A tailored multi-model ensemble for air traffic management: Demonstration and evaluation for the Eyjafjallajökull eruption in May 2010

High quality volcanic ash forecasts are crucial to minimize the economic impact of volcanic hazards on air traffic. Decision-making is usually based on numerical dispersion modeling with only one model realization. Given the inherent uncertainty of such approach, a multi-model multi-source term ensemble has been designed and evaluated for the Eyjafjallaj&ouml;kull eruption in May 2010. Its use for air traffic management is discussed. Two multi-model ensembles were built: the first is based on the output of four dispersion models and their own implementation of ash ejection. All a priori model source terms were constrained by observational evidence of the volcanic ash cloud top as a function of time. The second ensemble is based on the same four dispersion models, which were run with three additional source terms: (i) a source term obtained with background modeling constrained with satellite data (a posteriori source term), (ii) its lower bound estimate, and (iii) its upper bound estimate. The a priori ensemble gives valuable information about the probability of ash dispersion during the early phase of the eruption, when observational evidence is limited. However, its evaluation with observational data reveals lower quality compared to the second ensemble. While the second ensemble ash column load and ash horizontal location compare well to satellite observations, 3D ash concentrations are negatively biased. This might be caused by the vertical distribution of ash, which is too much diluted in all model runs, probably due to defaults in the a posteriori source term and vertical transport and/or diffusion processes in all models. Relevant products for the air traffic management are horizontal maps of ash concentration quantiles (median, 75 %, 99 %) at a fine-resolved flight level grid. These maps can be used for route optimization in the areas where ash does not pose a direct and urgent threat to aviation. Cost-optimized consideration of such hazards will result in much less impact on flight cancellations, reroutings, and traffic flow congestions.</p

MAP4K4 associates with BIK1 to regulate plant innate immunity

King Abdullah University of Science and Technology (KAUST). Grant Numbers: BAS/1/1062‐01‐01, URF/1/2965‐01‐01 Institut National de la Recherche Agronomique (INRA). Grant Number: ANR‐10‐LABX‐0040‐SPS Centre National de la Recherche Scientifique (CNRS). Grant Number: ANR‐10‐LABX‐0040‐SPS LabEx Saclay Plant Sciences‐SPSTo perceive pathogens, plants employ pattern recognition receptor (PRR) complexes, which then transmit these signals via the receptor-like cytoplasmic kinase BIK1 to induce defense responses. How BIK1 activity and stability are controlled is still not completely understood. Here, we show that the Hippo/STE20 homolog MAP4K4 regulates BIK1-mediated immune responses. MAP4K4 associates and phosphorylates BIK1 at Ser233, Ser236, and Thr242 to ensure BIK1 stability and activity. Furthermore, MAP4K4 phosphorylates PP2C38 at Ser77 to enable flg22-induced BIK1 activation. Our results uncover that a Hippo/STE20 homolog, MAP4K4, maintains the homeostasis of the central immune component BIK1

Specifications of EDPEPPS Toolset Prototype

This report summarises the specifications and features of the EDPEPPS Toolset prototype. Specifications for the three main tools available within the toolset are given. These specifications are intended to give a guide to the user about the capabilities and restrictions of the current versions of the tools. 2 Description of the Integrated EDPEPPS Toolse

Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

Instantaneous evapotranspiration rates and surface water stress levels can be deduced from remotely sensed surface temperature data through the surface energy budget. Two families of methods can be defined: the contextual methods, where stress levels are scaled on a given image between hot/dry and cool/wet pixels for a particular vegetation cover, and single-pixel methods, which evaluate latent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a modified triangle method, named VIT) and two single-pixel (TSEB, SEBS) are applied over one growing season (December–May) for a 4 km × 4 km irrigated agricultural area in the semi-arid northern Mexico. Their performance, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as an uncalibrated soil–vegetation–atmosphere transfer (SVAT) model forced with local in situ data including observed irrigation and rainfall amounts. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly biased, show good performance. The drop in model performance is observed for all models when vegetation is senescent, mostly due to a poor partitioning both between turbulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, contextual methods perform well when contrasted soil moisture and vegetation conditions are encountered in the same image (therefore, especially in spring and early summer) while they tend to exaggerate the spread in water status in more homogeneous conditions (especially in winter). Surface energy balance models run with available remotely sensed products prove to be nearly as accurate as the uncalibrated SVAT model forced with in situ data

An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions

High-quality volcanic ash forecasts are crucial to minimize the economic impact of volcanic hazards on air traffic. Decision-making is usually based on numerical dispersion modelling with only one model realization. Given the inherent uncertainty of such an approach, a multi-model multi-source term ensemble has been designed and evaluated for the Eyjafjallajökull eruption in May 2010. Its use for flight planning is discussed. Two multi-model ensembles were built: the first is based on the output of four dispersion models and their own implementation of ash ejection