Trends in intraseasonal temperature variability in Europe: Comparison of station data with gridded data and reanalyses

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F24%3A00586404" target="_blank" >RIV/68378289:_____/24:00586404 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11310/24:10483437

Výsledek na webu

<a href="https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.8512" target="_blank" >https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.8512</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/joc.8512" target="_blank" >10.1002/joc.8512</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Trends in intraseasonal temperature variability in Europe: Comparison of station data with gridded data and reanalyses

Popis výsledku v původním jazyce

Trends in temperature variability are often referred to have higher effect on temperature extremes than trends in the mean. We investigate trends in three complementary measures of intraseasonal temperature variability: (a) standard deviation of mean daily temperature (SD), (b) mean absolute value of day-to-day temperature change (DTD) and (c) 1-day lagged temporal autocorrelation of temperature (LAG). It is a well-established fact that different types of data (station, gridded, reanalyses) provide different temperature characteristics and particularly their trends. Moreover, we have uncovered that trends in measures of variability are considerably sensitive to data inhomogeneities. Therefore, we use five different datasets, one station based (ECA&D), one gridded (EOBS) and three reanalyses (JRA-55, NCEP/NCAR, 20CR), and compare them. The period from 1961 to 2014 where all datasets overlap is examined, and the linear regression method is utilized to calculate trends of investigated measures in summer and winter. Intraseasonal temperature variability tends to decrease in winter, especially in eastern and northern Europe, where trends below7%<middle dot>decade-1 are detected for all measures. Decreases in DTD and LAG (indicating increase in persistence) prevail also in summer while summer SD tends to increase. The increase in the width of temperature distribution and the simultaneous increase in persistence indicate a tendency towards the rise in the frequency of extended extreme events in summer. Unlike previous studies, our results imply that reanalyses are not the least accurate in determining trends. JRA-55 appears to be the least diverging from other datasets, while the largest discrepancies are detected for DTD at station data.

Název v anglickém jazyce

Trends in intraseasonal temperature variability in Europe: Comparison of station data with gridded data and reanalyses

Popis výsledku anglicky

Trends in temperature variability are often referred to have higher effect on temperature extremes than trends in the mean. We investigate trends in three complementary measures of intraseasonal temperature variability: (a) standard deviation of mean daily temperature (SD), (b) mean absolute value of day-to-day temperature change (DTD) and (c) 1-day lagged temporal autocorrelation of temperature (LAG). It is a well-established fact that different types of data (station, gridded, reanalyses) provide different temperature characteristics and particularly their trends. Moreover, we have uncovered that trends in measures of variability are considerably sensitive to data inhomogeneities. Therefore, we use five different datasets, one station based (ECA&D), one gridded (EOBS) and three reanalyses (JRA-55, NCEP/NCAR, 20CR), and compare them. The period from 1961 to 2014 where all datasets overlap is examined, and the linear regression method is utilized to calculate trends of investigated measures in summer and winter. Intraseasonal temperature variability tends to decrease in winter, especially in eastern and northern Europe, where trends below7%<middle dot>decade-1 are detected for all measures. Decreases in DTD and LAG (indicating increase in persistence) prevail also in summer while summer SD tends to increase. The increase in the width of temperature distribution and the simultaneous increase in persistence indicate a tendency towards the rise in the frequency of extended extreme events in summer. Unlike previous studies, our results imply that reanalyses are not the least accurate in determining trends. JRA-55 appears to be the least diverging from other datasets, while the largest discrepancies are detected for DTD at station data.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10510 - Climatic research

Projekt

<a href="/cs/project/GA21-07954S" target="_blank" >GA21-07954S: Měnící se proměnlivost atmosféry</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

International Journal of Climatology

ISSN

0899-8418

e-ISSN

1097-0088

Svazek periodika

44

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

3054-3074

Kód UT WoS článku

001230291400001

EID výsledku v databázi Scopus

2-s2.0-85194406179