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This study analyzed 1,636 top papers in the subject category of meteorology and atmospheric sciences about eleven years from 2011 to 2021, which included 1,636 highly cited papers and 24 hot papers in the field belonged to 20 Web of Science categories and 14 research areas. All top papers, written in English, were from 13,878 authors, 2,913 organizations, and 124 countries or territories, and published in 72 journals in the field. The top five journals are the Nature Climate Change (15.9% of the studied paper), Atmospheric Chemistry and Physics (12.1%), Journal of Climate (7.0%), Bulletin of the American Meteorological Society (6.7%), and Journal of Geophysical Research Atmospheres (4.6%), each published more than 76 papers. Top five countries were the USA, England, PR China, Germany, and France. Furthermore, top five organizations of National Oceanic and Atmospheric Administration (NOAA), National Center for Atmospheric Research (NCAR), National Aeronautics and Space Administration (NASA), Chinese Academy of Sciences, and University Colorado were popular based on contribution of articles more than 134 papers each. All keywords were separated into eight clusters for different research topic. Visualizations offer exploratory information on the current state in a scientific field or discipline, as well as can indicate possible developments in the future. [ABSTRACT FROM AUTHOR]

Lorenz (1963) provided the foundation of chaos theory and inspired a fundamental reappraisal of systems’ nonlinearity in many disciplines, including physical geography. I will provide a brief overview of chaos in nonlinear systems as documented in Lorenz (1963), including the major tenants of chaos theory, followed by a discussion of the effects of chaos theory within meteorology and climate sciences, geomorphology, and ecology and biogeography. In general, Lorenz (1963) provided the intellectual framework for reconsidering the predictability of many physical systems. [ABSTRACT FROM AUTHOR]

Educators can enrich their teaching with best practices, share resources, and contribute to the growing atmospheric science education research community by reading and participating in the scholarship of teaching and learning in atmospheric science. This body of scholarship has grown, particularly over the past 15 years, and is now a sizable literature base that documents and exemplifies numerous teaching innovations in undergraduate atmospheric science education. This literature base benefits the entire atmospheric science community because graduates of atmospheric science programs are better prepared to enter the workforce. This literature base has not yet been examined, however, to see how well the evidence supports education practices in the atmospheric science education literature. In this study, we characterized that evidence and show that the majority of papers we reviewed share education innovations with anecdotal or correlational evidence of effectiveness. While providing useful practitioner knowledge and preliminary evidence of the effectiveness of numerous innovative teaching practices, opportunities exist for increasing readers' confidence that the innovations caused the learning gains. Additional studies would also help move conclusions toward generalizability across academic institutions and student populations. We make recommendations for advancing atmospheric science education research and encourage atmospheric science educators to actively use the growing body of education literature as well as contribute to advancing atmospheric science education research. [ABSTRACT FROM AUTHOR]

The present study focused on the research publications of women faculty in the field of physics, Astrophysics, Astronomy and Atmospheric Science in India. To collect the data we have covered the women faculty of Central Universities, State Universities, IITs, NITs, IISER's, NISER's, research institutes, laboratories and some selected deemed universities. The first fact we found was that the number of women were very less as compare to male staff. To see the publication productivity of women authors we tried to analyze the year-wise productivity, authorship pattern, preferred journals, place and designation and the research papers received highest citations for the period of five years from 2011- 2015. Year 2014 found to be the most productive year and in authorship pattern, women authors preferred to publish their research in collaboration. Highest number of research papers was published in Journal of Applied Physics. [ABSTRACT FROM AUTHOR]

Aerosol–cloud interactions play a crucial role in shaping Earth's climate and hydrological cycle. Observing these interactions with high precision and accuracy is of the utmost importance for improving climate models and predicting Earth's climate. Over the past few decades, lidar techniques have emerged as powerful tools for investigating aerosol–cloud interactions due to their ability to provide detailed vertical profiles of aerosol particles and clouds with high spatial and temporal resolutions. This review paper provides an overview of recent advancements in the study of ACI using lidar techniques. The paper begins with a description of the different cloud microphysical processes that are affected by the presence of aerosol, and with an outline of lidar remote sensing application in characterizing aerosol particles and clouds. The subsequent sections delve into the key findings and insights gained from lidar-based studies of aerosol–cloud interactions. This includes investigations into the role of aerosol particles in cloud formation, evolution, and microphysical properties. Finally, the review concludes with an outlook on future research. By reporting the latest findings and methodologies, this review aims to provide valuable insights for researchers engaged in climate science and atmospheric research. [ABSTRACT FROM AUTHOR]

The land use, land-use change and forestry (LULUCF) sector, as a source and a sink of greenhouse gas (GHG) emissions, is critical for achieving carbon neutrality. Many academic journals have published papers on land use carbon emission or sink (LUCES), but LUCES reviews are relatively rare, which poses great challenges in accurately understanding the research progress and future prospects. This work analyzes the research characteristics, hotspots and future perspectives of LUCES research by using a bibliometric analysis (such as DDA, VOSviewer, CiteSpace software) and a review based on the data (6115 scientific papers) during 1991–2023 from the Web of Science (WoS) platform. We found that (1) over the past 33 years, it first presented a steady growth, then fluctuating growth, and finally a rapid growth trend in the yearly number of publications in LUCES research. The USA (17.31%), China (14.96%), and the UK (7.37%) occupy a dominant position in this research field. (2) The related LUCES research is interdisciplinary, which mainly cover science and technology, meteorology and atmospheric sciences, geology, and environmental sciences and ecology disciplines. (3) The research hotspot analysis on LUCES shows that these articles mostly covered the follow three aspects: ecosystem services, climate change, and carbon neutrality. (4) A review of the past LUCES literature suggests that it is mainly focused on exploring the forefront issues in terms of the definition and boundaries, evaluation method and influencing factors, etc. This work suggests that further research could explore the main scientific problems on quantification of land-based carbon neutrality, quantitative analysis of the impact mechanisms, as well as interdisciplinary research and collaborative governance needed for carbon neutrality. [ABSTRACT FROM AUTHOR]

At present, a variety of global remote sensing surface downwelling longwave radiation (SDL) products are used for atmospheric science research; however, there are few studies on the quantitative evaluation of differences among different SDL products. In order to evaluate the differences among different SDL products quantitatively, we have selected three commonly used SDL products—Clouds and the Earth's Radiant Energy System-Synoptic Radiative Fluxes and Clouds (CERES-SYN), the European Centre for Medium Range Weather Forecasts-Surface Radiation Budget (ECMWF-SRB) and the Global Energy and Water Exchanges Project-Surface Radiation Budget (GEWEX-SRB)—to comprehensively study in this paper. The results show that there are significant differences among the three SDL products in some areas, such as in the Arctic, the Antarctic, the Sahara, the Tibet Plateau, and Greenland. The maximum absolute root mean square error (RMSEab) in these areas is greater than 20 Wm−2, the maximum relative root mean square error (RMSEre) is greater than 20%, the maximum and minimum absolute mean bias error (MBEab) are about 20 Wm−2 and −20 Wm−2, respectively, and the maximum and minimum relative mean bias error (MBEre) are about 10% and −10%, respectively. Among the three SDL products, the difference between the ECMWF-SRB and GEWEX-SRB is the most significant. In addition, this paper also analyzed the differences among different SDL products based on three aspects. Firstly, the differences among the three SDL products show that there is significant seasonality, and the differences among different months may vary greatly. However, the differences are not sensitive to years. Secondly, there are some differences in cloud-forcing radiative fluxes (CFRFs) of different SDL products, which is also an important factor affecting the difference between different SDL products. Finally, in the process of converting high temporal resolution SDL products into monthly SDL products, data processing also affects the difference between different SDL products. [ABSTRACT FROM AUTHOR]

This paper presents theoretical foundations, numerical implementation and examples of application of a two-dimensional Discrete-Element bonded-particle Sea Ice model DESIgn. In the model, sea ice is represented as an assemblage of objects of two types: disk-shaped "grains", and semi-elastic bonds connecting them. Grains move on the sea surface under the influence of forces from the atmosphere and the ocean, as well as interactions with surrounding grains through a direct contact (Hertzian contact mechanics) and/or through bonds. The model has an option of taking into account quasi-threedimensional effects related to space- and time-varying curvature of the sea surface, thus enabling simulation of ice breaking due to stresses resulting from bending moments associated with surface waves. Examples of the model's application to simple sea ice deformation and breaking problems are presented, with an analysis of the influence of the basic model parameters ("microscopic" properties of grains and bonds) on the large-scale response of the modeled material. The model is written as a toolbox suitable for usage with the open-source numerical library LIGGGHTS. The code, together with a full technical documentation and example input files, is freely available with this paper and on the Internet. [ABSTRACT FROM AUTHOR]

Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record has been released by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF). ATOVS observations from the National Oceanic and Atmospheric Agency (NOAA)-15 through NOAA-19 and EUMETSAT's Meteorological operational (Metop-A) satellites have been consistently reprocessed to generate 13 years (1999-2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km x 90 km. After pre-processing, an optimal estimation scheme has been applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step an objective interpolation method (Kriging) has been applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer integrated water vapour (LPW) and layer mean temperature for five tropospheric layers, as well as specific humidity and temperature at six tropospheric levels and is referenced under doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. To our knowledge this is the first time that the ATOVS record (1998-now) has been consistently reprocessed (1999-2011) to retrieve water vapour and temperature products. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric InfraRed Sounder (AIRS) version 5 satellite data record. The TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are -0.2 and 3.3 kgm-2, respectively. The maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits an improved quality and an improved stability relative to the operational CM SAF ATOVS products when compared to the TPW from GUAN radiosonde data over the period 2004-2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record so that a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest threats to human living and health in the 21st century. Whilst a large number of papers have been published addressing the health impact of climate change, there is a lack of comprehensive bibliometric analysis in the crosscutting field. This study evaluated the global scientific output of research in the field of climate change and health between 1990 and 2020, based on the Web of Science Core Collection database. Research themes were identified using a social network analysis technique based on author keywords. Research trends were assessed by the change in overall publication number and the percentage of publications in each research theme. Articles were further categorized by the availability of funding and author affiliation to compare the difference between developed and developing countries. Results showed that the research output in the field of climate change and health has increased dramatically in the past 30 years, mainly dominated by researchers in developed countries. The percentage of research receiving funding was found to be the lowest in those published by developing countries only and the highest in those published by the collaboration of developed and developing countries. A total of nine major research themes was identified. Research related to 'risk assessment and adaptation', 'sustainable development' and 'infectious diseases' were relatively underfunded. A significant research trend was observed between 2006 and 2020, with increased attention on research themes related to 'risk assessment and adaptation', 'sustainable development', 'extreme events' and 'air pollution', and reduced attention on research themes related to 'ocean', 'infectious disease' and 'phenology'. The shift of the research trend was mainly driven by research in developed countries. Suggestions, recommendations and future priorities identified by experts in the field of atmospheric sciences, epidemiology, public health, climate change, environmental sciences, and policy development are also provided to guide future research. It is important to shift our focus from single health aspects to an integrated system (such as One Health framework, which considers environmental health, animal health and human health as a whole), with future research focusing more on the systemic impact of climate change in order to achieve better, more effective and efficient risk governance. More funding should be mobilized to support the research capacity building in developing countries and to support climate change adaptation strategies for sustainable development. [ABSTRACT FROM AUTHOR]

The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model's precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms. [ABSTRACT FROM AUTHOR]

These eight articles are summarized below: Two papers address the regional impacts of climate change in East Asia and the Mediterranean. Author Contributions D.E.R. conceptualized the theme of this Special Issue and A.D.P. prepared the original draft of this editorial. Anthropogenic climate change is responsible for warming global surface temperatures, which has increased the frequency and intensity of weather and climate events [[1]]. [Extracted from the article]

A numerical model based on Radial Basis Function-generated Finite Differences (RBFFD) is developed for simulating the Global Electric Circuit (GEC) within the Earth's atmosphere, represented by a 3-D variable coefficient linear elliptic PDE in a sphericallyshaped volume with the lower boundary being the Earth's topography and the upper boundary a sphere at 60 km. To our knowledge, this is (1) the first numerical model of the GEC to combine the Earth's topography with directly approximating the differential operators in 3-D space, and related to this (2) the first RBF-FD method to use irregular 3-D stencils for discretization to handle the topography. It benefits from the mesh-free nature of RBF-FD, which is especially suitable for modeling high-dimensional problems with irregular boundaries. The RBF-FD elliptic solver proposed here makes no limiting assumptions on the spatial variability of the coefficients in the PDE (i.e. the conductivity profile), the right hand side forcing term of the PDE (i.e. distribution of current sources) or the geometry of the lower boundary. [ABSTRACT FROM AUTHOR]

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested prac titioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks. [ABSTRACT FROM AUTHOR]

The Journal of the Meteorological Society of Japan (JMSJ) is a well-established journal in the field of meteorology and related sciences. The editorial board is committed to continuously improving the journal for authors, readers, and reviewers. In 2024, the JMSJ will publish its 102nd volume and will discontinue the note service for submissions. The journal has recently implemented minor reforms in the technical editing process. The JMSJ Award for 2023 was presented to authors who conducted novel research on important topics. The most accessed papers in 2023 included topics such as geostationary meteorological satellites and reanalysis data. The journal also organized three special editions on various topics. JMSJ authors are encouraged to use J- STAGE Data for archiving datasets related to their papers. The journal expresses gratitude to the meteorological research community for their support and looks forward to continued success in 2024. [Extracted from the article]

End to end modelling is an attractive and rapidly developing approach to solve developing strategies in marine systems science and management. However problems remain in the area of data matching and sub-model compatibility. A mechanism and novel interfacing system (Couplerlib) is presented whereby a physical/biogeochemical model (GOTM-ERSEM) that predicts dynamics of the lower trophic level (LTL) organisms in marine ecosystems is coupled to a dynamic ecosystem model (Ecosim) that predicts food-web interactions among higher trophic level (HTL) organisms. Coupling is achieved by means of a bespoke interface which handles the system incompatibilities between the models and a more generic Couplerlib library which uses metadata descriptions in extensible mark-up language (XML) to marshal data between groups, paying attention to functional group mappings and compatibility of units between models. In addition, within Couplerlib, models can be coupled across networks by means of socket mechanisms. As a demonstration of this approach, a food web model (Ecopath with Ecosim, EwE) and a physical/biogeochemical model (GOTM-ERSEM) representing the North Sea ecosystem were joined with Couplerlib. The output from GOTM-ERSEM varies between years dependent on oceanographic and meteorological conditions. Although inter-annual variability was clearly present, there was always the tendency for an annual cycle consisting of a peak of diatoms in spring, followed by (less nutritious) flagellates and dinoflagellates through the summer resulting in an early summer peak in the mesozooplankton biomass. Pelagic productivity, predicted by the LTL model, was highly seasonal with little winter food for the higher trophic levels. The Ecosim model was originally based on the assumption of constant annual inputs and, consequently, when coupled, pelagic species suffered population loss over the winter months. By contrast, benthic populations were more stable (although the benthic linkage modelled was purely at the detritus level). The coupled model was used to examine long term effects of environmental change, and showed the system to be nutrient limited, relatively unaffected by forecast climate change, especially in the benthos. The stability of an Ecosim formulation for large higher tropic level food webs is discussed and it is concluded that this kind of coupled model formulation is better for examining the effects of long term environmental change than short term perturbations. [ABSTRACT FROM AUTHOR]

Soil exchange of carbonyl sulfide (COS) is the second largest COS flux in terrestrial ecosystems. A novel application of COS is the separation of gross primary productivity (GPP) from concomitant respiration. This method requires that soil COS exchange is relatively small and can be well quantified. Existing models for soil COS flux have incorporated empirical temperature and moisture functions derived from laboratory experiments, but not explicitly resolved diffusion in the soil column. We developed a 1-D diffusion-reaction model for soil COS exchange that accounts for COS uptake and production, relates source-sink terms to environmental variables, and has an option to enable surface litter layers. We evaluated the model with field data from a wheat field (Southern Great Plains (SGP), OK, USA) and an oak woodland (Stunt Ranch Reserve, CA, USA). The model was able to reproduce all observed features of soil COS exchange such as diurnal variations and sink-source transitions. We found that soil COS uptake is strongly diffusion controlled, and limited by low COS concentrations in the soil if there is COS uptake in the litter layer. The model provides novel insights into the balance between soil COS uptake and production: a higher COS production capacity was required despite lower COS emissions during the growing season compared to the post-senescence period at SGP, and unchanged COS uptake capacity despite the dominant role of COS emissions after senescence. Once there is a database of soil COS parameters for key biomes, we expect the model will also be useful to simulate soil COS exchange at regional to global scales. [ABSTRACT FROM AUTHOR]

The atmospheric boundary layer (ABL) exhibit multilayered thermal structure especially in polar atmosphere during extreme winters. These thermal inversions are originated based on the combined forcing of local and large scale synoptic meteorology. At the local scale the thermal inversion layer forms near the surface and plays a central role in controlling the surface radiative cooling; however, depending upon the large scale synoptic meteorological forcing, an upper level thermal inversion can also exist topping the local ABL. In this article a numerical methodology is developed to determine all-thermal inver sion layers present in a given temperature profile and deduce some of their thermodynamic properties. The algorithm extract from the temperature profile the most important temperature variations defining thermal layers. This is accomplished by a linear interpolation function of variable length that minimizes an error function. The algorithm functionality is demonstrated on actual radiosonde profiles to deduce all-present inversion layers with an error fraction set independently. [ABSTRACT FROM AUTHOR]

The GRACE (Gravity Recovery and Climate Experiment) satellite, operational from its launch in 2002 until October 2017, documented critical changes in global terrestrial water storage, significantly advancing the fields of gravity field analysis, hydrological variations, and environmental monitoring. This study investigates the thematic evolution of 2,966 SCIE-indexed publications on GRACE satellite applications from 2002 to 2022, utilizing co-occurrence network mapping and complex network analysis. Our results indicate a steady growth in GRACE satellite application research, with early publications (2002-2004) achieving an average citation rate exceeding 100, underscoring their substantial impact. Keyword clustering identified four primary research themes: Hydrology and Water Resources, Atmospheric and Environmental Science, Geophysical and Temporal Analysis, and Polar and Glaciological Studies. Over time, these themes have expanded and deepened, transitioning from initial focuses on gravity field computations to hydrological applications, sea level studies, and more specific investigations into water resources, climate change, and advancements in satellite geodesy. Recent research has particularly concentrated on groundwater and water storage issues. Geographically, the United States leads in publication output, impact, and international collaborations, with China following in publication count and network centrality, albeit with potential for improved impact. European countries demonstrate significant influence and centrality within the cooperation network. The evolution index of the international cooperation network shows a significant increase in connectivity from 2002 to 2022, with closer cooperation between countries. There is notable growth in both the number and intensity of collaborations, as evidenced by the rising average degree and average weighted degree. Overall, these indices underscore the evolution towards a more connected and globally integrated research network in GRACE satellite research. Looking forward, technological advancements, enhanced international collaboration, and integration with other data sources will drive future research in GRACE satellite application research, with important implications for addressing global environmental and climate challenges. [ABSTRACT FROM AUTHOR]

The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions. [ABSTRACT FROM AUTHOR]

We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10-20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system. [ABSTRACT FROM AUTHOR]

The convective transport module, CVTRANS, of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model has been revised to better represent the physical flows and incorporate recent findings on the properties of the convective plumes. The modifications involve (i) applying intermediate time stepping based on a settable criterion, (ii) using an analytic expression to account for the intra time step mixing ratio evolution below cloud base, and (iii) implementing a novel expression for the mixing ratios of atmospheric compounds at the base of an updraft. Even when averaged over a year, the predicted mixing ratios of atmospheric compounds are significantly affected by the intermediate time stepping. For example, for an exponentially decaying atmospheric tracer with a lifetime of 1 day, the zonal averages can locally differ by more than a factor of 6 and the induced root mean square deviation from the original code is, weighted by the air mass, higher than 40% of the average mixing ratio. The other modifications result in smaller differences. However, since they do not require additional computational time, their application is also recommended. [ABSTRACT FROM AUTHOR]

The International Polar Year 2007-2008 was a synchronized effort to simultaneously collect data from polar regions. Being the fourth in a row of IPYs, the demand for interdisciplinarity and new data products was high. However, despite of all the research done on land, people, ocean, ice and atmosphere and the large amount of data collected, no central archive or portal was created for IPY data. In order to address these issues, a concerted effort between PANGAEA - Data Publisher for Earth and Environmental Science, the ICSU World Data System (WDS), and the International Council for Scientific and Technical Information (ICSTI) was undertaken to extract data resulting from IPY publications for long-term preservation. 1380 IPY-related references were collected. Out of these, only 450 contained accessible data. All data was extracted, quality checked, annotated with metadata and uploaded to PANGAEA. The 450 articles dealt with a multitude of IPY topics - plankton biomass, water chemistry, ice thickness, whale sightings, Inuit health, alien species introductions by travelers or tundra biomass change - to mention just a few. Both, the Arctic and the Antarctic were investigated in the articles, and all realms (land, people, ocean, ice and atmosphere) and a wide range of countries were covered. The data compilation can now be found with the identifier doi:10.1594/PANGAEA.150150 and individually searched for using the PANGAEA search engine (www.pangaea.de) and adding "+project:ipy". With this effort, we hope to improve the visibility, accessibility and long-term storage of IPY data for future research and new data products. [ABSTRACT FROM AUTHOR]

High precision analysis of the 17O/16O isotope ratio in water and water vapor is of interest in hydrological, paleoclimate, and atmospheric science applications. Of specific interest is the parameter 17Oexcess, a measure of the deviation from a linear relationship between 17O/16O and 18O/16O ratios. Conventional analyses of 17 Oexcess are obtained by fluorination of H2O to O2 that is analyzed by dual-inlet isotope ratio mass spectrometry (IRMS).We describe a new laser spectroscopy instrument for highprecision 17Oexcess measurements. The new instrument uses cavity ring-down spectroscopy (CRDS) with laser-current tuning to achieve reduced measurement drift com10 pared with previous-generation instruments. Liquid water and water vapor samples can be analyzed with better than 8 per meg precision for 17Oexcess using integration times of less than 30 min. Calibration with respect to accepted water standards demonstrates that both the precision and the accuracy are competitive with conventional IRMS methods. The new instrument also achieves simultaneous measurements of δ18O, δ17O 15 and δD with precision< 0.03‰, < 0.02‰ and < 0.2‰, respectively. [ABSTRACT FROM AUTHOR]

The study of precipitation is one of the most intriguing areas in atmospheric sciences, with significant implications for our daily lives and climate change projections. This paper explores the estimation of rainfall trends in South American regions using convolutional neural networks (CNNs). The study focuses on the application of Cloud-Net, a CNNbased model with a format similar to an autoencoder, to obtain qualitative estimates of precipitation patterns. The employed loss functions, Categorical Cross Entropy and Categorical Focal Loss, address the challenges of classifying minority categories in unbalanced data. Regional analysis was conducted, identifying days with high rainfall intensity and the predominant intensities in 25 regions. The CNN model's performance was compared with the XGBoost algorithm, showing excellent results for extreme rainfall categories and challenging intermediate categories. Furthermore, a comparison was made with Quantitative Precipitation Estimation (QPE) data and ground measurements from rain gauges. While the CNN model provided a valuable qualitative estimate of precipitation trends, achieving precise quantitative estimation would require an extensive data set of in-situ measurements. Overall, this research demonstrates the potential of CNNs for estimating rainfall trends and understanding precipitation patterns in South American regions. The findings offer valuable insights for further applications in meteorology and environmental studies. [ABSTRACT FROM AUTHOR]

This paper describes a neural network cloud masking scheme from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) multi-angle polarimetric measurements. The algorithm has been trained on synthetic measurements and has been applied to the processing of 1 year of PARASOL data. Comparisons of the retrieved cloud fraction with MODIS (Moderate Resolution Imaging Spectroradiometer) products show overall agreement in spatial and temporal patterns, but the PARASOL neural network (PARASOL-NN) retrieves lower cloud fractions. Comparisons with a goodness-of-fit mask from aerosol retrievals suggest that the NN cloud mask flags fewer clear pixels as cloudy than MODIS (∼ 3 % of the clear pixels versus ∼ 15 % by MODIS). On the other hand the NN classifies more pixels incorrectly as clear than MODIS (∼ 20 % by NN, versus ∼ 15 % by MODIS). Additionally, the NN and MODIS cloud mask have been applied to the aerosol retrievals from PARASOL using the Remote Sensing of Trace Gas and Aerosol Products (RemoTAP) algorithm. Validation with AERONET shows that the NN cloud mask performs comparably with MODIS in screening residual cloud contamination in retrieved aerosol properties. Our study demonstrates that cloud masking from multi-angle polarimeter (MAP) aerosol retrievals can be performed based on the MAP measurements themselves, making the retrievals independent of the availability of a cloud imager. [ABSTRACT FROM AUTHOR]

SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) is a 10‐channel infrared radiometer that is one of four instruments on the NASA TIMED (Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics) satellite mission to study the structure, energetics, chemistry, and dynamics of the Earth's mesosphere and lower thermosphere. Each of the ten SABER channels has a unique filter over its detector. The filter passes infrared radiation within a defined spectral region that optimizes the ability to derive temperature and constituent concentrations from the infrared radiance measurements. The TIMED spacecraft was launched into a 625 km circular polar orbit (74.1° inclination) via a Boeing Delta II rocket from Vandenberg Air Force Base on 7 December 2001. SABER continues to operate nominally and collect data routinely as it has for over 21 years. Nearly 2,200 peer‐reviewed journal articles have been published worldwide using SABER data. A list of these articles is included in Supporting Information S1 accompanying this paper. This paper presents a detailed technical description of the SABER instrument including major subsystems of the instrument and technical performance parameters. This paper comprehensively describes the instrument and its components and provides final instrument design and performance parameters. The motivation for this paper is to document this information permanently for future reference. The Space Dynamics Laboratory (SDL) of Utah State University designed, fabricated, and calibrated the SABER instrument in close collaboration with NASA Langley Research Center, Hampton University, and Global Atmospheric Technologies and Science (GATS). Plain Language Summary: Earth's mesosphere and lower thermosphere (MLT), approximately 50–180 km in altitude or 30 to 110 miles high, was the least explored region of the atmosphere 30 years ago. The MLT is a critical region of Earth's atmosphere as it is the boundary or interface between the space environment and the lower atmosphere. Today the region is referred to as part of the "geospace" environment. To examine the MLT in more detail, NASA developed the Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics or TIMED satellite mission beginning in 1996. Launch of the TIMED satellite occurred in December 2001. One of the four instruments carried by the TIMED satellite is named SABER (Sounding of the Atmosphere using Broadband Emission Radiometry). SABER continues to provide exceptional scientific results and is still routinely collecting data more than 21 years after launch. This paper provides a technical description of the SABER instrument. Key Points: Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) is an infrared limb sounding instrument observing the Earth's mesosphere and lower thermosphere continuously for over two decadesSABER was developed through a partnership involving NASA Langley, Space Dynamics Laboratory, Hampton University, and Global Atmospheric Technologies and ScienceSABER is still operational with no reduction in capability and has yielded nearly 2,200 peer‐reviewed journal articles by worldwide authors [ABSTRACT FROM AUTHOR]

Their paper Heathwaite et al. (2021) synthesizes the physical hydrology and biogeochemistry process-based understanding for a lowland groundwater-fed river, representative of systems where the river is continuously recharged by groundwater throughout the year. This Special Issue (SI) of I Hydrological Processes i features invited contributions led by women scientists at an advanced career stage who have made sustained contributions to the study of hydrological processes, advancing the field. The subject matters of the papers address how we can enhance our understanding of hydrological processes, but they are also interdisciplinary and extremely timely with focuses on the dynamics of ecohydrological processes, climate change, and human behaviour: B Dr. Christine Alewell b is a Professor at the University of Basel, Switzerland. She is an expert in physical-ecological interactions in river ecosystems, implications of physical riverine complexity for organic carbon storage, large wood in river floodplains and the effects of beaver activities on downstream fluxes of material in river corridors. [Extracted from the article]

Biosphere-atmosphere interactions play a critical role in governing atmospheric composition, mediating the concentration of key species such as ozone and aerosol, thereby influencing air quality and climate. The exchange of reactive trace gases and their oxidation products (both gas and particle phase) is of particular importance in this process. The FORCAsT (FORest Canopy AtmoSphere Transfer) one-dimensional model is developed to study the emission, deposition, chemistry and transport of volatile organic compounds (VOCs) and their oxidation products in the atmosphere within and above the forest canopy. We include an equilibrium partitioning scheme, making FORCAsT one of the few canopy models currently capable of simulating the formation of secondary organic aerosols (SOA) from VOC oxidation in a forest environment. We evaluate the capability of FORCAsT to reproduce observed concentrations of key gas-phase species and report modeled SOA concentrations within and above a mixed forest at the University of Michigan Biological Station (UMBS) during the Community Atmosphere-Biosphere Interactions Experiment (CABINEX) field campaign in summer 2009. We examine the impact of two different gas-phase chemical mechanisms on modelled concentrations of short-lived primary emissions, such as isoprene and monoterpenes, and their oxidation products. While the two chemistry schemes perform similarly under high-NOx conditions, they diverge at the low levels of NOx at UMBS. We identify peroxy radical and alkyl nitrate chemistry as the key causes of the differences, highlighting the importance of this chemistry in understanding the fate of biogenic VOCs (bVOCs) for both the modelling and measurement communities. [ABSTRACT FROM AUTHOR]

In this study we develop a Secondary Inorganic Aerosol (SIA) module for the chemistry transport model MOCAGE developed at CNRM. Based on the thermodynamic equilibrium module ISORROPIA II, the new version of the model is evaluated both at the global scale and at the regional scale. The results show high concentrations of secondary inorganic aerosols in the most polluted regions being Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emissions reduction in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the model global outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement in all geographical regions with MODIS AOD retrievals when introducing SIA. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA gives generally a better agreement for secondary inorganic aerosols precursors (nitric acid, sulfur dioxide, ammonia) in particular with a reduction of the Modified Normalised Mean Bias (MNMB). At the regional scale, over Europe, the model simulation with SIA are compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained with the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants being particulate matter, ozone and nitrogen dioxide concentrations. The introduction of the SIA in MOCAGE provides a reduction of the PM2.5 MNMB of 0.44 on a yearly basis and even 0.52 on a three spring months period (March, April, May) when SIA are maximum. [ABSTRACT FROM AUTHOR]

We present the new 3.5 version of the Louvain-la-Neuve sea ice model (LIM) integrated in NEMO 3.6. The main novelty is the improvement of model robustness and versatility for a wide range of applications, from global to regional scales. Several modifications to the code were required. First, the time stepping scheme of the model was changed from parallel to sequential (ice dynamics first, then thermodynamics). Such a scheme enables to diagnose the different physical processes responsible for exchanges through the air–ice–ocean interfaces, as well as the online inspection of mass, heat and salt conservation properties of the code. In the course of these developments, several minor conservation leaks were found and fixed, so that LIM3.5 is exactly conservative. Second, lateral boundary conditions for regional ice-covered configurations have been implemented. To illustrate the new capabilities, two simulations are performed. One is a global simulation at a nominal 2° resolution forced by atmospheric climatologies and is found reasonably realistic although no specific tuning was done. The other is a regional simulation at 2 km resolution around the Svalbard Archipelago in the Arctic Ocean, with prescribed conditions at the four boundaries including tides. The simulation is able to resolve small-scale features and transient events such as the opening and closing of coastal polynyas. The ice mass budgets for both simulations are illustrated and mostly differ by the strength of ice formation in open water. LIM3.5 now forms a solid base for future scientific studies and model developments. [ABSTRACT FROM AUTHOR]

The land biosphere, atmospheric chemistry and climate are intricately interconnected, yet the modeling of carbon-climate and chemistry-climate interactions have evolved as entirely separate research communities. We describe the Yale Interactive terrestrial Biosphere (YIBs) model version 1.0, a land carbon cycle model that has been developed for coupling to the NASA Goddard Institute for Space Studies (GISS) ModelE2 global chemistry-climate model. The YIBs model adapts routines from the mature TRIFFID (Top-down Representation of Interactive Foliage and Flora Including Dynamics) and CASA (Carnegie-Ames-Stanford Approach) models to simulate interactive carbon assimilation, allocation, and autotrophic and heterotrophic respiration. Dynamic daily leaf area index is simulated based on carbon allocation and temperature- and drought-dependent prognostic phenology. YIBs incorporates a semi-mechanistic ozone vegetation damage scheme. Here, we validate the present-day YIBs land carbon fluxes for three increasingly complex configurations: (i) offline local site level, (ii) offline global forced with WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) meteorology, and (iii) online coupled to the NASA ModelE2 (NASA ModelE2-YIBs). Offline YIBs has hourly and online YIBs has half-hourly temporal resolution. The large observational database used for validation includes carbon fluxes from 145 flux tower sites and multiple satellite products. At the site level, YIBs simulates reasonable seasonality (correlation coefficient R > 0.8) of gross primary productivity (GPP) at 121 out of 145 sites with biases in magnitude ranging from -19 to 7 % depending on plant functional type. On the global scale, the offline model simulates an annual GPP of 125 ± 3 Pg C and net ecosystem exchange (NEE) of -2.5 ± 0.7 Pg C for 1982-2011, with seasonality and spatial distribution consistent with the satellite observations. We assess present-day global ozone vegetation damage using the offline YIBs configuration. Ozone damage reduces global GPP by 2-5 % annually with regional extremes of 4-10 % in east Asia. The online model simulates annual GPP of 123 ± 1 Pg C and NEE of -2.7 ± 0.7 Pg C. NASA ModelE2-YIBs is a useful new tool to investigate coupled interactions between the land carbon cycle, atmospheric chemistry, and climate change. [ABSTRACT FROM AUTHOR]

Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data mea sured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10 to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27 to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations. The ERA-interim reanalysis data debiased at FLUXNET sites can be downloaded from the PANGAEA data center (http://doi.pangaea.de/10.1594/PANGAEA.838234). [ABSTRACT FROM AUTHOR]

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-Transform InfraRed) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases.We present a method that uses measured and modelled XCO2 for assessing the consistency of these data records. Our NDACC XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this NDACC XCO2 product(empirically obtained scatter between TCCON and NDACC is about 4‰for daily mean as well as monthly mean comparisons and the bias is 25 ‰). As XCO2 model we developed and used a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in-situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3 ‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3 ‰. [ABSTRACT FROM AUTHOR]

A comprehensive error characterisation of SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) limb ozone profiles has been established based upon SCIATRAN transfer model simulations. The study was carried out in order to evaluate the possible impact of parameter uncertainties, e.g., in albedo, stratospheric aerosol optical extinction, temperature, pressure, pointing and ozone absorption cross section on the limb ozone retrieval. Together with the a posteriori covariance matrix available from the retrieval, total random and systematic errors are defined for SCIAMACHY ozone profiles. Main error sources are the pointing errors, errors in the knowledge of stratospheric aerosol parameters, and cloud interference. Systematic errors are on the order of 7 %, while the random error amounts to 10-15% for a single profile for most part of the stratosphere. These numbers can be used for the interpretation of instrument intercomparison and validation of the SCIAMACHY limb ozone profiles in a rigorous manner. [ABSTRACT FROM AUTHOR]

From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between RemoTAP and GRASP AOD of 0.12 and 0.038 over land and ocean, respectively. The largest differences occur over the biomass burning region in equatorial Africa. The global mean values are virtually unbiased with respect to each other. For AE the RMSD between RemoTAP and GRASP is 0.33 over land and 0.23 over ocean. For SSA, we find much better agreement over land (bias = - 0.01, RMSD = 0.043 for retrievals with AOD > 0.2) than over ocean (bias = 0.053, RMSD = 0.074). As expected, the differences increase towards low AOD, over both land and ocean. We also compared the GRASP and RemoTAP AOD and AE products against MODIS. For AOD over land, the agreement of either GRASP or RemoTAP with MODIS is worse than the agreement between the two PARASOL algorithms themselves. Over ocean, the agreement is very similar among the three products for AOD. For AE, the agreement between GRASP and RemoTAP is much better than the agreement of both products with MODIS. The agreement of the latest product versions with each other and with AERONET improved significantly compared to the previous version of the global products of GRASP and RemoTAP. The results demonstrate that the dedicated effort in algorithm development for multi-angle polarimetric (MAP) aerosol retrievals still leads to substantial improvement of the resulting aerosol products, and this is still an ongoing process. [ABSTRACT FROM AUTHOR]

A source apportionment scheme based on gas and aerosol phase reactive tracers has been implemented in the chemical-transport model FARM, to efficiently estimate contributions of different sources to ambient concentrations. The on-line scheme deals with all the main processes that the chemical species undergo in the model, to enhance consistency with the calculation of bulk concentrations. The fate of precursors through gas-phase chemical reactions is followed by an efficient solver that determines their incremental reactivity, while the contributions to the secondary particulate species from their gaseous precursors is determined by assuming the thermodynamic equilibrium between the two phases. The paper details the new employed methodologies and illustrates the application of the apportionment scheme (based on 6 source sectors) to PM10 and O3, simulated on three domains of different dimensions in Italy, all sharing the same horizontal resolution and a common region (Lombardy). Spatial patterns of results show, on average, a relevant contribution of heating on PM10 concentration in January, with local hotspots dominated by road traffic. Contributions appear consistent in the three simulated domains, apart from the boundary conditions, influenced by the dimension of the domain. Hourly series of contributions to O3 concentrations in July at three selected sites show the dominance of boundary conditions, underlining the large scale of O3 formation. Finally, for PM10 components, the resulting sectorial contributions are compared with the impacts computed via the brute force method, showing that results are similar for elemental carbon and sulfate, while they are different for nitrate and ammonium, due to a different allocation of contributions and impacts between the methods. Each approach responds in principle to a different purpose, and their combined use provides possibly a wide set of information useful for addressing the different air quality management needs. [ABSTRACT FROM AUTHOR]

Trajectory ensemble receptor models (TERMs) were widely used to determine the likely source locations and apportionment of air pollutants. This paper describes the development and applications of the Trajectory-ensemble Potential Source Apportionment Web application (TraPSA-Web), a comprehensive toolkit for likely atmospheric pollutant source location apportionments using TERMs and back trajectories generated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The TERMs integrated within the TraPSA-web include Concentration Field Analysis (CFA), Concentration Weighted Trajectory (CWT), single-site and multiple-site Potential Source Contribution Function (PSCF), and Simplified Quantitative Transport Bias Analysis (SQBA). TraPSA-Web is designed as a web application with a user-friendly modern graphical user interface (GUI), which largely enhances the accessibility to the users. TraPSA-Web will provide the air quality research community with a sophisticated toolkit for (1) easy management of the research project and datasets, (2) efficient automatization for HYSPLIT configurations, calculations, and result aggregations, (3) flexible configurations for the research scenarios and TERM parameters, and (4) interactive visualizations for the pollutant pattern analysis and TERM result mapping. [ABSTRACT FROM AUTHOR]

Radio occultation (RO) by the Earth's atmosphere of the transmitted signals of the Global Navigation Satellite Systems' satellites has improved numerical weather prediction, has benefited atmospheric process studies, and benchmarked climate change by its strong traceability to the international definition of the second. Until now, research with RO has been isolated to the few centers that actually process the data and impracticable elsewhere because of limitations on data formats, organization and volume of the data, download bandwidth, and the lack of a database that can be queried before downloading data. We announce the availability of RO data in the Registry of Open Data of Amazon Web Services (AWS). RO data are freely available for download for the user and free to process and store for the manager of the repository. RO data as processed by the COSMIC Program Office at the University Corporation for Atmospheric Research, by the Radio Occultation Meteorology Satellite Application Facility (ROM SAF), by EUMETSAT, and by the NASA Jet Propulsion Laboratory are available beginning with calibrated (excess) phase, extending to bending angle and refractivity and to retrievals of pressure, temperature and water vapor. The same RO repository also contains a metadata database that permits simple querying, filtering, and download of data using a Python application programming interface provided by this same project. Four tutorial demonstrations are provided as jupyter notebooks to provide representative samples of code to perform common research activities with RO data, including database querying and analysis, inter‐center comparison of RO retrieval performance, and atmospheric process studies. Plain Language Summary: Radio occultation is a space‐based technique used to profile pressure, temperature, and water vapor in the Earth's atmosphere from the surface to the top of the stratosphere. It has unusual properties compared to other methods for measuring the atmosphere from space, particularly its powerful calibration and its astonishing vertical resolution, both made possible because it is based on a measurement of timing rather than radiance. This paper announces the availability of all Earth radio occultation (RO) data ever obtained (with a few small exceptions) from multiple data providers in the Registry of Open Data of Amazon Web Services. This repository of RO data is formulated to greatly ease access and manipulation of RO data to users anywhere in the world. It comes with tutorials on how the data can be accessed, downloaded, and analyzed in the form of jupyter notebooks. Key Points: A repository of all historical Earth Radio occultation (RO) data of the atmosphere is now freely accessible in the Amazon Web Services Registry of Open DataData are organized to enable common RO, atmospheric science, and climate science research by users anywhereRO sounding data are easily queried, subset, and downloaded through a Python package available by PyPI [ABSTRACT FROM AUTHOR]

Uncrewed aerial vehicles (UAVs) have become widely used in a range of atmospheric science research applications. Because of their small size, flexible range of motion, adaptability, and low cost, multirotor UAVs are especially well-suited for probing the lower atmosphere. However, their use so far has been limited to conditions outside of clouds, first because of the difficulty of flying beyond visual line of sight and second because of the challenge of flying in icing conditions in supercooled clouds. Here, we present two UAVs for cloud microphysical research: one UAV (the measurement UAV) equipped with a Portable Optical Particle Spectrometer (POPS) and meteorological sensors to probe the aerosol and meteorological properties in the boundary layer and one UAV (the seeding UAV) equipped with seeding flares to produce a plume of particles that can nucleate ice in supercooled clouds. A propeller heating mechanism on both UAVs allows for operating in supercooled clouds with icing conditions. These UAVs are an integral part of the CLOUDLAB project in which glaciogenic cloud seeding of supercooled low stratus clouds is utilized for studying aerosol–cloud interactions and ice crystal formation and growth. In this paper, we first show validations of the POPS on board the measurement UAV, demonstrating that the rotor turbulence has a small effect on measured particle number concentrations. We then exemplify the applicability for profiling the planetary boundary layer, as well as for sampling and characterizing aerosol plumes, in this case, the seeding plume. We also present a new method for filtering out high-concentration data to ensure good data quality of POPS. We explain the different flight patterns that are possible for both UAVs, namely horizontal or vertical leg patterns or hovering, with an extensive and flexible parameter space for designing the flight patterns according to our scientific goals. Finally, we show two examples of seeding experiments: first characterizing an out-of-cloud seeding plume with the measurement UAV flying horizontal transects through the plume and, second, characterizing an in-cloud seeding plume with downstream measurements from a POPS and a holographic imager mounted on a tethered balloon. Particle number concentrations and particle number size distributions of the seeding plume from the experiments reveal that we can successfully produce and measure the seeding plume, both in-cloud (with accompanying elevated ice crystal number concentrations) and out-of-cloud. The methods presented here will be useful for probing the lower atmosphere, for characterizing aerosol plumes, and for deepening our cloud microphysical understanding through cloud seeding experiments, all of which have the potential to benefit the atmospheric science community. [ABSTRACT FROM AUTHOR]