ALBERT

Description: A biogenic emissions scheme has been incorporated in the global dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic EcosystEms) in order to calculate global biogenic emissions of isoprene, monoterpenes, methanol, acetone, acetaldehyde, formaldehyde and formic and acetic acids. Important parameters such as the leaf area index are fully determined by the global vegetation model and the influences of light extinction (for isoprene emissions) and leaf age (for isoprene and methanol emissions) are also taken into account. We study the interannual variability of biogenic emissions using the satellite-based climate forcing ISLSCP-II as well as relevant CO2 atmospheric levels, for the 1983–1995 period. Mean global emissions of 460 TgC/yr for isoprene, 117 TgC/yr for monoterpenes, 106 TgC/yr for methanol and 42 TgC/yr for acetone are predicted. The mean global emission of all biogenic compounds is 752±16 TgC/yr with extremes ranging from 717 TgC/yr in 1986 to 778 TgC/yr in 1995, that is a 8.5% increase between both. This variability differs significantly from one region to another and among the regions studied, biogenic emissions anomalies were the most variable in Europe and the least variable in Indonesia (isoprene and monoterpenes) and North America (methanol). Two scenarios of land use changes are considered using the 1983 climate and atmospheric CO2 conditions, to study the sensitivity of biogenic emissions to vegetation alteration, namely tropical deforestation and European afforestation. Global biogenic emissions are highly affected by tropical deforestation, with a 29% decrease in isoprene emission and a 22% increase in methanol emission. Global emissions are not significantly affected by European afforestation, but on a European scale, total biogenic VOCs emissions increase by 54%.

Description: Recent results from the LUCID model intercomparison project have revealed large discrepancies in the simulated evapotranspiration (ET) response to the historical land-use change. Distinct land-surface parameterizations are behind those discrepancies, but understanding those differences rely on evaluations using still very limited measurements. Model benchmarking studies with observed ET are required in order to reduce the current uncertainties in the impacts of land use in terrestrial water flows. Here we present new estimates of historical land-use-induced ET changes based on three observation-driven products of ET. These products are used to derive empirical models of ET as a function of land-cover properties and environmental variables. An ensemble of reconstructions of past ET changes are derived with the same set of land-cover maps used in LUCID, with which we obtain an average decrease in global terrestrial ET of 1260 ± 850 km3 yr−1 between the preindustrial period and the present-day. This estimate is larger in magnitude than the mean ET change simulated within LUCID with process-based models, and substantially weaker than other estimates based on observations. Although decreases in annual ET dominate in deforested regions, large summertime increases in ET are diagnosed over areas of large cropland expansion. The multiple ET reconstructions carried out here show a large spread that we attribute principally to the different land-cover maps adopted and to the crops' ET rates deduced from the various products assessed. We therefore conclude that the current uncertainties of past ET changes could be reduced efficiently with improved historical land-cover reconstructions and better estimates of cropland ET.

Description: Recent model intercomparison studies, within the framework of the LUCID project, have revealed large discrepancies in the evapotranspiration (ET) changes simulated between the preindustrial period and the present in response to the historical change in land use. Distinct land-surface parameterizations are behind those discrepancies, but understanding those differences and attributing them to specific causes rely on evaluations using still very limited measurements. Model benchmarking studies with observed global-scale ET are required in order to reduce the current uncertainties in the impacts of land use in terrestrial water flows. Here we present a new estimate of historical land-use induced changes in ET based on three different state-of-the-art observation-based ET products. These products are used to derive regression models of ET as a function of land-cover partitioning, leaf area index and environmental variables. We then reconstruct past ET changes based on the set of land-cover maps of 1870 and 1992 used in LUCID. Our results show an average decrease in global terrestrial ET of 1260 ± 850 km3 yr−1 between the preindustrial period and the present-day. This estimate is of the same order but larger in magnitude than the model-mean change in ET simulated within LUCID, and substantially weaker in magnitude than other estimates based on observations. Although decreases in ET dominate in deforested regions, large summertime increases in ET are diagnosed over areas of large cropland expansion. The multiple ET reconstructions carried out here show a large spread that we attribute principally to the different land-cover maps adopted and to the crops' ET rates that are derived from the various products assessed. We therefore conclude that the current uncertainties of past ET changes could be reduced efficiently with improved historical land-cover reconstructions and better estimates of cropland ET.

Description: A primary goal of Earth system modelling is to improve understanding of the interactions and feedbacks between human decision making and biophysical processes. The nexus of land use and land cover change (LULCC) and the climate system is an important example. LULCC contributes to global and regional climate change, while climate affects the functioning of terrestrial ecosystems and LULCC. However, at present, LULCC is poorly represented in Global Circulation Models (GCMs). LULCC models that are explicit about human behaviour and decision making processes have been developed at local to regional scales, but the principles of these approaches have not yet been applied to the global scale level in ways that deal adequately with both direct and indirect feedbacks from the climate system. In this article, we explore current knowledge about LULCC modelling and the interactions between LULCC, GCMs and Dynamic Global Vegetation Models (DGVMs). In doing so, we propose new ways forward for improving LULCC representations in Earth System Models. We conclude that LULCC models need to better conceptualise the alternatives for up-scaling from the local to global. This involves better representation of human agency, including processes such as learning, adaptation and agent evolution, formalising the role and emergence of governance structures, institutional arrangements and policy as endogenous processes and better theorising about the role of tele-connections and connectivity across global networks. Our analysis underlines the importance of observational data in global scale assessments and the need for coordination in synthesising and assimilating available data.

Description: The impact of historical land use induced land cover change (LULCC) on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.

Description: Biogeophysical (BGP) and biogeochemical (BGC) effects of land-use and land cover change (LULCC) are separated at the global and regional scales in new interactive CO2 simulations for the 21st century. Results from four earth system models (ESMs) are analyzed for the future RCP8.5 scenario from simulations with and without land-use and land cover change (LULCC), contributing to the Land-Use and Climate, IDentification of robust impacts (LUCID) project. Over the period 2006–2100, LULCC causes the atmospheric CO2 concentration to increase by 12, 22, and 66 ppm in CanESM2, MIROC-ESM, and MPI-ESM-LR, respectively. Statistically significant changes in global near-surface temperature are found in three models with a BGC-induced global mean annual warming between 0.07 and 0.23 K. BGP-induced responses are simulated by three models in areas of intense LULCC of varying sign and magnitude (between −0.47 and 0.10 K). Modifications of the land carbon pool by LULCC are disentangled in accordance with processes that can lead to increases and decreases in this carbon pool. Global land carbon losses due to LULCC are simulated by all models: 218, 57, 35 and 34 Gt C by MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR and CanESM2, respectively. On the contrary, the CO2-fertilization effect caused by elevated atmospheric CO2 concentrations due to LULCC leads to a land carbon gain of 39 Gt C in MPI-ESM-LR and is almost negligible in the other models. A substantial part of the spread in models' responses to LULCC is attributed to the differences in implementation of LULCC (e.g., whether pastures or crops are simulated explicitly) and the simulation of specific processes. Simple idealized experiments with clear protocols for implementing LULCC in ESMs are needed to increase the understanding of model responses and the statistical significance of results, especially when analyzing the regional-scale impacts of LULCC.

Description: The impact of historical land use induced land cover change (LULCC) on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes is amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperature to LULCC is relatively large, we conclude that unless this forcing is included we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.

Description: Previous modeling and empirical studies have shown that the biophysical impact of deforestation is to warm the tropics and cool the extra-tropics. In this study, we use an earth system model to investigate how deforestation at various spatial scales affects ground temperature, with an emphasis on the latitudinal temperature response and its underlying mechanisms. Results show that the latitudinal pattern of temperature response depends non-linearly on the spatial extent of deforestation and the fraction of vegetation change. Compared with regional deforestation, temperature change in global deforestation is greatly amplified in temperate and boreal regions, but is dampened in tropical regions. Incremental forest removal leads to increasingly larger cooling in temperate and boreal regions, while the temperature increase saturates in tropical regions. The latitudinal and spatial patterns of the temperature response are driven by two processes with competing temperature effects: decreases in absorbed shortwave radiation due to increased albedo and decreases in evapotranspiration. These changes in the surface energy balance reflect the importance of the background climate on modifying the deforestation impact. Shortwave radiation and precipitation have an intrinsic geographical distribution that constrains the effects of biophysical changes and therefore leads to temperature changes that are spatially varying. For example, wet (dry) climate favors larger (smaller) evapotranspiration change, thus warming (cooling) is more likely to occur. Further analysis on the contribution of individual biophysical factors (albedo, roughness, and evapotranspiration efficiency) reveals that the latitudinal signature embodied in the temperature change probably result from the background climate conditions rather than the initial biophysical perturbation.

Description: A primary goal of Earth system modelling is to improve understanding of the interactions and feedbacks between human decision making and biophysical processes. The nexus of land use and land cover change (LULCC) and the climate system is an important example. LULCC contributes to global and regional climate change, while climate affects the functioning of terrestrial ecosystems and LULCC. However, at present, LULCC is poorly represented in global circulation models (GCMs). LULCC models that are explicit about human behaviour and decision-making processes have been developed at local to regional scales, but the principles of these approaches have not yet been applied to the global scale level in ways that deal adequately with both direct and indirect feedbacks from the climate system. In this article, we explore current knowledge about LULCC modelling and the interactions between LULCC, GCMs and dynamic global vegetation models (DGVMs). In doing so, we propose new ways forward for improving LULCC representations in Earth system models. We conclude that LULCC models need to better conceptualise the alternatives for upscaling from the local to global scale. This involves better representation of human agency, including processes such as learning, adaptation and agent evolution, formalising the role and emergence of governance structures, institutional arrangements and policy as endogenous processes and better theorising about the role of teleconnections and connectivity across global networks. Our analysis underlines the importance of observational data in global-scale assessments and the need for coordination in synthesising and assimilating available data.

Description: Biogeophysical (BGP) and biogeochemical (BGC) effects of land-use and land cover change (LULCC) are separated at the global and regional scales in new interactive CO2 simulations for the 21st century. Results from four Earth System models (ESMs) are analyzed for the future RCP8.5 scenario from simulations with and without land-use and land cover change (LULCC) contributing to the Land-Use and Climate, IDentification of robust impacts (LUCID) project. Over the period, 2006–2100, LULCC causes the atmospheric CO2 concentration to increase by 12, 22, and 66 ppm in CanESM2, MIROC-ESM, and MPI-ESM-LR, respectively. Statistically significant changes in global near-surface temperature are found in three models with a BGC-induced global mean annual warming between 0.07 and 0.23 K. BGP-induced responses are simulated by three models in areas of intense LULCC of varying sign and magnitude (between −0.47 and 0.10 K). Global land carbon losses due to LULCC are simulated by all models: 218, 57, 35 and 34 Gt C by MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR and CanESM2, respectively. On the contrary, the CO2-fertilization effect caused by elevated atmospheric CO2 concentrations due to LULCC leads to a land carbon gain of 39 Gt C in MPI-ESM-LR and is almost negligible in the other models. A substantial part of the spread in models' responses to LULCC is attributed to the differences in implementation of LULCC (e.g. whether pastures or crops are simulated explicitly) and the simulation of specific processes. Simple idealized experiments with clear protocols for implementing LULCC in ESMs are needed to increase the understanding of model responses and the statistical significance of results, especially, when analyzing the regional-scale impacts of LULCC.