A Gaussian process emulator for simulating ice sheet-climate interactions on a multi-million year timescale

2020 ◽  
Author(s):  
Jonas Van Breedam ◽  
Philippe Huybrechts ◽  
Michel Crucifix
Keyword(s):  
Gaussian Process ◽  
Climate Model ◽  
Ice Sheet ◽  
Climate System ◽  
Lapse Rate ◽  
Coupled Models ◽  
Climate Interactions ◽  
Coupling Time ◽  
Fully Coupled ◽  
Gaussian Process Emulator

<p>Fully coupled state-of-the-art Atmosphere-Ocean General Circulation Models are the best tool to investigate feedbacks between the different components of the climate system on a decadal to centennial timescale. On millennial to multi-millennial timescales, Earth System Models of Intermediate Complexity are used to explore the feedbacks in the climate system between the ice sheets, the atmosphere and the ocean. Those fully coupled models, even at coarser resolution, are computationally very expensive and other techniques have been proposed to simulate ice sheet-climate interactions on a million-year timescale. The asynchronous coupling technique proposes to run a climate model for a few decades and subsequently an ice sheet model for a few millennia. Another, more efficient method is the use of a matrix look-up table where climate model runs are performed for end-members and intermediate climatic states are linearly interpolated.</p><p>In this study, a novel coupling approach is presented where a Gaussian Process emulator applied to the climate model HadSM3 is coupled to the ice sheet model AISMPALEO. We have tested the sensitivity of the formulation of the ice sheet parameter and of the coupling time to the evolution of the ice sheet over time. Additionally, we used different lapse rate adjustments between the relatively coarse climate model and the much finer ice sheet model topography. It is shown that the ice sheet evolution over a million year timescale is strongly sensitive to the choice of the coupling time and to the implementation of the lapse rate adjustment. With the new coupling procedure, we provide a more realistic and computationally efficient framework for ice sheet-climate interactions on a multi-million year timescale.</p><p> </p>

scholarly journals A Gaussian process emulator for simulating ice sheet-climate interactions on a multi-million year timescale: CLISEMv1.0

2021 ◽  
Author(s):  
Jonas Van Breedam ◽  
Philippe Huybrechts ◽  
Michel Crucifix
Keyword(s):  
Gaussian Process ◽  
Climate Model ◽  
Ice Sheet ◽  
Lapse Rate ◽  
Balance Model ◽  
Computationally Efficient ◽  
Temperature And Precipitation ◽  
Time Sensitivity ◽  
Climate Interactions ◽  
Gaussian Process Emulator

Abstract. On multi-million year timescales, fully coupled ice sheet – climate simulations are hampered by computational limitations, even at coarser resolutions and when considering asynchronous coupling schemes. In this study, a novel coupling method CLISEMv1.0 (CLimate-Ice Sheet EMulator version 1.0) is presented where a Gaussian process emulator is applied to the climate model HadSM3 coupled to the ice sheet model AISMPALEO. The temperature and precipitation fields from HadSM3 are emulated to feed the mass balance model from AISMPALEO. The sensitivity of the evolution of the ice sheet over time is tested to the number of predefined ice sheet geometries the emulator is calibrated on, to the formulation of the ice sheet parameter (being either ice sheet volume, either ice sheet area, or both) and to the coupling time. Sensitivity experiments are conducted to explore the uncertainty introduced by the emulator. Additionally, different lapse rate adjustments are used between the relatively coarse climate model and the much finer ice sheet model topography. It is shown that the ice sheet evolution over a million-year timescale is strongly sensitive to the definition of the ice sheet parameter and to the number of predefined ice sheet geometries. With the new coupling procedure, we provide a computationally efficient framework for simulating ice sheet-climate interactions on a multi-million year timescale that allows for a large number of sensitivity tests.

Simulating Interactive Ice Sheets in the Multi-Resolution AWI-ESM: A case study using the SCOPE Coupler

2021 ◽  
Author(s):  
Paul Gierz ◽  
Lars Ackermann ◽  
Christian Rodehacke ◽  
Uta Krebs-Kanzow ◽  
Christian Stepanek ◽  
...  
Keyword(s):  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Global Ocean ◽  
Earth System ◽  
Last Interglacial ◽  
Ice Shelf ◽  
Coupled Models ◽  
Fully Coupled ◽  
Paleoclimate Studies

<p>Interactions between the climate and the cryosphere have the potential to induce strong non-linear transitions in the Earth's climate. These interactions influence both the atmospheric circulation, by changing the ice sheet's geometry, as well as the oceanic circulation, by modification of the water mass properties. Furthermore, the waxing and waning of large continental ice sheets influences the global albedo, altering the energy balance of the Earth System and inducing climate-ice sheet feedbacks on a global scale as evident in Pleistocene glacial-interglacial cycles. To date, few fully<br>comprehensive models exist, that do not only contain a coupled atmosphere/land/ocean component, but also consider interactive cryosphere physics. Yet, on glacial-interglacial and tectonic time scales, as well as in the Anthropocene, ice sheets are not in equilibrium with the climate, and prescribed fixed ice sheet representations in the model can principally be only an approximation to reality. Only climate models, that contain interactive ice sheets, can produce simulations of the Earth's climate which include all feedbacks and processes related to atmosphere-land-ocean-ice interactions. Previous fully coupled models were limited either by low spatial resolution or an incomplete representation of ice sheet processes, such as iceberg calving, surface ablation processes, and ocean/ice-shelf interactions. Here, we present the newly developed AWI-Earth System Model (AWI-ESM), which tackles some of these problems. Our modelling toolbox is based on the AWI-climate model, including atmosphere and vegetation components suitable for paleoclimate studies, a multi-resolution global ocean component which can be refined to simulate regions of interest at high resolution, and an ice sheet component suitable for simulating both ice sheet and ice shelf dynamics and thermodynamics. We describe the currently implemented coupling between these components, present first results for the Mid-Holocene and Last Interglacial, and introduce further ideas for scientific applications for both future and past climate states with a focus on the Northern Hemisphere. Finally, we provide an outlook on the potential of such fully coupled Earth System models in improving representation of climate-ice sheet feedbacks in future paleoclimate studies with this model.</p>

scholarly journals Dependence of Eemian Greenland temperature reconstructions on the ice sheet topography

2013 ◽  
Vol 9 (6) ◽  
pp. 6683-6732
Author(s):  
N. Merz ◽  
A. Born ◽  
C. C. Raible ◽  
H. Fischer ◽  
T. F. Stocker
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Large Scale ◽  
Surface Energy Balance ◽  
Climate Model ◽  
Surface Wind ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Lapse Rate

Abstract. The influence of a reduced Greenland ice sheet (GrIS) on Greenland's surface climate during the Eemian interglacial is studied using a comprehensive climate model. We find a distinct impact of changes in the GrIS topography on Greenland's surface air temperatures (SAT) even when correcting for changes in surface elevation which influences SAT through the lapse rate effect. The resulting lapse rate corrected SAT anomalies are thermodynamically driven by changes in the local surface energy balance rather than dynamically caused through anomalous advection of warm/cold air masses. The large-scale circulation is indeed very stable among all sensitivity experiments and the NH flow pattern does not depend on Greenland's topography in the Eemian. In contrast, Greenland's surface energy balance is clearly influenced by changes in the GrIS topography and this impact is seasonally diverse. In winter, the variable reacting strongest to changes in the topography is the sensible heat flux (SHFLX). The reason is its dependence on surface winds, which themselves are controlled to a large extent by the shape of the GrIS. Hence, regions where a receding GrIS causes higher surface wind velocities also experience anomalous warming through SHFLX. Vice-versa, regions that become flat and ice-free are characterized by low wind speeds, low SHFLX and anomalous cold winter temperatures. In summer, we find surface warming induced by a decrease in surface albedo in deglaciated areas and regions which experience surface melting. The Eemian temperature records derived from Greenland proxies, thus, likely include a temperature signal arising from changes in the GrIS topography. For the NEEM ice core site, our model suggests that up to 3.2 °C of the annual mean Eemian warming can be attributed to these topography-related processes and hence is not necessarily linked to large-scale climate variations.

scholarly journals PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

2021 ◽  
Author(s):  
Charles Pelletier ◽  
Thierry Fichefet ◽  
Hugues Goosse ◽  
Konstanze Haubner ◽  
Samuel Helsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Horizontal Resolution ◽  
Fine Tuning ◽  
Polar Regions ◽  
Surface Mass ◽  
The Impact ◽  
Fully Coupled

Abstract. We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

scholarly journals ENSO Predictability of a Fully Coupled GCM Model Using Singular Vector Analysis

2006 ◽  
Vol 19 (14) ◽  
pp. 3361-3377 ◽  
Author(s):  
Youmin Tang ◽  
Richard Kleeman ◽  
Sonya Miller
Keyword(s):  
Singular Vector ◽  
Climate Model ◽  
Global Climate Model ◽  
Heat Content ◽  
Enso Cycle ◽  
Coupled Models ◽  
Error Norm ◽  
Singular Vectors ◽  
Enso Predictability ◽  
Fully Coupled

Abstract Using a recently developed method of computing climatically relevant singular vectors (SVs), the error growth properties of ENSO in a fully coupled global climate model are investigated. In particular, the authors examine in detail how singular vectors are influenced by the phase of ENSO cycle—the physical variable under consideration as well as the error norm deployed. Previous work using SVs for studying ENSO predictability has been limited to intermediate or hybrid coupled models. The results show that the singular vectors share many of the properties already seen in simpler models. Thus, for example, the singular vector spectrum is dominated by one fastest growing member, regardless of the phase of ENSO cycle and the variable of perturbation or the error norm; in addition the growth rates of the singular vectors are very sensitive to the phase of the ENSO cycle, the variable of perturbation, and the error norm. This particular CGCM also displays some differences from simpler models; thus subsurface temperature optimal patterns are strongly sensitive to the phase of ENSO cycle, and at times an east–west dipole in the eastern tropical Pacific basin is seen. This optimal pattern also appears for SST when the error norm is defined using Niño-4. Simpler models consistently display a single-sign equatorial signature in the subsurface corresponding perhaps to the Wyrtki buildup of heat content before a warm event. Some deficiencies in the CGCM and their possible influences on SV growth are also discussed.

scholarly journals Coupling of climate models and ice sheet models by surface mass balance gradients: application to the Greenland Ice Sheet

2012 ◽  
Vol 6 (2) ◽  
pp. 255-272 ◽  
Author(s):  
M. M. Helsen ◽  
R. S. W. van de Wal ◽  
M. R. van den Broeke ◽  
W. J. van de Berg ◽  
J. Oerlemans
Keyword(s):  
Mass Balance ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Lapse Rate ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Temperature Lapse Rate

Abstract. It is notoriously difficult to couple surface mass balance (SMB) results from climate models to the changing geometry of an ice sheet model. This problem is traditionally avoided by using only accumulation from a climate model, and parameterizing the meltwater run-off as a function of temperature, which is often related to surface elevation (Hs). In this study, we propose a new strategy to calculate SMB, to allow a direct adjustment of SMB to a change in ice sheet topography and/or a change in climate forcing. This method is based on elevational gradients in the SMB field as computed by a regional climate model. Separate linear relations are derived for ablation and accumulation, using pairs of Hs and SMB within a minimum search radius. The continuously adjusting SMB forcing is consistent with climate model forcing fields, also for initially non-glaciated areas in the peripheral areas of an ice sheet. When applied to an asynchronous coupled ice sheet – climate model setup, this method circumvents traditional temperature lapse rate assumptions. Here we apply it to the Greenland Ice Sheet (GrIS). Experiments using both steady-state forcing and glacial-interglacial forcing result in realistic ice sheet reconstructions.

scholarly journals Simulating interactive ice sheets in the multi-resolution AWI-ESM 1.2: A case study using SCOPE 1.0

2020 ◽  
Author(s):  
Paul Gierz ◽  
Lars Ackermann ◽  
Christian B. Rodehacke ◽  
Uta Krebs-Kanzow ◽  
Christian Stepanek ◽  
...  
Keyword(s):  
Ice Sheets ◽  
Ice Sheet ◽  
Global Ocean ◽  
Earth System ◽  
Last Interglacial ◽  
Ice Shelf ◽  
Coupled Models ◽  
Earth’S Climate ◽  
Fully Coupled ◽  
Paleoclimate Studies

Abstract. Interactions between the climate and the cryosphere have the potential to induce strong non-linear transitions in the Earth's climate. These interactions influence both the atmospheric circulation, by changing the ice sheet's geometry, as well as the oceanic circulation, by modification of the water mass properties. Furthermore, the waxing and waning of large continental ice sheets influences the global albedo, altering the energy balance of the Earth System and inducing climate-ice sheet feedbacks on a global scale as evident in Pleistocene glacial-interglacial cycles. To date, few fully comprehensive models exist, that do not only contain a coupled atmosphere/land/ocean component, but also consider interactive cryosphere physics. Yet, on glacial-interglacial and tectonic time scales, as well as in the Anthropocene, ice sheets are not in equilibrium with the climate, and prescribed fixed ice sheet representations in the model can principally be only an approximation to reality. Only climate models, that contain interactive ice sheets, can produce simulations of the Earth's climate which include all feedbacks and processes related to atmosphere-land-ocean-ice interactions. Previous fully coupled models were limited either by low spatial resolution or an incomplete representation of ice sheet processes, such as iceberg calving, surface ablation processes, and ocean/ice-shelf interactions. Here, we present the newly developed AWI-Earth System Model (AWI-ESM), which tackles some of these problems. Our modelling toolbox is based on the AWI-climate model, including atmosphere and vegetation components suitable for paleoclimate studies, a multi-resolution global ocean component which can be refined to simulate regions of interest at high resolution, and an ice sheet component suitable for simulating both ice sheet and ice shelf dynamics and thermodynamics. We describe the currently implemented coupling between these components, present first results for the Mid-Holocene and Last Interglacial, and introduce further ideas for scientific applications for both future and past climate states with a focus on the Northern Hemisphere. Finally, we provide an outlook on the potential of such fully coupled Earth System models in improving representation of climate-ice sheet feedbacks in future paleoclimate studies with this model.

scholarly journals The Key Role of Coupled Chemistry–Climate Interactions in Tropical Stratospheric Temperature Variability

2020 ◽  
Vol 33 (17) ◽  
pp. 7619-7629
Author(s):  
Simchan Yook ◽  
David W. J. Thompson ◽  
Susan Solomon ◽  
Seo-Yeon Kim
Keyword(s):  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Stratospheric Temperature ◽  
Climate Interactions ◽  
Free Running ◽  
Polar Stratosphere ◽  
Fully Coupled ◽  
Do So

AbstractThe purpose of this study is to quantify the effects of coupled chemistry–climate interactions on the amplitude and structure of stratospheric temperature variability. To do so, the authors examine two simulations run on version 4 of the Whole Atmosphere Coupled Climate Model (WACCM): a “free-running” simulation that includes fully coupled chemistry–climate interactions and a “specified chemistry” version of the model forced with prescribed climatological-mean chemical composition. The results indicate that the inclusion of coupled chemistry–climate interactions increases the internal variability of temperature by a factor of ~2 in the lower tropical stratosphere and—to a lesser extent—in the Southern Hemisphere polar stratosphere. The increased temperature variability in the lower tropical stratosphere is associated with dynamically driven ozone–temperature feedbacks that are only included in the coupled chemistry simulation. The results highlight the fundamental role of two-way feedbacks between the atmospheric circulation and chemistry in driving climate variability in the lower stratosphere.

A global ensemble-based comparison of the last two glacial inceptions with LCice 2.0

2020 ◽  
Author(s):  
Marilena Geng ◽  
Lev Tarasov ◽  
Taimaz Bahadory
Keyword(s):  
Climate Model ◽  
Ice Sheet ◽  
Test Case ◽  
Glacial Cycles ◽  
Systems Model ◽  
External Forcings ◽  
Transient Simulations ◽  
Spatio Temporal ◽  
Global Mean Sea Level ◽  
Fully Coupled

<p>What determines the character of glacial inceptions? Does the spatio-temporal pattern of ice nucleation and expansion vary much between Late Pleistocene glacial inceptions? According to various benthic del18O stacks, the MIS 7 interglacial was the most anomalous in character of the last 4 interglacials. Key differences include a weaker interglacial state and an initial fast inception interrupted by a return to a similar and extended interglacial state. These anomalies of MIS 7 along with temporal proximity arguably make the last two glacial inceptions the best test case for addressing our opening questions. As part of a larger project to generate and analyze a data-constrained ensemble of fully coupled ice/climate transient simulations for the last two complete glacial cycles, herein we present initial results comparing the last two glacial inceptions (MIS 7 and 5d). We are using a new version of the fully coupled ice/climate model LCice. LCice now simulates all 4 paleo ice sheet complexes with hybrid shallow-shelf and shallow-ice physics. It has already been shown to capture northern hemispheric ice sheet growth and subsequent retreat consistent with inferences from global mean sea level proxies (Bahadory et al, 2019). Orbital and greenhouse gas changes are the only external forcings applied to the model. A 300 member ensemble probes parametric uncertainties in both the 3D Glacial Systems Model and LoveClim (Atmosphere/Ocean/Vegetation) components of LCice. Our presentation will compare the evolution and relative phasing of all 4 paleo ice sheets, and associated changes in the rest of the modelled climate system.</p>

scholarly journals Correcting a bias in a climate model with an augmented emulator

2019 ◽  
Author(s):  
Doug McNeall ◽  
Jonny Williams ◽  
Richard Betts ◽  
Ben Booth ◽  
Peter Challenor ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Land Surface ◽  
Structural Model ◽  
Climate Model ◽  
Input Parameter ◽  
Amazon Region ◽  
Model Errors ◽  
Input Parameters ◽  
Parameter Values ◽  
Gaussian Process Emulator

Abstract. A key challenge in developing flagship climate model configurations is the process of setting uncertain input parameters at values that lead to credible climate simulations. Setting these parameters traditionally relies heavily on insights from those involved in parameterisation of the underlying climate processes. Given the many degrees of freedom and computational expense involved in evaluating such a selection, this can be imperfect leaving open questions about whether any subsequent simulated biases result from mis-set parameters or wider structural model errors (such as missing or partially parameterised processes). Here we present a complementary approach to identifying plausible climate model parameters, with a method of bias correcting subcomponents of a climate model using a Gaussian process emulator that allows credible values of model input parameters to be found even in the presence of a significant model bias. A previous study (McNeall et al., 2016) found that a climate model had to be run using land surface input parameter values from very different, almost non-overlapping parts of parameter space to satisfactorily simulate the Amazon and other forests respectively. As the forest fraction of modelled non-Amazon forests was broadly correct at the default parameter settings and the Amazon too low, that study suggested that the problem most likely lay in the model's treatment of non-plant processes in the Amazon region. This might be due to (1) modelling errors such as missing deep-rooting in the Amazon in the land surface component of the climate model, (2) a warm-dry bias in the Amazon climate of the model, or a combination of both. In this study we bias correct the climate of the Amazon in a climate model using an augmented Gaussian process emulator, where temperature and precipitation, variables usually regarded as model outputs, are treated as model inputs alongside regular land surface input parameters. A sensitivity analysis finds that the forest fraction is nearly as sensitive to climate variables as changes in its land surface parameter values. Bias correcting the climate in the Amazon region using the emulator corrects the forest fraction to tolerable levels in the Amazon at many candidates for land surface input parameter values, including the default ones, and increases the valid input space shared with the other forests. We need not invoke a structural model error in the land surface model, beyond having too dry and hot a climate in the Amazon region. The augmented emulator allows bias correction of an ensemble of climate model runs and reduces the risk of choosing poor parameter values because of an error in a subcomponent of the model. We discuss the potential of the augmented emulator to act as a translational layer between model subcomponents, simplifying the process of model tuning when there are compensating errors, and helping model developers discover and prioritise model errors to target.

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