scholarly journals Assessing the impact of late Pleistocene megafaunal extinctions on global vegetation and climate

2013 ◽  
Vol 9 (4) ◽  
pp. 1761-1771 ◽  
Author(s):  
M.-O. Brault ◽  
L. A. Mysak ◽  
H. D. Matthews ◽  
C. T. Simmons
Keyword(s):  
Large Scale ◽  
Surface Albedo ◽  
Climate Model ◽  
Rapid Expansion ◽  
Atmospheric Co2 ◽  
Earth System ◽  
Global Mean Temperature ◽  
Pleistocene Climate ◽  
Global Vegetation ◽  
The Impact

Abstract. The end of the Pleistocene was a turning point for the Earth system as climate gradually emerged from millennia of severe glaciation in the Northern Hemisphere. The deglacial climate change coincided with an unprecedented decline in many species of Pleistocene megafauna, including the near-total eradication of the woolly mammoth. Due to an herbivorous diet that presumably involved large-scale tree grazing, the mammoth extinction has been associated with the rapid expansion of dwarf deciduous trees in Siberia and Beringia, thus potentially contributing to the changing climate of the period. In this study, we use the University of Victoria Earth System Climate Model (UVic ESCM) to simulate the possible effects of these extinctions on climate during the latest deglacial period. We have explored various hypothetical scenarios of forest expansion in the northern high latitudes, quantifying the biogeophysical effects in terms of changes in surface albedo and air temperature. These scenarios include a Maximum Impact Scenario (MIS) which simulates the greatest possible post-extinction reforestation in the model, and sensitivity tests which investigate the timing of extinction, the fraction of trees grazed by mammoths, and the southern extent of mammoth habitats. We also show the results of a simulation with free atmospheric CO2-carbon cycle interactions. For the MIS, we obtained a surface albedo increase and global warming of 0.006 and 0.175 °C, respectively. Less extreme scenarios produced smaller global mean temperature changes, though local warming in some locations exceeded 0.3 °C even in the more realistic extinction scenarios. In the free CO2 simulation, the biogeophysical-induced warming was amplified by a biogeochemical effect, whereby the replacement of high-latitude tundra with shrub forest led to a release of soil carbon to the atmosphere and a small atmospheric CO2 increase. Overall, our results suggest the potential for a small, though non-trivial, effect of megafaunal extinctions on Pleistocene climate.

scholarly journals Assessing the impact of late Pleistocene megafaunal extinctions on global vegetation and climate

2013 ◽  
Vol 9 (1) ◽  
pp. 435-465 ◽  
Author(s):  
M.-O. Brault ◽  
L. A. Mysak ◽  
H. D. Matthews ◽  
C. T. Simmons
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Surface Albedo ◽  
Climate Model ◽  
Atmospheric Co2 ◽  
Earth System ◽  
Terrestrial Mammals ◽  
Pleistocene Climate ◽  
Pleistocene Climate Change ◽  
The Impact

Abstract. The end of the Pleistocene marked a turning point for the Earth system as climate gradually emerged from millennia of severe glaciation in the Northern Hemisphere. It is widely acknowledged that the deglacial climate change coincided with an unprecedented decline in many species of large terrestrial mammals, including the near-total eradication of the woolly mammoth. Due to an herbivorous diet that presumably involved large-scale tree grazing, the mammoth expansion would have accelerated the expansion of dwarf deciduous trees in Siberia and Beringia, thus contributing to the changing climate of the period. In this study, we use the University of Victoria Earth System Climate Model (UVic ESCM) to simulate the possible effects of megafaunal extinctions on Pleistocene climate change. We have explored various hypothetical scenarios of forest expansion in the Northern Continents, quantifying the regional and global biogeophysical effects in terms of changes in surface albedo and air temperature. In particular, we focus our attention on a Maximum Impact Scenario (MIS) which simulates the greatest possible post-extinction reforestation in the model. More realistic experiments include sensitivity tests based on the timing of extinction, the fraction of trees grazed by mammoths, and the size of mammoth habitats. We also show the results of a simulation with free (non-prescribed) atmospheric CO2. For the MIS, we obtained a surface albedo increase of 0.006, which resulted in a global warming of 0.175 °C. Less extreme scenarios produced smaller global mean temperature changes, though local warming in some locations exceeded 0.3 °C even in the more realistic extinction scenarios. In the free CO2 simulation, the biogeophysical-induced warming was amplified by a biogeochemical effect whereby the replacement of high-latitude tundra with shrub forest led to a release of soil carbon to the atmosphere and a small atmospheric CO2 increase. Overall, our results suggest the potential for a small, though non-trivial, effect of megafaunal extinctions on Pleistocene climate change.

scholarly journals Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

2019 ◽  
Vol 16 (19) ◽  
pp. 3883-3910 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Co2 Concentration ◽  
Fire Regimes ◽  
Atmospheric Co2 ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Fire Models ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2 concentration, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric CO2 concentration. The effects of changes in atmospheric CO2 concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

Evaluating the Consistency between Statistically Downscaled and Global Dynamical Model Climate Change Projections

2008 ◽  
Vol 21 (22) ◽  
pp. 6052-6059 ◽  
Author(s):  
B. Timbal ◽  
P. Hope ◽  
S. Charles
Keyword(s):  
Global Warming ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Specific Humidity ◽  
Model Output ◽  
Winter Rainfall ◽  
Direct Model ◽  
The Impact

Abstract The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

scholarly journals Extending the Modular Earth Submodel System (MESSy v2.54) model hierarchy: the ECHAM/MESSy IdeaLized (EMIL) model setup

2020 ◽  
Vol 13 (11) ◽  
pp. 5229-5257
Author(s):  
Hella Garny ◽  
Roland Walz ◽  
Matthias Nützel ◽  
Thomas Birner
Keyword(s):  
Climate Model ◽  
Polar Vortex ◽  
Equilibrium Temperature ◽  
Earth System ◽  
Tracer Transport ◽  
Dynamical Core ◽  
Vortex Strength ◽  
Model Hierarchy ◽  
Model Setup ◽  
The Impact

Abstract. As models of the Earth system grow in complexity, a need emerges to connect them with simplified systems through model hierarchies in order to improve process understanding. The Modular Earth Submodel System (MESSy) was developed to incorporate chemical processes into an Earth System model. It provides an environment to allow for model configurations and setups of varying complexity, and as of now the hierarchy ranges from a chemical box model to a fully coupled chemistry–climate model. Here, we present a newly implemented dry dynamical core model setup within the MESSy framework, denoted as ECHAM/MESSy IdeaLized (EMIL) model setup. EMIL is developed with the aim to provide an easily accessible idealized model setup that is consistently integrated in the MESSy model hierarchy. The implementation in MESSy further enables the utilization of diagnostic chemical tracers. The setup is achieved by the implementation of a new submodel for relaxation of temperature and horizontal winds to given background values, which replaces all other “physics” submodels in the EMIL setup. The submodel incorporates options to set the needed parameters (e.g., equilibrium temperature, relaxation time and damping coefficient) to functions used frequently in the past. This study consists of three parts. In the first part, test simulations with the EMIL model setup are shown to reproduce benchmarks provided by earlier dry dynamical core studies. In the second part, the sensitivity of the coupled troposphere–stratosphere dynamics to various modifications of the setup is studied. We find a non-linear response of the polar vortex strength to the prescribed meridional temperature gradient in the extratropical stratosphere that is indicative of a regime transition. In agreement with earlier studies, we find that the tropospheric jet moves poleward in response to the increase in the polar vortex strength but at a rate that strongly depends on the specifics of the setup. When replacing the idealized topography to generate planetary waves by mid-tropospheric wave-like heating, the response of the tropospheric jet to changes in the polar vortex is strongly damped in the free troposphere. However, near the surface, the jet shifts poleward at a higher rate than in the topographically forced simulations. Those results indicate that the wave-like heating might have to be used with care when studying troposphere–stratosphere coupling. In the third part, examples for possible applications of the model system are presented. The first example involves simulations with simplified chemistry to study the impact of dynamical variability and idealized changes on tracer transport, and the second example involves simulations of idealized monsoon circulations forced by localized heating. The ability to incorporate passive and chemically active tracers in the EMIL setup demonstrates the potential for future studies of tracer transport in the idealized dynamical model.

scholarly journals Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)

2020 ◽  
Vol 13 (5) ◽  
pp. 2355-2377
Author(s):  
Vijay S. Mahadevan ◽  
Iulian Grindeanu ◽  
Robert Jacob ◽  
Jason Sarich
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
System Modeling ◽  
Spectral Element ◽  
Scientific Workflow ◽  
Model Coupling ◽  
Earth System ◽  
Modeling Framework

Abstract. One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) (Hill et al., 2004) and TempestRemap (Ullrich et al., 2013) offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) (Larson et al., 2001) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) (Tautges et al., 2004; Mahadevan et al., 2015) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

scholarly journals Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO<sub>2</sub> and satellite-based vegetation activity observations

2013 ◽  
Vol 10 (6) ◽  
pp. 4189-4210 ◽  
Author(s):  
D. Dalmonech ◽  
S. Zaehle
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Spatial Scales ◽  
Evaluation Framework ◽  
Atmospheric Co2 ◽  
Evaluation Methodology ◽  
Surface Model ◽  
System Modelling ◽  
Earth System ◽  
Vegetation Activity

Abstract. Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular the net land–atmosphere carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to better understand the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely sensed vegetation activity to provide a novel set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits) specifically considers the robustness of information given that the uncertainty of both data and evaluation methodology is largely unknown or difficult to quantify. Based on these considerations, we introduce a baseline benchmark – a minimum test that any model has to pass – to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI Earth System Model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite-based vegetation activity data allows pinpointing of specific model deficiencies that would not be possible by the sole use of atmospheric CO2 observations.

scholarly journals Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2

2019 ◽  
Vol 12 (7) ◽  
pp. 3099-3118 ◽  
Author(s):  
Kristian Strommen ◽  
Hannah M. Christensen ◽  
Dave MacLeod ◽  
Stephan Juricke ◽  
Tim N. Palmer
Keyword(s):  
Climate Model ◽  
Weather Forecasting ◽  
Southern Oscillation ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Beneficial Impact ◽  
The Impact ◽  
Mean State

Abstract. We introduce and study the impact of three stochastic schemes in the EC-Earth climate model: two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic Earth system model in atmosphere-only mode. Stochastic parametrization have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as El Niño–Southern Oscillation (ENSO), North Atlantic weather regimes, and the Indian monsoon. Stochasticity in the land component has been shown to improve the variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied. It is shown that the inclusion of all three schemes notably changes the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to significant changes in the model's energy budget and atmospheric circulation. This implies that in order to maintain the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.

Forcings of mass-balance variability in Karakoram-Himalaya

2020 ◽  
Author(s):  
Pankaj Kumar ◽  
Vladimir A. Ryabchenko ◽  
Aaquib Javed ◽  
Dmitry V. Sein ◽  
Md. Farooq Azam
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulation ◽  
Large Fraction ◽  
Water Security ◽  
Spatiotemporal Variability ◽  
Glacier Mass Balance ◽  
Russian Science ◽  
The Impact

&lt;p&gt;Glacier retreat is a key indicator of climate variability and change. Karakoram-Himalaya (KH) glaciers are the source of several perennial rivers protecting water security of a large fraction of the global population. The region is highly vulnerable to climate change impacts, hence the sensitivity of KH glaciers to regional microclimate, especially the impact of individual parameters forcing have been not quantified yet. The present study, using a coupled dynamical glacier-climate model simulation results, analyses the modelled interannual variability of mass-balance for the period 1989-2016. It is validated against available observations to quantify for the first time the sensitivity of the glaciers mass-balance to the individual forcing over KH. The snowfall variability emerges as the key factor, explaining ~60% of the variability of regional glacier mass balance. We provide insight into the recent divergent glacier response over the Karakoram Himalaya. The results underline the need for careful measurements and model representations of snowfall spatiotemporal variability, one of the HK's least-studied meteorological variables, to capture the large-scale, but region-specific, glacier changes at the third pole.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Acknowledgement:&lt;/p&gt;&lt;p&gt;The work was supported by Indian project no. DST/INT/RUS/RSF/P-33/G, and the Russian Science Foundation (Project 19-47-02015).&lt;/p&gt;

Constraining the model representation of the aerosol life cycle in relation to sources and sinks.

2020 ◽  
Author(s):  
Paul Kim ◽  
Daniel Partridge ◽  
James Haywood
Keyword(s):  
Climate Change ◽  
Life Cycle ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Evaluation Framework ◽  
Microphysical Properties ◽  
The Impact ◽  
Source And Sink

&lt;p&gt;Global climate model (GCM) ensembles still produce a significant spread of estimates for the future of climate change which hinders our ability to influence policymakers. The range of these estimates can only partly be explained by structural differences and varying choice of parameterisation schemes between GCMs. GCM representation of cloud and aerosol processes, more specifically aerosol microphysical properties, remain a key source of uncertainty contributing to the wide spread of climate change estimates. The radiative effect of aerosol is directly linked to the microphysical properties and these are in turn controlled by aerosol source and sink processes during transport as well as meteorological conditions.&lt;/p&gt;&lt;p&gt;A Lagrangian, trajectory-based GCM evaluation framework, using spatially and temporally collocated aerosol diagnostics, has been applied to over a dozen GCMs via the AeroCom initiative. This framework is designed to isolate the source and sink processes that occur during the aerosol life cycle in order to improve the understanding of the impact of these processes on the simulated aerosol burden. Measurement station observations linked to reanalysis trajectories are then used to evaluate each GCM with respect to a quasi-observational standard to assess GCM skill. The AeroCom trajectory experiment specifies strict guidelines for modelling groups; all simulations have wind fields nudged to ERA-Interim reanalysis and all simulations use emissions from the same inventories. This ensures that the discrepancies between GCM parameterisations are emphasised and differences due to large scale transport patterns, emissions and other external factors are minimised.&lt;/p&gt;&lt;p&gt;Preliminary results from the AeroCom trajectory experiment will be presented and discussed, some of which are summarised now. A comparison of GCM aerosol particle number size distributions against observations made by measurement stations in different environments will be shown, highlighting the difficulties that GCMs have at reproducing observed aerosol concentrations across all size ranges in pristine environments. The impact of precipitation during transport on aerosol microphysical properties in each GCM will be shown and the implications this has on resulting aerosol forcing estimates will be discussed. Results demonstrating the trajectory collocation framework will highlight its ability to give more accurate estimates of the key aerosol sources in GCMs and the importance of these sources in influencing modelled aerosol-cloud effects. In summary, it will be shown that this analysis approach enables us to better understand the drivers behind inter-model and model-observation discrepancies.&lt;/p&gt;

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