Martin Horwath

Prof. Martin Horwath

TECHNISCHE UNIVERSITÄT DRESDEN
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Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 April 2023 in Earth System Science Data
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IOInès N. Otosaka
Inès N. Otosaka
ASAndrew Shepherd
Andrew Shepherd
EIErik R. Ivins
Erik R. Ivins
NSNicole-Jeanne Schlegel
Nicole-Jeanne Schlegel
CACharles Amory
Charles Amory
BWBert Wouters
Bert Wouters
Ice losses from the Greenland and Antarctic ice sheets have accelerated since the 1990s, accounting for a significant increase in the global mean sea level. Here, we present a new 29-year record of ice sheet mass balance from 1992 to 2020 from the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE). We compare and combine 50 independent estimates of ice sheet mass balance derived from satellite observations of temporal changes in ice sheet flow, in ice sheet volume, and in Earth's gravity field. Between 1992 and 2020, the ice sheets contributed 21.0±1.9 mm to global mean sea level, with the rate of mass loss rising from 105 Gt yr −1 between 1992 and 1996 to 372 Gt yr −1 between 2016 and 2020. In Greenland, the rate of mass loss is 169±9 Gt yr −1 between 1992 and 2020, but there are large inter-annual variations in mass balance, with mass loss ranging from 86 Gt yr −1 in 2017 to 444 Gt yr −1 in 2019 due to large variability in surface mass balance. In Antarctica, ice losses continue to be dominated by mass loss from West Antarctica (82±9 Gt yr −1 ) and, to a lesser extent, from the Antarctic Peninsula (13±5 Gt yr −1 ). East Antarctica remains close to a state of balance, with a small gain of 3±15 Gt yr −1 , but is the most uncertain component of Antarctica's mass balance. The dataset is publicly available at https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452 (IMBIE Team, 2021).

5 February 2019 in The Cryosphere
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LSLudwig Schröder
Ludwig Schröder
MHMartin Horwath
Martin Horwath
RDReinhard Dietrich
Reinhard Dietrich
VHVeit Helm
Veit Helm
MBMichiel Van den Broeke
Michiel Van den Broeke
SLStefan R. M. Ligtenberg
Stefan R. M. Ligtenberg
We developed a multi-mission satellite altimetry analysis over the Antarctic Ice Sheet which comprises Seasat, Geosat, ERS-1, ERS-2, Envisat, ICESat and CryoSat-2. After a consistent reprocessing and a stepwise calibration of the inter-mission offsets, we obtained monthly grids of multi-mission surface elevation change (SEC) with respect to the reference epoch 09/2010 (in the format of month/year) from 1978 to 2017. A validation with independent elevation changes from in situ and airborne observations as well as a comparison with a firn model proves that the different missions and observation modes have been successfully combined to a seamless multi-mission time series. For coastal East Antarctica, even Seasat and Geosat provide reliable information and, hence, allow for the analysis of four decades of elevation changes. The spatial and temporal resolution of our result allows for the identification of when and where significant changes in elevation occurred. These time series add detailed information to the evolution of surface elevation in such key regions as Pine Island Glacier, Totten Glacier, Dronning Maud Land or Lake Vostok. After applying a density mask, we calculated time series of mass changes and found that the Antarctic Ice Sheet north of 81.5∘ S was losing mass at an average rate of -85±16 Gt yr−1 between 1992 and 2017, which accelerated to -137±25 Gt yr−1 after 2010.

7 February 2022 in Earth System Science Data
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MHMartin Horwath
Martin Horwath
BGBenjamin D. Gutknecht
Benjamin D. Gutknecht
ACAnny Cazenave
Anny Cazenave
HPHindumathi Kulaiappan Palanisamy
Hindumathi Kulaiappan Palanisamy
FMFlorence Marti
Florence Marti
Jérôme BenvenisteJérôme Benveniste
Jérôme Benveniste
Studies of the global sea-level budget (SLB) and the global ocean-mass budget (OMB) are essential to assess the reliability of our knowledge of sea-level change and its contributors. Here we present datasets for times series of the SLB and OMB elements developed in the framework of ESA's Climate Change Initiative. We use these datasets to assess the SLB and the OMB simultaneously, utilising a consistent framework of uncertainty characterisation. The time series, given at monthly sampling and available at https://doi.org/10.5285/17c2ce31784048de93996275ee976fff (Horwath et al., 2021), include global mean sea-level (GMSL) anomalies from satellite altimetry, the global mean steric component from Argo drifter data with incorporation of sea surface temperature data, the ocean-mass component from Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry, the contribution from global glacier mass changes assessed by a global glacier model, the contribution from Greenland Ice Sheet and Antarctic Ice Sheet mass changes assessed by satellite radar altimetry and by GRACE, and the contribution from land water storage anomalies assessed by the global hydrological model WaterGAP (Water Global Assessment and Prognosis). Over the period January 1993–December 2016 (P1, covered by the satellite altimetry records), the mean rate (linear trend) of GMSL is 3.05 ± 0.24 mm yr−1. The steric component is 1.15 ± 0.12 mm yr−1 (38 % of the GMSL trend), and the mass component is 1.75 ± 0.12 mm yr−1 (57 %). The mass component includes 0.64 ± 0.03 mm yr−1 (21 % of the GMSL trend) from glaciers outside Greenland and Antarctica, 0.60 ± 0.04 mm yr−1 (20 %) from Greenland, 0.19 ± 0.04 mm yr−1 (6 %) from Antarctica, and 0.32 ± 0.10 mm yr−1 (10 %) from changes of land water storage. In the period January 2003–August 2016 (P2, covered by GRACE and the Argo drifter system), GMSL rise is higher than in P1 at 3.64 ± 0.26 mm yr−1. This is due to an increase of the mass contributions, now about 2.40 ± 0.13 mm yr−1 (66 % of the GMSL trend), with the largest increase contributed from Greenland, while the steric contribution remained similar at 1.19 ± 0.17 mm yr−1 (now 33 %). The SLB of linear trends is closed for P1 and P2; that is, the GMSL trend agrees with the sum of the steric and mass components within their combined uncertainties. The OMB, which can be evaluated only for P2, shows that our preferred GRACE-based estimate of the ocean-mass trend agrees with the sum of mass contributions within 1.5 times or 0.8 times the combined 1σ uncertainties, depending on the way of assessing the mass contributions. Combined uncertainties (1σ) of the elements involved in the budgets are between 0.29 and 0.42 mm yr−1, on the order of 10 % of GMSL rise. Interannual variations that overlie the long-term trends are coherently represented by the elements of the SLB and the OMB. Even at the level of monthly anomalies the budgets are closed within uncertainties, while also indicating possible origins of remaining misclosures.

29 April 2021 in Remote Sensing
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AGA. Groh
A. Groh
MHMartin Horwath
Martin Horwath
We derived gravimetric mass change products, i.e., gridded and basin-averaged mass changes, for the Antarctic Ice Sheet (AIS) from time-variable gravity-field solutions acquired by the Gravity Recovery and Climate Experiment (GRACE) mission and its successor GRACE-FO, covering more than 18 years. For this purpose, tailored sensitivity kernels (TSKs) were generated for the application in a regional integration approach. The TSKs were inferred in a formal optimization approach minimizing the sum of both propagated mission errors and leakage errors. We accounted for mission errors by means of an empirical error covariance model, while assumptions on signal variances of potential sources of leakage were used to minimize leakage errors. To identify the optimal parameters to be used in the TSK generation, we assessed a set of TSKs by quantifying signal leakage from the processing of synthetic data and by inferring the noise level of the derived basin products. The finally selected TSKs were used to calculate mass change products from GRACE/GRACE-FO Level-2 spherical harmonic solutions covering 2002-04 to 2020-07. These products were compared to external data sets from satellite altimetry and the input–output method. For the period under investigation, the mass balance of the AIS was quantified to be −90.9±43.5 Gt a−1, corresponding to a mean sea-level rise of 0.25±0.12 mm a−1.

28 November 2017 in Water Resources Research
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BVBramha Dutt Vishwakarma
Bramha Dutt Vishwakarma
MHMartin Horwath
Martin Horwath
BDBalaji Devaraju
Balaji Devaraju
AGA. Groh
A. Groh
NSNico Sneeuw
Nico Sneeuw

25 September 2019 in Geosciences
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AGA. Groh
A. Groh
MHMartin Horwath
Martin Horwath
AHAlexander Horvath
Alexander Horvath
RMRakia Meister
Rakia Meister
LSLouise Sandberg Sørensen
Louise Sandberg Sørensen
ASAndrew Shepherd
Andrew Shepherd
Satellite gravimetry data acquired by the Gravity Recovery and Climate Experiment (GRACE) allows to derive the temporal evolution in ice mass for both the Antarctic Ice Sheet (AIS) and the Greenland Ice Sheet (GIS). Various algorithms have been used in a wide range of studies to generate Gravimetric Mass Balance (GMB) products. Results from different studies may be affected by substantial differences in the processing, including the applied algorithm, the utilised background models and the time period under consideration. This study gives a detailed description of an assessment of the performance of GMB algorithms using actual GRACE monthly solutions for a prescribed period as well as synthetic data sets. The inter-comparison exercise was conducted in the scope of the European Space Agency’s Climate Change Initiative (CCI) project for the AIS and GIS, and was, for the first time, open to everyone. GMB products generated by different groups could be evaluated and directly compared against each other. For the period from 2003-02 to 2013-12, estimated linear trends in ice mass vary between −99 Gt/yr and −108 Gt/yr for the AIS and between −252 Gt/yr and −274 Gt/yr for the GIS, respectively. The spread between the solutions is larger if smaller drainage basins or gridded GMB products are considered. Finally, findings from the exercise formed the basis to select the algorithms used for the GMB product generation within the AIS and GIS CCI project.