HYADES - A Global Archive of Annual Maxima Daily Precipitation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F24%3A100803" target="_blank" >RIV/60460709:41330/24:100803 - isvavai.cz</a>

Výsledek na webu

<a href="https://www-nature-com.infozdroje.czu.cz/articles/s41597-024-03109-2" target="_blank" >https://www-nature-com.infozdroje.czu.cz/articles/s41597-024-03109-2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41597-024-03109-2" target="_blank" >10.1038/s41597-024-03109-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

HYADES - A Global Archive of Annual Maxima Daily Precipitation

Popis výsledku v původním jazyce

Time series of annual maxima daily precipitation are crucial for understanding extreme precipitation behavior and its shifts toward nonstationarity with global warming. Extreme precipitation insight assists hydraulic infrastructure design, water resource management, natural hazard prevention, and climate change adaptation. However, not even a third of the records are of sufficient length, and the number of active stations keeps decreasing. Herein, we present HYADES: archive of yearly maxima of daily precipitation records, a global dataset derived from the Global Historical Climatology Network database of daily records (GHCN-Daily). The HYADES dataset contains records from 39 206 stations (heterogeneously distributed worldwide) with record lengths varying from 16 to 200 years between 1805 and 2023. HYADES was extracted through a methodology designed to accurately capture the true maxima even in the presence of missing values within the records. The method's thresholds were determined and evaluated through Monte Carlo simulations. Our approach demonstrates a 96.73% success rate in detecting the true maxima while preserving time series statistical properties of interest (L-moments and temporal monotonic trend).

Název v anglickém jazyce

HYADES - A Global Archive of Annual Maxima Daily Precipitation

Popis výsledku anglicky

Time series of annual maxima daily precipitation are crucial for understanding extreme precipitation behavior and its shifts toward nonstationarity with global warming. Extreme precipitation insight assists hydraulic infrastructure design, water resource management, natural hazard prevention, and climate change adaptation. However, not even a third of the records are of sufficient length, and the number of active stations keeps decreasing. Herein, we present HYADES: archive of yearly maxima of daily precipitation records, a global dataset derived from the Global Historical Climatology Network database of daily records (GHCN-Daily). The HYADES dataset contains records from 39 206 stations (heterogeneously distributed worldwide) with record lengths varying from 16 to 200 years between 1805 and 2023. HYADES was extracted through a methodology designed to accurately capture the true maxima even in the presence of missing values within the records. The method's thresholds were determined and evaluated through Monte Carlo simulations. Our approach demonstrates a 96.73% success rate in detecting the true maxima while preserving time series statistical properties of interest (L-moments and temporal monotonic trend).

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)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

SCIENTIFIC DATA

ISSN

2052-4463

e-ISSN

2052-4463

Svazek periodika

11

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

11

Strana od-do

1-11

Kód UT WoS článku

001185885000002

EID výsledku v databázi Scopus

2-s2.0-85188070853