TY - JOUR A1 - Haugk, Charlotte A1 - Jongejans, Loeka L. A1 - Mangelsdorf, Kai A1 - Fuchs, Matthias A1 - Ogneva, Olga A1 - Palmtag, Juri A1 - Mollenhauer, Gesine A1 - Mann, Paul J. A1 - Overduin, P. Paul A1 - Grosse, Guido A1 - Sanders, Tina A1 - Tuerena, Robyn E. A1 - Schirrmeister, Lutz A1 - Wetterich, Sebastian A1 - Kizyakov, Alexander A1 - Karger, Cornelia A1 - Strauss, Jens T1 - Organic matter characteristics of a rapidly eroding permafrost cliff in NE Siberia (Lena Delta, Laptev Sea region) JF - Biogeosciences N2 - Organic carbon (OC) stored in Arctic permafrost represents one of Earth's largest and most vulnerable terrestrial carbon pools. Amplified climate warming across the Arctic results in widespread permafrost thaw. Permafrost deposits exposed at river cliffs and coasts are particularly susceptible to thawing processes. Accelerating erosion of terrestrial permafrost along shorelines leads to increased transfer of organic matter (OM) to nearshore waters. However, the amount of terrestrial permafrost carbon and nitrogen as well as the OM quality in these deposits is still poorly quantified. We define the OM quality as the intrinsic potential for further transformation, decomposition and mineralisation. Here, we characterise the sources and the quality of OM supplied to the Lena River at a rapidly eroding permafrost river shoreline cliff in the eastern part of the delta (Sobo-Sise Island). Our multi-proxy approach captures bulk elemental, molecu- lar geochemical and carbon isotopic analyses of Late Pleistocene Yedoma permafrost and Holocene cover deposits, discontinuously spanning the last similar to 52 kyr. We showed that the ancient permafrost exposed in the Sobo-Sise cliff has a high organic carbon content (mean of about 5 wt %). The oldest sediments stem from Marine Isotope Stage (MIS) 3 interstadial deposits (dated to 52 to 28 cal ka BP) and are overlaid by last glacial MIS 2 (dated to 28 to 15 cal ka BP) and Holocene MIS 1 (dated to 7-0 cal ka BP) deposits. The relatively high average chain length (ACL) index of n-alkanes along the cliff profile indicates a predominant contribution of vascular plants to the OM composition. The elevated ratio of isoand anteiso-branched fatty acids (FAs) relative to mid- and long-chain (C >= 20) n-FAs in the interstadial MIS 3 and the interglacial MIS 1 deposits suggests stronger microbial activity and consequently higher input of bacterial biomass during these climatically warmer periods. The overall high carbon preference index (CPI) and higher plant fatty acid (HPFA) values as well as high C/N ratios point to a good quality of the preserved OM and thus to a high potential of the OM for decomposition upon thaw. A decrease in HPFA values downwards along the profile probably indicates stronger OM decomposition in the oldest (MIS 3) deposits of the cliff. The characterisation of OM from eroding permafrost leads to a better assessment of the greenhouse gas potential of the OC released into river and nearshore waters in the future. Y1 - 2022 U6 - https://doi.org/10.5194/bg-19-2079-2022 SN - 1726-4170 SN - 1726-4189 VL - 19 IS - 7 SP - 2079 EP - 2094 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Voglimacci-Stephanopoli, Joëlle A1 - Wendleder, Anna A1 - Lantuit, Hugues A1 - Langlois, Alexandre A1 - Stettner, Samuel A1 - Schmitt, Andreas A1 - Dedieu, Jean-Pierre A1 - Roth, Achim A1 - Royer, Alain T1 - Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation JF - Cryosphere N2 - Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar - SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015-2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30 circle) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types. Y1 - 2022 U6 - https://doi.org/10.5194/tc-16-2163-2022 SN - 1994-0416 SN - 1994-0424 VL - 16 IS - 6 SP - 2163 EP - 2181 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Kaya, Mustafa Yücel A1 - Dupont-Nivet, Guillaume A1 - Frieling, Joost A1 - Fioroni, Chiara A1 - Rohrmann, Alexander A1 - Altıner, Sevinç Özkan A1 - Vardar, Ezgi A1 - Tanyas, Hakan A1 - Mamtimin, Mehmut A1 - Zhaojie, Guo T1 - The Eurasian epicontinental sea was an important carbon sink during the Palaeocene-Eocene thermal maximum JF - Communications earth and environment N2 - The Palaeocene-Eocene Thermal Maximum (ca. 56 million years ago) offers a primary analogue for future global warming and carbon cycle recovery. Yet, where and how massive carbon emissions were mitigated during this climate warming event remains largely unknown. Here we show that organic carbon burial in the vast epicontinental seaways that extended over Eurasia provided a major carbon sink during the Palaeocene-Eocene Thermal Maximum. We coupled new and existing stratigraphic analyses to a detailed paleogeographic framework and using spatiotemporal interpolation calculated ca. 720–1300 Gt organic carbon excess burial, focused in the eastern parts of the Eurasian epicontinental seaways. A much larger amount (2160–3900 Gt C, and when accounting for the increase in inundated shelf area 7400–10300 Gt C) could have been sequestered in similar environments globally. With the disappearance of most epicontinental seas since the Oligocene-Miocene, an effective negative carbon cycle feedback also disappeared making the modern carbon cycle critically dependent on the slower silicate weathering feedback. Y1 - 2022 U6 - https://doi.org/10.1038/s43247-022-00451-4 SN - 2662-4435 VL - 3 IS - 1 PB - Springer Nature CY - London ER - TY - JOUR A1 - Albrecht, Torsten A1 - Winkelmann, Ricarda A1 - Levermann, Anders T1 - Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) BT - Part 1: boundary conditions and climatic forcing JF - The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union N2 - Simulations of the glacial-interglacial history of the Antarctic Ice Sheet provide insights into dynamic threshold behavior and estimates of the ice sheet's contributions to global sea-level changes for the past, present and future. However, boundary conditions are weakly constrained, in particular at the interface of the ice sheet and the bedrock. Also climatic forcing covering the last glacial cycles is uncertain, as it is based on sparse proxy data.
We use the Parallel Ice Sheet Model (PISM) to investigate the dynamic effects of different choices of input data, e.g., for modern basal heat flux or reconstructions of past changes of sea level and surface temperature. As computational resources are limited, glacial-cycle simulations are performed using a comparably coarse model grid of 16 km and various parameterizations, e.g., for basal sliding, iceberg calving, or for past variations in precipitation and ocean temperatures. In this study we evaluate the model's transient sensitivity to corresponding parameter choices and to different boundary conditions over the last two glacial cycles and provide estimates of involved uncertainties. We also discuss isolated and combined effects of climate and sea-level forcing. Hence, this study serves as a "cookbook" for the growing community of PISM users and paleo-ice sheet modelers in general.
For each of the different model uncertainties with regard to climatic forcing, ice and Earth dynamics, and basal processes, we select one representative model parameter that captures relevant uncertainties and motivates corresponding parameter ranges that bound the observed ice volume at present. The four selected parameters are systematically varied in a parameter ensemble analysis, which is described in a companion paper. Y1 - 2020 U6 - https://doi.org/10.5194/tc-14-599-2020 SN - 1994-0416 SN - 1994-0424 VL - 14 IS - 2 SP - 599 EP - 632 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Inceoglu, Fadil A1 - Shprits, Yuri A1 - Heinemann, Stephan G. A1 - Bianco, Stefano T1 - Identification of coronal holes on AIA/SDO images using unsupervised machine learning JF - The astrophysical journal : an international review of spectroscopy and astronomical physics N2 - Through its magnetic activity, the Sun governs the conditions in Earth's vicinity, creating space weather events, which have drastic effects on our space- and ground-based technology. One of the most important solar magnetic features creating the space weather is the solar wind that originates from the coronal holes (CHs). The identification of the CHs on the Sun as one of the source regions of the solar wind is therefore crucial to achieve predictive capabilities. In this study, we used an unsupervised machine-learning method, k-means, to pixel-wise cluster the passband images of the Sun taken by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory in 171, 193, and 211 angstrom in different combinations. Our results show that the pixel-wise k-means clustering together with systematic pre- and postprocessing steps provides compatible results with those from complex methods, such as convolutional neural networks. More importantly, our study shows that there is a need for a CH database where a consensus about the CH boundaries is reached by observers independently. This database then can be used as the "ground truth," when using a supervised method or just to evaluate the goodness of the models. Y1 - 2022 U6 - https://doi.org/10.3847/1538-4357/ac5f43 SN - 1538-4357 VL - 930 IS - 2 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Smirnov, Artem G. A1 - Kronberg, Elena A. A1 - Daly, Patrick W. A1 - Aseev, Nikita A1 - Shprits, Yuri A1 - Kellerman, Adam C. T1 - Adiabatic Invariants Calculations for Cluster Mission: A Long-Term Product for Radiation Belts Studies JF - Journal of Geophysical Research: Space Physics N2 - The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes. KW - L-Asterisk KW - magnetosphere KW - electrons KW - model Y1 - 2019 VL - 125 IS - 2 PB - John Wiley & Sons, Inc. CY - New Jersey ER - TY - JOUR A1 - Landis, Daji August A1 - Saikin, Anthony A1 - Zhelavskaya, Irina A1 - Drozdov, Alexander A1 - Aseev, Nikita A1 - Shprits, Yuri A1 - Pfitzer, Maximilian F. A1 - Smirnov, Artem G. T1 - NARX Neural Network Derivations of the Outer Boundary Radiation Belt Electron Flux JF - Space Weather: the international journal of research and applications N2 - We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used. KW - radiation belts KW - forecasting (1922, 4315, 7924, 7964) KW - machine learning (0555) Y1 - 2022 U6 - https://doi.org/10.1029/2021SW002774 SN - 1542-7390 VL - 20 IS - 5 PB - American Geophysical Union CY - Washington ER -