Articles | Volume 11, issue 4
https://doi.org/10.5194/essd-11-1531-2019
© Author(s) 2019. 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-11-1531-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
seNorge_2018, daily precipitation, and temperature datasets over Norway
Norwegian Meteorological Institute, Oslo, Norway
Ole Einar Tveito
Norwegian Meteorological Institute, Oslo, Norway
Andreas Dobler
Norwegian Meteorological Institute, Oslo, Norway
Ketil Tunheim
Norwegian Meteorological Institute, Oslo, Norway
Related authors
Cristian Lussana, Emma Baietti, Line Båserud, Thomas Nils Nipen, and Ivar Ambjørn Seierstad
Adv. Sci. Res., 20, 35–48, https://doi.org/10.5194/asr-20-35-2023, https://doi.org/10.5194/asr-20-35-2023, 2023
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We have compared hourly precipitation totals measured by rain gauges installed and maintained by citizens against professional weather stations managed by the national weather services of Finland, Norway and Sweden. The manufacturer of the citizen rain gauges is Netatmo. Despite the heterogeneity of citizens' measurements, our results show that the two data sources are comparable with each other, though with some limitations. The results also show how to improve the accuracy of citizens' data.
Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, and Christoffer A. Elo
Nonlin. Processes Geophys., 28, 61–91, https://doi.org/10.5194/npg-28-61-2021, https://doi.org/10.5194/npg-28-61-2021, 2021
Short summary
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An unprecedented amount of rainfall data is available nowadays, such as ensemble model output, weather radar estimates, and in situ observations from networks of both traditional and opportunistic sensors. Nevertheless, the exact amount of precipitation, to some extent, eludes our knowledge. The objective of our study is precipitation reconstruction through the combination of numerical model outputs with observations from multiple data sources.
Line Båserud, Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, Louise Oram, and Trygve Aspelien
Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, https://doi.org/10.5194/asr-17-153-2020, 2020
Short summary
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We present the open source project Titan for automatic quality control of meteorological in-situ observations. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations.
Titan serves real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. Further developments include transforming Titan into a more flexible library of functions.
Cristian Lussana, Tuomo Saloranta, Thomas Skaugen, Jan Magnusson, Ole Einar Tveito, and Jess Andersen
Earth Syst. Sci. Data, 10, 235–249, https://doi.org/10.5194/essd-10-235-2018, https://doi.org/10.5194/essd-10-235-2018, 2018
Short summary
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The observational gridded climate datasets are among the primary sources of information for climate analysis and monitoring. The seNorge2 high-resolution dataset of daily total precipitation (1957–2017) constitutes a valuable meteorological input for snow and hydrological simulations which are routinely conducted over Norway for research and to support operational applications for civil protection purposes. The dataset and the seNorge2 software are publicly available for download.
F. Uboldi, A. N. Sulis, C. Lussana, M. Cislaghi, and M. Russo
Hydrol. Earth Syst. Sci., 18, 981–995, https://doi.org/10.5194/hess-18-981-2014, https://doi.org/10.5194/hess-18-981-2014, 2014
C. Lussana
Adv. Sci. Res., 10, 59–64, https://doi.org/10.5194/asr-10-59-2013, https://doi.org/10.5194/asr-10-59-2013, 2013
Cristian Lussana, Emma Baietti, Line Båserud, Thomas Nils Nipen, and Ivar Ambjørn Seierstad
Adv. Sci. Res., 20, 35–48, https://doi.org/10.5194/asr-20-35-2023, https://doi.org/10.5194/asr-20-35-2023, 2023
Short summary
Short summary
We have compared hourly precipitation totals measured by rain gauges installed and maintained by citizens against professional weather stations managed by the national weather services of Finland, Norway and Sweden. The manufacturer of the citizen rain gauges is Netatmo. Despite the heterogeneity of citizens' measurements, our results show that the two data sources are comparable with each other, though with some limitations. The results also show how to improve the accuracy of citizens' data.
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
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A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Elinah Khasandi Kuya, Herdis Motrøen Gjelten, and Ole Einar Tveito
Adv. Sci. Res., 19, 73–80, https://doi.org/10.5194/asr-19-73-2022, https://doi.org/10.5194/asr-19-73-2022, 2022
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Climate normals are used as reference for climate monitoring. When calculating precipitation normals for the period 1991–2020 a homogeneous reference dataset is needed. Norway's observation network has changed drastically in the last 30 years and may have introduced non-climatic changes to the time series. Homogeneity analysis of monthly precipitation series for the period 1961–2018 was performed which produced a homogenous dataset that was used to calculate the new climate normals in Norway.
Erika Médus, Emma D. Thomassen, Danijel Belušić, Petter Lind, Peter Berg, Jens H. Christensen, Ole B. Christensen, Andreas Dobler, Erik Kjellström, Jonas Olsson, and Wei Yang
Nat. Hazards Earth Syst. Sci., 22, 693–711, https://doi.org/10.5194/nhess-22-693-2022, https://doi.org/10.5194/nhess-22-693-2022, 2022
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We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.
Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, and Christoffer A. Elo
Nonlin. Processes Geophys., 28, 61–91, https://doi.org/10.5194/npg-28-61-2021, https://doi.org/10.5194/npg-28-61-2021, 2021
Short summary
Short summary
An unprecedented amount of rainfall data is available nowadays, such as ensemble model output, weather radar estimates, and in situ observations from networks of both traditional and opportunistic sensors. Nevertheless, the exact amount of precipitation, to some extent, eludes our knowledge. The objective of our study is precipitation reconstruction through the combination of numerical model outputs with observations from multiple data sources.
Line Båserud, Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, Louise Oram, and Trygve Aspelien
Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, https://doi.org/10.5194/asr-17-153-2020, 2020
Short summary
Short summary
We present the open source project Titan for automatic quality control of meteorological in-situ observations. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations.
Titan serves real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. Further developments include transforming Titan into a more flexible library of functions.
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Stefan Liersch, Julia Tecklenburg, Henning Rust, Andreas Dobler, Madlen Fischer, Tim Kruschke, Hagen Koch, and Fred Fokko Hattermann
Hydrol. Earth Syst. Sci., 22, 2163–2185, https://doi.org/10.5194/hess-22-2163-2018, https://doi.org/10.5194/hess-22-2163-2018, 2018
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Application-oriented regional impact studies require accurate simulations of future climate variables and water availability. We analyse the quality of global and regional climate projections and discuss potentials of correction methods that partly overcome this quality issue. The model ensemble used in this study projects increasing average annual discharges and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.
Cristian Lussana, Tuomo Saloranta, Thomas Skaugen, Jan Magnusson, Ole Einar Tveito, and Jess Andersen
Earth Syst. Sci. Data, 10, 235–249, https://doi.org/10.5194/essd-10-235-2018, https://doi.org/10.5194/essd-10-235-2018, 2018
Short summary
Short summary
The observational gridded climate datasets are among the primary sources of information for climate analysis and monitoring. The seNorge2 high-resolution dataset of daily total precipitation (1957–2017) constitutes a valuable meteorological input for snow and hydrological simulations which are routinely conducted over Norway for research and to support operational applications for civil protection purposes. The dataset and the seNorge2 software are publicly available for download.
Abdelkader Mezghani, Andreas Dobler, Jan Erik Haugen, Rasmus E. Benestad, Kajsa M. Parding, Mikołaj Piniewski, Ignacy Kardel, and Zbigniew W. Kundzewicz
Earth Syst. Sci. Data, 9, 905–925, https://doi.org/10.5194/essd-9-905-2017, https://doi.org/10.5194/essd-9-905-2017, 2017
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Projected changes estimated from an ensemble of nine model simulations showed that annual means of temperature are expected to increase steadily by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5, which is accelerating assuming the RCP8.5 scenario and can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 to 10 % and by 8 to 16 % for the two future horizons and RCPs.
Andreas Dobler, Jan Erik Haugen, and Rasmus Emil Benestad
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2016-27, https://doi.org/10.5194/esd-2016-27, 2016
Revised manuscript has not been submitted
N. Akhtar, J. Brauch, A. Dobler, K. Béranger, and B. Ahrens
Nat. Hazards Earth Syst. Sci., 14, 2189–2201, https://doi.org/10.5194/nhess-14-2189-2014, https://doi.org/10.5194/nhess-14-2189-2014, 2014
F. Uboldi, A. N. Sulis, C. Lussana, M. Cislaghi, and M. Russo
Hydrol. Earth Syst. Sci., 18, 981–995, https://doi.org/10.5194/hess-18-981-2014, https://doi.org/10.5194/hess-18-981-2014, 2014
J. Steppeler, S.-H. Park, and A. Dobler
Geosci. Model Dev., 6, 875–882, https://doi.org/10.5194/gmd-6-875-2013, https://doi.org/10.5194/gmd-6-875-2013, 2013
C. Lussana
Adv. Sci. Res., 10, 59–64, https://doi.org/10.5194/asr-10-59-2013, https://doi.org/10.5194/asr-10-59-2013, 2013
Related subject area
Meteorology
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
MOPREDAScentury: a long-term monthly precipitation grid for the Spanish mainland
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
A long-term 1 km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations
Data rescue of historical wind observations in Sweden since the 1920s
East Asia Reanalysis System (EARS)
The EUPPBench postprocessing benchmark dataset v1.0
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
CHELSA-W5E5: Daily 1 km meteorological forcing data for climate impact studies
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites
Database of the Italian disdrometer network
Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium
Combined high-resolution rainfall and wind data collected for 3 months on a wind farm 110 km southeast of Paris (France)
Sub-mesoscale observations of convective cold pools with a dense station network in Hamburg, Germany
Observational data from uncrewed systems over Southern Great Plains
EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe
GPRChinaTemp1km: a high-resolution monthly air temperature data set for China (1951–2020) based on machine learning
STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China
A global dataset of spatiotemporally seamless daily mean land surface temperatures: generation, validation, and analysis
Historical and future weather data for dynamic building simulations in Belgium using the regional climate model MAR: typical and extreme meteorological year and heatwaves
Hourly historical and near-future weather and climate variables for energy system modelling
HCPD-CA: high-resolution climate projection dataset in central Asia
Development of East Asia Regional Reanalysis based on advanced hybrid gain data assimilation method and evaluation with E3DVAR, ERA-5, and ERA-Interim reanalysis
EUREC4A observations from the SAFIRE ATR42 aircraft
Observations of marine cold-air outbreaks: a comprehensive data set of airborne and dropsonde measurements from the Springtime Atmospheric Boundary Layer Experiment (STABLE)
Water vapor in cold and clean atmosphere: a 3-year data set in the boundary layer of Dome C, East Antarctic Plateau
Resilient dataset of rain clusters with life cycle evolution during April to June 2016–2020 over eastern Asia based on observations from the GPM DPR and Himawari-8 AHI
Dataset of daily near-surface air temperature in China from 1979 to 2018
C3ONTEXT: a Common Consensus on Convective OrgaNizaTion during the EUREC4A eXperimenT
The Large eddy Observatory, Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing
LegacyClimate 1.0: A dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the late Quaternary
Homogenized century-long surface incident solar radiation over Japan
EUREC4A's Maria S. Merian ship-based cloud and micro rain radar observations of clouds and precipitation
Deployment of the C-band radar Poldirad on Barbados during EUREC4A
Remote and autonomous measurements of precipitation for the northwestern Ross Ice Shelf, Antarctica
High-frequency observation during sand and dust storms at the Qingtu Lake Observatory
10 years of temperature and wind observation on a 45 m tower at Dome C, East Antarctic plateau
Global balanced wind derived from SABER temperature and pressure observations and its validations
EUREC4A's HALO
JOANNE: Joint dropsonde Observations of the Atmosphere in tropical North atlaNtic meso-scale Environments
Ground-based vertical profile observations of atmospheric composition on the Tibetan Plateau (2017–2019)
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
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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
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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.
Santiago Beguería, Dhais Peña-Angulo, Víctor Trullenque-Blanco, and Carlos González-Hidalgo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-63, https://doi.org/10.5194/essd-2023-63, 2023
Revised manuscript accepted for ESSD
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A gridded data set on monthly precipitation over mainland Spain between spanning 1916–2020. The dataset combines ground observations from the Spanish National Climate Data Bank and new data rescued from meteorological yearbooks published prior to 1951 which almost doubled the number of weather stations available during the first decades of the 20th century. Geostatistical techniques were used to interpolate a regular 10x10 km grid.
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
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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
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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
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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
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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
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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.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-2, https://doi.org/10.5194/essd-2023-2, 2023
Revised manuscript accepted for ESSD
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Newly digitized wind speed observations provide data from the time period from around 1920 to 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.
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 Discuss., https://doi.org/10.5194/essd-2022-429, https://doi.org/10.5194/essd-2022-429, 2023
Revised manuscript accepted for ESSD
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there is 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.
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 Discuss., https://doi.org/10.5194/essd-2022-465, https://doi.org/10.5194/essd-2022-465, 2023
Revised manuscript accepted for ESSD
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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-meter temperature forecasts is performed.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-367, https://doi.org/10.5194/essd-2022-367, 2022
Revised manuscript accepted for ESSD
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We present the first 1km, daily, global climate dataset for climate impact studies. We show that the high resolution data has 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.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
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Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
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 Discuss., https://doi.org/10.5194/essd-2022-317, https://doi.org/10.5194/essd-2022-317, 2022
Revised manuscript accepted for ESSD
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The paper describes the database of 1-minute 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.
Eva Beele, Maarten Reyniers, Raf Aerts, and Ben Somers
Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, https://doi.org/10.5194/essd-14-4681-2022, 2022
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This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
Auguste Gires, Jerry Jose, Ioulia Tchiguirinskaia, and Daniel Schertzer
Earth Syst. Sci. Data, 14, 3807–3819, https://doi.org/10.5194/essd-14-3807-2022, https://doi.org/10.5194/essd-14-3807-2022, 2022
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The Hydrology Meteorology and Complexity laboratory of École des Ponts ParisTech (https://hmco.enpc.fr) has made a data set of high-resolution atmospheric measurements (rainfall, wind, temperature, pressure, and humidity) available. It comes from a campaign carried out on a meteorological mast located on a wind farm in the framework of the Rainfall Wind Turbine or Turbulence project (RW-Turb; supported by the French National Research Agency – ANR-19-CE05-0022).
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
Fan Mei, Mikhail S. Pekour, Darielle Dexheimer, Gijs de Boer, RaeAnn Cook, Jason Tomlinson, Beat Schmid, Lexie A. Goldberger, Rob Newsom, and Jerome D. Fast
Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
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This work focuses on an expanding number of data sets observed using ARM TBS (133 flights) and UAS (seven flights) platforms by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research, such as the aerosol–cloud interaction in the boundary layer.
Vera Thiemig, Goncalo N. Gomes, Jon O. Skøien, Markus Ziese, Armin Rauthe-Schöch, Elke Rustemeier, Kira Rehfeldt, Jakub P. Walawender, Christine Kolbe, Damien Pichon, Christoph Schweim, and Peter Salamon
Earth Syst. Sci. Data, 14, 3249–3272, https://doi.org/10.5194/essd-14-3249-2022, https://doi.org/10.5194/essd-14-3249-2022, 2022
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EMO-5 is a free and open European high-resolution (5 km), sub-daily, multi-variable (precipitation, temperatures, wind speed, solar radiation, vapour pressure), multi-decadal meteorological dataset based on quality-controlled observations coming from almost 30 000 stations across Europe, and is produced in near real-time. EMO-5 (v1) covers the time period from 1990 to 2019. In this paper, we have provided insight into the source data, the applied methods, and the quality assessment of EMO-5.
Qian He, Ming Wang, Kai Liu, Kaiwen Li, and Ziyu Jiang
Earth Syst. Sci. Data, 14, 3273–3292, https://doi.org/10.5194/essd-14-3273-2022, https://doi.org/10.5194/essd-14-3273-2022, 2022
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We used three machine learning models and determined that Gaussian process regression (GPR) is best suited to the interpolation of air temperature data for China. The GPR-derived results were compared with that of traditional interpolation techniques and existing data sets and it was found that the accuracy of the GPR-derived data was better. Finally, we generated a gridded monthly air temperature data set with 1 km resolution and high accuracy for China (1951–2020) using the GPR model.
Yinghong Jing, Xinghua Li, and Huanfeng Shen
Earth Syst. Sci. Data, 14, 3137–3156, https://doi.org/10.5194/essd-14-3137-2022, https://doi.org/10.5194/essd-14-3137-2022, 2022
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Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
Falu Hong, Wenfeng Zhan, Frank-M. Göttsche, Zihan Liu, Pan Dong, Huyan Fu, Fan Huang, and Xiaodong Zhang
Earth Syst. Sci. Data, 14, 3091–3113, https://doi.org/10.5194/essd-14-3091-2022, https://doi.org/10.5194/essd-14-3091-2022, 2022
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Daily mean land surface temperature (LST) acquired from satellite thermal sensors is crucial for various applications such as global and regional climate change analysis. This study proposed a framework to generate global spatiotemporally seamless daily mean LST products (2003–2019). Validations show that the products outperform the traditional method with satisfying accuracy. Our further analysis reveals that the LST-based global land surface warming rate is 0.029 K yr−1 from 2003 to 2019.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
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This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
Hannah C. Bloomfield, David J. Brayshaw, Matthew Deakin, and David Greenwood
Earth Syst. Sci. Data, 14, 2749–2766, https://doi.org/10.5194/essd-14-2749-2022, https://doi.org/10.5194/essd-14-2749-2022, 2022
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There is a global increase in renewable generation to meet carbon targets and reduce the impacts of climate change. Renewable generation and electricity demand depend on the weather. This means there is a need for high-quality weather data for energy system modelling. We present a new European-level, 70-year dataset which has been specifically designed to support the energy sector. We provide hourly, sub-national climate outputs and include the impacts of near-term climate change.
Yuan Qiu, Jinming Feng, Zhongwei Yan, and Jun Wang
Earth Syst. Sci. Data, 14, 2195–2208, https://doi.org/10.5194/essd-14-2195-2022, https://doi.org/10.5194/essd-14-2195-2022, 2022
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A high-resolution climate projection dataset in central Asia, named the HCPD-CA dataset, is derived from the dynamically downscaled results based on three bias-corrected global climate models and contains 4 geostatic variables and 10 meteorological elements that are widely used to drive ecological and hydrological models. This dataset can serve as a scientific basis for assessing the potential impacts of projected climate changes over central Asia on many sectors.
Eun-Gyeong Yang, Hyun Mee Kim, and Dae-Hui Kim
Earth Syst. Sci. Data, 14, 2109–2127, https://doi.org/10.5194/essd-14-2109-2022, https://doi.org/10.5194/essd-14-2109-2022, 2022
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The East Asia Regional Reanalysis (EARR) system is developed based on the advanced hybrid gain data assimilation method (AdvHG) using the Weather Research and Forecasting (WRF) model and conventional observations. Based on EARR, high-resolution regional reanalysis and reforecast fields are produced with 12 km horizontal resolution over East Asia for the period 2010–2019. Compared to ERA5, EARR represents precipitation better for January and July 2017 over East Asia.
Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
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The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Janosch Michaelis, Amelie U. Schmitt, Christof Lüpkes, Jörg Hartmann, Gerit Birnbaum, and Timo Vihma
Earth Syst. Sci. Data, 14, 1621–1637, https://doi.org/10.5194/essd-14-1621-2022, https://doi.org/10.5194/essd-14-1621-2022, 2022
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A major goal of the Springtime Atmospheric Boundary Layer Experiment (STABLE) aircraft campaign was to observe atmospheric conditions during marine cold-air outbreaks (MCAOs) originating from the sea-ice-covered Arctic ocean. Quality-controlled measurements of several meteorological variables collected during 15 vertical aircraft profiles and by 22 dropsondes are presented. The comprehensive data set may be used for validating model results to improve the understanding of future trends in MCAOs.
Christophe Genthon, Dana E. Veron, Etienne Vignon, Jean-Baptiste Madeleine, and Luc Piard
Earth Syst. Sci. Data, 14, 1571–1580, https://doi.org/10.5194/essd-14-1571-2022, https://doi.org/10.5194/essd-14-1571-2022, 2022
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The surface atmosphere of the high Antarctic Plateau is very cold and clean. Such conditions favor water vapor supersaturation. A 3-year quasi-continuous series of atmospheric moisture in a ~40 m atmospheric layer at Dome C is reported that documents time variability, vertical profiles and occurrences of supersaturation. Supersaturation with respect to ice is frequently observed throughout the column, with relative humidities occasionally reaching values near liquid water saturation.
Aoqi Zhang, Chen Chen, Yilun Chen, Weibiao Li, Shumin Chen, and Yunfei Fu
Earth Syst. Sci. Data, 14, 1433–1445, https://doi.org/10.5194/essd-14-1433-2022, https://doi.org/10.5194/essd-14-1433-2022, 2022
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We constructed an event-based precipitation dataset with life cycle evolution based on coordinated application of observations from spaceborne active precipitation radar and geostationary satellites. The dataset provides both three-dimensional structures of the precipitation system and its corresponding life cycle evolution. The dataset greatly reduces the data size and avoids complex data processing algorithms for studying the life cycle evolution of precipitation microphysics.
Shu Fang, Kebiao Mao, Xueqi Xia, Ping Wang, Jiancheng Shi, Sayed M. Bateni, Tongren Xu, Mengmeng Cao, Essam Heggy, and Zhihao Qin
Earth Syst. Sci. Data, 14, 1413–1432, https://doi.org/10.5194/essd-14-1413-2022, https://doi.org/10.5194/essd-14-1413-2022, 2022
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Air temperature is an important parameter reflecting climate change, and the current method of obtaining daily temperature is affected by many factors. In this study, we constructed a temperature model based on weather conditions and established a correction equation. The dataset of daily air temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1°. Accuracy verification shows that the dataset has reliable accuracy and high spatial resolution.
Hauke Schulz
Earth Syst. Sci. Data, 14, 1233–1256, https://doi.org/10.5194/essd-14-1233-2022, https://doi.org/10.5194/essd-14-1233-2022, 2022
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Trade wind clouds are often organized on the mesoscale (O(100 km)), forming different cloud patterns. We present C3ONTEXT (a Common Consensus on Convective OrgaNizaTion during the EUREC4A eXperimenT), a dataset that contains information about the mesoscale cloud patterns identified during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign in January–February 2020 and thereby provide the mesoscale context for the campaign's measurements.
Karl Lapo, Anita Freundorfer, Antonia Fritz, Johann Schneider, Johannes Olesch, Wolfgang Babel, and Christoph K. Thomas
Earth Syst. Sci. Data, 14, 885–906, https://doi.org/10.5194/essd-14-885-2022, https://doi.org/10.5194/essd-14-885-2022, 2022
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The layer of air near the surface is poorly understood during conditions with weak winds. Further, it is even difficult to observe. In this experiment we used distributed temperature sensing to observe air temperature and wind speed at thousands of points simultaneously every couple of seconds. This incredibly rich data set can be used to examine and understand what drives the mixing between the atmosphere and surface during these weak-wind periods.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, 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 Discuss., https://doi.org/10.5194/essd-2022-38, https://doi.org/10.5194/essd-2022-38, 2022
Revised manuscript accepted for ESSD
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Climate reconstruction from proxy data can help evaluate climate models. Here 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, 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.
Qian Ma, Kaicun Wang, Yanyi He, Liangyuan Su, Qizhong Wu, Han Liu, and Youren Zhang
Earth Syst. Sci. Data, 14, 463–477, https://doi.org/10.5194/essd-14-463-2022, https://doi.org/10.5194/essd-14-463-2022, 2022
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Surface incident solar radiation plays a key role in atmospheric circulation, the water cycle, and ecological equilibrium on Earth. A homogenized century-long surface incident solar radiation dataset was obtained over Japan.
Claudia Acquistapace, Richard Coulter, Susanne Crewell, Albert Garcia-Benadi, Rosa Gierens, Giacomo Labbri, Alexander Myagkov, Nils Risse, and Jan H. Schween
Earth Syst. Sci. Data, 14, 33–55, https://doi.org/10.5194/essd-14-33-2022, https://doi.org/10.5194/essd-14-33-2022, 2022
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This publication describes the unprecedented high-resolution cloud and precipitation dataset collected by two radars deployed on the Maria S. Merian research vessel. The ship operated in the west Atlantic Ocean during the measurement campaign called EUREC4A, between 19 January and 19 February 2020. The data collected are crucial to investigate clouds and precipitation and understand how they form and change over the ocean, where it is so difficult to measure them.
Martin Hagen, Florian Ewald, Silke Groß, Lothar Oswald, David A. Farrell, Marvin Forde, Manuel Gutleben, Johann Heumos, Jens Reimann, Eleni Tetoni, Gregor Köcher, Eleni Marinou, Christoph Kiemle, Qiang Li, Rebecca Chewitt-Lucas, Alton Daley, Delando Grant, and Kashawn Hall
Earth Syst. Sci. Data, 13, 5899–5914, https://doi.org/10.5194/essd-13-5899-2021, https://doi.org/10.5194/essd-13-5899-2021, 2021
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The German polarimetric weather radar Poldirad was deployed for the international campaign EUREC4A on Barbados. The focus was monitoring clouds and precipitation in the trade wind region east of Barbados. Observations were with a temporal sequence of 5 min and a maximum range of 375 km. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution show the potential for further studies on the life cycle of precipitating shallow cumulus clouds.
Mark W. Seefeldt, Taydra M. Low, Scott D. Landolt, and Thomas H. Nylen
Earth Syst. Sci. Data, 13, 5803–5817, https://doi.org/10.5194/essd-13-5803-2021, https://doi.org/10.5194/essd-13-5803-2021, 2021
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The Antarctic Precipitation System project deployed and maintained four sites across Antarctica from November 2017 to November 2019. The goals for the project included the collection of in situ observations of precipitation in Antarctica, an improvement in the understanding of precipitation in Antarctica, and the ability to validate precipitation data from atmospheric numerical models. The collected dataset represents some of the first year-round observations of precipitation in Antarctica.
Xuebo Li, Yongxiang Huang, Guohua Wang, and Xiaojing Zheng
Earth Syst. Sci. Data, 13, 5819–5830, https://doi.org/10.5194/essd-13-5819-2021, https://doi.org/10.5194/essd-13-5819-2021, 2021
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High-frequency observatory data (50 Hz 3D wind velocity, 50 Hz temperature and 1 Hz PM10) for studying the features of the fluid and dust field during sand and dust storms were presented. It is anticipated that data collected in this work will be of utility not only specifically for the boundary layer community in building a model for sand and dust storms but also broadly for communities studying the exchange of the dust and fluid field and energy transfer for the particle-laden two-phase flow.
Christophe Genthon, Dana Veron, Etienne Vignon, Delphine Six, Jean-Louis Dufresne, Jean-Baptiste Madeleine, Emmanuelle Sultan, and François Forget
Earth Syst. Sci. Data, 13, 5731–5746, https://doi.org/10.5194/essd-13-5731-2021, https://doi.org/10.5194/essd-13-5731-2021, 2021
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A 10-year dataset of observation in the atmospheric boundary layer at Dome C on the high Antarctic plateau is presented. This is obtained with sensors at six levels along a tower higher than 40 m. The temperature inversion can reach more than 25 °C along the tower in winter, while full mixing by convection can occur in summer. Different amplitudes of variability for wind and temperature at the different levels reflect different signatures of solar vs. synoptic forcing of the boundary layer.
Xiao Liu, Jiyao Xu, Jia Yue, You Yu, Paulo P. Batista, Vania F. Andrioli, Zhengkuan Liu, Tao Yuan, Chi Wang, Ziming Zou, Guozhu Li, and James M. Russell III
Earth Syst. Sci. Data, 13, 5643–5661, https://doi.org/10.5194/essd-13-5643-2021, https://doi.org/10.5194/essd-13-5643-2021, 2021
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Based on the gradient balance wind theory and the SABER observations, a dataset of monthly mean zonal wind has been developed at heights of 18–100 km and latitudes of 50° Sndash;50° N from 2002 to 2019. The dataset agrees with the zonal wind from models (MERRA2, UARP, HWM14) and observations by meteor radar and lidar at seven stations. The dataset can be used to study seasonal and interannual variations and can serve as a background for wave studies of tides and planetary waves.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Geet George, Bjorn Stevens, Sandrine Bony, Robert Pincus, Chris Fairall, Hauke Schulz, Tobias Kölling, Quinn T. Kalen, Marcus Klingebiel, Heike Konow, Ashley Lundry, Marc Prange, and Jule Radtke
Earth Syst. Sci. Data, 13, 5253–5272, https://doi.org/10.5194/essd-13-5253-2021, https://doi.org/10.5194/essd-13-5253-2021, 2021
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Dropsondes measure atmospheric parameters such as temperature, pressure, humidity and horizontal winds. The EUREC4A field campaign deployed 1215 dropsondes during January–February 2020 in the north Atlantic trade-wind region in order to characterize the thermodynamic and the dynamic structure of the atmosphere, primarily at horizontal scales of ~ 200 km. We present JOANNE, the dataset that provides these dropsonde measurements and thereby a rich characterization of the trade-wind atmosphere.
Chengzhi Xing, Cheng Liu, Hongyu Wu, Jinan Lin, Fan Wang, Shuntian Wang, and Meng Gao
Earth Syst. Sci. Data, 13, 4897–4912, https://doi.org/10.5194/essd-13-4897-2021, https://doi.org/10.5194/essd-13-4897-2021, 2021
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Observations of atmospheric composition, especially vertical profile observations, remain sparse and rare on the Tibetan Plateau (TP), due to extremely high altitude, topographical heterogeneity and the grinding environment. This paper introduces a high-time-resolution (~ 15 min) vertical profile observational dataset of atmospheric composition (aerosols, NO2, HCHO and HONO) on the TP for more than 1 year (2017–2019) using a passive remote sensing technique.
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Short summary
seNorge_2018 is a collection of observational gridded datasets for daily total precipitation and daily mean, minimum, and maximum temperature for the Norwegian mainland covering the time period from 1957 to the present day. The fields have 1 km of grid spacing. The data are used for applications in climatology, hydrology, and meteorology. seNorge_2018 provides a "gridded truth", especially in data-dense regions. The uncertainty increases with decreasing data density.
seNorge_2018 is a collection of observational gridded datasets for daily total precipitation and...