Articles | Volume 11, issue 4
https://doi.org/10.5194/essd-11-1947-2019
© 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-11-1947-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
16 Dec 2019
Data description paper |
| 16 Dec 2019
| 16 Dec 2019
Iberia01: a new gridded dataset of daily precipitation and temperatures over Iberia
Sixto Herrera
CORRESPONDING AUTHOR
Meteorology Group, Dept. of Applied Mathematics and Computer Science, Universidad de Cantabria, Santander, Spain
Rita Margarida Cardoso
Instituto Dom Luiz (IDL), Facultade de Ciências, Universidade de Lisboa, Lisbon, Portugal
Pedro Matos Soares
Instituto Dom Luiz (IDL), Facultade de Ciências, Universidade de Lisboa, Lisbon, Portugal
Fátima Espírito-Santo
Instituto Português do Mar e da Atmosfera (IPMA), Lisbon, Portugal
Pedro Viterbo
Instituto Português do Mar e da Atmosfera (IPMA), Lisbon, Portugal
José Manuel Gutiérrez
Meteorology Group, Instituto de Física de Cantabria, CSIC-University of Cantabria, Santander, Spain
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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
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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.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
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
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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
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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
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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
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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
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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
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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
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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.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
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
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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
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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
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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
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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
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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.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
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To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
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
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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
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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
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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
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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
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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 m temperature forecasts is performed.
Santiago Beguería, Dhais Peña-Angulo, Víctor Trullenque-Blanco, and Carlos González-Hidalgo
Earth Syst. Sci. Data, 15, 2547–2575, https://doi.org/10.5194/essd-15-2547-2023, https://doi.org/10.5194/essd-15-2547-2023, 2023
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A gridded dataset on monthly precipitation over mainland Spain between spans 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 10 x 10 km grid.
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
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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
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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
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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
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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
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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
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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.
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.
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.
Cited articles
Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of
Global Precipitation Products for Orographic Effects, J. Climate, 19,
15–38, https://doi.org/10.1175/JCLI3604.1, 2006. a
Beguería, S., Vicente-Serrano, S. M., Tomás-Burguera, M., and Maneta,
M.: Bias in the variance of gridded data sets leads to misleading conclusions
about changes in climate variability, Int. J. Climatol.,
36, 3413–3422, https://doi.org/10.1002/joc.4561, 2016. a, b
Belo-Pereira, M., Dutra, E., and Viterbo, P.: Evaluation of global
precipitation data sets over the Iberian Peninsula, J. Geophys.
Res.-Atmos., 116, D20101, https://doi.org/10.1029/2010JD015481,
2011. a
Cardoso, R., Soares, P., Miranda, P., and Belo-Pereira, M.: WRF high resolution
simulation of Iberian mean and extreme precipitation climate, Int. J. Climatol., 33, 2591–2608, https://doi.org/10.1002/joc.3616,
2013. a
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J. M., and Jones,
P. D.: An Ensemble Version of the E-OBS Temperature and Precipitation Data
Sets, J. Geophys. Res.-Atmos., 123, 9391–9409,
https://doi.org/10.1029/2017JD028200, 2018. a, b
Craven, P. and Wahba, G.: Smoothing noisy data with spline functions,
Numer. Math., 31, 377–403, 1979. a
Durand, Y., Brun, E., Merindol, L., Guyomarc'h, G., Lesaffre, B., and Martin,
E.: A meteorological estimation of relevant parameters for snow models,
Ann. Glaciol., 18, 65–71, https://doi.org/10.3189/S0260305500011277, 1993. a
Esteban-Parra, M., Rodrigo, F., and Castro-Diez, Y.: Spatial and temporal
patterns of precipitation in Spain for the period 1880–1992, Int. J. Climatol., 18, 1557–1574,
https://doi.org/10.1002/(SICI)1097-0088(19981130)18:14<1557::AID-JOC328>3.0.CO;2-J, 1998. a
Frei, C.: Interpolation of temperature in a mountainous region using nonlinear
profiles and non-Euclidean distances, Int. J. Climatol.,
34, 1585–1605, https://doi.org/10.1002/joc.3786, 2014. a, b, c
Frei, C., Christensen, J. H., Déqué, M., Jacob, D., Jones, R. G., and
Vidale, P. L.: Daily precipitation statistics in regional climate models:
Evaluation and intercomparison for the European Alps, J. Geophys.
Res.-Atmos., 108, https://doi.org/10.1029/2002JD002287, 2003. a
Frick, C., Steiner, H., Mazurkiewicz, A., Riediger, U., Rauthe, M., Reich, T.,
and Gratzki, A.: Central European high-resolution gridded daily data sets
(HYRAS): Mean temperature and relative humidity, Meteorol. Z.,
23, 15–32, https://doi.org/10.1127/0941-2948/2014/0560, 2014. a
Giorgi, F., Jones, C., and Asrar, G. R.: Addressing climate information needs
at the regional level: the CORDEX framework, World Meteorological
Organization (WMO) Bulletin, 58, 175–183, 2009. a
Häggmark, L., Ivarsson, K.-I., Gollvik, S., and Olofsson, P.-O.: Mesan, an
operational mesoscale analysis system, Tellus A, 52, 2–20, https://doi.org/10.3402/tellusa.v52i1.12250, 2000. a
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution
grids of monthly climatic observations – the CRU TS3.10 Dataset,
Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711,
2014. a
Haylock, M., Hofstra, N., Klein-Tank, A., Klok, E. J., Jones, P., and New, M.:
A European daily high-resolution gridded data set of surface temperature and
precipitation for 1950–2006, J. Geophys. Res., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008. a, b
Herrera, S.: Desarrollo, Validación Y Aplicaciones de Spain02:
Una Rejilla de Alta Resolución de Observaciones Interpoladas Para
Precipitación Y Temperatura en España, PhD thesis,
Universidad de Cantabria, available at:
http://www.meteo.unican.es/tesis/herrera (last access: 22 September 2019), 2011 (in Spanish). a, b, c
Herrera, S., Fernández, J., and Gutierrez, J. M.: Update of the Spain02 gridded
observational dataset for EURO-CORDEX evaluation: assessing the effect of the
interpolation methodology, Int. J. Climatol., 36,
900–908, https://doi.org/10.1002/joc.4391, 2015. a, b, c
Herrera, S., Cardoso, R. M., Soares, P. M. M., Espírito-Santo, F., Viterbo, P., and Gutiérrez, J. M.: Iberia01: Daily gridded (0.1∘ resolution)
dataset of precipitation and temperatures over the Iberian Peninsula, DIGITAL.CSIC, https://doi.org/10.20350/digitalCSIC/8641, 2019a. a, b
Herrera, S., Kotlarski, S., Soares, P. M. M., Cardoso, R. M., Jaczewski, A.,
Gutiérrez, J. M., and Maraun, D.: Uncertainty in gridded precipitation
products: Influence of station density, interpolation method and grid
resolution, Int. J. Climatol., 39, 3717–3729,
https://doi.org/10.1002/joc.5878, 2019b. a, b, c
Hofstra, N., Haylock, M., New, M., and Jones, P.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res., 114, D21101,
https://doi.org/10.1029/2009JD011799, 2009. a
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dynam., 35, 841–858,
https://doi.org/10.1007/s00382-009-0698-1, 2010. a
Hutchinson, M.: Interpolation of rainfall data with thin plate smoothing
splines – Part I: two dimensional smoothing of data with short range
correlation, Journal of Geographic Information and Decision Analysis, 2,
139–151, 1998a. a
Hutchinson, M.: Interpolation of rainfall data with thin plate smoothing
splines – Part II: analysis of topographic dependence, Journal of
Geographic Information and Decision Analysis, 2, 152–167,
1998b. a
Iturbide, M., Bedia, J., Herrera, S., Baño-Medina, J., Fernández, J., Frías,
M. D., Manzanas, R., San-Martín, D., Cimadevilla, E., Cofiño, A. S., and
Gutiérrez, J. M.: The R-based climate4R open framework for reproducible
climate data access and post-processing, Environ. Model. Softw.,
111, 42–54, https://doi.org/10.1016/j.envsoft.2018.09.009,
2019. a
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O., Bouwer, L.,
Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet,
A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler,
K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van
Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C.,
Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana,
J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.:
EURO-CORDEX: new high-resolution climate change projections for European
impact research, Reg. Environ. Change, 14, 563–578,
https://doi.org/10.1007/s10113-013-0499-2, 2014. a
Johansson, B.: Areal Precipitation and Temperature in the Swedish Mountains: An Evaluation from a Hydrological Perspective, Hydrol. Res., 31, 207,
https://doi.org/10.2166/nh.2000.0013, 2000. a
Johansson, B. and Chen, D.: The influence of wind and topography on
precipitation distribution in Sweden: statistical analysis and modelling,
Int. J. Climatol., 23, 1523–1535, https://doi.org/10.1002/joc.951,
2003. a
Jones, P. D., Wigley, T. M. L., and Kelly, P. M.: Variations in Surface Air
Temperatures: Part 1. Northern Hemisphere, 1881–1980, Mon. Weather
Rev., 110, 59–70, https://doi.org/10.1175/1520-0493(1982)110<0059:VISATP>2.0.CO;2,
1982. a
Jones, P. D., Raper, S. C. B., Bradley, R. S., Diaz, H. F., Kellyo, P. M., and
Wigley, T. M. L.: Northern Hemisphere Surface Air Temperature Variations:
1851–1984, J. Climate Appl. Meteorol., 25, 161–179,
https://doi.org/10.1175/1520-0450(1986)025<0161:NHSATV>2.0.CO;2, 1986a. a
Jones, P. D., Raper, S. C. B., and Wigley, T. M. L.: Southern Hemisphere
Surface Air Temperature Variations: 1851–1984, J. Climate
Appl. Meteorol., 25, 1213–1230, https://doi.org/10.1175/1520-0450(1986)025<1213:SHSATV>2.0.CO;2, 1986b. a
Kidd, C., Bauer, P., Turk, J., Huffman, G. J., Joyce, R., Hsu, K.-L., and
Braithwaite, D.: Intercomparison of High-Resolution Precipitation Products
over Northwest Europe, J. Hydrometeor., 13, 67–83, https://doi.org/10.1175/JHM-D-11-042.1, 2011. a
Klein Tank, A. M. G., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée,
G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L., Kern-Hansen, C.,
Heino, R., Bessemoulin, P., Müller-Westermeier, G., Tzanakou, M., Szalai,
S., Pálsdóttir, T., Fitzgerald, D., Rubin, S., Capaldo, M., Maugeri, M.,
Leitass, A., Bukantis, A., Aberfeld, R., van Engelen, A. F. V., Forland, E.,
Mietus, M., Coelho, F., Mares, C., Razuvaev, V., Nieplova, E., Cegnar, T.,
Antonio López, J., Dahlström, B., Moberg, A., Kirchhofer, W., Ceylan, A.,
Pachaliuk, O., Alexander, L. V., and Petrovic, P.: Daily dataset of
20th-century surface air temperature and precipitation series for the
European Climate Assessment, Int. J. Climatol., 22,
1441–1453, https://doi.org/10.1002/joc.773,
2002. a
Klok, E. J. and Klein Tank, A. M. G.: Updated and extended European dataset of daily climate observations, Int. J. Climatol., 29,
1182–1191, https://doi.org/10.1002/joc.1779, 2009. a, b
Kotlarski, S., Szabó, P., Herrera, S., Räty, O., Keuler, K., Soares,
P. M., Cardoso, R. M., Bosshard, T., Pagé, C., Boberg, F., Gutiérrez,
J. M., Isotta, F. A., Jaczewski, A., Kreienkamp, F., Liniger, M. A., Lussana,
C., and Pianko-Kluczynska, K.: Observational uncertainty and regional climate model
evaluation: A pan-European perspective, Int. J. Climatol., 39, 3730–3749, https://doi.org/10.1002/joc.5249, 2019. a
Krige, D. G.: A statistical approach to some basic mine valuation problems on
the Witwatersrand, Journal of the Chemical, Metallurgical and Mining Society
of South Africa, 52, 119–139, 1951. a
Lakatos, M., Szentimrey, T., Bihari, Z., and Szalai, S.: Creation of a homogenized climate database for the Carpathian region by applying the MASH procedure and
the preliminary analysis of the data, Q. J. Hungarian
Meteorol. Serv., 117, 143–158, 2013. a
Lorente, P., Hernández, E., Queralt, S., and Ribera, P.: The flood event
that affected Badajoz in November 1997, Adv. Geosci., 16, 73–80,
2008. a
Lussana, C., Saloranta, T., Skaugen, T., Magnusson, J., Tveito, O. E., and Andersen, J.: seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day, Earth Syst. Sci. Data, 10, 235–249, https://doi.org/10.5194/essd-10-235-2018, 2018. a
Matheron, G.: Traité de Géostatistique appliquée, Tome 1–2,
Editions Technip, Paris, France, 1962. a
MeteoSwiss: Documentation of MeteoSwiss Grid-Data Products: Daily Mean, Minimum
and Maximum Temperature: TabsD, TminD, TmaxD, Tech. rep., Federal Office of
Meteorology and Climatology MeteoSwiss, Federal Department of Home Affairs
FDHA, Switzerland, available at: https://www.meteoswiss.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/produkt/raeumliche-daten-temperatur/doc/ProdDoc_TabsD.pdf (last access: 22 September 2019), 2013a. a
MeteoSwiss: Documentation of MeteoSwiss Grid-Data Products: Daily Precipitation
(final analysis): RhiresD, Tech. rep., Federal Office of Meteorology and
Climatology MeteoSwiss, Federal Department of Home Affairs FDHA, Switzerland, available at: https://www.meteoswiss.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/produkt/raeumliche-daten-niederschlag/doc/ProdDoc_RhiresD.pdf (last access: 22 September 2019), 2013b. a
Muñoz-Díaz, D. and Rodrigo, F. S.: Spatio-temporal patterns of seasonal rainfall in Spain (1912-2000) using cluster and principal component analysis: comparison, Ann. Geophys., 22, 1435–1448, https://doi.org/10.5194/angeo-22-1435-2004, 2004. a
Peral, C., Navascués, B., and Ramos, P.: Serie de precipitación diaria en
rejilla con fines climáticos., Nota técnica de AEMET 24/2017, Ministerio de
Agricultura y Pesca, Alimentación y Medio Ambiente – Agencia Estatal de
Meteorología, C/ Leonardo Prieto Castro, 8, 28040 Madrid, available at:
http://www.aemet.es/documentos/es/conocermas/recursos_en_linea/publicaciones_y_estudios/publicaciones/NT_24_AEMET/NT_24_AEMET.pdf (last access: 22 September 2019), 2017 (in Spanish). a
Prein, A. F. and Gobiet, A.: Impacts of uncertainties in European gridded
precipitation observations on regional climate analysis, Int. J. Climatol., 37, 305–327, https://doi.org/10.1002/joc.4706, 2017. a
Quintana-Seguí, P., Le Moigne, P., Durand, Y., Martin, E., Habets, F.,
Baillon, M., Canellas, C., Franchisteguy, L., and Morel, S.: Analysis of
Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over
France, J. Appl. Meteorol. Climatol., 47, 92–107,
https://doi.org/10.1175/2007JAMC1636.1, 2008. a
Quintana-Seguí, P., Turco, M., Herrera, S., and Miguez-Macho, G.: Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim, Hydrol. Earth Syst. Sci., 21, 2187–2201, https://doi.org/10.5194/hess-21-2187-2017, 2017. a, b
Ramos, A. M., Trigo, R., Liberato, M. L., and Tomé, R.: Daily Precipitation
Extreme Events in the Iberian Peninsula and Its Association with Atmospheric
Rivers, J. Hydrometeorol., 16, 579–597,
https://doi.org/10.1175/JHM-D-14-0103.1, 2015. a
Ramos, C. and Reis, E.: Floods in southern Portugal: their physical and human
causes, impacts and human response, in: Mitigation and Adaptation Strategies for Global Change, 7, 267–284, https://doi.org/10.1023/A:1024475529524, 2002. a
Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., and Gratzki, A.: A
Central European precipitation climatology – Part I: Generation and
validation of a high-resolution gridded daily data set (HYRAS),
Meteorol. Z., 22, 235–256, https://doi.org/10.1127/0941-2948/2013/0436, 2013. a
Rudolf, B., Hauschild, H., Rueth, W., and Schneider, U.: Terrestrial
Precipitation Analysis: Operational Method and Required Density of Point
Measurements, in: Global Precipitations and Climate Change, edited by:
Desbois, M. and Désalmand, F., Springer Berlin Heidelberg,
Berlin, Heidelberg, 173–186, 1994. a
Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian,
S., and Hsu, K.-L.: A Review of Global Precipitation Data Sets: Data
Sources, Estimation, and Intercomparisons, Rev. Geophys., 56, 79–107,
https://doi.org/10.1002/2017RG000574, 2018. a
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought,
Nat. Clim. Change, 4, 17–22, https://doi.org/10.1038/nclimate2067, 2014. a
Uboldi, F., Lussana, C., and Salvati, M.: Three-dimensional spatial
interpolation of surface meteorological observations from high-resolution
local networks, Meteorol. Appl., 15, 331–345,
https://doi.org/10.1002/met.76, 2008. a
van den Besselaar, E. J. M., Haylock, M. R., van der Schrier, G., and
Klein Tank, A. M. G.: A European daily high-resolution observational gridded
data set of sea level pressure, J. Geophys. Res.-Atmos.,
116, D11110, https://doi.org/10.1029/2010JD015468, 2011. a
Vidal, J.-P., Martin, E., Franchisteguy, L., Baillon, M., and Soubeyroux,
J.-M.: A 50-year high-resolution atmospheric reanalysis over France with the
Safran system, Int. J. Climatol., 30, 1627–1644,
https://doi.org/10.1002/joc.2003, 2010. a
Wahba, G.: Spline models for Observational Data, in: CBMS-NSF Regional
Conference Series in Applied Mathematics, Society for
Industrial and Applied Mathematics, Philadelphia, https://doi.org/10.1137/1.9781611970128, 1990. a
Whiteman, C. D.: Breakup of Temperature Inversions in Deep Mountain Valleys:
Part I. Observations, J. Appl. Meteorol., 21, 270–289,
https://doi.org/10.1175/1520-0450(1982)021<0270:BOTIID>2.0.CO;2,
1982. a
Whiteman, C. D.: Observations of Thermally Developed Wind Systems in
Mountainous Terrain, American Meteorological Society, Boston, MA, 5–42,
https://doi.org/10.1007/978-1-935704-25-6_2, 1990. a
Whiteman, C. D. and McKee, T. B.: Breakup of Temperature Inversions in Deep
Mountain Valleys: Part II. Thermodynamic Model, J. Appl.
Meteorol., 21, 290–302,
https://doi.org/10.1175/1520-0450(1982)021<0290:BOTIID>2.0.CO;2, 1982. a
Short summary
A new observational dataset of daily precipitation and temperatures for the Iberian Peninsula and the Balearic Islands has been developed and made publicly available for the community. In this work the capabilities of the new dataset to reproduce the mean and extreme regimes of precipitation and temperature are assessed and compared with the E-OBS dataset (including the ensemble version for observational uncertainty assessment).
A new observational dataset of daily precipitation and temperatures for the Iberian Peninsula...
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