SC Earth A Station based Serially Complete Earth Dataset from 1950 to 2019

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A86952" target="_blank" >RIV/60460709:41330/21:86952 - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-21-0067.1/JCLI-D-21-0067.1.xml" target="_blank" >https://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-21-0067.1/JCLI-D-21-0067.1.xml</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1175/JCLI-D-21-0067.1" target="_blank" >10.1175/JCLI-D-21-0067.1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SC Earth A Station based Serially Complete Earth Dataset from 1950 to 2019

Popis výsledku v původním jazyce

Meteorological data from ground stations suffer from temporal discontinuities caused by missing values and short measurement periods. Gap filling and reconstruction techniques have proven to be effective in producing serially complete station datasets (SCDs) that are used for a myriad of meteorological applications (developing gridded meteorological datasets and validating models). To our knowledge, all SCDs are developed at regional scales. In this study, we developed the serially complete Earth (SC Earth) dataset, which provides daily precipitation, mean temperature, temperature range, dewpoint temperature, and wind speed data from 1950 to 2019. SC Earth utilizes raw station data from the Global Historical Climatology Network Daily (GHCN D) and the Global Surface Summary of the Day (GSOD). A unified station repository is generated based on GHCN-D and GSOD after station merging and strict quality control. ERA5 is optimally matched with station data considering the time shift issue and then used to a

Název v anglickém jazyce

SC Earth A Station based Serially Complete Earth Dataset from 1950 to 2019

Popis výsledku anglicky

Meteorological data from ground stations suffer from temporal discontinuities caused by missing values and short measurement periods. Gap filling and reconstruction techniques have proven to be effective in producing serially complete station datasets (SCDs) that are used for a myriad of meteorological applications (developing gridded meteorological datasets and validating models). To our knowledge, all SCDs are developed at regional scales. In this study, we developed the serially complete Earth (SC Earth) dataset, which provides daily precipitation, mean temperature, temperature range, dewpoint temperature, and wind speed data from 1950 to 2019. SC Earth utilizes raw station data from the Global Historical Climatology Network Daily (GHCN D) and the Global Surface Summary of the Day (GSOD). A unified station repository is generated based on GHCN-D and GSOD after station merging and strict quality control. ERA5 is optimally matched with station data considering the time shift issue and then used to a

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10501 - Hydrology

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

JOURNAL OF CLIMATE

ISSN

0894-8755

e-ISSN

1520-0442

Svazek periodika

34

Číslo periodika v rámci svazku

16

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

19

Strana od-do

6493-6511

Kód UT WoS článku

000677665400001

EID výsledku v databázi Scopus

2-s2.0-85111124217