33 research outputs found

    Global Characteristics of the Correlation and Time Lag Between Solar and Ionospheric Parameters in the 27-day Period

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    The 27-day variations of topside ionosphere are investigated using the in-situ electron density measurements from the CHAMP planar Langmuir probe and GRACE K-band ranging system. As the two satellite systems orbit at the altitudes of approx. 370 km and approx. 480 km, respectively, the satellite data sets are greatly valuable for examining the electron density variations in the vicinity of F2-peak. In a 27-day period, the electron density measurements from the satellites are in good agreements with the solar flux, except during the solar minimum period. The time delays are mostly 1-2 day and represent the hemispherical asymmetry. The globally-estimated spatial patterns of the correlation between solar flux and in-situ satellite measurements show poor correlations in the (magnetic) equatorial region, which are not found from the ground measurements of vertically-integrated electron content. We suggest that the most plausible cause for the poor correlation is the vertical movement of ionization due to atmospheric dynamic processes that is not controlled by the solar extreme ultraviolet radiation

    Ice Velocity Mapping of Ross Ice Shelf, Antarctica by Matching Surface Undulations Measured by Icesat Laser Altimetry

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    We present a novel method for estimating the surface horizontal velocity on ice shelves using laser altimetrydata from the Ice Cloud and land Elevation Satellite (ICESat; 20032009). The method matches undulations measured at crossover points between successive campaigns

    Active subglacial lakes and channelized water flow beneath the Kamb Ice Stream

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    We identify two previously unknown subglacial lakes beneath the stagnated trunk of the Kamb Ice Stream (KIS). Rapid fill-drain hydrologic events over several months are inferred from surface height changes measured by CryoSat-2 altimetry and indicate that the lakes are probably connected by a subglacial drainage network, whose structure is inferred from the regional hydraulic potential and probably links the lakes. The sequential fill-drain behavior of the subglacial lakes and concurrent rapid thinning in a channel-like topographic feature near the grounding line implies that the subglacial water repeatedly flows from the region above the trunk to the KIS grounding line and out beneath the Ross Ice Shelf. Ice shelf elevation near the hypothesized outlet is observed to decrease slowly during the study period. Our finding supports a previously published conceptual model of the KIS shutdown stemming from a transition from distributed flow to well-drained channelized flow of subglacial water. However, a water-piracy hypothesis in which the KIS subglacial water system is being starved by drainage in adjacent ice streams is also supported by the fact that the degree of KIS trunk subglacial lake activity is relatively weaker than those of the upstream lakes.OAIID:RECH_ACHV_DSTSH_NO:T201501631RECH_ACHV_FG:RR00200001ADJUST_YN:EMP_ID:A079127CITE_RATE:4.906FILENAME:2016_Kim_TC.pdfDEPT_NM:지구과학교육과EMAIL:[email protected]_YN:YFILEURL:https://srnd.snu.ac.kr/eXrepEIR/fws/file/0f782ccb-87d7-4af5-89fc-9ed5599fd0f7/linkCONFIRM:

    Encoder-decoder multimodal speaker change detection

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    The task of speaker change detection (SCD), which detects points where speakers change in an input, is essential for several applications. Several studies solved the SCD task using audio inputs only and have shown limited performance. Recently, multimodal SCD (MMSCD) models, which utilise text modality in addition to audio, have shown improved performance. In this study, the proposed model are built upon two main proposals, a novel mechanism for modality fusion and the adoption of a encoder-decoder architecture. Different to previous MMSCD works that extract speaker embeddings from extremely short audio segments, aligned to a single word, we use a speaker embedding extracted from 1.5s. A transformer decoder layer further improves the performance of an encoder-only MMSCD model. The proposed model achieves state-of-the-art results among studies that report SCD performance and is also on par with recent work that combines SCD with automatic speech recognition via human transcription.Comment: 5 pages, accepted for presentation at INTERSPEECH 202

    Mass balance of the Greenland Ice Sheet from 1992 to 2018

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    In recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise1,2, and it is expected to be so in the future3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions15 and as ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario17, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate

    Constrained Linear Deconvolution of GRACE Anomalies to Correct Spatial Leakage

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    Time-varying gravity observed by the Gravity Recovery and Climate Experiment (GRACE) satellites measures surface water and ice mass redistribution driven by weather and climate forcing and has emerged as one of the most important data types in measuring changes in Earth’s climate. However, spatial leakage of GRACE signals, especially in coastal areas, has been a recognized limitation in quantitatively assessing mass change. It is evident that larger terrestrial signals in coastal regions spread into the oceans and vice versa and various remedies have been developed to address this problem. An especially successful one has been Forward Modeling but it requires knowledge of geographical locations of mass change to be fully effective. In this study, we develop a new method to suppress leakage effects using a linear least squares operator applied to GRACE spherical harmonic data. The method is effectively a constrained deconvolution of smoothing inherent in GRACE data. It assumes that oceanic mass changes near the coast are negligible compared to terrestrial changes, with additional spatial regularization constraints. Some calibration of constraint weighting is required. We apply the method to estimate surface mass loads over Australia using both synthetic and real GRACE data. Leakage into the oceans is effectively suppressed and when compared with mascon solutions there is better performance over interior basins

    Antarctic ice mass variations from 1979 to 2017 driven by anomalous precipitation accumulation

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    Antarctic ice mass balance is determined by precipitation and ice discharge, and understanding their relative contributions to contemporary Antarctic ice mass change is important to project future ice mass loss and resulting sea level rise. There has been evidence that anomalous precipitation affects Antarctic ice mass loss estimates, and thus the precipitation contribution should be understood and considered in future projections. In this study, we revisit changes in Antarctic ice mass over recent decades and examine precipitation contributions over this period. We show that accumulated (time-integrated) precipitation explains most inter-annual anomalies of Antarctic ice mass change during the GRACE period (2003-2017). From 1979 to 2017, accumulated Antarctic precipitation contributes to significant ice mass loss acceleration in the Pacific sector and deceleration in the Atlantic-Indian Sectors, forming a bi-polar spatial pattern. Principal component analysis reveals that such a bi-polar pattern is likely modulated by the Southern Annular Mode (SAM). We also find that recent ice mass loss acceleration in 2007 is related to a variation in precipitation accumulation. Overall ice discharge has accelerated at a steady rate since 1992, but has not seen a recent abrupt increase.Y
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