Abstract: Local-scale daily climate scenarios are required for assessment of climate change impacts. ELPIS is a repository of local-scale climate scenarios for Europe, which are based on the LARS-WG weather generator and future projections from 2 multi-model ensembles, CMIP3 and EU-ENSEMBLES. In ELPIS, the site parameters for the 1980-2010 baseline scenarios were estimated by LARS-WG using daily weather from the European Crop Growth Monitoring System (CGMS) used in many European agricultural assessment studies. The objective of this paper was to compare ELPIS baseline scenarios with observed daily weather obtained independently from the European Climate Assessment (ECA) data set. Several statistical tests were used to compare distributions of climatic variables derived from ECA-observed daily weather and ELPIS-generated baseline scenarios. About 30% of selected sites have a difference in altitude of > 50 m compared with the CGMS grid-cell altitude that was selected to represent agricultural land within a grid-cell. Differences in altitude can explain significant Kolmogorov-Smirnov test (KS-test) results for distribution of daily temperature and in t-tests for temperature monthly means, because of the well-known negative correlation between temperature and elevation. For daily precipitation, the KS-test showed little difference between generated and observed data; however, the more sensitive t-test showed significant results for the sites where altitude differences were large. Approximately 11% of sites showed small positive or negative bias in monthly solar radiation, although 86% sites showed > 3 significant t-test results for monthly means. These results can be explained by differences in conversion of sunshine hours to solar radiation used in CGMS and LARS-WG. We conclude that, considering the limitations above, ELPIS baseline scenarios are suitable for agricultural impact assessments in Europe.

Abstract: Regionalized model calculations showed increased rainfall and temperatures in winter and less precipitation and higher temperatures in summer due to climate change effects in the future for numerous countries in the northern hemisphere. Furthermore, model simulations predicted enhanced weather variability with an increased risk of yield losses and reduced yield stability. Recently, double cropping systems (DCS) were suggested as an environmental friendly and productive adaptation strategy with increased yield stability. This paper reviews the potential benefit of four DCS (rye (Secale cereale L.) as first crop and maize (Zea mays L.), sunflower (Helianthus annuus L.), sorghum (Sorghum sudanense L. x Sorghum bicolor L.) and sudan grass (S. sudanense L.) as second crops) in comparison with four conventional sole cropping systems (SCS) (maize, sunflower, sorghum and sudan grass) with regard to dry matter (DM) yield and soil water under conditions of climate change. We used the agro-ecosystem model HERMES for simulating these variables until the year 2100. The investigated crops sunflower, sorghum and sudan grass were parameterised first for HERMES achieving a satisfying performance. Results showed always higher DM yields per year of DCS compared with SCS. This was mainly caused by yield increases of the first crop winter rye harvested at the stage of milk ripeness. As a winter hardy crop, rye will benefit from increased precipitation and higher temperatures during winter months as well as from extended growth periods with an earlier onset in spring and an increase of growing days. Furthermore, rye is able to use the increased winter humidity for its spring growth in an efficient way. By contrast, model simulations showed that summer crops will be affected by reduced precipitation and higher temperatures during summer month for periods from 2050 onwards with the consequence of reduced yields. This yield reduction was found for all summer crops both in conventional sole crop and in DCS. Preponed harvesting of first crop winter rye as a consequence of earlier onset of growth period in spring under prospective climatic conditions lead to yield decrease, which could not be equalised by preponed sowing of second crops and extension of their growth period. Hence, total annual yield of both crops together decreased. The modification of sowing and harvesting dates as an adaptation strategy requires further research with the use of more holistic simulation models. To summarize, DCS may provide a promising adaptation strategy to effects of climate change with a substantial stabilisation of crop yields.

Abstract: The impact of climate change on European agriculture is subject to a significant uncertainty, which reflects the intertwined nature of agriculture. This issue involves a large number of processes, ranging from field to global scales, which have not been fully integrated yet. In this study, we intend to help bridging this gap by quantifying the effect of farm-scale autonomous adaptations in response to changes in climate. To do so, we use a modelling framework coupling the STICS generic crop model to the AROPAj microeconomic model of European agricultural supply. This study provides a first estimate of the role of such adaptations, consistent at the European scale while detailed across European regions. Farm-scale autonomous adaptations significantly alter the impact of climate change over Europe, by widely alleviating negative impacts on crop yields and gross margins. They significantly increase European production levels. However, they also have an important and heterogeneous impact on irrigation water withdrawals, which exacerbate the differences in ambient atmospheric carbon dioxide concentrations among climate change scenarios. (c) 2012 Elsevier B.V. All rights reserved.