A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP)

Flux footprint models are often used for interpretation of flux tower measurements, to estimate position and size of surface source areas, and the relative contribution of passive scalar sources to measured fluxes. Accurate knowledge of footprints is of crucial importance for any upscaling exercises from single site flux measurements to local or regional scale. Hence, footprint models are ultimately also of considerable importance for improved greenhouse gas budgeting. With increasing numbers of flux towers within large monitoring networks such as FluxNet, ICOS (Integrated Carbon Observation System), NEON (National Ecological Observatory Network), or AmeriFlux, and with increasing temporal range of observations from such towers (of the order of decades) and availability of airborne flux measurements, there has been an increasing demand for reliable footprint estimation. Even though several sophisticated footprint models have been developed in recent years, most are still not suitable for application to long time series, due to their high computational demands. Existing fast footprint models, on the other hand, are based on surface layer theory and hence are of restricted validity for real-case applications. <br><br> To remedy such shortcomings, we present the two-dimensional parameterisation for Flux Footprint Prediction (FFP), based on a novel scaling approach for the crosswind distribution of the flux footprint and on an improved version of the footprint parameterisation of Kljun et al. (2004b). Compared to the latter, FFP now provides not only the extent but also the width and shape of footprint estimates, and explicit consideration of the effects of the surface roughness length. The footprint parameterisation has been developed and evaluated using simulations of the backward Lagrangian stochastic particle dispersion model LPDM-B (Kljun et al., 2002). Like LPDM-B, the parameterisation is valid for a broad range of boundary layer conditions and measurement heights over the entire planetary boundary layer. Thus, it can provide footprint estimates for a wide range of real-case applications. <br><br> The new footprint parameterisation requires input that can be easily determined from, for example, flux tower measurements or airborne flux data. FFP can be applied to data of long-term monitoring programmes as well as be used for quick footprint estimates in the field, or for designing new sites

Application of long-range weather forecasts to agricultural decision problems in Europe

Agriculture can benefit substantially from long-range weather forecasts, for the month or the season, which can help to optimize farming operations and deal more effectively with the adverse impacts of climate variability, including extreme weather events. In the context of climate change, long-range weather forecasts also represent key elements for the development of adaptation strategies. In spite of an undeniable potential, long-range forecasts issued for instance by the European Centre for Medium-Range Weather Forecasts (ECMWF) have yet to find widespread application in European agriculture. To address partially the question of why this is the case, the performance of the ECMWF monthly ensemble forecasting system was examined. It was noted that predictability is currently limited to about 3 weeks for temperature and 2 weeks for precipitation and solar radiation. This may appear deceptive at first sight, but it was noticed that precipitation forecasts over a month are, overall, at least as valuable as information obtained from observed climatology. Encouraged by this finding, the possibility of using monthly forecasts to predict soil water availability was tested. In an operational context, this could serve as a basis for scheduling irrigation. Positive skills were found for lead times of up to 1 month. It was concluded that more systematic investigations of the possibilities offered by long-range forecasts should be undertaken in the future. However, this will require additional efforts to increase the quality of the forecasts, design appropriate application tools and promote the dissemination of the outcome within the agriculture communit

Tethered balloon measurements of biogenic volatile organic compounds at a Boreal forest site

Measurements of biogenic volatile organic compounds (VOCs) were performed at Hyytiälä, a Boreal forest site in Southern Finland as part of the OSOA (origin and formation of secondary organic aerosol) project in August 2001. At this site, frequent formation of new particles has been observed and the role of biogenic VOCs in this process is still unclear. Tethered balloons served as platforms to collect VOC samples within the planetary boundary layer at heights up to 1.2 km above ground during daytime. Mean mixed layer concentrations of total monoterpenes varied between 10 and 170 pptv, with <font face='Symbol'>a</font>-pinene, limonene and <font face='Symbol'>D</font>³-carene as major compounds, isoprene was detected at levels of 2-35 pptv. A mixed layer gradient technique and a budget approach are applied to derive surface fluxes representative for areas of tens to hundreds of square kilometres. Effects of spatial heterogeneity in surface emissions are examined with a footprint analysis. Depending on the source area considered, mean afternoon emissions of the sum of terpenes range between 180 and 300 <font face='Symbol'>m</font>g m^-2 h^-1 for the period of 2-12 August 2001. Surface fluxes close to Hyytiälä were higher than the regional average, and agree well with mean emissions predicted by a biogenic VOC emission model. Total rates of monoterpene oxidation were calculated with a photochemical model. The rates did not correlate with the occurrence of new particle formation, but the ozone pathway was of more importance on days with particle formation. Condensable vapour production from the oxidation of monoterpenes throughout the mixed layer can only account for a fraction of the increase in aerosol mass observed at the surface

Implications of changes in seasonal mean temperature for agricultural production systems: three case studies

- The performance of dairy cows will suffer from elevated temperatures, reflecting the extent and uncertainty of projected warming in different scenarios, with a marked increase in heat stress for non-intervention scenarios (A1B and A2) toward the end of the century. This calls for the adoption of protective measures in the management of indoor and outdoor animal environments. - A substantial risk of a prolonged pest control season for the codling moth (an apple pest) is projected toward the end of the century for Northern Switzerland sites, and mid-century for the Ticino. Timely preventive programs are anticipated to represent a key ingredient of adaptation to changing risks from agricultural pests. - Results suggest that in the near future viticulture could benefit from increasing temperatures as a wider range of grape varieties could be grown. Toward the end of the century negative impacts from extreme temperatures are nevertheless expected to become important

A Motor Learning Oriented, Compliant and Mobile Gait Orthosis

People affected by Cerebral Palsy suffer from physical disabilities due to irreversible neural impairment since the very beginning of their life. Difficulties in motor control and coordination often relegate these patients to the use of a wheelchair and to the unavoidable upcoming of disuse syndromes. As pointed out in recent literature Damiano [7] physical exercise, especially in young ages, can have a deep impact on the patient health and quality of life. For training purposes is very important to keep an upright position, although in some severe cases this is not trivial. Many commercial mobile orthoses are designed to facilitate the standing, but not all the patients are able to deploy them. ARGO, the Active Reciprocated Gait Orthosis we developed, is a device that overcomes some of the limitations of these devices. It is an active device that is realized starting from a commercial reciprocated Gait Orthosis applying sensors and actuators to it. With ARGO we aim to develop a device for helping limbs in a non-coercive way accordingly to user’s intention. In this way patients can drive the orthosis by themselves, deploying augmented biofeedback over movements. In fact Cerebral Palsy patients usually have weak biofeedback mechanisms and consequently are hardly inclined to learn movements. To achieve this behavior ARGO deploys a torque planning algorithm and a force control system. Data collected from a single case of study shows benefits of the orthosis. We will show that our test patient reaches complete autonomous walking after few hour of training with prototype

Dynamic simulation of management events for assessing impacts of climate change on pre-alpine grassland productivity

The productivity of permanent temperate cut grasslands is mainly driven by weather, soil characteristics, botanical composition and management. To adapt management to climate change, adjusting the cutting dates to reflect earlier onset of growth and expansion of the vegetation period is particularly important. Simulations of cut grassland productivity under climate change scenarios demands management settings to be dynamically derived from actual plant development rather than using static values derived from current management operations. This is even more important in the alpine region, where the predicted temperature increase is twice as high as compared to the global or Northern Hemispheric average. For this purpose, we developed a dynamic management module that provides timing of cutting and manuring events when running the biogeochemical model LandscapeDNDC. We derived the dynamic management rules from long-term harvest measurements and monitoring data collected at pre-alpine grassland sites located in S Germany and belonging to the TERENO monitoring network. We applied the management module for simulations of two grassland sites covering the period 2011–2100 and driven by scenarios that reflect the two representative concentration pathways (RCP) 4.5 and 8.5 and evaluated yield developments of different management regimes. The management module was able to represent timing of current management operations in high agreement with several years of field observations (r2 > 0.88). Even more, the shift of the first cutting dates scaled to a +1 ◦C temperature increase simulated with the climate change scenarios (− 9.1 to − 17.1 days) compared well to the shift recorded by the German Weather Service (DWD) in the study area from 1991− 2016 (− 9.4 to − 14.0 days). In total, the shift in cutting dates and expansion of the growing season resulted in 1− 2 additional cuts per year until 2100. Thereby, climate change increased yields of up to 6 % and 15 % in the RCP 4.5 and 8.5 scenarios with highest increases mainly found for dynamically adapted grassland management going along with increasing fertilization rates. In contrast, no or only minor yield increases were associated with simulations restricted to fertilization rates of 170 kg N ha− 1 yr− 1 as required by national legislations. Our study also shows that yields significantly decreased in drought years, when soil moisture is limiting plant growth but due to comparable high precipitation and water holding capacity of soils, this was observed mainly in the RCP 8.5 scenario in the last decades of the century

Impact of Climate Change on Voltinism and Prospective Diapause Induction of a Global Pest Insect – Cydia pomonella (L.)

Global warming will lead to earlier beginnings and prolongation of growing seasons in temperate regions and will have pronounced effects on phenology and life-history adaptation in many species. These changes were not easy to simulate for actual phenologies because of the rudimentary temporal (season) and spatial (regional) resolution of climate model projections. We investigate the effect of climate change on the regional incidence of a pest insect with nearly worldwide distribution and very high potential for adaptation to season length and temperature – the Codling Moth, Cydia pomonella. Seasonal and regional climate change signals were downscaled to the hourly temporal scale of a pest phenology model and the spatial scale of pest habitats using a stochastic weather generator operating at daily scale in combination with a re-sampling approach for simulation of hourly weather data. Under future conditions of increased temperatures (2045–2074), the present risk of below 20% for a pronounced second generation (peak larval emergence) in Switzerland will increase to 70–100%. The risk of an additional third generation will increase from presently 0–2% to 100%. We identified a significant two-week shift to earlier dates in phenological stages, such as overwintering adult flight. The relative extent (magnitude) of first generation pupae and all later stages will significantly increase. The presence of first generation pupae and later stages will be prolonged. A significant decrease in the length of overlap of first and second generation larval emergence was identified. Such shifts in phenology may induce changes in life-history traits regulating the life cycle. An accordingly life-history adaptation in photoperiodic diapause induction to shorter day-length is expected and would thereby even more increase the risk of an additional generation. With respect to Codling Moth management, the shifts in phenology and voltinism projected here will require adaptations of plant protection strategies to maintain their sustainability

Process-based modelling of the nutritive value of forages: a review

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Evaluation of a high-resolution regional climate simulation over Greenland

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.Peer reviewe

Modelling responses of forages to climate change with a focus on nutritive value

European livestock agriculture is extraordinarily diverse, and so are the challenges it faces. This diversity has contributed to the development of a fragmented set of research communities. As a result, livestock research is often under-represented at policy level, despite its high relevance for the environment and food security.Understanding livestock systems and how they can sustainably adapt to global change requires inputs across research areas, including grasslands, nutrition, health, welfare and ecology. It also requires experimental researchers, modellers and stakeholders to work closely together.Networks and capacity building structures are vital to enable livestock research to meet the challenges of climate change. They need to maintain shared resources and provide non-competitive arenas to share and synthesize results for policy support.  Long term strategic investment is needed to support such structures. Their leadership requires very different skills to those effective in scientific project coordination