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Nowcasting sunshine number using logistic modeling

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F13%3A00389974" target="_blank" >RIV/67985807:_____/13:00389974 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/s00703-013-0240-1" target="_blank" >http://dx.doi.org/10.1007/s00703-013-0240-1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00703-013-0240-1" target="_blank" >10.1007/s00703-013-0240-1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Nowcasting sunshine number using logistic modeling

  • Original language description

    In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127?136, 2002). Our statistical approach isbased on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/LD12009" target="_blank" >LD12009: Advanced methods for energy production forecasting by photovoltaic systems using high resolution NWP models</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Meteorology and Atmospheric Physics

  • ISSN

    0177-7971

  • e-ISSN

  • Volume of the periodical

    120

  • Issue of the periodical within the volume

    1-2

  • Country of publishing house

    AT - AUSTRIA

  • Number of pages

    11

  • Pages from-to

    61-71

  • UT code for WoS article

    000316689700006

  • EID of the result in the Scopus database