Abstract. The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust.For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.
Verticillium longisporum is a vascular fungal pathogen leading to severe crop loss, particular in oilseed rape. Transcription factors (TF) are highly suited for genetic engineering of pathogen-resistant crops, as they control sets of functionally associated genes. Applying the AtTORF-Ex (Arabidopsis thaliana transcription factor open reading frame expression) collection, a simple and robust screen of TF-overexpressing plants was established displaying reduced fungal colonization. Distinct members of the large ethylene response factor (ERF) family, namely ERF96 and the six highly related subgroup IXb members ERF102 to ERF107, were identified. Whereas overexpression of these ERF significantly reduces fungal propagation, single loss-of-function approaches did not reveal altered susceptibility. Hence, this gain-of-function approach is particularly suited to identify redundant family members. Expression analyses disclosed distinct ERF gene activation patterns in roots and leaves, suggesting functional differences. Transcriptome studies performed on chemically induced ERF106 expression revealed an enrichment of genes involved in the biosynthesis of antimicrobial indole glucosinolates (IG), such as CYP81F2 (CYTOCHROME P450-MONOOXYGENASE 81F2), which is directly regulated by IXb-ERF via two GCC-like cis-elements. The impact of IG in restricting fungal propagation was further supported as the cyp81f2 mutant displayed significantly enhanced susceptibility. Taken together, this proof-of-concept approach provides a novel strategy to identify candidate TF that are valuable genetic resources for engineering or breeding pathogen-resistant crop plants.
Mineral dust is a key player in the Earth system that affects the weather and climate through absorbing and scattering the radiation. Such effects strongly depend on the optical properties of the particles that are in turn affected by the particle shape. For simplicity, dust particles are usually assumed to be spherical. But this assumption can lead to large errors in modeling and remote sensing applications. This study investigates the impact of dust particle shape on its direct radiative effect in a next‐generation atmospheric modeling system ICON‐ART (ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases) to verify if accounting for nonsphericity enhances the model‐observation agreement. Two sets of numerical experiments are conducted by changing the optical shape of the particles: one assuming spherical particles and the other one assuming a mixture of 35 randomly oriented triaxial ellipsoids. The simulations are compared to MISR (Multiangle Imaging Spectroradiometer), AERONET (Aerosol Robotic Network), and CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations (with focus on North Africa). The results show that consideration of particle nonsphericity increases the dust AOD (Aerosol Optical Depth) at 550 nm by up to 28% and leads to slight enhancement of the agreement between modeled and measured AOD. However, the model performance varies significantly when focusing on specific regions in North Africa. These differences stem from the uncertainties associated with particle size distribution and emission mechanisms in the model configuration. Regarding the attenuated backscatter, the simulated profile assuming nonsphericity differs by a factor of 2 to 5 from the experiment assuming spherical dust and is in a better agreement with the CALIPSO observations.
<p><strong>Abstract.</strong> The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV power generation during a Saharan dust outbreak over Germany at 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV power forecast for 65&#8201;% of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64&#8201;%, indirect effects for 20&#8201;% and synergistic interaction effects for 16&#8201;% of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.</p>
Abstract. Dusty cirrus clouds are extended optically thick cirrocumulus decks that occur during strong mineral dust events. So far they have been mostly documented over Europe associated with dust-infused baroclinic storms. Since today's numerical weather prediction models neither predict mineral dust distributions nor consider the interaction of dust with cloud microphysics, they cannot simulate this phenomenon. We postulate that the dusty cirrus forms through a mixing instability of moist clean air with drier dusty air. A corresponding sub-grid parameterization is suggested and tested in the ICON-ART model. Only with help of this parameterization ICON-ART is able to simulate the formation of the dusty cirrus, which leads to substantial improvements in cloud cover and radiative fluxes compared to simulations without this parameterization. A statistical evaluation over six Saharan dust events with and without observed dusty cirrus shows robust improvements in cloud and radiation scores. The ability to simulate dusty cirrus formation removes the linear dependency on mineral dust aerosol optical depth from the bias of the radiative fluxes. This suggests that the formation of dusty cirrus clouds is the dominant aerosol-cloud-radiation effect of mineral dust over Europe.
Abstract. Dusty cirrus clouds are extended optically thick cirrocumulus decks that occur during strong mineral dust events. So far they have mostly been documented over Europe associated with dust-infused baroclinic storms. Since today's global numerical weather prediction models neither predict mineral dust distributions nor consider the interaction of dust with cloud microphysics, they cannot simulate this phenomenon. We postulate that the dusty cirrus forms through a mixing instability of moist clean air with drier dusty air. A corresponding sub-grid parameterization is suggested and tested in the ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases (ICON-ART). Only with the help of this parameterization is ICON-ART able to simulate the formation of the dusty cirrus, which leads to substantial improvements in cloud cover and radiative fluxes compared to simulations without this parameterization. A statistical evaluation over six Saharan dust events with and without observed dusty cirrus shows robust improvements in cloud and radiation scores. The ability to simulate dusty cirrus formation removes the linear dependency on mineral dust aerosol optical depth from the bias of the radiative fluxes. For the six Saharan dust episodes investigated in this study, the formation of dusty cirrus clouds is the dominant aerosol–cloud–radiation effect of mineral dust over Europe.
Información sobre los autores:LAG-P: realizó el analisis, la identificaciones y escribio el manuscrito; LAG-P, MVB, JQ, SQ, DT, JM: realizaron las colectas de campo, revisaron y aprobaron el manuscrito.Los autores no incurren en conflictos de intereses. Presentado:16/01/2017 Aceptado:13/06/2017 Publicado online: 20/07/2017 ResumenSe registra por primera vez para Perú a Cricocephalus albus (Digenea: Pronocephalidae) en la tortuga verde del Pacífico oriental (Chelonia mydas agassizii). Los parásitos fueron colectados durante la necropsia de una tortuga verde varada en el estuario de Virrilá localizado en la provincia de Sechura, Departamento de Piura, Perú. El presente trabajo realiza una breve descripción de C. albus, así como la discusión de sus hospederos y distribución geográfica.Palabras clave: Trematoda; Plagiorchiida; Cricocephalus albus; quelonio; Chelonia mydas agassizii; Virrilá. AbstractCricocephalus albus (Digenea: Pronocephalidae) is registered for first time in Peru in the East Pacific green turtle (Chelonia mydas agassizii). The parasites were collected during a necropsy carried out in a stranded sea turtle in the Virrilá estuary, located in the Sechura province of Piura, Peru. The specimens were studied morphologically and identified as C. albus. The current work describes C. albus, as well as the discussion of its hosts and geographic distribution.
Abstract. The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in south-west Germany (8.4298° E, 49.0953° N) from April 7 to 9, 2018 combining a scanning LIDAR (90°, 30°), a vertical LIDAR (90°), a sun photometer, and the transport model ICON-ART. The LIDAR measurements show that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm−1 Sr−1, an extinction coefficient of 40 ± 0.8 Mm−1, a LIDAR ratio of 46 ± 5 sr, and a particle depolarization ratio of 0.33 ± 0.07. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the model simulation predicts the plume arrival time, its layer height, and structure very well but overestimates the backscatter coefficient. In this manuscript, we discuss the complementarity and advantages of the different measurement methods as well model simulations to predict Saharan dust plumes. Main conclusions are that the ICON-ART model can predict the structure of Saharan dust plumes very well but overestimates the backscatter coefficients by a factor of 2.2 ± 0.16 at 355 nm and underestimates the aerosol optical depth (AOD) by a factor of 1.5 ± 0.11 at 340 nm for this Saharan dust plume event. Employing a scanning aerosol LIDAR allows determining backscatter coefficient, particle depolarization ratio and especially LIDAR ratio of Saharan dust both for daytime and nighttime independently. Combining LIDAR with sun photometer data allows constraining aerosol optical depth in different ways and determining column integrated LIDAR ratios. These comprehensive datasets allow for a better understanding of Saharan dust plumes in Western Europe.
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