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Dry deposition is a key component of surface- atmosphere exchange of compounds, acting as a sink for several chemical species. Meteorological factors, chemical properties of the trace gas considered and land surface properties are strong drivers of dry deposition efficiency and variability. Under both climatic and anthropogenic pressure, the vegetation distribution over the Earth has been changing a lot over the past centuries and could be significantly altered in the future. In this study, we perform a modeling investigation of the potential impact of land-cover changes between the present day (2006) and the future (2050) on dry deposition velocities at the surface, with special interest for ozone (O3) and nitric acid (HNO3), two compounds which are characterized by very different physicochemical properties. The 3-D chemistry-transport model LMDz-INCA is used, considering changes in vegetation distribution based on the three future projections, RCPs 2.6, 4.5 and 8.5, and present-day (2007) meteorology. The 2050 RCP 8.5 vegetation distribution leads to a rise of up to 7% (C0:02 cm s-1) in the surface deposition velocity calculated for ozone (Vd,O3) and a decrease of -0:06 cm s-1 in the surface deposition velocity calculated for nitric acid (Vd,HNO3) relative to the present-day values in tropical Africa and up to C18 and -15%, respectively, in Australia. When taking into account the RCP 4.5 scenario, which shows dramatic land-cover change in Eurasia, Vd,HNO3 increases by up to 20% (annual-mean value) and reduces Vd,O3 by the same magnitude in this region. When analyzing the impact of surface dry deposition change on atmospheric chemical composition, our model calculates that the effect is lower than 1 ppb on annual-mean surface ozone concentration for both the RCP 8.5 and RCP 2.6 scenarios. The impact on HNO3 surface concentrations is more disparate between the two scenarios regarding the spatial repartition of effects. In the case of the RCP 4.5 scenario, a significant increase of the surface O3 concentration reaching locally by up to 5 ppb (C5%) is calculated on average during the June-August period. This scenario also induces an increase of HNO3 deposited flux exceeding locally 10% for monthly values. Comparing the impact of land-cover change to the impact of climate change, considering a 0.93 °C increase of global temperature, on dry deposition velocities, we estimate that the strongest increase over lands occurs in the Northern Hemisphere during winter, especially in Eurasia, by C50% (C0:07 cm s-1) for Vd,O3 and C100% (C0:9 cm s-1) for Vd,HNO3. However, different regions are affected by both changes, with climate change impact on deposition characterized by a latitudinal gradient, while the land-cover change impact is much more heterogeneous depending on vegetation distribution modification described in the future RCP scenarios. The impact of long-term land-cover changes on dry deposition is shown to be significant and to differ strongly from one scenario to another. It should therefore be considered in biosphere-atmospheric chemistry interaction studies in order to have a fully consistent picture. [ABSTRACT FROM AUTHOR]

Recent results from the LUCID model intercomparison project have revealed large discrepancies in the simulated evapotranspiration (ET) response to the historical landuse 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 landcover reconstructions and better estimates of cropland ET. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Regional cooling resulting from increases in surface albedo has been identified in several studies as the main biogeophysical effect of past land use-induced land cover changes (LCC) on climate. However, the amplitude of this effect remains quite uncertain due to, among other factors, (a) uncertainties in the extent of historical LCC and, (b) differences in the way various models simulate surface albedo and more specifically its dependency on vegetation type and snow cover. We derived monthly albedo climatologies for croplands and four other land cover types from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. We then reconstructed the changes in surface albedo between preindustrial times and present-day by combining these climatologies with the land cover maps of 1870 and 1992 used by seven land surface models (LSMs) in the context of the LUCID ("Land Use and Climate: identification of robust Impacts") intercomparison project. These reconstructions show surface albedo increases larger than 10% (absolute) in winter, and larger than 2% in summer between 1870 and 1992 over areas that experienced intense deforestation in the northern temperate regions. The historical surface albedo changes estimated with MODIS data were then compared to those simulated by the various climate models participating in LUCID. The inter-model mean albedo response to LCC shows a similar spatial and seasonal pattern to the one resulting from the MODIS-based reconstructions, that is, larger albedo increases in winter than in summer, driven by the presence of snow. However, individual models show significant differences between the simulated albedo changes and the corresponding reconstructions, despite the fact that land cover change maps are the same. Our analyses suggest that the primary reason for those discrepancies is how LSMs parameterize albedo. Another reason, of secondary importance, results from differences in their simulated snow extent. Our methodology is a useful tool not only to infer observations-based historical changes in land surface variables impacted by LCC, but also to point out deficiencies of the models.We therefore suggest that it could be more widely developed and used in conjunction with other tools in order to evaluate LSMs. [ABSTRACT FROM AUTHOR]

Cooling resulting from increases in surface albedo has been identified in several studies as the main biogeophysical effect of past land-use induced land cover changes (LCC) on climate. However, the amplitude of this effect remains quite uncertain due to, among other factors, (a) uncertainties in the magnitude of historical LCC and, (b) differences in the way various models simulate surface albedo and more specifically its dependency on vegetation type and snow cover. We have derived monthly albedo climatologies for croplands and four other land-cover types from MODIS satellite observations. We have then estimated the changes in surface albedo since preindustrial times by combining these climatologies with the land-cover maps of 1870 and 1992 used by modelers in the context of the LUCID intercomparison project. These reconstructions show surface albedo increases larger than 10% (absolute) in winter and 2% in summer between 1870 and 1992 over areas that have experienced intense deforestation in the northern temperate regions. The MODIS-based reconstructions of historical changes in surface albedo were then compared to those simulated by the various models participating to LUCID. The inter-model mean albedo response to LCC shows a similar spatial and seasonal pattern to the one resulting from the reconstructions, that is larger increases in winter than in summer driven by the presence of snow. However, individual models show significant differences with the satellite-based reconstructions, despite the fact that land-cover change maps are the same. Our analyses suggest that the primary reason for those discrepancies is how land-surface models parameterize albedo. Another reason, of secondary importance, results from differences in the simulated snowpack. Our methodology is a useful tool not only to infer observations-based historical changes in land surface variables impacted by LCC, but also to point to major deficiencies within the models; we therefore suggest that it could be more widely developed and used in conjunction with other tools in order to evaluate global land-surface models. [ABSTRACT FROM AUTHOR]

The article presents a study on the effect of land use induced land cover change (LULCC) on temperature and rainfall extremes. It states that four climate models within the land use and climate, identification of robust impacts (LUCID) project protocol were used. It concludes that there is a similarity between the changes in temperature extremes and mean temperature caused by LULCC.

Abstract: Present-day Sahelian vegetation in a highly anthropized semi-arid region is assessed from local to regional scales, through the joint analysis of MODIS LAI (1km2 and 8-day resolutions), daily rainfall, morphopedological and land cover datasets covering the period 2000–2008. The study area is located in northwest Senegal and consists of the “Niayes” and the northwestern “Peanut Basin” eco-regions, characterized by market gardening and rain-fed cultivated crops, respectively. The objectives are i) to analyse at pixel scale LAI time series and their relation to vegetation and soil types, ii) the estimation of phenological metrics (start of season SOS, end of season EOS, growing season length GSL) and their inter-annual variability, iii) to recognize the vegetation responses to rainfall trends (mean annual precipitation, MAP; frequency of rainy events, K; combination of MAP and K, called F). Pixel-scale analyses show that LAI time series 1) describe the actual phenology (agreeing with ground-truth AGHRYMET data), and thus can be used as a proxy for Sahelian vegetation dynamics, 2) are strongly dependent on soil types. Median maps of SOS and EOS suggest an increase of the GSL from Saint-Louis to Dakar, in agreement with both the North-South rainfall gradient and the intensification of agricultural practices around Dakar. Significant correlations (R: 0.64) between annual variation coefficient of LAI and MAP for both herbaceous crops and natural vegetation are highlighted; this correlation is reinforced (R: 0.7) using the rainfall distribution factors K and F. Rainfall thresholds allowing the SOS can be defined for each type of vegetation. These thresholds are estimated at 0–5mm, 20mm and 40mm for natural herbs, herbaceous crops and shrublands, respectively. If previous works revealed the close link between the MAP and the SOS, our results highlight that LAI dynamics are also controlled by rainfall distribution during the Monsoon season. In this study, climatic indicators are proposed for estimating vegetation dynamics and monitoring SOS. Coupling Earth Observation data, such as MODIS LAI, with rainfall data, vegetation and soil information is found to be a reliable method for vegetation monitoring and for assessing the impact of human pressure on vegetation degradation. [Copyright &y& Elsevier]