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Urine patches from grazing cattle are hotspots of nitrous oxide (N2O) emissions. The default IPCC emission factor for urine patches (EFurine) is 0.77% for wet climates and 0.32% for dry climates. However, literature reports a considerable range of cattle urine EF values and urine characteristics used in experimental studies, revealing contrary results on the effects of urine patch characteristics and seasonal pattern. Therefore, we examined N2O emissions and corresponding EFurine values in relation to urine patch characteristics (urine N concentration, urine volume, patch area, urine composition) and environmental drivers (precipitation, water filled pore space, soil temperature). Ten artificial urine application experiments were performed from July 2020 to June 2022 on a pasture located in Eastern Switzerland. Urine N concentration, patch area, volume and urine N composition showed no significant effects on the EFurine value (p > 0.05). EFurine varied, however, strongly over time (0.17–2.05%). A large part of the variation could be predicted either by cumulative precipitation 20 days after urine application using a second order polynomial model (Adj. R2 = 0.60) or average WFPS 30 days after urine application using a linear model (Adj. R2 = 0.45). The derived precipitation model was used to simulate EFurine weekly over the last 20 years showing no significant differences between the seasons of a year. The resulting overall average EFurine was 0.67%. More field studies are needed across sites/regions differing in climate and soil properties to implement a country-specific EF3 for Switzerland and to improve the quantification of N2O emissions at the national scales. [ABSTRACT FROM AUTHOR]

In this study, we investigated the consequences of climate change on bioclimatic indices in vineyards along the edge of Lake Neuchatel in Switzerland. Like in other vineyards all around the world, the typicity of wines and the phenology of vines have changed, particularly since the 1970s. Trends in the growing season average temperature and in Huglin's heliothermal index show that the climate in the Neuchatel vineyards changed from very cool or cool to temperate during the last decades. Trends in the cool night index and in the prior to harvest cool night index both indicate that in the near future this wine region will frequently experience temperate instead of cool nights during the weeks leading up to harvest. Our results highlight the need for adaptation strategies, such as an upward elevational shift for Pinot Noir, as climatic conditions will become too warm at its current location in the next decades. They also show that conditions in this region are already favorable for more thermophilic varieties such as Merlot. In the context of global warming, this kind of analysis should be conducted throughout winegrowing regions in order to develop efficient adaptation strategies at the microclimatic scale. [ABSTRACT FROM AUTHOR]

Global changes pose both risks and opportunities to agriculture and forestry, and biological forecasts can inform future management strategies. Here, we investigate potential land-use opportunities arising from climate change for these sectors in Europe, and risks associated with the introduction and establishment of novel insect pests. Adopting a metaweb approach including all interaction links between 126 crops and forest tree species and 89 black-listed insect pest species, we show that the metawebs shift toward increased numbers of links and overlap of suitable area under climate change. Decomposing the metaweb across regions shows large saturation in southern Europe, while many novel interactions are expected for northern Europe. In light of the rising consumer awareness about human health and environmental impacts of food and wood production, the challenge will be to effectively exploit new opportunities to create diverse local agriculture and forestry while controlling pest species and reducing risks from pesticide use. Marc Grünig et al. report a study of land-use opportunities and risks of introducing novel insect pests in Europe that may arise from global climate change. Using a metaweb approach, they find that there is a predicted general increase in risk of pests to managed plant species under climate change due to an increase in land with suitable climate for both pests and plants. [ABSTRACT FROM AUTHOR]

Accumulated growing degree-days (aGDD) are widely used to predict phenological stages of plants and insects. It has been shown in the past that the best predictive performance is obtained when aGDD are computed from hourly temperature data. As the latter are not always available, models of diurnal temperature changes are often employed to retrieve the required information from data of daily minimum and maximum temperatures. In this study, we examine the performance of a well-known model of hourly temperature variations in the context of a spatial assessment of aGDD. Specifically, we examine whether a generic calibration of such a temperature model is sufficient to infer in a reliable way spatial patterns of key phenological stages across the complex territory of Switzerland. Temperature data of a relatively small number of meteorological stations is used to obtain a generic model parameterization, which is first compared with site-specific calibrations. We show that, at the local scale, the predictive skill of the generic model does not significantly differ from that of the site-specific models. We then show that for aGDD up to 800 °C d (on a base temperature of 10 °C), phenological dates predicted with aGDD obtained from estimated hourly temperature data are within ± 3 days of dates estimated on the basis of observed hourly temperatures. This suggests the generic calibration of hourly temperature models is indeed a valid approach for pre-processing temperature data in regional studies of insect and plant phenology. [ABSTRACT FROM AUTHOR]

Smallholder agriculture in the Central Andes of Peru is based to large extent on rainfed cropping systems, is exposed to climatic risks and is expected to respond sensitively to increasing temperatures and shifts in the precipitation regime. Here, we examine the potential implications of early twenty-first century climate change scenarios for the cultivation of potato, maize, wheat, barley and broad bean, five annual crops that account for 50 % of the cultivated area in the Department of Cusco and Apurímac and provide the dietary backbone for a large share of the local population. The scenarios disclose a regionally coherent increase in temperature of the order of 1 °C but overall only moderate changes in growing season precipitation by 2030. A simple crop model is used to assess the effects of these changes on crop phenology and development. The results show earlier harvest dates, shorter cropping seasons and, in a few cases, a slightly higher risk of planting failure in the near future. This suggests that a better understanding of changes in the precipitation regime at the onset of the cropping season is required to evaluate short-term needs and possibilities for adaptation. However, as the scenarios are highly uncertain, these conclusions should be verified. [ABSTRACT FROM AUTHOR]

Besides its primary role in producing food and fiber, agriculture also has relevant effects on several other functions, such as management of renewable natural resources. Climate change (CC) may lead to new trade-offs between agricultural functions or aggravate existing ones, but suitable agricultural management may maintain or even improve the ability of agroecosystems to supply these functions. Hence, it is necessary to identify relevant drivers (e.g., cropping practices, local conditions) and their interactions, and how they affect agricultural functions in a changing climate. The goal of this study was to use a modeling framework to analyze the sensitivity of indicators of three important agricultural functions, namely crop yield (food and fiber production function), soil erosion (soil conservation function), and nutrient leaching (clean water provision function), to a wide range of agricultural practices for current and future climate conditions. In a two-step approach, cropping practices that explain high proportions of variance of the different indicators were first identified by an analysis of variance-based sensitivity analysis. Then, most suitable combinations of practices to achieve best performance with respect to each indicator were extracted, and trade-offs were analyzed. The procedure was applied to a region in western Switzerland, considering two different soil types to test the importance of local environmental constraints. Results show that the sensitivity of crop yield and soil erosion due to management is high, while nutrient leaching mostly depends on soil type. We found that the influence of most agricultural practices does not change significantly with CC; only irrigation becomes more relevant as a consequence of decreasing summer rainfall. Trade-offs were identified when focusing on best performances of each indicator separately, and these were amplified under CC. For adaptation to CC in the selected study region, conservation soil management and the use of cropped grasslands appear to be the most suitable options to avoid trade-offs. [ABSTRACT FROM AUTHOR]

In several regions of the world, climate change is expected to have severe impacts on agricultural systems. Changes in land management are one way to adapt to future climatic conditions, including land-use changes and local adjustments of agricultural practices. In previous studies, options for adaptation have mostly been explored by testing alternative scenarios. Systematic explorations of land management possibilities using optimization approaches were so far mainly restricted to studies of land and resource management under constant climatic conditions. In this study, we bridge this gap and exploit the benefits of multi-objective regional optimization for identifying optimum land management adaptations to climate change. We design a multi-objective optimization routine that integrates a generic crop model and considers two climate scenarios for 2050 in a meso-scale catchment on the Swiss Central Plateau with already limited water resources. The results indicate that adaptation will be necessary in the study area to cope with a decrease in productivity by 0–10 %, an increase in soil loss by 25–35 %, and an increase in N-leaching by 30–45 %. Adaptation options identified here exhibit conflicts between productivity and environmental goals, but compromises are possible. Necessary management changes include (i) adjustments of crop shares, i.e. increasing the proportion of early harvested winter cereals at the expense of irrigated spring crops, (ii) widespread use of reduced tillage, (iii) allocation of irrigated areas to soils with low water-retention capacity at lower elevations, and (iv) conversion of some pre-alpine grasslands to croplands. [ABSTRACT FROM AUTHOR]

We present the integration of early 21st century climate projections for Europe based on simulations carried out within the EU-FP6 ENSEMBLES project with the LARS-WG stochastic weather generator. The aim was to upgrade ELPIS, a repository of local-scale climate scenarios for use in impact studies and risk assessments that already included global projections from the CMIP3 ensemble and regional scenarios for Japan. To obtain a more reliable simulation of daily rainfall and extremes, changes in wet and dry series derived from daily ENSEMBLES outputs were taken into account. Kernel average smoothers were used to reduce noise arising from sampling artefacts. Examples of risk analyses based on 25-km climate projections from the ENSEMBLES ensemble of regional climate models illustrate the possibilities offered by the updated version of ELPIS. The results stress the importance of tailored information for local-scale impact assessments at the European level. [ABSTRACT FROM AUTHOR]

In this paper, we assess climate change impacts on an intensively managed grassland system at the Swiss Plateau using the process-based grassland model PROGRASS. Taking the CO fertilization into account, we find increasing yield levels (in the range of 10-24%) and sharp increases in production risks for an illustrative climate change scenario that suggests a marked increase in temperature and decrease in summer rainfall. Climate change-induced increases in the coefficients of variation of grassland yields are in the range of 21 and 50%. This finding underpins that additional risk management strategies are needed to cope with climate-change impacts on grassland production. The outputs from the grassland model are evaluated economically using certainty equivalents, i.e., accounting for mean quasi rents and production risks. To identify potential risk management strategies under current and future climatic conditions, we consider adjustments of production intensity and farm-level yield insurance. The impact of climate change on production intensities is found to be ambiguous: farmers' will increase intensity under unconstrained production conditions, but will decrease production intensity in the presence of a cross-compliance scheme. Our results also show that the considered insurance scheme is a powerful tool to manage climate risks in grassland production under current and future conditions because it can reduce the coefficients of variation of quasi rents by up to 50%. However, we find that direct payments tend to reduce farmers' incentives to use such insurance scheme. [ABSTRACT FROM AUTHOR]

The Mesoscale Alpine Programme’s Riviera project investigated the turbulence structure and related exchange processes in an Alpine valley by combining a detailed experimental campaign with high-resolution numerical modelling. The present contribution reviews published material on the Riviera Valley’s boundary layer structure and discusses new material on the near-surface turbulence structure. The general conclusion of the project is that despite the large spatial variability of turbulence characteristics and the crucial influence of topography at all scales, the physical processes can accurately be understood and modelled. Nevertheless, many of the “text book characteristics” like the interaction between the valley and slope wind systems or the erosion of the nocturnal valley inversion need reconsideration, at least for small non-ideal valleys like the Riviera Valley. The project has identified new areas of research such as post-processing methods for turbulence variables in complex terrain and new approaches for the surface energy balance when advection is non-negligible. The exchange of moisture and heat between the valley atmosphere and the free troposphere is dominated by local “secondary” circulations due to the curvature of the valley axis. Because many curved valleys exist, and operational models still have rather poor resolution, parameterization of these processes may be required. [ABSTRACT FROM AUTHOR]

A simple model of yield was used along with climate scenarios to assess the impact of climate change on grain maize productivity and associated economic risk in Switzerland. In a first application, changes in the precipitation regime alone were shown to affect the distribution of yield considerably, with shifts not only in the mean but also in the standard deviation and the skewness. Production risk was found to respond more markedly to changes in the long-term mean than in the inter-annual variability of seasonal precipitation amounts. In a further application, yield projections were generated with respect to a full climate scenario, with the emission pathway as specified in the IPCC A2 scenario. Anticipation of the sowing date was found to reduce the negative impact of climate change on yield stability, but was not sufficient to ensure average productivity levels comparable to those observed at present. We argued that this was caused by the reduction in the duration of the growing season, which had a stronger impact than suggested by previous studies. Assuming no change in price relations, the results also revealed a strong increase in production risk with climate change, with more than a doubling in the probability of yield falling short of a critical threshold as compared to today’s situation. [ABSTRACT FROM AUTHOR]

Changes of the summer evapotranspiration regime under increased levels of atmospheric greenhouse gases are discussed for three Alpine river basins on the basis of a new set of simulations carried out with a high-resolution hydrological model. The climate change signal was inferred from the output of two simulations with a state-of-the-art global climate model (GCM), a reference run valid for 1961--1990 and a time-slice simulation valid for 2071--2100 under forcing from the A2 IPCC emission scenario. In this particular GCM experiment and with respect to the Alpine region summer temperature was found to increase by 3 to 4.C, whereas precipitation was found to decrease by 10 to 20%. Global radiation and water vapor pressure deficit were found to increase by about 5% and 2 hPa, respectively. On this background, an overall increase of potential evapotranspiration of about 20% relative to the baseline was predicted by the hydrological model, with important variations between but also within individual basins. The results of the hydrological simulations also revealed a reduction in the evapotranspiration efficiency that depends on altitude. Accordingly, actual evapotranspiration was found to increase at high altitudes and to the south of the Alps, but to decrease in low elevation areas of the northern forelands and in the inner-Alpine domain. Such a differentiation does not appear in the GCM scenario, which predicts an overall increase in evapotranspiration over the Alps. This underlines the importance of detailed simulations for the quantitative assessment of the regional impact of climate change on the hydrological cycle. [ABSTRACT FROM AUTHOR]

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations. [ABSTRACT FROM AUTHOR]