Hasil untuk "Meteorology. Climatology"

Jake Spisak, Christopher P. Riedel, Andrey Sushko et al.

WindBorne Systems has developed a constellation of long-duration atmospheric balloons to collect meteorological data across the globe, filling gaps in current in-situ data collection methods. Each Global Sounding Balloon (GSB) is capable of flying for weeks or months and performing dozens of soundings while measuring pressure, temperature, humidity, and GNSS-derived position, altitude, and wind velocity. This data is transmitted to ground via satellite, processed, and made available within minutes of being collected. The current meteorological sensor package has remained largely unchanged since mid-2024 and has flown on thousands of GSBs totaling over one million hours of flight time. Here we present the design and performance of this sensor package. The custom readout architecture and housing allow for data collection across nearly all in-flight conditions while minimizing sources of bias and noise. Uncertainty is characterized via sounding reproducibility studies and in-house calibration of pressure, humidity, and temperature sensors. The calibration and data processing procedures have been optimized and validated by comparison with external datasets. We present external validation in the form of 1) side-by-side radiosonde launches performed in collaboration with the Center for Western Weather and Water Extremes at the Scripps Institution of Oceanography, which show agreement within expected uncertainty limits, and 2) intercomparison studies with European Centre for Medium-Range Weather Forecasts Reanalysis v5, which show an aggregate root mean square difference of: Geopotential height -- 14 m; Pressure -- 0.36 hPa; Temperature -- 0.91 K; Wind speed u -- 2.45 m/s; Wind speed v -- 2.50 m/s; Relative humidity -- 13%.

Marcos Suárez-Vázquez, Sylvana Varela Ballesta, Alberto Otero-Cacho et al.

In past years, several studies have proposed new methods and applications for urban wind simulations. In this article, we present a fast and automatic methodology for reconstructing airflows within urban environments using LiDAR and cadastral data coupled with Computational Fluid Dynamics (CFD) simulations. Our approach integrates meteorological predictions with computational techniques to simulate the complex interactions between wind currents, buildings, vegetation, water zones and terrain morphology within urban environments. Accurate boundary conditions based on meteorological predictions are introduced into a coupled methodology that directly creates the terrain shape inside the simulation environment, simplifying the geometry creation process, which is one of the most prevalent problems in CFD urban simulations. The simulation results are confronted against ground-truth real data obtained from a meteorological station, showing strong agreement with the outcomes generated by the proposed CFD model, with a concordance correlation coefficient up to $ρ_c = 0.985$ for the wind direction and $ρ_c = 0.853$ for the wind speed. The results from these simulations are then used for validating a wind tunnel approach that mimics the interaction between a moving drone and the extracted wind currents, demonstrating a great improvement in computation times when compared to the most straightforward approach that consists in embedding the drone within the full urban landscape. This research contributes to the advancement of urban CFD modeling, and it has significant implications for various applications, providing valuable insights for urban development.

M. A. Cafolla, S. C. Chapman, N. W. Watkins et al.

Abstract Total Electron Content (TEC) is central to characterizing ionospheric response to solar and geomagnetic activity. Variations in TEC structures over time provide insight into underlying physical processes and inform monitoring of space weather events, which pose a risk to navigation and communication systems. JPL processed GNSS observations over 20 years provide a series of 15‐min Global Ionospheric Maps (GIMs) of spatial resolution 1°×1° longitude/latitude. We translate these into geomagnetic coordinates centered about the sub‐solar point and we isolate the top 1% of TEC values in each map to define High Density Regions (HDRs) of TEC. Image processing tools are used to develop an algorithm that detects and tracks these to compile a set of contiguous, uniquely labeled space‐time TEC HDRs. We find that HDRs naturally divide into two populations by peak area, separated by a size of 8.0×106km2, which is around the continental scale. These populations are studied for different storm conditions—quiet (Kp <4), moderate (4≤ Kp <7) and extreme (Kp ≥7): small HDRs form primarily around four magnetic latitude bands and move roughly parallel to lines of constant magnetic latitude toward later MLT. Large HDRs form around the same latitude bands but follow more complex paths. The statistical nature of these results could be used in predictive ionospheric models and identify reproducible trends on these spatial/temporal scales.

J. J. Curto, A. Segarra, J. M. Torta et al.

Abstract Geomagnetic storms produce global variations in the geomagnetic field that are measured at magnetic observatories. Roughly one half of magnetic storms are preceded by sudden increases in the horizontal component of the magnetic field world‐wide. These increases, called storm sudden commencements (SSC), produce geomagnetically induced currents and cause other space weather disturbances whose study is paramount due to the technological dependence of our society. SSC event lists date back to 1868 and provide invaluable information about interplanetary conditions over centennial time scales. Since 1975, the Service of Rapid Magnetic Variations has been responsible for the maintenance and consistency of the SSC list. Here we will review the significant changes in the definition and methods of SSC detection that have been introduced over time and will analyze and discuss whether those changes have affected the homogeneity of the SSC series. Alerted by the greatly reduced number of SSCs in solar cycle 24, we have reanalyzed SSC occurrence in the period 2006–2017. As a result, we found a 26% increase in the number of SSCs, which motivates a change in the adopted SSC definition but leaves the SSC level exceptionally low during this period. We completed the study by examining the relation and dependency of SSCs with solar sunspot numbers and the temporal variation of the horizontal magnetic field.

Natasha M. Garner, Fabian Mahrt, Jens Top et al.

Abstract Secondary organic aerosol (SOA) comprises most of the submicron atmospheric particle mass, and often becomes internally mixed with other particles. When SOA mixes with transition metal (e.g., iron) containing particles, metal-organic complexes can form, enabling photochemical reactions that change aerosol physicochemical properties. We studied the photochemistry of α-pinene SOA formed on iron-containing ammonium sulfate seed particles at varying relative humidities (RH). Chemical composition and photochemical reduction of particles were analyzed by X-ray spectromicroscopy and infrared spectroscopy. SOA formed at low vs. high RH had different chemical functionality, including abundant carboxylic acids and alcohols. Following photolysis, carboxylic acids and unsubstituted alkanes decreased, and alcohols increased, consistent with decarboxylation reactions. Iron in SOA formed at high RH was readily photochemically reduced, but iron in SOA formed at low RH was not. Overall, RH conditions at SOA formation affect not only chemical composition but also iron-complex formation and hence photochemical processing of aerosols.

Valter Barrera, Cristian Guerrero, Guadalupe Galindo et al.

Nevertheless, there is a lot to know about air pollutants in Mexico’s largest cities, like San Luis Potosi City, which is one of the 12 most crowded cities and is expected to grow in the next years; however, there is little information about air pollutant levels mainly particulate matter in their regulated size fractions (PM₁₀ or PM_2.5), and its main component of the Organic fraction: Black Carbon (BC), which is especially important because of its chemical properties and their effects on human health, air pollution, and climate change. This work presents a one-year BC monitoring in the northern part of the city (2018–2019) and another one-year BC monitoring in the southern area (2019–2020) during the health contingency situation due to the SARX-CoV-2 virus to obtain direct equivalent black carbon (eBC) concentrations and their main fractions related to fossil fuel and biomass burning using aethalometer AE-33, as well as other air pollutants concentrations measured at the same periods by the governmental local monitoring network (SEGAM). At the North, BC mass annual average concentration was (1.11 µg m⁻³), divided into seasonal stations, the cold season was the highest with (1.44 µg m⁻³), followed by the dry season (1.23 µg m⁻³), rainy season (0.94 µg m⁻³) and finally warm dry season (0.83 µg m⁻³). In the south, BC annual average concentration was (1.96 µg m⁻³); divided into seasons, the highest was the dry season with (2.73 µg m⁻³), followed by the cold season (2.37 µg m⁻³), dry warm season (1.61 µg m⁻³) and the rainy season (1.28 µg m⁻³). One of the main findings was the dominance of annual mean concentrations of BC originating from fossil fuels (BCff) on the north site in the city was 0.97 and on the south site (BCff) was 0.91 due to some forest fires during the monitoring period. This study presented information from two zones of a growing city in Mexico to generate new air pollutant indicators to have a better understanding of pollutant interactions in the city, to decrease the emission precursor sources, and reduce the health risks in the population.

Giacomo Blanco, Luca Barco, Lorenzo Innocenti et al.

Air pollution poses a significant threat to public health and well-being, particularly in urban areas. This study introduces a series of machine-learning models that integrate data from the Sentinel-5P satellite, meteorological conditions, and topological characteristics to forecast future levels of five major pollutants. The investigation delineates the process of data collection, detailing the combination of diverse data sources utilized in the study. Through experiments conducted in the Milan metropolitan area, the models demonstrate their efficacy in predicting pollutant levels for the forthcoming day, achieving a percentage error of around 30%. The proposed models are advantageous as they are independent of monitoring stations, facilitating their use in areas without existing infrastructure. Additionally, we have released the collected dataset to the public, aiming to stimulate further research in this field. This research contributes to advancing our understanding of urban air quality dynamics and emphasizes the importance of amalgamating satellite, meteorological, and topographical data to develop robust pollution forecasting models.

Isabell Stucke, Deborah Morgenstern, Georg J. Mayr et al.

This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat, especially to wind turbines, as the long-duration current of UL can cause significant damage. Current risk assessment methods overlook the impact of meteorological conditions, potentially underestimating UL risks. Therefore, this study employs random forests, a machine learning technique, to analyze the relationship between UL measured at Gaisberg Tower (Austria) and $35$ larger-scale meteorological variables. Of these, the larger-scale upward velocity, wind speed and direction at 10 meters and cloud physics variables contribute most information. The random forests predict the risk of UL across the study area at a 1 km$^2$ resolution. Strong near-surface winds combined with upward deflection by elevated terrain increase UL risk. The diurnal cycle of the UL risk as well as high-risk areas shift seasonally. They are concentrated north/northeast of the Alps in winter due to prevailing northerly winds, and expanding southward, impacting northern Italy in the transitional and summer months. The model performs best in winter, with the highest predicted UL risk coinciding with observed peaks in measured lightning at tall objects. The highest concentration is north of the Alps, where most wind turbines are located, leading to an increase in overall lightning activity. Comprehensive meteorological information is essential for UL risk assessment, as lightning densities are a poor indicator of lightning at tall objects.

Chng Saun Fong, Suneja Manavvi, Radhakrishnan Shanthi Priya et al.

Urban heat islands (UHIs) are negatively impacting the quality of the urban environment and outdoor thermal comfort (OTC) levels, which have raised concerns regarding their impact on urban health and well-being. Understanding of OTC level is crucial, particularly in tropical cities with year-round high temperatures and humidity. A study was conducted in Kuala Lumpur (KL), Malaysia, to determine the OTC level in a selected urban area through microclimate measurements and questionnaire surveys with 1157 respondents. Over half of the urban dwellers reported thermal discomfort, with a high perceived OTC level, indicating strong thermal adaptive behaviours among the urban dwellers despite the physiological stress. Confounding factors such as urban morphology, land cover and human activity patterns also influence the OTC level in the tropical city. The findings emphasize the need for interventions to improve the urban environment and promote better outdoor thermal comfort for city dwellers through measures such as green infrastructure, UHI mitigation and increasing public awareness.

Sicong Zhu, Yongdi Qiao, Wenjie Peng et al.

To estimate traffic facility-oriented particulate matter (PM) emissions, emission factors are both necessary and critical for traffic planners and the community of traffic professionals. This study used locally calibrated laser-scattering sensors to collect PM emission concentrations in a tunnel. Emission factors of both light-duty and heavy-duty vehicles were found to be higher in autumn compared to summer. Based on this study’s data analysis, PM emissions, in terms of mass, have a strong seasonal effect. The study also conducted a PM composition test on normal days and during haze events. Preliminary results suggested that the transformation of gaseous tailpipe emissions to PM is significant within the tunnel during a haze event. This study, therefore, recommends locally calibrated portable devices to monitor mobile-source traffic emissions. The study suggests that emission factor estimation of traffic modeling packages should consider the dynamic PM formation mechanism. The study also presents traffic policy implications regarding PM emission control.

G V Cesana, A S Ackerman, N Črnivec et al.

In the Earth system models (ESMs) participating in the Coupled Models Intercomparison Project phase 6 (CMIP6), the tropical low-cloud feedback is 50% more positive than its predecessors (CMIP5) and continues to dominate the spread in simulated climate sensitivity. In the context of recent studies reporting larger feedbacks for stratocumulus (Sc) than shallow cumulus (Cu) clouds, it appears crucial to faithfully represent the geographical extent of each cloud type to simulate realistic low-cloud feedbacks. Here we use a novel observation-based method to distinguish Sc and Cu clouds together with satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Clouds and the Earth’s Radiant Energy System (CERES) to evaluate Sc and Cu cloud fractions, cloud radiative effects and cloud feedbacks in the two latest generations of CMIP ESMs. Overall, the CMIP6 models perform better than the CMIP5 models in most aspects considered here, indicating progress. Yet the ensemble mean continues to underestimate the marine tropical low-cloud fraction, mostly attributable to Sc. Decomposition of the bias reveals that the Sc-regime cloud fraction is better represented in CMIP6, although Sc regimes occur too infrequently—even less frequently than in CMIP5. Building on our Sc and Cu discrimination method, we demonstrate that CMIP6 models also simulate more realistic low-cloud feedbacks than CMIP5 models, especially the Sc component. Finally, our results suggest that part of the CMIP6 low-cloud feedback increase can be traced back to greater cloud fraction in Sc-dominated regions.

Aurelienne A. S. Jorge, Douglas Uba, Alex A. Fernandes et al.

The study of complex systems in nature is essential to understand the interactions between different elements and how they influence one another. Complex network theory is a powerful tool that helps us to analyze these interactions and gain insights into the behavior of such systems. Surprisingly, this theory has been underutilized in the field of weather science, which focuses on the immediate state of the atmosphere. Our research aims to fill this gap by exploring the use of complex network theory in weather science. Specifically, we employ weather radar data to construct event-based geographical networks. By analyzing the relations between meteorological properties and network metrics in these event-based networks, we can gain a better understanding of the behavior of precipitation events. Our findings reveal significant correlations between various meteorological properties and network metrics, shedding light on the underlying mechanisms that govern precipitation events. Through our work, we hope to demonstrate the potential of complex network theory in weather science and inspire further research in this field.

Pascal Marquet

The aim of this note is to describe several meteorological properties shown in a conference talk (Marquet, January 2022) for the moist-air specific entropy, the associated potential temperature ($θ_s$) defined in Marquet (2011) and the associated potential vorticity $PV(θ_s)$ defined in Marquet (2014), with in particular regions of negative values of $PV(θ_s)$ close to the cold fronts that seems to indicate regions of symmetric instability.

Luis Eduardo Ordoñez Palacios, Víctor Bucheli Guerrero, Hugo Ordoñez

Knowing the behavior of solar radiation at a geographic location is essential for the use of energy from the sun using photovoltaic systems; however, the number of stations for measuring meteorological parameters and for determining the size of solar fields in remote areas is limited. In this work, images obtained from the GOES-13 satellite were used, from which variables were extracted that could be integrated into datasets from meteorological stations. From this, 3 different models were built, on which the performance of 5 machine learning algorithms in predicting solar radiation was evaluated. The neural networks had the highest performance in the model that integrated the meteorological variables and the variables obtained from the images, according to an analysis carried out using four evaluation metrics; although if the rRMSE is considered, all results obtained were higher than 20%, which classified the performance of the algorithms as fair. In the 2012 dataset, the estimation results according to the metrics MBE, R2, RMSE, and rRMSE corresponded to -0.051, 0.880, 90.99 and 26.7%, respectively. In the 2017 dataset, the results of MBE, R2, RMSE, and rRMSE were -0.146, 0.917, 40.97 and 22.3%, respectively. Although it is possible to calculate solar radiation from satellite images, it is also true that some statistical methods depend on radiation data and sunshine captured by ground-based instruments, which is not always possible given that the number of measurement stations on the surface is limited.

Yao Yu, Ruikai Sun, Yindong Sun et al.

Ports offer an effective way to facilitate the global economy. However, massive carbon emission during port operating aggravates the atmospheric pollution in port cities. Capturing characteristics of port carbon emission is vital to reduce GHG (greenhouse gas) in the maritime realm as well as to achieve China’s carbon neutral objective. In this work, an integrated framework is proposed for exploring the driving factors of China ports’ emissions combined with stochastic effects on population, affluence and technology regression (STIRPAT), Global Malmquist-Luenberger (<i>GML</i>) and multiple linear regression (MLR). The port efficiency is estimated for each port and the potential driving factors of carbon emission are explored. The results indicate that port carbon emissions have a strong connection with port throughput, productivity, containerization and intermodal transshipment. It is worth noting that the containerization ratio and port physical facility with fossil-free energy improvement have positively correlated with carbon emissions. However, the specific value of waterborne transshipment shows a complex impact on carbon dioxide emission as the ratio increases. The findings reveal that China port authorities need to improve containerization ratio and develop intermodal transportation; meanwhile, it is responsible for port authorities to update energy use and improve energy efficiency in ways to minimize the proportion of non-green energy consumption in accordance with optimizing port operation management including peak shaving and intelligent management systems under a new horizon of clean energy and automatic equipment.

Chunxue Wang, Yueqing Li

In this study, the relationship between the East Asian subtropical westerly jet (EASWJ) and the East Asian summer monsoon (EASM) (westerly monsoon) and the correlation with the atmospheric heat source (AHS) on the Tibetan plateau (TP), especially the possible connection of the sudden enhancement of the correlation in August were analyzed. The results show that there is a significant correlation between the EASWJ and the EASM from June to October in terms of both intra-annual variability and interannual fluctuations, and the correlation between the AHS over TP and the EASWJ and the EASM during the same period is significantly enhanced in August. The synthetic analysis indicated that when the AHS was strong, a positive anomaly of a horizontal temperature gradient appeared over TP, which was conducive to the southward shift of the high-altitude temperature gradient center, resulting in the southward position of the axis of the 200 hPa westerly jet, and an upward and downward inclined westerly anomaly zone appeared from the south slope of TP to the main body and its north slope. Meanwhile, the East Asia–Pacific (EAP) teleconnection pattern with a negative phase appeared at 500 hPa, and TP to western Japan was located in the negative value area of the wave train. The AHS was conducive to the enhancement of the EAP negative phase, which was not conducive to the further northward transportation of water vapor by the EASM. On the contrary, when the AHS on TP was weak, the position of the westerly jet was northward and the EAP positive phase enhanced, contributing to the further northward transport of water vapor from the EASM.

Wesam Alyeddin, Sarah Peters, Adrianna Aleksandra Zembrzycka et al.

To reduce the environmental sequelae associated with medical education, at Oxford Medical School we have piloted a scheme since Spring 2020 to clean, repackage and then reuse non-sharp, traditionally ‘single-use-only’ equipment used in clinical skills training. Here we summarize the progress made by April 2022, which includes substantial reductions in the amount of equipment we have needed to procure, the quantities of clinical waste sent for disposal, and the associated financial costs. We estimate that annually our project results in more than 247 kg of reusable equipment being diverted from clinical waste at our institution. It has been crucial to ensure that equipment is recycled to a standard which still provides students with a safe learning experience which closely simulates the real clinical environment. Meeting the ongoing demand for clinical equipment essential to the day to day running of the clinical skills laboratory has also required consistent work. However, through this project we have developed methods for reusing equipment in the clinical skills setting which overcome these challenges. The Standard Operating Procedures provided here are designed to enable other clinical skills centers to introduce similar initiatives, so that collectively we may work to reduce the environmental impact of clinical skills teaching. This project is part of a wider movement within Oxford Medical School to include sustainability as a cross-curricular theme, and provides students with firsthand experience of how their work setting can be adapted to reduce its environmental impact.

Aprizon Putra, I. Dewata, M. Gusman

Climate change has had an impact on increasing hydrometeorological disasters in Indonesia. the Meteorology, Climatology and Geophysics Agency (BMKG) estimates, until mid-May 2020 Indonesia is threatened with a hydrometeorological disaster. Most of the Indonesian people are in areas prone to hydrometeorological disasters. To reduce its impact, the government needs to make adaptation efforts to climate change, which are carried out holistically and integrated by involving all elements of society and the government by referring to the National Action Plan for Climate Change Adaptation in Indonesia that has been prepared by the government of Indonesia.

N. Anggraini, B. Slamet

Evapotranspiration plays a big role in the hydrology process. Potential Evapotranspiration (PET) always keeps soil moisture available, although an amount of water evaporates through evaporation and transpiration. The Thornthwaite equation uses air temperature and latitude from meteorological observations for estimating PET. Medan City is one of the biggest cities in Indonesia that have a problem with land-use change that affected water balance. This study is to estimate the PET and to learn the water balance in Medan City. The monthly temperature data for the period 2011-2020 is collected from three meteorological stations for estimating PET using the Thornthwaite equation. The highest monthly temperature is in Belawan Maritime Meteorological Station yet the lowest rainfall. The trends of PET depend on the month. The highest PET in Jan.-Apr. and Sep.-Dec. are in Belawan Maritime Meteorological Station, while the highest PET in May-Aug. is in Indonesia Agency for Meteorology Climatology and Geophysics Region I Medan. The P-PET has shown negative and positive values. The lowest P-PET is found in Belawan Maritime Meteorological Station in March and the highest P-PET is found in Indonesia Agency for Meteorology Climatology and Geophysics Region I Medan in October.

Thomas A. Guinn, Daniel J. Halperin, Christopher G. Herbster

AbstractGeneral aviation (GA) accidents involving controlled flight into terrain often occur when pilots are unaware that their aircraft’s true altitude is lower than the altitude indicated by the pressure altimeter as a result of colder-than-standard temperatures. However, little guidance is available that quantifies the magnitude of these altimeter errors and their variation with season. In this study, the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset is combined with the pressure–altitude equation to construct a 30-yr monthly climatology, covering much of the United States and Canada, of D value (i.e., true altitude minus pressure altitude) corrected for the standard-atmosphere height separation between the altimeter setting and standard mean sea level pressure. This “corrected” D value therefore provides a useful estimate of the error between true and altimeter-indicated altitude. During winter, the mean corrected D values reach values as low as −350 m (~−1200 ft) in northern, low-terrain regions for flights near a pressure altitude of 3600 m, meaning the aircraft would be nearly 350 m lower than the altimeter indicates. Furthermore, the minimum (i.e., maximum negative) corrected D values are nearly double their mean values for the same time period. In addition, the reanalysis-based corrected D values are compared with estimated values calculated using a simple rule of thumb that is based solely on the air temperature at altitude and the surface elevation. The rule of thumb tends to underpredict the magnitude of the estimated error, in some cases by 70 m (~200 ft), and therefore gives a lower margin of safety.