In the field: an interview with Roger Hanlon

Roger Hanlon is a Senior Scientist at the Marine Biological Laboratory, USA, where he investigates body patterning and colour change in cephalopods. After his undergraduate degree in 1969 at Florida State University, USA, he joined the US Army and travelled before completing his MSc (1975) and PhD (1978) at the University of Miami Rosenstiel School of Marine and Atmospheric Sciences, USA. After a NATO Postdoctoral Fellowship at the University of Cambridge, UK, in 1981, Hanlon joined the Marine Biomedical Institute, University of Texas Medical Branch, where he became a full Professor, before joining the Marine Biological Laboratory in 1995. Hanlon talks about the seminal experience in his early 20s that inspired his career and the methods and equipment he uses to study cephalopod camouflage and communication across the globe.

Exploration on the Construction of Online and Offline Blending Teaching Mode in the Introduction to Earth Science

The course “Introduction to earth science” is a basic general course integrating science and interest run by the School of Atmospheric Sciences in Chengdu University of Information Technology. It is also a public elective course for the cultivation of college students' scientific quality. With the development of Internet plus education and the promotion of information technology, the paper combines the traditional offline teaching mode with the online teaching mode adopted during the spring semester in 2020 because of the COVID-19, giving full play to the advantages of the two teaching modes. According to the school's teaching environment and teaching objectives, the online and offline blending teaching mode is constructed by introducing the recording of course video + MOOC + SPOC+ online resources of high-quality open courses + Flipped Classroom+ Rain Classroom + QQ group + WeChat + Tencent meeting, in order to improve the comprehensive teaching performance, and provide an important reference for the educational reform of similar courses in the post epidemic era.

New Perspectives on Ensemble Sensitivity Analysis with Applications to a Climatology of Severe Convection

Ensemble sensitivity analysis (ESA) is a statistical technique applied within an ensemble to reveal the atmospheric flow features that relate to a chosen aspect of the flow. Given its ease of use (it is simply a linear regression between a chosen function of the forecast variables and the entire atmospheric state earlier or simultaneously in time), ensemble sensitivity has been the focus of several studies over roughly the last ten years. Such studies have primarily tried to understand the relevant dynamics and/or key precursors of high-impact weather events. Other applications of ESA have been more operationally oriented, including observation targeting within data assimilation systems and real-time adjustment techniques that attempt to utilize both sensitivity information and observations to improve forecasts.While ESA has gained popularity, its fundamental properties remain a substantially underutilized basis for realizing the technique’s full scientific potential. For example, the relationship between ensemble sensitivity and the pure dynamics of the system can teach us how to appropriately apply various sensitivity-based applications, and combining sensitivity with other ensemble properties such as spread can distinguish between a fluid dynamics problem and a predictability one. This work aims to present new perspectives on ensemble sensitivity, and clarify its fundamentals, with the hopes of making it a more accessible, attractive, and useful tool in the atmospheric sciences. These new perspectives are applied in part to a short climatology of severe convection forecasts to demonstrate the unique knowledge that can gained through broadened use of ESA.

Synergies: University-Museum Collaborations

The purpose of this report is to provide documentation of the University-Museums Synergies Initiative between a Department of Marine, Earth, and Atmospheric Sciences and a Museum of Natural Sciences.The goals of this initiative were to 1)identify specific projects and opportunities might be developed to strengthen the collaboration between institutions and 2) gain a betterunderstanding of MEAS researchers’ and Museum employees' perspectives onuniversity-museum partnerships.

Calibration and assessment of electrochemical low-cost sensors in remote alpine harsh environments

This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) <5 ppb (parts per billion), limit of quantification (LOQ) <17 ppb, linear dynamic range (LDR) up to 250 ppb, intra-Pearson correlation coefficient (PCC) up to 0.96, inter-PCC >0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.

Direct Observations of Anthracene Clusters at Ice Surfaces

Heterogeneous processes can control atmospheric composition. Snow and ice present important, but poorly understood, reaction media that can greatly alter the composition of air in the cryosphere in polar and temperate regions. Atmospheric scientists struggle to reconcile model predictions with field observations in snow-covered regions due to experimental challenges associated with monitoring reactions at air-ice interfaces, and debate regarding reaction kinetics and mechanisms has persisted for over a decade. In this work, we use wavelength-resolved fluorescence microscopy to determine the distribution and chemical speciation of the pollutant anthracene at the surfaces of environmentally relevant frozen surfaces. We show that anthracene adsorbs to frozen surfaces in monomeric form, but that following lateral diffusion, molecules ultimately reside within brine channels at saltwater ice surfaces, and in micron-sized clusters at freshwater ice surfaces; emission profiles indicate extensive self-association. We also measure anthracene photodegradation kinetics in aqueous solution and artificial snow prepared from frozen freshwater and saltwater solutions and use the micro-spectroscopic observations to explain the rate constants measured in different environments. These results resolve long-standing debates and will improve predictions of pollutant fate in the cryosphere. The techniques used can be applied to numerous surfaces within and beyond the atmospheric sciences.

The blessing of dimensionality for the analysis of climate data

We give a simple description of the blessing of dimensionality with the main focus on the concentration phenomena. These phenomena imply that in high dimensions the lengths of independent random vectors from the same distribution have almost the same length and that independent vectors are almost orthogonal. In the climate and atmospheric sciences we rely increasingly on ensemble modelling and face the challenge of analysing large samples of long time series and spatially extended fields. We show how the properties of high dimensions allow us to obtain analytical results for e.g. correlations between sample members and the behaviour of the sample mean when the size of the sample grows. We find that the properties of high dimensionality with reasonable success can be applied to climate data. This is the case although most climate data show strong anisotropy and both spatial and temporal dependence, resulting in effective dimensions around 25–100.

Integration-based Extraction and Visualization of Jet Stream Cores

Jet streams are fast three-dimensional coherent air flows that interact with other atmospheric structures such as warm conveyor belts (WCBs) and the tropopause. Individually, these structures have a significant impact on the mid-latitude weather evolution, and the impact of their interaction is still subject of research in the atmospheric sciences. A first step towards a deeper understanding of the meteorological processes is to extract the geometry of jet streams, for which we develop an integration-based feature extraction algorithm. Thus, rather than characterizing jet coreline purely as extremal line structure of wind magnitude, our coreline definition includes a regularization to favor jet corelines that align with the wind vector field. Based on the line geometry, proximity-based filtering can automatically detect potential interactions between WCBs and jets, and results of an automatic detection of split and merge events of jets can be visualized in relation to the tropopause. Taking ERA5 reanalysis data as input, we first extract jet stream corelines using an integration-based predictor-corrector approach that admits momentarily weak air streams. Using WCB trajectories and the tropopause geometry as context, we visualize individual cases, showing how WCBs influence the acceleration and displacement of jet streams, and how the tropopause behaves near split and merge locations of jets. Multiple geographical projections, slicing, as well as direct and indirect volume rendering further support the interactive analysis. Using our tool, we obtained a new perspective onto the three-dimensional jet movement, which can stimulate follow-up research.

The “State” of Active Learning in the Atmospheric Sciences: Strategies Instructors Use and Directions for Future Research

Extensive research within STEM fields has demonstrated that active learning leads to greater educational success for students relative to traditional lecture methods. While studies have explored active learning use across various STEM fields, minimal research has focused specifically on the atmospheric sciences. A baseline knowledge of the use of active learning in this field is vital for determining instructional effectiveness and can identify areas for improvement.The goal of this study is to provide a baseline regarding the state of active learning within the atmospheric sciences, including understanding what active learning strategies are most widely used, their frequency of use, and who is using them. Atmospheric science instructors were invited to participate in an online survey to provide information about their active learning use in the classroom and resources used to learn more about active learning strategies. Survey results indicate that case studies are the most popular high-use active learning strategy across all levels of instruction, though how they are implemented within the classroom is not clear. New atmospheric science instructors, instructors beyond the typical 5 year tenure mark, and female instructors exhibit the highest number of unique active learning strategies. Future work stresses the need for a larger sample size and more direct classroom observation of instructors using active learning.