validation report (vr) (d3.2) · figure 1.2: map of antarctica indicating the geographic regions...

Regional glacial isostatic adjustment and

CryoSat elevation rate corrections in Antarctica (REGINA)

Validation Report (VR) (D3.2)

The REGINA consortium German Research Centre for Geosciences (GFZ)

Newcastle University (NCL) TU München (IAPG)

University of Bristol (UOB) Email: [email protected]

www.regina-science.eu

ESA ITT Ref.: EOP-SA/0175/DFP-dfp Tender: AO 1-7158

Contract-Nr.: 4000107393/12/I-NB Issue: 2.2

Date: December 21, 2014 Ref.: REGINA_D3_2_Issue_2.2

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Document history: REGINA_D3_2_issue_1.0: First version sent to Mark Drinkwater REGINA_D3_2_issue_1.1: Update based on comments by M. Drinkwater, ESA REGINA_D3_2_issue_2.1: Final draft REGINA_D3_2_issue_2.2: Final document for publication

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Table of contents

0 Preface ............................................................................................................. 4

1 Introduction ..................................................................................................... 6

2 Validation of GIA fields from REGINA ............................................................... 7

2.1 Spectral rate of geoid-height change ............................................................................. 8

2.2 Spatial rate of geoid-height change ............................................................................... 9

2.3 Spectral rate of radial displacement ............................................................................ 11

2.3.1 Apparent smoothing for “thick” lithospheres................................................................. 12

2.3.2 Magnitude of uplift for “thin” lithospheres .................................................................... 12

2.3.3 Effect of ductile layer ...................................................................................................... 13

2.4 Spatial rate of radial displacement .............................................................................. 14

3 Concluding remarks ........................................................................................ 17

4 References ..................................................................................................... 17

Appendix ............................................................................................................. 19

A1. Additional simulations ................................................................................................ 19

A2. Earth model parameters ............................................................................................. 21

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0 Preface

Purpose of this document

The project REGINA (www.regina-science.eu) funded by the Support To Science Element (STSE) of the European Space Agency (ESA) aims at improving land-elevation rate corrections for CryoSat due to glacial-isostatic adjustment (GIA) for Antarctica, employing multiple space-geodetic data and numerical modeling. This document is the Validation Report (VR), presenting the experimental error analysis and validation activities of the developed GIA estimate.

Applicable documentation

In addition to published literature, the following applicable documents [AD] developed during the study are cited in this report and can be obtained upon request from the REGINA project PI:

[AD-1] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Requirements Baseline for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 1.1, Doc. Ref. REGINA_D1_1_issue_1.1, http://dep1doc.gfz-potsdam.de/documents/46, www.regina-science.eu.

[AD-2] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Dataset User Manual (D2.2) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 2.2, Doc. Ref. REGINA_D2_2_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/47, www.regina-science.eu.

[AD-3] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Algorithm Theoretical Basis Document (D3.1) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 2.0, Doc. Ref. REGINA_D3_1_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/56, www.regina-science.eu.

[AD-4] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Validation Report (D3.2) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 2.2, Doc. Ref. REGINA_D3_2_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/61, www.regina-science.eu.

[AD-5] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Impact Assessment Report (D5.1) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 2.2, Doc. Ref. REGINA_D5_1_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/62, www.regina-science.eu.

[AD-6] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Scientific Roadmap (D5.2) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica, Issue 2.2, Doc. Ref. REGINA_D5_2_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/69, www.regina-science.eu.

[AD-7] Sasgen, I. & the REGINA Consortium (2014): ESA ITT CryoSat+ REGINA: Final Report (D6.1) for determining Regional glacial isostatic adjustment and CryoSat elevation rate corrections

http://dep1doc.gfz-potsdam.de/documents/46


http://www.regina-science.eu/














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in Antarctica, Issue 2.2, Doc. Ref. REGINA_D6_1_issue_2.2, http://dep1doc.gfz-potsdam.de/documents/70, www.regina-science.eu.

Section overview and relation to requirement baselines

Section 1 gives a brief introduction into the approaches towards determining GIA in Antarctica. More information can be found in [AD-1] and [AD-2].

Section 2 describes the activities taken in validate the ensemble of GIA estimates resulting from REGINA using published GIA corrections (Baseline Requirement [GI01] in [AD-1]).

Section 3 provides concluding remarks.

Appendix A lists the Earth model parameters as described in the ATBD [AD-3] underlying the elastic viscoelastic kernels [GI03]. In addition, GIA predictions based on the glacial history of Pollard & DeConto 2013 are shown, as well as a list of data sets relevant for this validation.




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1 Introduction

The validation activities presented in this report address the comparability of the resulting REGINA GIA fields to published GIA corrections. There are two basic approaches for determining the GIA signals in Antarctica (Fig. 1.1).

First, numerical models of the dynamic behavior of the ice sheets and the solid Earth, ideally, coupled to each other, are used to predict surface-displacement and gravity field changes (e.g. Whitehouse et al. 2012; Ivins et al. 2013). Input data of these models are the past evolution of the ice sheets, either constrained by geomorphological data and / or dynamically modelled subject to atmospheric and oceanic climate forcing. Parameters governing the behavior of ice / solid Earth system are the thermomechanical properties of ice, as well as the viscoelastic rheology of the Earth. Examples for geomorphological constraints are trim lines, cosmogenic exposure dates and relative sea-level curves.

An alternative approach of determining Antarctic GIA is to make use of the different signatures and sensitivities of elastic and viscoelastic processes in the satellite-geodetic data of bedrock deformation, ice-sheet elevation changes and gravity changes (e.g. Riva et al., 2009). This approach has been followed within the REGINA project (ATBD, [AD-3]). Some estimates rely on information from GIA predictions (e.g. the regional spatial pattern) and include it in the estimation procedure (e.g. Sasgen et al. 2013)

Figure 1.1: Overview of the two main approaches towards determining GIA in Antarctica and the attribution of the validation data sets to these concepts.

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Figure 1.2: Map of Antarctica indicating the geographic regions mentioned in the text. Additionally, the 25 drainage basins are shown, which will be addressed in detail in the Impact Assessment Report (IAR; [AD-5]).

2 Validation of GIA fields from REGINA

In the following section, the REGINA GIA fields are compared with published GIA predictions and estimates of Baseline Requirement [GI01] ([AD-2], Section 4 and Table 1; [AD-3], Table 0.1); namely, W12a (Whitehouse et al. 2012), IJ05 R2 (Ivins et al. 2013), RIVA09 (Riva et al. 2009) and AGE1 (Sasgen et al. 2013). The comparison addresses the rate of geoid-height change (Sections 2.1 and 2.2) and rate of radial displacement (Section 2.3 and 2.4), both in the spectral and spatial domains, respectively. Please note that geoid rates for IJ05 R2 and RIVA09 are not available to REGINA and excluded in the comparison.

The REGINA fields shown rely on the gravimetry [GR04], altimetry [AL01] & [AL02] and GPS data [GP04] & [GP05] and various viscoelastic response kernels [GI03] (Appendix, Table 3.1). For the examples presented below, the spatial coverage of the GPS derived radial displacement rates is limited to those locations with most reliable non-zero trends as in the ATBD [AD-3] (49 sites out of 85 sites; GPS A, see Appendix A.3 [AD-5]). Although, the derived GIA fields may vary depending on which set of GPS rates is considered, the variability is sufficiently small to allow the choice of one representative example for this validation exercise. A more detailed assessment of the influence of the input data set on the GIA fields is presented in the Impact Assessment Report (IAR [AD-5]).

In addition, in the equilibrium state of the GIA response to the ongoing loading (see [AD-3], Section 4), the resulting viscoelastic kernels only depend on the thickness of the elastic lithosphere ℎ𝑙 and not on the upper- and lower mantle viscosities, 𝜂𝑈𝑀 | 𝑙𝑀. Therefore, the comparison is

limited to taking the lithosphere thickness at 30 km, 40 km, … , 90 km, 150 km and 200 km (see Table A.2) in the equilibrium simulations.

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Figure 2.1: Degree-power spectrum of the rate of geoid-height change (mm/yr) for the Antarctic REGINA GIA fields obtained assuming different lithosphere thicknesses West Antarctica (red to blue curves) with (solid) and without (dashed) the ductile layer, as well as the minimum and maximum degree-power of the published GIA fields W12 and AGE1 (grey shaded area).

Throughout this report, the reference GIA estimate based on the data sets specified above is termed RE000, if necessary together with the lithospheric thickness, e.g. RE000-090 is the reference GIA estimate relying on a lithosphere thickness of 90 km (sim. #25 without ductile layer and sim. #53 with ductile layer; Table A.1).

2.1 Spectral rate of geoid-height change

Figure 2.1 shows the degree-power spectrum of the rate of geoid-height change for the ensemble of REGINA GIA estimates RE000 with different lithosphere thicknesses in comparison to two published GIA estimates. It is visible that the power at degrees 𝑗 < 20 (ca. 1000 km) is lower in RE000 than in the published data sets. Above this degree, the power spectrum follows the upper limit of the published data sets, here mainly representing W12a. For j > 35, deviations between the estimates with lithosphere thickness of 150 and 200 km, and those with ℎ𝑙 ≤ 90 km are visible. However, these deviations are minor since the different viscoelastic kernels of the geoid-height change are very similar. The correction for remaining elastic signals using GPS rates is small, despite being sensitive to, and dependent on, very different viscoelastic kernels of surface displacement. It is expected that these deviations result in only minor differences in the spatial rate of geoid-height change (Fig. 2.2).

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2.2 Spatial rate of geoid-height change

The spatial pattern of the rate of geoid-height change of the end members of RE000 ensemble (30 km, with DL; 200 km, no DL) are shown in Fig. 2.2, together with those of W12a and AGE1. As expected RE000-030 and RE000-200 are nearly identical, even though the higher spectral content of RE000-030 appears as smaller scale features in the Amundsen / Bellingshausen Sea sectors, as well as in parts of the Ross Ice Shelf. Please note, the lithosphere thickness for East Antarctica is fixed to ℎ𝐿=150 km (and 200 km, for the end member of ℎ𝐿 = 200 km in West Antarctica). Overall, differences between the REGINA ensemble simulations are below a geoid rate of ± 0.1 mm/yr.

The spatial representation shows that RE000 is similar to W12a and AGE1 in terms of the locations of the major geoid-height anomalies in the Filchner-Ronne and Ross ice shelves. Also the magnitude of the signals falls into the range spanned by W12a and AGE1 (-0.0 to 0.9 mm /yr geoid rates). The overall Antarctic signal is positive, meaning mass gain; however, as W12a (and opposed to AGE1), RE000 shows a negative anomaly in Coats Land, which Whitehouse et al. 2012 have attributed substantial ice-thickness increase in the late Holocene. It also shares some of the negative signal in central East Antarctica, associated with increased accumulation due to the warming atmosphere after the Last Glacial Maximum (LGM).

Inconsistent with any of the published GIA corrections is the uplift signal in the western Wilkes Land (longitude of ca. 90°E). Also, glaciological evidence does not support a strong ice retreat in this region (Mackintosh et al. 2013), necessary to produce this uplift anomaly. This suggests that the present signal arises from unsatisfactory removal of present-day ice-mass changes. As a consequence, the current GIA estimate may be biased, particularly as correction for GRACE.

Inspecting the input data sets shows that this positive anomaly is present in the GRACE trends (Figure 3.4 of IAR [AD-5]) – most likely attributable to an accumulation event, which is then incompletely reduced with the altimetry data set. In fact, altimetry rates are spatially very heterogeneous in this region (Figure 5.1 of IAR [AD-5]), which could suggest a sampling issue, as well as the superposition of the ice-dynamic and accumulation signals in the data, difficult to attribute a single snow / ice density to. Clearly, detailed investigations are needed to track down the reason for this likely artefact. Unfortunately, also GPS rates cannot resolve this issue; because the trend is poorly captured with campaign data (see Section 5.2 of IAR [AD-5]).

Fig. 2.2 already indicates that integrated over the entire Antarctic continent, the mass rate associated with the GIA signals and its bias introduced in ice-mass balances from GRACE is very comparable for the models shown. This is presented in the IAR [AD-5].

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Figure 2.2: Spatial rate of geoid-height change (mm/yr). Shown are the rates of the REGINA GIA fields for the two end members of the ensemble, a) ℎ𝑙: 30 km with ductile layer (RE000-30; Table A2 Sim #29) and b) ℎ𝑙: 200 km without ductile layer (RE000-200; Table A2 Sim #59), both with a asthenosphere viscosity of 1 1018 Pa s, as well as of the published GIA fields c) W12a and d) AGE1.

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Figure 2.3: Degree-power spectrum of the rate of radial displacement (mm/yr) for the published GIA fields (W12a, dashed; IJ05 R2, dotted; RVIA0, dash-dotted; and AGE1, solid), as well as the minimum and maximum degree-power of the published GIA fields (grey shaded area).

2.3 Spectral rate of radial displacement

Next, we will discuss the rate of radial displacement in the REGINA GIA fields. The rate of radial displacement here is equal to the surface-elevation correction applicable to CryoSat-2 measurement, which is the main objective of this project. The impact of the radial displacement on mass balance estimates from CryoSat-2 is addressed in the IAR [AD-5].

Fig. 2.3 shows the degree-power spectrum of the rate of radial displacement for the published GIA corrections W12a, AGE1, RIVA09 and IJ05R2. The strongest uplift rates are produced by W12a over nearly all parts of the spectrum, i.e. for the entire range of spatial wavelength. In contrast, AGE1 yields the weakest uplift rates, also over most of the spectral range shown. AGE1 and IJ05 R2 are similar in terms of their magnitude and spectral signature. RIVA09 lies between the minimum and maximum degree power of W12a and AGE1 and tends to reach the rates of W12a at degrees > 60.

Figure 2.4 shows the degree-power spectrum of the rate of radial displacement for the ensemble RE000. It is visible that RE000 lies within the range of the published models until 𝑗 ≈ 15, and exceeds them after that. Marked differences occur for RE000 with lithosphere thickness 30 to 90 km, 150 km and 200 km, starting at 𝑗 ≈ 35 (ca. 570 km spatial wavelength). All ensemble GIA estimates with lithosphere thicknesses below 90 km remain very similar until 𝑗 ≈ 60. At higher degrees, estimates with ℎ𝑙 = 30 to 90 km become distinguishable, as well as the effect of in- or excluding the ductile layer. A number of features can be observed from Fig. 2.4, which are discussed in the following section.

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Figure 2.4: Degree-power spectrum of the rate of radial displacement (mm/yr) for the REGINA GIA fields obtained assuming different lithosphere thicknesses (red to blue curves) with (solid) and without (dashed) the ductile layer, as well as the minimum and maximum degree-power of the published GIA fields (grey shaded area; W12a, IJ05 R2, RIVA09 and AGE1, see Fig. 2.3).

2.3.1 Apparent smoothing for “thick” lithospheres

Simulations with 150 km and 200 km lithosphere thickness produce smooth viscoelastic kernels due to the dampening properties of a thick lithosphere broadening the flexure. The resulting spectrum is similar to the maximum estimate of the published GIA corrections (here, W12a). This will be addressed later in the discussion of Fig. 2.6 and Fig. 2.7. The inherent smoothing also results in significantly lower uplift rates over broader spatial scales.

2.3.2 Magnitude of uplift for “thin” lithospheres

For simulations with lithosphere thicknesses from 30 to 90 km, high spatial frequencies constitute a large part of the total signal. This means, that when adopting this kind of Earth structure, degrees and orders > 35 have to be included to reproduce correct uplift rates. Since the GPS uplift rates are local measurements and not spatially smoothed, limiting the viscoelastic kernels to low degrees and orders or smoothing them is likely to introduce a bias when fitted to the GPS rates. However, whether the limited resolution of the GRACE trend, upon which these GIA estimates are based, allows estimating signals in this high spectral range remains debatable. In this instance, converting the viscoelastic kernels of the geoid-height to those of the radial displacement is similar to a high pass filtering of the smoothed gravity signal, amplifying the noise and generating spurious signals. Possibly, linear trends derived from GOCE/GRACE combined solutions may result in higher spatial resolutions, which are useful in this context (e.g. Bouman et al. 2014); however, it remains debated whether newly revealed spatial patterns may be a result of the band-pass-filtered GOCE and GRACE gravity gradients, opposed to a true increase in resolution.

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2.3.3 Effect of ductile layer

The presence of the ductile layer influences only the high degrees and orders of the deformation spectrum; as shown in [AD-3] it localizes deformation and amplifies the magnitude of uplift rates. However, as visible from Fig. 2.1 it is irrelevant for the predicted geoid-height change. As a consequence, the ductile layer matters for interpreting GPS rates (e.g. the high uplift rates observed in the Amundsen Sea Sector), but there is no information contained in the gravity field data, upon which the estimate is also based. This could lead to spurious signals in regions where there is no GPS rate available, and where only GRACE data is used.

A possibility to avoid causing a bias when considering local GPS rates and at the same time overcome introducing spurious signals is to perform a posteriori filtering of the resulting deformation fields. The degree-power spectrum of the filtered ensemble is shown in Fig. 2.5; the filter parameters are chosen equal to those considered for the input data sets, i.e. Gaussian filter with 200 km filter width. It is visible that now the spectra mostly lie within the range spanned by the published models, except between degree 40 to 60. It is also visible that now the range spanned by the different lithosphere thicknesses is significantly reduced.

Figure 2.5: Same as Fig. 2.4, but with 200 km Gaussian filtering applied a posteriori to the REGINA GIA fields.

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2.4 Spatial rate of radial displacement

To get an additional view on the resulting GIA fields, Fig. 2.6 shows the spatial patterns of the radial displacement rate for the end members of the REGINA ensemble, without and with Gaussian smoothing of 200 km. These are compared with the published GIA fields shown in Fig. 2.7. As expected from Fig. 2.6, RE000-030 (with DL) produces much larger uplift rates (up to ca. 30 mm/yr) at much finer spatial scales than RE000-200 (no DL) which are < 10 mm/yr. The apparent smoothing due to the thick lithosphere is also visible. Please note that the uplift for East Antarctica relies on the same viscoelastic kernels (ℎ𝑙: 150 km) and is almost identical in RE000-030 and RE000-200.

Applying the 200 km Gaussian filter leads to similar magnitudes in RE000-030 and RE000-200, even though the higher spectral content is RE000-030 remains visible (see Fig. 2.6). It should be noted that applying the filtering to RE000-200 has only a small effect, while for RE000-030 it reduces the uplift rates of the small scale features by a factor of about 3.

Fig. 2.7 shows the uplift rates for the published GIA corrections. It is visible that the overall magnitude between the models varies by a factor of ca. 2, with W12a showing the strongest uplift signals. W12a compares well with the RE000-030 (filtered), as well as RE000-200 (unfiltered and filtered); the location and magnitude of the main GIA signal in the Filchner-Ronne and Ross Ice shelves agree. Also, the negative (subsidence) anomaly east to the Filchner ice shelf (Coats Land), only shown by W12a is reproduced in RE000.

Most striking difference to all the published GIA fields shown here is the strong uplift anomaly in the western part Wilkes Land, East Antarctica (at longitude ca. 90°E), which was discussed in more detail in Section 2.2. Moreover, the GIA signal inferred for the Amundsen Sea Sector is localized in RE000, but connected with the Filchner-Ronne uplift signal in W12a. In contrast to the models where an ongoing relaxation is assumed, in this study only the equilibrium state after the viscoelastic relaxation is assumed. This results in an amplification of the higher degree components in the response which is visible in 2.4.

Another peculiarity of RE000 is the subsidence signal in the Bellingshausen Sea Sector, which is not supported by any of the published GIA corrections. It is likely, that this anomaly is entirely related to an overestimation of mass increase in the altimetry fields, resulting in a negative anomaly when subtracted from the GRACE trends. The Bellingshausen Sea Sector is a high-accumulation area, receiving strong moisture flux from the adjacent ocean. It is likely that an accumulation event within the observation period caused the height change in the altimetry data and is attributed more to snow than to ice. Due to the lack of GPS sites in this region, an elastic correction based on the wrong density assumption is not improved in the second step of the estimation procedure detailed in the ATBD [AD-4]. Possible approaches to overcome these issues are either employing a mass balance estimate of the input-output method (Rignot et al. 2008), or by improving the snow / firn density using output from a regional climate model (see Scientific Roadmap, [AD-6]).

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Figure 2.6: Spatial rate of radial displacement (mm/yr) of the REGINA GIA fields for the two end

members of the ensemble, a) ℎ𝑙: 30 km & ductile layer and b) ℎ𝑙: 200 km & no ductile layer, c) and d) same as a) and b), but with 200 km Gaussian filtering applied a posteriori. Please note the different scales in a) compared to b), c) and d).

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Figure 2.7: Spatial rate of radial displacement (mm/yr) for the published GIA fields a) IJ05 R2, b) AGE1, c) W12a and d) RIVA09. Please note the different scales in a), b) and c), d).

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3 Concluding remarks

The GIA fields resulting from REGINA share many characteristics with the published GIA corrections in their low spectral range (i.e. at low degrees, where 0 ≤ j ≤ 30) and for most of the spectrum when employing lithosphere thicknesses of 150 and 200 km. For the smaller lithosphere thicknesses with a posteriori filtering, location and magnitude of the main GIA centers lie within the range of the published models. Unique to the REGINA GIA estimates is the high spectral range, producing uplift rates of up to 30 mm/yr. Simulations have shown that such uplift rates are plausible, given a weak Earth structure including the presence of a ductile layer and recent (< 2 kyr BP) glacial forcing [AD-3]. Such high uplift rates in the higher spectral range can be excited by contemporary glacial ice mass variations (Appendix A.1). However, it may be considered doubtful whether the limited GRACE resolution allows inferring such fine scale structures. And, even though working with localized GPS data does require considering uplift signature in their full spatial resolution, it may be advisable to a posteriori filter the radial displacement fields.

Therefore, a future project will benefit from a higher resolution in the temporal gravity field data, as may be achieved by a GRACE / GOCE combination (Bouman et al. 2014), as spatial resolution is the main limitation in identifying fine-scale GIA structure using the current approach. In addition, a better spatial and temporal coverage of the GPS data will allow a significant improvement of the GIA estimate, as they will allow reducing the uncertainty in the density estimate. Also, coeval temporal coverage with the satellite observing systems is desirable. In parallel, it is necessary to proceed with this analysis to identify the dominant signals at present and possible GPS site, and to thus enabling us to make recommendations on which stations to consider in a long-term deployment and maintenance plan. Finally, also the GIA modelling will considerably improve from better knowledge of the Earth structure beneath Antarctica. In a first approximation, lateral variations could at least be accounted for in the this approach by assigning each disc simulations an own lithosphere and viscosity profile (currently only East and West Antarctica). In this context, GOCE is suitable to provide a key data constraint on the Moho depth, which can then be absorbed on state-of-the art GIA modelling. The remarks sketched here are addressed in greater detail in the Scientific Roadmap (SR [AD-6]).

4 References

Bouman, J., Fuchs, M., Ivins, E., Wal, W., Schrama, E., Visser, P. N. A. M., & Horwath, M. (2014). Antarctic outlet glacier mass change resolved at basin scale from satellite gravity gradiometry. Geophysical Research Letters, 41(16), 5919-5926.

Groh, A., Ewert, H., Scheinert, M., Fritsche, M., Rülke, A., Richter, A., Rosenau, R., Dietrich, R. (2012). An investigation of Glacial Isostatic Adjustment over the Amundsen Sea sector, West Antarctica. Global and Planetary Change, 98–99(0), 45-53. doi: http://dx.doi.org/10.1016/j.gloplacha.2012.08.001

Ivins, E. R., T. S. James, J. Wahr, E. J. O. Schrama, F. W. Landerer, and K. M. Simon (2013): Antarctic contribution to sea level rise observed by GRACE with improved GIA correction, J. Geophys. Res. Solid Earth, 118, doi:10.1002/jgrb.50208.

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Mackintosh, A. N., Verleyen, E., O'Brien, P. E., White, D. A., Jones, R. S., McKay, R., ... & Masse, G. (2013). Retreat history of the East Antarctic Ice Sheet since the Last Glacial Maximum. Quaternary Science Reviews.

Pollard, D. and DeConto, R. M.: Description of a hybrid ice sheet-shelf model, and application to Antarctica, Geosci. Model Dev., 5, 1273-1295, doi:10.5194/gmd-5-1273-2012, 2012.

Rignot, E., Bamber, J. L., Van Den Broeke, M. R., Davis, C., Li, Y., Van De Berg, W. J., & Van Meijgaard, E. (2008). Recent Antarctic ice mass loss from radar interferometry and regional climate modelling. Nature Geoscience, 1(2), 106-110.

Riva, R. E., Gunter, B. C., Urban, T. J., Vermeersen, B. L., Lindenbergh, R. C., Helsen, M. M., Bamber, J. L., van de Wal, R. S., van den Broeke, M. R., and Schutz, B. E. (2009): Glacial Isostatic Adjustment over Antarctica from combined ICESat and GRACE satellite data, Earth Planet. Sci. Lett., 288, 516–523, doi:10.1016/j.epsl.2009.10.013.

Sasgen, I., Konrad, H., Ivins, E. R., Van den Broeke, M. R., Bamber, J. L., Martinec, Z., and Klemann, V. (2013): Antarctic ice-mass balance 2003 to 2012: regional reanalysis of GRACE satellite gravimetry measurements with improved estimate of glacial-isostatic adjustment based on GPS uplift rates, The Cryosphere, 7, 1499-1512, doi:10.5194/tc-7-1499-2013.

Whitehouse, P. L., Bentley, M. J., Milne, G. A., King, M. A., and Thomas, I. D. (2012b): A new glacial isostatic adjustment model for Antarctica: calibrated and tested using observations of relative sea-level change and present-day uplift rates, Geophys. J. Int., 190, 1464–1482, doi:10.1111/j.1365-246X.2012.05557.x.

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Appendix

A1. Additional simulations

Fig. A1.1 (overleaf) shows the rate of radial displacement for the GIA simulation excited by the glacial history of Pollard & DeConto (2012). It is visible that a thin elastic lithosphere allows for smaller-scale GIA signals; the presence of the ductile layer amplifies the small-scale feature. Even though the model is not particularly tuned to adequately represent the most recent deglaciation (which is most relevant for the weak Earth structures investigated here), it is visible that the forcing produces uplift structures similar in spatial scale and magnitude to those shown in Fig. 2.6 for a thin elastic lithosphere of a) 60 km in including a ductile layer. For thicker elastic lithospheres of b) 60 km and c) 120 km the spatial pattern is smoother and comparable to other published estimates, e.g. d) AGE1. It should be stated that also the simulation based Pollard & DeConto (2012) does not exhibit a GIA anomaly in Wilkes Land, as produced GIA estimate of REGINA.

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Figure A1.1: Spatial rate of radial displacement (mm/yr) using the forcing of the thermomechanical ice sheet model of Pollard & DeConto (2012) for the “soft” Earth model parameters of Sim.#15 (Table A2.1) a) low viscosity with ductile layer and b) low viscosity without ductile layer, as well as Earth model parameters similar to Sim.#58 c) “standard” viscosity and 120 km lithosphere thickness), as well as the d)GIA estimate AGE1.

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A2. Earth model parameters

Table A2.1: Simulation number (Sim. #) and associated Earth model parameters; presence of ductile layer (DL; 1=no, 2=yes), depth of the lithosphere/mantle boundary (Depth; ML) and viscosity of the asthenosphere (Viscosity; AS). The equilibrium simulations used in the combination are marked with brown font.(modified after Table 4.2, ATBD, [AD-2]).

Sim. # DL Depth (km) Viscosity (1018

Pa s) Sim. # ctd. DL Depth (km) Viscosity (10

18 Pa s)

1 no 30 1 29† yes 30 1

2 no 30 3 30 yes 30 3

3 no 30 10 31 yes 30 10

4 no 30 30 32 yes 30 30

5 no 40 1 33 yes 40 1

6 no 40 3 34 yes 40 3

7 no 40 10 35 yes 40 10

8 no 40 30 36 yes 40 30

9 no 50 1 37 yes 50 1

10 no 50 3 38 yes 50 3

11 no 50 10 39 yes 50 10

12 no 50 30 40 yes 50 30

13 no 60 1 41 yes 60 1

14 no 60 3 42 yes 60 3

15 no 60 10 43 yes 60 10

16 no 60 30 44 yes 60 30

17 no 70 1 45 yes 70 1

18 no 70 3 46 yes 70 3

19 no 70 10 47 yes 70 10

20 no 70 30 48 yes 70 30

21 no 80 1 49 yes 80 1

22 no 80 3 50 yes 80 3

23 no 80 10 51 yes 80 10

24 no 80 30 52 yes 80 30

25 no 90 1 53 yes 90 1

26 no 90 3 54 yes 90 3

27 no 90 10 55 yes 90 10

28 no 90 30 56 yes 90 30

† RE000-030 (Reference end member soft Earth structure) 57 no 150 1

‡ RE000-200 (Reference end member strong Earth structure) 58 no 150 500

59‡* no 200 1

* East Antarctica

60* no 200 500

** Elastic

61** no n.a. ∞

VR


Date 2014-12-21

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A3. List of data sets relevant for this validation activity

Table A3.1: Data sets involved in the REGINA project. Required data sets are those relevant for the generation of the prototype GIA estimate presented in Section 5, Validation data sets are considered for assessing the plausibility of the prototype GIA estimate (excerpt from ATBD [AD-3]).

Required data sets Source Temporal

coverage Baseline requirement Comment

Surface-mass density trends (ye) & uncertainties

GRACE 2003-2009 [GR04] Derived by conversion approach

Surface-elevation trends (yh) & uncertainties

Envisat & ICESat 2003-2009 [AL01] & [AL02] Combined altimetry estimate

Bedrock displacement rate (yu) & uncertainties

GPS 1995-2014 [GP04] & [GP05] 85 sites with data available

Elastic and viscoelastic response functions

Numerical simulation

2000 yrs BP to present

[GI03] 60 different combinations of viscoelastic Earth model parameters. 1 elastic Earth model parameterization

Validation data sets Source Temporal coverage

Baseline requirement Comment

Firn compaction and SMB rate (dh/dt; dm/dt)

RACMO2/ANT 2003-2010 [AL03] Validation of inferred density

State of the art published GIA corrections (du/dt)

Numerical simulation & Publications

Last-glacial maximum to present

[GI01] Validation of GIA uplift magnitude and location

Ancillary data sets Source Temporal coverage

Baseline requirement Comment

Glacial history Pollard & DeConto (2012)

-40 kyrs to present

Amendment to [GI01]

Validation of fine-scale GIA pattern for weak Earth structure

Bedrock displacement rate (yu) & uncertainties for Amundsen Sea Embayment

Groh et al. 2012 Campaign data (2006 & 2010)

Amendment to [GP04] & [GP05]

3 sites (BEAR, MANT & PIG2) for Amundsen Sea Embayment

validation report (vr) (d3.2) · figure 1.2: map of antarctica indicating the geographic regions...

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