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5 results on '"Micha Schöll"'

1. Methodology to create a new total solar irradiance record: Making a composite out of multiple data records

Author

Greg Kopp, Thierry Dudok de Wit, Claus Fröhlich, Micha Schöll, Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], Professionnel sans affiliation, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), European Project: 313188,EC:FP7:SPA,FP7-SPACE-2012-1,SOLID(2012), and Sans affiliation

Subjects
010504 meteorology & atmospheric sciences, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], Maximum likelihood, Composite number, FOS: Physical sciences, Astrophysics, Solar irradiance, 01 natural sciences, 0103 physical sciences, Statistical physics, Instrumentation and Methods for Astrophysics (astro-ph.IM), 010303 astronomy & astrophysics, Scaling, Solar and Stellar Astrophysics (astro-ph.SR), 0105 earth and related environmental sciences, Physics, Radiative forcing, Multiple data, Geophysics, Astrophysics - Solar and Stellar Astrophysics, 13. Climate action, Physics - Data Analysis, Statistics and Probability, General Earth and Planetary Sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Data Analysis, Statistics and Probability (physics.data-an), Merge (linguistics)
Abstract

Many observational records critically rely on our ability to merge different (and not necessarily overlapping) observations into a single composite. We provide a novel and fully-traceable approach for doing so, which relies on a multi-scale maximum likelihood estimator. This approach overcomes the problem of data gaps in a natural way and uses data-driven estimates of the uncertainties. We apply it to the total solar irradiance (TSI) composite, which is currently being revised and is critical to our understanding of solar radiative forcing. While the final composite is pending decisions on what corrections to apply to the original observations, we find that the new composite is in closest agreement with the PMOD composite and the NRLTSI2 model. In addition, we evaluate long-term uncertainties in the TSI, which reveal a 1/f scaling, slightly expanded version of a manuscript to appear in Geophysical Research Letters (2017)

Published
2017

2. Making of a solar spectral irradiance dataset I: observations, uncertainties, and methods

Author

Margit Haberreiter, Matthieu Kretzschmar, Micha Schöll, Thierry Dudok de Wit, Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National d’Études Spatiales [Paris] (CNES), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), European Project: 313188,EC:FP7:SPA,FP7-SPACE-2012-1,SOLID(2012), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Computer science, Irradiance, Data analysis, Time series analysis, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, lcsh:QC851-999, Solar irradiance, 7. Clean energy, 01 natural sciences, Proxy (climate), 0103 physical sciences, Statistics and probability, Time series, 010303 astronomy & astrophysics, 0105 earth and related environmental sciences, Remote sensing, [SDU.ASTR.SR]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR], Missing data, Autoregressive model, Solar spectrum, 13. Climate action, Space and Planetary Science, Outlier, Anomaly detection, lcsh:Meteorology. Climatology, Algorithms
Abstract

Context. Changes in the spectral solar irradiance (SSI) are a key driver of the variability of the Earth’s environment, strongly affecting the upper atmosphere, but also impacting climate. However, its measurements have been sparse and of different quality. The “First European Comprehensive Solar Irradiance Data Exploitation project” (SOLID) aims at merging the complete set of European irradiance data, complemented by archive data that include data from non-European missions. Aims. As part of SOLID, we present all available space-based SSI measurements, reference spectra, and relevant proxies in a unified format with regular temporal re-gridding, interpolation, gap-filling as well as associated uncertainty estimations. Methods. We apply a coherent methodology to all available SSI datasets. Our pipeline approach consists of the pre-processing of the data, the interpolation of missing data by utilizing the spectral coherency of SSI, the temporal re-gridding of the data, an instrumental outlier detection routine, and a proxy-based interpolation for missing and flagged values. In particular, to detect instrumental outliers, we combine an autoregressive model with proxy data. We independently estimate the precision and stability of each individual dataset and flag all changes due to processing in an accompanying quality mask. Results. We present a unified database of solar activity records with accompanying meta-data and uncertainties. Conclusions. This dataset can be used for further investigations of the long-term trend of solar activity and the construction of a homogeneous SSI record.

Published
2016

3. Identification of photospheric activity features from SOHO/MDI data using the ASAP tool

Author

Stan Ipson, Rami Qahwaji, Omar W Ashamari, Margit Haberreiter, Micha Schöll, O. Nibouche, University of Bradford, Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), School of Computing and Mathematics, University of Ulster, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), SOHO is a project of international cooperation between ESA and NASA, and European Project: 313188,EC:FP7:SPA,FP7-SPACE-2012-1,SOLID(2012)

Subjects
Atmospheric Science, Meteorology, Solar image processing, Computer science, Irradiance, FOS: Physical sciences, lcsh:QC851-999, Solar irradiance, Solar cycle, 7. Clean energy, symbols.namesake, Photosphere, Magnetogram, Segmentation, Solar and Stellar Astrophysics (astro-ph.SR), Remote sensing, Sunspot, Active region, Sun, Magnetic field, Spectral irradiance, Astrophysics - Solar and Stellar Astrophysics, 13. Climate action, Space and Planetary Science, [SDU]Sciences of the Universe [physics], symbols, lcsh:Meteorology. Climatology, Doppler effect
Abstract

International audience; The variation of solar irradiance is one of the natural forcing mechanisms of the terrestrial climate. Hence, the time-dependent solar irradiance is an important input parameter for climate modelling. The solar surface magnetic field is a powerful proxy for solar irradiance reconstruction. The analyses of data obtained with the Michelson Doppler Imager (MDI) on board the SOHO mission are therefore useful for the identification of solar surface magnetic features to be used in solar irradiance reconstruction models. However, there is still a need for automated technologies that would enable the identification of solar activity features from large databases. To achieve this we present a series of enhanced segmentation algorithms developed to detect and calculate the area coverages of specific magnetic features from MDI intensitygrams and magnetograms. These algorithms are part of the Automated Solar Activity Prediction (ASAP) tool. The segmentation algorithms allow us to identify the areas on the solar disk covered by magnetic elements inside and outside boundaries of active regions. Depending on their contrast properties, magnetic features within an active region boundary are classified as sunspot umbra and penumbra, or faculae. Outside an active region boundary magnetic elements are identified as network. We present the detailed steps involved in the segmentation process and provide the area coverages of the segmented MDI intensitygrams and magnetograms. The feature segmentation has been carried out on daily intensitygrams and magnetograms from April 21, 1996 to April 11, 2011. This offers an exciting opportunity to undertake further investigations that benefit from solar features segmentations, such as solar irradiance reconstruction, which we plan to investigate in the future.

Published
2015

4. Solar Spectral Irradiance Observations from the PICARD/PREMOS Radiometer

Author

Micha Schöll, Gaël Cessateur, Werner Schmutz, Christoph Wehrli, Julian Groebner, Margit Haberreiter, Matthieu Kretzschmar, Alexander Shapiro, Gérard Thuillier, Wolfgang Finsterle, Nigel Fox, Jean-François Hochedez, Silvio Koller, Mustapha Meftah, Stephan Nyeki, Daniel Pfiffner, Hansjörg Roth, Michel Rouzé, Marcel Spescha, Rinat Tagirov, Lutz Werner, Jules Wyss, Cardon, Catherine, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), Max-Planck-Institut für Sonnensystemforschung = Max Planck Institute for Solar System Research (MPS), Max-Planck-Gesellschaft, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), National Physical Laboratory [Teddington] (NPL), Centre National d'Études Spatiales [Toulouse] (CNES), Physikalisch-Technische Bundesanstalt [Berlin] (PTB), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National d’Études Spatiales [Paris] (CNES), and Max-Planck-Institut für Sonnensystemforschung (MPS)

Subjects
[SDU.ASTR.SR]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR], [SDU.ASTR.SR] Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR]
Abstract

International audience; Space weather and space climate studies require accurate Solar Spectral Irradiance (SSI) observations. The PREcision Monitoring Sensor (PREMOS) instrument aboard the PICARD satellite acquired solar irradiance measurements in specific spectral windows in the UV, visible and near infrared from October 2010 to March 2014. This contribution aims at presenting the Level 3 data, corrected for non solar features as well as for degradation. These level 3 data has been tested over different scientific cases, such as observations during the Venus transit and the presence of the p-mode signature within high-cadence data. The PREMOS Level 3 data have also been compared to others data sets, namely the SOLSTICE and SIM instruments aboard SORCE, for nearly 3 and half years. An excellent correlation has been found for the UV spectral ranges. We have also found a rather good correlation for visible and near-infrared observations for short-term variations, for which an error of about 200 ppm has been estimated within PREMOS visible and near-infrared observations. The PREMOS data could also be used to address several scientific topics, i.e. for validating semi-empirical models of the solar irradiance. We will emphasize about our new irradiance model, COSIR for Code of Solar Irradiance Reconstruction, which is successful at reproducing the solar modulation as seen in the PREMOS, SoHO/Virgo and SORCE data.

Published
2015

5. Solar irradiance observations with PREMOS filter radiometers on the PICARD mission: In-flight performance and data release

Author

Julian Gröbner, S. Nyeki, Peter Meindl, T. Egorova, Wolfgang Finsterle, Gaël Cessateur, Jean-François Hochedez, Rinat Tagirov, Mustapha Meftah, G. Thuillier, Christoph Wehrli, M. Rouzé, Hansjörg Roth, Alexander Shapiro, Werner Schmutz, Eugene Rozanov, Nigel Fox, Matthieu Kretzschmar, S. Koller, Micha Schöll, M. Haberreiter, Marcel Spescha, Daniel Pfiffner, Lutz Werner, Jules U Wyss, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Max-Planck-Institut für Sonnensystemforschung = Max Planck Institute for Solar System Research (MPS), Max-Planck-Gesellschaft, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), National Physical Laboratory [Teddington] (NPL), Physikalisch-Technische Bundesanstalt [Berlin] (PTB), Centre National d'Études Spatiales [Toulouse] (CNES), European Community’s Seventh Framework Programme (FP7/2007-2013), CNES/PICARD GI programme, European Project: 313188,EC:FP7:SPA,FP7-SPACE-2012-1,SOLID(2012), European Project: 284461,EC:FP7:SPA,FP7-SPACE-2011-1,EHEROES(2012), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National d’Études Spatiales [Paris] (CNES), and Max-Planck-Institut für Sonnensystemforschung (MPS)

Subjects
010504 meteorology & atmospheric sciences, Meteorology, Infrared, Solar activity, Irradiance, Venus, Radiation, Solar irradiance, 01 natural sciences, 7. Clean energy, Instrumentation: photometers, UV radiation, 0103 physical sciences, Solar radiation, Solstice, 010303 astronomy & astrophysics, 0105 earth and related environmental sciences, Remote sensing, Physics, Radiometer, biology, Spacecraft, business.industry, Astronomy and Astrophysics, biology.organism_classification, [SDU.ASTR.IM]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM], 13. Climate action, Space and Planetary Science, Solar-terrestrial relations, business
Abstract

International audience; The PREcision Monitoring Sensor (PREMOS) is a solar radiometer on board the French PICARD mission that was launched in June 2010 and decommissioned in April 2014.Aims. The PREMOS radiometer obtains solar irradiance measurements in specific spectral windows in the UV, visible, and near- infrared. In this paper, the PREMOS data and calibration methods are presented.Methods. Using back-up channels, the degradation can theoretically be assessed to correct operational channels. However, a strong degradation within all PREMOS channels requires the application of additional methods, namely using back-up channels and assess- ing the degradation via a proxy-based model.Results. The corrected Level 3 PREMOS data are then used in different contexts in order to be validated. First, the signature of the p-mode are retrieved from the PREMOS data. The Venus transit allows us to empirically determine the intrinsic noise level within the PREMOS high cadence data for the visible and near-infrared channels. We then compare the PREMOS data directly to other data sets, namely from the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) and the Solar Irradiance Monitor (SIM) instru- ments on board the SOlar Radiation and Climate Experiment (SORCE) spacecraft. Regarding the UV channels, we found an excellent correlation over the lifetime of the PREMOS mission. The ratio between SORCE and PREMOS observations is always less than 1%. Regarding the SSI measurements in the visible and near-infrared, a comparison of short-term variations (i.e. 27-day modulation) shows a rather good correlation by taking into consideration the intrinsic noise within both SIM and PREMOS observations.

Published
2016

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