MARS Bulletin Vol.22 No 1 (2014)

Crop Monitoring in EuropeJRC.H.4-Monitoring Agricultural Resource

MARS Bulletin Vol. 23 No 1 (2015) - Weakly hardened winter cereals in Europe

Crop monitoring in EuropeJRC.H.4-Monitoring Agricultural Resource

MARS Bulletin Vol. 23 No 2 (2015) - Winter cereals remain weakly hardened

Crop monitoring in EuropeJRC.H.4-Monitoring Agricultural Resource

MARS Bulletin Vol.22 No 2 (2014) - Exceptional mild winter and very wet in western Europe

Crop Monitoring in EuropeJRC.H.4-Monitoring Agricultural Resource

Early heat waves over Italy and their impacts on durum wheat yields

In the last decades the Euro-Mediterranean region has experienced an increase in extreme temperature events such as heat waves. These extreme weather conditions can strongly affect arable crop growth and final yields. Here, early heat waves over Italy from 1995 to 2013 are identified and characterised and their impact on durum wheat yields is investigated. As expected, results confirm the impact of the 2003 heat wave and highlight a high percentage of concurrence of early heat waves and significant negative yield anomalies in 13 out of 39 durum wheat production areas. In south-eastern Italy (the most important area for durum wheat production), the percentage of concurrent events exceeds 80%.JRC.H.4-Monitoring Agricultural Resource

Climate resilience of the top ten wheat producers in the Mediterranean and the Middle East

Wheat is the main staple crop and an important commodity in the Mediterranean and the Middle East. These are among the few areas in the world where the climate is suitable for growing durum wheat but also are among the most rapidly warming ones, according to the available scenarios of climate projections. How much food security and market stability in the Mediterranean and the Middle East, both depending on wheat production and its interannual variability, are going to be compromised by global warming is an overarching question. To contribute in addressing it, we use a recently established indicator to quantify crop production climate resilience. We present a methodological framework allowing to compute the annual production resilience indicator from nonstationary time series. We apply this approach on the wheat production of the 10 most important producers in the Mediterranean and the Middle East. Our findings shows that if no adaptation will take place, wheat production reliability in the Mediterranean and the Middle East will be threatened by climate change already at 1.5 °C global warming. Average climaterelated wheat production losses will exceed the worst past event even if the 2 °C mitigation target is met. These results call for urgent action on adaptation to climate change and support further efforts for mitigation, fully consistently with the Paris Agreement recommendations.Fil: Zampieri, Matteo. Joint Research Centre; ItaliaFil: Toreti, Andrea. Joint Research Centre; ItaliaFil: Ceglar, Andrej. Joint Research Centre; ItaliaFil: Naumann, Gustavo. Joint Research Centre; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Turco, Marco. Universidad de Murcia; EspañaFil: Tebaldi, Claudia. Joint Global Change Research Institute; Itali

Summer drought predictability over Europe: empirical versus dynamical forecasts

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.We acknowledge the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, for making the data available on their website http://www.esrl.noaa.gov/psd/. This work was partially funded by the Projects IMPREX (EU–H2020 PE024400) and SPECS (FP7-ENV-2012-308378). Marco Turco was supported by the Spanish Juan de la Cierva Programme (IJCI-2015-26953).Peer ReviewedPostprint (published version

Climate service driven adaptation may alleviate the impacts of climate change in agriculture

Building a resilient and sustainable agricultural sector requires the development and implementation of tailored climate change adaptation strategies. By focusing on durum wheat (Triticum turgidum subsp. durum) in the Euro-Mediterranean region, we estimate the benefits of adapting through seasonal cultivar-selection supported by an idealised agro-climate service based on seasonal climate forecasts. The cost of inaction in terms of mean yield losses, in 2021–2040, ranges from −7.8% to −5.8% associated with a 7% to 12% increase in interannual variability. Supporting cultivar choices at local scale may alleviate these impacts and even turn them into gains, from 0.4% to 5.3%, as soon as the performance of the agro-climate service increases. However, adaptation advantages on mean yield may come with doubling the estimated increase in the interannual yield variability.info:eu-repo/semantics/publishedVersio

Analysing the resilience of agricultural production systems with ResiPy, the Python production resilience estimation package

Abstract We present ResiPy, a Python object-oriented software to compute the annual production resilience indicator. This indicator can be applied to different anthropic and natural systems, e.g., agricultural production, natural vegetation and water resources, to quantify their stabilities and the risk of adverse events. We propose an illustrative application of ResiPy to agricultural production in Europe, expressed in economic terms. After estimating the single-country or single-crop resilience, we evaluate the overall resilience of diversified production systems, composed of different crops and different cultivation areas. ResiPy also includes a powerful graphical tool to visually estimate the impact of diversity on complex production systems. The robustness of the indicator and the simplicity of the code ensure its effective applicability in many fields and with different datasets