Articles | Volume 17, issue 3
https://doi.org/10.5194/essd-17-837-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-837-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Mar 2025
Data description paper |
| 05 Mar 2025
| 05 Mar 2025
A new high-resolution multi-drought-index dataset for mainland China
Qi Zhang
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jiajia Su
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jiaojiao Gou
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jinlong Hu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Xi Zhao
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Ye Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Related authors
Jinlong Hu, Chiyuan Miao, Jiajia Su, Qi Zhang, Jiaojiao Gou, and Qiaohong Sun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-20, https://doi.org/10.5194/essd-2025-20, 2025
Preprint under review for ESSD
Short summary
Short summary
We developed a high-precision daily precipitation dataset for mainland China called CHM_PRE V2. Using data from 3,476 rain gauges, 11 related precipitation variables and advanced machine learning methods, we created a daily precipitation dataset spanning 1960–2023 with unprecedented accuracy. Compared to existing datasets, it better captures rainfall events while reducing false alarms. This work provides a reliable tool for studying water resources, climate change, and disaster management.
Yi Wu, Chiyuan Miao, Yiying Wang, Qi Zhang, Jiachen Ji, and Yuanfang Chai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-600, https://doi.org/10.5194/essd-2024-600, 2025
Preprint under review for ESSD
Short summary
Short summary
Our study introduces BMA-ET, a novel multi-dataset fusion product. Spanning 1980 to 2020 with spatial resolution of 0.5° and 1°, BMA-ET uses Bayesian model averaging (BMA) to combine thirty ET datasets. A key innovation is its dynamic weighting scheme, which adjusts for different vegetation types and non-common coverage years among ET datasets. BMA-ET provides a comprehensive resource for understanding global ET patterns and trends, addressing the limitation of prior ET fusion efforts.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
Short summary
Short summary
Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Jinlong Hu, Chiyuan Miao, Jiajia Su, Qi Zhang, Jiaojiao Gou, and Qiaohong Sun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-20, https://doi.org/10.5194/essd-2025-20, 2025
Preprint under review for ESSD
Short summary
Short summary
We developed a high-precision daily precipitation dataset for mainland China called CHM_PRE V2. Using data from 3,476 rain gauges, 11 related precipitation variables and advanced machine learning methods, we created a daily precipitation dataset spanning 1960–2023 with unprecedented accuracy. Compared to existing datasets, it better captures rainfall events while reducing false alarms. This work provides a reliable tool for studying water resources, climate change, and disaster management.
Yi Wu, Chiyuan Miao, Yiying Wang, Qi Zhang, Jiachen Ji, and Yuanfang Chai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-600, https://doi.org/10.5194/essd-2024-600, 2025
Preprint under review for ESSD
Short summary
Short summary
Our study introduces BMA-ET, a novel multi-dataset fusion product. Spanning 1980 to 2020 with spatial resolution of 0.5° and 1°, BMA-ET uses Bayesian model averaging (BMA) to combine thirty ET datasets. A key innovation is its dynamic weighting scheme, which adjusts for different vegetation types and non-common coverage years among ET datasets. BMA-ET provides a comprehensive resource for understanding global ET patterns and trends, addressing the limitation of prior ET fusion efforts.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
Short summary
Short summary
Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492, https://doi.org/10.5194/hess-27-1477-2023, https://doi.org/10.5194/hess-27-1477-2023, 2023
Short summary
Short summary
The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable infiltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Liren Wei, Duoying Ji, Chiyuan Miao, Helene Muri, and John C. Moore
Atmos. Chem. Phys., 18, 16033–16050, https://doi.org/10.5194/acp-18-16033-2018, https://doi.org/10.5194/acp-18-16033-2018, 2018
Short summary
Short summary
We analyzed streamflow and flood frequency under the stratospheric aerosol geoengineering scenario simulated by climate models. Stratospheric aerosol geoengineering appears to reduce flood risk in most regions, but the overall effects are largely determined by the large-scale geographic pattern. Over the Amazon, stratospheric aerosol geoengineering ameliorates the drying trend here under a future warming climate.
W. Gong, Q. Duan, J. Li, C. Wang, Z. Di, Y. Dai, A. Ye, and C. Miao
Hydrol. Earth Syst. Sci., 19, 2409–2425, https://doi.org/10.5194/hess-19-2409-2015, https://doi.org/10.5194/hess-19-2409-2015, 2015
J. Li, Q. Y. Duan, W. Gong, A. Ye, Y. Dai, C. Miao, Z. Di, C. Tong, and Y. Sun
Hydrol. Earth Syst. Sci., 17, 3279–3293, https://doi.org/10.5194/hess-17-3279-2013, https://doi.org/10.5194/hess-17-3279-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Meteorology
HighResClimNevada: a high-resolution climatological dataset for a high-altitude region in Southern Spain (Sierra Nevada)
The PAZ polarimetric radio occultation research dataset for scientific applications
Water vapor Raman lidar observations from multiple sites in the framework of WaLiNeAs
SARAH-3 – satellite-based climate data records of surface solar radiation
An Updated Reconstruction of Antarctic Near-Surface Air Temperatures at Monthly Intervals Since 1958
Homogenized daily sunshine duration over China from 1961 to 2022
Estimation of Long-term Gridded Cloud Radiative Kernel and Radiative Effects Based on Cloud Fraction
The SAIL dataset of marine atmospheric electric field observations over the Atlantic Ocean
A database of deep convective systems derived from the intercalibrated meteorological geostationary satellite fleet and the TOOCAN algorithm (2012–2020)
Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data
Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)
Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau
MDG625: A daily high-resolution meteorological dataset derived by geopotential-guided attention network in Asia (1940–2023)
Multifrequency radar observations of marine clouds during the EPCAPE campaign
Data collected using small uncrewed aircraft systems during the TRacking Aerosol Convection interactions ExpeRiment (TRACER)
LGHAP v2: a global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big Earth data analytics
Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River Watershed during SPLASH, 2021–2023
Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain
Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg
The 2023 National Offshore Wind data set (NOW-23)
Dataset of stable isotopes of precipitation in the Eurasian continent
A 7-year record of vertical profiles of radar measurements and precipitation estimates at Dumont d'Urville, Adélie Land, East Antarctica
Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)
Year-long buoy-based observations of the air–sea transition zone off the US west coast
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: a comprehensive long-term dataset of remote sensing observations
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output
Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Derivation and compilation of lower-atmospheric properties relating to temperature, wind, stability, moisture, and surface radiation budget over the central Arctic sea ice during MOSAiC
CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
An integrated and homogenized global surface solar radiation dataset and its reconstruction based on a convolutional neural network approach
IWIN: the Isfjorden Weather Information Network
A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations
A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range
The EUPPBench postprocessing benchmark dataset v1.0
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Database of the Italian disdrometer network
East Asia Reanalysis System (EARS)
Data rescue of historical wind observations in Sweden since the 1920s
LegacyClimate 1.0: a dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the last 30 kyr and beyond
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Combined wind lidar and cloud radar for high-resolution wind profiling
An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020
TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations
The AntAWS dataset: a compilation of Antarctic automatic weather station observations
HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020
Matilde García-Valdecasas Ojeda, Feliciano Solano-Farias, David Donaire-Montaño, Emilio Romero-Jiménez, Juan José Rosa-Cánovas, Yolanda Castro-Díez, Sonia Raquel Gámiz-Fortis, and María Jesús Esteban-Parra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-522, https://doi.org/10.5194/essd-2024-522, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This work aims to present a series of climate datasets for Sierra Nevada, a region especially vulnerable to climate change in Southern Spain. The database consists of primary climate variables such as precipitation, temperature, radiation, wind speed, pressure, and atmospheric humidity, but also bioclimatic variables and extreme indices, both useful information for assessing the impact of climate change in this region. These datasets are only available on https://doi.org/10.5281/zenodo.14364865
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
Short summary
Short summary
This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
Short summary
Short summary
We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
Short summary
Short summary
The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
David Bromwich, Sheng-Hung Wang, Xun Zou, and Alexandra Ensign
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-353, https://doi.org/10.5194/essd-2024-353, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Antarctica is a major player in Earth’s climate with the most direct influence arising from its potential to raise global sea level by a meter or more in the coming decades. Near-surface air temperature is the primary variable used to monitor the climate of this remote but important region. Continent-wide direct but sparse measurements that started around 1958 are used to construct a monthly air temperature data set for all of Antarctica spanning 1958–2022.
Yanyi He, Kaicun Wang, Kun Yang, Chunlüe Zhou, Changkun Shao, and Changjian Yin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-493, https://doi.org/10.5194/essd-2024-493, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
To address key gaps in data availability and homogeneity of sunshine duration, we compiled raw data and made a homogenization protocol to produce a homogenized daily observational dataset of sunshine duration from 1961 to 2022 in China. The dataset avoids a sharp drop in zero-value frequency after 2019, caused by the instrument upgrade, but also is more continuous for various periods. This dataset is crucial for accurately assessing the dimming and brightening, and supporting other applications.
Xinyan Liu, Tao He, Qingxin Wang, Xiongxin Xiao, Yichuan Ma, Yanyan Wang, Shanjun Luo, Lei Du, and Zhaocong Wu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-458, https://doi.org/10.5194/essd-2024-458, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This study addresses the challenge of how clouds affect the Earth's energy balance, which is vital for understanding climate change. We developed a new method to create long-term cloud radiative kernels to improve the accuracy of sunlight reaching the surface, which significantly reduces errors. Findings suggest that prior estimates of cloud cooling effects may have been overstated, emphasizing the need for better strategies to manage climate change impacts in the Arctic.
Susana Barbosa, Nuno Dias, Carlos Almeida, Guilherme Amaral, António Ferreira, António Camilo, and Eduardo Silva
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-245, https://doi.org/10.5194/essd-2024-245, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The electric field present in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (thunderstorms, pollution, aerosols) and space weather. Marine measurements of the electric field are rare. Here, a unique dataset of atmospheric electric field measurements performed over the Atlantic Ocean is presented. This dataset is relevant not only for atmospheric electricity studies but also for climate and space-Earth interaction studies.
Thomas Fiolleau and Rémy Roca
Earth Syst. Sci. Data, 16, 4021–4050, https://doi.org/10.5194/essd-16-4021-2024, https://doi.org/10.5194/essd-16-4021-2024, 2024
Short summary
Short summary
This paper presents a database of tropical deep convective systems over the 2012–2020 period, built from a cloud-tracking algorithm called TOOCAN, which has been applied to homogenized infrared observations from a fleet of geostationary satellites. This database aims to analyze the tropical deep convective systems, the evolution of their associated characteristics over their life cycle, their organization, and their importance in the hydrological and energy cycle.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
Short summary
Short summary
This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
Short summary
Short summary
Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Zijiang Song, Zhixiang Cheng, Yuying Li, Shanshan Yu, Xiaowen Zhang, Lina Yuan, and Min Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-137, https://doi.org/10.5194/essd-2024-137, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
It is hard to access long-time series and high-resolution meteorological data for historical years. In this paper, we proposed a geopotential-guide attention network (GeoAN) for downscaling, which can produce high-resolution data from the given low-resolution data. Quantitative and visual comparisons reveal our GeoAN producing better results in most metrics. Using GeoAN, historical meteorological data called MDG625 has been produced daily since 1940.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
Short summary
Short summary
This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
Short summary
Short summary
This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
Short summary
Short summary
A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Christopher J. Cox, Janet M. Intrieri, Brian Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-158, https://doi.org/10.5194/essd-2024-158, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Snow is an essential water resource in the intermountain western United States and predictions are made using models. We made observations to validate, constrain, and develop the models. The data is from the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in Colorado’s East River Valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
Short summary
Short summary
Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
Short summary
Short summary
This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
Short summary
Short summary
We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
Short summary
Short summary
This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
Short summary
Short summary
Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
Short summary
Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
Short summary
Short summary
The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
Short summary
Short summary
Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
Short summary
Short summary
We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
Short summary
Short summary
CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
Short summary
Short summary
We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
Short summary
Short summary
We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
Short summary
Short summary
Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
Short summary
Short summary
This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
Short summary
Short summary
This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
Short summary
Short summary
The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
Short summary
Short summary
Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
Short summary
Short summary
This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
Short summary
Short summary
A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
Short summary
Short summary
We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
Short summary
Short summary
The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
Short summary
Short summary
A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
Short summary
Short summary
Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
Short summary
Short summary
Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
Short summary
Short summary
EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
Short summary
Short summary
This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
Short summary
Short summary
This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
Short summary
Short summary
We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
Short summary
Short summary
Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
Short summary
Short summary
Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
Short summary
Short summary
We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Cited articles
Aadhar, S. and Mishra, V.: Increased drought risk in south asia under warming climate: Implications of uncertainty in potential evapotranspiration estimates, J. Hydrometeorol., 21, 2979–2996, https://doi.org/10.1175/JHM-D-19-0224.1, 2020.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration – Guidelines for computing crop water requirements (FAO Irrigation and drainage, paper 56), Food and Agriculture Organizatoin of the United Nations, Rome, 17–28, https://www.fao.org/3/X0490E/X0490E00.htm (last access: 17 October 2024), 1998.
Allen, R. G., Walter, I. A., Elliott, R., Howell, T., Itenfisu, D., and Jensen M.: The ASCE standardized reference evapotranspiration equation, Rep. 0-7844-0805-X, 59 pp., https://ascelibrary.org/doi/epdf/10.1061/9780784408056.fm (last access: 5 February 2025), 2005.
Bai, X., Shen, W., Wu, X., and Wang, P.: Applicability of long-term satellite-based precipitation products for drought indices considering global warming, J. Environ. Manage., 255, 109846, https://doi.org/10.1016/j.jenvman.2019.109846, 2020.
Beguería, S., Vicente-Serrano, S. M., and Angulo-Martínez, M.: A multiscalar global drought dataset: The SPEI base: A new gridded product for the analysis of drought variability and impacts, B. Am. Meteorol. Soc., 91, 1351–1354, https://doi.org/10.1175/2010BAMS2988.1, 2010.
Cheng, Y., Liu, L., Cheng, L., Fa, K., Liu, X., Huo, Z., and Huang, G.: A shift in the dominant role of atmospheric vapor pressure deficit and soil moisture on vegetation greening in China, J. Hydrol., 615, 128680, https://doi.org/10.1016/j.jhydrol.2022.128680, 2022.
Dai, A.: Drought under global warming: a review, WIREs Clim. Change, 2, 45–65, https://doi.org/10.1002/wcc.81, 2011.
Dai, A., Kevin, E. T., and Taotao, Q.: A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming, J. Hydrometeorol., 5, 1117–1130, https://doi.org/10.1175/JHM-386.1, 2004.
Dobson, B., Coxon, G., Freer, J., Gavin, H., Mortazavi-Naeini, M., and Hall, J. W.: The Spatial Dynamics of Droughts and Water Scarcity in England and Wales, Water Resour. Res., 56, e2020WR027187, https://doi.org/10.1029/2020WR027187, 2020.
Dracup, J. A., Lee, K. S., and Paulson, E. G.: On the statistical characteristics of drought events, Water Resour. Res., 16, 289–296, https://doi.org/10.1029/WR016i002p00289, 1980.
Gamelin, B. L., Feinstein, J., Wang, J., Bessac, J., Yan, E., and Kotamarthi, V. R.: Projected U. S. drought extremes through the twenty-first century with vapor pressure deficit, Sci. Rep., 12, 8615, https://doi.org/10.1038/s41598-022-12516-7, 2022.
Gampe, D., Zscheischler, J., Reichstein, M., O'Sullivan, M., Smith, W. K., Sitch, S., and Buermann, W.: Increasing impact of warm droughts on northern ecosystem productivity over recent decades, Nat. Clim. Change, 11, 772–779, https://doi.org/10.1038/s41558-021-01112-8, 2021.
GNDAR: Global Natural Disaster Assessment Report 2020, UN Annu. Rep., 1–80, https://www.gddat.cn/WorldInfoSystem/production/BNU/2020-EN.pdf (last access: 5 February 2025) 2021.
Green, R. M. and Hay, S. I.: The potential of Pathfinder AVHRR data for providing surrogate climatic variables across Africa and Europe for epidemiological applications, Remote Sens. Environ., 79, 166–175, https://doi.org/10.1016/S0034-4257(01)00270-X, 2002.
Han, J., Miao, C., Gou, J., Zheng, H., Zhang, Q., and Guo, X.: A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations, Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, 2023.
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset, Sci. Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3, 2020.
Hashimoto, H., Dungan, J. L., White, M. A., Yang, F., Michaelis, A. R., Running, S. W., and Nemani, R. R.: Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data, Remote Sens. Environ., 112, 142–155, https://doi.org/10.1016/j.rse.2007.04.016, 2008.
He, J., Yang, K., Tang, W., Lu, H., Qin, J., Chen, Y., and Li, X.: The first high-resolution meteorological forcing dataset for land process studies over China, Sci. Data, 7, 25, https://doi.org/10.1038/s41597-020-0369-y, 2020.
Heim, R. R.: A Review of Twentieth-Century Drought Indices Used in the United States, B. Am. Meteorol. Soc., 83, 1149–1166, https://doi.org/10.1175/1520-0477-83.8.1149, 2002.
Hobbins, M. T., Wood, A., McEvoy, D. J., Huntington, J. L., Morton, C., Anderson, M., and Hain, C.: The evaporative demand drought index. Part I: Linking drought evolution to variations in evaporative demand, J. Hydrometeorol., 17, 1745–1761, https://doi.org/10.1175/JHM-D-15-0121.1, 2016.
Huang, S., Huang, Q., Leng, G., and Liu, S.: A nonparametric multivariate standardized drought index for characterizing socioeconomic drought: A case study in the Heihe River Basin, J. Hydrol., 542, 875–883, https://doi.org/10.1016/j.jhydrol.2016.09.059, 2016.
Jin, X., Qiang, H., Zhao, L., Jiang, S., Cui, N., Cao, Y., and Feng, Y.: SPEI-based analysis of spatio-temporal variation characteristics for annual and seasonal drought in the Zoige Wetland, Southwest China from 1961 to 2016, Theor. Appl. Climatol., 139, 711–725, https://doi.org/10.1007/s00704-019-02981-y, 2020.
Lesk, C., Coffel, E., Winter, J., Ray, D., Zscheischler, J., Seneviratne, S. I., and Horton, R.: Stronger temperature–moisture couplings exacerbate the impact of climate warming on global crop yields, Nat. Food, 2, 683–691, https://doi.org/10.1038/s43016-021-00341-6, 2021.
Li, C., Fu, B., Wang, S., Stringer, L. C., Wang, Y., Li, Z., Liu, Y., and Zhou, W.: Drivers and impacts of changes in China's drylands, Nature Reviews Earth & Environment, 2, 858–873, https://doi.org/10.1038/s43017-021-00226-z, 2021.
Li, L., She, D., Zheng, H., Lin, P., and Yang, Z.-L.: Elucidating Diverse Drought Characteristics from Two Meteorological Drought Indices (SPI and SPEI) in China, J. Hydrometeorol., 21, 1513–1530, https://doi.org/10.1175/jhm-d-19-0290.1, 2020.
Li, S., Wang, G., Chai, Y., Miao, L., Fiifi Tawia Hagan, D., Sun, S., Huang, J., Su, B., Jiang, T., Chen, T., Lu, C., and Guan, Z.: Increasing vapor pressure deficit accelerates land drying, J. Hydrol., 625, 130062, https://doi.org/10.1016/j.jhydrol.2023.130062, 2023.
Li, T., He, B., Chen, D., Chen, H. W., Guo, L., Yuan, W., Fang, K., Shi, F., Liu, L., and Zheng, H.: Increasing sensitivity of tree radial growth to precipitation, Geophys. Res. Lett., 51, e2024GL110003, https://doi.org/10.1029/2024GL110003, 2024.
Liu, J., Chen, H., Yang, S., Wang, W., Xiang, Y., and Zhao, C.: Comparison of interpolation methods on annual mean precipitation in Hebei Province, Acta Ecologica Sinica, 29, 3493–3500, 2009 (in Chinese).
Liu, X., Yu, S., Yang, Z., Dong, J., and Peng, J.: The first global multi-timescale daily SPEI dataset from 1982 to 2021, Sci. Data, 11, 223, https://doi.org/10.1038/s41597-024-03047-z, 2024.
Lyu, Z. Z., Gao, H., Gao, R., and Ding, T.: Extreme characteristics and causes of the drought event in the whole Yangtze River Basin in the midsummer of 2022, Advances in Climate Change Research, 14, 642–650, https://doi.org/10.1016/j.accre.2023.09.007, 2023.
Ma, F. and Yuan, X.: When Will the Unprecedented 2022 Summer Heat Waves in Yangtze River Basin Become Normal in a Warming Climate?, Geophys. Res. Lett., 50, e2022GL101946, https://doi.org/10.1029/2022GL101946, 2023.
McKee, T. B., Doesken, N. J., and Kliest, J.: The relationship of drought frequency and duration to time scales, in: Proceedings of the 8th Conference of Applied Climatology, 17–22 January, Anaheim, CA, American Meteorological Society, Boston, MA, 179–184, https://www.droughtmanagement.info/literature/AMS_Relationship_Drought_Frequency_Duration_Time_Scales_1993.pdf (last access: 28 November 2023), 1993.
Miao, C., Immerzeel, W. W., Xu, B., Yang, K., Duan, Q., and Li, X.: Understanding the Asian water tower requires a redesigned precipitation observation strategy, P. Natl. Acad. Sci. USA, 121, e2403557121, https://doi.org/10.1073/pnas.2403557121, 2024.
Mishra, A. K. and Singh, V. P.: A review of drought concepts, J. Hydrol., 391, 202–216, https://doi.org/10.1016/j.jhydrol.2010.07.012, 2010.
Naumann, G., Cammalleri, C., Mentaschi, L., and Feyen, L.: Increased economic drought impacts in Europe with anthropogenic warming, Nat. Clim. Change, 11, 485–491, https://doi.org/10.1038/s41558-021-01044-3, 2021.
Noguera, I., Vicente-Serrano, S. M., Domínguez-Castro, F., and Reig, F.: Assessment of parametric approaches to calculate the Evaporative Demand Drought Index, Int. J. Climatol., 42, 834–849, https://doi.org/10.1002/joc.7275, 2022.
Palmer, W. C.: Meteorological Drought. Office of Climatology Research Paper No. 45, Washington DC: US Weather Bureau, https://www.droughtmanagement.info/literature/USWB_Meteorological_Drought_1965.pdf (last access: 28 November 2023), 1965.
Pyarali, K., Peng, J., Disse, M., and Tuo, Y.: Development and application of high resolution SPEI drought dataset for Central Asia, Sci. Data, 9, 172, https://doi.org/10.1038/s41597-022-01279-5, 2022.
Sadiqi, S. S. J., Hong, E. M., Nam, W. H., and Kim, T.: Review: An integrated framework for understanding ecological drought and drought resistance, Sci. Total Environ., 846, 157477, https://doi.org/10.1016/j.scitotenv.2022.157477, 2022.
Shao, D., Chen, S., Tan, X., and Gu, W.: Drought characteristics over China during 1980–2015, Int. J. Climatol., 38, 3532–3545, https://doi.org/10.1002/joc.5515, 2018.
Shen, F., Xu, C., and Hu, M.: Comparison of approaches to spatiotemporally interpolate land surface air temperature for the Qinghai–Tibet Plateau, Environ. Earth Sci., 82, 452, https://doi.org/10.1007/s12665-023-11151-3, 2023.
Shi, H., Chen, J., Wang, K., and Niu, J.: A new method and a new index for identifying socioeconomic drought events under climate change: A case study of the East River basin in China, Sci. Total Environ., 616–617, 363–375, https://doi.org/10.1016/j.scitotenv.2017.10.321, 2018.
Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., Quichimbo, E. A., and Michaelides, K.: Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981–present, Sci. Data, 8, 224, https://doi.org/10.1038/s41597-021-01003-9, 2021.
Su, B., Huang, J., Fischer, T., Wang, Y., Kundzewicz, Z. W., Zhai, J., Sun, H., Wang, A., Zeng, X., Wang, G., Tao, H., Gemmer, M., Li, X., and Jiang, T.: Drought losses in China might double between the 1.5 °C and 2.0 °C warming, P. Natl. Acad. Sci. USA, 115, 10600–10605, https://doi.org/10.1073/pnas.1802129115, 2018.
Svoboda, M. D. and Fuchs, B. A.: Handbook of drought indicators and indices, in: Drought and Water Crises: Integrating Science, Management, and Policy, 2nd edn., World Meteorological Organization Geneva, Switzerland 2016, ISBN 978-92-63-11173-9, https://doi.org/10.1201/b22009, 2017.
Tu, Y., Wang, X., Zhou, J., Wang, X., Jia, Z., Ma, J., Yao, W., Zhang, X., Sun, Z., Luo, P., Feng, X., and Fu, B.: Atmospheric water demand dominates terrestrial ecosystem productivity in China, Agr. Forest Meteorol., 355, 110151, https://doi.org/10.1016/J.AGRFORMET.2024.110151, 2024.
Venkatappa, M. and Sasaki, N.: Datasets of drought and flood impact on croplands in Southeast Asia from 1980 to 2019, Data Brief, 38, 107406, https://doi.org/10.1016/j.dib.2021.107406, 2021.
Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J. I.: A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index, J. Climate, 23, 1696–1718, https://doi.org/10.1175/2009JCLI2909.1, 2010a.
Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I., Angulo, M., and El Kenawy, A.: A new global 0.5° gridded dataset (1901–2006) of a multiscalar drought index: Comparison with current drought index datasets based on the palmer drought severity index, J. Hydrometeorol., 11, 1033–1043, https://doi.org/10.1175/2010JHM1224.1, 2010b.
Vicente-Serrano, S. M., Domínguez-Castro, F., Reig, F., Tomas-Burguera, M., Peña-Angulo, D., Latorre, B., Beguería, S., Rabanaque, I., Noguera, I., Lorenzo-Lacruz, J., and El Kenawy, A.: A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop-growing regions, Geosci. Data J., 10, 505–518, https://doi.org/10.1002/gdj3.178, 2023.
Wang, J., Zhang, Q., Zhang, L., Wang, Y., Yue, P., Hu, Y., and Ye, P.: The Global Pattern and Development Trends and Directions on the Drought Monitoring Research from 1983 to 2020 by Using Bibliometric Analysis, B. Am. Meteorol. Soc., 103, E2081–E2107, https://doi.org/10.1175/BAMS-D-21-0324.1, 2022.
Wang, J., Yan, R., Wu, G., Liu, Y., Wang, M., Zeng, N., Jiang, F., Wang, H., He, W., Wu, M., Ju, W., and Chen, J. M.: Unprecedented decline in photosynthesis caused by summer 2022 record-breaking compound drought-heatwave over Yangtze River Basin, Sci. Bull. (Beijing), 68, 2160–2163, https://doi.org/10.1016/j.scib.2023.08.011, 2023.
Wang, K. C. and Dickinson, R. E.: A review on global terrestrial evapotranspiration: observation, modeling, climatology, and Climatic Variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011RG000373, 2012.
Wang, Q., Zeng, J., Qi, J., Zhang, X., Zeng, Y., Shui, W., Xu, Z., Zhang, R., Wu, X., and Cong, J.: A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018, Earth Syst. Sci. Data, 13, 331–341, https://doi.org/10.5194/essd-13-331-2021, 2021.
Wells, N., Goddard, S., and Hayes, M. J.: A self-calibrating Palmer Drought Severity Index, J. Climate, 17, 2335–2351, https://doi.org/10.1175/1520-0442(2004)017<2335:ASPDSI>2.0.CO;2, 2004.
WMO: Guide to Meteorological Instruments and Methods of Observation, 8, World Meteorological Organization, http://library.wmo.int/pmb_ged/wmo_8_en-2012.pdf (last access: 1 November 2013), 2012.
Wu, J. and Gao, X. J.: A gridded daily observation dataset over China region and comparison with the other datasets, Acta Geophys. Sinica, 56, 1102–1111, https://doi.org/10.6038/cjg20130406, 2013.
Xiang, K., Li, Y., Horton, R., and Feng, H.: Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review, Agr. Water Manage., 232, 106043, https://doi.org/10.1016/j.agwat.2020.106043, 2020.
Xu, X., X. Zhang, and X. Li.: Evaluation of the Applicability of Three Methods for Climatic Spatial Interpolation in the Hengduan Mountains Region, J. Hydrometeorol., 24, 35–51, https://doi.org/10.1175/JHM-D-22-0039.1, 2022.
Xu, Y., Gao, X., Shen, Y., Xu, C., Shi, Y., and Giorgi, F.: A daily temperature dataset over China and its application in validating a RCM simulation, Adv. Atmos. Sci., 26, 763–772, https://doi.org/10.1007/s00376-009-9029-z, 2009.
Yuan, W., Zheng, Y., Piao, S., Ciais, P., Lombardozzi, D., Wang, Y., Ryu, Y., Chen, G., Dong, W., Hu, Z., Jain, A. K., Jiang, C., Kato, E., Li, S., Lienert, S., Liu, S., Nabel, J. E. M. S., Qin, Z., Quine, T., Sitch, S., Smith, W. K., Wang, F., Wu, C., Xiao, Z., and Yang, S.: Increased atmospheric vapor pressure deficit reduces global vegetation growth, Sci. Adv., 5, eaax1396, https://doi.org/10.1126/sciadv.aax1396, 2019.
Zhai, J., Su, B., Krysanova, V., Vetter, T., Gao, C., and Jiang, T.: Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of china, J. Climate, 23, 649–663, https://doi.org/10.1175/2009JCLI2968.1, 2010.
Zhang, L., Guo, G., Xiong, K., Qin, P., and Wu, Y.: Causes of the high temperature process in the Yangtze River Basin in 2022, Progress in Geography, 42, 971–981, https://doi.org/10.18306/dlkxjz.2023.05.011, 2023a.
Zhang, Q. and Miao, C.: CHM_Drought, Zenodo [data set], https://doi.org/10.5281/zenodo.14634773, 2025.
Zhang, Q., Miao, C., Gou, J., Wu, J., Jiao, W., Song, Y., and Xu, D.: Spatiotemporal characteristics of meteorological to hydrological drought propagation under natural conditions in China, Weather Clim. Extrem., 38, 100505, https://doi.org/10.1016/j.wace.2022.100505, 2022a.
Zhang, R., Bento, V. A., Qi, J., Xu, F., Wu, J., Qiu, J., Li, J., Shui, W., and Wang, Q.: The first high spatial resolution multi-scale daily SPI and SPEI raster dataset for drought monitoring and evaluating over China from 1979 to 2018, Big Earth Data, 7, 860–885, https://doi.org/10.1080/20964471.2022.2148331, 2023b.
Zhang, X., Su, Z., Lv, J., Liu, W., Ma, M., Peng, J., and Leng, G.: A set of satellite-based near real-time meteorological drought monitoring data over China, Remote Sens., 11, 453, https://doi.org/10.3390/rs11040453, 2019.
Zhang, X., Hao, Z., Singh, V. P., Zhang, Y., Feng, S., Xu, Y., and Hao, F.: Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors, Sci. Total Environ., 838, 156021, https://doi.org/10.1016/j.scitotenv.2022.156021, 2022b.
Zhao, H., Gao, G., An, W., Zou, X., Li, H., and Hou, M.: Timescale differences between SC-PDSI and SPEI for drought monitoring in China, Phys. Chem. Earth, 102, 48–58, https://doi.org/10.1016/j.pce.2015.10.022, 2017a.
Zhao, M., Geruo, A., Velicogna, I., and Kimball, J. S.: A global gridded dataset of GRACE drought severity index for 2002-14: Comparison with PDSI and SPEI and a case study of the Australia millennium drought, J. Hydrometeorol., 18, 2117–2129, https://doi.org/10.1175/JHM-D-16-0182.1, 2017b.
Zhong, R., Chen, X., Lai, C., Wang, Z., Lian, Y., Yu, H., and Wu, X.: Drought monitoring utility of satellite-based precipitation products across mainland China, J. Hydrol., 568, 343–359, https://doi.org/10.1016/j.jhydrol.2018.10.072, 2019.
Short summary
Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland...
Altmetrics
Final-revised paper
Preprint