The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

Microbial Diversity of Psychrotolerant Bacteria Isolated from Wild Flora of Andes Mountains and Patagonia of Chile towards the Selection of Plant Growth-Promoting Bacterial Consortia to Alleviate Cold Stress in Plants

Cold stress decreases the growth and productivity of agricultural crops. Psychrotolerant plant growth-promoting bacteria (PGPB) may protect and promote plant growth at low temperatures. The aims of this study were to isolate and characterize psychrotolerant PGPB from wild flora of Andes Mountains and Patagonia of Chile and to formulate PGPB consortia. Psychrotolerant strains were isolated from 11 wild plants (rhizosphere and phyllosphere) during winter of 2015. For the first time, bacteria associated with Calycera, Orites, and Chusquea plant genera were reported. More than 50% of the 130 isolates showed ≥33% bacterial cell survival at temperatures below zero. Seventy strains of Pseudomonas, Curtobacterium, Janthinobacterium, Stenotrophomonas, Serratia, Brevundimonas, Xanthomonas, Frondihabitans, Arthrobacter, Pseudarthrobacter, Paenarthrobacter, Brachybacterium, Clavibacter, Sporosarcina, Bacillus, Solibacillus, Flavobacterium, and Pedobacter genera were identified by 16S rRNA gene sequence analyses. Ten strains were selected based on psychrotolerance, auxin production, phosphate solubilization, presence of nifH (nitrogenase reductase) and acdS (1-aminocyclopropane-1-carboxylate (ACC) deaminase) genes, and anti-phytopathogenic activities. Two of the three bacterial consortia formulated promoted tomato plant growth under normal and cold stress conditions. The bacterial consortium composed of Pseudomonas sp. TmR5a & Curtobacterium sp. BmP22c that possesses ACC deaminase and ice recrystallization inhibition activities is a promising candidate for future cold stress studies