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Journal articles on the topic 'ERA5-Land'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Muñoz-Sabater, Joaquín, Emanuel Dutra, Anna Agustí-Panareda, et al. "ERA5-Land: a state-of-the-art global reanalysis dataset for land applications." Earth System Science Data 13, no. 9 (2021): 4349–83. http://dx.doi.org/10.5194/essd-13-4349-2021.

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Abstract. Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, coul

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2

Qian, Lihui, and Peng Zhao. "Assessment of ERA5-Land Reanalysis Precipitation Data in the Qilian Mountains of China." Atmosphere 16, no. 7 (2025): 826. https://doi.org/10.3390/atmos16070826.

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Precipitation serves as a crucial indicator of climate change and a vital part of the water cycle in mountainous regions. ERA5-Land, a cutting-edge global reanalysis dataset designed for land applications, has been extensively utilized in climate-related studies. In this research, we assessed the reliability of ERA5-Land monthly averaged reanalysis precipitation data in the Qilian Mountains (QLM). We did this by comparing it with the observations from 17 meteorological stations spanning from 1979 to 2017. The findings indicated that, overall, the ERA5-Land reanalysis precipitation data tended

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3

Gao, Limimg, Yaonan Zhang, and Lele Zhang. "Validation and Spatiotemporal Analysis of Surface Net Radiation from CRA/Land and ERA5-Land over the Tibetan Plateau." Atmosphere 14, no. 10 (2023): 1542. http://dx.doi.org/10.3390/atmos14101542.

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High spatial–temporal resolution surface net radiation (RN) data are of great significance to the study of climate, ecology, hydrology and cryosphere changes on the Tibetan Plateau (TP), but the verification of the surface net radiation products on the plateau is not sufficient. In this study, the China Meteorological Administration Global Land Surface Reanalysis Products (CRA/Land) and ECMWF Land Surface Reanalysis version 5 (ERA5-Land) RN data were validated using ground measurements at daily and monthly time scales, and the spatiotemporal patterns were also analyzed. The results indicate th

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4

Zhang, Liancheng, Guli Jiapaer, Tao Yu, et al. "Evaluating and Correcting Temperature and Precipitation Grid Products in the Arid Region of Altay, China." Remote Sensing 16, no. 2 (2024): 283. http://dx.doi.org/10.3390/rs16020283.

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Temperature and precipitation are crucial indicators for investigating climate changes, necessitating precise measurements for rigorous scientific inquiry. While the Fifth Generation of European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis (ERA5), ERA5 of the Land Surface (ERA5-Land), and China Meteorological Forcing Dataset (CMFD) temperature and precipitation products are widely used worldwide, their suitability for the Altay region of arid and semi-arid areas has received limited attention. Here, we used the Altay region as the study area, utilizing meteorological statio

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5

Guo, Chunrui, Ning Ning, Hao Guo, Yunfei Tian, Anming Bao, and Philippe De Maeyer. "Does ERA5-Land Effectively Capture Extreme Precipitation in the Yellow River Basin?" Atmosphere 15, no. 10 (2024): 1254. http://dx.doi.org/10.3390/atmos15101254.

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ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability of monitoring extreme precipitation. The evaluation study is conducted from three perspectives: precipitation amount, extreme precipitation indices, and characteristics of extreme precipitation events. The results show that ERA5-Land can effectively capture the spatial distributio

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6

Parsons, Danny, David Stern, Denis Ndanguza, and Mouhamadou Bamba Sylla. "Evaluation of Satellite-Based Air Temperature Estimates at Eight Diverse Sites in Africa." Climate 10, no. 7 (2022): 98. http://dx.doi.org/10.3390/cli10070098.

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High resolution satellite and reanalysis-based air temperature estimates have huge potential to complement the sparse networks of air temperature measurements from ground stations in Africa. The recently released Climate Hazards Center Infrared Temperature with Stations (CHIRTS-daily) dataset provides daily minimum and maximum air temperature estimates on a near-global scale from 1983 to 2016. This study assesses the performance of CHIRTS-daily in comparison with measurements from eight ground stations in diverse locations across Africa from 1983 to 2016, benchmarked against the ERA5 and ERA5-

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7

Zhang, Ye, Yintang Wang, Lingjie Li, et al. "Error Decomposition of CRA40-Land and ERA5-Land Reanalysis Precipitation Products over the Yongding River Basin in North China." Atmosphere 13, no. 11 (2022): 1936. http://dx.doi.org/10.3390/atmos13111936.

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Long-term and high-resolution reanalysis precipitation datasets provide important support for research on climate change, hydrological forecasting, etc. The comprehensive evaluation of the error performances of the newly released ERA5-Land and CRA40-Land reanalysis precipitation datasets over the Yongding River Basin in North China was based on the two error decomposition schemes, namely, decomposition of the total mean square error into systematic and random errors and decomposition of the total precipitation bias into hit bias, missed precipitation, and false precipitation. Then, the error f

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8

Kouki, Kerttu, Kari Luojus, and Aku Riihelä. "Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018." Cryosphere 17, no. 12 (2023): 5007–26. http://dx.doi.org/10.5194/tc-17-5007-2023.

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Abstract. Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as tourism and agriculture. Monitoring snow cover at a continental scale is only possible from satellites or using reanalysis data. This study aims to analyze the time series of snow water equivalent (SWE), snow cover extent (SCE), and surface albedo in spring in ERA5 and ERA5-Land reanalysis data and to compare the time series with several satellite-based datasets. As reference data for the SWE intercomparison, we use bias-corrected SnowC

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9

Mayer, Johannes, Michael Mayer, and Leopold Haimberger. "Consistency and Homogeneity of Atmospheric Energy, Moisture, and Mass Budgets in ERA5." Journal of Climate 34, no. 10 (2021): 3955–74. http://dx.doi.org/10.1175/jcli-d-20-0676.1.

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AbstractThis study uses advanced numerical and diagnostic methods to evaluate the atmospheric energy budget with the fifth major global reanalysis produced by ECMWF (ERA5) in combination with observed and reconstructed top of the atmosphere (TOA) energy fluxes for the period 1985–2018. We assess the meridional as well as ocean–land energy transport and perform internal consistency checks using mass-balanced data. Furthermore, the moisture and mass budgets in ERA5 are examined and compared with previous budget evaluations using ERA-Interim as well as observation-based estimates. Results show th

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10

Raharjo, MHFY, IS Lukito, Martarizal, A. Sail, and S. Soekirno. "A Comparative Analysis of Air Temperature Data from Automatic Weather Station and ERA5-Land Reanalysis in Java." Journal of Physics: Conference Series 2989, no. 1 (2025): 012030. https://doi.org/10.1088/1742-6596/2989/1/012030.

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Abstract The present work assesses the relationship between air temperature measurements obtained from Automatic Weather Stations (AWS) and ERA5-Land reanalysis data in Java, Indonesia. The statistical indicators, including Pearson correlation coefficient (r), mean bias error (MBE), and mean absolute error (MAE), were analyzed on data from five AWS sites with different heights. Analysis reveals strong correlations (r > 0.9) between the AWS and ERA5-Land datasets, except for Dieng, which exhibits a weaker correlation (r = 0.75) and a substantial overestimation (MBE = 5.64). In general, ERA5-

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Martens, Brecht, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles. "Evaluating the land-surface energy partitioning in ERA5." Geoscientific Model Development 13, no. 9 (2020): 4159–81. http://dx.doi.org/10.5194/gmd-13-4159-2020.

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Abstract. Climate reanalyses provide a plethora of global atmospheric and surface parameters in a consistent manner over multi-decadal timescales. Hence, they are widely used in many fields, and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets, and to help guide their development. Recently, the European Centre for Medium-Range Weather Forecasts (ECMWF) released the new state-of-the-art climate reanalysis ERA5, following up on its popular predecess

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12

Dhawan, Pranav, Daniele Dalla Torre, Ariele Zanfei, Andrea Menapace, Michele Larcher, and Maurizio Righetti. "Assessment of ERA5-Land Data in Medium-Term Drinking Water Demand Modelling with Deep Learning." Water 15, no. 8 (2023): 1495. http://dx.doi.org/10.3390/w15081495.

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Drinking water demand modelling and forecasting is a crucial task for sustainable management and planning of water supply systems. Despite many short-term investigations, the medium-term problem needs better exploration, particularly the analysis and assessment of meteorological data for forecasting drinking water demand. This work proposes to analyse the suitability of ERA5-Land reanalysis data as weather input in water demand modelling. A multivariate deep learning model based on the long short-term memory architecture is used in this study over a prediction horizon ranging from seven days t

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13

Cao, Bin, Gabriele Arduini, and Ervin Zsoter. "Brief communication: Improving ERA5-Land soil temperature in permafrost regions using an optimized multi-layer snow scheme." Cryosphere 16, no. 7 (2022): 2701–8. http://dx.doi.org/10.5194/tc-16-2701-2022.

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Abstract. We previously reported a notable warm bias in ERA5-Land soil temperature in permafrost regions that was supposedly being caused by an underestimation of snow density. In this study, we implemented and evaluated a new multi-layer snow scheme in the land surface scheme of ERA5-Land, i.e., HTESSEL, with revised snow densification parameterizations. We compared permafrost soil temperatures from the numerical experiments with observations and the original ERA5-Land with a single-layer snow scheme. The revised HTESSEL significantly improved the representation of soil temperature in permafr

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14

Dyukarev, Egor. "Comparison of Artificial Neural Network and Regression Models for Filling Temporal Gaps of Meteorological Variables Time Series." Applied Sciences 13, no. 4 (2023): 2646. http://dx.doi.org/10.3390/app13042646.

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Continuous meteorological variable time series are highly demanded for various climate related studies. Five statistical models were tested for application of temporal gaps filling in time series of surface air pressure, air temperature, relative air humidity, incoming solar radiation, net radiation, and soil temperature. A bilayer artificial neural network, linear regression, linear regression with interactions, and the Gaussian process regression models with exponential and rational quadratic kernel were used to fill the gaps. Models were driven by continuous time series of meteorological va

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15

Ma, Ziqiang, Jintao Xu, Yaoming Ma, et al. "AERA5-Asia: A Long-Term Asian Precipitation Dataset (0.1°, 1-hourly, 1951–2015, Asia) Anchoring the ERA5-Land under the Total Volume Control by APHRODITE." Bulletin of the American Meteorological Society 103, no. 4 (2022): E1146—E1171. http://dx.doi.org/10.1175/bams-d-20-0328.1.

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Abstract Accurate long-term precipitation information is critical for understanding the mechanisms behind how precipitation couples with Earth’s water fluxes, energy balances, and biogeochemical cycles across space–time scales under the changing climate. This study proposes a novel approach [daily total volume controlled merging and disaggregation algorithm (DTVCMDA)] for generating a new long-term precipitation dataset, AERA5-Asia (0.1°, 1-hourly, 1951–2015, Asia; “AERA5” is a combination of the “A” from APHRODITE and the “ERA5” from ERA5-Land), by comprehensively considering the characterist

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16

Zhang, Liumeng, Yaping Yang, Yangxiaoyue Liu, and Xiafang Yue. "Evaluation of Long Time-Series Soil Moisture Products Using Extended Triple Collocation and In Situ Measurements in China." Atmosphere 14, no. 9 (2023): 1351. http://dx.doi.org/10.3390/atmos14091351.

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Currently, satellite-based soil moisture (SM) products and land surface model assimilation techniques are widely utilized. However, the presence of systematic errors in the observation process, algorithmic discrepancies between products, and variations in spatial and temporal scales result in diverse accuracy characteristics and applicability. This study evaluates three prominent SM products in China, namely, the Essential Climate Variable Soil Moisture (ECV), the European Centre for Medium-Range Weather Forecasts’ Fifth-Generation Land Surface Reanalysis Data (ERA5-Land), and the Global Land

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17

Kusch, Erik, and Richard Davy. "KrigR—a tool for downloading and statistically downscaling climate reanalysis data." Environmental Research Letters 17, no. 2 (2022): 024005. http://dx.doi.org/10.1088/1748-9326/ac48b3.

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Abstract Advances in climate science have rendered obsolete the gridded observation data widely used in downstream applications. Novel climate reanalysis products outperform legacy data products in accuracy, temporal resolution, and provision of uncertainty metrics. Consequently, there is an urgent need to develop a workflow through which to integrate these improved data into biological analyses. The ERA5 product family (ERA5 and ERA5-Land) are the latest and most advanced global reanalysis products created by the European Center for Medium-range Weather Forecasting. These data products offer

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18

Gu, Lei, Ziye Gu, Qiang Guo, et al. "Can Satellite and Atmospheric Reanalysis Products Capture Compound Moist Heat Stress-Floods?" Remote Sensing 14, no. 18 (2022): 4611. http://dx.doi.org/10.3390/rs14184611.

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Satellite-retrieved and model-based reanalysis precipitation products with high resolution have received increasing attention in recent decades. Their hydrological performance has been widely evaluated. However, whether they can be applied in characterizing the novel category of extreme events, such as compound moist heat-flood (CMHF) events, has not been fully investigated to date. The CMHF refers to the rapid transition from moist heat stress to devastating floods and has occurred increasingly frequently under the current warming climate. This study focuses on the applicability of the Integr

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19

van der Schalie, Robin, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu. "Characterizing natural variability in complex hydrological systems using passive microwave-based climate data records: a case study for the Okavango Delta." Hydrology and Earth System Sciences 26, no. 13 (2022): 3611–27. http://dx.doi.org/10.5194/hess-26-3611-2022.

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Abstract. The Okavango River system in southern Africa is known for its strong interannual variability of hydrological conditions. Here, we present how this is exposed in surface soil moisture, land surface temperature, and vegetation optical depth as derived from the Land Parameter Retrieval Model, using an inter-calibrated, long-term, multi-sensor passive microwave satellite data record (1998–2020). We also investigate how these interannual variations relate to state-of-the-art climate reanalysis data from ERA5-Land. We analysed both the upstream river catchment and the Okavango delta, suppo

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20

Amazirh, Abdelhakim, Youness Ouassanouan, Houssne Bouimouass, et al. "Remote Sensing-Based Multiscale Analysis of Total and Groundwater Storage Dynamics over Semi-Arid North African Basins." Remote Sensing 16, no. 19 (2024): 3698. http://dx.doi.org/10.3390/rs16193698.

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This study evaluates the use of remote sensing data to improve the understanding of groundwater resources in climate-sensitive regions with limited data availability and increasing agricultural water demands. The research focuses on estimating groundwater reserve dynamics in two major river basins in Morocco, characterized by significant local variability. The study employs data from Gravity Recovery and Climate Experiment satellite (GRACE) and ERA5-Land reanalysis. Two GRACE terrestrial water storage (TWS) products, CSR Mascon and JPL Mascon (RL06), were analyzed, along with auxiliary dataset

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Gourgouletis, Nikolaos, Marianna Gkavrou, and Evangelos Baltas. "Comparison of Empirical ETo Relationships with ERA5-Land and In Situ Data in Greece." Geographies 3, no. 3 (2023): 499–521. http://dx.doi.org/10.3390/geographies3030026.

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Reference evapotranspiration (ETo) estimation is essential for water resources management. The present research compares four different ETo estimators based on reanalysis data (ERA5-Land) and in situ observations from three different cultivation sites in Greece. ETo based on FAO56-Penman–Monteith (FAO-PM) is compared to ETo calculated from the empirical methods of Copais, Valiantzas and Hargreaves-Samani using both reanalysis and in situ data. The daily and monthly biases of each method are calculated against the FAO56-PM method. ERA5-Land data are also compared to ground-truth observations. A

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Duveiller, Gregory, Mark Pickering, Joaquin Muñoz-Sabater, et al. "Getting the leaves right matters for estimating temperature extremes." Geoscientific Model Development 16, no. 24 (2023): 7357–73. http://dx.doi.org/10.5194/gmd-16-7357-2023.

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Abstract. Atmospheric reanalyses combine observations and models through data assimilation techniques to provide spatio-temporally continuous fields of key surface variables. They can do so for extended historical periods whilst ensuring a coherent representation of the main Earth system cycles. ERA5 and its enhanced land surface component, ERA5-Land, are widely used in Earth system science and form the flagship products of the Copernicus Climate Change Service (C3S) of the European Commission. Such land surface modelling frameworks generally rely on a state variable called leaf area index (LA

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23

Xie, Meixia, Zhenhua Di, Jianguo Liu, et al. "Evaluation of Three High-Resolution Satellite and Meteorological Reanalysis Precipitation Datasets over the Yellow River Basin in China." Water 16, no. 22 (2024): 3183. http://dx.doi.org/10.3390/w16223183.

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Recently, Integrated Multi-satellite Retrievals for the Global Precipitation Measurement (IMERG) mission and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) precipitation datasets have been widely used in remote sensing and atmospheric studies, respectively, because of their high accuracy. A dataset of 268 site-gauge precipitation measurements over the Yellow River Basin in China was used in this study to comprehensively evaluate the performance of three high-resolution precipitation products, each with a spatial resolution of 0.1°, consisting of two satellite-derived d

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Scherrer, S. C., M. Hirschi, C. Spirig, F. Maurer, and S. Kotlarski. "Trends and drivers of recent summer drying in Switzerland." Environmental Research Communications 4, no. 2 (2022): 025004. http://dx.doi.org/10.1088/2515-7620/ac4fb9.

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Abstract The Alpine region recently experienced several dry summers with important and adverse impacts on economy, society and ecology. Here, we analyse drought indicators, evapotranspiration and meteorological data from point observations, reanalyses and regional climate model data to assess trends and drivers of summer drought in Switzerland in the period 1981–2020. The drought indicators from station observations and ERA5-Land and ERA5 reanalyses show a tendency towards drier summer half-years (climatic water balance: −39 mm decade−1, 0–1 m integrated soil water content: −5 to −7 mm decade−

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Kageyama, Yuya, and Yohei Sawada. "Global assessment of subnational drought impact based on the Geocoded Disasters dataset and land reanalysis." Hydrology and Earth System Sciences 26, no. 18 (2022): 4707–20. http://dx.doi.org/10.5194/hess-26-4707-2022.

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Abstract. Despite the importance of a link between hydrometeorological drought hazards and their socioeconomic impact, the link at a subnational level has yet to be evaluated due to the lack of precise subnational information on disaster locations. Using the newly developed Geocoded Disasters (GDIS) dataset, we examined whether the subnational socioeconomic drought impact information in GDIS could be represented by hydrometeorological hazards quantified from soil moisture in ERA5-Land during 1964–2018. We found that the socioeconomic drought impacts shown in GDIS were generally represented by

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Shangguan, Wei, Ruqing Zhang, Lu Li, et al. "Assessment of Agricultural Drought Based on Reanalysis Soil Moisture in Southern China." Land 11, no. 4 (2022): 502. http://dx.doi.org/10.3390/land11040502.

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Accurate assessment of agricultural drought is useful for ecosystem services. This is a successive work of our previous study that assessed agricultural drought using the soil water deficit index (SWDI) based on ERA5-Land in the four southern provinces of China from 2017 to 2019. Firstly, in addition to ERA5-Land, the suitability of CLDAS (China Land Data Assimilation System) soil moisture for drought assessment was investigated. Then, the study was extended with more comprehensive analysis and a much longer period (1981–2020). Based on three climate zones, in situ soil moisture was used for e

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Jiang, Yi, Shuai Han, Chunxiang Shi, Tao Gao, Honghui Zhen, and Xiaoyan Liu. "Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea." Atmosphere 12, no. 6 (2021): 766. http://dx.doi.org/10.3390/atmos12060766.

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Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. Th

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Sabu, Maria Kalista Hadia, Doddi Yudianto, and Obaja Triputera Wijaya. "Evaluasi Curah Hujan Berbasis Data Global pada DAS Wae Mese, Labuan Bajo." JURNAL SUMBER DAYA AIR 21, no. 1 (2025): 15–30. https://doi.org/10.32679/jsda.v21i1.906.

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Accuracy of rainfall data is very important in hydrological analysis, especially in areas with limited data such as Labuan Bajo City, Indonesia. Global climate data generated from satellite observations and assimilation products, which are freely available, have great potential for use in data scarce areas. However, this data needs to be evaluated to measure its accuracy in rainfall estimates. This research aims to evaluate the accuracy of eight global rainfall data products, namely Global Precipitation Measurement (GPM), Precipitation Estimation from Remotely Sensed Information using Artifici

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Linarka, Utoyo A., Mangapul P. Tambunan, Eko Kusratmoko, and Arnida L. Latifah. "Assessing the spatiotemporal precipitation trends from ERA5-Land over Indonesia region." IOP Conference Series: Earth and Environmental Science 1438, no. 1 (2025): 012046. https://doi.org/10.1088/1755-1315/1438/1/012046.

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Abstract The availability and accuracy of high-resolution spatial and temporal climate data are required for various climate-related analyses, especially in areas with varying topography and climate. The long-term ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecast (ECMWF) combines climate model and observation data from around the world into a complete and consistent collection with a spatial resolution of 0.1°. This high-resolution climate data is considered to be a reliable gridded dataset spanning various regions. Due to the scarcity of ground-based data in

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Albergel, Clément, Emanuel Dutra, Bertrand Bonan, et al. "Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation." Remote Sensing 11, no. 5 (2019): 520. http://dx.doi.org/10.3390/rs11050520.

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This study aims to assess the potential of the LDAS-Monde platform, a land data assimilation system developed by Météo-France, to monitor the impact on vegetation state of the 2018 summer heatwave over Western Europe. The LDAS-Monde is driven by ECMWF’s (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (IFS-HRES), used in conjunction with the assimilation of Copernicus Global Land Service (CGLS) satellite-derived products, namely the Surface Soil Moisture (SSM) and the Leaf Area Index (LAI). The study of long time series of satellite derived C

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Zhang, Ruqing, Lu Li, Ye Zhang, et al. "Assessment of Agricultural Drought Using Soil Water Deficit Index Based on ERA5-Land Soil Moisture Data in Four Southern Provinces of China." Agriculture 11, no. 5 (2021): 411. http://dx.doi.org/10.3390/agriculture11050411.

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It is important to accurately assess agricultural drought because of its harmful impacts on the ecosystem and economy. Soil moisture reanalysis datasets provide an important way to assess agricultural drought. In this study, the ERA5-Land surface and subsurface soil moisture was used to estimate the soil water deficit index (SWDI) in four southern provinces of China. The ERA5-Land dataset was evaluated with in situ soil moisture observations from agrometeorological stations. Agricultural drought was assessed for three climate zones at a weekly scale from 2017 to 2019 and was compared with the

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Xu, Chao, Wen Wang, Yanjun Hu, and Yongwei Liu. "Evaluation of ERA5, ERA5-Land, GLDAS-2.1, and GLEAM potential evapotranspiration data over mainland China." Journal of Hydrology: Regional Studies 51 (February 2024): 101651. http://dx.doi.org/10.1016/j.ejrh.2023.101651.

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Burdanowitz, Jörg, Stefan A. Buehler, Stephan Bakan, and Christian Klepp. "The sensitivity of oceanic precipitation to sea surface temperature." Atmospheric Chemistry and Physics 19, no. 14 (2019): 9241–52. http://dx.doi.org/10.5194/acp-19-9241-2019.

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Abstract. Our study forms the oceanic counterpart to numerous observational studies over land concerning the sensitivity of extreme precipitation to a change in air temperature. We explore the sensitivity of oceanic precipitation to changing sea surface temperature (SST) by exploiting two novel datasets at high resolution. First, we use the Ocean Rainfall And Ice-phase precipitation measurement Network (OceanRAIN) as an observational along-track shipboard dataset at 1 min resolution. Second, we exploit the most recent European Reanalysis version 5 (ERA5) at hourly resolution on a 31 km grid. M

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Skrynyk, Oleg, Enric Aguilar, and Caterina Cimolai. "The Sensitivity of Heatwave Climatology to Input Gridded Datasets: A Case Study of Ukraine." Atmosphere 16, no. 3 (2025): 289. https://doi.org/10.3390/atmos16030289.

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In this research, based on a case study of Ukraine, we (1) examined the sensitivity of heatwave (HW) climatology to input gridded data and (2) statistically compared HW metrics (such as duration, intensity, etc.) calculated from the gridded data against similar results derived from high-quality station time series. For the first task, we used a mini statistical ensemble of gridded datasets of the daily maximum air temperature (TX). The ensemble included the following: ClimUAd and E-OBS (Ukrainian and European observation-based gridded data, respectively), reanalyzes ERA5, ERA5-Land, NOAA-CIRES

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Junqueira, Rubens, Marcelo R. Viola, Jhones da S. Amorim, et al. "Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin." Water 14, no. 14 (2022): 2178. http://dx.doi.org/10.3390/w14142178.

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Analyzing historical droughts is essential to improve the assessment of future hydrological risks and to understand the effects of climate variability on streamflow. However, prolonged and consistent hydrological time series are scarce in the Brazilian savanna region. This study aimed to analyze the performance of climate reanalysis products in precipitation estimation, hydrological modeling, and historical drought analysis in a Brazilian savanna basin. For this purpose, precipitation data from the twentieth-century atmospheric model ensemble (ERA-20CM) and the land component of the fifth gene

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Xu, Lei, Jinjin Du, Jiwei Ren, et al. "Improving the ERA5-Land Temperature Product through a Deep Spatiotemporal Model That Uses Fused Multi-Source Remote Sensing Data." Remote Sensing 16, no. 18 (2024): 3510. http://dx.doi.org/10.3390/rs16183510.

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Temperature is a crucial indicator for studying climate, as well as the social and economic changes in a region. Temperature reanalysis products, such as ERA5-Land, have been widely used in studying temperature change. However, global-scale temperature reanalysis products have errors because they overlook the influence of multiple factors on temperature, and this issue is more obvious in smaller areas. During the cold months (January, February, March, November, and December) in the Yellow River Basin, ERA5-Land products exhibit significant errors compared to temperatures observed by meteorolog

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Cao, Bin, Stephan Gruber, Donghai Zheng, and Xin Li. "The ERA5-Land soil temperature bias in permafrost regions." Cryosphere 14, no. 8 (2020): 2581–95. http://dx.doi.org/10.5194/tc-14-2581-2020.

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Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (

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Schönauer, Marian, Christoph Pucher, Jan Altman, Josef Weißbacher, Lars Sprengel, and Boris Rewald. "Beyond meteorological data: Modelling tree growth with ERA5-Land." Agricultural and Forest Meteorology 372 (September 2025): 110679. https://doi.org/10.1016/j.agrformet.2025.110679.

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Sebbar, Badr-eddine, Saïd Khabba, Olivier Merlin, et al. "Machine-Learning-Based Downscaling of Hourly ERA5-Land Air Temperature over Mountainous Regions." Atmosphere 14, no. 4 (2023): 610. http://dx.doi.org/10.3390/atmos14040610.

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In mountainous regions, the scarcity of air temperature (Ta) measurements is a major limitation for hydrological and crop monitoring. An alternative to in situ measurements could be to downscale the reanalysis Ta data provided at high-temporal resolution. However, the relatively coarse spatial resolution of these products (i.e., 9 km for ERA5-Land) is unlikely to be directly representative of actual local Ta patterns. To address this issue, this study presents a new spatial downscaling strategy of hourly ERA5-Land Ta data with a three-step procedure. First, the 9 km resolution ERA5 Ta is corre

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Gualtieri, Giovanni. "Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers." Energies 14, no. 14 (2021): 4169. http://dx.doi.org/10.3390/en14144169.

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The reliability of ERA5 reanalyses for directly predicting wind resources and energy production has been assessed against observations from six tall towers installed over very heterogeneous sites around the world. Scores were acceptable at the FINO3 (Germany) offshore platform for both wind speed (bias within 1%, r = 0.95−0.96) and capacity factor (CF, at worst biased by 6.70%) and at the flat and sea-level site of Cabauw (Netherlands) for both wind speed (bias within 7%, r = 0.93−0.94) and CF (bias within 6.82%). Conversely, due to the ERA5 limited resolution (~31 km), large under-predictions

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Siles, Gabriela Llanet, and Robert Leconte. "Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study." Hydrology 10, no. 5 (2023): 108. http://dx.doi.org/10.3390/hydrology10050108.

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Reservoir ice can have an important impact on the watershed scale and influence hydraulic operations. On the other hand, hydropower generation can also impact the ice regime. In this study, multi-source satellite and ERA5-land data are used to evaluate ice conditions. Specifically, ice-controlling variables (temperature, water levels), ice regime (cover/deformation, thickness) and their interrelations are assessed for a 5-year period from 2017 to 2021. The methodology is applied to the Manicouagan reservoir, one of the largest hydropower reservoirs in Quebec, Canada. The satellite-based land s

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Obeid, Zahraa, Abdulhussain Abbas, and Zuhal Hamza. "Investigation of the Best Satellite Rainfall Data in Northern Iraq." Iraqi Geological Journal 58, no. 1C (2025): 165–79. https://doi.org/10.46717/igj.58.1c.13ms-2025-3-28.

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Many watersheds lack reliable rainfall data due to limitations in ground-based meteorological stations, which is critical for accurate water resource modelling. This study evaluates the suitability of satellite precipitation data as an alternative source. Four data sources were compared: NASA-POWER, which is the Prediction of Worldwide Energy Resource dataset, ERA5-Land (European Re-analysis Land Component), which stands for ECMWF (European Centre for Medium-Range Weather Forecasts), the Climate Hazards Group Infra-Red Precipitation with Station dataset CHIRPSv.2, and Terra-Climate. The satell

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Chen, Yueli, Minghu Ding, Guo Zhang, Ying Wang, and Jianduo Li. "Evaluation of ERA5 Reanalysis Precipitation Data in the Yarlung Zangbo River Basin of the Tibetan Plateau." Journal of Hydrometeorology 24, no. 9 (2023): 1491–507. http://dx.doi.org/10.1175/jhm-d-22-0229.1.

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Abstract Atmospheric simulation-based gridded precipitation datasets have been widely used in hydrological and land surface modeling, but may contain larger uncertainties in mountainous regions. This study compared the performance of the fifth European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) precipitation data with two fused precipitation datasets [China Meteorological Administration Land Data Assimilation System version 2.0 (CLDAS2.0) and China Meteorological Forcing Dataset (CMFD)] in the Yarlung Zangbo River basin (YZRB), which has a complex terrain and climate. Compared

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Xie, Aihong, Jiangping Zhu, Xiang Qin, and Shimeng Wang. "The Antarctic Amplification Based on MODIS Land Surface Temperature and ERA5." Remote Sensing 15, no. 14 (2023): 3540. http://dx.doi.org/10.3390/rs15143540.

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With global warming accelerating, polar amplification is one of the hot issues in climate research. However, most studies focus on Arctic amplification, and little attention has been paid to Antarctic amplification (AnA), and there is no relevant research based on MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature observations. Compared with 128 stations’ observations, MODIS can capture the variations in temperature over Antarctica. In addition, the temperature changes in Antarctica, East Antarctica, West Antarctica and the Antarctic Peninsula during the period 2001

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Xu, Yanqin, Shuai Han, Chunxiang Shi, et al. "Comparative Analysis of Three Near-Surface Air Temperature Reanalysis Datasets in Inner Mongolia Region." Sustainability 15, no. 17 (2023): 13046. http://dx.doi.org/10.3390/su151713046.

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Near-surface air temperature is important for climate change, agriculture, animal husbandry, and ecosystems undergoing climate warming in Inner Mongolia. Land surface reanalysis products feature finer spatial and temporal resolutions, that can provide important data support for the determination of crop growth limits, grassland biomass growth, and desertification research in Inner Mongolia. In this study, 119 in situ observed sites were collected to compare and evaluate the performance of near-surface air temperature in three reanalysis products from 2018 to 2020 in Inner Mongolia. The three r

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Qiu, Chao, Leiding Ding, Lan Zhang, Jintao Xu, and Ziqiang Ma. "Quantitative Characteristics of the Current Multi-Source Precipitation Products over Zhejiang Province, in Summer, 2019." Water 13, no. 3 (2021): 334. http://dx.doi.org/10.3390/w13030334.

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Precipitation data with fine quality plays vital roles in hydrological-related applications. In this study, we choose the high-quality China Merged Precipitation Analysis data (CMPA) as the benchmark for evaluating four satellite-based precipitation products (PERSIANN-CCS, FY4A QPE, GSMap_Gauge, IMERG-Final) and one model-based precipitation product (ERA5-Land), respectively, at 0.1°, hourly scales over the Zhejiang province, China, in summer, from June to August 2019. The main conclusions were as follows—(1) all other products demonstrate similar patterns with CMPA (~325.60 mm/h, std ~0.07 mm

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Wang, Xiqiang, and Rensheng Chen. "Evaluation of Spatial and Temporal Variations in the Difference between Soil and Air Temperatures on the Qinghai–Tibetan Plateau Using Reanalysis Data Products." Remote Sensing 15, no. 7 (2023): 1894. http://dx.doi.org/10.3390/rs15071894.

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Many extreme meteorological events are closely related to the strength of land–atmosphere interactions. In this study, the heat exchange regime between the shallow soil layer and the atmosphere over the Qinghai–Tibetan Plateau (QTP) was investigated using a reanalysis dataset. The analysis was conducted using a simple metric ΔT, defined as the difference between the temperatures of the shallow soil and the air. First, the performance of 4 widely used reanalysis data products (GLDAS-Noah, NCEP-R2, ERA5 and ERA5-land) in estimating ΔT on the QTP at soil depths of 0~7 or 0~10 cm was evaluated dur

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Vargas-Brochero, José, Sebastián Hurtado-Castillo, Jesús Altamiranda, Frederico Carlos M. de Menezes Filho, Alexandre Beluco, and Fausto A. Canales. "Optimizing Renewable Energy Systems for Water Security: A Comparative Study of Reanalysis Models." Sustainability 16, no. 11 (2024): 4862. http://dx.doi.org/10.3390/su16114862.

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The current global scenario of unequal access to water and electricity motivates the search for solutions based on available resources, such as renewable energies and desalination. Additionally, adequate sizing of renewables requires extensive and reliable time series, which are usually unavailable. Reanalysis models are an option to consider, but only after evaluating their local accuracy, generally through performance metrics. This study evaluated the performance of the solar radiation, temperature, and wind speed products from MERRA2 and ERA5-Land in comparison to ground data, as well as th

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Zhang, Runze, Steven Chan, Rajat Bindlish, and Venkataraman Lakshmi. "Evaluation of Global Surface Water Temperature Data Sets for Use in Passive Remote Sensing of Soil Moisture." Remote Sensing 13, no. 10 (2021): 1872. http://dx.doi.org/10.3390/rs13101872.

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Inland open water bodies often pose a systematic error source in the passive remote sensing retrievals of soil moisture. Water temperature is a necessary variable used to compute water emissions that is required to be subtracted from satellite observation to yield actual emissions from the land portion, which in turn generates accurate soil moisture retrievals. Therefore, overestimation of soil moisture can often be corrected using concurrent water temperature data in the overall mitigation procedure. In recent years, several data sets of lake water temperature have become available, but their

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Huang, Xiaolong, Shuai Han, and Chunxiang Shi. "Multiscale Assessments of Three Reanalysis Temperature Data Systems over China." Agriculture 11, no. 12 (2021): 1292. http://dx.doi.org/10.3390/agriculture11121292.

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Temperature is one of the most important meteorological variables for global climate change and human sustainable development. It plays an important role in agroclimatic regionalization and crop production. To date, temperature data have come from a wide range of sources. A detailed understanding of the reliability and applicability of these data will help us to better carry out research in crop modelling, agricultural ecology and irrigation. In this study, temperature reanalysis products produced by the China Meteorological Administration Land Data Assimilation System (CLDAS), the U.S. Global

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