PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F24%3A100711" target="_blank" >RIV/60460709:41330/24:100711 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.envsoft.2024.106076" target="_blank" >https://doi.org/10.1016/j.envsoft.2024.106076</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.envsoft.2024.106076" target="_blank" >10.1016/j.envsoft.2024.106076</a>

Jazyk výsledku

angličtina

Název v původním jazyce

PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data

Popis výsledku v původním jazyce

Simulation models are a fundamental tool for investigating hydrological processes and for water resource management. In this study, we introduce PyCoSMoS, a Python toolbox that enables researchers to simulate observed univariate time series mimicking hydroclimatic processes. This toolbox preserves arbitrary marginal distribution and autocorrelation functions, while significantly reducing computational burden. PyCoSMoS is built upon the mixed -Uniform CoSMoS method recently proposed by Papalexiou et al. (2023). The toolbox is designed to minimize the user's input, requiring only observed time series, marginal distribution, correlation function, and the number of lags. The output provides both visual and quantitative comparisons between the observed and simulated time series. We evaluate the performance of the package using various synthetic case studies and the results demonstrate satisfactory accuracy. Furthermore, we apply the toolbox to three real case studies: precipitation, temperature, and relative humidity, for which the toolbox can successfully simulate the observed time series in each case.

Název v anglickém jazyce

PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data

Popis výsledku anglicky

Simulation models are a fundamental tool for investigating hydrological processes and for water resource management. In this study, we introduce PyCoSMoS, a Python toolbox that enables researchers to simulate observed univariate time series mimicking hydroclimatic processes. This toolbox preserves arbitrary marginal distribution and autocorrelation functions, while significantly reducing computational burden. PyCoSMoS is built upon the mixed -Uniform CoSMoS method recently proposed by Papalexiou et al. (2023). The toolbox is designed to minimize the user's input, requiring only observed time series, marginal distribution, correlation function, and the number of lags. The output provides both visual and quantitative comparisons between the observed and simulated time series. We evaluate the performance of the package using various synthetic case studies and the results demonstrate satisfactory accuracy. Furthermore, we apply the toolbox to three real case studies: precipitation, temperature, and relative humidity, for which the toolbox can successfully simulate the observed time series in each case.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10510 - Climatic research

Projekt

<a href="/cs/project/GM22-33266M" target="_blank" >GM22-33266M: Vyhodnocení intenzifikace suchozemského hydrologického cyklu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Environmental Modelling & Software

ISSN

1364-8152

e-ISSN

1364-8152

Svazek periodika

2024

Číslo periodika v rámci svazku

178

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

001247709400001

EID výsledku v databázi Scopus

2-s2.0-85194478705