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 % 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.</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.