S U M M A R YThe DEOS Mass Transport release 1 (DMT-1) model has been produced on the basis of intersatellite K-band ranging data acquired by the GRACE satellite mission. The functional model exploited in the data processing can be considered as a variant of the acceleration approach. Each element of the data vector is defined as a linear combination of three successive range measurements and can be interpreted as the line-of-sight projection of a weighted average of intersatellite accelerations. As such, the data vector can be directly linked to parameters of the gravitational field. In this way, a series of unconstrained monthly gravity field solutions is produced, each of which is defined as a set of spherical harmonic coefficients complete to degree 120. At the post-processing stage, the unconstrained solutions are filtered with a statistically optimal Wiener-type filter based on full covariance matrices of noise and signal. As such, the DMT-1 model is free from along-track artefacts, which are typical for many other GRACE gravity models. The accuracy of the DMT-1 model has been analysed in different ways. First, the signals observed in areas with minimal mass variations (Sahara, East Antarctica and the middle of the Pacific Ocean) are analysed and interpreted as an upper bound of the noise in the DMT-1 model. It is concluded that the pointwise errors after filtering are of the order of 2-3 cm in terms of equivalent water heights. For the mean mass variations in an area of 10 6 km 2 , the corresponding error reduces to 1.5-2 cm. Second, a time-series of mass variations in the Marie Byrd Land (Antarctica) has been analysed, where the true signal (mostly caused by postglacial rebound) is expected to be close to a linear trend. The rms of the post-fit residuals is found to be 3.3 cm, which is consistent with the error analysis in areas with minimal mass variations. Thirdly, the DMT-1 model has been applied to estimate mass variations in [2003][2004][2005][2006] in Lake Victoria (Africa), where a large drop of water level is observed in recent years. The obtained linear trend (−31 ± 3 cm yr −1 ) is in good agreement with that derived from the satellite altimetry data (−35 ± 1 cm yr −1 ).
Silva, R.; van Tussenbroek, B.I.; Escudero-Castillo, M.; Mariño-Tapia, I.; Dijkstra, H.A.; van Westen, R.M.; Pietrzak, J.D.; Candy, A.S.; Katsman, C.A.; van der Boog, C.G.; Riva, R.E.M.; Slobbe, C.; Klees, R.; Stapel, J.; van der Heide, T.; van Katwijk, M.M.; Herman, P.M.J. & Bouma, T.J. (2019). Maintaining tropical beaches with seagrass and algae: a promising alternative to engineering solutions. BioScience, 69, 136-142 is available online at: https://dx.
Rising sea levels due to climate change can have severe consequences for coastal populations and ecosystems all around the world. Understanding and projecting sea-level rise is especially important for low-lying countries such as the Netherlands. It is of specific interest for vulnerable ecological and morphodynamic regions, such as the Wadden Sea UNESCO World Heritage region.Here we provide an overview of sea-level projections for the 21st century for the Wadden Sea region and a condensed review of the scientific data, understanding and uncertainties underpinning the projections. The sea-level projections are formulated in the framework of the geological history of the Wadden Sea region and are based on the regional sea-level projections published in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). These IPCC AR5 projections are compared against updates derived from more recent literature and evaluated for the Wadden Sea region. The projections are further put into perspective by including interannual variability based on long-term tide-gauge records from observing stations at Den Helder and Delfzijl.We consider three climate scenarios, following the Representative Concentration Pathways (RCPs), as defined in IPCC AR5: the RCP2.6 scenario assumes that greenhouse gas (GHG) emissions decline after 2020; the RCP4.5 scenario assumes that GHG emissions peak at 2040 and decline thereafter; and the RCP8.5 scenario represents a continued rise of GHG emissions throughout the 21st century. For RCP8.5, we also evaluate several scenarios from recent literature where the mass loss in Antarctica accelerates at rates exceeding those presented in IPCC AR5.For the Dutch Wadden Sea, the IPCC AR5-based projected sea-level rise is 0.07±0.06m for the RCP4.5 scenario for the period 2018–30 (uncertainties representing 5–95%), with the RCP2.6 and RCP8.5 scenarios projecting 0.01m less and more, respectively. The projected rates of sea-level change in 2030 range between 2.6mma−1for the 5th percentile of the RCP2.6 scenario to 9.1mma−1for the 95th percentile of the RCP8.5 scenario. For the period 2018–50, the differences between the scenarios increase, with projected changes of 0.16±0.12m for RCP2.6, 0.19±0.11m for RCP4.5 and 0.23±0.12m for RCP8.5. The accompanying rates of change range between 2.3 and 12.4mma−1in 2050. The differences between the scenarios amplify for the 2018–2100 period, with projected total changes of 0.41±0.25m for RCP2.6, 0.52±0.27m for RCP4.5 and 0.76±0.36m for RCP8.5. The projections for the RCP8.5 scenario are larger than the high-end projections presented in the 2008 Delta Commission Report (0.74m for 1990–2100) when the differences in time period are considered. The sea-level change rates range from 2.2 to 18.3mma−1for the year 2100.We also assess the effect of accelerated ice mass loss on the sea-level projections under the RCP8.5 scenario, as recent literature suggests that there may be a larger contribution from Antarctica than presented in IPCC AR5 (potentially exceeding 1m in 2100). Changes in episodic extreme events, such as storm surges, and periodic (tidal) contributions on (sub-)daily timescales, have not been included in these sea-level projections. However, the potential impacts of these processes on sea-level change rates have been assessed in the report.
S U M M A R YThe focus of this paper is on the quantification of ongoing mass and volume changes over the Greenland ice sheet. For that purpose, we used elevation changes derived from the Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry mission and monthly variations of the Earth's gravity field as observed by the Gravity Recovery and Climate Experiment (GRACE) mission.Based on a stand alone processing scheme of ICESat data, the most probable estimate of the mass change rate from 2003 February to 2007 April equals −139 ± 68 Gton yr −1 . Here, we used a density of 600 ± 300 kg m −3 to convert the estimated elevation change rate in the region above 2000 m into a mass change rate. For the region below 2000 m, we used a density of 900 ± 300 kg m −3 .Based on GRACE gravity models from half 2002 to half 2007 as processed by CNES, CSR, DEOS and GFZ, the estimated mass change rate for the whole of Greenland ranges between −128 and −218 Gton yr −1 .Most GRACE solutions show much stronger mass losses as obtained with ICESat, which might be related to a local undersampling of the mass loss by ICESat and uncertainties in the used snow/ice densities.To solve the problem of uncertainties in the snow and ice densities, two independent joint inversion concepts are proposed to profit from both GRACE and ICESat observations simultaneously. The first concept, developed to reduce the uncertainty of the mass change rate, estimates this rate in combination with an effective snow/ice density. However, it turns out that the uncertainties are not reduced, which is probably caused by the unrealistic assumption that the effective density is constant in space and time. The second concept is designed to convert GRACE and ICESat data into two totally new products: variations of ice volume and variations of snow volume separately. Such an approach is expected to lead to new insights in ongoing mass change processes over the Greenland ice sheet. Our results show for different GRACE solutions a snow volume change of −11 to 155 km 3 yr −1 and an ice loss with a rate of −136 to −292 km 3 yr −1 .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.