Articles | Volume 8, issue 1
https://doi.org/10.5194/amt-8-421-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-421-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Jan 2015
Research article |
| 27 Jan 2015
The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis
Brookhaven National Laboratory, Upton, NY, USA
T. Toto
Brookhaven National Laboratory, Upton, NY, USA
D. Troyan
Brookhaven National Laboratory, Upton, NY, USA
P. E. Ciesielski
Colorado State University, Fort Collins, CO, USA
D. Holdridge
Argonne National Laboratory, Argonne, IL, USA
J. Kyrouac
Argonne National Laboratory, Argonne, IL, USA
J. Schatz
ARM Climate Research Facility, Southern Great Plains site, Billings, OK, USA
Y. Zhang
Lawrence Livermore National Laboratory, Livermore, CA, USA
Lawrence Livermore National Laboratory, Livermore, CA, USA
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We examine the lifecycle of isolated deep convective clouds (DCCs) in the Amazon rainforest. Weather radar echoes from the DCCs are tracked to evaluate their lifecycle. The DCC size and intensity increase, reach a peak, and then decrease over the DCC lifetime. Vertical profiles of air motion and mass transport from different seasons are examined to understand the transport of energy and momentum within DCC cores and to address the deficiencies in simulating DCCs using weather and climate models.
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This work compares the large-scale meteorology, cloud, aerosol, precipitation, and thermodynamics of closed- and open-cell cloud organizations using long-term observations from the astern North Atlantic. Open-cell cases are associated with cold-air outbreaks and occur in deeper boundary layers, with stronger winds and higher rain rates compared to closed-cell cases. These results offer important benchmarks for model representation of boundary layer clouds in this climatically important region.
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Uncertainties in marine boundary layer clouds arise in the presence of biomass burning aerosol, as is the case over the southeast Atlantic Ocean. Heating due to this aerosol has the potential to alter the thermodynamic profile as the aerosol is transported across the Atlantic Ocean. Radiation transfer experiments indicate local shortwave aerosol heating is ~2–8 K d−1; however uncertainties in this quantity exist due to the single-scattering albedo and back trajectories of the aerosol plume.
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Scott E. Giangrande, Zhe Feng, Michael P. Jensen, Jennifer M. Comstock, Karen L. Johnson, Tami Toto, Meng Wang, Casey Burleyson, Nitin Bharadwaj, Fan Mei, Luiz A. T. Machado, Antonio O. Manzi, Shaocheng Xie, Shuaiqi Tang, Maria Assuncao F. Silva Dias, Rodrigo A. F de Souza, Courtney Schumacher, and Scot T. Martin
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Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
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Revised manuscript under review for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Dié Wang, Roni Kobrosly, Tao Zhang, Tamanna Subba, Susan van den Heever, Siddhant Gupta, and Michael Jensen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2436, https://doi.org/10.5194/egusphere-2024-2436, 2024
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We use a new method to understand how tiny particles in the air, called aerosols, affect rain clouds in the Houston-Galveston area. Aerosols generally do not make these clouds grow much taller, with an average height increase of about 1 km under certain conditions. However, their effects on rainfall strength and cloud expansion are less certain. Clouds influenced by sea breezes show a stronger aerosol impact, possibly due to unaccounted factors like vertical winds in near-surface layers.
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Preprint under review for GMD
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Siddhant Gupta, Dié Wang, Scott E. Giangrande, Thiago S. Biscaro, and Michael P. Jensen
Atmos. Chem. Phys., 24, 4487–4510, https://doi.org/10.5194/acp-24-4487-2024, https://doi.org/10.5194/acp-24-4487-2024, 2024
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We examine the lifecycle of isolated deep convective clouds (DCCs) in the Amazon rainforest. Weather radar echoes from the DCCs are tracked to evaluate their lifecycle. The DCC size and intensity increase, reach a peak, and then decrease over the DCC lifetime. Vertical profiles of air motion and mass transport from different seasons are examined to understand the transport of energy and momentum within DCC cores and to address the deficiencies in simulating DCCs using weather and climate models.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022, https://doi.org/10.5194/acp-22-9129-2022, 2022
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Michael P. Jensen, Virendra P. Ghate, Dié Wang, Diana K. Apoznanski, Mary J. Bartholomew, Scott E. Giangrande, Karen L. Johnson, and Mandana M. Thieman
Atmos. Chem. Phys., 21, 14557–14571, https://doi.org/10.5194/acp-21-14557-2021, https://doi.org/10.5194/acp-21-14557-2021, 2021
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This work compares the large-scale meteorology, cloud, aerosol, precipitation, and thermodynamics of closed- and open-cell cloud organizations using long-term observations from the astern North Atlantic. Open-cell cases are associated with cold-air outbreaks and occur in deeper boundary layers, with stronger winds and higher rain rates compared to closed-cell cases. These results offer important benchmarks for model representation of boundary layer clouds in this climatically important region.
Yang Wang, Guangjie Zheng, Michael P. Jensen, Daniel A. Knopf, Alexander Laskin, Alyssa A. Matthews, David Mechem, Fan Mei, Ryan Moffet, Arthur J. Sedlacek, John E. Shilling, Stephen Springston, Amy Sullivan, Jason Tomlinson, Daniel Veghte, Rodney Weber, Robert Wood, Maria A. Zawadowicz, and Jian Wang
Atmos. Chem. Phys., 21, 11079–11098, https://doi.org/10.5194/acp-21-11079-2021, https://doi.org/10.5194/acp-21-11079-2021, 2021
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This paper reports the vertical profiles of trace gas and aerosol properties over the eastern North Atlantic, a region of persistent but diverse subtropical marine boundary layer (MBL) clouds. We examined the key processes that drive the cloud condensation nuclei (CCN) population and how it varies with season and synoptic conditions. This study helps improve the model representation of the aerosol processes in the remote MBL, reducing the simulated aerosol indirect effects.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Thiago S. Biscaro, Luiz A. T. Machado, Scott E. Giangrande, and Michael P. Jensen
Atmos. Chem. Phys., 21, 6735–6754, https://doi.org/10.5194/acp-21-6735-2021, https://doi.org/10.5194/acp-21-6735-2021, 2021
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This study suggests that there are two distinct modes driving diurnal precipitating convective clouds over the central Amazon. In the wet season, local factors such as turbulence and nighttime cloud coverage are the main controls of daily precipitation, while dry-season daily precipitation is modulated primarily by the mesoscale convective pattern. The results imply that models and parameterizations must consider different formulations based on the seasonal cycle to correctly resolve convection.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
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A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
Hsi-Yen Ma, Chen Zhou, Yunyan Zhang, Stephen A. Klein, Mark D. Zelinka, Xue Zheng, Shaocheng Xie, Wei-Ting Chen, and Chien-Ming Wu
Geosci. Model Dev., 14, 73–90, https://doi.org/10.5194/gmd-14-73-2021, https://doi.org/10.5194/gmd-14-73-2021, 2021
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We propose an experimental design of a suite of multi-year, short-term hindcasts and compare them with corresponding observations or measurements for periods based on different weather and climate phenomena. This atypical way of evaluating model performance is particularly useful and beneficial, as these hindcasts can give scientists a robust picture of modeled precipitation, and cloud and radiation processes from their diurnal variation to year-to-year variability.
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, https://doi.org/10.5194/gmd-13-4443-2020, 2020
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This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single-column model, is much faster to run than the full climate model, and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single-column model can directly benefit the field.
Allison B. Marquardt Collow, Mark A. Miller, Lynne C. Trabachino, Michael P. Jensen, and Meng Wang
Atmos. Chem. Phys., 20, 10073–10090, https://doi.org/10.5194/acp-20-10073-2020, https://doi.org/10.5194/acp-20-10073-2020, 2020
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Uncertainties in marine boundary layer clouds arise in the presence of biomass burning aerosol, as is the case over the southeast Atlantic Ocean. Heating due to this aerosol has the potential to alter the thermodynamic profile as the aerosol is transported across the Atlantic Ocean. Radiation transfer experiments indicate local shortwave aerosol heating is ~2–8 K d−1; however uncertainties in this quantity exist due to the single-scattering albedo and back trajectories of the aerosol plume.
Francesca Gallo, Janek Uin, Stephen Springston, Jian Wang, Guangjie Zheng, Chongai Kuang, Robert Wood, Eduardo B. Azevedo, Allison McComiskey, Fan Mei, Adam Theisen, Jenni Kyrouac, and Allison C. Aiken
Atmos. Chem. Phys., 20, 7553–7573, https://doi.org/10.5194/acp-20-7553-2020, https://doi.org/10.5194/acp-20-7553-2020, 2020
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Continuous high-time-resolution ambient data can include periods when aerosol properties do not represent regional aerosol processes due to high-concentration local events. We develop a novel aerosol mask at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) facility in the eastern North Atlantic (ENA). We use two ground sites to validate the mask, include a comparison with aircraft overflights, and provide guidance to increase data quality at ENA and other locations.
Qi Tang, Stephen A. Klein, Shaocheng Xie, Wuyin Lin, Jean-Christophe Golaz, Erika L. Roesler, Mark A. Taylor, Philip J. Rasch, David C. Bader, Larry K. Berg, Peter Caldwell, Scott E. Giangrande, Richard B. Neale, Yun Qian, Laura D. Riihimaki, Charles S. Zender, Yuying Zhang, and Xue Zheng
Geosci. Model Dev., 12, 2679–2706, https://doi.org/10.5194/gmd-12-2679-2019, https://doi.org/10.5194/gmd-12-2679-2019, 2019
Tao Zhang, Minghua Zhang, Wuyin Lin, Yanluan Lin, Wei Xue, Haiyang Yu, Juanxiong He, Xiaoge Xin, Hsi-Yen Ma, Shaocheng Xie, and Weimin Zheng
Geosci. Model Dev., 11, 5189–5201, https://doi.org/10.5194/gmd-11-5189-2018, https://doi.org/10.5194/gmd-11-5189-2018, 2018
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Tuning of uncertain parameters in global atmospheric general circulation models has extreme computational cost. In this study, we provide an automatic tuning method by combining an auto-optimization algorithm with hindcasts to improve climate simulations in CAM5. The tuning improved the overall performance of a well-calibrated model by about 10 %. The computational cost of the entire auto-tuning procedure is just equivalent to a single 20-year simulation of CAM5.
Guangjie Zheng, Yang Wang, Allison C. Aiken, Francesca Gallo, Michael P. Jensen, Pavlos Kollias, Chongai Kuang, Edward Luke, Stephen Springston, Janek Uin, Robert Wood, and Jian Wang
Atmos. Chem. Phys., 18, 17615–17635, https://doi.org/10.5194/acp-18-17615-2018, https://doi.org/10.5194/acp-18-17615-2018, 2018
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Here, we elucidate the key processes that drive marine boundary layer (MBL) aerosol size distribution in the eastern North Atlantic (ENA) using long-term measurements. The governing equations of particle concentration are established for different modes. Particles entrained from the free troposphere represent the major source of MBL cloud condensation nuclei (CCN), contributing both directly to CCN population and indirectly by supplying Aitken-mode particles that grow to CCN in the MBL.
Kai Zhang, Philip J. Rasch, Mark A. Taylor, Hui Wan, Ruby Leung, Po-Lun Ma, Jean-Christophe Golaz, Jon Wolfe, Wuyin Lin, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon, Hailong Wang, Yun Qian, Qi Tang, Peter Caldwell, and Shaocheng Xie
Geosci. Model Dev., 11, 1971–1988, https://doi.org/10.5194/gmd-11-1971-2018, https://doi.org/10.5194/gmd-11-1971-2018, 2018
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The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations for sea level rise projection. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model.
Luiz A. T. Machado, Alan J. P. Calheiros, Thiago Biscaro, Scott Giangrande, Maria A. F. Silva Dias, Micael A. Cecchini, Rachel Albrecht, Meinrat O. Andreae, Wagner F. Araujo, Paulo Artaxo, Stephan Borrmann, Ramon Braga, Casey Burleyson, Cristiano W. Eichholz, Jiwen Fan, Zhe Feng, Gilberto F. Fisch, Michael P. Jensen, Scot T. Martin, Ulrich Pöschl, Christopher Pöhlker, Mira L. Pöhlker, Jean-François Ribaud, Daniel Rosenfeld, Jaci M. B. Saraiva, Courtney Schumacher, Ryan Thalman, David Walter, and Manfred Wendisch
Atmos. Chem. Phys., 18, 6461–6482, https://doi.org/10.5194/acp-18-6461-2018, https://doi.org/10.5194/acp-18-6461-2018, 2018
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This overview discuss the main precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin. It presents a review of the knowledge acquired about cloud processes and rainfall formation in Amazonas. In addition, this study provides a characterization of the seasonal variation and rainfall sensitivities to topography, surface cover, and aerosol concentration. Airplane measurements were evaluated to characterize and contrast cloud microphysical properties.
Scott E. Giangrande, Zhe Feng, Michael P. Jensen, Jennifer M. Comstock, Karen L. Johnson, Tami Toto, Meng Wang, Casey Burleyson, Nitin Bharadwaj, Fan Mei, Luiz A. T. Machado, Antonio O. Manzi, Shaocheng Xie, Shuaiqi Tang, Maria Assuncao F. Silva Dias, Rodrigo A. F de Souza, Courtney Schumacher, and Scot T. Martin
Atmos. Chem. Phys., 17, 14519–14541, https://doi.org/10.5194/acp-17-14519-2017, https://doi.org/10.5194/acp-17-14519-2017, 2017
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The Amazon forest is the largest tropical rain forest on the planet, featuring
prolific and diverse cloud conditions. The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment was motivated by demands to gain a better understanding of aerosol and cloud interactions on climate and the global circulation. The routine DOE ARM observations from this 2-year campaign are summarized to help quantify controls on clouds and precipitation over this undersampled region.
Shuaiqi Tang, Shaocheng Xie, Yunyan Zhang, Minghua Zhang, Courtney Schumacher, Hannah Upton, Michael P. Jensen, Karen L. Johnson, Meng Wang, Maike Ahlgrimm, Zhe Feng, Patrick Minnis, and Mandana Thieman
Atmos. Chem. Phys., 16, 14249–14264, https://doi.org/10.5194/acp-16-14249-2016, https://doi.org/10.5194/acp-16-14249-2016, 2016
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Data observed during the Green Ocean Amazon (GoAmazon2014/5) experiment are used to derive the large-scale fields in this study. The morning propagating convective systems are active during the wet season but rare during the dry season. The afternoon convections are active in both seasons, with heating and moistening in the lower level corresponding to the vertical convergence of eddy fluxes. Case study shows distinguish large-scale environments for three types of convective systems in Amazonia.
Michael P. Jensen, Donna J. Holdridge, Petteri Survo, Raisa Lehtinen, Shannon Baxter, Tami Toto, and Karen L. Johnson
Atmos. Meas. Tech., 9, 3115–3129, https://doi.org/10.5194/amt-9-3115-2016, https://doi.org/10.5194/amt-9-3115-2016, 2016
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An intercomparison of Vaisala's latest-generation radiosonde RS41 and the widely used RS92 was performed in north-central Oklahoma, USA, during June 2014. The results indicate that for the conditions observed during the intercomparison the measurements of pressure, temperature, humidity, and winds agree to within the manufacturer-specified combined uncertainties. Some important exceptions were noted when exiting liquid cloud layers where evaporative cooling has less impact for RS41 measurements.
B. A. Drewniak, U. Mishra, J. Song, J. Prell, and V. R. Kotamarthi
Biogeosciences, 12, 2119–2129, https://doi.org/10.5194/bg-12-2119-2015, https://doi.org/10.5194/bg-12-2119-2015, 2015
B. Drewniak, J. Song, J. Prell, V. R. Kotamarthi, and R. Jacob
Geosci. Model Dev., 6, 495–515, https://doi.org/10.5194/gmd-6-495-2013, https://doi.org/10.5194/gmd-6-495-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
The role of time averaging of eddy covariance fluxes on water use efficiency dynamics of maize
Number- and size-controlled rainfall regimes in the Netherlands: physical reality or statistical mirage?
The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 2: First measurements of the emissivity of water in the far-infrared
Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics
Hybrid instrument network optimization for air quality monitoring
Double moment normalization of hail size number distributions over Switzerland
Objective identification of pressure wave events from networks of 1 Hz, high-precision sensors
Adjustment of 1 min rain gauge time series using co-located drop size distribution and wind speed measurements
Estimating turbulent energy flux vertical profiles from uncrewed aircraft system measurements: exemplary results for the MOSAiC campaign
Gap filling of turbulent heat fluxes over rice–wheat rotation croplands using the random forest model
Estimation of raindrop size distribution and rain rate with infrared surveillance camera in dark conditions
Estimates of the spatially complete, observational-data-driven planetary boundary layer height over the contiguous United States
Detection of turbulence occurrences from temperature, pressure, and position measurements under superpressure balloons
Inferring surface energy fluxes using drone data assimilation in large eddy simulations
Raindrop size distribution (DSD) during the passage of tropical cyclone Nivar: effect of measuring principle and wind on DSDs and retrieved rain integral and polarimetric parameters from impact and laser disdrometers
Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC)
Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC
Considerations for improving data quality of thermo-hygrometer sensors on board unmanned aerial systems for planetary boundary layer research
Characteristics of the derived energy dissipation rate using the 1 Hz commercial aircraft quick access recorder (QAR) data
Low-level buoyancy as a tool to understand boundary layer transitions
Estimating vertical wind power density using tower observation and empirical models over varied desert steppe terrain in northern China
Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems
Wind speed and direction estimation from wave spectra using deep learning
Options to correct local turbulent flux measurements for large-scale fluxes using an approach based on large-eddy simulation
Global ensemble of temperatures over 1850–2018: quantification of uncertainties in observations, coverage, and spatial modeling (GETQUOCS)
Reconstruction of the mass and geometry of snowfall particles from multi-angle snowflake camera (MASC) images
A new zenith hydrostatic delay model for real-time retrievals of GNSS-PWV
Sampling error in aircraft flux measurements based on a high-resolution large eddy simulation of the marine boundary layer
Separation of convective and stratiform precipitation using polarimetric radar data with a support vector machine method
An approach to minimize aircraft motion bias in multi-hole probe wind measurements made by small unmanned aerial systems
Interpolation uncertainty of atmospheric temperature profiles
Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification
An improved post-processing technique for automatic precipitation gauge time series
Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR)
Atmospheric condition identification in multivariate data through a metric for total variation
Identifying persistent temperature inversion events in a subalpine basin using radon-222
Evaluation of wake influence on high-resolution balloon-sonde measurements
Improving the mean and uncertainty of ultraviolet multi-filter rotating shadowband radiometer in situ calibration factors: utilizing Gaussian process regression with a new method to estimate dynamic input uncertainty
Empirical high-resolution wind field and gust model in mountainous and hilly terrain based on the dense WegenerNet station networks
Performance of the FMI cosine error correction method for the Brewer spectral UV measurements
Computational efficiency for the surface renewal method
Raindrop fall velocities from an optical array probe and 2-D video disdrometer
Novel approaches to estimating the turbulent kinetic energy dissipation rate from low- and moderate-resolution velocity fluctuation time series
Smoothing data series by means of cubic splines: quality of approximation and introduction of a repeating spline approach
Data-driven clustering of rain events: microphysics information derived from macro-scale observations
Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera
Dust opacities inside the dust devil column in the Taklimakan Desert
Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring
Ensemble mean density and its connection to other microphysical properties of falling snow as observed in Southern Finland
An automated nowcasting model of significant instability events in the flight terminal area of Rio de Janeiro, Brazil
Arun Rao Karimindla, Shweta Kumari, Saipriya S R, Syam Chintala, and BVN P. Kambhammettu
Atmos. Meas. Tech., 17, 5477–5490, https://doi.org/10.5194/amt-17-5477-2024, https://doi.org/10.5194/amt-17-5477-2024, 2024
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This study investigates the role of the averaging period of eddy covariance fluxes on the energy balance ratio and further propagation into water use efficiency dynamics. Application was demonstrated on a maize field considering EC flux data. We found that the time averages of EC fluxes that yield the most effective EBR are at 45 and 60 min. The 30 min averaging period was insufficient to capture low-frequency fluxes. Time averaging of EC fluxes needs to be performed based on crop growth stage.
Marc Schleiss
Atmos. Meas. Tech., 17, 4789–4802, https://doi.org/10.5194/amt-17-4789-2024, https://doi.org/10.5194/amt-17-4789-2024, 2024
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Research is conducted to identify special rainfall patterns in the Netherlands using multiple types of rainfall sensors. A total of eight potentially unique events are analyzed, considering both the number and size of raindrops. However, no clear evidence supporting the existence of a special rainfall regime could be found. The results highlight the challenges in experimentally confirming well-established theoretical ideas in the field of precipitation sciences.
Laura Warwick, Jonathan E. Murray, and Helen Brindley
Atmos. Meas. Tech., 17, 4777–4787, https://doi.org/10.5194/amt-17-4777-2024, https://doi.org/10.5194/amt-17-4777-2024, 2024
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We describe a method for measuring the emissivity of natural surfaces using data from the new Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument. We demonstrate our method by making measurements of the emissivity of water. We then compare our results to the emissivity predicted using a model and find good agreement. The observations from FINESSE are novel because they allow us to determine surface emissivity at longer wavelengths than have been routinely measured before.
Jairo M. Valdivia, José Luis Flores-Rojas, Josep J. Prado, David Guizado, Elver Villalobos-Puma, Stephany Callañaupa, and Yamina Silva-Vidal
Atmos. Meas. Tech., 17, 2295–2316, https://doi.org/10.5194/amt-17-2295-2024, https://doi.org/10.5194/amt-17-2295-2024, 2024
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In this study, we explored hailstorms in the Central Andes of Peru. We used historical records and radar measurements to understand the frequency, timing, and characteristics of these hail events. Our research found a trend of decreasing hail frequency, probably due to anthropogenic climate change. Understanding these weather patterns is critical for local communities, as it can help improve weather forecasts and manage risks related to these potentially destructive events.
Nishant Ajnoti, Hemant Gehlot, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 17, 1651–1664, https://doi.org/10.5194/amt-17-1651-2024, https://doi.org/10.5194/amt-17-1651-2024, 2024
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This research focuses on the optimal placement of hybrid instruments (sensors and monitors) to maximize satisfaction function considering population, PM2.5 concentration, budget, and other factors. Two algorithms are developed in this study: a genetic algorithm and a greedy algorithm. We tested these algorithms on various regions. The insights of this work aid in quantitative placement of air quality monitoring instruments in large cities, moving away from ad hoc approaches.
Alfonso Ferrone, Jérôme Kopp, Martin Lainer, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-2, https://doi.org/10.5194/amt-2024-2, 2024
Revised manuscript accepted for AMT
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Estimates of hail size have been collected by a network of hail sensors, installed in three regions of Switzerland, since September 2018. In this study, we use a technique called “double moment normalization” to model the distribution of diameter sizes. The parameters of the method have been defined over 70 % of the dataset, and testes over the remaining 30 %. An independent distribution of hail sizes, collected by a drone, has also been used to evaluate the method.
Luke R. Allen, Sandra E. Yuter, Matthew A. Miller, and Laura M. Tomkins
Atmos. Meas. Tech., 17, 113–134, https://doi.org/10.5194/amt-17-113-2024, https://doi.org/10.5194/amt-17-113-2024, 2024
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We present a data set of high-precision surface air pressure observations and a method for detecting wave signals from the time series of pressure. A wavelet-based method is used to find wave signals at specific times and wave periods. From networks of pressure sensors spaced tens of kilometers apart, the wave phase speed and direction are estimated. Examples of wave events and their meteorological context are shown using radar data, weather balloon data, and other surface weather observations.
Arianna Cauteruccio, Mattia Stagnaro, Luca G. Lanza, and Pak-Wai Chan
Atmos. Meas. Tech., 16, 4155–4163, https://doi.org/10.5194/amt-16-4155-2023, https://doi.org/10.5194/amt-16-4155-2023, 2023
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Adjustments for the wind-induced bias of traditional rainfall gauges are applied to data from the Hong Kong Observatory using numerical simulation results. An optical disdrometer allows us to infer the collection efficiency of the rainfall gauge. Due to the local climatology, adjustments are limited but result in a significant amount of available freshwater resources that would be missing from the calculated hydrological budget of the region should the adjustments be neglected.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
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This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Jianbin Zhang, Zexia Duan, Shaohui Zhou, Yubin Li, and Zhiqiu Gao
Atmos. Meas. Tech., 16, 2197–2207, https://doi.org/10.5194/amt-16-2197-2023, https://doi.org/10.5194/amt-16-2197-2023, 2023
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In this paper, we used a random forest model to fill the observation gaps of the fluxes measured during 2015–2019. We found that the net radiation was the most important input variable. And we justified the reliability of the model. Further, it was revealed that the model performed better after relative humidity was removed from the input. Lastly, we compared the results of the model with those of three other machine learning models, and we found that the model outperformed all of them.
Jinwook Lee, Jongyun Byun, Jongjin Baik, Changhyun Jun, and Hyeon-Joon Kim
Atmos. Meas. Tech., 16, 707–725, https://doi.org/10.5194/amt-16-707-2023, https://doi.org/10.5194/amt-16-707-2023, 2023
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Our study addresses raindrop size distribution and rain rate by extracting rain streaks using a k-nearest-neighbor-based algorithm, estimating rainfall intensity using raindrop size distribution based on physical optics analysis, and verifying the estimated raindrop size distribution using a disdrometer. Experimentation demonstrated the possibility of estimating an image-based raindrop size distribution and rain rate obtained based on such low-cost equipment in dark conditions.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
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Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Richard Wilson, Clara Pitois, Aurélien Podglajen, Albert Hertzog, Milena Corcos, and Riwal Plougonven
Atmos. Meas. Tech., 16, 311–330, https://doi.org/10.5194/amt-16-311-2023, https://doi.org/10.5194/amt-16-311-2023, 2023
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Strateole-2 is an French–US initiative designed to study atmospheric events in the tropical upper troposphere–lower stratosphere. In this work, data from several superpressure balloons, capable of staying aloft at an altitude of 18–20 km for over 3 months, were used. The present article describes methods to detect the occurrence of atmospheric turbulence – one efficient process impacting the properties of the atmosphere composition via stirring and mixing.
Norbert Pirk, Kristoffer Aalstad, Sebastian Westermann, Astrid Vatne, Alouette van Hove, Lena Merete Tallaksen, Massimo Cassiani, and Gabriel Katul
Atmos. Meas. Tech., 15, 7293–7314, https://doi.org/10.5194/amt-15-7293-2022, https://doi.org/10.5194/amt-15-7293-2022, 2022
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In this study, we show how sparse and noisy drone measurements can be combined with an ensemble of turbulence-resolving wind simulations to estimate uncertainty-aware surface energy exchange. We demonstrate the feasibility of this drone data assimilation framework in a series of synthetic and real-world experiments. This new framework can, in future, be applied to estimate energy and gas exchange in heterogeneous landscapes more representatively than conventional methods.
Basivi Radhakrishna
Atmos. Meas. Tech., 15, 6705–6722, https://doi.org/10.5194/amt-15-6705-2022, https://doi.org/10.5194/amt-15-6705-2022, 2022
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Raindrop size distributions (DSDs) measured by various types of disdrometers are different in the same environmental conditions. The mass-weighted mean diameter (Dm) measured from JWD is larger, and ZDR is smaller than LPM and PARSIVEL due to the resonance effect at X-band frequency. The effect of wind on DSD measured by various disdrometers is not uniform in different regions of a tropical cyclone.
Katarzyna Ośródka, Irena Otop, and Jan Szturc
Atmos. Meas. Tech., 15, 5581–5597, https://doi.org/10.5194/amt-15-5581-2022, https://doi.org/10.5194/amt-15-5581-2022, 2022
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The quality control of sub-hourly rain gauge data is a challenging task due to the high variability and low spatial consistency of the data. We developed an innovative approach to the quality control of telemetric rain gauge data focused on assessing the reliability of individual observations. Our scheme employs weather radar data to detect erroneous rain gauge measurements and to assess the data reliability. The scheme is used operationally by the Polish meteorological and hydrological service.
Gina Jozef, John Cassano, Sandro Dahlke, and Gijs de Boer
Atmos. Meas. Tech., 15, 4001–4022, https://doi.org/10.5194/amt-15-4001-2022, https://doi.org/10.5194/amt-15-4001-2022, 2022
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During the MOSAiC expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 uncrewed aircraft system. These data were used to identify the best method for atmospheric boundary layer height detection by comparing visually identified subjective boundary layer height to that identified by several objective automated detection methods. The results show a bulk Richardson number-based approach gives the best estimate of boundary layer height.
Antonio R. Segales, Phillip B. Chilson, and Jorge L. Salazar-Cerreño
Atmos. Meas. Tech., 15, 2607–2621, https://doi.org/10.5194/amt-15-2607-2022, https://doi.org/10.5194/amt-15-2607-2022, 2022
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The mitigation of undesired contamination, sensor characterization, and signal conditioning and restoration is crucial to improve the reliability of the weather unmanned aerial system (UAS) deliverables. This study presents an overview of the general considerations and procedures to compensate for slow sensor response and other sources of error for temperature and humidity measurements collected using a UAS.
Soo-Hyun Kim, Jeonghoe Kim, Jung-Hoon Kim, and Hye-Yeong Chun
Atmos. Meas. Tech., 15, 2277–2298, https://doi.org/10.5194/amt-15-2277-2022, https://doi.org/10.5194/amt-15-2277-2022, 2022
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The cube root of the energy dissipation rate (EDR), as a standard reporting metric of atmospheric turbulence, is estimated using 1 Hz commercial quick access recorder data from Korean-based national air carriers with two different types of aircraft. Various EDRs are estimated using zonal, meridional, and derived vertical wind components and the derived equivalent vertical gust. Characteristics of the observed EDR estimates using 1 Hz flight data are examined to observe strong turbulence cases.
Francesca M. Lappin, Tyler M. Bell, Elizabeth A. Pillar-Little, and Phillip B. Chilson
Atmos. Meas. Tech., 15, 1185–1200, https://doi.org/10.5194/amt-15-1185-2022, https://doi.org/10.5194/amt-15-1185-2022, 2022
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This study evaluates how a classically defined variable, air parcel buoyancy, can be used to interpret transitions in the atmospheric boundary layer (ABL). To capture the high-resolution variations, remotely piloted aircraft systems are used to collect data in two field campaigns. This paper finds that buoyancy has distinct evolutions prior to low-level jet and convective initiation cases. Additionally, buoyancy mixes well to act as an ABL height indicator comparable to other methods.
Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li
Atmos. Meas. Tech., 15, 757–773, https://doi.org/10.5194/amt-15-757-2022, https://doi.org/10.5194/amt-15-757-2022, 2022
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Our research has determined the possible relationship between Weibull natural wind mesoscale parameter c and shape factor k with height under the conditions of a desert steppe terrain in northern China, which has great potential in wind power generation. We have gained an enhanced understanding of the seasonal changes in the surface roughness of the desert grassland and the changes in the incoming wind direction.
Xinhua Zhou, Tian Gao, Eugene S. Takle, Xiaojie Zhen, Andrew E. Suyker, Tala Awada, Jane Okalebo, and Jiaojun Zhu
Atmos. Meas. Tech., 15, 95–115, https://doi.org/10.5194/amt-15-95-2022, https://doi.org/10.5194/amt-15-95-2022, 2022
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Air temperature from sonic temperature and air moisture has been used without an exact equation. We present an exact equation of such air temperature for closed-path eddy-covariance flux measurements. Air temperature from this equation is equivalent to sonic temperature in its accuracy and frequency response. It is a choice for advanced flux topics because, with it, thermodynamic variables in the flux measurements can be temporally synchronized and spatially matched at measurement scales.
Haoyu Jiang
Atmos. Meas. Tech., 15, 1–9, https://doi.org/10.5194/amt-15-1-2022, https://doi.org/10.5194/amt-15-1-2022, 2022
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Sea surface wind and waves are important ocean parameters that can be continuously observed by meteorological buoys. Meteorological buoys are sparse in the ocean due to their high cost of deployment and maintenance. In contrast, low-cost compact wave buoys are suited for deployment in large numbers. Although wave buoys are not designed for wind measurement, we found that deep learning can estimate wind from wave measurements accurately, making wave buoys a good-quality data source for sea wind.
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021, https://doi.org/10.5194/amt-14-7835-2021, 2021
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Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.
Maryam Ilyas, Douglas Nychka, Chris Brierley, and Serge Guillas
Atmos. Meas. Tech., 14, 7103–7121, https://doi.org/10.5194/amt-14-7103-2021, https://doi.org/10.5194/amt-14-7103-2021, 2021
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Instrumental temperature records are fundamental to climate science. There are spatial gaps in the distribution of these measurements across the globe. This lack of spatial coverage introduces coverage error. In this research, a methodology is developed and used to quantify the coverage errors. It results in a data product that, for the first time, provides a full description of both the spatial coverage uncertainties along with the uncertainties in the modeling of these spatial gaps.
Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Longjiang Li, Suqin Wu, Kefei Zhang, Xiaoming Wang, Wang Li, Zhen Shen, Dantong Zhu, Qimin He, and Moufeng Wan
Atmos. Meas. Tech., 14, 6379–6394, https://doi.org/10.5194/amt-14-6379-2021, https://doi.org/10.5194/amt-14-6379-2021, 2021
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The zenith hydrostatic delay (ZHD) derived from blind models are of low accuracy, especially in mid- and high-latitude regions. To address this issue, the ratio of the ZHD to zenith total delay (ZTD) is firstly investigated; then, based on the relationship between the ZHD and ZTD, a new ZHD model was developed using the back propagation artificial neural network (BP-ANN) method which took the ZTD as an input variable. The model outperforms blind models.
Grant W. Petty
Atmos. Meas. Tech., 14, 1959–1976, https://doi.org/10.5194/amt-14-1959-2021, https://doi.org/10.5194/amt-14-1959-2021, 2021
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Aircraft measurements of turbulent fluxes of matter and energy are important in field investigations of the interaction of the Earth's surface and the atmosphere. Because these measurements are of randomly fluctuating quantities, averages must be taken over longer flight tracks to reduce uncertainty. This paper investigates the relationship between track length and measurement error using a computer model simulation of a marine environment and compares the results with published theory.
Yadong Wang, Lin Tang, Pao-Liang Chang, and Yu-Shuang Tang
Atmos. Meas. Tech., 14, 185–197, https://doi.org/10.5194/amt-14-185-2021, https://doi.org/10.5194/amt-14-185-2021, 2021
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The motivation of this work is to develop a precipitation separation approach that can be implemented on those radars with fast scanning schemes. In these schemes, the higher tilt radar data are not available, which poses a challenge for the traditional approaches. This approach uses artificial intelligence, which integrates polarimetric radar variables. The quantitative precipitation estimation will benefit from the output of this algorithm.
Loiy Al-Ghussain and Sean C. C. Bailey
Atmos. Meas. Tech., 14, 173–184, https://doi.org/10.5194/amt-14-173-2021, https://doi.org/10.5194/amt-14-173-2021, 2021
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Unmanned aerial vehicles equipped with multi-hole probes are an effective approach to measure the wind vector with high spatial and temporal resolution. However, the aircraft motion must be removed from the measured signal first, a process often introducing bias due to small errors in the relative orientation of coordinates. We present an approach that has successfully been applied in post-processing, which was found to minimize the influence of aircraft motion on wind measurements.
Alessandro Fassò, Michael Sommer, and Christoph von Rohden
Atmos. Meas. Tech., 13, 6445–6458, https://doi.org/10.5194/amt-13-6445-2020, https://doi.org/10.5194/amt-13-6445-2020, 2020
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Modern radiosonde balloons fly from ground level up to the lower stratosphere and take temperature measurements. What is the uncertainty of interpolated values in the resulting atmospheric temperature profiles? To answer this question, we introduce a general statistical–mathematical model for the computation of interpolation uncertainty. Analysing more than 51 million measurements, we provide some understanding of the consequences of filling missing data with interpolated ones.
Jussi Leinonen and Alexis Berne
Atmos. Meas. Tech., 13, 2949–2964, https://doi.org/10.5194/amt-13-2949-2020, https://doi.org/10.5194/amt-13-2949-2020, 2020
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The appearance of snowflakes provides a signature of the atmospheric processes that created them. To get this information from large numbers of snowflake images, automated analysis using computer image recognition is needed. In this work, we use a neural network that learns the structure of the snowflake images to divide a snowflake dataset into classes corresponding to different sizes and structures. Unlike with most comparable methods, only minimal input from a human expert is needed.
Amber Ross, Craig D. Smith, and Alan Barr
Atmos. Meas. Tech., 13, 2979–2994, https://doi.org/10.5194/amt-13-2979-2020, https://doi.org/10.5194/amt-13-2979-2020, 2020
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The raw data derived from most automated accumulating precipitation gauges often suffer from non-precipitation-related fluctuations in the measurement of the gauge bucket weights from which the precipitation amount is determined. This noise can be caused by electrical interference, mechanical noise, and evaporation. This paper presents an automated filtering technique that builds on the principle of iteratively balancing noise to produce a clean precipitation time series.
Soo-Hyun Kim, Hye-Yeong Chun, Jung-Hoon Kim, Robert D. Sharman, and Matt Strahan
Atmos. Meas. Tech., 13, 1373–1385, https://doi.org/10.5194/amt-13-1373-2020, https://doi.org/10.5194/amt-13-1373-2020, 2020
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We retrieve the eddy dissipation rate (EDR) from the derived equivalent vertical gust included in the Aircraft Meteorological Data Relay data for more reliable and consistent observations of aviation turbulence globally with the single preferred EDR metric. We convert the DEVG to the EDR using two methods (lognormal mapping scheme and best-fit curve between EDR and DEVG), and the DEVG-derived EDRs are evaluated against in situ EDR data reported by US-operated carriers.
Nicholas Hamilton
Atmos. Meas. Tech., 13, 1019–1032, https://doi.org/10.5194/amt-13-1019-2020, https://doi.org/10.5194/amt-13-1019-2020, 2020
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The identification of atmospheric conditions within a multivariable atmospheric data set is an important step in validating emerging and existing models used to simulate wind plant flows and operational strategies. The total variation approach developed here offers a method founded in tested mathematical metrics and can be used to identify and characterize periods corresponding to quiescent conditions or specific events of interest for study or wind energy development.
Dafina Kikaj, Janja Vaupotič, and Scott D. Chambers
Atmos. Meas. Tech., 12, 4455–4477, https://doi.org/10.5194/amt-12-4455-2019, https://doi.org/10.5194/amt-12-4455-2019, 2019
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A new method was developed to identify persistent temperature inversion events in a subalpine basin using a radon-based method (RBM). By comparing with an existing pseudo-vertical temperature gradient method, the RBM was shown to be more reliable and seasonally independent. The RBM has the potential to increase the understanding of meteorological controls on air pollution episodes in complex terrain beyond the capability of contemporary atmospheric stability classification tools.
Jens Faber, Michael Gerding, Andreas Schneider, Andreas Dörnbrack, Henrike Wilms, Johannes Wagner, and Franz-Josef Lübken
Atmos. Meas. Tech., 12, 4191–4210, https://doi.org/10.5194/amt-12-4191-2019, https://doi.org/10.5194/amt-12-4191-2019, 2019
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Atmospheric measurements on rising balloons can be compromised by the balloon's wake. The aim of this study is to provide a tool for assessing the likelihood of encountering the balloon's wake at the position of the gondola. This includes an uncertainty analysis of the calculation and a retrieval of vertical winds. We find an average wake encounter probability of 28 % for a standard radiosonde. Additionally, we evaluate the influence of wake from smaller objects on turbulence measurements.
Maosi Chen, Zhibin Sun, John M. Davis, Yan-An Liu, Chelsea A. Corr, and Wei Gao
Atmos. Meas. Tech., 12, 935–953, https://doi.org/10.5194/amt-12-935-2019, https://doi.org/10.5194/amt-12-935-2019, 2019
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Combining a new dynamic uncertainty estimation method with Gaussian process regression (GP), we provide a generic and robust solution to estimate the underlying mean and uncertainty functions of time series with variable mean, noise, sampling density, and length of gaps. The GP solution was applied and validated on three UV-MFRSR Vo time series at three ground sites with improved accuracy of the smoothed time series in terms of aerosol optical depth compared with two other smoothing methods.
Christoph Schlager, Gottfried Kirchengast, and Juergen Fuchsberger
Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, https://doi.org/10.5194/amt-11-5607-2018, 2018
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In this work we further developed and evaluated an operational weather diagnostic application, the WegenerNet Wind Product Generator (WPG), and applied it to the WegenerNet Johnsbachtal (JBT), a dense meteorological station network located in a mountainous Alpine region. The WPG automatically generates gridded high-resolution wind fields in near-real time with a temporal resolution of 30 min and a spatial resolution of 100 m x 100 m.
Kaisa Lakkala, Antti Arola, Julian Gröbner, Sergio Fabian León-Luis, Alberto Redondas, Stelios Kazadzis, Tomi Karppinen, Juha Matti Karhu, Luca Egli, Anu Heikkilä, Tapani Koskela, Antonio Serrano, and José Manuel Vilaplana
Atmos. Meas. Tech., 11, 5167–5180, https://doi.org/10.5194/amt-11-5167-2018, https://doi.org/10.5194/amt-11-5167-2018, 2018
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The performance of the cosine error correction method for correcting spectral UV measurements of the Brewer spectroradiometer was studied. The correction depends on the sky radiation distribution, which can change during one spectral scan. The results showed that the correction varied between 4 and 14 %, and that the relative differences between the reference and the Brewer diminished by 10 %. The method is applicable to other instruments as long as the required input parameters are available.
Jason Kelley and Chad Higgins
Atmos. Meas. Tech., 11, 2151–2158, https://doi.org/10.5194/amt-11-2151-2018, https://doi.org/10.5194/amt-11-2151-2018, 2018
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Measuring fluxes of energy and trace gases using the surface renewal (SR) method can be economical and robust, but it requires computationally intensive calculations. Several new algorithms were written to perform the required calculations more efficiently and rapidly, and were tested with field data and computationally rigorous SR methods. These efficient algorithms facilitate expanded use of SR in atmospheric experiments, for applied monitoring, and in novel field implementations.
Viswanathan Bringi, Merhala Thurai, and Darrel Baumgardner
Atmos. Meas. Tech., 11, 1377–1384, https://doi.org/10.5194/amt-11-1377-2018, https://doi.org/10.5194/amt-11-1377-2018, 2018
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Raindrop fall velocities are important for rain rate estimation, soil erosion studies and in numerical modelling of rain formation in clouds. The assumption that the fall velocity is uniquely related to drop size is made inherently based on laboratory measurements under still air conditions from nearly 68 years ago. There have been very few measurements of drop fall speeds in natural rain under both still and turbulent wind conditions. We report on fall speed measurements in natural rain shafts.
Marta Wacławczyk, Yong-Feng Ma, Jacek M. Kopeć, and Szymon P. Malinowski
Atmos. Meas. Tech., 10, 4573–4585, https://doi.org/10.5194/amt-10-4573-2017, https://doi.org/10.5194/amt-10-4573-2017, 2017
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We propose two novel methods to estimate turbulent kinetic energy dissipation rate applicable to airborne measurements. In this way we increase robustness of the dissipation rate retrieval and extend its applicability to a wider range of data sets. The new approaches relate the predicted form of the dissipation spectrum to the mean of zero crossings of the measured velocity fluctuations. The methods are easy to implement numerically, and estimates remain unaffected by certain measurement errors.
Sabine Wüst, Verena Wendt, Ricarda Linz, and Michael Bittner
Atmos. Meas. Tech., 10, 3453–3462, https://doi.org/10.5194/amt-10-3453-2017, https://doi.org/10.5194/amt-10-3453-2017, 2017
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Cubic splines with equidistant spline sampling points are a common method in atmospheric science for the approximation of background conditions by means of filtering superimposed fluctuations from a data series. However, splines can generate considerable artificial oscillations in the background and the residuals. We introduce a repeating spline approach which is able to significantly reduce this phenomenon and to apply it to TIMED-SABER vertical temperature profiles from 2010 to 2014.
Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes
Atmos. Meas. Tech., 10, 1557–1574, https://doi.org/10.5194/amt-10-1557-2017, https://doi.org/10.5194/amt-10-1557-2017, 2017
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The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.
Christophe Praz, Yves-Alain Roulet, and Alexis Berne
Atmos. Meas. Tech., 10, 1335–1357, https://doi.org/10.5194/amt-10-1335-2017, https://doi.org/10.5194/amt-10-1335-2017, 2017
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The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling snowflakes and ice crystals. A method is proposed to automatically classify these pictures into six classes of snowflakes as well to estimate the degree of riming and to detect whether or not the particles are melting. Multinomial logistic regression is used with a manually classified
reference set. The evaluation demonstrates the good and reliable performance of the proposed technique.
Zhaopeng Luan, Yongxiang Han, Tianliang Zhao, Feng Liu, Chong Liu, Mark J. Rood, Xinghua Yang, Qing He, and Huichao Lu
Atmos. Meas. Tech., 10, 273–279, https://doi.org/10.5194/amt-10-273-2017, https://doi.org/10.5194/amt-10-273-2017, 2017
Zofia Baldysz, Grzegorz Nykiel, Andrzej Araszkiewicz, Mariusz Figurski, and Karolina Szafranek
Atmos. Meas. Tech., 9, 4861–4877, https://doi.org/10.5194/amt-9-4861-2016, https://doi.org/10.5194/amt-9-4861-2016, 2016
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In this paper two official processing strategies of GPS observations were analysed. The main purpose was to assess differences in long-term (linear trends) and short-term (oscillations) changes between these two sets of data. Investigation was based on 18-year and 16-year time series and showed that, despite the general consistency, for selected stations a change of processing strategy may have caused significant differences (compared to the uncertainties) in estimated linear trend values.
Jussi Tiira, Dmitri N. Moisseev, Annakaisa von Lerber, Davide Ori, Ali Tokay, Larry F. Bliven, and Walter Petersen
Atmos. Meas. Tech., 9, 4825–4841, https://doi.org/10.5194/amt-9-4825-2016, https://doi.org/10.5194/amt-9-4825-2016, 2016
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In this study winter measurements collected in Southern Finland are used to document microphysical properties of falling snow. It is shown that a new video imager can be used for such studies. Snow properties do vary between winters.
Gutemberg Borges França, Manoel Valdonel de Almeida, and Alessana C. Rosette
Atmos. Meas. Tech., 9, 2335–2344, https://doi.org/10.5194/amt-9-2335-2016, https://doi.org/10.5194/amt-9-2335-2016, 2016
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This paper presents a novel model, based on neural network techniques, to produce short-term and locally specific forecasts of significant instability for flights in the terminal area of Rio de Janeiro's airport, Brazil. Twelve years of data were used for neural network training/validation and test. The test showed that the proposed model can grab the physical content inside the data set, and its performance is encouraging for the first and second hours to nowcast significant instability events.
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Short summary
A major component of the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state. This manuscript describes the details of the MC3E radiosonde operations including the instrumentation, data processing and analysis of the impacts of bias correction and algorithm assumptions on the determination of forcing data sets.
A major component of the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) was a...
