Semi operational real-data large eddy simulations for agricultural applications

<p><span>One of societies greatest challenges is to provide food and energy for an increasing global population while minimizing agricultural production's environmental footprint. </span><span>To alleviate pollution and halt the reduction in biodiversity, a more productive arable land is needed, and agro-chemical inputs must be reduced. </span><span>A crucial aspect is precise agricultural management and planning, in which soil-vegetation-</span><span>atmosphere</span><span> (SVA) modeling is a major tool to provide forecasts and bridge the gap between </span><span>in-situ</span><span> measurements at the point scale and information required at the field scale to fully exploit the potential of spatiotemporal information.</span></p><p><span>We are using the scale-consistent Terrestrial System Modeling Platform (TSMP), which is composed of an atmospheric model </span><span>(Icosahedral Nonhydrostatic</span><strong><span> - </span></strong><span>ICON or Consortium for Small-scale Modeling - COSMO)</span><span>, a land surface model (NCAR Community Land Model - CLM), and a subsurface flow model (ParFlow) coupled via the OASIS3-MCT library. In this contribution, we show a real-data, semi-operational, field-scale large eddy simulation (LES) application from the atmosphere to the subsurface</span><span>. </span><span>W</span><span>e outline the setup of the agricultural domain located in the western part of Germany and introduce the nested model chain from pan-European scale over region and local scale to the target resolution at field-scale of </span><span>&#8710;x=10m. Demonstrating the added value of </span><span><em>O</em></span><span>(10</span>^{<span>1</span>}<span>m) simulations, we provide a basis for improved insights into scale-dependent processes based on real-data LES, </span><span>which may lead to improved operational forecasting capabilities in the future.</span></p>