Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China DOI Creative Commons
Peng Zhao,

Zhibin He,

Dengke Ma

et al.

Frontiers in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 11

Published: Feb. 24, 2023

An increase in extreme temperature events could have a significant impact on terrestrial ecosystems. Reanalysis data are an important set for estimation mountainous areas with few meteorological stations. The ability of ERA5-Land reanalysis to capture the index published by Expert Team Climate Change Detection and Indices (ETCCDI) was evaluated using observational from 17 stations Qilian Mountains (QLM) during 1979–2017. results show that can well daily maximum temperature, two warm extremes (TXx TX90p) one cold (FD0) QLM. ERA5-Land’s is best summer worst spring winter. In addition, trends all indices except range (DTR). main bias due difference elevation between ground observation station grid point. simulation accuracy increases decrease difference. provide reference study local data.

Language: Английский

Evaluation of ERA5 and ERA5-Land reanalysis precipitation datasets over Spain (1951–2020) DOI Creative Commons
José Gomis-Cebolla, Viera Rattayová, Sergio Salazar-Galán

et al.

Atmospheric Research, Journal Year: 2023, Volume and Issue: 284, P. 106606 - 106606

Published: Jan. 4, 2023

Reanalysis precipitation estimates are widely used in the fields of meteorology and hydrology because they can provide physical, spatial, temporal coherent long time series at a global scale. Nevertheless, as pre-requisite for many applications their performance needs to be assessed. The objective this study was evaluate European Centre Medium-Range Weather Forecasts (ECMWF) latest fifth-generation reanalysis products, i.e., ERA5 ERA5-Land, country scale Spain. For doing so, we compared it against high-resolution product Spanish Meteorological Agency which spans approximately 70 years (1951–2020). A comprehensive assessment (continuous, categorical, probability distribution function (pdf), spatial pattern, trend) performed order ascertain quality products. Results analysis revealed general agreement between observations ERA5-Land/ERA5 estimates: spearman correlation values 0.5 0.9, Root Mean Square Error (RMSE) mostly 2 8 mm/d Kling Gupta Efficiency (KGE) >0.4. Categorical additionally indicated good (Heiken Skill score (HSS) score, also known kappa, 0.4 0.8). found dependent on climatic region, intensity orography. Correlation north-west (higher values) south-east (lower gradient while relative bias (RBIAS) RMSE patterns were positively correlated with slope (ρ = 0.41/0.35, 0.69/0.70, respectively). In addition, by categorical analysis, along Mediterranean coast wet (i.e., overestimation days precipitation) found. detection capacity (kappa) shown negative −0.29/−0.34). Worst model is obtained during summer months, generalized overestimation. pdf that tended overestimate light (≥1 < 5 mm/day), moderate (≥5 20 mm/day) categories underestimating heavy (≥20 40 violent (≥40 categories. Moderate provided best capacity, precipitation-intensity analysis. showed reproduce trends observations. ERA5-Land ERA5, different resolution, very similar all considered. northern highlighted most critical modelling purposes its performance.

Language: Английский

Citations

102
Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America DOI Creative Commons
Ting‐Chen Chen, François Collet, Alejandro Di Luca

et al.

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 44(3), P. 729 - 747

Published: Feb. 1, 2024

Abstract While the ERA5 reanalysis is commonly utilized in climate studies on extratropical cyclones (ETCs), only a few have quantified its ability representation of ETCs over land. To address this gap, study evaluates ERA5's skill representing ETC‐associated 10‐m wind speed and precipitation central eastern North America during 2005–2019. Hourly data collected from ~3000 stations, amounting to around 420 million reports stored Integrated Surface Database, used as reference. For spatial‐averaged ETC properties, shows good for with normalized mean bias (NMB) −0.7% root‐mean‐square error (NRMSE) 14.3%, despite tendency overestimate low winds underestimate high winds. The worse than NMB −10.4% NRMSE 56.5% strong values. both variables, best worst performance found DJF JJA, respectively. Negative biases are often identified regions stronger precipitation/wind speeds, systematic underestimation Rockies complex topography. Compared averaged ETCs, deteriorates top 5% extreme (NMB −10.2% −22.6%, respectively). Furthermore, local values within spatial averages. Our results highlight some important limitations products looking at possible impacts ETCs.

Language: Английский

Citations

18
The first global multi-timescale daily SPEI dataset from 1982 to 2021 DOI Creative Commons
Xuebang Liu,

Shuying Yu,

Zhiwei Yang

et al.

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Feb. 21, 2024

Global warming accelerates water cycle, causing more droughts globally that challenge monitoring and forecasting. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to assess drought characteristics response time of natural economic systems at various timescales. However, existing SPEI datasets have coarse spatial or temporal resolution limited extent, restricting their ability accurately identify the start end dates extent global scale. To narrow these gaps, we developed a daily dataset (SPEI-GD), with 0.25° from 1982 2021 multiple timescales (5, 30, 90, 180 360 days), based on precipitation European Center for Medium Weather Forecasting Reanalysis V5 (ERA5) potential evapotranspiration Singer's dataset. Compared widely SPEIbase dataset, SPEI-GD can improve spatial-temporal accuracy in areas where meteorological sites are lacking. significantly correlates site-based soil moisture. Our solidly supports sub-seasonal daily-scale regional research.

Language: Английский

Citations

18
How much water vapour does the Tibetan Plateau release into the atmosphere? DOI Creative Commons
Chaolei Zheng, Jia Li, Guangcheng Hu

et al.

Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(2), P. 485 - 506

Published: Jan. 23, 2025

Abstract. Water vapour flux, expressed as evapotranspiration (ET), is critical for understanding the earth climate system and complex heat–water exchange mechanisms between land surface atmosphere in high-altitude Tibetan Plateau (TP) region. However, performance of ET products over TP has not been adequately assessed, there still considerable uncertainty magnitude spatial variability water released from into atmosphere. In this study, we evaluated 22 against situ observations basin-scale balance estimations. This study also spatiotemporal total flux its components to clarify TP. The results showed that remote sensing high-resolution global data ETMonitor PMLV2 had a high accuracy, with overall better accuracy than other regional fine resolution (∼ 1 km), when comparing observations. When compared estimates at basin scale, finer GLEAM TerraClimate coarse good agreement. Different different patterns variability, large differences central western multi-year multi-product mean was 333.1 mm yr−1, standard deviation 38.3 yr−1. (i.e. plant transpiration, soil evaporation, canopy rainfall interception open-water snow/ice sublimation) available some were compared, contribution these varied considerably, even cases where similar. Soil evaporation accounts most TP, followed by transpiration while contributions sublimation cannot be negligible.

Language: Английский

Citations

3
Comparing the use of ERA5 reanalysis dataset and ground-based agrometeorological data under different climates and topography in Italy DOI Creative Commons
Daniela Vanella, Giuseppe Longo-Minnolo, Oscar Rosario Belfiore

et al.

Journal of Hydrology Regional Studies, Journal Year: 2022, Volume and Issue: 42, P. 101182 - 101182

Published: July 22, 2022

The study region is represented by seven irrigation districts distributed under different climate and topography conditions in Italy. This explores the reliability consistency of global ERA5 single levels ERA5-Land reanalysis datasets predicting main agrometeorological estimates commonly used for crop water requirements calculation. In particular, data was compared, variable-by-variable (e.g., solar radiation, Rs; air temperature, Tair; relative humidity, RH; wind speed, u10; reference evapotranspiration, ET0), with situ observations obtained from 66 automatic weather stations (2008–2020). addition, presence a climate-dependency on their accuracy assessed at districts. A general good agreement between observed variables both daily seasonal scales. best performance Tair, followed RH, Rs, u10 datasets, especially temperate conditions. These performances were translated into slightly higher ET0 product, confirming potential using as an alternative source retrieving overcoming unavailability data.

Language: Английский

Citations

63
Changes in wind energy potential over China using a regional climate model ensemble DOI
Zhuo Chen, Junhong Guo,

Wei Li

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2022, Volume and Issue: 159, P. 112219 - 112219

Published: Feb. 16, 2022

Language: Английский

Citations

57
Assessing the use of ERA5-Land reanalysis and spatial interpolation methods for retrieving precipitation estimates at basin scale DOI
Giuseppe Longo-Minnolo, Daniela Vanella, Simona Consoli

et al.

Atmospheric Research, Journal Year: 2022, Volume and Issue: 271, P. 106131 - 106131

Published: March 8, 2022

Language: Английский

Citations

45
A First Evaluation of ERA5-Land Reanalysis Temperature Product Over the Chinese Qilian Mountains DOI Creative Commons
Peng Zhao, Zhibin He

Frontiers in Earth Science, Journal Year: 2022, Volume and Issue: 10

Published: Aug. 8, 2022

Reanalysis temperature products are important datasets for estimates over high-elevation areas with few meteorological stations. In this study, surface 2 m air data from 17 stations 1979 to 2017 in the Qilian Mountains (QLM) used comparison newest reanalysis product: ERA5-Land derived European Centre Medium-Range Weather Forecasts (ECMWF). general, product can reproduce observation variation at different time scales very well. A high monthly correlation coefficient that ranges 0.978 0.998 suggests could capture observations However, attention should be paid before using individual sites because of average root-mean-square-error (RMSE) 2.2°C all The biases between and mainly caused by elevation differences grid points sites. annual mean shows a significant warming trend (0.488°C/decade) based on observations. captures increasing well (0.379°C/decade). biggest positive trends both found summer values 0.574°C/decade 0.496°C/decade, respectively. We suggest generally reproduces is reliable scientific research QLM.

Language: Английский

Citations

42
A global typical meteorological year (TMY) database on ERA5 dataset DOI
Yi Wu, Jingjing An,

Chenxi Gui

et al.

Building Simulation, Journal Year: 2023, Volume and Issue: 16(6), P. 1013 - 1026

Published: March 26, 2023

Language: Английский

Citations

28
Optimizing the rate of straw returning to balance trade-offs between carbon emission budget and rice yield in China DOI

Ruo-Chen Li,

Yugang Tian, Fan Wang

et al.

Sustainable Production and Consumption, Journal Year: 2024, Volume and Issue: 47, P. 166 - 177

Published: March 27, 2024

Language: Английский

Citations

12