Large-Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F23%3A97558" target="_blank" >RIV/60460709:41330/23:97558 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1029/2022WR034094" target="_blank" >http://dx.doi.org/10.1029/2022WR034094</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1029/2022WR034094" target="_blank" >10.1029/2022WR034094</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Large-Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites

Popis výsledku v původním jazyce

Stochastic simulations of spatiotemporal patterns of hydroclimatic processes, such as precipitation, are needed to build alternative but equally plausible inputs for water-related design and management, and to estimate uncertainty and assess risks. However, while existing stochastic simulation methods are mature enough to deal with relatively small domains and coarse spatiotemporal scales, additional work is required to develop simulation tools for large-domain analyses, which are more and more common in an increasingly interconnected world. This study proposes a methodological advancement in the CoSMoS framework, which is a flexible simulation framework preserving arbitrary marginal distributions and correlations, to dramatically decrease the computational burden and make the algorithm fast enough to perform large-domain simulations in short time. The proposed approach focuses on correlated processes with mixed (zero-inflated) Uniform marginal distributions. These correlated processes act as intermediates between the target process to simulate (precipitation) and parent Gaussian processes that are the core of the simulation algorithm. Working in the mixed-Uniform space enables a substantial simplification of the so-called correlation transformation functions, which represent a computational bottle neck in the original CoSMoS formulation. As a proof of concept, we simulate 40 years of daily precipitation records from 1,000 gauging stations in the Mississippi River basin. Moreover, we extend CoSMoS incorporating parent non-Gaussian processes with different degrees of tail dependence and suggest potential improvements including the separate simulation of occurrence and intensity processes, and the use of advection, anisotropy, and nonstationary spatiotemporal correlation functions.

Název v anglickém jazyce

Large-Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites

Popis výsledku anglicky

Stochastic simulations of spatiotemporal patterns of hydroclimatic processes, such as precipitation, are needed to build alternative but equally plausible inputs for water-related design and management, and to estimate uncertainty and assess risks. However, while existing stochastic simulation methods are mature enough to deal with relatively small domains and coarse spatiotemporal scales, additional work is required to develop simulation tools for large-domain analyses, which are more and more common in an increasingly interconnected world. This study proposes a methodological advancement in the CoSMoS framework, which is a flexible simulation framework preserving arbitrary marginal distributions and correlations, to dramatically decrease the computational burden and make the algorithm fast enough to perform large-domain simulations in short time. The proposed approach focuses on correlated processes with mixed (zero-inflated) Uniform marginal distributions. These correlated processes act as intermediates between the target process to simulate (precipitation) and parent Gaussian processes that are the core of the simulation algorithm. Working in the mixed-Uniform space enables a substantial simplification of the so-called correlation transformation functions, which represent a computational bottle neck in the original CoSMoS formulation. As a proof of concept, we simulate 40 years of daily precipitation records from 1,000 gauging stations in the Mississippi River basin. Moreover, we extend CoSMoS incorporating parent non-Gaussian processes with different degrees of tail dependence and suggest potential improvements including the separate simulation of occurrence and intensity processes, and the use of advection, anisotropy, and nonstationary spatiotemporal correlation functions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

WATER RESOURCES RESEARCH

ISSN

0043-1397

e-ISSN

0043-1397

Svazek periodika

59

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

24

Strana od-do

1-24

Kód UT WoS článku

000973564300001

EID výsledku v databázi Scopus

2-s2.0-85152536109