scholarly journals Spatio-temporal variability of the photospheric magnetic field

2010 ◽  
Vol 6 (S274) ◽  
pp. 204-206
Author(s):  
A. Vecchio ◽  
M. Laurenza ◽  
D. Meduri ◽  
V. Carbone ◽  
M. Storini
Keyword(s):  
Magnetic Field ◽  
Time Evolution ◽  
Empirical Mode Decomposition ◽  
Temporal Variability ◽  
Solar Magnetic Field ◽  
Temporal Dynamics ◽  
Heliographic Latitude ◽  
Preliminary Results ◽  
Mode Decomposition ◽  
Spatio Temporal

AbstractThe spatio-temporal dynamics of the solar magnetic field has been investigated by using NSO/Kitt Peak synoptic magnetic maps covering ~28 yr. For each heliographic latitude the field has been analyzed through the Empirical Mode Decomposition, in order to investigate the time evolution of the various characteristic oscillating frequencies. Preliminary results are discussed.

scholarly journals Time Evolution of the Large-Scale Solar Magnetic Field

1971 ◽  
Vol 43 ◽  
pp. 588-594 ◽  
Author(s):  
Martin D. Altschuler ◽  
Gordon Newkirk ◽  
Dorothy E. Trotter ◽  
Robert Howard
Keyword(s):  
Magnetic Field ◽  
Time Evolution ◽  
Large Scale ◽  
Solar Magnetic Field ◽  
Magnetic Polarity ◽  
Zonal Harmonic ◽  
The North

The six years of data from the Mt. Wilson Magnetic Atlas were analyzed in terms of surface harmonics. Between 1959 and 1962 the dominant harmonic corresponded to a dipole lying in the plane of the equator (2 sectors). There was also a significant zonal harmonic in which both solar poles had the same magnetic polarity, opposite to that at the equator. From the end of 1962 through 1964, the harmonic corresponding to 4 sectors was dominant. In 1965 and 1966, the harmonic of the north-south dipole became significant.

Diagnosing chromospheric magnetic field through simultaneous spectropolarimetry in Hα and Ca II 854.2 nm

2019 ◽  
Vol 15 (S354) ◽  
pp. 46-52
Author(s):  
K. Nagaraju ◽  
K. Sankarasubramanian ◽  
K. E. Rangarajan
Keyword(s):  
Magnetic Field ◽  
Time Evolution ◽  
Opposite Polarity ◽  
Point Of View ◽  
Current Understanding ◽  
Small Scale ◽  
Preliminary Results

AbstractMeasurement of magnetic field in this layer is challenging both from point of view of observations and interpretation of the data. We present in this work about spectropolarimetric observations of a pore, simultaneously in Ca ii (CaIR) at 854.2 nm (CaIR) and H α (656.28 nm). The observed region includes a small scale energetic event (SSEE) taking place in the region between the pore and the region which show opposite polarity to that of pore at the photosphere. The energetic event appears to be a progressive reconnection event as shown by the time evolution of the intensity profiles. Closer examination of the intensity profiles from the downflow regions suggest that the height of formation of CaIR is higher than that of Hi α, contrary to the current understanding about their height of formation. Preliminary results on the inversion of Stokes-I and V profiles of CaIR are also presented.

scholarly journals The dynamics of 3-min wavefronts and their relation to sunspot magnetic fields

2020 ◽  
Vol 379 (2190) ◽  
pp. 20200180 ◽  
Author(s):  
Robert Sych ◽  
David B. Jess ◽  
Jiangtao Su
Keyword(s):  
Magnetic Field ◽  
Temporal Dynamics ◽  
Oscillation Period ◽  
Motion Path ◽  
Solar Dynamics Observatory ◽  
Digital Technique ◽  
Wave Dynamics ◽  
Mode Decomposition ◽  
Inclination Angles ◽  
Field Inclination

We present a study of wave processes occurring in solar active region NOAA 11131 on 10 December 2010, captured by the Solar Dynamics Observatory in the 1600 Å, 304 Å and 171 Å channels. For spectral analysis, we employed pixelized wavelet filtering together with a developed digital technique based on empirical mode decomposition. We studied the ∼3-minute wave dynamics to obtain relationships with the magnetic structuring of the underlying sunspot. We found that during development of wave trains the motion path occurred along a preferential direction, and that the broadband wavefronts can be represented as a set of separate narrowband oscillation sources. These sources become visible as the waves pass through the umbral inhomogeneities caused by the differing magnetic field inclination angles. We found the spatial and frequency fragmentation of wavefronts, and deduced that the combination of narrowband spherical and linear parts of the wavefronts provide the observed spirality. Maps of the magnetic field inclination angles confirm this assumption. We detect the activation of umbral structures as the increasing of oscillations in the sources along the front ridge. Their temporal dynamics are associated with the occurrence of umbral flashes. Spatial localization of the sources is stable over time and depends on the oscillation period. We propose that these sources are the result of wave paths along the loops extending outwards from the magnetic bundles of the umbra. This article is part of the Theo Murphy meeting issue ‘High-resolution wave dynamics in the lower solar atmosphere’.

Investigating spatio-temporal variability of soil moisture in a small farmland: from point to catchment scale

2020 ◽  
Author(s):  
Tailin Li ◽  
Nina Noreika ◽  
Jakub Jeřábek ◽  
Josef Krasa ◽  
David Zumr ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Temporal Dynamics ◽  
Anthropogenic Impacts ◽  
Temporal Patterns ◽  
Point Scale ◽  
Catchment Scale ◽  
Climate Conditions ◽  
Spatio Temporal ◽  
Hillslope Scale

<p>Many studies in recent years have focused on spatio-temporal variability of soil moisture and its value in hydrology and agriculture. The highly dynamic of soil moisture is controlled by soil properties, topography, landuse, climate conditions, and anthropogenic impacts. However, the understanding of soil moisture dynamics is limited by measurement restrictions. The aim of this study is to analyse spatio-temporal patterns of soil moisture using various soil moisture monitoring techniques and numerical modelling approaches that have been developed for application at differing scales at the Nucice experimental catchment (0.53 km<sup>2</sup>), which is located just outside of Prague, the Czech Republic.</p><p>The experimental catchment is dominated by agricultural activities. To identify spatio-temporal patterns in the catchment, we have implemented shallow soil moisture measurements at point-scale, hillslope-scale, and catchment-scale. We have deployed FDR (frequency domain reflectometry) sensors at different depths for point-scale measurements. The monitoring of hillslope-scale and catchment-scale have been mostly accomplished by field surveys with HydroSense II sensors. Subsequently, we have applied geostatistical analyses (Kriging and inverse distance weighting interpolation) for the measured soil moisture data to discover spatial patterns in soil moisture across the catchment. Besides, numerical models Hydrus (1D and 2D), MIKE-SHE, and SWAT have been set up at this study site. These models have been calibrated with event-based data and soil moisture measurements, which present a better image of the hydrological processes and spatio-temporal dynamics of soil moisture at various scales. The modelling outcomes have not only fit agreeably with the observed discharge and the temporal dynamics of soil moisture but have also identified wet zones along hillslopes.</p><p>Further research will intensify the soil moisture monitoring at the catchment-scale by using remote sensing and Comsic-ray soil moisture probes. Also, anthropogenic impacts (e.g. influence of wheel track) should be considered in the modelling approach. Ultimately, we should be able to understand and predict the spatio-temporal dynamics of soil moisture in small scale agricultural catchments under different climate conditions.</p><p>This research has been supported by project H2020 No. 773903 SHui, focused on water scarcity in European and Chinese cropping systems.</p>

scholarly journals Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets

2016 ◽  
Vol 374 (2065) ◽  
pp. 20150197 ◽  
Author(s):  
Zhaohua Wu ◽  
Jiaxin Feng ◽  
Fangli Qiao ◽  
Zhe-Min Tan
Keyword(s):  
Time Series ◽  
Empirical Mode Decomposition ◽  
High Efficiency ◽  
Function Analysis ◽  
Ensemble Empirical Mode Decomposition ◽  
Local Analysis ◽  
Mode Decomposition ◽  
Speed Up ◽  
Non Local ◽  
Spatio Temporal

In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal–spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders.

Time Evolution of the Large-Scale Solar Magnetic Field

1971 ◽  
pp. 588-594 ◽  
Author(s):  
Martin D. Altschuler ◽  
Gordon Newkirk ◽  
Dorothy E. Trotter ◽  
Robert Howard
Keyword(s):  
Magnetic Field ◽  
Time Evolution ◽  
Large Scale ◽  
Solar Magnetic Field
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