PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 28, 2025International Journal of Climatology2 citationsOpen Access

Intercomparison of Daily Maximum and Minimum Temperature Gridded Products Over Mainland Spain

View Full Paper
SHSixto HerreraFRFidel González RoucoRSRoberto Serrano‐Notivoli

Key Points

  • Observational uncertainty is greater for minimum temperatures compared to maximum temperatures.
  • Analysis of 10 gridded datasets shows strengths and limitations in statistical distribution and extreme events.
  • A robust examination across multiple evaluation dimensions highlights how specific datasets differ in reliability.
  • The STEAD dataset remains the most stable, while PTI‐Clima v0 has limitations in underestimating extremes.

Abstract

ABSTRACT The sensitivity to the observational reference has been reported in recent studies, highlighting the importance of observational uncertainty in climate research. These studies stress the importance of properly comparing available datasets, recognising their respective strengths and limitations. Here, we conduct a comprehensive analysis of the various datasets of maximum and minimum daily temperatures available for mainland Spain. We examined 10 publicly available daily gridded datasets of maximum and minimum temperatures, analysing multiple evaluation dimensions to identify the key strengths and limitations of each dataset: statistical distribution, extreme events, temporal structure and spells and spatial patterns. We conclude that observational uncertainty is greater for minimum temperatures than for maximum temperatures. This uncertainty is not strictly linked to the type of dataset (interpolation, analysis or reanalysis) or its spatial domain (national, European or global) but rather to specific datasets which vary depending on the analysis dimension. Overall, the most stable dataset across all evaluated indices is STEAD, whereas the PTI‐Clima v0 dataset exhibits some underestimation of extremes and spells but performs well in capturing central parameters and temporal correlations.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Herrera et al. (2025) studied this question.

synapsesocial.com/papers/68d90a0a41e1c178a14f6836https://doi.org/10.1002/joc.70111
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Ensemble Version of the E‐OBS Temperature and Precipitation Data Sets2018 · 1,930 citations
  2. 2EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe2022 · 50 citations
  3. 3An Alternative Measure of the Reliability of Ordinary Kriging Estimates2000 · 176 citations
  4. 4Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over France2008 · 659 citations
  5. 5Designing AfriCultuReS services to support food security in Africa2020 · 16 citations