InitMIP-Antarctica experiments with the ice sheet model SICOPOLIS

Greve, Ralf; Galton-Fenzi, Benjamin K.

doi:10.5281/zenodo.4766983

InitMIP-Antarctica experiments with the ice sheet model SICOPOLIS

Greve, Ralf; Galton-Fenzi, Benjamin K.

Publisher: Zenodo
DOI: 10.5281/zenodo.4766983
Repository: zenodo.org
Language: en

Abstract

Presentation No. MIS10-01, JpGU-AGU Joint Meeting 2017, Makuhari Messe, Chiba, Japan, 24 May 2017. Abstract. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) brings together a consortium of international ice sheet and climate models to explore the contribution from the Greenland and Antarctic ice sheets to future sea level rise. For such projections, initialisations are required that provide initial states of the respective ice sheet. InitMIP-Antarctica is an early initiative within ISMIP6 in order to explore this issue for the Antarctic ice sheet across a variety of models and initialisation techniques. We contribute to InitMIP-Antarctica with the ice sheet model SICOPOLIS and a spin-up-type initialisation, that is, a paleoclimatic simulation over 135 ka until the present. A major new component of the model is a physically-based parameterisation of ice shelf basal melting. In this parameterisation, basal melting of ice shelves is computed as a function of both the depth of ice below mean sea level and far-field ocean temperatures. The parameterisation is tuned differently for eight Antarctic sectors in order to achieve reasonable agreement with the modern spatial distribution of ice shelf basal melting. InitMIP-Antarctica also comprises three future climate scenarios, all to be run over 100 a: ctrl (present-day climate), asmb (prescribed schematic surface mass balance anomaly) and abmb (prescribed schematic basal melting anomaly under ice shelves). We present and discuss the performance of the spin-up in terms of agreement between simulated and observed present-day geometry and flow. Further, we investigate the response of the Antarctic ice sheet to the three future climate scenarios.

Full text

InitMIP-Antarctica experiments with the ice sheet model SICOPOLIS Ralf Greve1, Benjamin K. Galton-Fenzi2 (1) Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan (2) Australian Antarctic Division, Kingston, Tasmania, Australia Presentation No. MIS10-01, JpGU–AGU Joint Meeting 2017, Makuhari Messe, Chiba, Japan, 24 May 2017 R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 2 InitMIP-Antarctica: Antarctic ice sheet model initialisation experiments Early initiative within Initialise ice sheet to present day with method of choice (init) Run three forward experiments (100 a) unforced control run (ctrl) prescribed schematic SMB anomaly (asmb) prescribed sub-ice-shelf melting anomaly (abmb) (Seroussi et al., in prep.) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 3 Spin-up with SICOPOLIS (www.sicopolis.net) Model time: t= –135 ka ... 0 ka (one glacial cycle). Grid spacing: ∆x= 16 km. (1) Without ice-stream dynamics / (2) with ice-stream dynamics. Fixed topography (except first 100 a and last 500 a). Surface temperature anomaly ∆T from Vostok δD record. (Petit et al., 1999) Precip = precip_today x fct(∆T). (Precip_today: Arthern et al., 2006; Le Brocq et al., 2010) Runoff: PDD. Parameterization of ice-shelf basal melting (next slides). R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 4 Parameterisation of ice-shelf basal melting Basal melting rate ab= function of ocean temperature Toc: (modified after Beckmann and Goosse, 2003) Ω:sensitivity parameter for each sector. d:ice-shelf draft (reference value d0= 200 m). α:non-linearity parameter. Tm,b:melting temperature at ice-shelf base, depends on draft d. R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 5 Definition of eight sectors ①Western East Antarctica. ②Amery/Prydz Bay. ③Sabrina Coast/Aurora subglacial basin. ④George V Coast/Wilkes subglacial basin. ⑤Ross Sea. ⑥Amundsen Sea. ⑦Bellingshausen Sea ⑧Weddell Sea Basal/seafloor topography (m AMSL) ① ② ③ ④ ⑤ ⑥ ⑦ ⑧ Tuning by “observed” melting rates… R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 6 Distribution of basal melting Enhanced melting near deep grounding lines reproduced well. Due to different physics: No enhanced melting near calving fronts. No accretion of frazil ice. (on a 10-km grid) ab(m/a) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 7 Distribution of basal melting Enhanced melting near deep grounding lines reproduced well. Due to different physics: No enhanced melting near calving fronts. No accretion of frazil ice. (on a 10-km grid) ab(m/a) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 8 Spin-up: simulated vs. observed surface velocity Observed: Rignot et al. (2011, 2017) Simulated Without ice-stream dynamics: Very sharp transitions between sheet and shelves. R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 9 Spin-up: simulated vs. observed surface velocity Observed: Rignot et al. (2011, 2017) Simulated With ice-stream dynamics: Smoother transitions between sheet and shelves. R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 16 Ice sheet model SICOPOLIS “SImulation COde for POLythermal Ice Sheets” Open-source model, mainly delevoped at ILTS (www.sicopolis.net). Coded in Fortran. Shallow ice + shallow shelf approximations. Finite difference method. R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 17 Ice sheet model SICOPOLIS Rectangular boxes: prognostic model components. Ovals: model input. Appendix B: Ice-shelf basal melting R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 19 Sector-averaged ocean temperature ① ② ③ ④ ⑤ ⑥ ⑦ ⑧ 0.23°C –1.61°C –0.16°C –0.22°C –1.55°C 0.62°C 0.42°C –1.80°C [World Ocean Atlas 2009 (Locarnini et al., 2010) at 500 m depth] R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 20 Tuning strategy (for each sector) (1) Target basal melting rate: “observed”, from (2) Assume α(non-linearity parameter). (3) Compute point-wise Ω(sensitivity parameter) with nearest-neighbor Toc (ocean temperature). (4) Set up the parameterisation for abwith sector-averaged Ωand Toc. (5) Compute misfit to “observed” ab. (6) Repeat with different α’s → minimize misfit. (7) Scale Ω’s → sectorial and total melt by Rignot et al. (2013) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 21 Ω’s, α’s and melt rates Qtot = 1323.9 Gt/a Ω’s, α’s Sectorial melt rates Appendix C: InitMIP anomalies R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 23 Schematic SMB anomaly (asmb) (Seroussi et al., in prep.) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 24 Schematic basal melt anomaly (abmb) (Seroussi et al., in prep.) R. Greve & B. K. Galton-Fenzi: InitMIP-Antarctica with SICOPOLIS 25 References Arthern, R. J., D. P. Winebrenner and D. G. Vaughan. 2006. Antarctic snow accumulation mapped using polarization of 4.3-cm wavelength microwave emission. J. Geophys. Res. Atmos. 111 (D6), D06107, doi:10.1029/2004JD005667. Beckmann, A. and H. Goosse. 2003. A parameterization of ice shelf–ocean interaction for climate models. Ocean Modelling 5(2), 157-170, doi: 10.1016/S1463-5003(02)00019-7. Fretwell, P. and 59 others. 2013. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica. Cryosphere 7(1), 375-393, doi:10.5194/tc-7-375-2013. Le Brocq, A. M., A. J. Payne and A. Vieli. 2010. 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