Science topics: GeoscienceAtmospheric Sciences
Science topic
Atmospheric Sciences - Science topic
Explore the latest publications in Atmospheric Sciences, and find Atmospheric Sciences experts.
Publications related to Atmospheric Sciences (7,699)
Sorted by most recent
Shallow, sparse, non-precipitating convective clouds forming over the ocean are considered among the least organized cloud fields. The formation mechanism of these clouds is associated with random, local perturbations that create buoyant parcels. Their sparseness suggests no or very weak interactions between clouds. Here, we show that such clouds f...
Ice nucleation and growth are critical in many fields, including atmospheric science, cryobiology, and aviation. However, understanding the detailed mechanisms of ice crystal growth remains challenging. In this work, crystallization at the ice/quasi-liquid layer (QLL) interface of the basal and primary prism (prism1) surfaces of hexagonal ice (Ih)...
This interdisciplinary study examines the alignment of scientific phenomena described in Surah Al-Baqarah (Chapter 2) and Surah Maryam (Chapter 19) of the Quran with modern empirical discoveries, positing these congruences as evidence of the Quran's transcendent origin. Through a systematic analysis of key verses, the manuscript highlights how thes...
Accurate measurements of direct solar radiation spectra are crucial for atmospheric science, climatology, agriculture, and solar energy. Existing systems depend on costly dual-axis tracking devices, leading to high maintenance and error rates. This study presents a free-form surface-based polar-axis rotating solar direct radiation spectrometer, ena...
The high-resolution ship emission inventory serves as a crucial dataset for various disciplines including atmospheric science, marine science, and environmental management. Here, we present a global high-spatiotemporal-resolution ship emission inventory at a resolution of 0.1° × 0.1° for the years 2013 and 2016–2021, generated by the state-of-the-a...
Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. However, due to the complex interactions between reagent ions and target compounds, chemical understanding remains limited and compound identification difficult. In this study, we apply machine learning to a reference dataset of pesticides in two standard...
The North Atlantic Climate System Integrated Study (ACSIS) was a large multidisciplinary research programme funded by the UK's Natural Environment Research Council (NERC). ACSIS ran from 2016 to 2022 and brought together around 80 scientists from seven leading UK-based environmental research institutes to deliver major advances in the understanding...
The Nord Stream pipeline leaks on 26 September 2022 released 465 ± 20 kt of methane into the atmosphere, which is the largest recorded transient anthropogenic methane emission event. While most of the gas escaped directly to the atmosphere, a fraction dissolved in the water. So far, studies on the fate of this dissolved methane rely on pipeline vol...
Physics-based numerical models have been the bedrock of atmospheric sciences for decades, offering robust solutions but often at the cost of significant computational resources. Deep learning (DL) models have emerged as powerful tools in meteorology, capable of analyzing complex weather and climate data by learning intricate dependencies and provid...
Climate is one of the most important components and elements of the environment. Because abnormal climate change in each of the elements will eliminate the possibility of living beings, including humans, plants and animals, to continue living properly. Droughts, destructive floods, frosts, severe storms (weather hazards) are considered to be such h...
Severe convective storms and tornadoes rank among nature’s most hazardous phenomena, inflicting significant property damage and casualties. Near-surface weather conditions are closely governed by large-scale synoptic patterns. It is crucial to delve into the involved multiscale associations to understand tornado potential in response to climate cha...
I designed this book for students and professionals who want to understand and apply basic meteorological concepts, but who don’t need to derive
equations.
To make this book accessible to more people, I
converted the equations into algebra. With algebraic
approximations to the atmosphere, you can see the
physical meaning of each term and you c...
The effects of model resolution on the simulation of sea-level variability were analyzed based on the second-generation climate system ocean model from the State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics, Institute of Atmosphere Physics (LICOM2) with resolutions of 1° (LICOM2-L) and 0.1° (LICOM2-H)....
High-resolution simulations such as the ICOsahedral Non-hydrostatic Large-Eddy Model (ICON-LEM) can be used to understand the interactions among aerosols, clouds, and precipitation processes that currently represent the largest source of uncertainty involved in determining the radiative forcing of climate change. Nevertheless, due to the exceptiona...
Quantum computers have attracted much attention in recent years. This is because the development of the actual quantum machine is accelerating. Research on how to use quantum computers is active in the fields such as quantum chemistry and machine learning, where vast amounts of computation are required. However, in weather and climate simulations,...
Thorpe analysis is a commonly used method to study turbulence, an important research object in the field of atmospheric science. However, using Thorpe analysis to retrieve turbulence parameters from radiosonde data can reduce inversion accuracy due to instrument noise. Therefore, this paper presents a new wavelet denoising method to determine the o...
Record breaking atmospheric methane growth rates were observed in 2020 and 2021 (15.2±0.5 and 17.8±0.5 parts per billion per year), the highest since the early 1980s. Here we use an ensemble of atmospheric inversions informed by surface or satellite methane observations to infer emission changes during these two years relative to 2019. Results show...
The study of Precipitable Water Vapour (PWV) using satellite data and ground-based observation is crucial for understanding hydrological processes, atmospheric circulation, and weather systems. It is considered the most prominent greenhouse gas in the Earth’s atmosphere. It is highly variable in both space and time across the Earth. Precipitable Wa...
Advanced three-dimensional (3D) tracking methods are essential for studying particle dynamics across a wide range of complex systems, including multiphase flows, environmental and atmospheric sciences, colloidal science, biological and medical research, and industrial manufacturing processes. This review provides a comprehensive summary of 3D parti...
Teaching synoptic analysis and forecasting consumes a
large fraction of my time and attention each fall semester
and has done so for over a decade. But I don’t mind. In
fact, teaching a course that is linked to exciting weather
phenomena and current meteorological situations is as
enjoyable as it is challenging. Each time I teach the class,
I...
The increasing amount of data in meteorological science requires effective data-reduction methods. Our study demonstrates the use of advanced scientific lossy compression techniques to significantly reduce the size of these large datasets, achieving reductions ranging from 5× to over 150×, while ensuring data integrity is maintained. A key aspect o...
Analogs are similar states of a system, occurring at remote times within independent numerical simulations or previous observations. This concept has been developed in atmospheric sciences, and was further used in atmospheric and ocean sciences for forecasting, downscaling, upscaling, extreme event attribution, and many other applications. The dist...
Based on the C-Coupler platform, the semi-unstructured Climate System Model, Synthesis Community Integrated Model version 2 (SYCIM2.0), has been developed at the School of Atmospheric Sciences, Sun Yat-sen University. SYCIM2.0 aims to meet the demand for seamless climate prediction through accurate climate simulation and projection. This paper prov...
High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume dispersion in complex terrain. However, their high computational cost makes them impractical for applications requiring rapid responses or iterative processes, such as optimization, uncertainty quantification, or inverse modeling. To address this ch...
This dissertation integrates advanced machine learning (ML) techniques with radar technology to address significant challenges in atmospheric sciences, cloud profiling, and aviation safety. It aims to enhance the accuracy and reliability of radar-based measurements, improve the prediction of atmospheric relative humidity and Cloud Liquid Water Cont...
Remote sensing time series research and applications are advancing rapidly in land, ocean, and atmosphere science, demonstrating emerging capabilities in space-based monitoring methodologies and diverse application prospects. This prompts a comprehensive review of remote sensing time series observations, time series data reconstruction, derived pro...
Climate change intensifies weather-related disasters, necessitating innovative mitigation strategies beyond conventional weather prediction methods. The Control Simulation Experiment (CSE) framework proposes altering weather systems through small perturbations, but its effectiveness relative to other control methods remains uncertain. This study ev...
Atmospheric aerosol, also commonly called airborne particulate matter (PM), is
a subject of extensive research that, since the beginning of the 1980s, has received
increased attention from the atmospheric science community. This is in part
due to the enormous advances in measurement technologies from that period,
which have allowed for an increasin...
For many disciplines of science, all conceivable collisional cross-sections and reactions must be precisely known. Although recent decades have seen a trial of large-scale research to obtain such data, many essential atomic and molecular cross-section data are still missing, and the reliability of the existing cross-sections has to be validated. In...
Os organizadores vêm expressar seus sinceros e calorosos agradecimentos a todos os professores e alunos que desenvolveram com suas pesquisas para a realização deste livro. A dedicação, o esforço e a paixão com que cada um de vocês se comprometeu em suas investigações foram fundamentais para a concretização desta obra. Cada capítulo enviado, com sua...
This paper aimed to analyze the effectiveness of the CCWorldWeatherGen tool, focusing on climate change in São Paulo, São Paulo State, Brazil. For this, dry-bulb temperature, relative humidity, global solar radiation, and wind speed data from the test reference year weather file (1954) and the CCWorldWeatherGen file for the 2020 period (representin...
Abstrak Prediksi cuaca terus berkembang seiring dengan kemajuan dalam ilmu atmosfer, teknologi komputasi, dan analisis data. Namun, penting untuk diingat bahwa cuaca adalah sistem yang kompleks dan sulit untuk diprediksi dengan sempurna. Prediksi cuaca masih memiliki keterbatasan dan tingkat ketidakpastian tertentu, terutama dalam jangka waktu yang...
Atmospheric rivers (ARs) are narrow corridors of intense water vapor transport, shaping precipitation, floods, and economies. Temporal clustering of ARs tripled losses compared to isolated events, yet the reasons behind this clustering remain unclear. AR orientation further modulates hydrological impacts through terrain interaction. Here we identif...
Atmospheric visibility is a crucial meteorological element impacting urban air pollution monitoring, public transportation, and military security. Traditional visibility detection methods, primarily manual and instrumental, have been costly and imprecise. With advancements in data science and computing, deep learning-based visibility detection tech...
Understanding and quantifying the predictability of various meteorological variables remains a significant challenge in atmospheric sciences, particularly in regions with complex climates. This study aims to assess the predictability limit of wind speed, pressure, temperature, and relative humidity using permutation entropy (PermEn) analysis. By an...
A student-focused field measurement campaign was held in the vicinity of Mt. Chacaltaya
in the Bolivian Andes near the city of La Paz on May 24, 2022. The campaign was part of a
program funded by the US Department of State, the main goal of which was to foster cultural
and scientific exchange among Bolivian and US students. As part of this exchange...
A new concept of time, termed natural time, was introduced in 2001. This new concept reveals unique dynamic features hidden behind time-series originating from complex systems. In particular, it was shown that the analysis of natural time enables the study of the dynamical evolution of a complex system and identifies when the system enters a critic...
In this paper, we consider generalized Kadomtsev-Petviashvili (KP) equation and presents new closed-form solutions through an analytical technique and Lie symmetry analysis. The KP equation, a key tool in modeling long waves and frequency dispersion, is relevant in various nonlinear physical systems. New soliton solutions—including single, multi, e...
El presente trabajo tiene como objetivo realizar un primer análisis, desde el enfoque de la cultura material, al barómetro que Benjamín Vicuña Mackenna identificó como el único que existía en Santiago de Chile a principios del siglo XIX. Tras una revisión de los primeros medios de comunicación publicados en el país, como La Aurora de Chile o El Mer...
The Benjamin-Ono equation can be used to describe the propagation and interaction of internal waves in stratified deep fluids. In this paper, we investigate a generalized (2+1)-dimensional Benjamin-Ono equation. We discuss the analytic solutions, including soliton, lump, and hybrid solutions, as well as the dynamic behaviors of those for this equat...
In recent years, the application of machine learning methods has become increasingly common in atmospheric science, particularly in modeling and predicting processes that impact air quality. This study focuses on predicting hydrogen production from solid oxide electrolytic cells (SOECs), a technology with significant potential for reducing greenhou...
Coastal fog occurs along many of the world’s west coast continental environments. It is particularly consequential during summer when an increased frequency of fog co-occurs with the seasonal dryness characteristic of most west coast climate systems, for example, in the Pacific coast of North and South America, the southwestern African coast, and s...
Analogue methods are widely used in atmospheric science for weather forecasting and climate risk studies. The concept of weather/climate analogues is straightforward: it quantifies the similarity between weather conditions at target and candidate time periods by computing a distance using relevant atmospheric variables (e.g., temperatures and geopo...
Evaluation of the Voigt function, a convolution of a Lorentzian and a Gaussian profile, is essential in various fields such as spectroscopy, atmospheric science, and astrophysics. Efficient computation of the function is crucial, especially in applications where the function may be called for an enormous number of times. In this paper, we present a...
Satellite observations have become increasingly important in scientific studies of the Earth’s climate, especially for oceanographic science. A next generation sensor known as the Ocean Color Instrument (OCI) was launched in February 2024 onboard the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) platform, and will extend the data set of on-o...
The Pyrenean Platform for Observation of the Atmosphere (P2OA) is a coupled plain–mountain instrumented platform in southwestern France. It is composed of two physical sites: the “Pic du Midi” mountaintop observatory (2877 m a.s.l.) and the “Centre de Recherches Atmosphériques” (600 m a.s.l). Both sites are complementarily instrumented for the moni...
Air pollution, characterized by high levels of particulate matter (PM), poses the greatest environmental threat to human health, causing an estimated 7 million deaths annually and accounting for 5 % of the global gross domestic product (GDP). While the health impacts of PM are influenced by the toxicity of its individual chemical constituents, the...
The complexities of urban climate and environmental challenges have garnered significant attention in the 21st century. Numerical simulations, offering high spatiotemporal resolution meteorological data, are essential tools in meteorological research and atmospheric science. Accurate representation of urban morphology parameters is crucial for enha...
Vertically resolved information on aerosol particles represents a key aspect in many atmospheric studies, including aerosol–climate interactions and aerosol impacts on air quality and human health. This information is primarily derived by lidar active remote sensing, in particular with extensive networks currently in operation worldwide. In Italy,...
This study investigates the chemical composition and physical properties of aerosols, which play a crucial role in influencing human health, cloud physics, and local climate. Our focus centers on the hygroscopicity of ambient aerosols, a key property reflecting the ability to take up moisture from the atmosphere and serve as cloud condensation nucl...
The Forecasters' WEB initiative organized a transformative 12‐day exchange/hackathon program; a collaboration between the Department of Meteorology and Climate Science at Kwame Nkrumah University of Science and Technology and the University of Energy and Natural Resources. Aimed at addressing climate change challenges, it equipped participants with...
This investigation explores the analytical solutions to the time-fractional multi-dimensional Navier–Stokes (NS) problem using advanced approaches, namely the Aboodh residual power series method and the Aboodh transform iteration method, within the context of the Caputo operator. The NS equation governs the motion of fluid flow and is essential in...
Since the 1970s, a network of disciplines has emerged to address the environmental crisis, starting with biological and atmospheric sciences and expanding to include international environmental law, engineering, and design. Our understanding has evolved from the human environment to sustainability, and now concepts like biophilia, biomimicry, regen...
This study presents an innovative approach to creating a dynamic, AI based emission inventory system for use with the Weather Research and Forecasting model coupled with Chemistry (WRF Chem), designed to simulate vehicular and other anthropogenic emissions at satellite detectable resolution. The methodology leverages state of the art deep learning...
Artificial intelligence and machine learning (AI/ML) have attracted a great deal of attention from the atmospheric science community. The explosion of attention on AI/ML development carries implications for the operational community, prompting questions about how novel AI/ML advancements will translate from research into operations. However, the fi...
Ice nucleation and growth are critical in many fields, including atmospheric science, cryobiology, and aviation. However, understanding the detailed mechanisms of ice crystal growth remains challenging. In this work, crystallization at the ice/quasi-liquid layer (QLL) interface of the basal and primary prism (prism1) surfaces of hexagonal ice (Ih)...
The analysis of photochemical data poses significant computational challenges due to its complexity and large dataset requirements. To address these limitations, this study proposes the development of an IT framework leveraging Graphics Processing Unit (GPU) acceleration. The framework integrates GPU-based parallel processing with optimized algorit...
El tránsito de los siglos XVIII a XIX conoció aportaciones muy significativas para el avance de las ciencias del tiempo y clima. Se propusieron interpretaciones sobre la naturaleza que manifestaron la influencia de las ideas filosóficas del momento. Autores como Kant, Laplace, Humboldt desarrollaron sus teorías sobre la naturaleza, mismas que evolu...
In this proof-of-concept study, we conduct multivariate timeseries forecasting for the concentrations of nitrogen dioxide (NO2), ozone (O3), and (fine) particulate matter (PM10 & PM2.5) with meteorological covariates between two locations using various deep learning models, with a focus on long short-term memory (LSTM) and gated recurrent unit (GRU...
📢 Call for Book Chapters
We are excited to announce a Call for Chapters for the upcoming book titled:
📖 Advances in Mathematical Modeling and Scientific Computing for Complex Systems
Subtitle: Innovative Applications in Biology, Medicine, Earth, and Atmospheric Science
Publisher: Elsevier (No publication charges)
Indexing: Scopus
To be publish...
Wind erosion is a phenomenon that involves various complex factors that are not yet fully
comprehended. Its study requires knowledge of multiple disciplines, including atmospheric sciences, fluid
dynamics, soil science, environmental and agricultural science, and land management. The desert areas of Iran
are geographically classified into two gener...
Atmospheric state analysis is a difficult scientific problem due to the chaotic nature of the atmosphere. Data assimilation is a framework for generating an accurate state analysis of a physical system using probability density functions (PDFs) describing uncertainty of information on the state of the physical system. However, since PDFs cannot be...
This paper investigates the feasibility of downscaling within high-dimensional Lorenz models through the use of machine learning (ML) techniques. This study integrates atmospheric sciences, nonlinear dynamics, and machine learning, focusing on using large-scale atmospheric data to predict small-scale phenomena through ML-based empirical models. The...
Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud‐SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi‐decadal SST variability. A heat‐...
Atmospheric state analysis is a difficult scientific problem but essential for atmospheric sciences. Data assimilation can generate accurate analyses by integrating information on the atmospheric state using probability density functions (PDFs), where the Gaussian approximation is typically used and PDFs are described by error covariance matrices (...