Articles | Volume 12, issue 6
https://doi.org/10.5194/amt-12-3463-2019
© 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/amt-12-3463-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2019
Research article |
| 28 Jun 2019
| 28 Jun 2019
Automated wind turbine wake characterization in complex terrain
Sibley School of Mechanical and Aerospace Engineering, Cornell
University, Ithaca, New York, USA
Sara C. Pryor
Department of Earth and Atmospheric Sciences, Cornell University,
Ithaca, New York, USA
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Revised manuscript under review for WES
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Wind turbines in offshore lease areas (LA) along the eastern U.S. may be impacted by hurricanes. Regional simulations with atmosphere-only and coupled atmosphere-ocean-wave regional models well reproduce historical hurricanes and indicate no exceedance of 50 m s-1 wind speeds in the LA and only brief periods with low power production. Coupled simulations lead to more intense hurricanes possibly indicating that previous atmosphere-only simulations underestimate the risk to offshore wind turbines.
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Frederick Letson, Rebecca J. Barthelmie, Weifei Hu, and Sara C. Pryor
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Preprint withdrawn
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Paola Crippa, Ryan C. Sullivan, Abhinav Thota, and Sara C. Pryor
Atmos. Chem. Phys., 17, 1511–1528, https://doi.org/10.5194/acp-17-1511-2017, https://doi.org/10.5194/acp-17-1511-2017, 2017
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Here we quantify WRF-CHEM sensitivity in simulating meteorological, chemical and aerosol properties as a function of spatial resolution.
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H. Wang, R. J. Barthelmie, P. Doubrawa, and S. C. Pryor
Atmos. Meas. Tech., 9, 4123–4139, https://doi.org/10.5194/amt-9-4123-2016, https://doi.org/10.5194/amt-9-4123-2016, 2016
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Hui Wang, Rebecca J. Barthelmie, Sara C. Pryor, and Gareth. Brown
Atmos. Meas. Tech., 9, 1653–1669, https://doi.org/10.5194/amt-9-1653-2016, https://doi.org/10.5194/amt-9-1653-2016, 2016
P. Crippa, R. C. Sullivan, A. Thota, and S. C. Pryor
Atmos. Chem. Phys., 16, 397–416, https://doi.org/10.5194/acp-16-397-2016, https://doi.org/10.5194/acp-16-397-2016, 2016
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F. Yu, G. Luo, S. C. Pryor, P. R. Pillai, S. H. Lee, J. Ortega, J. J. Schwab, A. G. Hallar, W. R. Leaitch, V. P. Aneja, J. N. Smith, J. T. Walker, O. Hogrefe, and K. L. Demerjian
Atmos. Chem. Phys., 15, 13993–14003, https://doi.org/10.5194/acp-15-13993-2015, https://doi.org/10.5194/acp-15-13993-2015, 2015
Short summary
Short summary
The role of low-volatility organics in new particle formation (NPF) in the atmosphere is assessed. An empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics significantly overpredicts NPF in the summer.
Two different schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America.
S. C. Pryor, K. E. Hornsby, and K. A. Novick
Atmos. Chem. Phys., 14, 11985–11996, https://doi.org/10.5194/acp-14-11985-2014, https://doi.org/10.5194/acp-14-11985-2014, 2014
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What role do forests play in determining the concentration (and composition) of climate-relevant aerosol particles? This study seeks to address two aspects of this question. Firstly, we document high in-canopy removal of recently formed particles. Then we show evidence that growth rates of particles are a function of soil water availability via a reduction in canopy emissions of gases responsible for particle growth to climate-relevant sizes during drought conditions.
J. Ortega, A. Turnipseed, A. B. Guenther, T. G. Karl, D. A. Day, D. Gochis, J. A. Huffman, A. J. Prenni, E. J. T. Levin, S. M. Kreidenweis, P. J. DeMott, Y. Tobo, E. G. Patton, A. Hodzic, Y. Y. Cui, P. C. Harley, R. S. Hornbrook, E. C. Apel, R. K. Monson, A. S. D. Eller, J. P. Greenberg, M. C. Barth, P. Campuzano-Jost, B. B. Palm, J. L. Jimenez, A. C. Aiken, M. K. Dubey, C. Geron, J. Offenberg, M. G. Ryan, P. J. Fornwalt, S. C. Pryor, F. N. Keutsch, J. P. DiGangi, A. W. H. Chan, A. H. Goldstein, G. M. Wolfe, S. Kim, L. Kaser, R. Schnitzhofer, A. Hansel, C. A. Cantrell, R. L. Mauldin, and J. N. Smith
Atmos. Chem. Phys., 14, 6345–6367, https://doi.org/10.5194/acp-14-6345-2014, https://doi.org/10.5194/acp-14-6345-2014, 2014
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In this paper, we propose a data fusion method to obtain the no-blind-zone wind speed profiles covering the whole atmospheric boundary layer based on the joint measurements of coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS). Since the above instruments are widely deployed in China, we believe this method has broad application prospects for the improvement of the boundary layer parameterization scheme in numerical forecast models.
Sebastiano Padovan, Axel von Engeln, Saverio Paolella, Yago Andres, Chad R. Galley, Riccardo Notarpietro, Veronica Rivas Boscan, Francisco Sancho, Francisco Martin Alemany, Nicolas Morew, and Christian Marquardt
Atmos. Meas. Tech., 18, 3217–3228, https://doi.org/10.5194/amt-18-3217-2025, https://doi.org/10.5194/amt-18-3217-2025, 2025
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Using about 120 000 occultations recorded by the Sentinel-6A and COSMIC-2 satellites, we show that using high-rate (1 s) GLONASS clock products greatly improves GLONASS occultation statistics and vertical error correlation. For GPS, the best performance is obtained with 5 s clock products. These findings result from the short-timescale behavior of the onboard atomic clocks and are important given the impact of radio occultation measurements on numerical weather predictions and climate studies.
Chengli Ji, Qiankai Jin, Feilong Li, Yuyang Liu, Zhicheng Wang, Jiajia Mao, Xiaoyu Ren, Yan Xiang, Wanlin Jian, Zhenyi Chen, and Peitao Zhao
Atmos. Meas. Tech., 18, 3179–3191, https://doi.org/10.5194/amt-18-3179-2025, https://doi.org/10.5194/amt-18-3179-2025, 2025
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This study presents the humidity measurements with a synergistic algorithm combining Raman lidar, microwave radiometer, and satellite. The results from 47 sites in China show the best correlation over 0.9 concerning the radiosonde measurements. This validates the relative humidity (RH) accuracy with various data integrations. Three representative sites present the different seasonal characteristics, indicating the geographic and height influences on the RH vertical distribution.
Erlend Øydvin, Renaud Gaban, Jafet Andersson, Remco (C. Z.) van de Beek, Mareile Astrid Wolff, Nils-Otto Kitterød, Christian Chwala, and Vegard Nilsen
Atmos. Meas. Tech., 18, 2279–2293, https://doi.org/10.5194/amt-18-2279-2025, https://doi.org/10.5194/amt-18-2279-2025, 2025
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We present a novel method for classifying rain and snow by combining data from commercial microwave links (CMLs) with weather radar. We compare this to a reference method using dew point temperature for precipitation type classification. Evaluations with nearby disdrometers show that CMLs improve the classification of dry snow and rainfall, outperforming the reference method.
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025, https://doi.org/10.5194/amt-18-1961-2025, 2025
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Long-term records of plant fluorescence offer vital insights into changing vegetation activity. The GOME-2A sensor provides extensive global observations but suffers from calibration and instrument degradation, which affects data consistency. This study presents the SIFTER v3 algorithm, which effectively resolves these issues and includes other improvements, resulting in robust, accurate, and consistent GOME-2A fluorescence measurements from 2007 to 2017.
Nadia Smith and Christopher D. Barnet
Atmos. Meas. Tech., 18, 1823–1839, https://doi.org/10.5194/amt-18-1823-2025, https://doi.org/10.5194/amt-18-1823-2025, 2025
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CLIMCAPS extends the Aqua AIRS+AMSU record with retrievals from CrIS+ATMS on Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System series (JPSS-1 to JPSS-4). With “continuous”, we mean a data record that is consistent in its characterization of natural variation despite changes in source instrumentation. Here we investigate how sounding continuity can improve across the full CLIMCAPS record (2002 to the present day), spanning multiple instruments and satellites.
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech., 18, 1841–1857, https://doi.org/10.5194/amt-18-1841-2025, https://doi.org/10.5194/amt-18-1841-2025, 2025
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This study analyzes three years of wind lidar measurements to explore the dynamics of the urban planetary boundary layer in Hefei, China. Results reveal that nocturnal low-level jets are most frequent in spring and intensify in summer, significantly enhancing turbulence and shear near the surface, particularly at night. Additionally, cloud cover raises the mixing layer height by approximately 100 m at night due to the greenhouse effect but reduces it by up to 200 m in the afternoon.
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025, https://doi.org/10.5194/amt-18-1731-2025, 2025
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This paper provides a comprehensive evaluation of the quality of radar-based precipitation estimation in mountainous areas and presents a method to mitigate the main shortcomings identified. It then compares three different ensemble analysis methods that combine radar-based precipitation estimates with forecasts from an ensemble numerical weather prediction model.
Sabine Wüst, Lisa Küchelbacher, Franziska Trinkl, and Michael Bittner
Atmos. Meas. Tech., 18, 1591–1607, https://doi.org/10.5194/amt-18-1591-2025, https://doi.org/10.5194/amt-18-1591-2025, 2025
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Information on the energy transported by atmospheric gravity waves (GWs) is crucial for improving atmosphere models. Most space-based studies report the potential energy. We use Aeolus wind data to estimate the kinetic energy (density). However, the data quality is a challenge for such analyses, as the accuracy of the data is in the range of typical GW amplitudes. We find a temporal coincidence between enhanced or breaking planetary waves and enhanced gravity wave kinetic energy density.
Martin Fencl and Marc Schleiss
EGUsphere, https://doi.org/10.5194/egusphere-2025-487, https://doi.org/10.5194/egusphere-2025-487, 2025
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A novel disaggregation algorithm for commercial microwave links (CMLs), named CLEAR (CML Segments with Equal Amounts of Rain), is proposed. CLEAR utilizes a multiplicative random cascade generator to control the splitting of link segments. The evaluation performed both on virtual and real CML data shows that CLEAR outperforms a commonly used benchmark algorithm. Moreover, the stochastic nature of CLEAR allows it to represent uncertainty as an ensemble of rain rate distributions along CML paths.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
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A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Joshua Jeremias Müller, Michael Schäfer, Sophie Rosenburg, André Ehrlich, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/amt-2024-3967, https://doi.org/10.5194/amt-2024-3967, 2025
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We retrieved high-resolution maps of Arctic surface temperature and type using airborne thermal infrared imagery from the HALO-(𝒜𝒞)3 campaign. Our study highlights small-scale surface variability, complementing satellite observations. Surface temperature was retrieved via radiative transfer simulations, while surface type was classified using machine learning. Additionally, we analyzed segment sizes of each surface type, presenting results based on their distance from the sea-ice edge.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025, https://doi.org/10.5194/amt-18-1269-2025, 2025
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This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.
Linda Megner, Jörg Gumbel, Ole Martin Christensen, Björn Linder, Donal Patrick Murtagh, Nickolay Ivchenko, Lukas Krasauskas, Jonas Hedin, Joachim Dillner, Gabriel Giono, Georgi Olentsenko, Louis Kern, and Jacek Stegman
EGUsphere, https://doi.org/10.5194/egusphere-2025-265, https://doi.org/10.5194/egusphere-2025-265, 2025
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The MATS satellite mission studies atmospheric gravity waves, crucial for momentum transport between atmospheric layers. Launched in November 2022, MATS uses a limb-viewing telescope to capture high-resolution images of Noctilucent clouds and airglow, visualizing wave patterns in the high atmosphere. This paper accompanies the public release of the level 1b data set, i.e. calibrated limb images. Later products will provide global maps of gravity wave properties, airglow and Noctilucent clouds.
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025, https://doi.org/10.5194/amt-18-1185-2025, 2025
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This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Réunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
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Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech., 18, 793–816, https://doi.org/10.5194/amt-18-793-2025, https://doi.org/10.5194/amt-18-793-2025, 2025
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Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
Marco Coppola, Alessandro Battaglia, Frederic Tridon, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-416, https://doi.org/10.5194/egusphere-2025-416, 2025
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The WIVERN conically scanning Doppler W-band radar, has the potential, for the first time, to map the mesoscale and synoptic variability of cloud dynamics, and precipitation microphysics. This study shows that the oblique angle of incidence will be advantageous compared to standard nadir-looking radars due to substantial clutter suppression over ocean surface. This feature will enable the detection and quantification of light and moderate precipitation, with improved proximity to the surface.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
EGUsphere, https://doi.org/10.5194/egusphere-2025-19, https://doi.org/10.5194/egusphere-2025-19, 2025
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Tropospheric gradients provide information on the moisture distribution, whereas ZTDs provide the absolute amount of moisture through integrated water vapor. When TGs are assimilated with ZTDs, it helps the model actuate the moisture fields, correcting its dynamics. In our research, we show evidence that in particular regions with very few GNSS stations, the assimilation of gradients on top of ZTDs can provide the same impact as the assimilation of only ZTDs with dense coverage of GNSS stations.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 18, 471–485, https://doi.org/10.5194/amt-18-471-2025, https://doi.org/10.5194/amt-18-471-2025, 2025
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground–airborne synergy between the two instruments yielded optimal sounding results.
Shuai Zhang, Haoran Li, and Dmitri Moisseev
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-194, https://doi.org/10.5194/amt-2024-194, 2025
Revised manuscript accepted for AMT
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The data quality of weather radar near coastlines can be affected by echoes from ships, and this interference is exacerbated when pulse compression technology is used. This study developed a hybrid ship clutter identification algorithm based on artificial intelligence and heuristic criteria, effectively mitigating the issue. The successful reproduction of ship tracks in the Gulf of Finland supports this conclusion.
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
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This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
Luuk D. van der Valk, Oscar K. Hartogensis, Miriam Coenders-Gerrits, Rolf W. Hut, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2974, https://doi.org/10.5194/egusphere-2024-2974, 2025
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Yunfan Yang, Wei Han, Haofei Sun, Jun Li, Jiapeng Yan, and Zhiqiu Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-175, https://doi.org/10.5194/amt-2024-175, 2024
Revised manuscript accepted for AMT
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Our research improves satellite-based precipitation monitoring by using deep learning to reconstruct radar observations from passive microwave radiances. Active radar is costly, so we focus on a more accessible approach. Using data from the FengYun-3G satellite, we successfully tracked severe weather like Typhoon Khanun and heavy rainfall in Beijing in 2023. This method enhances global precipitation data and helps better understand extreme weather.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2894, https://doi.org/10.5194/egusphere-2024-2894, 2024
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Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Ollie Lewis, Chris Brunt, Malcolm Kitchen, Neill E. Bowler, and Edmund K. Stone
EGUsphere, https://doi.org/10.5194/egusphere-2024-2273, https://doi.org/10.5194/egusphere-2024-2273, 2024
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Humidity observations are crucial for an accurate weather forecast. We propose a new way to measure humidity by measuring how radio signals from commercial aircraft are refracted by the atmosphere. Humidity affects the refractive index of air, allowing its presence to be detected. With thousands of flights in the airspace over the United Kingdom every day, there is the potential for a large increase in the number of humidity measurements for use in weather forecasting models.
Dianrun Zhao, Shanshan Du, Chu Zou, Longfei Tian, Meng Fan, Yulu Du, and Liangyun Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3118, https://doi.org/10.5194/egusphere-2024-3118, 2024
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The TanSat-2 satellite is designed for global carbon monitoring. It provides high-resolution, dual-band observations of solar-induced chlorophyll fluorescence, a key indicator of plant photosynthesis. Through simulations, we optimized the satellite's data processing and found it can retrieve this fluorescence with great accuracy. These findings suggest that TanSat-2 will enhance global monitoring of carbon cycles and vegetation health, offering valuable insights for climate change research.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Cited articles
Abkar, M. and Porte-Agel, F.: Influence of the Coriolis force on the
structure and evolution of wind turbine wakes, Phys. Rev. Fluids, 1, 063701,
https://doi.org/10.1103/PhysRevFluids.1.063701, 2016.
Ainslie, J. F.: Calculating the flow field in the wake of wind turbines,
J. Wind. Eng. Ind. Aerod., 27, 213–224, 1988.
Aitken, M. L. and Lundquist, J. K.: Utility-Scale Wind Turbine Wake
Characterization Using Nacelle-Based Long-Range Scanning Lidar, J.
Atmos. Ocean. Tech., 31, 1529–1539,
https://doi.org/10.1175/jtech-d-13-00218.1, 2014.
Aitken, M. L., Banta, R. M., Pichugina, Y. L., and Lundquist, J. K.:
Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor
Data, J. Atmos. Ocean. Tech., 31, 765–787,
https://doi.org/10.1175/jtech-d-13-00104.1, 2014.
Banta, R. M., Pichugina, Y. L., Brewer, W. A., Lundquist, J. K., Kelley, N.
D., Sandberg, S. P., Alvarez, R. J., Hardesty, R. M., and Weickmann, A. M.:
3D Volumetric Analysis of Wind Turbine Wake Properties in the Atmosphere
Using High-Resolution Doppler Lidar, J. Atmos. Ocean.
Tech., 32, 904–914, https://doi.org/10.1175/jtech-d-14-00078.1, 2015.
Barthelmie, R. J.: The effects of atmospheric stability on coastal wind
climates, Meteorol. Appl., 6, 39–47, 1998.
Barthelmie, R. J. and Jensen, L. E.: Evaluation of wind farm efficiency and
wind turbine wakes at the Nysted offshore wind farm, Wind Energy, 13,
573–586, 2010.
Barthelmie, R. J. and Pryor, S. C.: Wake model evaluation using data from
the Virtual Wakes Laboratory, Appl. Energy, 104, 834–844, 2013.
Barthelmie, R. J. and Pryor, S. C.: The impact of wind direction yaw angle
on cliff flows, Wind Energy, 21, 1254–1265, 2018.
Barthelmie, R. J. and Pryor, S. C.: Cornell Galion Scanning Lidar Data,
Version 1.0. UCAR/NCAR –- Earth Observing Laboratory, data
set, https://doi.org/10.26023/74K3-7KYB-3G03, 2019.
Barthelmie, R. J., Folkerts, L., Ormel, F., Sanderhoff, P., Eecen, P.,
Stobbe, O., and Nielsen, N. M.: Offshore wind turbine wakes measured by
SODAR, J. Atmos. Ocean. Tech., 30, 466–477, 2003.
Barthelmie, R. J., Larsen, G. C., Pryor, S. C., Jørgensen, H. E.,
Bergström, H., Schlez, W., Rados, K., Lange, B., Vølund, P.,
Neckelmann, S., Mogensen, S., Schepers, G., Hegberg, T., Folkerts, L., and
Magnusson, M.: Efficient development of offshore windfarms (ENDOW):
modelling wake and boundary layer interactions, Wind Energy, 7, 225–245,
2004.
Barthelmie, R. J., Frandsen, S. T., Nielsen, N. M., Pryor, S. C., Rethore,
P. E., and Jørgensen, H. E.: Modelling and measurements of power losses
and turbulence intensity in wind turbine wakes at Middelgrunden offshore
wind farm, Wind Energy, 10, 217–228, 2007.
Barthelmie, R. J., Pryor, S. C., Frandsen, S. T., Hansen, K., Schepers, J.
G., Rados, K., Schlez, W., Neubert, A., Jensen, L. E., and Neckelmann, S.:
Quantifying the impact of wind turbine wakes on power output at offshore
wind farms, J. Atmos. Ocean. Tech., 27, 1302–1317,
2010.
Barthelmie, R. J., Hansen, K. S., and Pryor, S. C.: Meteorological controls
on wind turbine wakes, Proc. IEEE, 101, 1010–1019, 2013.
Barthelmie, R. J., Crippa, P., Wang, H., Smith, C. M., Krishnamurthy, R.,
Choukulkar, A., Calhoun, R., Valyou, D., Marzocca, P., Matthiesen, D.,
Brown, G., and Pryor, S. C.: 3D Wind and Turbulence Characteristics of the
Atmospheric Boundary Layer, B. Am. Meteorol. Soc.,
95, 743–756, https://doi.org/10.1175/bams-d-12-00111.1, 2014.
Barthelmie, R. J., Doubrawa, P., Wang, H., Giroux, G., and Pryor, S. C.:
Effects of an escarpment on flow parameters of relevance to wind turbines,
Wind Energy, 19, 2271–2286, 2016a.
Barthelmie, R. J., Doubrawa, P., Wang, H., and Pryor, S. C.: Defining wake
characteristics from scanning and vertical full- scale lidar measurements,
J. Phys. Conf. Ser., 753, 032034, https://doi.org/10.1088/1742-6596/753/3/032034, 2016b.
Barthelmie, R. J., Pryor, S. C., Wildmann, N., and Menke, R.: Wind turbine
wake charcaterisation in complex terrain via integrated Doppler lidar data
from the Perdigao experiment, J. Phys. Conf. Ser., 1037,
052022, https://doi.org/10.1088/1742-6596/1037/5/052022, 2018.
Berg, J., Vasiljevic, N., Kelly, M., Lea, G., and Courtney, M.: Addressing
Spatial Variability of Surface-Layer Wind with Long-Range WindScanners,
J. Atmos. Ocean. Tech., 32, 518–527,
https://doi.org/10.1175/jtech-d-14-00123.1, 2015.
Bodini, N., Zardi, D., and Lundquist, J. K.: Three-dimensional structure of wind turbine wakes as measured by scanning lidar, Atmos. Meas. Tech., 10, 2881–2896, https://doi.org/10.5194/amt-10-2881-2017, 2017.
Christiansen, M. B. and Hasager, C.: Wake effects of large offshore wind
farms identified from satellite SAR, Remote Sens. Environ., 98,
251–268, 2005.
Clifton, A., Clive, P., Gottschall, J., Schlipf, D., Simley, E., Simmons,
L., and Würth, I.: IEA Wind Task 32: Wind lidar identifying and
mitigating barriers to the adoption of wind lidar, Remote Sens., 10,
406, https://doi.org/10.3390/rs10030406, 2018.
Coppin, P. A., Bradley, E. F., and Finnigan, J. J.: Measurements of flow
over an elongated ridge and its thermal stability dependence: The mean
field, Bound.-Lay. Meteor., 69, 173–199, https://doi.org/10.1007/bf00713302, 1994.
Doubrawa, P., Barthelmie, R. J., Wang, H., Pryor, S. C., and Churchfield,
M.: Wind Turbine Wake Characterization from Temporally Disjunct 3-D
Measurements, Remote Sens., 8, 939, https://doi.org/10.3390/rs8110939, 2016.
Doubrawa, P., Barthelmie, R. J., Wang, H., and Churchfield, M. J.: A
stochastic wind turbine wake model based on new metrics for wake
characterization, Wind Energy, 20, 449–463, https://doi.org/10.1002/we.2015, 2017.
Durran, D. R.: Mountain Waves and Downslope Winds, in: Atmospheric Process
over Complex Terrain,, edited by: Blumen, W., American Meteorological
Society, Boston, MA, 59–81, 1990.
El-Asha, S., Zhan, L., and Iungo, G. V.: Quantification of power losses due
to wind turbine wake interactions through SCADA, meteorological and wind
LiDAR data, Wind Energy, 20, 1823–1839, https://doi.org/10.1002/we.2123, 2017.
Emeis, S., Frank, H., and Fiedler, F.: Modification of air flow over an
escarpment – results from the Hjardemal Experiment, Bound.-Lay.
Meteor., 74, 131–161, 1995.
Fernando, H. J. S., Mann, J., Palma, J. M. L. M., Lundquist, J. K.,
Barthelmie, R. J., BeloPereira, M., Brown, W. O. J., Chow, F. K., Gerz, T.,
Hocut, C. M., Klein, P. M., Leo, L. S., Matos, J. C., Oncley, S. P., Pryor,
S. C., Bariteau, L., Bell, T. M., Bodin, I. N., Carney, M. B., Courtney, M.,
Creegan, E., Dimitrova, R., Gomes, S., Hagen, M., Hyde, O., Kigle, S.,
Krishnamurthy, R., Lopes, J. C., Mazzaro, L., Neher, J. M. T., Menke, R.,
Murphy, P., Oswald, L., Otarola-Bustos, S., Pattantyus, A. K., Rodrigues,
C., Schady, A., Sirin, N., Spuler, S., Svensson, E., Tomaszewski, J.,
Turner, D. D., van Veen, L., Vasiljevic, N., Vassalo, D., Voss, S.,
Wildmann, N., and Wang, Y.: The Perdigão: Peering into Microscale
Details of Mountain Winds, B. Am. Meteorol. Soc.,
May, 799–819, 2019.
Finnigan, J. and Belcher, S.: Flow over a hill covered with a plant canopy,
Q. J. Roy. Meteorol. Soc., 130, 1–29, 2004.
Han, X., Liu, D., Xu, C., and Shen, W. Z.: Atmospheric stability and
topography effects on wind turbine performance and wake properties in
complex terrain, Renew. Energ., 126, 640–651,
https://doi.org/10.1016/j.renene.2018.03.048, 2018.
Hunt, J. C. R., Richards, K. J., and Brighton, P. W. M.: Stably stratified
shear flow over low hills, Q. J. Roy. Meteorol.
Soc., 114, 859–886, https://doi.org/10.1002/qj.49711448203, 1988.
Iungo, G. V., Wu, Y.-T., and Porté-Agel, F.: Field measurements of wind
turbine wakes with LiDARs, J. Atmos. Ocean. Tech.,
30, 274–287, https://doi.org/10.1175/jtech-d-12-00051.1, 2013.
Jackson, P. and Hunt, J.: Turbulent wind flow over a low hill, Q.
J. Roy. Meteorol. Soc., 101, 929–955, 1975.
Jensen, N. O.: A note on wind turbine interaction, Risø National
Laboratory, Roskilde, Denmark, Risø-M-2411, 16, 1983.
Kaimal, J. C. and Finnigan, J. J.: Atmospheric Boundary Layer Flows: Their
Structure and Measurement, Oxford University Press, New York, 289 pp.,
1994.
Katic, I., Højstrup, J., and Jensen, N. O.: A simple model for cluster
efficiency, European Wind Energy Association, Rome, 407–409, 1986.
Larsen, G. C., Madsen, H. A., Thomsen, K., and Larsen, T. J.: Wake
meandering: a pragmatic approach, Wind Energy, 11, 377–395, https://doi.org/10.1002/we.267,
2008.
Letson, F., Barthelmie, R. J., Hu, W., and Pryor, S. C.: Characterizing wind gusts in complex terrain, Atmos. Chem. Phys., 19, 3797–3819, https://doi.org/10.5194/acp-19-3797-2019, 2019.
Machefaux, E., Larsen, G. C., Koblitz, T., Troldborg, N., Kelly, M. C.,
Chougule, A., Hansen, K. S., and Rodrigo, J. S.: An experimental and
numerical study of the atmospheric stability impact on wind turbine wakes,
Wind Energy, 19, 1785–1805, https://doi.org/10.1002/we.1950, 2016.
Mann, J., Angelou, N., Arnqvist, J., Callies, D., Cantero, E., Arroyo, R.
C., Courtney, M., Cuxart, J., Dellwik, E., Gottschall, J., Ivanell, S.,
Kühn, P., Lea, G., Matos, J. C., Palma, J. M. L. M., Pauscher, L.,
Peña, A., Rodrigo, J. S., Söderberg, S., Vasiljevic, N., and
Rodrigues, C. V.: Complex terrain experiments in the New European Wind
Atlas, Philos. T. R. Soc. A, 375, 20160101, https://doi.org/10.1098/rsta.2016.0101, 2017.
Menke, R., Vasiljević, N., Mann, J., and Lundquist, J. K.: Characterization of flow recirculation zones at the Perdigão site using multi-lidar measurements, Atmos. Chem. Phys., 19, 2713–2723, https://doi.org/10.5194/acp-19-2713-2019, 2019.
Mikkelsen, T., Mann, J., Courtney, M., and Sjoholm, M.: Windscanner: 3-D
wind and turbulence measurements from three steerable Doppler Lidars, in:
14th International Symposium for the Advancement of Boundary Layer Remote
Sensing, edited by: Mann, J., Bingol, F., Courtney, M., Jorgensen, H. E.,
Lindelow, P., Mikkelsen, T., Pena, A., Sjoholm, M., and Wagner, R., IOP
Conference Series-Earth and Environmental Science, 2008.
New European Wind Atlas data portal: available at:
https://perdigao.fe.up.pt/, last access: 30 August 2018.
Ohba, R., Hara, T., Nakamura, S., Ohya, Y., and Uchida, T.: Gas diffusion
over an isolated hill under neutral, stable and unstable conditions,
Atmos. Environ., 36, 5697–5707,
https://doi.org/10.1016/S1352-2310(02)00642-8, 2002.
Pauscher, L., Vasiljevic, N., Callies, D., Lea, G., Mann, J., Klaas, T.,
Hieronimus, J., Gottschall, J., Schwesig, A., and Kühn, M.: An
Inter-Comparison Study of Multi-and DBS Lidar Measurements in Complex
Terrain, Remote Sens., 8, 782, https://doi.org/10.3390/rs8090782, 2016.
Pieterse, J. E. and Harms, T. M.: CFD investigation of the atmospheric
boundary layer under different thermal stability conditions, J. Wind Eng. Ind. Aerod., 121, 82–97,
https://doi.org/10.1016/j.jweia.2013.07.014, 2013.
Politis, E. S., Prospathopoulos, J., Cabezon, D., Hansen, K. S.,
Chaviaropoulos, P. K., and Barthelmie, R. J.: Modeling wake effects in large
wind farms in complex terrain: the problem, the methods and the issues, Wind
Energy, 15, 161–182, https://doi.org/10.1002/we.481, 2012.
Pryor, S. C., Barthelmie, R. J., and Shepherd, T.: The influence of
real-world wind turbine deployments on regional climate, J.
Geophys. Res.-Atmos., 123, 5804–5826, https://doi.org/10.1029/2017JD028114, 2018.
Risan, A., Lund, J., Chang, C.-Y., and Sætran, L.: Wind in Complex
Terrain – Lidar Measurements for Evaluation of CFD Simulations, Remote
Sens., 10, 59, https://doi.org/10.3390/rs10010059, 2018.
Sanz Rodrigo, J., Chávez Arroyo, R. A., Moriarty, P., Churchfield, M.,
Kosović, B., Réthoré, P. E., Hansen, K. S., Hahmann, A.,
Mirocha, J. D., and Rife, D.: Mesoscale to microscale wind farm flow
modeling and evaluation, WIRES Energy. Environ., 6, e214, https://doi.org/10.1002/wene.214, 2017.
Smith, C. M., Barthelmie, R. J., and Pryor, S. C.: In situ observations of
the influence of a large onshore wind farm on near-surface temperature,
turbulence intensity and wind speed profiles, Environ. Res. Lett.,
8, 034006, https://doi.org/10.1088/1748-9326/8/3/034006, 2013.
Stull, R. B.: An introduction to boundary layer meteorology, Kluwer Publications Ltd, Dordrecht, 666 pp., 1988.
Torres Garcia, E., Aubrun, S., Boquet, M., Royer, P., Coupiac, O., and
Girard, N.: Wake meandering and its relationship with the incoming wind
characteristics: a statistical approach applied to long-term on-field
observations, IOP Conf. Series, J. Phys. Conf. Series, 854, 012045, https://doi.org/10.1088/1742-6596/854/1/012045, 2017.
Vasiljević, N., L. M. Palma, J. M., Angelou, N., Carlos Matos, J., Menke, R., Lea, G., Mann, J., Courtney, M., Frölen Ribeiro, L., and M. G. C. Gomes, V. M.: Perdigão 2015: methodology for atmospheric multi-Doppler lidar experiments, Atmos. Meas. Tech., 10, 3463–3483, https://doi.org/10.5194/amt-10-3463-2017, 2017.
Wang, H., Barthelmie, R. J., Clifton, A., and Pryor, S. C.: Wind
measurements from arc scans with Doppler wind lidar, J. Atmos.
Ocean. Tech. 32, 2024–2040, 2015.
Wang, H., Barthelmie, R. J., Pryor, S. C., and Brown, Gareth.: Lidar arc scan uncertainty reduction through scanning geometry optimization, Atmos. Meas. Tech., 9, 1653–1669, https://doi.org/10.5194/amt-9-1653-2016, 2016.
Whiteman, C. D. and Doran, J. C.: The relationship between overlying
synoptic-scale flows and winds within in a valley, J. Appl.
Meteorol., 32, 1669–1682, 1993.
Wildmann, N., Vasiljevic, N., and Gerz, T.: Wind turbine wake measurements with automatically adjusting scanning trajectories in a multi-Doppler lidar setup, Atmos. Meas. Tech., 11, 3801–3814, https://doi.org/10.5194/amt-11-3801-2018, 2018.
Short summary
Wakes are volumes of air with low wind speed that form downwind of wind turbines. Their properties and behaviour determine optimal turbine spacing in wind farms. We use scanning Doppler lidar to accurately and precisely measure wake characteristics at a complex terrain site in Portugal. We develop and apply an automatic processing algorithm to detect wakes and quantify their characteristics. In higher wind speeds, the wake centres are lower. Wake centres are also lower in convective conditions.
Wakes are volumes of air with low wind speed that form downwind of wind turbines. Their...
