scholarly journals Assessment of the solar energy potential in Greece using ground-based measurements, satellite observations and numerical simulations of radiative transfer models

2018 ◽  
Author(s):  
Παναγιώτης-Νεκτάριος Κοσμόπουλος
Keyword(s):  
Solar Energy ◽  
Radiative Transfer ◽  
Numerical Simulations ◽  
Satellite Observations ◽  
Surface Radiation ◽  
Energy Potential ◽  
Radiative Transfer Models ◽  
Transfer Models

Η παρούσα διδακτορική διατριβή πραγματεύεται την εκτίμηση του ηλιακού δυναμικού στον Ελλαδικό χώρο με επίγειες και δορυφορικές παρατηρήσεις και αριθμητικές προσομοιώσεις μοντέλων διάδοσης της ακτινοβολίας. Αρχικά χρησιμοποιήθηκαν πυρανόμετρα από το Ελληνικό Δίκτυο Ηλιακής Ενέργειας και το δίκτυο σταθμών του Εθνικού Αστεροσκοπείου Αθηνών με σκοπό την αξιολόγηση προγνώσεων ηλιακής ενέργειας 1 και 2 ημερών μπροστά από το μοντέλο MM5. Το ολικό δυναμικό ηλιακής ενέργειας βρέθηκε να κυμαίνεται μεταξύ 1,5 και 1,9 MWh/m2 με τη νέφωση να προκαλεί αύξηση των σφαλμάτων πρόγνωσης της τάξης του 10%. Εν συνεχεία, εκτιμήθηκε η επίδραση των αιωρούμενων σωματιδίων στην επιφανειακή ηλιακή ακτινοβολία, εστιάζοντας σε ένα έντονο επεισόδιο σκόνης, αναδεικνύοντας τις υψηλές απώλειες ηλιακής ενέργειας της τάξης του 80 και 50% για τα συγκεντρωτικά (CSP) και τα φωτοβολταϊκά (PV) συστήματα αντίστοιχα. Οι παραπάνω αναλύσεις πραγματικών σεναρίων και ατμοσφαιρικών συνθηκών συνεισφέρουν στην κατανόηση αλλά και στην ποσοτικοποίηση του εύρους της επίδρασης που έχουν τα νέφη και τα αιωρούμενα σωματίδια στην ηλιακή ενέργεια, αλλά και στις δυνητικές αστοχίες πρόγνωσης σε περιοχές με υψηλό ηλιακό δυναμικό όπως είναι η Ελλάδα. Ταυτόχρονα, αναπτύχθηκε μια σειρά από καινοτόμα μοντέλα εκτίμησης του δυναμικού ηλιακής ενέργειας τα οποία δύνανται να λειτουργούν επιχειρησιακά και σε πραγματικό χρόνο. Τα μοντέλα αυτά βασίζονται σε πίνακες προσομοιώσεων διάδοσης της ακτινοβολίας, σε τεχνικές υπολογιστικής επιτάχυνσης με νευρωνικά δίκτυα και εξισώσεις πολλαπλής παλινδρόμησης και δορυφορικά δεδομένα εισόδου πραγματικού χρόνου. Η αξιοπιστία τους επαληθεύτηκε με επίγειες μετρήσεις των δικτύων Baseline Surface Radiation Network και Global Atmosphere Watch από τη νότια Αφρική μέχρι τη βόρεια Ευρώπη, ενώ πραγματοποιήθηκε και μια ανάλυση ευαισθησίας των δεδομένων εισόδου (κυρίως νεφών και αιωρούμενων σωματιδίων) ως προς την επίδρασή τους στην ηλιακή ακτινοβολία. Η συνολική προσέγγιση του διδακτορικού στοχεύει στο να αποτελέσει ένα βήμα μπροστά στην πρόγνωση της ηλιακής ενέργειας, στον επιχειρησιακά εφικτό ενεργειακό σχεδιασμό των ηλιακών πάρκων, στην αποτελεσματική εκμετάλλευση της ηλιακής ενέργειας, αλλά και στο να συνεισφέρει στο σχηματισμό πολιτικών που αφορούν τις ανανεώσιμες πηγές ενέργειας.

scholarly journals Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over North-Eastern Canada

2018 ◽  
Author(s):  
Fanny Larue ◽  
Alain Royer ◽  
Danielle De Sève ◽  
Alexandre Roy ◽  
Emmanuel Cosme
Keyword(s):  
Radiative Transfer ◽  
Forest Cover ◽  
Snow Water Equivalent ◽  
Satellite Observations ◽  
Passive Microwave ◽  
Observation Error ◽  
Error Matrix ◽  
Radiative Transfer Models ◽  
Hydrological Applications ◽  
Transfer Models

Abstract. Over northeastern Canada, the amount of water stored in a snowpack, estimated by its snow water equivalent (SWE) amount, is a key variable for hydrological applications. The limited number of weather stations driving snowpack models over large and remote northern areas generates great uncertainty in SWE evolution. A data assimilation (DA) scheme was developed to improve SWE estimates by updating meteorological forcing data and snowpack states using passive microwave (PMW) satellite observations without using any surface-based data. In this DA experiment, a particle filter with a Sampled Importance Resampled algorithm (SIR) was applied and an inflation technique of the observation error matrix was developed to avoid ensemble degeneracy. The Advanced Microwave Scanning Radiometer – 2 (AMSR-2) brightness temperatures (TB) observations were assimilated into a chain of models composed of the Crocus multi-layer snowpack model and radiative transfer models. The microwave snow emission model (Dense Media Radiative Transfer – Multi-Layers (DMRT-ML)), the vegetation transmissivity model (ω–τopt), and atmospheric and soil radiative transfer models were calibrated to simulate the contributions from the snowpack, the vegetation and the soil, respectively, at the top of the atmosphere. DA experiments were performed over 12 stations where daily continuous SWE measurements were acquired during 4 winters (2012–2016). Best SWE estimates are obtained with the assimilation of the TBs at 11, 19 and 37 GHz in vertical polarizations. The overall SWE bias is reduced by 71% compared to original SWE simulations, from 23.7 kg m−2 without assimilation to 6.9 kg m−2 with the assimilation of the three frequencies. The overall SWE relative percentage of error (RPE) is 14.6 % for sites with a fraction of forest cover below 75 %, which is in the range of accuracy needed for hydrological applications. This research opens the way for global applications to improve SWE estimates over large and remote areas, even when vegetation contributions are up to 50 % of the PMW signal.

scholarly journals Comparison of observed and modelled longwave downward radiation (2010–2016) at the high mountain BSRN Izaña station

2018 ◽  
Author(s):  
Rosa Delia García ◽  
Africa Barreto ◽  
Emilio Cuevas ◽  
Julian Gröbner ◽  
Omaira Elena García ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Excellent Agreement ◽  
Surface Radiation ◽  
High Mountain ◽  
Comparison Study ◽  
Radiative Transfer Models ◽  
Downward Radiation ◽  
Transfer Models

Abstract. A 7-year (2010–2016) comparison study between measured and simulated longwave downward radiation (LDR) under cloud-free conditions has been performed at the Izaña Atmospheric Observatory (IZO, Spain). This analysis encompasses a total of 2062 cases distributed almost 50 % between day and night. Results show an excellent agreement between Baseline Surface Radiation Network (BSRN) measurements and simulations with LibRadtran V2.0.1 and MODTRAN V6 radiative transfer models (RTM), similar for both models. Mean bias (simulated-measured)

scholarly journals Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada

2018 ◽  
Vol 22 (11) ◽  
pp. 5711-5734 ◽  
Author(s):  
Fanny Larue ◽  
Alain Royer ◽  
Danielle De Sève ◽  
Alexandre Roy ◽  
Emmanuel Cosme
Keyword(s):  
Radiative Transfer ◽  
Forest Cover ◽  
Snow Water Equivalent ◽  
Satellite Observations ◽  
Passive Microwave ◽  
Observation Error ◽  
Error Matrix ◽  
Radiative Transfer Models ◽  
Hydrological Applications ◽  
Transfer Models

Abstract. Over northeastern Canada, the amount of water stored in a snowpack, estimated by its snow water equivalent (SWE) amount, is a key variable for hydrological applications. The limited number of weather stations driving snowpack models over large and remote northern areas generates great uncertainty in SWE evolution. A data assimilation (DA) scheme was developed to improve SWE estimates by updating meteorological forcing data and snowpack states with passive microwave (PMW) satellite observations and without using any surface-based data. In this DA experiment, a particle filter with a Sequential Importance Resampling algorithm (SIR) was applied and an inflation technique of the observation error matrix was developed to avoid ensemble degeneracy. Advanced Microwave Scanning Radiometer 2 (AMSR-2) brightness temperature (TB) observations were assimilated into a chain of models composed of the Crocus multilayer snowpack model and radiative transfer models. The microwave snow emission model (Dense Media Radiative Transfer – Multi-Layer model, DMRT-ML), the vegetation transmissivity model (ω-τopt), and atmospheric and soil radiative transfer models were calibrated to simulate the contributions from the snowpack, the vegetation, and the soil, respectively, at the top of the atmosphere. DA experiments were performed for 12 stations where daily continuous SWE measurements were acquired over 4 winters (2012–2016). Best SWE estimates are obtained with the assimilation of the TBs at 11, 19, and 37 GHz in vertical polarizations. The overall SWE bias is reduced by 68 % compared to the original SWE simulations, from 23.7 kg m−2 without assimilation to 7.5 kg m−2 with the assimilation of the three frequencies. The overall SWE relative percentage of error (RPE) is 14.1 % (19 % without assimilation) for sites with a fraction of forest cover below 75 %, which is in the range of accuracy needed for hydrological applications. This research opens the way for global applications to improve SWE estimates over large and remote areas, even when vegetation contributions are up to 50 % of the PMW signal.

Inference over radiative transfer models using variational and expectation maximization methods

2021 ◽  
Author(s):  
Daniel Heestermans Svendsen ◽  
Daniel Hernández-Lobato ◽  
Luca Martino ◽  
Valero Laparra ◽  
Álvaro Moreno-Martínez ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Expectation Maximization ◽  
Radiative Transfer Models ◽  
Transfer Models

scholarly journals Comparisons of Ocean Radiative Transfer Models With SMAP and AMSR2 Observations

2019 ◽  
Vol 124 (11) ◽  
pp. 7683-7699 ◽  
Author(s):  
Lise Kilic ◽  
Catherine Prigent ◽  
Jacqueline Boutin ◽  
Thomas Meissner ◽  
Stephen English ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Models ◽  
Transfer Models
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