The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Overview and Performance

The Helioseismic and Magnetic Imager (HMI) began near-continuous full-disk solar measurements on 1 May 2010 from the Solar Dynamics Observatory (SDO). An automated processing pipeline keeps pace with observations to produce observable quantities, including the photospheric vector magnetic field, from sequences of filtergrams. The basic vector-field frame list cadence is 135 seconds, but to reduce noise the filtergrams are combined to derive data products every 720 seconds. The primary 720 s observables were released in mid-2010, including Stokes polarization parameters measured at six wavelengths, as well as intensity, Doppler velocity, and the line-of-sight magnetic field. More advanced products, including the full vector magnetic field, are now available. Automatically identified HMI Active Region Patches (HARPs) track the location and shape of magnetic regions throughout their lifetime. The vector field is computed using the Very Fast Inversion of the Stokes Vector (VFISV) code optimized for the HMI pipeline; the remaining 180^° azimuth ambiguity is resolved with the Minimum Energy (ME0) code. The Milne–Eddington inversion is performed on all full-disk HMI observations. The disambiguation, until recently run only on HARP regions, is now implemented for the full disk. Vector and scalar quantities in the patches are used to derive active region indices potentially useful for forecasting; the data maps and indices are collected in the SHARP data series, hmi.sharp_720s. Definitive SHARP processing is completed only after the region rotates off the visible disk; quick-look products are produced in near real time. Patches are provided in both CCD and heliographic coordinates. HMI provides continuous coverage of the vector field, but has modest spatial, spectral, and temporal resolution. Coupled with limitations of the analysis and interpretation techniques, effects of the orbital velocity, and instrument performance, the resulting measurements have a certain dynamic range and sensitivity and are subject to systematic errors and uncertainties that are characterized in this report.     

X-ray, Lyα and Hα emission from simulated disk galaxies

The X-ray properties of the haloes of disk galaxies formed in fully cosmological, hydro/gravity simulations are discussed. The results are found to be consistent with observational X-ray detections and upper limits. Disk galaxy haloes are predicted to be about an order of magnitude brighter at z ∼ 1 than at z=0. The Lyα and Hα surface brightness of an edge-on, Milky Way like model galaxy has been determined. The emission is found to be quite extended, with a scale height of about 600 pc, neglecting dust corrections. This revised version was published online in August 2006 with corrections to the Cover Date.     

Transport of suspended matter in a bar-built Danish estuary

The river Varde Å discharges into the bay of Ho Bugt on the western coast of Jutland forming a small, bar-built estuary. This paper deals with tidal fluxes of water and sediment in the Varde Å estuary.The inflowing water at flood tide is part of a turbidity maximum in the northern part of the bay. At high tide slack water the suspended material deposits inside the estuary. During ebb-tide it is resuspended, and the estuary bottom is washed clean coinciding with the influx of relatively pure freshwater from the drainage area.From one station in the estuary mouth, current velocities and concentrations of suspended material have been measured during 10 tidal periods covering all four seasons. It is shown how these data can be used in a quantitative calculation of the transport of water and suspended material through the cross-section of study.A model has been formulated which—based on half-tidal periods—quantifies the transport of water and suspended material through the estuary mouth.The model is calibrated on the basis of measurements made during the above-mentioned 10 tidal periods. The rather small number of measurements is to some extent compensated for by a carefully pre-arranged selection of tidal periods.The model is discussed in relation to the prediction of net suspended transport through the estuary mouth in different weather and tidal situations.     

Objectives of fisheries management: case studies from the UK, France, Spain and Denmark

The main objectives of fisheries management are generally similar throughout the world. These are often stated in policy documents such as the Common Fisheries Policy and the Magnuson–Stevens Fishery Conservation and Management Act. However, at the local level often the key objectives of management are more detailed, characterised by both the overriding management structure and the status and type of fishery concerned. In this paper, we consider case study fisheries from the UK, France, Spain and Denmark to compare some of the various types of fisheries and fisheries management systems that exist in the European Union. From this, we define the key objectives for each management system.     

Line-of-Sight Observables Algorithms for the <Emphasis Type="Italic">Helioseismic and Magnetic Imager</Emphasis> (HMI) Instrument Tested with <Emphasis Type="Italic">Interferometric Bidimensional Spectrometer</Emphasis> (IBIS) Observations

The Helioseismic and Magnetic Imager (HMI) instrument onboard the Solar Dynamics Observatory produces line-of-sight (LOS) observables (Doppler velocity, magnetic-field strength, Fe i line width, line depth, and continuum intensity) as well as vector magnetic-field maps at the solar surface. The accuracy of LOS observables is dependent on the algorithm used to translate a sequence of HMI filtergrams into the corresponding observables. Using one hour of high-cadence imaging spectropolarimetric observations of a sunspot in the Fe i line at 6173 Å through the Interferometric Bidimensional Spectrometer installed at the Dunn Solar Telescope, and the Milne–Eddington inversion of the corresponding Stokes vectors, we test the accuracy of the observables algorithm currently implemented in the HMI data-analysis pipeline: the MDI-like algorithm. In an attempt to improve the accuracy of HMI observables, we also compare this algorithm to others that may be implemented in the future: a least-squares fit with a Gaussian profile, a least-squares fit with a Voigt profile, and the use of second Fourier coefficients in the MDI-like algorithm.     

Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.