{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T21:49:18Z","timestamp":1778363358501,"version":"3.51.4"},"reference-count":41,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,5,5]],"date-time":"2019-05-05T00:00:00Z","timestamp":1557014400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s H2020 program","award":["654984"],"award-info":[{"award-number":["654984"]}]},{"DOI":"10.13039\/501100005910","name":"Bundesministerium f\u00fcr Umwelt, Naturschutz, Bau und Reaktorsicherheit","doi-asserted-by":"publisher","award":["209913807"],"award-info":[{"award-number":["209913807"]}],"id":[{"id":"10.13039\/501100005910","id-type":"DOI","asserted-by":"publisher"}]},{"name":"German Federal Ministry for Economic Affairs and Energy","award":["0324307A"],"award-info":[{"award-number":["0324307A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The incoming downward shortwave solar irradiance is harvested to an increasing extent by solar power plants. However, the variable nature of this energy source poses an operational challenge for solar power plants and electrical grids. Intra hour solar irradiance nowcasts with a high temporal and spatial resolution could be used to tackle this challenge. All sky imager (ASI) based nowcasting systems fulfill the requirements in terms of temporal and spatial resolution. However, ASI nowcasts can only be used if the required accuracies for applications in solar power plants and electrical grids are fulfilled. Scalar error metrics, such as mean absolute deviation, root mean square deviation, and skill score are commonly used to estimate the accuracy of nowcasting systems. However, these overall error metrics represented by a single number per metric are neither suitable to determine the real time accuracy of a nowcasting system in the actual weather situation, nor suitable to describe any spatially resolved nowcast accuracy. The performance of ASI-based nowcasting systems is strongly related to the prevailing weather conditions. Depending on weather conditions, large discrepancies between the overall and current system uncertainties are conceivable. Furthermore, the nowcast accuracy varies strongly within the irradiance map as higher errors may occur at transient zones close to cloud shadow edges. In this paper, we present a novel approach for the spatially resolved real-time uncertainty specification of ASI-based nowcasting systems. The current irradiance conditions are classified in one of eight distinct temporal direct normal irradiance (DNI) variability classes. For each class and lead-time, an upper and lower uncertainty value is derived from historical data, which describes a coverage probability of 68.3%. This database of uncertainty values is based on deviations of the irradiance maps, compared to three reference pyrheliometers in Tabernas, Andalucia over two years (2016 and 2017). Increased uncertainties due to transient effects are considered by detecting transient zones close to cloud shadow edges within the DNI map. The width of the transient zones is estimated by the current average cloud height, cloud speed, lead-time, and Sun position. The final spatially resolved uncertainties are validated with three reference pyrheliometers, using a data set consisting of the entire year 2018. Furthermore, we developed a procedure based on the DNI temporal variability classes to estimate the expected average uncertainties of the nowcasting system at any geographical location. The novel method can also be applied for global tilted or horizontal irradiance and is assumed to improve the applicability of the ASI nowcasts.<\/jats:p>","DOI":"10.3390\/rs11091059","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T08:19:59Z","timestamp":1557389999000},"page":"1059","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Real-Time Uncertainty Specification of All Sky Imager Derived Irradiance Nowcasts"],"prefix":"10.3390","volume":"11","author":[{"given":"Bijan","family":"Nouri","sequence":"first","affiliation":[{"name":"German Aerospace Center (DLR), Institute of Solar Research, Ctra de Senes s\/n km 4, 04200 Tabernas, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3573-3004","authenticated-orcid":false,"given":"Stefan","family":"Wilbert","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), Institute of Solar Research, Ctra de Senes s\/n km 4, 04200 Tabernas, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Kuhn","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), Institute of Solar Research, Ctra de Senes s\/n km 4, 04200 Tabernas, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalie","family":"Hanrieder","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), Institute of Solar Research, Ctra de Senes s\/n km 4, 04200 Tabernas, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1854-903X","authenticated-orcid":false,"given":"Marion","family":"Schroedter-Homscheidt","sequence":"additional","affiliation":[{"name":"DLR, Institut f\u00fcr Vernetzte Energiesysteme, Carl-von-Ossietzky-Stra\u00dfe 15, 26129 Oldenburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Kazantzidis","sequence":"additional","affiliation":[{"name":"Laboratory of Atmospheric Physics, Department of Physics, University of Patras, 26500 Patras, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Zarzalejo","sequence":"additional","affiliation":[{"name":"CIEMAT Energy Department\u2013Renewable Energy Division, Av. Complutense 40, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philippe","family":"Blanc","sequence":"additional","affiliation":[{"name":"MINES ParisTech, 06904 Sophia Antipolis CEDEX, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sharad","family":"Kumar","sequence":"additional","affiliation":[{"name":"NETRA, NTPC Ltd., E3 Echotech Ii, Udhyog Vihar Greater Noida, Gautam Budh Nagar. Pin 201306, Up, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neeraj","family":"Goswami","sequence":"additional","affiliation":[{"name":"NETRA, NTPC Ltd., E3 Echotech Ii, Udhyog Vihar Greater Noida, Gautam Budh Nagar. Pin 201306, Up, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ravi","family":"Shankar","sequence":"additional","affiliation":[{"name":"NETRA, NTPC Ltd., E3 Echotech Ii, Udhyog Vihar Greater Noida, Gautam Budh Nagar. Pin 201306, Up, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roman","family":"Affolter","sequence":"additional","affiliation":[{"name":"CSP Services. Paseo de Almer\u00eda 73, 2, 04001 Almer\u00eda, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Pitz-Paal","sequence":"additional","affiliation":[{"name":"DLR, Institute of Solar Research, Linder H\u00f6he, 51147 Cologne, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Noureldin, K., Hirsch, T., Kuhn, P., Nouri, B., Yasser, Z., and Pitz-Paal, R. (2017, January 26\u201329). Modelling an Automatic Controller for Parabolic Trough Solar Fields under Realistic Weather Conditions. Proceedings of the 23rd SolarPACES Conference, Santiago, Chile.","DOI":"10.1063\/1.5067211"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.pecs.2013.06.002","article-title":"Solar forecasting methods for renewable energy integration","volume":"39","author":"Inman","year":"2013","journal-title":"Prog. Energy Combust. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.solener.2014.01.030","article-title":"Cloud tracking methodology for intra-hour DNI forecasting","volume":"102","author":"Chu","year":"2014","journal-title":"Sol. Energy"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Richardson, W., Krishnaswami, H., Vega, R., and Cervantes, M. (2017). A low cost, edge computing, all-sky imager for cloud tracking and intra-hour irradiance forecasting. Sustainability, 9.","DOI":"10.3390\/su9040482"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1016\/j.solener.2015.05.037","article-title":"3D cloud detection and tracking system for solar forecast using multiple sky imagers","volume":"118","author":"Peng","year":"2015","journal-title":"Sol. Energy"},{"key":"ref_6","unstructured":"Kariniotakis, G. (2017). Short-term forecasting based on all-sky cameras. Renewable Energy Forecasting, Elsevier Science."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/LGRS.2014.2356616","article-title":"Neural Networks and Support Vector Machine Algorithms for Automatic Cloud Classification of Whole-Sky Ground-Based Images","volume":"12","author":"Taravat","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5729","DOI":"10.1109\/TGRS.2017.2712809","article-title":"DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features","volume":"55","author":"Ye","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"557","DOI":"10.5194\/amt-3-557-2010","article-title":"Automatic cloud classification of whole sky images","volume":"3","author":"Heinle","year":"2010","journal-title":"Atmos. Meas. Tech."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.atmosres.2012.05.005","article-title":"Cloud detection and classification with the use of whole-sky ground-based images","volume":"113","author":"Kazantzidis","year":"2012","journal-title":"Atmos. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1286","DOI":"10.1175\/JTECH-D-11-00009.1","article-title":"A hybrid thresholding algorithm for cloud detection on ground-based color images","volume":"28","author":"Li","year":"2011","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Huang, H., Yoo, S., Yu, D., Huang, D., and Qin, H. (2012, January 12). Correlation and local feature based cloud motion estimation. Proceedings of the Twelfth International Workshop on Multimedia Data Mining, New York, NY, USA.","DOI":"10.1145\/2343862.2343863"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/j.solener.2015.03.030","article-title":"Cloud motion and stability estimation for intra-hour solar forecasting","volume":"115","author":"Chow","year":"2015","journal-title":"Sol. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4151","DOI":"10.5194\/amt-9-4151-2016","article-title":"Coupling sky images with radiative transfer models: A new method to estimate cloud optical depth","volume":"9","author":"Mejia","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.renene.2016.04.026","article-title":"The effect of clouds on surface solar irradiance, based on data from an all-sky imaging system","volume":"95","author":"Tzoumanikas","year":"2016","journal-title":"Renew. Energy"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1175\/JAM2277.1","article-title":"Cloud-base-height estimation from paired ground-based hemispherical observations","volume":"44","author":"Kassianov","year":"2005","journal-title":"J. Appl. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"14231","DOI":"10.5194\/acp-16-14231-2016","article-title":"Cloud photogrammetry with dense stereo for fisheye cameras","volume":"16","author":"Beekmans","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/j.solener.2013.09.016","article-title":"Predicting solar irradiance with all-sky image features via regression","volume":"97","author":"Fu","year":"2013","journal-title":"Sol. Energy"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.solener.2014.09.005","article-title":"Continuous short-term irradiance forecasts using sky images","volume":"110","author":"Bernecker","year":"2014","journal-title":"Sol. Energy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.neucom.2015.02.022","article-title":"A hybrid method based on extreme learning machine and k-nearest neighbor for cloud classification of ground-based visible cloud image","volume":"160","author":"Xia","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3399","DOI":"10.5194\/acp-16-3399-2016","article-title":"Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts","volume":"16","author":"Schmidt","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1002\/pip.2968","article-title":"Validation of an all-sky imager-based nowcasting system for industrial PV plants","volume":"26","author":"Kuhn","year":"2017","journal-title":"Prog. Photovolt. Res. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Marquez, R., and Coimbra, C.F. (2013). Proposed metric for evaluation of solar forecasting models. J. Sol. Energy Eng., 135.","DOI":"10.1115\/1.4007496"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.solener.2019.02.004","article-title":"Determination of cloud transmittance for all sky imager based solar nowcasting","volume":"181","author":"Nouri","year":"2019","journal-title":"Sol. Energy"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Schroedter-Homscheidt, M., Kosmale, M., Jung, S., and Kleissl, J. (2018). Classifying ground-measured 1 minute temporal variability within hourly intervals for direct normal irradiances. Meteorol. Z.","DOI":"10.1127\/metz\/2018\/0875"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.solener.2018.10.079","article-title":"Cloud height and tracking accuracy of three all sky imager systems for individual clouds","volume":"177","author":"Nouri","year":"2019","journal-title":"Sol. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1989","DOI":"10.1016\/j.egypro.2015.03.205","article-title":"Screening and flagging of solar irradiation and ancillary meteorological data","volume":"69","author":"Geuder","year":"2015","journal-title":"Energy Procedia"},{"key":"ref_28","unstructured":"Wilbert, S., Nouri, B., Prahl, C., Garcia, G., Ramirez, L., Zarzalejo, L., Valenzuela, L., Ferrera, F., Kozonek, N., and Liria, J. (2016, January 20\u201324). Application of Whole Sky Imagers for Data Selection for Radiometer Calibration. Proceedings of the EU PVSEC 2016, Munich, Germany."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nouri, B., Kuhn, P., Wilbert, S., Prahl, C., Pitz-Paal, R., Blanc, P., Schmidt, T., Yasser, Z., Ramirez Santigosa, L., and Heineman, D. (2018). Nowcasting of DNI maps for the solar field based on voxel carving and individual 3D cloud objects from all sky images. AIP Conf. Proc.","DOI":"10.1063\/1.5067196"},{"key":"ref_30","unstructured":"Jung, S. (2015). Variabilit\u00e4t der solaren Einstrahlung in 1-Minuten aufgel\u00f6sten Strahlungszeitserien. [Master\u2018s Thesis, Universit\u00e4t Augsburg]."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.solener.2013.04.012","article-title":"Economic merits of a state-of-the-art concentrating solar power forecasting system for participation in the Spanish electricity market","volume":"93","author":"Kraas","year":"2013","journal-title":"Sol. Energy"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1016\/j.solener.2011.03.016","article-title":"Parameterization of site-specific short-term irradiance variability","volume":"85","author":"Perez","year":"2011","journal-title":"Sol. Energy"},{"key":"ref_33","unstructured":"Stein, J.S., Hansen, C.W., and Reno, M.J. (2012, January 13\u201317). The variability index: A new and novel metric for quantifying irradiance and PV output variability. Proceedings of the World Renewable Energy Forum, Denver, CO, USA."},{"key":"ref_34","unstructured":"Kleissl, J. (2013). Overview of Solar-Forecasting Methods and a Metric for Accuracy Evaluation. Solar Energy Forecasting and Resource Assessment, Academic Press."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.solener.2016.01.051","article-title":"Modeling beam attenuation in solar tower plants using common DNI measurements","volume":"129","author":"Hanrieder","year":"2016","journal-title":"Sol. Energy"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wilbert, S., Kleindiek, S., Nouri, B., Geuder, N., Habte, A., Schwandt, M., and Vignola, F. (2016). Uncertainty of rotating shadowband irradiometers and Si-pyranometers including the spectral irradiance error. AIP Conf. Proc.","DOI":"10.1063\/1.4949241"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/S0038-092X(02)00045-2","article-title":"A new airmass independent formulation for the Linke turbidity coefficient","volume":"73","author":"Ineichen","year":"2002","journal-title":"Sol. Energy"},{"key":"ref_38","unstructured":"Schwarzb\u00f6zl, P., Gross, V., Quaschnig, V., and Ahlbrink, N. (2011, January 20\u201323). A low-cost dynamic shadow detection system for site evaluation. In proceeding of the 17th SolarPACES, Granada, Spain."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.solener.2018.12.038","article-title":"Determination of the optimal camera distance for cloud height measurements with two all-sky imagers","volume":"179","author":"Kuhn","year":"2019","journal-title":"Sol. Energy"},{"key":"ref_40","first-page":"252","article-title":"Methods for fast morphological image transforms using bitmapped binary images","volume":"54","year":"1992","journal-title":"CVGIP: Graph. Models Image Process."},{"key":"ref_41","first-page":"11045","article-title":"Automatic cloud-type classification based on the combined use of a sky camera and a ceilometer","volume":"122","year":"2017","journal-title":"J. Geophys. Res. Atmos."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/9\/1059\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:49:12Z","timestamp":1760186952000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/9\/1059"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,5]]},"references-count":41,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2019,5]]}},"alternative-id":["rs11091059"],"URL":"https:\/\/doi.org\/10.3390\/rs11091059","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,5]]}}}