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D. A. Knopf, K. R. Barry, T. A. Brubaker, L. G. Jahl, K. A., L. Jankowski, J. Li, Y. Lu, L. W. Monroe, K. A. Moore, F. A. Rivera-Adorno, K. A. Sauceda, Y. Shi, J. M. Tomlin, H. S. K. Vepuri, P. Wang, N. N. Lata, E. J. T. Levin, J. M. Creamean, T. C. J. Hill, S. China, P. A. Alpert, R. C. Moffet, N. Hiranuma, R. C. Sullivan, A. M. Fridlind, M. West, N. Riemer, A. Laskin, P. J. DeMott, and X. Liu

Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol-ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on co-located measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, that are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol-ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

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A. Gannet Hallar, Steven S. Brown, Erik Crosman, Kelley C. Barsanti, Christopher D. Cappa, Ian Faloona, Jerome Fast, Heather A. Holmes, John Horel, John Lin, Ann Middlebrook, Logan Mitchell, Jennifer Murphy, Caroline C. Womack, Viney Aneja, Munkhbayar Baasandorj, Roya Bahreini, Robert Banta, Casey Bray, Alan Brewer, Dana Caulton, Joost de Gouw, Stephan F.J. De Wekker, Delphine K. Farmer, Cassandra J. Gaston, Sebastian Hoch, Francesca Hopkins, Nakul N. Karle, James T. Kelly, Kerry Kelly, Neil Lareau, Keding Lu, Roy L. Mauldin III, Derek V. Mallia, Randal Martin, Daniel L. Mendoza, Holly J. Oldroyd, Yelena Pichugina, Kerri A. Pratt, Pablo E. Saide, Philip J. Silva, William Simpson, Britton B. Stephens, Jochen Stutz, and Amy Sullivan

Abstract

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

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Charles O. Stanier, R. Bradley Pierce, Maryam Abdi-Oskouei, Zachariah E. Adelman, Jay Al-Saadi, Hariprasad D. Alwe, Timothy H. Bertram, Gregory R. Carmichael, Megan B. Christiansen, Patricia A. Cleary, Alan C. Czarnetzki, Angela F. Dickens, Marta A. Fuoco, Dagen D. Hughes, Joseph P. Hupy, Scott J. Janz, Laura M. Judd, Donna Kenski, Matthew G. Kowalewski, Russell W. Long, Dylan B. Millet, Gordon Novak, Behrooz Roozitalab, Stephanie L. Shaw, Elizabeth A. Stone, James Szykman, Lukas Valin, Michael Vermeuel, Timothy J. Wagner, Andrew R. Whitehill, and David J. Williams

Abstract

The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multi-agency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes, the role of lake breezes, contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management, and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9–12 June, and 14–16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

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George C. Craig, Andreas H. Fink, Corinna Hoose, Tijana Janjić, Peter Knippertz, Audine Laurian, Sebastian Lerch, Bernhard Mayer, Annette Miltenberger, Robert Redl, Michael Riemer, Kirsten I. Tempest, and Volkmar Wirth

Abstract

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-year phase of our planned duration of 12 years and employ 36 doctoral and post-doctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely upscale error growth, errors associated with cloud processes, and probabilistic prediction of high impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early career scientists, and to support education, equal opportunities, and outreach, which are also described here.

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Thomas A. Green Jr., Daniel Leins, Gary M. Lackmann, James Morrow, and Jonathan Blaes

Abstract

Nearly 100 North Carolina State University students have participated in a unique, highly structured internship course conducted by the National Weather Service Forecast Office in Raleigh, NC. Here, we explore the impact that this course has had on their professional development and career trajectories. The course has now been running for 17 years, and this paper provides an update on how the course has changed over time, including an evolution of the interview process to participate in the course, the number of students enrolled each semester has systematically been lowered to allow for more individual attention, and additional experiences outside of the WFO have been added. There are benefits for the students, with about half of the students now employed by the NWS, and nearly universal praise for how the course impacted their career progression. The university benefits from the course because the course serves as a compelling selling point for the MEAS department when recruiting students and the department also ensures that the curriculum is adequately preparing potential students for the job market. Finally, the NWS gains by creating a pool of potential employees that will require less spin-up time if hired, and graduates of the NCSU program have gone on to be involved with similar student volunteer programs at their respective offices once hired.

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Emily V. Fischer, Brittany Bloodhart, Kristen Rasmussen, Ilana B. Pollack, Meredith G. Hastings, Erika Marin-Spiotta, Ankur R. Desai, Joshua P. Schwarz, Stephen Nesbitt, and Deanna Hence

Abstract

Sexual harassment in field settings brings unique challenges for prevention and response, as field research occurs outside “typical” workplaces, often in remote locations that create additional safety concerns and new team dynamics. We report on a project that has 1) trained field project participants to recognize, report, and confront sexual harassment, and 2) investigated the perceptions, attitudes, and experiences of field researchers regarding sexual harassment. Pre-campaign surveys from four major, multi-institutional, domestic and international field projects indicate that the majority of sexual harassment reported prior to the field campaigns was hostile work environment harassment, and women were more likely to be the recipients, on average reporting 2-3 incidents each. The majority of those disclosing harassment indicated that they coped with past experiences by avoiding their harasser or downplaying incidents. Of the incidences reported (47) in post-campaign surveys of the four field teams, all fell under the category of hostile work environment and included incidents of verbal, visual, and physical harassment. Women’s harassment experiences were perpetrated by men 100% of the time, and the majority of the perpetrators were in more senior positions than the victims. Men’s harassment experiences were perpetrated by a mix of women and men, and the majority came from those at the same position of seniority. Post-project surveys indicate that the training programs (taking place before the field projects) helped participants come away with more positive than negative emotions and perceptions of the training, the leadership, and their overall experiences on the field campaign.

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Xiaoduo Pan, Xuejun Guo, Xin Li, Xiaolei Niu, Xiaojuan Yang, Min Feng, Tao Che, Rui Jin, Youhua Ran, Jianwen Guo, Xiaoli Hu, and Adan Wu

Abstract

The Tibetan Plateau, as the world's third pole due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the third pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript.

The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect third pole-related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the third pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.

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Olivia VanBuskirk, Paulina Ćwik, Renee A. McPherson, Heather Lazrus, Elinor Martin, Charles Kuster, and Esther Mullens

Abstract

Heavy precipitation events and their associated flooding can have major impacts on communities and stakeholders. There is a lack of knowledge, however, about how stakeholders make decisions at the sub-seasonal to seasonal (S2S) timescales (i.e., two weeks to three months). To understand how decisions are made and S2S predictions are or can be used, the project team for “Prediction of Rainfall Extremes at Sub-seasonal to Seasonal Periods” (PRES2iP) conducted a two-day workshop in Norman, Oklahoma, during July 2018. The workshop engaged 21 professionals from environmental management and public safety communities across the contiguous United States in activities to understand their needs for S2S predictions of potential extended heavy precipitation events. Discussions and role-playing activities aimed to identify how workshop participants manage uncertainty and define extreme precipitation, the timescales over which they make key decisions, and the types of products they use currently. This collaboration with stakeholders has been an integral part of PRES2iP research and has aimed to foster actionable science. The PRES2iP team is using the information produced from this workshop to inform the development of predictive models for extended heavy precipitation events and to collaboratively design new forecast products with our stakeholders, empowering them to make more-informed decisions about potential extreme precipitation events.

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Dan Fu, Justin Small, Jaison Kurian, Yun Liu, Brian Kauffman, Abishek Gopal, Sanjiv Ramachandran, Zhi Shang, Ping Chang, Gokhan Danabasoglu, Katherine Thayer-Calder, Mariana Vertenstein, Xiaohui Ma, Hengkai Yao, Mingkui Li, Zhao Xu, Xiaopei Lin, Shaoqing Zhang, and Lixin Wu

Abstract

The development of high-resolution, fully-coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly-developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include: 1) assessing the skill of R-CESM in a multi-year, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean-atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean-atmosphere interactions. We also discuss capabilities under development such as i) regional refinement using a high-resolution ROMS nested within global CESM; and ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.

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E. RoTimi Ojo and Lynn Manaigre

Abstract

Established primarily to improve weather monitoring across the agricultural regions of the province, the Manitoba Agriculture Weather Program (MAWP) began officially in 2005 with funding from the provincial government for the establishment of a network of 28 automated weather monitoring stations. The network steadily grew to 46 stations between 2007 and 2014 as a result of partnership with local commodity and research groups. In response to the Manitoba flood of 2011, more stations were installed and the network grew to 108 weather stations in 2019. The stations are solar-powered and scheduled maintenance is conducted at each station twice per year. Weather parameters monitored include air temperature, barometric pressure, precipitation, relative humidity, soil moisture, soil temperature, solar radiation, wind speed and wind direction using research-grade sensors. The observations are transmitted via cellular telemetry every 15 minutes in the spring, summer and fall but hourly in the winter to conserve energy supply due to reduced daylight and below freezing temperatures. The data can be viewed by the public within one minute of data collection. It is used to generate agronomic-related maps such as thermal unit computation of growing degree days and corn heat units as well as disease risk maps such as Fusarium Head Blight. Beyond agriculture, the data has been used for aviation investigation and for undergraduate course instruction among other applications.

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