| 1. |
- Boysen, Lena R., et al.
(författare)
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Global climate response to idealized deforestation in CMIP6 models
- 2020
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 17, s. 5615-5638
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Tidskriftsartikel (refereegranskat)abstract
- Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water and carbon exchange with the atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth system models (ESMs) carried out an idealized experiment in the framework of the Coupled Model Intercomparison Project, phase 6 (CMIP6). Starting from their pre-industrial state, models linearly replace 20×106 km2 of forest area in densely forested regions with grasslands over a period of 50 years followed by a stabilization period of 30 years. Most of the deforested area is in the tropics, with a secondary peak in the boreal region. The effect on global annual near-surface temperature ranges from no significant change to a cooling by 0.55 ∘C, with a multi-model mean of −0.22±0.21 ∘C. Five models simulate a temperature increase over deforested land in the tropics and a cooling over deforested boreal land. In these models, the latitude at which the temperature response changes sign ranges from 11 to 43∘ N, with a multi-model mean of 23∘ N. A multi-ensemble analysis reveals that the detection of near-surface temperature changes even under such a strong deforestation scenario may take decades and thus longer than current policy horizons. The observed changes emerge first in the centre of deforestation in tropical regions and propagate edges, indicating the influence of non-local effects. The biogeochemical effect of deforestation are land carbon losses of 259±80 PgC that emerge already within the first decade. Based on the transient climate response to cumulative emissions (TCRE) this would yield a warming by 0.46 ± 0.22 ∘C, suggesting a net warming effect of deforestation. Lastly, this study introduces the “forest sensitivity” (as a measure of climate or carbon change per fraction or area of deforestation), which has the potential to provide lookup tables for deforestation–climate emulators in the absence of strong non-local climate feedbacks. While there is general agreement across models in their response to deforestation in terms of change in global temperatures and land carbon pools, the underlying changes in energy and carbon fluxes diverge substantially across models and geographical regions. Future analyses of the global deforestation experiments could further explore the effect on changes in seasonality of the climate response as well as large-scale circulation changes to advance our understanding and quantification of deforestation effects in the ESM frameworks.
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| 2. |
- Ito, Akihiko, et al.
(författare)
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Soil carbon sequestration simulated in CMIP6-LUMIP models : Implications for climatic mitigation
- 2020
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9318 .- 1748-9326. ; 15:12
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Tidskriftsartikel (refereegranskat)abstract
- Land-use change affects both the quality and quantity of soil organic carbon (SOC) and leads to changes in ecosystem functions such as productivity and environmental regulation. Future changes in SOC are, however, highly uncertain owing to its heterogeneity and complexity. In this study, we analyzed the outputs of simulations of SOC stock by Earth system models (ESMs), most of which are participants in the Land-Use Model Intercomparison Project. Using a common protocol and the same forcing data, the ESMs simulated SOC distribution patterns and their changes during historical (1850-2014) and future (2015-2100) periods. Total SOC stock increased in many simulations over the historical period (30 ± 67 Pg C) and under future climate and land-use conditions (48 ± 32 Pg C for ssp126 and 49 ± 58 Pg C for ssp370). Land-use experiments indicated that changes in SOC attributable to land-use scenarios were modest at the global scale, in comparison with climatic and rising CO2 impacts, but they were notable in several regions. Future net soil carbon sequestration rates estimated by the ESMs were roughly 0.4‰ yr-1 (0.6 Pg C yr-1). Although there were considerable inter-model differences, the rates are still remarkable in terms of their potential for mitigation of global warming. The disparate results among ESMs imply that key parameters that control processes such as SOC residence time need to be better constrained and that more comprehensive representation of land management impacts on soils remain critical for understanding the long-term potential of soils to sequester carbon.
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| 3. |
- McGuire, A. David, et al.
(författare)
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Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009
- 2016
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Ingår i: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 30:7, s. 1015-1037
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Tidskriftsartikel (refereegranskat)abstract
- A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8x10(3)km(2)yr(-1)). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954TgCyr(-1) between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.
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| 4. |
- Wang, Wenli, et al.
(författare)
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Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region
- 2016
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Ingår i: Cryosphere. - : Copernicus GmbH. - 1994-0416. ; 10:4, s. 1721-1737
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Tidskriftsartikel (refereegranskat)abstract
- A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C-1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
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| 5. |
- Xia, Jianyang, et al.
(författare)
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Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
- 2017
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Ingår i: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 122:2, s. 430-446
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Tidskriftsartikel (refereegranskat)abstract
- Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246±6gCm-2yr-1), most models produced higher NPP (309±12gCm-2yr-1) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800gCm-2yr-1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
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