Homogenised Monthly and Daily Temperature and Precipitation Time Series in China and Greece since 1960

Abstract

In this paper, we describe and analyze two datasets entitled “Homogenised monthly and daily temperature and precipitation time series in China during 1960–2021” and “Homogenised monthly and daily temperature and precipitation time series in Greece during 1960–2010”. These datasets provide the homogenised monthly and daily mean (TG), minimum (TN), and maximum (TX) temperature and precipitation (RR) records since 1960 at 366 stations in China and 56 stations in Greece. The datasets are available at the Science Data Bank repository and can be downloaded from https://doi.org/10.57760/sciencedb.01731 and https://doi.org/10.57760/sciencedb.01720. For China, the regional mean annual TG, TX, TN, and RR series during 1960–2021 showed significant warming or increasing trends of 0.27°C (10 yr)−1, 0.22°C (10 yr)−1, 0.35°C (10 yr)−1, and 6.81 mm (10 yr)−1, respectively. Most of the seasonal series revealed trends significant at the 0.05 level, except for the spring, summer, and autumn RR series. For Greece, there were increasing trends of 0.09°C (10 yr)−1, 0.08°C (10 yr)−1, and 0.11°C (10 yr)−1 for the annual TG, TX, and TN series, respectively, while a decreasing trend of −23.35 mm (10 yr)−1 was present for RR. The seasonal trends showed a significant warming rate for summer, but no significant changes were noted for spring (except for TN), autumn, and winter. For RR, only the winter time series displayed a statistically significant and robust trend [−15.82 mm (10 yr)−1]. The final homogenised temperature and precipitation time series for both China and Greece provide a better representation of the large-scale pattern of climate change over the past decades and provide a quality information source for climatological analyses.

Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes

“…Homogenized daily surface relative humidity from Li et al 83 and surface air temperature from Argiriou et al 84 were employed to verify the trend of T w and E a derived from the original observations. We also adopted monthly T w and E a from the Met Office Hadley Centre Integrated Surface Database Humidity (HadISDH, https://www.metoffice.gov.uk/hadobs/hadisdh ).…”

Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables

“…The data from these five stations were previously obtained by [7]. Because it has been stated [25] that to detect longterm climate change reliably via good quality research, one must work with homogenized series, in this study, the meteorological series were homogenized with the Climatol library "https://climatol.eu (accessed on 12 January 2024)" [24,39]. This software is based on the standard normal homogeneity test method [26].…”

“…(a) For essential climate variables, using the National Meteorological Service (SMN)-National Water Commission (CONAGUA) database [23], daily series of precipitation and maximum-minimum temperatures were obtained. To obtain reliable, long-term, good quality results [24,25], the SMN-CONAGUA daily series were homogenized using the standard normal homogeneity test method [26]. With the homogenized series, the mean daily temperature (meanT) was determined.…”

Terrestrial Evapotranspiration Over China From 1982 to 2020: Consistency of Multiple Data Sets and Impact of Input Data

“…In recent years, considerable efforts have been devoted to detecting and correcting inhomogeneity in observed meteorological variables in China, including surface incident solar radiation (F. Feng & Wang, 2021a, 2021b; He et al., 2018; W. Tang et al., 2011; K. Wang, 2014), precipitation (Argiriou et al., 2023; Q. Li et al., 2012; W. Liu et al., 2019), air temperature (L. Cao et al., 2016; Yan & Jones, 2008), relative humidity (Z. Li et al., 2020; Y. Zhu et al., 2015), and wind speed (Yan et al., 2014; Z. Zhang & Wang, 2021, 2023). Inhomogeneity affects the estimation of long‐term variations in these meteorological variables.…”

“…Tang et al, 2011;K. Wang, 2014), precipitation (Argiriou et al, 2023;Q. Li et al, 2012;, air temperature (L. Cao et al, 2016;Yan & Jones, 2008), relative humidity (Z.…”