Signatures of the slow solar wind streams from active regions in the inner corona

Some of local sources of the slow solar wind can be associated with spectroscopically detected plasma outflows at edges of active regions accompanied with specific signatures in the inner corona. The EUV telescopes (e.g. SPIRIT/CORONAS-F, TESIS/CORONAS-Photon and SWAP/PROBA2) sometimes observed extended ray-like structures seen at the limb above active regions in 1MK iron emission lines and described as "coronal rays". To verify the relationship between coronal rays and plasma outflows, we analyze an isolated active region (AR) adjacent to small coronal hole (CH) observed by different EUV instruments in the end of July - beginning of August 2009. On August 1 EIS revealed in the AR two compact outflows with the Doppler velocities V =10-30 km/s accompanied with fan loops diverging from their regions. At the limb the ARCH interface region produced coronal rays observed by EUVI/STEREO-A on July 31 as well as by TESIS on August 7. The rays were co-aligned with open magnetic field lines expanded to the streamer stalks. Using the DEM analysis, it was found that the fan loops diverged from the outflow regions had the dominant temperature of ~1 MK, which is similar to that of the outgoing plasma streams. Parameters of the solar wind measured by STEREO-B, ACE, WIND, STEREO-A were conformed with identification of the ARCH as a source region at the Wang-Sheeley-Arge map of derived coronal holes for CR 2086. The results of the study support the suggestion that coronal rays can represent signatures of outflows from ARs propagating in the inner corona along open field lines into the heliosphere.Comment: Accepted for publication in Solar Physics; 31 Pages; 13 Figure

Past and present distribution, densities and movements of blue whales <i>Balaenoptera musculus</i> in the Southern Hemisphere and northern Indian Ocean

1Blue whale locations in the Southern Hemisphere and northern Indian Ocean were obtained from catches (303 239), sightings (4383 records of =8058 whales), strandings (103), Discovery marks (2191) and recoveries (95), and acoustic recordings.2Sighting surveys included 7 480 450 km of effort plus 14 676 days with unmeasured effort. Groups usually consisted of solitary whales (65.2%) or pairs (24.6%); larger feeding aggregations of unassociated individuals were only rarely observed. Sighting rates (groups per 1000 km from many platform types) varied by four orders of magnitude and were lowest in the waters of Brazil, South Africa, the eastern tropical Pacific, Antarctica and South Georgia; higher in the Subantarctic and Peru; and highest around Indonesia, Sri Lanka, Chile, southern Australia and south of Madagascar.3Blue whales avoid the oligotrophic central gyres of the Indian, Pacific and Atlantic Oceans, but are more common where phytoplankton densities are high, and where there are dynamic oceanographic processes like upwelling and frontal meandering.4Compared with historical catches, the Antarctic (‘true’) subspecies is exceedingly rare and usually concentrated closer to the summer pack ice. In summer they are found throughout the Antarctic; in winter they migrate to southern Africa (although recent sightings there are rare) and to other northerly locations (based on acoustics), although some overwinter in the Antarctic.5Pygmy blue whales are found around the Indian Ocean and from southern Australia to New Zealand. At least four groupings are evident: northern Indian Ocean, from Madagascar to the Subantarctic, Indonesia to western and southern Australia, and from New Zealand northwards to the equator. Sighting rates are typically much higher than for Antarctic blue whales.6South-east Pacific blue whales have a discrete distribution and high sighting rates compared with the Antarctic. Further work is needed to clarify their subspecific status given their distinctive genetics, acoustics and length frequencies.7Antarctic blue whales numbered 1700 (95% Bayesian interval 860–2900) in 1996 (less than 1% of original levels), but are increasing at 7.3% per annum (95% Bayesian interval 1.4–11.6%). The status of other populations in the Southern Hemisphere and northern Indian Ocean is unknown because few abundance estimates are available, but higher recent sighting rates suggest that they are less depleted than Antarctic blue whales.</li

The Scientific Foundations of Forecasting Magnetospheric Space Weather

The magnetosphere is the lens through which solar space weather phenomena are focused and directed towards the Earth. In particular, the non-linear interaction of the solar wind with the Earth's magnetic field leads to the formation of highly inhomogenous electrical currents in the ionosphere which can ultimately result in damage to and problems with the operation of power distribution networks. Since electric power is the fundamental cornerstone of modern life, the interruption of power is the primary pathway by which space weather has impact on human activity and technology. Consequently, in the context of space weather, it is the ability to predict geomagnetic activity that is of key importance. This is usually stated in terms of geomagnetic storms, but we argue that in fact it is the substorm phenomenon which contains the crucial physics, and therefore prediction of substorm occurrence, severity and duration, either within the context of a longer-lasting geomagnetic storm, but potentially also as an isolated event, is of critical importance. Here we review the physics of the magnetosphere in the frame of space weather forecasting, focusing on recent results, current understanding, and an assessment of probable future developments.Peer reviewe

Basic Methods for Computing Special Functions

This paper gives an overview of methods for the numerical evaluation of special functions, that is, the functions that arise in many problems from mathematical physics, engineering, probability theory, and other applied sciences. We consider in detail a selection of basic methods which are frequently used in the numerical evaluation of special functions: converging and asymptotic series, including Chebyshev expansions, linear recurrence relations, and numerical quadrature. Several other methods are available and some of these will be discussed in less detail. We give examples of recent software for special functions where these methods are used. We mention a list of new publications on computational aspects of special functions available on our website