@article{SahaOwenOrretal.2019, author = {Saha, Sourav and Owen, Lewis A. and Orr, Elizabeth N. and Caffee, Marc W.}, title = {High-frequency Holocene glacier fluctuations in the Himalayan-Tibetan orogen}, series = {Quaternary science reviews : the international multidisciplinary research and review journal}, volume = {220}, journal = {Quaternary science reviews : the international multidisciplinary research and review journal}, publisher = {Elsevier}, address = {Oxford}, issn = {0277-3791}, doi = {10.1016/j.quascirev.2019.07.021}, pages = {372 -- 400}, year = {2019}, abstract = {Holocene glacial chronostratigraphies in glaciated valleys spread throughout the Himalayan-Tibetan orogen, including the Himalaya, Tibet, Pamir, and Tian Shan, are developed using a landsystems approach, detailed geomorphic mapping, and new and published Be-10 surface exposure dating. New studies in the Kulti valley of Lahul and the Parkachik valley of the Nun Kun massif of the Himalaya of northern India define three glacier advances at similar to 14.7, 12.2, 0.5 ka, in addition to one historically dated late 19th Century advance in the Kulti valley, and one Late Holocene advance at similar to 0.2 ka in the Parkachik valley. Three major climatic groups (subdivided into five climatic zones) are defined across the orogen using Cluster Analysis (CA) and Principal Component Analysis (PCA) to identify glaciated regions with comparable climatic characteristics to evaluate the timing, and extent of Holocene glacier advances across these regions. Our regional analyses across the Himalayan-Tibetan orogen suggest at least one Lateglacial (similar to 15.3-11.8 ka) and five Himalayan-Tibetan Holocene glacial stages (HTHS) at similar to 11.5-9.5, similar to 8.8-7.7, similar to 7.0-3.2, similar to 2.3-1.0, and <1 ka. The extent (amplitude) of glacier advances in 77 glaciated valleys is reconstructed and defined using equilibrium-line altitudes (ELAs). Modern glacier hypsometries are also assessed to help explain the intra-regional variations in glacier amplitudes during each regional glacier advance. A linear inverse glacier flow model is used to decipher the net changes in temperature (Delta T) between periods of reconstructed regional glacier advances in 66 glaciated valleys across different climatic regions throughout the orogen. The Be-10, ELAs, and Delta T data suggest enhanced monsoonal and increased precipitation during the Early Holocene, followed by relative cooling and increased aridity during the Mid- and Late Holocene that influenced glaciation. The sublimation-dominated cold-based glaciers in the northern regions of Himalayan-Tibetan orogen are more affected during these shifts in climate than the temperate glaciers in the south. (C) 2019 Elsevier Ltd. All rights reserved.}, language = {en} } @article{SahaOwenOrretal.2019, author = {Saha, Sourav and Owen, Lewis A. and Orr, Elizabeth N. and Caffee, Marc W.}, title = {Cosmogenic Be-10 and equilibrium-line altitude dataset of Holocene glacier advances in the Himalayan-Tibetan orogen}, series = {Data in brief}, volume = {26}, journal = {Data in brief}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-3409}, doi = {10.1016/j.dib.2019.104412}, pages = {13}, year = {2019}, abstract = {A comprehensive analysis of the variable temporal and spatial responses of tropical-subtropical high-altitude glaciers to climate change is critical for successful model predictions and environmental risk assessment in the Himalayan-Tibetan orogen. High-frequency Holocene glacier chronostratigraphies are therefore reconstructed in 79 glaciated valleys across the orogen using 519 published and 16 new terrestrial cosmogenic 10Be exposure age dataset. Published 10Be ages are compiled only for moraine boulders (excluding bedrock ages). These ages are recalculated using the latest ICE-D production rate calibration database and the scaling scheme models. Outliers for the individual moraine are detected using the Chauvenet's criterion. In addition, past equilibrium-line altitudes (ELAs) are determined using the area-altitude (AA), area accumulation ratio (AAR), and toe-headwall accumulation ratio (THAR) methods for each glacier advance. The modern maximum elevations of lateral moraines (MELM) are also used to estimate modern ELAs and as an independent check on mean ELAs derived using the above three methods. These data may serve as an essential archive for future studies focusing on the cryospheric and environmental changes in the Himalayan-Tibetan orogen. A more comprehensive analysis of the published and new 10Be ages and ELA results and a list of references are presented in Saha et al. (2019, High-frequency Holocene glacier fluctuations in the Himalayan-Tibetan orogen. Quaternary Science Reviews, 220, 372-400).}, language = {en} } @phdthesis{Bittermann2015, author = {Bittermann, Klaus}, title = {Semi-empirical sea-level modelling}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-93881}, school = {Universit{\"a}t Potsdam}, pages = {v, 88}, year = {2015}, abstract = {Semi-empirical sea-level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers, in the following global mean temperature. This model class evolved as a supplement to process-based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea-level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea-level rise. Semi-empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea-level rise, consistently giving significantly higher projections than process-based models. In the following different aspects of semi-empirical sea-level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level, and to infer past global temperature from sea-level data via inverse modelling. Periods studied encompass the instrumental period, covered by tide gauges (starting 1700 CE (Common Era) in Amsterdam) and satellites (first launched in 1992 CE), the era from 1000 BCE (before CE) to present, and the full length of the Holocene (using proxy data). Accordingly different data, model formulations and implementations have been used. It could be shown in Bittermann et al. (2013) that SEMs correctly predict 20th century sea-level when calibrated with data until 1900 CE. SEMs also turned out to give better predictions than the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report (AR4, IPCC (2007)) models, for the period from 1961-2003 CE. With the first multi-proxy reconstruction of global sea-level as input, estimate of the human-induced component of modern sea-level change and projections of future sea-level rise were calculated (Kopp et al. (2016)). It turned out with 90\% confidence that more than 40 \% of the observed 20th century sea-level rise is indeed anthropogenic. With the new semi-empirical and IPCC (2013) 5th assessment report (AR5) projections the gap between SEM and process-based model projections closes, giving higher credibility to both. Combining all scenarios, from strong mitigation to business as usual, a global sea-level rise of 28-131 cm relative to 2000 CE, is projected with 90\% confidence. The decision for a low carbon pathway could halve the expected global sea-level rise by 2100 CE. Present day temperature and thus sea level are driven by the globally acting greenhouse-gas forcing. Unlike that, the Milankovich forcing, acting on Holocene timescales, results mainly in a northern-hemisphere temperature change. Therefore a semi-empirical model can be driven with northernhemisphere temperatures, which makes it possible to model the main subcomponent of sea-level change over this period. It showed that an additional positive constant rate of the order of the estimated Antarctic sea-level contribution is then required to explain the sea-level evolution over the Holocene. Thus the global sea level, following the climatic optimum, can be interpreted as the sum of a temperature induced sea-level drop and a positive long-term contribution, likely an ongoing response to deglaciation coming from Antarctica.}, language = {en} }