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The Spatial Weather Generator SPAGETTA: Hard Times of its Adolescence
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SYSNO ASEP 0558946 Druh ASEP A - Abstrakt Zařazení RIV Záznam nebyl označen do RIV Zařazení RIV Není vybrán druh dokumentu Název The Spatial Weather Generator SPAGETTA: Hard Times of its Adolescence Tvůrce(i) Dubrovský, Martin (UFA-U) RID, ORCID
Lhotka, Ondřej (UFA-U) RID, ORCID
Mikšovský, Jiří (UEK-B) RID
Štěpánek, Petr (UEK-B) RID, SAI, ORCID
Meitner, Jan (UEK-B) ORCID, SAI, RIDCelkový počet autorů 5 Zdroj.dok. EGU General Assembly 2022. - Göttingen : European Geosciences Union, 2022
EGU22-7485Poč.str. 1 s. Forma vydání Online - E Akce EGU22 FAQs Datum konání 23.05.2022 - 27.05.2022 Místo konání Vienna Země AT - Rakousko Typ akce WRD Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova Stochastic weather generator ; climate change impact experiment ; SPAGETTA Vědní obor RIV DG - Vědy o atmosféře, meteorologie Obor OECD Climatic research Vědní obor RIV – spolupráce Vědy o atmosféře, meteorologie Institucionální podpora UFA-U - RVO:68378289 ; RVO:67179843 - RVO:67179843 Anotace Stochastic weather generators (WGs) are tools for producing weather series, mimicking statistical properties of their real-world counterparts. They are often used in climate change impact experiments as a source of the data representing the present and/or future climates (alternative to RCMs and GCMs). Development of our SPAGETTA generator started in 2016 (Dubrovsky et al 2020; https://doi.org/10.1007/s00704-019-03027-z). The presentation will focus on (A) Basic details. (B) Functionalities of the generator. (C) Results obtained with the generator by now. (D) Most critical problems, which were met (and not yet satisfactorily solved) while making the generator fully operational.
A. SPAGETTA is a multivariate multisite parametric generator, which is based on autoregressive modeling (following the D. Wilks’ papers). It is designed mainly (but not solely) for use in agricultural and hydrological modeling. It may produce time series of up to 8 variables for as many as (approx.) 200 stations or grid points. Typically, it produces time series of temperature, precipitation, solar radiation, humidity and wind speed. It usually runs with a daily time step.
B. The main functionalities include: (1) It may produce arbitrarily long time series representing the climate defined by the data used for calibrating the generator (might be observational data or, for example, RCM outputs). (2) Having modified the WG parameters by the climate change scenario (typically derived from GCM or RCM simulations), SPAGETTA may produce weather series representing the future climate. In this case, one may study sensitivity of selected climatic indices to changes in various statistics (e.g. means and standard deviations of weather variables, and characteristics of temporal and spatial structure of the time series). (3) SPAGETTA may be interpolated so that it can produce weather series for sites with no observational data. (4) It can be linked with the circulation generator so that WG may better represent larger-scale (both in space and time) weather variability.
C. The results obtained with the generator by now include: (a) Validation of the generator in terms of WG parameters, various climatic indices, and outputs of hydrological model fed by the synthetic series produced by SPAGETTA. (b) Impacts of the forthcoming climate change on various climatic characteristics (RCM-based climate change scenarios were used here). Focus was put on spatial temperature-precipitation compound characteristics. (c) Validation of the interpolated generator. (d) Validation of the generator driven by the larger scale circulation generator.
D. Problems to be solved: (i) Under some circumstances (especially when a large number of the stations is used, or while interpolating the generator), matrices of the AR model imply unstable AR process which diverges to unrealistic values of weather variables. (ii) The generator underestimates the low frequency variability. Development of the larger scale circulation generator, which would eliminate this drawback, is still under development.
Only examples of the previous points will be shown in the presentation.Pracoviště Ústav fyziky atmosféry Kontakt Kateřina Adamovičová, adamovicova@ufa.cas.cz, Tel.: 272 016 012 ; Kateřina Potužníková, kaca@ufa.cas.cz, Tel.: 272 016 019 Rok sběru 2023
Počet záznamů: 1