recent increase in demand for these resources, little is known about the triggers and sources of extreme sediment flux events, which lower water quality and account for extensive hydropower reservoir filling and turbine abrasion. Here, we present a comprehensive analysis of the spatiotemporal trends in suspended sediment flux based on daily data during the past decade (2001-2009) from four sites along the Sutlej River and from four of its main tributaries. In conjunction with satellite data depicting rainfall and snow cover, air temperature and earthquake records, and field observations, we infer climatic and geologic controls of peak suspended sediment concentration (SSC) events. Our study identifies three key findings: First, peak SSC events (a parts per thousand yen 99th SSC percentile) coincide frequently (57-80%) with heavy rainstorms and account for about 30% of the suspended sediment flux in the semi-arid to arid interior of the orogen. Second, we observe an increase of suspended sediment flux from the Tibetan Plateau to the Himalayan Front at mean annual timescales. This sediment-flux gradient suggests that averaged, modern erosion in the western Himalaya is most pronounced at frontal regions, which are characterized by high monsoonal rainfall and thick soil cover. Third, in seven of eight catchments, we find an anticlockwise hysteresis loop of annual sediment flux variations with respect to river discharge, which appears to be related to enhanced glacial sediment evacuation during late summer. Our analysis emphasizes the importance of unconsolidated sediments in the high-elevation sector that can easily be mobilized by hydrometeorological events and higher glacial-meltwater contributions. In future climate change scenarios, including continuous glacial retreat and more frequent monsoonal rainstorms across the Himalaya, we expect an increase in peak SSC events, which will decrease the water quality and impact hydropower generation.
Seasonal precipitation gradients and their impact on fluvial sediment flux in the Northwest Himalaya
(2010)
Precipitation in the form of rain and snowfall throughout the Himalaya controls river discharge and erosional processes and, thus, has a first-order control on the fluvial sediment flux. Here, we analyze daily precipitation data (1998-2007) of 80 weather stations from the northwestern Himalaya in order to decipher temporal and spatial moisture gradients. In addition, suspended sediment data allow assessment of the impact of precipitation on the fluvial sediment flux for a 10(3)-km(2) catchment (Baspa). We find that weather stations located at the mountain front receive similar to 80% of annual precipitation during summer (May-Oct), whereas stations in the orogenic interior, i.e., leeward of the orographic barrier, receive similar to 60% of annual precipitation during winter (Nov-Apr). In both regions 4-6 rainstorm days account for similar to 40% of the summer budgets, while rainstorm magnitude-frequency relations, derived from 40-year precipitation time-series, indicate a higher storm variability in the interior than in the frontal region. This high variability in maximum annual rainstorm days in the orogenic interior is reflected by a high variability in extreme suspended sediment events in the Baspa Valley, which strongly affect annual erosion yields. The two most prominent 5-day-long erosional events account for 50% of the total 5-year suspended sediment flux and coincide with synoptic-scale monsoonal rainstorms. This emphasizes the erosional impact of the Indian Summer Monsoon as the main driving force for erosion processes in the orogenic interior, despite more precipitation falling during the winter season.
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.
Variation of deuterium excess in surface waters across a 5000-m elevation gradient in eastern Nepal
(2020)
The strong elevation gradient of the Himalaya allows for investigation of altitude and orographic impacts on surface water delta O-18 and delta D stable isotope values. This study differentiates the time- and altitude-variable contributions of source waters to the Arun River in eastern Nepal. It provides isotope data along a 5000-m gradient collected from tributaries as well as groundwater, snow, and glacial-sourced surface waters and time-series data from April to October 2016. We find nonlinear trends in delta O-18 and delta D lapse rates with high-elevation lapse rates (4000-6000 masl) 5-7 times more negative than low-elevation lapse rates (1000-3000 masl). A distinct seasonal signal in delta O-18 and delta D lapse rates indicates time-variable source-water contributions from glacial and snow meltwater as well as precipitation transitions between the Indian Summer Monsoon and Winter Westerly Disturbances. Deuterium excess correlates with the extent of snowpack and tracks melt events during the Indian Summer Monsoon season. Our analysis identifies the influence of snow and glacial melt waters on river composition during low-flow conditions before the monsoon (April/May 2016) followed by a 5-week transition to the Indian Summer Monsoon-sourced rainfall around mid-June 2016. In the post-monsoon season, we find continued influence from glacial melt waters as well as ISM-sourced groundwater.
Present erosion and sediment flux in the semi-arid intramontane Santa Maria Basin, NW Argentina are compared with conditions during a period of wetter and more variable climate at about 30,000 14C yrs ago. The results suggest that the influence of climate change on the overall erosional sediment budget is significant, mainly because of a change in the erosion regime coupled with an increase in mass movements. The most effective mechanism to increase landslide activity in this environment is a highly variable climate on inter-annual timescales. In contrast, Quaternary changes in erosional budgets due to variations in moisture regimes is small in the Santa Maria Basin. Since the magnitude of a potential increase in background erosion as well as enhanced landsliding is smaller than typical levels of uncertainty of erosional budgets for such large basins, it is not likely that climate-driven erosional unloading can influence tectonic style and rates in this semi-arid environment on time scales of several 103 to 104 years.
Multiple landslide clusters record quaternary climate changes in the northwestern Argentine andes
(2003)
The chronology of multiple landslide deposits and related lake sediments in the semi-arid eastern Argentine Cordillera suggests that major mass movements cluster in two time periods during the Quaternary, i.e. between 40 and 25 and after 5 14C kyr BP. These clusters may correspond to the Minchin (maximum at around 28-27 14C kyr BP) and Titicaca wet periods (after 3.9 14C kyr BP). The more humid conditions apparently caused enhanced landsliding in this environment. In contrast, no landslide-related damming and associated lake sediments occurred during the Coipasa (11.5- 10 14C yr BP) and Tauca wet periods (14.5-11 14C yr BP). The two clusters at 40-25 and after 5 14C kyr BP may correspond to periods where the El Niño-Southern Oscillation (ENSO) and Tropical Atlantic Sea Surface Temperature Variability (TAV) were active. This, however, was not the case during the Coipasa and Tauca wet periods. Lake-balance modelling of a landslide-dammed lake suggests a 10-15% increase in precipitation and a 3-4 ° C decrease in temperature at ~30 14C kyr BP as compared to the present. In addition, time-series analysis reveals a strong ENSO and TAV during that time. The landslide clusters in northwestern Argentina are therefore best explained by periods of more humid and more variable climates.
Hazards and accessibility
(2018)
The assessment of natural hazards and risk has traditionally been built upon the estimation of threat maps, which are used to depict potential danger posed by a particular hazard throughout a given area. But when a hazard event strikes, infrastructure is a significant factor that can determine if the situation becomes a disaster. The vulnerability of the population in a region does not only depend on the area’s local threat, but also on the geographical accessibility of
the area. This makes threat maps by themselves insufficient for supporting real-time decision-making, especially for those tasks that involve the use of the road network, such as management of relief operations, aid distribution, or planning of evacuation routes, among others. To overcome this problem, this paper proposes a multidisciplinary approach divided in two parts. First, data fusion of satellite-based threat data and open infrastructure data from OpenStreetMap, introducing a threat-based routing service. Second, the visualization of this data through cartographic generalization and schematization. This emphasizes critical areas along roads in a simple way and allows users to visually evaluate the impact natural hazards may have on infrastructure. We develop and illustrate this methodology with a case study of landslide threat for an area in Colombia.
Fluvial fill terraces in intermontane basins are valuable geomorphic archives that can record tectonically and/or climatically driven changes of the Earth-surface process system. However, often the preservation of fill terrace sequences is incomplete and/or they may form far away from their source areas, complicating the identification of causal links between forcing mechanisms and landscape response, especially over multi-millennial timescales. The intermontane Toro Basin in the southern Central Andes exhibits at least five generations of fluvial terraces that have been sculpted into several-hundred-meter-thick Quaternary valley-fill conglomerates. New surface-exposure dating using nine cosmogenic Be-10 depth profiles reveals the successive abandonment of these terraces with a 100 kyr cyclicity between 75 +/- 7 and 487 +/- 34 ka. Depositional ages of the conglomerates, determined by four Al-26/Be-10 burial samples and U-Pb zircon ages of three intercalated volcanic ash beds, range from 18 +/- 141 to 936 +/- 170 ka, indicating that there were multiple cut-and-fill episodes. Although the initial onset of aggradation at similar to 1 Ma and the overall net incision since ca. 500 ka can be linked to tectonic processes at the narrow basin outlet, the superimposed 100 kyr cycles of aggradation and incision are best explained by eccentricity-driven climate change. Within these cycles, the onset of river incision can be correlated with global cold periods and enhanced humid phases recorded in paleoclimate archives on the adjacent Bolivian Altiplano, whereas deposition occurred mainly during more arid phases on the Altiplano and global interglacial periods. We suggest that enhanced runoff during global cold phases - due to increased regional precipitation rates, reduced evapotranspiration, or both - resulted in an increased sediment-transport capacity in the Toro Basin, which outweighed any possible increases in upstream sediment supply and thus triggered incision. Compared with two nearby basins that record precessional (21-kyr) and long-eccentricity (400-kyr) forcing within sedimentary and geomorphic archives, the recorded cyclicity scales with the square of the drainage basin length. (C) 2017 Elsevier B.V. All rights reserved.
Along the NE Pamir margin, flights of late Quaternary fluvial terraces span actively deforming fault-related folds. We present detailed results on two terraces dated using optically stimulated luminescence (OSL) and cosmogenic radionuclide Be-10 (CRN) techniques. Quartz OSL dating of two different grain sizes (4-11 mu m and 90-180 mu m) revealed the fine-grain quartz fraction may overestimate the terrace ages by up to a factor of ten. Two-mm, small-aliquot, coarse-grain quartz OSL ages, calculated using the minimum age model, yielded stratigraphically consistent ages within error and dated times of terrace deposition to similar to 9 and similar to 16 ka. We speculate that, in this arid environment, fine-grain samples can be transported and deposited in single, turbid, and (sometimes) night-time floods that prevent thorough bleaching and, thereby, can lead to relatively large residual OSL signals. In contrast, sand in the fluvial system is likely to have a much longer residence time during transport, thereby providing greater opportunities for thorough bleaching. CRN Be-10 depth profiles date the timing of terrace abandonment to similar to 8 and similar to 14 ka: ages that generally agree with the coarse-grain quartz OSL ages. Our new terrace age of similar to 13-14 ka is broadly consistent with other terraces in the region that indicate terrace deposition and subsequent abandonment occurred primarily during glacial-interglacial transitions, thereby suggesting a climatic control on the formation of these terraces on the margins of the Tarim Basin. Furthermore, tectonic shortening rates calculated from these deformed terraces range from similar to 1.2 to similar to 4.6 mm/a and, when combined with shortening rates from other structures in the region, illuminate the late Quaternary basinward migration of deformation to faults and folds along the Pamir-Tian Shan collisional interface.
Piggyback basins on the margins of growing orogens commonly serve as sensitive recorders of the onset of thrust deformation and changes in source areas. The Bieertuokuoyi piggyback basin, located in the hanging wall of the Pamir Frontal Thrust, provides an unambiguous record of the outward growth of the northeast Pamir margin in northwest China from the Miocene through the Quaternary. To reconstruct the deformation along the margin, we synthesized structural mapping, stratigraphy, magnetostratigraphy, and cosmogenic burial dating of basin fill and growth strata. The Bieertuokuoyi basin records the initiation of the Pamir Frontal Thrust and the Takegai Thrust similar to 5-6Ma, as well as clast provenance and paleocurrent changes resulting from the Pliocene-to-Recent uplift and exhumation of the Pamir to the south. Our results show that coeval deformation was accommodated on the major structures on the northeast Pamir margin throughout the Miocene to Recent. Furthermore, our data support a change in the regional kinematics around the Miocene-Pliocene boundary (similar to 5-6Ma). Rapid exhumation of NE Pamir extensional domes, coupled with cessation of the Kashgar-Yecheng Transfer System on the eastern margin of the Pamir, accelerated the outward propagation of the northeastern Pamir margin and the southward propagation of the Kashi-Atushi fold-and-thrust belt in the southern Tian Shan. This coeval deformation signifies the coupling of the Pamir and Tarim blocks and the transfer of shortening north to the Pamir frontal faults and across the quasi-rigid Tarim Basin to the southern Tian Shan Kashi-Atushi fold-and-thrust system.
Erosional exhumation and topography in mountain belts are temporally and spatially variable over million year timescales because of changes in both the location of deformation and climate. We investigate spatiotemporal variations in exhumation across a 150 x 250 km compartment of the NW Himalaya, India. Twenty-four new and 241 previously published apatite and zircon fission track and white mica Ar-40/Ar-39 ages are integrated with a 1-D numerical model to quantify rates and timing of exhumation alongstrike of several major structures in the Lesser, High, and Tethyan Himalaya. Analysis of thermochronometer data suggests major temporal variations in exhumation occurred in the early middle Miocene and at the Plio-Pleistocene transition. (1) Most notably, exhumation rates for the northern High Himalayan compartments were high (2-3 mm a(-1)) between similar to 23-19 and similar to 3-0 Ma and low (0.5-0.7 mm a(-1)) in between similar to 19-3 Ma. (2) Along the southern High Himalayan slopes, however, high exhumation rates of 1-2 mm a(-1) existed since 11 Ma. (3) Our thermochronology data sets are poorly correlated with present-day rainfall, local relief, and specific stream power which may likely result from (1) a lack of sensitivity of changes in crustal cooling to spatial variations in erosion at high exhumation rates (>similar to 1 mm a(-1)), (2) spatiotemporal variation in erosion not mimicking the present-day topographic or climatic conditions, or (3) the thermochronometer samples in this region having cooled under topography that only weakly resembled the modern-day topography.
Along the Southern Himalayan Front (SHF), areas with concentrated precipitation coincide with rapid exhumation, as indicated by young mineral cooling ages. Twenty new, young ( < 1-5 Ma) apatite fission track (AFT) ages have been obtained from the Himalayan Crystalline Core along the Sutlej Valley, NW India. The AFT ages correlate with elevation, but show no spatial relationship to tectonic structures, such as the Main Central Thrust or the Southern Tibetan Fault System. Monsoonal precipitation in this region exerts a strong influence on erosional surface processes. Fluvial erosional unloading along the SHF is focused on high mountainous areas, where the orographic barrier forces out > 80% of the annual precipitation. AFT cooling ages reveal a coincidence between rapid erosion and exhumation that is focused in a similar to 50-70-km-wide sector of the Himalaya, rather than encompassing the entire orogen. Assuming simplified constant exhumation rates, the rocks of two age vs. elevation transects were exhumed at similar to 1.4 +/- 0.2 and similar to 1.1 +/- 0.4 mm/a with an average cooling rate of similar to 40-50degreesC/Ma during Pliocene-Quarternary time. Following other recently published hypotheses regarding the relation between tectonics and climate in the Himalaya, we suggest that this concentrated loss of material was accommodated by motion along a back-stepping thrust to the south and a normal fault zone to the north as part of an extruding wedge. Climatically controlled erosional processes focus on this wedge and suggest that climatically controlled surface processes determine tectonic deformation in the internal part of the Himalaya. (C) 2004 Elsevier B.V. All rights reserved
Metamorphic dome complexes occur within the internal structures of the northern Himalaya and southern Tibet. Their origin, deformation, and fault displacement patterns are poorly constrained. We report new field mapping, structural data, and cooling ages from the western flank of the Leo Pargil dome in the northwestern Himalaya in an attempt to characterize its post-middle Miocene structural development. The western flank of the dome is characterized by shallow, west-dipping pervasive foliation and WNW-ESE mineral lineation. Shear-sense indicators demonstrate that it is affected by east-west normal faulting that facilitated exhumation of high-grade metamorphic rocks in a contractional setting. Sustained top-to-northwest normal faulting during exhumation is observed in a progressive transition from ductile to brittle deformation. Garnet and kyanite indicate that the Leo Pargil dome was exhumed from the mid-crust. Ar- 40/Ar-39 mica and apatite fission track (AFT) ages constrain cooling and exhumation pathways front 350 to 60 degrees C and suggest that the dome cooled in three stages since the middle Miocene. Ar-40/Ar-39 white mica ages of 16-14 Ma suggest a first phase of rapid cooling and provide minimum estimates for the onset of dome exhumation. AFT ages between 10 and 8 Ma suggest that ductile fault displacement had ceased by then, and AFT track-length data from high-elevation samples indicate that the rate of cooling had decreased significantly. We interpret this to indicate decreased fault displacement along the Leo Pargil shear zone and possibly a transition to the Kaurik-Chango normal fault system between 10 and 6 Ma. AFT ages from lower elevations indicate accelerated cooling since the Pliocene that cannot be related to pure fault displacement, and therefore may reflect more pronounced regionally distributed and erosion-driven exhumation
Whether variations in the spatial distribution of erosion influence the location, style, and magnitude of deformation within the Himalayan orogen is a matter of debate. We report new Ar-40/Ar-39 white mica and apatite fission- track (AFT) ages that measure the vertical component of exhumation rates along an similar to 120-km-wide NE-SW transect spanning the greater Sutlej region of northwest India. The Ar-40/Ar-39 data indicate that first the High Himalayan Crystalline units cooled below their closing temperature during the early to middle Miocene. Subsequently, Lesser Himalayan Crystalline nappes cooled rapidly, indicating southward propagation of the orogen during late Miocene to Pliocene time. The AFT data, in contrast, imply synchronous exhumation of a NE-SW-oriented similar to 80 x 40 km region spanning both crystalline nappes during the Pliocene-Quaternary. The locus of pronounced exhumation defined by the AFT data correlates with a region of high precipitation, discharge, and sediment flux rates during the Holocene. This correlation suggests that although tectonic processes exerted the dominant control on the denudation pattern before and until the middle Miocene; erosion may have been the most important factor since the Pliocene
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.
Orogenic plateaus are extensive, high-elevation areas with low internal relief that have been attributed to deep-seated and/or climate-driven surface processes. In the latter case, models predict that lateral plateau growth results from increasing aridity along the margins as range uplift shields the orogen interior from precipitation. We analyze the spatiotemporal progression of basin isolation and filling at the eastern margin of the Puna Plateau of the Argentine Andes to determine if the topography predicted by such models is observed. We find that the timing of basin filling and reexcavation is variable, suggesting nonsystematic plateau growth. Instead, the Airy isostatically compensated component of topography constitutes the majority of the mean elevation gain between the foreland and the plateau. This indicates that deep-seated phenomena, such as changes in crustal thickness and/or lateral density, are required to produce high plateau elevations. In contrast, the frequency of the uncompensated topography within the plateau and in the adjacent foreland that is interrupted by ranges appears similar, although the amplitude of this topographic component increases east of the plateau. Combined with sedimentologic observations, we infer that the low internal relief of the plateau likely results from increased aridity and sediment storage within the plateau and along its eastern margin.
Forecasting the onset and withdrawal of the Indian summer monsoon is crucial for the life and prosperity of more than one billion inhabitants of the Indian subcontinent. However, accurate prediction of monsoon timing remains a challenge, despite numerous efforts. Here we present a method for prediction of monsoon timing based on a critical transition precursor. We identify geographic regions-tipping elements of the monsoon-and use them as observation locations for predicting onset and withdrawal dates. Unlike most predictability methods, our approach does not rely on precipitation analysis but on air temperature and relative humidity, which are well represented both in models and observations. The proposed method allows to predict onset 2 weeks earlier and withdrawal dates 1.5 months earlier than existing methods. In addition, it enables to correctly forecast monsoon duration for some anomalous years, often associated with El Nino-Southern Oscillation.
This paper employs a complex network approach to determine the topology and evolution of the network of extreme precipitation that governs the organization of extreme rainfall before, during, and after the Indian Summer Monsoon (ISM) season. We construct networks of extreme rainfall events during the ISM (June-September), post-monsoon (October-December), and pre-monsoon (March-May) periods from satellite-derived (Tropical Rainfall Measurement Mission, TRMM) and rain-gauge interpolated (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE) data sets. The structure of the networks is determined by the level of synchronization of extreme rainfall events between different grid cells throughout the Indian subcontinent. Through the analysis of various complex-network metrics, we describe typical repetitive patterns in North Pakistan (NP), the Eastern Ghats (EG), and the Tibetan Plateau (TP). These patterns appear during the pre-monsoon season, evolve during the ISM, and disappear during the post-monsoon season. These are important meteorological features that need further attention and that may be useful in ISM timing and strength prediction.
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
(2019)
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.
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
(2019)
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.
The Upper Indus Basin (UIB), which covers a wide range of climatic and topographic settings, provides an ideal venue to explore the relationship between climate and topography. While the distribution of snow and glaciers is spatially and temporally heterogeneous, there exist regions with similar elevation-snow relationships. In this work, we construct elevation-binned snow-cover statistics to analyze 3415 watersheds and 7357 glaciers in the UIB region. We group both glaciers and watersheds using a hierarchical clustering approach and find that (1) watershed clusters mirror large-scale moisture transport patterns and (2) are highly dependent on median watershed elevation. (3) Glacier clusters are spatially heterogeneous and are less strongly controlled by elevation, but rather by local topographic parameters that modify solar insolation. Our clustering approach allows us to clearly define self-similar snow-topographic regions. Eastern watersheds in the UIB show a steep snow cover-elevation relationship whereas watersheds in the central and western UIB have moderately sloped relationships, but cluster in distinct groups. We highlight this snow-cover-topographic transition zone and argue that these watersheds have different hydrologic responses than other regions. Our hierarchical clustering approach provides a potential new framework to use in defining climatic zones in the cyrosphere based on empirical data.
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.
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.
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.
Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
(2015)
Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity.
In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min.
The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.
Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity.
In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min.
The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.
Insolation differences play a primary role in controlling microclimate and vegetation cover, which together influence the development of topography. Topographic asymmetry (TA), or slope differences between terrain aspects, has been well documented in small-scale, field-based, and modeling studies. Here we combine a suite of environmental (e.g., vegetation, temperature, solar insolation) and topographic (e.g., elevation, drainage network) data to explore the driving mechanisms and markers of TA on a global scale. Using a novel empirical TA analysis method, we find that (1) steeper terrain has higher TA magnitudes, (2) globally, pole-facing terrain is on average steeper than equator-facing terrain, especially in mid-latitude, tectonically quiescent, and vegetated landscapes, and (3) high-elevation and low-temperature regions tend to have terrain steepened toward the equator. We further show that there are distinct differences in climate and vegetation cover across terrain aspects, and that TA is reflected in the size and form of fluvial drainage networks. Our work supports the argument that insolation asymmetries engender differences in local microclimates and vegetation on opposing terrain aspects, which broadly encourage the development of asymmetric topography across a range of lithologic, tectonic, geomorphic, and climatic settings.
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.
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.
Snowfall comprises a significant percentage of the annual water budget in High Mountain Asia (HMA), but snow water equivalent (SWE) is poorly constrained due to lack of in-situ measurements and complex terrain that limits the efficacy of modeling and observations. Over the past few decades, SWE has been estimated with passive microwave (PM) sensors with generally good results in wide, flat, terrain, and lower reliability in densely forested, complex, or high-elevation areas. In this study, we use raw swath data from five satellite - sensors the Special Sensor Microwave/Imager (SSMI) and Special Sensor Microwave Imager/Sounder (SSMIS) (1987-2015, F08, F11, F13, F17), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E, 2002-2011), AMSR2 (2012-2015), and the Global Precipitation Measurement (GPM, 2014-2015) - in order to understand the spatial and temporal structure of native sensor, topographic, and land cover biases in SWE estimates in HMA. We develop a thorough understanding of the uncertainties in our SWE estimates by examining the impacts of topographic parameters (aspect, relief, hillslope angle, and elevation), land cover, native sensor biases, and climate parameters (precipitation, temperature, and wind speed). HMA, with its high seasonality, large topographic gradients and low relief at high elevations provides an excellent context to examine a wide range of climatic, land-cover, and topographic settings to better constrain SWE uncertainties and potential sensor bias. Using a multi-parameter regression, we compare long-term SWE variability to forest fraction, maximal multiyear snow depth, topographic parameters, and long-term average wind speed across both individual sensor time series and a merged multi-sensor dataset. In regions where forest cover is extensive, it is the strongest control on SWE variability. In those regions where forest density is low (<5%), maximal snow depth dominates the uncertainty signal. In our regression across HMA, we find that forest fraction is the strongest control on SWE variability (75.8%), followed by maximal multi-year snow depth (7.82%), 90th percentile 10-m wind speed of a 10-year December-January-February (DJF) time series (5.64%), 25th percentile DJF 10-m wind speed (5.44%), and hillslope angle (5.24%). Elevation, relief, and terrain aspect show very low influence on SWE variability (<1%). We find that the GPM sensor provides the most robust regression results, and can be reliably used to estimate SWE in our study region. While forest cover and elevation have been integrated into many SWE algorithms, wind speed and long-term maximal snow depth have not. Our results show that wind redistribution of snow can have impacts on SWE, especially over large, flat, areas. Using our regression results, we have developed an understanding of sensor specific SWE uncertainties and their spatial patterns. The uncertainty maps developed in this study provide a first-order approximation of SWE-estimate reliability for much of HMA, and imply that high-fidelity SWE estimates can be produced for many high-elevation areas. (C) 2016 Elsevier Inc. All rights reserved.
High Mountain Asia provides water for more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow - the vast majority of which is not monitored by sparse weather networks. We leverage passive microwave data from the SSMI series of satellites (SSMI, SSMI/S, 1987-2016), reprocessed to 3.125 km resolution, to examine trends in the volume and spatial distribution of snow-water equivalent (SWE) in the Indus Basin. We find that the majority of the Indus has seen an increase in snow-water storage. There exists a strong elevation-trend relationship, where high-elevation zones have more positive SWE trends. Negative trends are confined to the Himalayan foreland and deeply-incised valleys which run into the Upper Indus. This implies a temperature-dependent cutoff below which precipitation increases are not translated into increased SWE. Earlier snowmelt or a higher percentage of liquid precipitation could both explain this cutoff.(1) Earlier work 2 found a negative snow-water storage trend for the entire Indus catchment over the time period 1987-2009 (-4 x 10(-3) mm/yr). In this study based on an additional seven years of data, the average trend reverses to 1.4 x 10(-3). This implies that the decade since the mid-2000s was likely wetter, and positively impacted long-term SWE trends. This conclusion is supported by an analysis of snowmelt onset and end dates which found that while long-term trends are negative, more recent (since 2005) trends are positive (moving later in the year).(3)
Snow meltwaters account for most of the yearly water budgets of many catchments in High Mountain Asia (HMA). We examine trends in snow water equivalent (SWE) using passive microwave data (1987 to 2009). We find an overall decrease in SWE in HMA, despite regions of increased SWE in the Pamir, Kunlun Shan, Eastern Himalaya, and Eastern Tien Shan. Although the average decline in annual SWE across HMA (contributing area, 2641 x 10(3) km(2)) is low (average, -0.3%), annual SWE losses conceal distinct seasonal and spatial heterogeneities across the study region. For example, the Tien Shan has seen both strong increases in winter SWE and sharp declines in spring and summer SWE. In the majority of catchments, the most negative SWE trends are found in mid-elevation zones, which often correspond to the regions of highest snow-water storage and are somewhat distinct from glaciated areas. Negative changes in SWE storage in these mid-elevation zones have strong implications for downstream water availability.
Fluvial fill terraces preserve sedimentary archives of landscape responses to climate change, typically over millennial timescales. In the Humahuaca Basin of NW Argentina (Eastern Cordillera, southern Central Andes), our 29 new optically stimulated luminescence ages of late Pleistocene fill terrace sediments demonstrate that the timing of past river aggradation occurred over different intervals on the western and eastern sides of the valley, despite their similar bedrock lithology, mean slopes, and precipitation. In the west, aggradation coincided with periods of increasing precipitation, while in the east, aggradation coincided with decreasing precipitation or more variable conditions. Erosion rates and grain size dependencies in our cosmogenic Be-10 analyses of modern and fill terrace sediments reveal an increased importance of landsliding compared to today on the west side during aggradation, but of similar importance during aggradation on the east side. Differences in the timing of aggradation and the Be-10 data likely result from differences in valley geometry, which causes sediment to be temporarily stored in perched basins on the east side. It appears as if periods of increasing precipitation triggered landslides throughout the region, which induced aggradation in the west, but blockage of the narrow bedrock gorges downstream from the perched basins in the east. As such, basin geometry and fluvial connectivity appear to strongly influence the timing of sediment movement through the system. For larger basins that integrate subbasins with differing geometries or degrees of connectivity (like Humahuaca), sedimentary responses to climate forcing are likely attenuated.
Uplifted Neogene marine sediments and Quaternary fluvial terraces in the Mut Basin, southern Turkey, reveal a detailed history of surface uplift along the southern margin of the Central Anatolian plateau from the Late Miocene to the present. New surface exposure ages (Be-10, Al-26, and Ne-21) of gravels capping fluvial strath terraces located between 28 and 135 m above the Goksu River in the Mut Basin yield ages ranging from ca. 25 to 130 ka, corresponding to an average incision rate of 0.52 to 0.67 mm/yr. Published biostratigraphic data combined with new interpretations of the fossil assemblages from uplifted marine sediments reveal average uplift rates of 0.25 to 0.37 mm/yr since Late Miocene time (starting between 8 and 5.45 Ma), and 0.72 to 0.74 mm/yr after 1.66 to 1.62 Ma. Together with the terrace abandonment ages, the data imply 0.6 to 0.7 mm/yr uplift rates from 1.6 Ma to the present. The different post-Late Miocene and post-1.6 Ma uplift rates can imply increasing uplift rates through time, or multi-phased uplift with slow uplift or subsidence in between. Longitudinal profiles of rivers in the upper catchment of the Mut and Ermenek basins show no apparent lithologic or fault control on some knickpoints that occur at 1.2 to 1.5 km elevation, implying a transient response to a change in uplift rates. Projections of graded upper relict channel segments to the modern outlet, together with constraints from uplifted marine sediments, show that a slower incision/uplift rate of 0.1 to 0.2 mm/yr preceded the 0.7 mm/yr uplift rate. The river morphology and profile projections therefore reflect multi-phased uplift of the plateau margin, rather than steadily increasing uplift rates. Multi-phased uplift can be explained by lithospheric slab break-off and possibly also the arrival of the Eratosthenes Seamount at the collision zone south of Cyprus.
The response of surface processes to climatic forcing is fundamental for understanding the impacts of climate change on landscape evolution. In the Himalaya, most large rivers feature prominent fill terraces that record an imbalance between sediment supply and transport capacity, presumably due to past fluctuations in monsoon precipitation and/or effects of glaciation at high elevation. Here, we present volume estimates, chronological constraints, and Be-10-derived paleo-erosion rates from a prominent valley fill in the Yamuna catchment, Garhwal Himalaya, to elucidate the coupled response of rivers and hillslopes to Pleistocene climate change. Although precise age control is complicated due to methodological problems, the new data support formation of the valley fill during the late Pleistocene and its incision during the Holocene. We interpret this timing to indicate that changes in discharge and river-transport capacity were major controls. Compared to the present day, late Pleistocene hillslope erosion rates were higher by a factor of similar to 2-4, but appear to have decreased during valley aggradation. The higher late Pleistocene erosion rates are largely unrelated to glacial erosion and could be explained by enhanced sediment production on steep hillslopes due to increased periglacial activity that declined as temperatures increased. Alternatively, erosion rates that decrease during valley aggradation are also consistent with reduced landsliding from threshold hillslopes as a result of rising base levels. In that case, the similarity of paleo-erosion rates near the end of the aggradation period with modern erosion rates might imply that channels and hillslopes are not yet fully coupled everywhere and that present-day hillslope erosion rates may underrepresent long-term incision rates. (C) 2015 Elsevier B.V. All rights reserved.
High Asian glacial landscapes have large variations in topographic relief and the size and steepness of snow accumulation areas. Associated differences in glacial cover and dynamics allow a first-order determination of the dominant processes shaping these landscapes. Here we provide a regional synthesis of the topography and flow characteristics of 287 glaciers across High Asia using digital elevation analysis and remotely sensed glacier surface velocities. Glaciers situated in low-relief areas on the Tibetan Plateau are mainly nourished by direct snowfall, have little or no debris cover, and have a relatively symmetrical distribution of velocities along their length. In contrast, avalanche-fed glaciers with steep accumulation areas, which occur at the deeply incised edges of the Tibetan Plateau, are heavily covered with supraglacial debris, and flow velocities are highest along short segments near their headwalls but greatly reduced along their debris-mantled lower parts. The downstream distribution of flow velocities suggests that the glacial erosion potential is progressively shifted upstream as accumulation areas get steeper and hillslope debris fluxes increase. Our data suggest that the coupling of hillslopes and glacial dynamics increases with topographic steepness and debris cover. The melt-lowering effect of thick debris cover allows the existence of glaciers even when they are located entirely below the snow line. However, slow velocities limit the erosion potential of such glaciers, and their main landscape-shaping contribution may simply be the evacuation of debris from the base of glacial headwalls, which inhibits the formation of scree slopes and thereby allows ongoing headwall retreat by periglacial hillslope processes. We propose a conceptual model in which glacially influenced plateau margins evolve from low-relief to high-relief landscapes with distinctive contributions of hillslope processes and glaciers to relief production and decay.
Controversy about the current state and future evolution of Himalayan glaciers has been stirred up by erroneous statements in the fourth report by the Intergovernmental Panel on Climate Change(1,2). Variable retreat rates(3-6) and a paucity of glacial mass-balance data(7,8) make it difficult to develop a coherent picture of regional climate-change impacts in the region. Here, we report remotely-sensed frontal changes and surface velocities from glaciers in the greater Himalaya between 2000 and 2008 that provide evidence for strong spatial variations in glacier behaviour which are linked to topography and climate. More than 65% of the monsoon-influenced glaciers that we observed are retreating, but heavily debris-covered glaciers with stagnant low-gradient terminus regions typically have stable fronts. Debris-covered glaciers are common in the rugged central Himalaya, but they are almost absent in subdued landscapes on the Tibetan Plateau, where retreat rates are higher. In contrast, more than 50% of observed glaciers in the westerlies-influenced Karakoram region in the northwestern Himalaya are advancing or stable. Our study shows that there is no uniform response of Himalayan glaciers to climate change and highlights the importance of debris cover for understanding glacier retreat, an effect that has so far been neglected in predictions of future water availability(9,10) or global sea level(11).
Erosion in the Himalaya is responsible for one of the greatest mass redistributions on Earth and has fueled models of feedback loops between climate and tectonics. Although the general trends of erosion across the Himalaya are reasonably well known, the relative importance of factors controlling erosion is less well constrained. Here we present 25 Be-10-derived catchment-averaged erosion rates from the Yamuna catchment in the Garhwal Himalaya, northern India. Tributary erosion rates range between similar to 0.1 and 0.5mmyr(-1) in the Lesser Himalaya and similar to 1 and 2mmyr(-1) in the High Himalaya, despite uniform hillslope angles. The erosion-rate data correlate with catchment-averaged values of 5 km radius relief, channel steepness indices, and specific stream power but to varying degrees of nonlinearity. Similar nonlinear relationships and coefficients of determination suggest that topographic steepness is the major control on the spatial variability of erosion and that twofold to threefold differences in annual runoff are of minor importance in this area. Instead, the spatial distribution of erosion in the study area is consistent with a tectonic model in which the rock uplift pattern is largely controlled by the shortening rate and the geometry of the Main Himalayan Thrust fault (MHT). Our data support a shallow dip of the MHT underneath the Lesser Himalaya, followed by a midcrustal ramp underneath the High Himalaya, as indicated by geophysical data. Finally, analysis of sample results from larger main stem rivers indicates significant variability of Be-10-derived erosion rates, possibly related to nonproportional sediment supply from different tributaries and incomplete mixing in main stem channels.
Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.
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.
The spatial pattern of extreme precipitation from 40 years of gauge data in the central Himalaya
(2022)
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.
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.
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.
Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.
Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.