<mods:mods version="3.3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mods:titleInfo><mods:title>Spatial Analysis of Weather-induced Annual and&#13;
Decadal Average Yield Variability as Modeled by EPIC&#13;
for Rain-fed Wheat in Europe</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">N.</mods:namePart><mods:namePart type="family">Khabarov</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">J.</mods:namePart><mods:namePart type="family">Balkovic</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">E.</mods:namePart><mods:namePart type="family">Schmid</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">A.</mods:namePart><mods:namePart type="family">Schwartz</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">L.</mods:namePart><mods:namePart type="family">Azevedo</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">M.</mods:namePart><mods:namePart type="family">Obersteiner</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>In our analysis we evaluate the accuracy of near-term (decadal) average crop yield assessments as supported by the biophysical crop growth model EPIC. A spatial assessment of averages and variability has clear practical implications for agricultural producers and investors concerned with an estimation of the basic stochastic characteristics of a crop yield distribution. &#13;
As a reliable weather projection for a time period of several years will apparently remain a challenge in the near future, we have employed the existing gridded datasets on historical weather as a best proxy for the current climate. Based on different weather inputs to EPIC, we analyzed the model runs (as implemented by IIASA and BOKU) for the rain-fed wheat for 1968-2007 employing AgGRID/GGCMIii) simulations that use harmonized inputs and assumptions (weather datasets: GRASP and Princeton).</mods:abstract><mods:originInfo><mods:dateIssued encoding="iso8601">2017-02-27</mods:dateIssued></mods:originInfo><mods:genre>Conference or Workshop Item</mods:genre></mods:mods>