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5 results for “Solar Physics”
EUV-ML solar physics dataset from STEREO + SOHO, 2 solar cycles
<p>A unified ML-ready dataset of all SOHO EIT and STEREO EUVI EUV images, aligned and set to 512x512 pixels, are available via the NASA TOPS ODR in HelioCloud at s3://gov-nasa-hdrl-data1/contrib/euvml/ (inside of AWS, and with free egress via https). We also provide the software used to create it via a public github repository, and a sample Python Jupyter Notebook (in this Zenodo link, and in the HelioCloud sample tutorials) for accessing them via the 'cloudcatalog' Python client.We</p> <p>We created a full set of ML-ready EUV data from 1995 to present, accessible via the cloud, by bringing in historical restoration of the STEREO/SOHO era into a machine-learning (ML) -ready dataset. This work will enable research on events, evolution of solar irradiance, segmentation approaches, 360 degree maps of the sun, and other research topics as well as for use with space weather. The reduced dataset is 6TB in size. The data will be freely available to scientists both within the AWS cloud and for downloading for local use on their laptops. The creation of this dataset had several steps, starting with the mechnical ingest stage (get the raw data), an analysis of best approach to create the ML-ready set, bulk processing, uploading the cloud, and dissemination and promotion. The task also required determination best approaches for cadence matching, interpolation, and effective spans of contiguous data for ML applications.</p> <p>Work was funded under NASA Heliophysics 21-LWSTM21_2-0018, award number 80NSSC22K0643.</p>
Supplementary material for "Stellar flares" (Living Reviews in Solar Physics)
<p>The file supplementary.tar.gz contains a Jupyter notebook (Figs.ipynb) and supplementary material for recreating Figures 13, 35, 38, and 40 in Kowalski, A.F. (2024), "Stellar flares", <em>Living Reviews in Solar Physics</em> 24, 1 (<a href="10.1007/s41116-024-00039-4">https://doi.org/10.1007/s41116-024-00039-4</a>).</p>
Ionospheric Electron Densities, Neutral Temperature, Winds and Post-processed Output from TIEGCM Simulations in Support of Publication "Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill"
This dataset is associated with the publication "Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill". In particular, the NCAR- Community model: high-resolution thermosphere-ionosphere-electrodynamics general circulation model (TIEGCM) has been used to investigate the response of ionospheric F2-region electron density (Ne) at Millstone Hill (42.610N, 71.480W, maximum obscuration: 63%) to the Great American Solar Eclipse on 21 August 2017. Two sets of model runs were done, one with the eclipse and the other without. Model outputs of winds, temperatures and electron densities, as well as diagnostic variables of key chemical and physical processes that determined the ionosphere responses to the eclipse, were analyzed and used in producing a paper: Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill.
SD4EO - Physically Based Rendering images of human settlements for solar panel detection
<p>This dataset contains part of the results of the SD4EO project, including images corresponding to the use case of solar panel detection on human settlements. The dataset contains images that have been simulated corresponding to low altitude aerial images. Each image in the dataset includes pixel-level labels for each element present in the image, ensuring perfect accuracy due to the synthetic nature of the images. This eliminates common errors in manual or semi-automatic labeling processes.</p> <p><strong>Image labeling</strong></p> <p><strong>(Open Street Map color code)</strong></p> <div> <table> <tbody> <tr> <td> <p><strong>Element</strong></p> </td> <td> <p><strong>R</strong></p> </td> <td> <p><strong>G</strong></p> </td> <td> <p><strong>B</strong></p> </td> </tr> <tr> <td> <p>Road</p> </td> <td> <p>255</p> </td> <td> <p>255</p> </td> <td> <p>255</p> </td> </tr> <tr> <td> <p>Building</p> </td> <td> <p>196</p> </td> <td> <p>182</p> </td> <td> <p>171</p> </td> </tr> <tr> <td> <p>Highway</p> </td> <td> <p>232</p> </td> <td> <p>146</p> </td> <td> <p>162</p> </td> </tr> <tr> <td> <p>Industrial zone</p> </td> <td> <p>234</p> </td> <td> <p>203</p> </td> <td> <p>228</p> </td> </tr> <tr> <td> <p>Parking</p> </td> <td> <p>238</p> </td> <td> <p>238</p> </td> <td> <p>238</p> </td> </tr> <tr> <td> <p>Railway</p> </td> <td> <p>112</p> </td> <td> <p>112</p> </td> <td> <p>112</p> </td> </tr> <tr> <td> <p>Residential zone</p> </td> <td> <p>224</p> </td> <td> <p>223</p> </td> <td> <p>223</p> </td> </tr> <tr> <td> <p>Vegetation</p> </td> <td> <p>174</p> </td> <td> <p>223</p> </td> <td> <p>163</p> </td> </tr> <tr> <td> <p>Water</p> </td> <td> <p>170</p> </td> <td> <p>211</p> </td> <td> <p>223</p> </td> </tr> </tbody> </table> </div> <p>For solar panels masks white color is used to mark the pixels corresponding to solar panels.</p> <p><br><strong>Image name convention</strong></p> <p>The name convention follows the next schema of fields, separated by the character “_”</p> <p>- ID number</p> <p>- Sub ID number</p> <p>- Meters per pixel resolution</p> <p>- Type of image: color, labels, solarpanels</p> <p><strong>Creation and funding</strong></p> <p>All the images have been generated using a tool developed in Unity. This tool will be soon available to enable the generation of new datasets.</p> <p>This research work has been funded by the European Space Agency (ESA) under the FutureEO program and the SD4EO project (Contract No.: 4000142334/23/I-DT), supervised by the ESA Φ-lab.</p> <p><strong>License and attribution</strong></p> <p>This dataset <span>is</span> licensed under a <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a> (CC <span>BY</span> <span>4.0</span>).</p> <p><span>When using the images from this dataset, please attribute them as follows: "Synthetic images created by the research group ARTEC - IRTIC - University of Valencia".</span></p>
High Spectral Resolution, High Cadence, Imaging X-ray Microcalorimeters for Solar Physics - Phase 2 Project
<p> Microcalorimeter x-ray instruments are non-dispersive, high spectral resolution, broad-band, high cadence imaging spectrometers. We have been developing these instruments for x-ray astrophysics for over 25 years and have successfully flown them on both suborbital and orbital observatories. Microcalorimeter spectrometers are true spatial-spectral event-driven instruments. The core instrument for the Astro-H observatory to be launched in 2014 and for the International X-ray Observatory planned for around 2022 [1] are both microcalorimeter spectrometers. For the past two years, supported by the Solar and Heliospheric ROSES program, we have been adapting this highly successful technology to the very different requirements of solar physics. This leverages the large NASA investment in this technology to produce instruments optimized for solar physics with only a moderate development program.</p> <p> During the past two years, we have developed a high spatial resolution, high cadence microcalorimeter optimized for solar observations with a ground-breaking spectral resolving power of nearly 3000 at 6 keV. This exceeds the performance goals of our program. In fact, the single-pixel performance achieved during this program is already sufficient for a solar optimized instrument as described in section 2, albeit using small arrays of detectors. We propose here to continue this successful program by developing large focal-plane arrays, optimized for solar physics and their read-out systems. This complements our existing development programs in astrophysics, where we have already produced and tested kilo-pixel arrays for IXO. The end-result of the proposed work will be a solar-optimized detector system proven and ready for integration into a suborbital payload and then onto a space-borne observatory. Both the suborbital program and an orbital instrument would allow high cadence spatial-spectral observations across the x-ray band from 0.1 to above 10 keV, enabling new science as described in section 1.4. Ultimately this will produce instrumentation suitable for deployment on an Explorer-class mission and, possibly, a remote sensing contribution to the Solar Energetic Particle Acceleration and Transport (SEPAT) Solar-Terrestrial Probe [2]. &nbsp;</p>
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OpenNeuro
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