5 research outputs found
Photospheric and Subphotospheric Dynamics of Emerging Magnetic Flux
Magnetic fields emerging from the Sun's interior carry information about
physical processes of magnetic field generation and transport in the convection
zone. Soon after appearance on the solar surface the magnetic flux gets
concentrated in sunspot regions and causes numerous active phenomena on the
Sun. This paper discusses some properties of the emerging magnetic flux
observed on the solar surface and in the interior. A statistical analysis of
variations of the tilt angle of bipolar magnetic regions during the emergence
shows that the systematic tilt with respect to the equator (the Joy's law) is
most likely established below the surface. However, no evidence of the
dependence of the tilt angle on the amount of emerging magnetic flux, predicted
by the rising magnetic flux rope theories, is found. Analysis of surface plasma
flows in a large emerging active region reveals strong localized upflows and
downflows at the initial phase of emergence but finds no evidence for
large-scale flows indicating future appearance a large-scale magnetic
structure. Local helioseismology provides important tools for mapping
perturbations of the wave speed and mass flows below the surface. Initial
results from SOHO/MDI and GONG reveal strong diverging flows during the flux
emergence, and also localized converging flows around stable sunspots. The wave
speed images obtained during the process of formation of a large active region,
NOAA 10488, indicate that the magnetic flux gets concentrated in strong field
structures just below the surface. Further studies of magnetic flux emergence
require systematic helioseismic observations from the ground and space, and
realistic MHD simulations of the subsurface dynamics.Comment: 21 pages, 15 figures, to appear in Space Science Review
A decentralized approach to model national and global food and land use systems
The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities
Solar Weather Event Modelling and Prediction
Key drivers of solar weather and mid-term solar weather are reviewed by considering
a selection of relevant physics- and statistics-based scientific models as well as aselection of related prediction models, in order to provide an updated operational scenario
for space weather applications. The characteristics and outcomes of the considered scientific
and prediction models indicate that they only partially cope with the complex nature of solar
activity for the lack of a detailed knowledge of the underlying physics. This is indicated by
the fact that, on one hand, scientific models based on chaos theory and non-linear dynamics
reproduce better the observed features, and, on the other hand, that prediction models
based on statistics and artificial neural networks perform better. To date, the solar weather
prediction success at most time and spatial scales is far from being satisfactory, but the forthcoming
ground- and space-based high-resolution observations can add fundamental tiles to
the modelling and predicting frameworks as well as the application of advanced mathematical
approaches in the analysis of diachronic solar observations, that are a must to provide
comprehensive and homogeneous data sets.peerReviewe