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Early Career Scientists' (ECS) Contributions to Meteorology (2023)

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A special issue of Meteorology (ISSN 2674-0494).

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 23181

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Dr. Edoardo Bucchignani

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Meteorology Laboratory, CIRA Italian Aerospace Research Center, 81043 Capua, CE, Italy
Interests: regional climate modeling; climate changes; numerical weather prediction models; extreme events
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Special Issue Information

Dear Colleagues,

In 2022, we launched a Special Issue (SI) aiming to provide an opportunity for early-career scientists in meteorology to share their valuable results with the scientific community. This SI attracted many young scientists and a relevant number of papers has already been published. For this reason, we have decided to launch the 2023 edition of this SI.

As for the previous edition, we welcome the submission of manuscripts concerning all meteorological topics. Examples of exciting subjects that could be addressed in this SI are:

Current challenging areas in weather models, including (but not limited to) data assimilation techniques, the optimization of parameterization schemes, model calibrations and ensemble forecasting.
AI and machine learning techniques for improving weather forecasts.
Coupling between air quality and meteorological models.
Small-scale processes in the atmosphere: improvement in terms of the representation of clouds and the diurnal cycle of deep convection.
Remote sensing in meteorology (e.g., innovative studies focusing on cloud microphysics and wind profile satellite observations).
Urban weather: urban heat islands, the interaction between meteorological and social worlds and local nowcasting tools for the drone operational spaces (low atmosphere).

This Special Issue accepts manuscripts in the form of original research or review articles, where the first author is an ECS (a student, a PhD candidate or a practicing scientist who received their highest certificate within the past 5 years). We plan to provide additional discounts on the APC (article processing charge) upon request, as well as additional guidance on how to address reviewer comments; the publication process will be as transparent and efficient as possible. Submissions will be assessed by at least two referees, as rigorously as any other paper submitted to the journal Meteorology.

Dr. Edoardo Bucchignani
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Meteorology is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

numerical weather prediction models
remote sensing
model assessment
extreme events
urban weather
small-scale processes

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Related Special Issues

Early Career Scientists' (ECS) Contributions to Meteorology (2024) in Meteorology (3 articles)
Early Career Scientists' (ECS) Contributions to Meteorology (2022) in Meteorology (15 articles)

Published Papers (13 papers)

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Editorial

Jump to: Research

3 pages, 168 KiB

Open AccessEditorial

Early Career Scientists’ (ECS) Contributions to Meteorology 2023

by Edoardo Bucchignani

Meteorology 2024, 3(2), 232-234; https://doi.org/10.3390/meteorology3020011 - 27 May 2024

Viewed by 581

Abstract

In the frame of the current growing awareness of climate change and its impact on society and ecosystems [...] Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

Research

Jump to: Editorial

27 pages, 9997 KiB

Open AccessArticle

System for Analysis of Wind Collocations (SAWC): A Novel Archive and Collocation Software Application for the Intercomparison of Winds from Multiple Observing Platforms

by Katherine E. Lukens, Kevin Garrett, Kayo Ide, David Santek, Brett Hoover, David Huber, Ross N. Hoffman and Hui Liu

Meteorology 2024, 3(1), 114-140; https://doi.org/10.3390/meteorology3010006 - 7 Mar 2024

Viewed by 1145

Abstract

Accurate atmospheric 3D wind observations are one of the top priorities for the global scientific community. To address this requirement, and to support researchers’ needs to acquire and analyze wind data from multiple sources, the System for Analysis of Wind Collocations (SAWC) was jointly developed by NOAA/NESDIS/STAR, UMD/ESSIC/CISESS, and UW-Madison/CIMSS. SAWC encompasses the following: a multi-year archive of global 3D winds observed by Aeolus, sondes, aircraft, stratospheric superpressure balloons, and satellite-derived atmospheric motion vectors, archived and uniformly formatted in netCDF for public consumption; identified pairings between select datasets collocated in space and time; and a downloadable software application developed for users to interactively collocate and statistically compare wind observations based on their research needs. The utility of SAWC is demonstrated by conducting a one-year (September 2019–August 2020) evaluation of Aeolus level-2B (L2B) winds (Baseline 11 L2B processor version). Observations from four archived conventional wind datasets are collocated with Aeolus. The recommended quality controls are applied. Wind comparisons are assessed using the SAWC collocation application. Comparison statistics are stratified by season, geographic region, and Aeolus observing mode. The results highlight the value of SAWC’s capabilities, from product validation through intercomparison studies to the evaluation of data usage in applications and advances in the global Earth observing architecture. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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14 pages, 4472 KiB

Open AccessArticle

On the Human Thermal Load in Fog

by Erzsébet Kristóf, Ferenc Ács and Annamária Zsákai

Meteorology 2024, 3(1), 83-96; https://doi.org/10.3390/meteorology3010004 - 6 Feb 2024

Viewed by 997

Abstract

We characterized the thermal load of a person walking and/or standing in the fog by analyzing the thermal resistance of clothing, r_cl, and operative temperature, T_o. The r_cl–T_o model applies to individuals using weather data. The body mass index and basal metabolic flux density values of the person analyzed in this study are 25 kg m⁻² and 40 W m⁻², respectively. Weather data are taken from the nearest automatic weather station. We observed 146 fog events in the period 2017–2024 in Martonvásár (Hungary’s Great Plain region, Central Europe). The main results are as follows: (1) The r_cl and T_o values were mostly between 2 and 0.5 clo and −4 and 16 °C during fog events, respectively. (2) The largest and smallest r_cl and T_o values were around 2.5 and 0 clo and −7 and 22 °C, respectively. (3) The r_cl differences resulting from interpersonal and wind speed variability are comparable, with a maximum value of around 0.5–0.7 clo. (4) Finally, r_cl values are significantly different for standing and walking persons. At the very end, we can emphasize that the thermal load of the fog depends noticeably on the person’s activity and anthropometric characteristics. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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34 pages, 10447 KiB

Open AccessArticle

The Impact of the Tropical Sea Surface Temperature Variability on the Dynamical Processes and Ozone Layer in the Arctic Atmosphere

by Andrew R. Jakovlev and Sergei P. Smyshlyaev

Meteorology 2024, 3(1), 36-69; https://doi.org/10.3390/meteorology3010002 - 22 Jan 2024

Cited by 1 | Viewed by 1072

Abstract

Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period from 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the CP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warming events are often observed, which lead to the destruction of PV and an increase in column ozone. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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35 pages, 9464 KiB

Open AccessArticle

A Data-Driven Study of the Drivers of Stratospheric Circulation via Reduced Order Modeling and Data Assimilation

by Julie Sherman, Christian Sampson, Emmanuel Fleurantin, Zhimin Wu and Christopher K. R. T. Jones

Meteorology 2024, 3(1), 1-35; https://doi.org/10.3390/meteorology3010001 - 19 Dec 2023

Cited by 1 | Viewed by 1608

Abstract

Stratospheric dynamics are strongly affected by the absorption/emission of radiation in the Earth’s atmosphere and Rossby waves that propagate upward from the troposphere, perturbing the zonal flow. Reduced order models of stratospheric wave–zonal interactions, which parameterize these effects, have been used to study [...] Read more.

Λ

, forcing the mean radiative zonal wind gradient, and h, a perturbation parameter representing the effect of Rossby waves. We take one such reduced order model with 20 years of ECMWF atmospheric reanalysis data and estimate

Λ

and h using both a particle filter and an ensemble smoother to investigate if the highly-simplified model can accurately reproduce the averaged reanalysis data and which parameter properties may be required to do so. We find that by allowing additional complexity via an unparameterized

Λ (t)

, the model output can closely match the reanalysis data while maintaining behavior consistent with the dynamical properties of the reduced-order model. Furthermore, our analysis shows physical signatures in the parameter estimates around known SSW events. This work provides a data-driven examination of these important parameters representing fundamental stratospheric processes through the lens and tractability of a reduced order model, shown to be physically representative of the relevant atmospheric dynamics. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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17 pages, 3066 KiB

Open AccessArticle

Comparison Link Function from Summer Rainfall Network in Amazon Basin

by C. Arturo Sánchez P., Alan J. P. Calheiros, Sâmia R. Garcia and Elbert E. N. Macau

Meteorology 2023, 2(4), 530-546; https://doi.org/10.3390/meteorology2040030 - 13 Dec 2023

Viewed by 1555

Abstract

The Amazon Basin is the largest rainforest in the world, and studying the rainfall in this region is crucial for understanding the functioning of the entire rainforest ecosystem and its role in regulating the regional and global climate. This work is part of the application of complex networks, which refer to a network modeled by graphs and are characterized by their high versatility, as well as the extraction of key information from the system under study. The main objective of this article is to examine the precipitation system in the Amazon basin during the austral summer. The networks are defined by nodes and connections, where each node represents a precipitation time series, while the connections can be represented by different similarity functions. For this study, three rainfall networks were created, which differ based on the correlation function used (Pearson, Spearman, and Kendall). By comparing these networks, we can identify the most effective method for analyzing the data and gain a better understanding of rainfall’s spatial structure, thereby enhancing our knowledge of its impact on different Amazon basin regions. The results reveal the presence of three important regions in the Amazon basin. Two areas were identified in the northeast and northwest, showing incursions of warm and humid winds from the oceans and favoring the occurrence of large mesoscale systems, such as squall lines. Additionally, the eastern part of the central Andes may indicate an outflow region from the basin with winds directed toward subtropical latitudes. The networks showed a high level of activity and participation in the center of the Amazon basin and east of the Andes. Regarding information transmission, the betweenness centrality identified the main pathways within a basin, and some of these are directly related to certain rivers, such as the Amazon, Purus, and Madeira. Indicating the relationship between rainfall and the presence of water bodies. Finally, it suggests that the Spearman and Kendall correlation produced the most promising results. Although they showed similar spatial patterns, the major difference was found in the identification of communities, this is due to the meridional differences in the network’s response. Overall, these findings highlight the importance of carefully selecting appropriate techniques and methods when analyzing complex networks. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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20 pages, 5097 KiB

Open AccessArticle

The Relationships between Adverse Weather, Traffic Mobility, and Driver Behavior

by Ayman Elyoussoufi, Curtis L. Walker, Alan W. Black and Gregory J. DeGirolamo

Meteorology 2023, 2(4), 489-508; https://doi.org/10.3390/meteorology2040028 - 19 Nov 2023

Cited by 2 | Viewed by 2801

Abstract

Adverse weather conditions impact mobility, safety, and the behavior of drivers on roads. In an average year, approximately 21% of U.S. highway crashes are weather-related. Collectively, these crashes result in over 5300 fatalities each year. As a proof-of-concept, analyzing weather information in the context of traffic mobility data can provide unique insights into driver behavior and actions transportation agencies can pursue to promote safety and efficiency. Using 2019 weather and traffic data along Colorado Highway 119 between Boulder and Longmont, this research analyzed the relationship between adverse weather and traffic conditions. The data were classified into distinct weather types, day of the week, and the direction of travel to capture commuter traffic flows. Novel traffic information crowdsourced from smartphones provided metrics such as volume, speed, trip length, trip duration, and the purpose of travel. The data showed that snow days had a smaller traffic volume than clear and rainy days, with an All Times volume of approximately 18,000 vehicles for each direction of travel, as opposed to 21,000 vehicles for both clear and wet conditions. From a trip purpose perspective, the data showed that the percentage of travel between home and work locations was 21.4% during a snow day compared to 20.6% for rain and 19.6% for clear days. The overall traffic volume reduction during snow days is likely due to drivers deciding to avoid commuting; however, the relative increase in the home–work travel percentage is likely attributable to less discretionary travel in lieu of essential work travel. In comparison, the increase in traffic volume during rainy days may be due to commuters being less likely to walk, bike, or take public transit during inclement weather. This study demonstrates the insight into human behavior by analyzing impact on traffic parameters during adverse weather travel. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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24 pages, 4091 KiB

Open AccessArticle

Espresso: A Global Deep Learning Model to Estimate Precipitation from Satellite Observations

by Léa Berthomier and Laurent Perier

Meteorology 2023, 2(4), 421-444; https://doi.org/10.3390/meteorology2040025 - 26 Sep 2023

Cited by 2 | Viewed by 2975

Abstract

Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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18 pages, 4148 KiB

Open AccessArticle

No City Left Behind: Building Climate Policy Bridges between the North and South

by Mohamed Hachaichi

Meteorology 2023, 2(3), 403-420; https://doi.org/10.3390/meteorology2030024 - 5 Sep 2023

Viewed by 1594

Abstract

Cities are progressively heightening their climate aspirations to curtail urban carbon emissions and establish a future where economies and communities can flourish within the Earth’s ecological limits. Consequently, numerous climate initiatives are being launched to control urban carbon emissions, targeting various sectors, including transport, residential, agricultural, and energy. However, recent scientific literature underscores the disproportionate distribution of climate policies. While cities in the Global North have witnessed several initiatives to combat climate change, cities in the Global South remain uncovered and highly vulnerable to climate hazards. To address this disparity, we employed the Balanced Iterative Reducing and Clustering using the Hierarchies (BRICH) algorithm to cluster cities from diverse geographical areas that exhibit comparable socioeconomic profiles. This clustering strives to foster enhanced cooperation and collaboration among cities globally, with the goal of addressing climate change in a comprehensive manner. In summary, we identified similarities, patterns, and clusters among peer cities, enabling mutual and generalizable learning among worldwide peer-cities regarding urban climate policy exchange. This exchange occurs through three approaches: (i) inner-mutual learning, (ii) cross-mutual learning, and (iii) outer-mutual learning. Our findings mark a pivotal stride towards attaining worldwide climate objectives through a shared responsibility approach. Furthermore, they provide preliminary insights into the implementation of “urban climate policy exchange” among peer cities on a global scale. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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16 pages, 9897 KiB

Open AccessArticle

Characteristics of Convective Parameters Derived from Rawinsonde and ERA5 Data Associated with Hailstorms in Northeastern Romania

by Vasilică Istrate, Dorin Podiuc, Dragoș Andrei Sîrbu, Eduard Popescu, Emil Sîrbu and Doru Dorian Popescu

Meteorology 2023, 2(3), 387-402; https://doi.org/10.3390/meteorology2030023 - 23 Aug 2023

Viewed by 1418

Abstract

Using a database of 378 hail days between 1981 and 2020, the climatic characteristics of 23 convective parameters from sounding data and ERA5 data were statistically analysed. The goal of this work is to evaluate the usefulness and representativeness of convective parameters derived from sounding data and reanalysis data for the operational forecast of the hail phenomenon. As a result, the average values from 12:00 UTC were 433 J/kg for CAPE in the case of data from ERA5 and 505 J/kg from rawinsonde, respectively. The Spearman correlation coefficient matrix between the values of the parameters indicates high correlations among the parameters calculated based on the parcel theory, humidity indices, and the complex indices. The probability for large hail increases with high values of low-level and boundary-layer moisture, high CAPE, and a high lifting condensation level (LCL) height. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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15 pages, 14356 KiB

Open AccessArticle

Influence of Underlying Topography on Post-Monsoon Cyclonic Systems over the Indian Peninsula

by Jayesh Phadtare

Meteorology 2023, 2(3), 329-343; https://doi.org/10.3390/meteorology2030020 - 31 Jul 2023

Cited by 2 | Viewed by 1648

Abstract

During the post-monsoon cyclone season, the landfalls of westward-moving cyclonic systems often lead to extreme rainfall over the east coast of the Indian peninsula. A stationary cyclonic system over the coast can produce heavy rainfall for several days and cause catastrophic flooding. This study analyzes the dynamics of a propagating and stationary cyclonic system over the east coast, highlighting the possible cause behind the stagnation. The vorticity budgets of these two systems are presented using a reanalysis dataset. Vortex stretching and horizontal vorticity advection were the dominant terms in the budget. Vertical advection and tilting terms were significant over the orography. The horizontal advection of vorticity was positive (negative) on the western (eastern) side of the systems and, thus, favored westward propagation. Vortex stretching was confined to the upstream of orography in the stationary vortex. In the propagating vortex, the vortex stretching occurred over the orography during its passage. Data from the radiosonde soundings over a coastal station showed orographic blocking of the low-level winds in the stationary case. Conversely, the flow crossed the orographic barrier in the propagating case. Thus, the predominance of the upstream orographic convergence over the vortex circulation can be the reason for system stagnation over the coast. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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15 pages, 8351 KiB

Open AccessArticle

Influence of Air Mass Advection on the Amount of Global Solar Radiation Reaching the Earth’s Surface in Poland, Based on the Analysis of Backward Trajectories (1986–2015)

by Kinga Kulesza

Meteorology 2023, 2(1), 37-51; https://doi.org/10.3390/meteorology2010003 - 9 Jan 2023

Viewed by 1859

Abstract

The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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18 pages, 6949 KiB

Open AccessArticle

Heat Waves Amplify the Urban Canopy Heat Island in Brno, Czechia

by Zdeněk Janků and Petr Dobrovolný

Meteorology 2022, 1(4), 477-494; https://doi.org/10.3390/meteorology1040030 - 30 Nov 2022

Cited by 4 | Viewed by 2399

Abstract

This study used homogenised mean, maximum, and minimum daily temperatures from 12 stations located in Brno, Czechia, during the 2011–2020 period to analyse heat waves (HW) and their impact on the canopy urban heat island (UHI). HWs were recognized as at least three consecutive days with T_x ≥ 30 °C and urban–rural and intra-urban differences in their measures were analysed. To express the HWs contribution to UHI, we calculated the UHI intensities (UHII) separately during and outside of HWs to determine the heat magnitude (HM). Our results show that all HW measures are significantly higher in urban areas. UHII is mostly positive, on average 0.65 °C; however, day-time UHII is clearly greater (1.93 °C). Furthermore, day-time UHII is amplified during HWs, since HM is on average almost 0.5 °C and in LCZ 2 it is even 0.9 °C. Land use parameters correlate well with UHII and HM at night, but not during the day, indicating that other factors can affect the air temperature extremity. Considering a long-term context, the air temperature extremity has been significantly increasing recently in the region, together with a higher frequency of circulation types that favour the occurrence of HWs, and the last decade mainly contributed to this increase. Full article

(This article belongs to the Special Issue Early Career Scientists' (ECS) Contributions to Meteorology (2023))

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