Articles | Volume 13, issue 2
https://doi.org/10.5194/essd-13-697-2021
© Author(s) 2021. 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-13-697-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
26 Feb 2021
Data description paper |
| 26 Feb 2021
| 26 Feb 2021
Real-time WRF large-eddy simulations to support uncrewed aircraft system (UAS) flight planning and operations during 2018 LAPSE-RATE
James O. Pinto
CORRESPONDING AUTHOR
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Anders A. Jensen
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Pedro A. Jiménez
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Tracy Hertneky
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Domingo Muñoz-Esparza
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Arnaud Dumont
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Matthias Steiner
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
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CHESS-SCAPE is a suite of high-resolution climate projections for the United Kingdom to 2080, derived from UKCP18 and designed to support climate impacts modelling. It contains four realisations each of four different scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), provided with and without bias-correction to historical data. The variables are available at 1 km resolution and daily timestep, with monthly, seasonal and annual means, plus twenty-year mean-monthly timeslices.
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.
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.
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.
Cited articles
Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R.,
Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A.,
Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., and Kenyon, J. S.: A
North American hourly assimilation and model forecast cycle: The Rapid Refresh, Mon. Weather Rev., 144, 1669–1694, https://doi.org/10.1175/MWR-D-15-0242.1, 2016.
Bryan, G. H., Wyngaard, J. C., and Fritsch, J. M.: Resolution requirements
for the simulation of deep moist convection, Mon. Wea. Rev., 131, 2394–2416,
https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2, 2003.
Campbell, S. E., Clark, D. A., and Evans, J. E.: Preliminary Weather Information Gap Analysis for UAS Operations, Technical Report, MIT Lincoln
Laboratory, Boston, MA, USA, 2017.
Computational and Information Systems Laboratory (CISL): Cheyenne: HPE/SGI
ICE XA System (NCAR Community Computing), Boulder, CO, National Center for
Atmospheric Research, https://doi.org/10.5065/D6RX99HX, 2019.
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a three
dimensional model, Bound.-Lay. Meteorol., 18, 495–527, 1980.
de Boer, G., Diehl, C., Jacob, J., Houston, A., Smith, S. W., Chilson, P., Schmale III., D. G., Intrieri, J., Pinto, J., Elston, J., Brus, D., Kemppinen, O., Clark, A., Lawrence, D., Bailey, S. C. C., Sama, M. P., Frazier, A., Crick, C., Natalie, V., Pillar-Little, E., Klein, P., Waugh, S., Lundquist, J. K., Barbieri, L., Kral, S. T., Jensen, A. A., Dixon, C., Borenstein, S., Hesselius, D., Human, K., Hall, P., Argrow, B., Thornberry, T., Wright, R., and Kelly, J. T.: Development of community, capabilities and
understanding through unmanned aircraft-based atmospheric research: The
LAPSE-RATE campaign, B. Am. Meteorol. Soc., 101, E684–E699, https://doi.org/10.1175/BAMS-D-19-0050.1, 2020a.
de Boer, G., Houston, A., Jacob, J., Chilson, P. B., Smith, S. W., Argrow, B., Lawrence, D., Elston, J., Brus, D., Kemppinen, O., Klein, P., Lundquist, J. K., Waugh, S., Bailey, S. C. C., Frazier, A., Sama, M. P., Crick, C., Schmale III, D., Pinto, J., Pillar-Little, E. A., Natalie, V., and Jensen, A.: Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview, Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, 2020b.
Doubrawa, P. and Muñoz-Esparza, D.: Simulating real atmospheric
boundary layers at gray-zone resolutions: How do currently available
turbulence parameterizations perform?, Atmosphere, 11, 345, 10.3390/atmos11040345, 2020.
Dudhia, J.: Numerical study of convection observed during the Winter Monsoon
Experiment using a mesoscale two–dimensional model, J. Atmos. Sci., 46,
3077–3107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2, 1989.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm
refinements and characterization of new datasets, Remote Sens. Environ., 114, 168–182, 168, https://doi.org/10.1016/j.rse.2009.08.016, 2010.
Garrett-Glaser, B.: Are Low-Altitude Weather Services Ready for Drones and
Air Taxis? Aviation Today, available at: https://www.aviationtoday.com/2020/04/26/low-altitude-weather-services-ready-drones-air-taxis/,
last access: 1 August 2020.
Glasheen, K., Pinto, J., Steiner, M., and Frew, E.: Assessment of finescale
local wind forecasts using small unmanned aircraft systems, J. Aerosp. Inf. Syst., 17,
182–192, https://doi.org/10.2514/1.I010747, 2020.
Haupt, S. E., Kosovic, B., Shaw, W., Berg, L. K., Churchfield, M., Cline, J., Draxl, C., Ennis, B., Koo, E., Kotamarthi, R., Mazzaro, L., Mirocha, J., Moriarty, P., Muñoz-Esparza, D., Quon, E., Rai, R. K., Robinson, M., and Sever, G.: On bridging a modeling scale gap. Mesoscale to
microscale coupling for wind energy, B. Am. Meteorol. Soc., 100, 2533–2549,
https://doi.org/10.1175/BAMS-D-18-0033.1, 2019.
Hong, S.-Y. and Lim, J.-O. J.: The WRF single-moment 6-class microphysics
scheme (WSM6), J. Korean Meteor. Soc., 42, 129–151, 2006.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S.
A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys. Res., 113,
D13103, https://doi.org/10.1029/2008JD009944, 2008.
Jensen, A. A., Pinto, J. O., Bailey, S. C. C., Sobash, R. A., de Boer, G., Houston, A. L., Chilson, P. B., Bell, T., Romine, G., Smith, S. W., Lawerence, D. A., Dixon, C., Lundquist, J. K., Jacob, J. D., Elston, J., Waugh, S., and Steiner, M. : Assimilation of a coordinated fleet of UAS
observations in complex terrain. Part I: EnKF system design and preliminary
assessment, Mon. Weather Rev., in press, 2021.
Jiménez, P. A., Dudhia, J., González-Rouco, J. F., Navarro, J.,
Montávez, J. P., and García-Bustamante, E.: A revised scheme for the WRF
surface layer formulation, Mon. Weather Rev., 140,
898–918, https://doi.org/10.1175/MWR-D-11-00056.1, 2012.
Jiménez, P. A., Muñoz-Esparza, D., and Kosović, B.: A high
resolution coupled fire-atmosphere forecasting system to minimize the
impacts of wildland fires: Applications to the Chimney Tops II wildland
event, Atmosphere, 9, 197, https://doi.org/10.3390/atmos9050197, 2018.
Klemp, J. B., Dudhia, J., and Hassiotis, A. D.: An upper gravity-wave
absorbing layer for NWP applications, Mon. Weather Rev., 136, 3987–4004,
https://doi.org/10.1175/2008MWR2596.1, 2008.
Lilly, D. K.: On the application of the eddy viscosity concept in the
inertial sub-range of turbulence, NCAR Tech. Rep. 123, NCAR Press, Boulder, Colorado, USA, 1966a.
Lilly, D. K.: The representation of small-scale Turbulence in numerical simulation experiments. Pre-publication Review Copy, NCAR Manuscript #281, Boulder, Colorado, USA, 24 pp., https://doi.org/10.5065/D62R3PMM, 1966b.
Liu, Y., Warner, T., Liu, Y., Vincent, C., Wu, W., Mahoney, B., Swerdlin,
S., Parks, K., and Boehnert, J.: Simultaneous nested modeling from the
synoptic scale to the LES scale for wind energy applications, J. Wind Eng. Ind. Aerodyn., 99,
308–319, 2011.
Liu, Y., Liu, Y., Muñoz-Esparza, D., Hu, F., Yan, C., and Miao, S.:
Simulation of flow fields in complex terrain with WRF-LES: sensitivity
assessment of different PBL treatments, J. Appl. Meteorol. Clim., 59, 1481–1501, https://doi.org/10.1175/JAMC-D-19-0304.1, 2020.
Markowski, P. M. and Bryan, G. H.: LES of laminar flow in the PBL: A
potential problem for convective storm simulations, Mon. Weather Rev., 144, 1841–1850,
2016.
Muñoz-Esparza, D. and Kosović, B.: Generation of inflow turbulence
in large-eddy simulations of non-neutral atmospheric boundary layers with
the cell perturbation method, Mon. Weather Rev., 146, 1889–1909, 2018.
Muñoz-Esparza, D., Kosović, B., Mirocha, J., and van Beeck, J.:
Bridging the transition from mesoscale to microscale turbulence in numerical
weather prediction models, Bound.-Lay. Meteorol., 153, 409–440, 2014.
Muñoz-Esparza, D., Lundquist, J. K., Sauer, J. A., Kosović, B., and
Linn, R. R.: Coupled mesoscale-LES modeling of a diurnal cycle during the
CWEX-13 field campaign: From weather to boundary-layer eddies, J. Adv. Model. Earth Syst., 9,
1572–1594, https://doi.org/10.1002/2017MS000960, 2017.
Muñoz-Esparza, D., Sharman, R., Sauer, J., and Kosović, B.: Toward
low-level turbulence forecasting at eddy-resolving scales, Geophys. Res. Lett., 45, 8655–8664,
https://doi.org/10.1029/2018GL078642, 2018.
Nakanishi, M. and Niino, H.: Development of an improved turbulence closure
model for the atmospheric boundary layer, J. Meteorol. Soc. Jpn., 87,
895–912, https://doi.org/10.2151/jmsj.87.895, 2009.
Nolan, P. J., Pinto, J., González-Rocha, J., Jensen, J., Vezzi, C. N., Bailey, S. C. C., de Boer, G., Diehl, C., Laurence II., R., Powers, C. W., Foroutan, H., Ross, S. D., and Schmale III., D. G.: Coordinated Unmanned Aircraft System (UAS) and
ground-based weather measurements to predict Lagrangian Coherent Structures
(LCSs), Sensors, 18, 4448, https://doi.org/10.3390/s18124448, 2018.
Olson, J. B., Kenyon, J. S., Djalalova, I., Bianco, L., Turner, D. D., Pichugina, Y., Choukulkar, A., Toy, M. D., Brown, J. M., Angevine, W. M., Akish, E., Bao, J.-W., Jiménez, P., Kosovic, B., Lundquist, K. A., Draxl, C., Lundquist, J. K., McCaa, J., McCaffery, K., Lantz, K., Long, C., Wilczak, J., Banta, R., Marquis, M., Redfern, S., Berg, L. K., Shaw, W., and Cline, J.: Improving wind energy forecasting through
numerical weather prediction model development, B. Am. Meteorol. Soc., 100, 2201–2220,
https://doi.org/10.1175/BAMS-D-18-0040.1, 2019
Pinto, J. O., Jiménez, P. A., Hertneky, T. J., Jensen, A. A., Muñoz-Esparza,
D., and Steiner, M.: WRF Large-Eddy Simulation Data from Realtime Runs Used to Support UAS Operations during LAPSE-RATE [Data set], UCAR/NCAR – DASH Repository, https://doi.org/10.5065/83r2-0579, 2020a.
Pinto, J. O., Jiménez, P. A., Jensen, A. A., Hertneky, T. J., Muñoz-Esparza,
D., and Steiner, M.: Realtime WRF Large-Eddy Simulation Data (Version V1)
[Data set], available at: https://zenodo.org/record/3706365#.X8VwZrd7mpo (last access: 15 January 2021), 2020b.
Rai, R. K., Berg, L. K., Kosović, B., Mirocha, J. D., Pekour, M. S., and
Shaw, W. J.: Comparison of measured and numerically simulated turbulence
statistics in a convective boundary layer over complex terrain,
Bound.-Lay. Meteorol., 163, 69–89, 2016.
Rai, R. K., Berg, L. K., Kosović, B., Haupt, S. E., Mirocha, J. D.,
Ennis, B., and Draxl, C.: Evaluation of the impact of horizontal grid
spacing in terra incognita on coupled mesoscale–microscale simulations
using the WRF framework, Mon. Weather Rev., 147, 1007–1027, https://doi.org/10.1175/MWR-D-18-0282.1,
2019.
Ranquist, E., Steiner, M., and Argrow, B.: Exploring the range of weather
impacts on UAS operations. 18th Conf. on Aviation, Range, and Aerospace
Meteorology, 22–27 January 2017, Seattle, WA, USA, Amer. Meteor. Soc., J3.1, available at: https://ams.confex.com/ams/97Annual/webprogram/Paper309274.html (last access: 15 August 2020), 2017.
Roseman, C. A. and Argrow, B. M.: Weather Hazard Risk Quantification for
SUAS Safety Risk Management, J. Atmos. Ocean. Tech., 37, 1251–1268,
https://doi.org/10.1175/JTECH-D-20-0009.1, 2020.
Silvestro, F., Rossi, L., Campo, L., Parodi, A., Fiori, E., Rudari, R., and
Ferraris, L.: Impact-based flash-flood forecasting system: Sensitivity to
high resolution numerical weather prediction systems and soil moisture, J. Hydrol.,
572, 388–402, 2019.
Skamarock, W. C. and Klemp, J.B.: A time-split non-hydrostatic atmospheric
model for weather research and forecasting applications, J. Comput. Phys., 227, 3465–3485.
https://doi.org/10.1016/j.jcp.2007.01.037, 2008.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A description of the
advanced research WRF Version 3, National Center for Atmospheric Research,
NCAR, Boulder, CO, USA, TN-475+STR, 2008.
Steiner, M.: Urban Air Mobility: Opportunities for the weather community,
B. Am. Meteorol. Soc., 100, 2131–2133, https://doi.org/10.1175/BAMS-D-19-0148.1, 2019.
Tesfuhuney, W., Walker, S., van Rensburg, L., and Everson, C.: Water vapor,
temperature and wind profiles within maize canopy under in-field rainwater
harvesting with wide and narrow runoff strips, Atmosphere, 4, 428–444,
https://doi.org/10.3390/atmos4040428, 2013.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek,
M., Gayno, G., Wegiel, J., and Cuenca, R. H.: Implementation and
verification of the unified NOAH land surface model in the WRF model, 20th conference on weather analysis and forecasting/16th conference on numerical weather prediction, 11–15 January 2004, Seattle, Washingtion, USA, 11–15, 2004.
Wyngaard, J. C.: Toward numerical modeling in the “terra incognita”, J. Atmos. Sci., 61,
1816–1826, https://doi.org/10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2, 2004.
Zhou, B., Simon, J. S., and Chow, F. K.: The convective boundary layer in
the terra incognita, J. Atmos. Sci., 71, 2545–2563, https://doi.org/10.1175/JAS-D-13-0356.1, 2014.
Short summary
The dataset produced here was generated as part of a real-time demonstration of a new capability to provide fine-scale weather guidance to support small UAS operations. The nested model configuration enabled us to resolve large turbulent eddies that developed in response to daytime heating and demonstrated the current state of the science in coupling mesoscale forcing with a large eddy simulation (LES) model. Output from these real-time simulations was used for planning IOPs during LAPSE-RATE.
The dataset produced here was generated as part of a real-time demonstration of a new capability...
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