Future fires in the Coupled Model Intercomparison Project (CMIP) phase 6

2020 ◽  
Author(s):  
Gitta Lasslop ◽  
Stijn Hantson ◽  
Victor Brovkin ◽  
Fang Li ◽  
David Lawrence ◽  
...  
Keyword(s):  
Land Use ◽  
Fire Regime ◽  
Coupled Model ◽  
Fire Regimes ◽  
Atmospheric Composition ◽  
Cloud Formation ◽  
Burned Area ◽  
Earth System ◽  
System Models ◽  
Earth System Models

<p>Fires are an important component in Earth system models (ESMs), they impact vegetation carbon storage, vegetation distribution, atmospheric composition and cloud formation. The representation of fires in ESMs contributing to CMIP phase 5 was still very simplified. Several Earth system models updated their representation of fires in the meantime. Using the latest simulations of CMIP6 we investigate how fire regimes change in the future for different scenarios and how land use, climate and atmospheric CO<sub>2</sub> concentration contribute to the fire regimes changes. We quantify changes in fire danger, burned area and carbon emissions on an annual and seasonal basis. Factorial model simulations allow to quantify the influence of land use, climate and atmospheric CO<sub>2</sub> on fire regimes.</p><p>We complement the information on fire regime change supplied by ESMs that include a fire module with a statistical modelling approach for burned area. This will use information from simulated changes in climate, vegetation and socioeconomic changes (population density and land use) provided for a set of different future scenarios. This allows the integration of information provided by global satellite products on burned area with the process-based simulations of climate and vegetation changes and information from socioeconomic scenarios.</p><p> </p>

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.

Disentangeling the shortwave surface energy balance in earth system models

2021 ◽  
Author(s):  
Kine Onsum Moseid
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Atmospheric Aerosols ◽  
Surface Energy Balance ◽  
Coupled Model ◽  
Shortwave Radiation ◽  
Earth System ◽  
System Models ◽  
Aerosol Forcing ◽  
Earth System Models

<p>The Earth’s surface energy balance is heavily affected by incoming solar radiation and how it propagates through our atmosphere. How the sunlight propagates towards the surface depends on the atmospheric presence of aerosols, gases, and clouds. </p><p>Surface temperature evolution according to earth system models (ESMs) in the historical experiment from the coupled model intercomparison project phase 6 (CMIP6) suggests that models may be overly sensitive to aerosol forcing. Other studies have found that ESMs do not recreate observed decadal patterns in surface shortwave radiation - suggesting the models inaccurately underestimate the shortwave impact of atmospheric aerosols. These contradictory results act as a basis for our study.<br>Our study decomposes what determines both all sky and clear sky downwelling shortwave radiation at the surface in ESMs, using different experiments of CMIP6. We try to determine the respective role of aerosols, clouds and gases in the shortwave energy balance at the surface, and assess the effect of seasonality and regional differences.</p>

Are Earth system models able to reproduce the soil heterotrophic respiration fluxes?

2021 ◽  
Author(s):  
Bertrand Guenet ◽  
Jérémie Orliac ◽  
Lauric Cécillon ◽  
Olivier Torres ◽  
Laurent Bopp
Keyword(s):  
Soil Respiration ◽  
Coupled Model ◽  
Global Scale ◽  
Heterotrophic Respiration ◽  
Earth System ◽  
Mixed Effect ◽  
Microbial Decomposition ◽  
System Models ◽  
Earth System Models ◽  
Climate Dynamic

<p>Earth system models (ESMs) are numerical representations of the Earth system aiming at representing the climate dynamic including feedbacks between climate and carbon cycle. CO<sub>2</sub> flux due to soil respiration including heterotrophic respiration coming from the soil organic matter (SOM) microbial decomposition and autotrophic respiration coming from the roots respiration is one of the most important flux between the surface and the atmosphere. Thus, even small changes in this flux may impact drastically the climate dynamic. It is therefore essential that ESMs reliably reproduce soil respiration. Until recently, such an evaluation at global scale of the ESMs was not straightforward because of the absence of observation-derived product to evaluate heterotrophic respiration fluxes from ESMs at global scale. Recently, several gridded products were published opening a new research avenue on climate-carbon feedbacks. In this study, we used simulations from 13 ESMs performed within the sixth coupled model intercomparison project (CMIP6) and we evaluate their capacities to reproduce the heterotrophic respiration flux using three gridded observation-based products. We first evaluate the total heterotrophic respiration flux for each model as well as the spatial patterns. We observed that most of the models are able to reproduce the total heterotrophic respiration flux but the spatial analysis underlined that this was partially due to some bias compensation between regions overestimating the flux and regions underestimating the flux. To better identify the causes of the identified bias in predicting the total heterotrophic respiration flux, we analysed the residues of ESMs using linear mixed effect models and we observed that lithology and climate were the most important drivers of the ESMs residues. Our results suggest that the response of SOM microbial decomposition to soil moisture and temperature must be improved in the next ESMs generation and that the effect of lithology should be better taken into account.</p>

scholarly journals Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6

2020 ◽  
Author(s):  
Roland Séférian ◽  
Sarah Berthet ◽  
Andrew Yool ◽  
Julien Palmiéri ◽  
Laurent Bopp ◽  
...  
Keyword(s):  
Coupled Model ◽  
Climate Feedback ◽  
Full Potential ◽  
Earth System ◽  
Current Generation ◽  
System Models ◽  
Biogeochemical Models ◽  
Marine Biogeochemistry ◽  
Intercomparison Project ◽  
Earth System Models

Abstract Purpose of Review The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). Recent Findings The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Summary Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).

scholarly journals Ideas and Perspectives: Climate-Relevant Marine Biologically-Driven Mechanisms in Earth System Models

2016 ◽  
Author(s):  
Inga Hense ◽  
Irene Stemmler ◽  
Sebastian Sonntag
Keyword(s):  
Mechanical Properties ◽  
Functional Groups ◽  
Atmospheric Composition ◽  
Marine Biota ◽  
Earth System ◽  
System Models ◽  
System Components ◽  
Optical And Mechanical Properties ◽  
Earth System Models

Abstract. Marine biota drives a number of climate-relevant mechanisms not all of which are included in current Earth system models (ESMs). We identify three classes of mechanisms and distinguish (1) those related to matter cycling via "biogeochemical pumps", (2) those affecting the atmospheric composition via the "biological gas and particle shuttles" and (3) those changing the thermal, optical and mechanical properties of the ocean via the "biogeophysical mechanisms". We argue that to adequately resolve these mechanisms, ESMs need to account for five functional groups, including bulk phyto- and zooplankton, calcifiers as well as coastal gas and surface mat producers. Thereby links to other Earth system components are ensured and a larger number of relevant feedbacks are enabled to take place.

scholarly journals Plant Physiology Increases the Magnitude and Spread of the Transient Climate Response to CO2 in CMIP6 Earth System Models

2020 ◽  
Vol 33 (19) ◽  
pp. 8561-8578
Author(s):  
Claire M. Zarakas ◽  
Abigail L. S. Swann ◽  
Marysa M. Laguë ◽  
Kyle C. Armour ◽  
James T. Randerson
Keyword(s):  
Plant Physiology ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Physiological Effect ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Near Surface ◽  
System Models ◽  
Earth System Models

AbstractIncreasing concentrations of CO2 in the atmosphere influence climate both through CO2’s role as a greenhouse gas and through its impact on plants. Plants respond to atmospheric CO2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded in most Earth system models, and a robust literature demonstrates that they can affect global-scale temperature. However, the physiological contribution to transient warming has yet to be assessed systematically in Earth system models. Here this gap is addressed using carbon cycle simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-yr window centered on the time of CO2 doubling relative to preindustrial CO2 concentrations. In CMIP6 models, the physiological effect contributes 0.12°C (σ: 0.09°C; range: 0.02°–0.29°C) of warming to the TCR, corresponding to 6.1% of the full TCR (σ: 3.8%; range: 1.4%–13.9%). Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the intermodel spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO2-forced warming—and the intermodel spread in warming—occurs over land, especially in forested regions.

Compatible Fossil Fuel CO2 emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway experiments of the 21st Century

2020 ◽  
pp. 1-72
Author(s):  
Spencer K. Liddicoat ◽  
Andy J. Wiltshire ◽  
Chris D. Jones ◽  
Vivek K. Arora ◽  
Victor Brovkin ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Fossil Fuel ◽  
Coupled Model ◽  
Historical Record ◽  
Emission Rates ◽  
Earth System ◽  
Uncertainty Range ◽  
System Models ◽  
Earth System Models ◽  
Fossil Fuel Emissions

AbstractWe present the compatible CO2 emissions from fossil fuel burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth System Models (ESMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The multi-model mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (392±63 GtC vs 400±20 GtC respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the Integrated Assessment Models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4 and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land use and land cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

ESMValCore: analyzing CMIP data made easy

2020 ◽  
Author(s):  
Bouwe Andela ◽  
Lisa Bock ◽  
Björn Brötz ◽  
Faruk Diblen ◽  
Laura Dreyer ◽  
...  
Keyword(s):  
Open Source ◽  
Performance Metrics ◽  
Modular Design ◽  
Coupled Model ◽  
Application Programming Interface ◽  
Earth System ◽  
Evaluation Tool ◽  
System Models ◽  
Scientific Analysis ◽  
Earth System Models

<p>The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2019, www.esmvaltool.org) features a brand new design, consisting of ESMValCore (https://github.com/esmvalgroup/esmvalcore), a package for working with CMIP data and ESMValTool (https://github.com/esmvalgroup/esmvaltool), a package containing the scientific analysis scripts. This new version has been specifically developed to handle the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex Earth system models. The tool also supports CMIP5 and CMIP3 datasets, as well as a large number of re-analysis and observational datasets that can be formatted according to the same standards (CMOR) on-the-fly or through scripts currently included in the ESMValTool package.</p><p>At the heart of this new version is the ESMValCore software package, which provides a configurable framework for finding CMIP files using a “data reference syntax”, applying commonly used pre-processing functions to them, running analysis scripts, and recording provenance. Numerous pre-processing functions, e.g. for data selection, regridding, and statistics are readily available and the modular design makes it easy to add more. The ESMValCore package is easy to install with relatively few dependencies, written in Python 3, based on state-of-the-art open-source libraries such as Iris and Dask, and widely used standards such as YAML, NetCDF, CF-Conventions, and W3C PROV. An extensive set of automated tests and code quality checks ensure the reliability of the package. Documentation is available at https://esmvaltool.readthedocs.io.</p><p>The ESMValCore package uses human-readable recipes to define which variables and datasets to use, how to pre-process that data, and what scientific analysis scripts to run. The package provides convenient interfaces, based on the YAML and NetCDF/CF-convention file formats, for running diagnostic scripts written in any programming language. Because the ESMValCore framework takes care of running the workflow defined in the recipe in parallel, most analyses run much faster, with no additional programming effort required from the authors of the analysis scripts. For example, benchmarks show a factor of 30 speedup with respect to version 1 of the tool for a representative recipe on a 24 core machine. A large collection of standard recipes and associated analysis scripts is available in the ESMValTool package for reproducing selected peer-reviewed analyses. The ESMValCore package can also be used with any other script that implements it’s easy to use interface. All pre-processing functions of the ESMValCore can also be used directly from any Python program. These features allow for use by a wide community of scientific users and developers with different levels of programming skills and experience.</p><p>Future plans involve extending the public Python API (application programming interface) from just preprocessor functions to include all functionality, including finding the data and running diagnostic scripts. This would make ESMValCore suitable for interactive data exploration from a Jupyter Notebook.</p>

scholarly journals A global assessment of gross and net land change dynamics for current conditions and future scenarios

2018 ◽  
Vol 9 (2) ◽  
pp. 441-458 ◽  
Author(s):  
Richard Fuchs ◽  
Reinhard Prestele ◽  
Peter H. Verburg
Keyword(s):  
Land Use ◽  
Shifting Cultivation ◽  
Large Scale ◽  
Earth System ◽  
Grid Cells ◽  
Land Change ◽  
System Models ◽  
Change Dynamics ◽  
Earth System Models ◽  
Land Changes

Abstract. The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30–100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5∘ grid cells was substantially larger than net changes in all parts of the world. As 0.5∘ grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

scholarly journals Sensitivity of simulated historical burned area to environmental andanthropogenic controls: A comparison of seven fire models

2019 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Global Change ◽  
Fire Regime ◽  
Fire Behavior ◽  
Fire Regimes ◽  
Burned Area ◽  
Strong Response ◽  
Fire Models ◽  
In Fire ◽  
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 of fire, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2, 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 1900. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trend in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the strongest differences leading to diverging trajectories are related to the way anthropogenic ignitions and suppression, as well as the effects of land-use on vegetation and fire, are incorporated in individual models. This points to a need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire for global change applications. Only two models show a strong response to CO2 and the response to lightning on global scale is low for all models. The sensitivity to climate shows a spatially heterogeneous response and globally only two models show a significant trend. It was not possible to attribute the climate-induced changes in burned area to model assumptions or specific climatic parameters. However, the strong influence of climate on the inter-annual variability in burned area, shown by all the models, shows that we need to pay attention to the simulation of fire weather but also meteorological influences on biomass accumulation and fuel properties in order to better capture extremes in fire behavior.

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