All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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

The result's identifiers

  • Result code in 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>

  • Alternative codes found

    RIV/00216208:11310/24:10483437

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10510 - Climatic research

Result continuities

  • Project

    <a href="/en/project/GA21-07954S" target="_blank" >GA21-07954S: Varying atmospheric variability</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Climatology

  • ISSN

    0899-8418

  • e-ISSN

    1097-0088

  • Volume of the periodical

    44

  • Issue of the periodical within the volume

    9

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    21

  • Pages from-to

    3054-3074

  • UT code for WoS article

    001230291400001

  • EID of the result in the Scopus database

    2-s2.0-85194406179