the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Uncertainties originating from GCM downscaling and bias correction with application to the MIS-11c Greenland Ice Sheet
Lev Tarasov
Michael Schulz
Matthias Prange
Abstract. The Marine Isotope Stage 11c (MIS-11c) interglacial is an enigmatic period characterized by a long duration of relatively weak insolation forcing, but is thought to have been coincident with a large global sea level rise of 6–13 m. The configuration of the Greenland Ice Sheet during the MIS-11c interglacial highstand is therefore of great interest. Given the limited data constraints, model-based analysis may be of use, but only if model uncertainties are adequately accounted for. A particularly under-addressed issue in coupled climate and ice sheet modeling is the coupling of surface air temperatures to the ice model. Many studies apply a uniform “lapse rate” accounting for the temperature differences at different altitudes over the ice surface, but this uniformity neglects both regional and seasonal differences in near-surface temperature changes. Herein we provide the first such analysis for MIS-11c Greenland that addresses these uncertainties by comparing 1-way coupled CESM and ice sheet model results from several different downscaling methodologies.
In our study, a spatially- and temporally-varying temperature downscaling method produced the greatest success rate in matching limited paleodata constraints, and suggests a peak ice volume loss from Greenland during MIS-11c of near 50 % compared to present day (~3.9 m contribution to sea level rise). This result is on the lower bound of existing data- and model-based studies, partly as a consequence of the applied one-way coupling methodology which neglects some feedbacks. Additional uncertainties are examined by comparing two different present-day regional climate analyses for bias correction of temperatures and precipitation, a spread of initialization states and times, and different spatial configurations of precipitation bias corrections. No other factor exhibited greater influence over the simulated Greenland ice sheet than the choice of temperature downscaling scheme.
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Brian R. Crow et al.
Status: open (until 27 Sep 2023)
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RC1: 'Comment on egusphere-2023-1367', Anonymous Referee #1, 28 Jul 2023
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Crow and co-authors employed an offline ice sheet model to investigate the impact of spinup-time, climate forcing, and temperature downscaling on the evolution of the Greenland ice sheet during MIS11. The authors utilized CESM time-slice simulations as the basis for the climate forcing, which was further bias-corrected in various ways, and the impact thereof was investigated. The study highlights the substantial influence of both climate forcing bias correction (here RACMO vs MAR) and the approach used for temperature downscaling on the ice sheet evolution. Conversely, spinup-time and bias correction of precipitation were found to have minimal effects during MIS11. The authors also concluded that a spatially and temporally variable lapse rate for temperature downscaling is not only the most physically realistic approach but also yields the best results in reproducing paleodata constraints from Summit and DYE3. By using these two data constraints, the authors found that the Greenland ice sheet must have contributed at least 3.9 m sle at the peak of MIS11.
The manuscript is very well-written and nicely illustrated. The description of the model setups, coupling approach, and investigated sensitivities is mostly clear, but could benefit from some minor further additions. Furthermore, the compromises made with regard to coupling strategy, bias corrections, and ice sheet initialization are clearly explained, and it is convincingly demonstrated that these are reasonable given the scientific question the authors aim to answer. The study thoroughly evaluates the model's sensitivities to various sources of uncertainties, such as climate forcing and bias corrections, and extensively discusses the limitations of the employed models and approaches As such, I only have some minor comments, which I outline below.
Minor and technical points:
L80-85: You could also mention the recently published evidence from Camp Century being ice free during MIS11 (Christ et al., 2023, doi:10.1126/science.ade4248).
L117: Can you give more information which and how many time-slices you used.
L118: Please give a reference for the GHG concentrations used.
L125: Selected variables for what?
L259: Does the relatively coarse resolution also contribute to this (by not resolving small fjords etc.)?
L270: Please note relative to which dataset this biases exists. ERA or something else?
L276: Please elaborate a bit more how this scale factor was calculated. Is this the ratio between time-slice versus PD mean?
L338: Can you give the percentage of these 31 simulations that use the STV lapse rates?
L426: It seems that the difference between RACMO and MAR (Fig. 6) is similar impactful as the choice of lapse rate.
L436: Can you provide a figure with maps of the differences in temperature based on the different downscaling approaches for instances at 405 ka either in the main text or appendix/supplement? This would provide a better visualization of the impact of the different approaches.
Fig. 2: I think it could be more intuitive to depict blue colors as cold bias in CESM and red colors as warm bias, i.e., opposite to how it is shown now.
Tab. 1: Since either RACMO or MAR were used for both temperature and precipitation, it would make sense to combine both columns into one.
Citation: https://doi.org/10.5194/egusphere-2023-1367-RC1
Brian R. Crow et al.
Brian R. Crow et al.
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