scholarly journals Optimal initial conditions for coupling ice sheet models to Earth system models

2014 ◽  
Vol 119 (9) ◽  
pp. 1894-1917 ◽  
Author(s):  
Mauro Perego ◽  
Stephen Price ◽  
Georg Stadler
Keyword(s):  
Initial Conditions ◽  
Ice Sheet ◽  
Earth System ◽  
System Models ◽  
Earth System Models

scholarly journals Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

2016 ◽  
Vol 9 (5) ◽  
pp. 1827-1851 ◽  
Author(s):  
Roland Séférian ◽  
Marion Gehlen ◽  
Laurent Bopp ◽  
Laure Resplandy ◽  
James C. Orr ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Initial Conditions ◽  
Model Performance ◽  
Cmip5 Models ◽  
Biogeochemical Model ◽  
Earth System ◽  
Model Intercomparison ◽  
System Models ◽  
Marine Biogeochemistry ◽  
Earth System Models

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

scholarly journals CPMIP: measurements of real computational performance of Earth system models in CMIP6

2017 ◽  
Vol 10 (1) ◽  
pp. 19-34 ◽  
Author(s):  
Venkatramani Balaji ◽  
Eric Maisonnave ◽  
Niki Zadeh ◽  
Bryan N. Lawrence ◽  
Joachim Biercamp ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Performance Model ◽  
Earth System ◽  
System Models ◽  
Performance Engineering ◽  
Computational Performance ◽  
Sensitive Dependence ◽  
Earth System Models

Abstract. A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).

scholarly journals CPMIP: Measurements of Real Computational Performance of Earth System Models

2016 ◽  
Author(s):  
V. Balaji ◽  
E. Maisonnave ◽  
N. Zadeh ◽  
B. N. Lawrence ◽  
J. Biercamp ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Earth System ◽  
System Models ◽  
Performance Engineering ◽  
Multi Scale ◽  
Computational Performance ◽  
Sensitive Dependence ◽  
Earth System Models

Abstract. A climate model represents a multitude of processes on a variety of time and space scales; a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory bound. Such weak-scaling, I/O and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth System) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform, and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. We present results for these measures for a diverse suite of models from several modeling centres, and propose to use these measures as a basis for a CPMIP, a computational performance MIP.

From the last interglacial to the future – new insights from modeling the last glacial-interglacial cycle in PalMod

2021 ◽  
Author(s):  
Kerstin Fieg ◽  
Mojib Latif ◽  
Michael Schulz ◽  
Tatjana Ilyina
Keyword(s):  
Climate Variability ◽  
Ice Sheet ◽  
Earth System ◽  
Glacial Cycle ◽  
System Models ◽  
Last Glacial ◽  
The Future ◽  
Fully Coupled ◽  
Earth System Models ◽  
The Last Glacial

<p>We present new insights from the project PalMod, which started in 2016 and is envisioned to run for a decade. The modelling initiative PalMod aims at filling the long-standing scientific gaps in our understanding of the dynamics and variability of the climate system during the last glacial-interglacial cycle. One of the grand challenges in this context is to quantify the processes that determine the spectrum of climate variability on timescales that range from seasons to millennia. Climatic processes are intimately coupled across these timescales. Understanding variability at any one timescale requires understanding of the whole spectrum. If we could successfully simulate the spectrum of climate variability during the last glacial cycle in Earth system models, would this enable us to more reliably assess the future climate change? Such simulations are necessary to deduce, for example, if a regime shift in climate variability could occur during the next centuries and millennia in response to global warming. PalMod is specifically designed to enhance our understanding of the Earth system dynamics and its variability on timescales up to the multimillennial with complex Earth System Models.</p><p>The following major goals were achieved up to now:</p><ul><li>Full coupling of atmosphere, ocean and ice-sheet models, enabling investigation of Heinrich Events and bi-stability of the AMOC, and millennial-scale transient climate-ice sheet simulations.</li> <li>Implementation of a coupled ocean and land biogeochemistry enabling simulations with prognostic atmospheric CO<sub>2</sub> concentrations and including improved representation of methane (CH<sub>4</sub>) in transient deglaciation runs.</li> <li>Systematic comparison of newly compiled proxy data with model simulations.</li> </ul><p>The major goal for the next two years is to set up the fully coupled physical-biogeochemical model which will be tested for three time periods: deglaciation, glacial inception and Marine Isotope Stage 3 (MIS3). This fully coupled model will be eventually used to simulate the complete glacial cycle and project the climate over the next few millennia.</p>

scholarly journals The importance of external climate forcing for the variability and trends of coastal upwelling in past and future climate

Ocean Science ◽  
2016 ◽  
Vol 12 (3) ◽  
pp. 807-823 ◽  
Author(s):  
Nele Tim ◽  
Eduardo Zorita ◽  
Birgit Hünicke ◽  
Xing Yi ◽  
Kay-Christian Emeis
Keyword(s):  
Radiative Forcing ◽  
Coastal Upwelling ◽  
Initial Conditions ◽  
Climate Forcing ◽  
Earth System ◽  
System Models ◽  
The Past ◽  
Eastern Boundary ◽  
The Impact ◽  
Earth System Models

Abstract. The eastern boundary upwelling systems, located in the subtropics at the eastern boundary of the Atlantic and Pacific oceans and mainly driven by the trade winds, are the major coastal upwelling regions. Previous studies have suggested that the intensity of upwelling in these areas in the past centuries may have been influenced by the external radiative forcing, for instance by changes in solar irradiance, and it will also be influenced in the future by the increasing atmospheric greenhouse gases. Here, we analyse the impact of the external climate forcing on these upwelling systems in ensembles of simulations of two Earth system models. The ensembles contain three simulations for each period covering the past millennium (900–1849) and the 20th century (1850–2005). One of these Earth system models additionally includes the near future (2006–2100). Using a set of simulations, differing only in their initial conditions, enables us to test whether the observed variability and trends are driven by the external radiative forcing. Our analysis shows that the variability of the simulated upwelling is largely not affected by the external forcing and that, generally, there are no significant trends in the periods covering the past and future. Only in future simulations with the strongest increase of greenhouse gas concentrations the upwelling trends are significant and appear in all members of the ensemble.

scholarly journals Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

2015 ◽  
Vol 8 (10) ◽  
pp. 8751-8808 ◽  
Author(s):  
R. Séférian ◽  
M. Gehlen ◽  
L. Bopp ◽  
L. Resplandy ◽  
J. C. Orr ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Initial Conditions ◽  
Model Performance ◽  
Cmip5 Models ◽  
Biogeochemical Model ◽  
Earth System ◽  
Model Intercomparison ◽  
System Models ◽  
Marine Biogeochemistry ◽  
Earth System Models

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were carried out on the systematic assessment of the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. Mean-state assessments routinely compared model hindcasts to available modern biogeochemical observations. However, these assessments considered neither the extent of equilibrium in modeled biogeochemical reservoirs nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESM) contribute to model-to-model differences in the simulated fields. We take advantage of a 500 year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and is consistent when confronted against a larger ensemble of CMIP5 models. This shows that drift has implications on their performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercices in order to provide realistic ESM results on marine biogeochemistry and carbon cycle feedbacks.

scholarly journals The evaluation of Earth System Models: discussion summary

2011 ◽  
Vol 6 ◽  
pp. 216-221
Author(s):  
Sönke Zaehle ◽  
Colin Prentice ◽  
Sarah Cornell
Keyword(s):  
Earth System ◽  
System Models ◽  
Earth System Models

scholarly journals Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

2015 ◽  
Vol 8 (4) ◽  
pp. 3235-3292 ◽  
Author(s):  
A. L. Atchley ◽  
S. L. Painter ◽  
D. R. Harp ◽  
E. T. Coon ◽  
C. J. Wilson ◽  
...  
Keyword(s):  
Carbon Sink ◽  
Thermal Response ◽  
Field Measurements ◽  
Early Summer ◽  
Active Layer Thickness ◽  
Earth System ◽  
Model Refinement ◽  
System Models ◽  
Developed Surface ◽  
Earth System Models

Abstract. Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.

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