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Today societies face an unprecedented challenge to limit global warming and restore agricultural soils. Recent studies show that the introduction of cover crops over Europe could result in a cooling impact due to an increase in soil organic carbon stocks, a decrease in the use of fertilizers, and an increase in surface albedo of the croplands. Based on the use of remote sensing data, land cover database, meteorological data, national agricultural statistics, and ground measurements, a generic model was developed to simulate the radiative forcing following the change in surface albedo. This article analyzes the impact of the introduction of cover crops in Europe during the fallow periods. Compared to previous studies, this work discusses: (i) The maximum greening potential in Europe and the associated indirect surface properties changes (ii) for snowfall episodes, and (iii) due to an increase in organic matter. This study shows that the mitigation potential of cover crops through albedo effects could reach 6.74 MtCO2-eq.yr−1 by extending the periods of the introduction of the cover crops to all possible fallow periods. This mitigation could be limited to 5.68 MtCO2-eq.yr−1 if the impact of snowfalls is considered. This would be equivalent to 9.12 gCO2.m−2.yr−1. Finally, this study investigates the feedback loop due to soil darkening with soil organic carbon content increase when cover crops are introduced, considering two scenarios. The first considers the soil organic carbon content increase following repeated incorporation of cover crop biomass into the soil, simulated with the DayCent model. The second, more conceptual and extreme scenario aims at alerting on the possible impact of a combination of carbon farming practices, such as biochar or organic amendments. Our results show that this effect could lead to a loss of 20% of the climate benefit (i.e., 5.39 MtCO2-eq.yr−1). In conclusion, this study shows that cover crops have a strong potential for climate mitigation through direct albedo effects (soil coverage). However, once introduced, cropland should be permanently covered by vegetation or straws in order to avoid this darkening feedback loop effect. [ABSTRACT FROM AUTHOR]

In the context of the first phase of the Euro-CORDEX Flagship Plot Study (FPS) Land Use and Climate Across Scales (LUCAS), we investigate the afforestation impact on the seasonal cycle of soil temperature over the European continent with an ensemble of ten regional climate models (RCMs). For this purpose, each ensemble member performed two idealized land cover experiments in which Europe is covered either by forests or grasslands. The multi-model mean exhibits a reduction of the annual amplitude of soil temperature (AAST) over all European regions, although this not a robust feature among the models. In Mediterranean, the simulated AAST response to afforestation is between -4 K and +2 K while in Scandinavia the inter-model spread ranges from -7 K to +1 K. We then examine the role of changes in the annual amplitude of ground heat flux (AAGHF) and summer soil moisture content (SMC) in determining the effect of afforestation on AAST response. In contrast with the diverging results in AAST, all the models consistently indicate a widespread AAGHF decrease and summer SMC decline due to afforestation. The AAGHF changes effectively explain the largest part of the inter-model variance in AAST response in most regions, while the changes in summer SMC determine the sign of AAST response within a group of three simulations sharing the same land surface model. Finally, we pair FLUXNET sites to compare the simulated results with observation-based evidence of the impact of forest on soil temperature. In line with models, observations indicate a summer ground cooling in forested areas compared to open lands. The vast majority of models agree with the sign of the observed reduction in AAST, although with a large variation in the magnitude of changes. Overall, we aspire to emphasize the effects of afforestation on soil temperature profile with this study, given that changes in the seasonal cycle of soil temperature potentially perturb crucial biochemical processes. Such perturbations can be of societal relevance as afforestation is proposed as a climate change mitigation strategy. [ABSTRACT FROM AUTHOR]

Around 70 Mha of land cover changes (LCCs) occurred in Europe from 1992 to 2015. Despite LCCs being an important driver of regional climate variations, their temperature effects at a continental scale have not yet been assessed. Here, we integrate maps of historical LCCs with a regional climate model to investigate air temperature and humidity effects. We find an average temperature change of −0.12 ± 0.20 °C, with widespread cooling (up to −1.0 °C) in western and central Europe in summer and spring. At continental scale, the mean cooling is mainly correlated with agriculture abandonment (cropland-to-forest transitions), but a new approach based on ridge-regression decomposing the temperature change to the individual land transitions shows opposite responses to cropland losses and gains between western and eastern Europe. Effects of historical LCCs on European climate are non-negligible and region-specific, and ignoring land-climate biophysical interactions may lead to sub-optimal climate change mitigation and adaptation strategies. Land cover change contributes to regional climate trends. Here, the authors use high-resolution land cover maps and state-of-the-art climate modelling to assess land cover change effects across Europe over 1992-2015, showing widespread cooling after agricultural abandonment but also different, region-specific effects. [ABSTRACT FROM AUTHOR]

• A RCM is used to study the effect of LCC on climate extremes in Europe. • LCC significantly changes the occurrence frequency and duration of extreme climate. • Increasing understanding of land cover change-climate interactions. • Findings are helpful in developing future land management strategies in Europe. Extremes in climate and weather can pose significant challenges to economy, ecosystems and human health. Changes in land cover are one of the drivers for variability in frequency and magnitude of extreme climate at regional and local levels. In this study, a regional climate model (COSMO-CLM v4.8) is used to simulate effects in climate extremes from two different idealized land cover change scenarios in Europe. These two simulations involve abrupt large-scale conversion of today forestland to herbaceous vegetation (deforestation), and of today cropland to evergreen needle-leave forest (afforestation). A control simulation with today land cover distribution is used to identify differences in extreme climate. We find significant changes in extreme climate in both deforestation and afforestation simulations, with seasonal and spatial differences. Deforestation causes a warmer summer (with higher annual maximum temperature) and a colder winter (with lower annual minimum temperature). Afforestation slightly increases the average intensity of the hot extremes, although with high spatial variability (a reduction is common in several locations), and mitigates cold extremes in winter. Changes in extreme indices show that deforestation increases both the frequency and duration of hot and cold extremes, while afforestation causes a lower frequency of extreme cold climate. The two simulations show opposing results in the number of frozen days, as they increase for deforestation and decrease for afforestation. A drier climate is found after deforestation, whereas a wetter climate is observed after afforestation. In general, deforestation and afforestation increase the frequency of hot extreme climate as they reduce the return period and increase the return level. Overall, our findings show the potential critical effects that land cover changes can have on climate extremes, and the possible synergies that land management strategies and planning can have for climate change mitigation and adaptation at a regional scale. [ABSTRACT FROM AUTHOR]

Context: Integrative mitigation and adaptation strategies are needed to counter climate change. Indicators can be valuable that focus on the specific relevance of cities' socioeconomic and spatial properties. While previous analyses have identified socioeconomic influences on urban greenhouse gas emissions, information about the role of spatial urban structures and land use and land cover patterns is sparse. Objective: This study advances the use of spatial metrics for analyzing the linkages between the spatial properties of a city and its greenhouse gas emissions. Methods: The relationship between nine types of spatial structure, four land use and land cover-based indicators, and the emissions of 52 European cities is investigated by spatially and statistically analyzing high resolution data from European Union's 'Urban Atlas'. Results: Spatial determinants of urban greenhouse gas emissions are identified, indicating a strong connection between urban sprawl and increasing emissions. In particular, high amounts of sparsity in the urban fabric within large distances to the city center relate to increased per capita emissions. Thus, a 10 % reduction of very low density urban fabrics is correlated with 9 % fewer emissions per capita. In contrast, high amounts of fragmented, dense urban patches relate with lower emissions. Conclusions: This study links urban spatial properties and land use and land cover compositions to greenhouse gas emissions and advances the understanding of urban sprawl. Future research needs to combine knowledge about socioeconomic drivers with information about the identified spatial influences of urban greenhouse gas emissions to help cities realize their climate change mitigation potential. [ABSTRACT FROM AUTHOR]

Today, European forests face many challenges but also offer opportunities, such as climate change mitigation, provision of renewable resources, energy and other ecosystem services. Large-scale analyses to assess these opportunities are hindered by the lack of a consistent, spatial and accessible forest structure data. This study presents a freely available pan-European forest structure data set. Building on our previous work, we used data from six additional countries and consider now ten key forest stand variables. Harmonized inventory data from 16 European countries were used in combination with remote sensing data and a gap-filling algorithm to produce this consistent and comparable forest structure data set across European forests. We showed how land cover data can be used to scale inventory data to a higher resolution which in turn ensures a consistent data structure across sub-regional, country and European forest assessments. Cross validation and comparison with published country statistics of the Food and Agriculture Organization (FAO) indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe, even for areas where no inventory data were available. [ABSTRACT FROM AUTHOR]