GLBD-FED: a global first-hand in-situ daily temperature dataset preferentially with a 00:00–24:00 UTC 24 h window (1981–2024)

Abstract. Large amounts of sub-daily temperature data are shared globally through the Global Telecommunication System (GTS) in near-real time and through international data exchanges. However, converting these data into a global daily temperature dataset with a uniform definition – especially for daily maximum (Tmax) and minimum (Tmin) temperatures – has proven challenging due to the independent observation schedules across the world. To address this issue, we developed a new method that decomposes sub-daily Tmax and Tmin records from the Integrated Surface Database (ISD) into finer intervals, subsequently reaggregating them into daily Tmax and Tmin based on a prospective 00:00–24:00 UTC dateline. This new method increased the global daily Tmax and Tmin data counts by 64 % and 45 %, respectively, compared to the original method, which relied on either two consecutive Tmax/Tmin records over 12 h or a single Tmax/Tmin record over 24 h. The Global Land Base Dataset-First Estimate Daily Data (GLBD-FED) was established for the period from 1981 to 2024, following corrections for misrecorded Tmax and Tmin and quality control. GLBD-FED includes daily maximum (Tmax), average (Tave), and minimum temperature (Tmin) from approximately 17 000 global sites, with daily data amounts reaching about 10 000 entries per day in the current decade. When compared to the Global Summary of the Day (GSOD) dataset, GLBD-FED exhibits less extreme daily values over the last 40 years, showing a slightly lower daily Tmax (around −0.3 °C) and a higher daily Tmin (around +0.3 °C), with a nearly identical daily Tave (approximately +0.1 °C). These systematic differences arise from multiple sources, including: (1) UTC-boundary double-counting artifacts in GSOD (which alone introduced an average bias of +0.28 °C in Tmax and −0.85 °C in Tmin across ∼18 million and ∼11 million duplicated records, respectively); (2) differing sub-daily data source preferences (Synoptic vs. METAR reports); and (3) divergent date boundary treatment methods. The database and associated data can be found at https://doi.org/10.5281/zenodo.17895292 (Yang et al., 2025).