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Author Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E.
Title Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century Type Journal Article
Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change
Volume 134 Issue (down) 1-2 Pages 283-297
Keywords regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes
Abstract Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0165-0009 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4805
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Author Mirschel, W.; Barkusky, D.; Hufnagel, J.; Kersebaum, K.C.; Nendel, C.; Laacke, L.; Luzi, K.; Rosner, G.
Title Coherent multi-variable field data set of an intensive cropping system for agro-ecosystem modelling from Müncheberg, Germany Type Journal Article
Year 2016 Publication Open Data Journal for Agricultural Research Abbreviated Journal Open Data J. Agric. Res.
Volume 2 Issue (down) 1 Pages 1-10
Keywords
Abstract A six-year (1993-1998) multivariable data set for a four-plot intensive crop rotation (sugar beet – winter wheat – winter barley – winter rye – catch crop) located at Leibniz Centre for Agricultural Landscape Research (ZALF) Experimental Station, Müncheberg, Germany, is documented in detail. The experiment targets crop response to water supply on sandy soils (Eutric Cambisol), applying rain-fed and irrigated treatments. Weather as well as soil and crop processes were intensively monitored and management actions were consistently recorded. The data set contains coherent data for soil (water, nitrogen contents), crop (ontogenesis, plant, tiller and ear numbers, above-ground and root biomasses, yield, carbon and nitrogen content in biomass and their fractions, sugar content in beet), weather (all standard meteorological variables) and management (soil tillage, sowing, fertilisation, irrigation, harvest). In addition, observation methods are briefly described. The data set is available via the Open Research Data Portal at ZALF Müncheberg and is published under doi:10.4228/ZALF.1992.271. The data set was used for model intercomparison within the crop modelling part (CropM) of the international FACCE MACSUR project.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2352-6378 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4762
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Author Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P.
Title Statistical modelling of agrometeorological time series by exponential smoothing Type Journal Article
Year 2016 Publication International Agrophysics Abbreviated Journal International Agrophysics
Volume 30 Issue (down) 1 Pages 57-65
Keywords exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather
Abstract Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0236-8722 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4728
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Author Yin, X.G.; Olesen, J.E.; Wang, M.; Öztürk, I.; Chen, F.
Title Climate effects on crop yields in the Northeast Farming Region of China during 1961–2010 Type Journal Article
Year 2016 Publication Journal of Agricultural Science Abbreviated Journal J. Agric. Sci.
Volume 154 Issue (down) 07 Pages 1190-1208
Keywords
Abstract Crop production in the Northeast Farming Region of China (NFR) is affected considerably by variation in climatic conditions. Data on crop yield and weather conditions from a number of agro-meteorological stations in NFR were used in a mixed linear model to evaluate the impacts of climatic variables on the yield of maize (Zea mays L.), rice (Oryza sativa L.), soybean (Glycine max L. Merr.) and spring wheat (Triticum aestivum L.) in different crop growth phases. The crop growing season was divided into three growth phases based on the average crop phenological dates from records covering 1981 and 2010 at each station, comprising pre-flowering (from sowing to just prior to flowering), flowering (20 days around flowering) and post-flowering (10 days after flowering to maturity). The climatic variables were mean minimum temperature, thermal time (which is used to indicate changes in the length of growth cycles), average daily solar radiation, accumulated precipitation, aridity index (which is used to assess drought stress) and heat degree-days index (HDD) (which is used to indicate heat stress) were calculated for each growth phase and year. Over the 1961–2010 period, the minimum temperature increased significantly in each crop growth phase, the thermal time increased significantly in the pre-flowering phase of each crop and in the post-flowering phases of maize, rice and soybean, and HDD increased significantly in the pre-flowering phase of soybean and wheat. Average solar radiation decreased significantly in the pre-flowering phase of all four crops and in the flowering phase of soybean and wheat. Precipitation increased during the pre-flowering phase leading to less aridity, whereas reduced precipitation in the flowering and post-flowering phases enhanced aridity. Statistical analyses indicated that higher minimum temperature was beneficial for maize, rice and soybean yields, whereas increased temperature reduced wheat yield. Higher solar radiation in the pre-flowering phase was beneficial for maize yield, in the post-flowering phase for wheat yield, whereas higher solar radiation in the flowering phase reduced rice yield. Increased aridity in the pre-flowering and flowering phases severely reduced maize yield, higher aridity in the flowering and post-flowering phases reduced rice yield, and aridity in all growth phases reduced soybean and wheat yields. Higher HDD in all growth phases reduced maize and soybean yield and HDD in the pre-flowering phase reduced rice yield. Such effects suggest that projected future climate change may have marked effects on crop yield through effects of several climatic variables, calling for adaptation measures such as breeding and changes in crop, soil and agricultural water management.
Address 2016-09-30
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0021-8596 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4782
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Author Ebrahimi, E.; Manschadi, A.M.; Neugschwandtner, R.W.; Eitzinger, J.; Thaler, S.; Kaul, H.-P.
Title Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria Type Journal Article
Year 2016 Publication Journal of Agricultural Science Abbreviated Journal J. Agric. Sci.
Volume 154 Issue (down) 07 Pages 1153-1170
Keywords
Abstract Climate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0021-8596 ISBN Medium Article
Area Expedition Conference
Notes TradeM Approved no
Call Number MA @ admin @ Serial 4723
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