Meteorological Observation Network Research Articles

Electric buses as an air pollution and meteorological observation network: Methodology and preliminary results

Many local agencies in the United States and other countries are tasked to install air pollution monitoring systems of highly accurate sensors that have high acquisition, operating, and maintenance costs. The need for expanded coverage of air quality measurements across Salt Lake County (SLCO), Utah is being met by mounting air quality and temperature sensors on an expanding fleet of battery electric buses (BEBs). Monitoring air quality from a mobile sensor network provides real-time insights into air pollution patterns at high temporal and spatial resolution. Mobile measurements contribute to assessing residents' exposure to air pollution, facilitating the implementation of cost-effective public health policies and highlighting disparities. The Electric Bus Air Quality Observation Project was launched in SLCO during July 2021 and has collected millions of observations to date. A BEB traveling at typical traffic speeds (~10 m s−1) can provide multiple measurements along city block lengths of up to ~200 m. With careful analysis that factors in the time response of the differing sensors, variability from block-to-block may be attributed to fine-scale factors (e.g., pollution and heat sources, tree shading and urban vegetation, etc.). Preliminary findings showcase the value of increased coverage and resolution. During an extreme heat event in July 2023, both the morning and afternoon temperature readings showed differences of over 6.5 °C (12 °F), primarily as an east-west gradient with similar gradients in ozone. We conclude that temperature and pollutant concentration readings, at fine spatial and temporal resolutions, will facilitate future health studies and equitable policy and mitigation strategies. Our study demonstrates that our partnerships established with governmental, non-profit, and transit agencies facilitate the successful transfer of research and development to operational real-time mobile air quality monitoring.

Research on Wind Speed Prediction Method Based on Feature Fusion

Wind speed occupies a central position in the study of atmospheric circulation and climate change, playing a crucial role in the accuracy and reliability of meteorological forecasting models. The current meteorological observation network, especially in remote and mountainous areas, faces challenges due to insufficient data resulting from low station density. This limitation hampers a comprehensive understanding of wind field dynamics, subsequently affecting the performance of forecasting models. To enhance the performance of meteorological prediction models, this study adopts an innovative approach that combines boxplot difference indexing and feature-level fusion techniques to filter key predictive features and reduce information redundancy. Furthermore, by integrating spatial location information, the contribution of geographic data to wind field prediction is enhanced, improving the quality of the fused data and thereby increasing the accuracy of model predictions. Experimental comparisons demonstrate that the integrated wind field dataset, post feature fusion, achieves better results across various deep learning models.

An approach to refining the ground meteorological observation stations for improving PM2.5 forecasts in the Beijing–Tianjin–Hebei region

Abstract. This paper investigates how to refine the ground meteorological observation network to greatly improve the PM2.5 concentration forecasts by identifying sensitive areas for targeted observations that are associated with a total of 48 forecasts in eight heavy haze events during the years of 2016–2018 over the Beijing–Tianjin–Hebei (BTH) region. The conditional nonlinear optimal perturbation (CNOP) method is adopted to determine the sensitive area of the surface meteorological fields for each forecast, and a total of 48 CNOP-type errors are obtained including wind, temperature, and water vapor mixing ratio components. It is found that, although all the sensitive areas tend to locate within and/or around the BTH region, their specific distributions are dependent on the events and the start times of the forecasts. Based on these sensitive areas, the current ground meteorological stations within and around the BTH region are refined to form a cost-effective observation network, which makes the relevant PM2.5 forecasts starting from different initial times for varying events assimilate fewer observations, but overall, it achieve the forecasting skill comparable to and even higher than that obtained by assimilating all ground station observations. This network sheds light on the idea that some of the current ground stations within and around the BTH region are very useless for improving the PM2.5 forecasts in the BTH region and can be greatly scattered to avoid unnecessary work.

Urbanization-Induced Diurnal Variation in Short-Duration Rainfall Events in Wuhan, China

Increasing of evidence suggests that rapid urbanization modifies precipitation and increases atmospheric instability in urban areas mainly due to urban heat island (UHI)-induced thermal effects and urban building-induced dynamic effects. However, few studies focus on the impact of urbanization on the diurnal variations in urban rainfall in terms of initiating time, frequency, amount, and intensity. Here, six years of hourly data from a relatively dense meteorological observation network in the Wuhan area in central China are used to quantify the issue of urbanization-induced diurnal variations in hourly rainfall and short-duration rainfall (SDR) events by comparing urban and surrounding rural stations during the summer dry period (13 July to 4 August), corresponding to hot weather with little rainfall and high evaporation. The results indicate that: (i) A higher frequency of hourly rainfall appears during night-time and afternoon over urban areas as compared to rural areas. The urban rainfall is more concentrated during the night-time; (ii) More and stronger urban SDR events are triggered during the night-time over urban areas, especially in terms of amount and intensity of rainfall events. A greater diurnal urban–rural difference in SDR events is detected than that in hourly mean rainfall; (iii) There is an enhancement in the night-time and afternoon urban SDR events when UHI intensity increases before they are initiated, and this is detectable in the frequency, amount, and intensity of SDR events. It is also found that the UHI-induced thermal effects are the main reason for the stronger nocturnal SDR events in Wuhan during the summer dry period, which is caused by increases in the convection current and water vapor flux convergence in the urban areas.

Диагностика града на основе данных ДМРЛ-С и результатов численного моделирования

The results of improving the algorithms for diagnosing hail on the Earth surface and its size based on the DMRL-C network and numerical prediction data are presented. The algorithms are implemented as part of an automated technology that operates in real time, with the presentation of results in a database and in the form of maps. A two-hour (relative to the observation period) animation of the diagnosed hail zones is provided. An algorithm for identifying the phase state of precipitation in a cloud is implemented, which made it possible to refine the diagnosis of hail in late spring and early autumn, rejecting cases with snow and ice pellets. The results of verifying the probability of detection of hail are given. It is concluded that the results of improving hail diagnosis using radar data will make it possible to refine data on cases of hail reaching the Earth surface in the European part of Russia, supplementing the already existing ones, according to the information of the network of meteorological and remote observations, which is also of practical importance for producing more accurate storm warnings about the occurrence of the phenomenon. Keywords: hail, diagnosis, phase state of precipitation in a cloud, radar data, DMRL-C network, automated technology

Performance Evaluation of TerraClimate Monthly Rainfall Data after Bias Correction in the Fes-Meknes Region (Morocco)

Morocco’s meteorological observation network is quite old, but the spatial coverage is insufficient to conduct studies over large areas, especially in mountainous regions, such as the Fez-Meknes region, where spatio-temporal variability in precipitation depends on altitude and exposure. The lack of station data is the main reason that led us to look for alternative solutions. TerraClimate (TC) reanalysis data were used to remedy this situation. However, reanalysis data are usually affected by a bias in the raw values. Bias correction methods generally involve a procedure in which a “transfer function” between the simulated and corrected variable is derived from the cumulative distribution functions (CDFs) of these variables. We explore the possibilities of using TC precipitation data for the Fez-Meknes administrative region (Morocco). This examination is of great interest for the region whose mountain peaks constitute the most important reservoir of water in the country, where TC data can overcome the difficulty of estimating precipitation in mountainous regions where the spatio-temporal variability is very high. Thus, we carried out the validation of TC data on stations belonging to plain and mountain topographic units and having different bioclimatic and topographic characteristics. Overall, the results demonstrate that the TC data capture the altitudinal gradient of precipitation and the average rainfall pattern, with a maximum in November and a minimum in July, which is a characteristic of the Mediterranean climate. However, we identified quasi-systematic biases, negative in mountainous regions and positive in lowland stations. In addition, summer precipitation is overestimated in mountain regions. It is considered that this bias comes from the imperfect representation of the physical processes of rainfall formation by the models. To reduce this bias, we applied the quantile mapping (QM) method. After correction using five QM variants, a significant improvement was observed for all stations and most months, except for May. Validation statistics for the five bias correction variants do not indicate the superiority of any particular method in terms of robustness. Indeed, results indicate that most QM methods lead to a significant improvement in TC data after monthly bias corrections.

Quality Management System for an IoT Meteorological Sensor Network—Application to Smart Seoul Data of Things (S-DoT)

Meteorological data with a high horizontal resolution are essential for user-specific weather application services, such as flash floods, heat waves, strong winds, and road ice, in urban areas. National meteorological observation networks, such as the Automated Synoptic Observing System (ASOS) and Automated Weather System (AWS), provide accurate but low horizontal resolution data to address urban-scale weather phenomena. Many megacities are constructing their own Internet of Things (IoT) sensor networks to overcome this limitation. This study investigated the status of the smart Seoul data of things (S-DoT) network and the spatial distribution of temperature on heatwave and coldwave event days. The temperature at above 90% of S-DoT stations was higher than that at the ASOS station, mainly because of different surface covers and surrounding local climate zones. A quality management system for an S-DoT meteorological sensor network (QMS-SDM) comprising pre-processing, basic quality control, extended quality control, and data reconstruction using spatial gap-filling was developed. The upper threshold temperatures for the climate range test were set higher than those adopted by the ASOS. A 10-digit flag for each data point was defined to discriminate between normal, doubtful, and erroneous data. Missing data at a single station were imputed using the Stineman method, and the data with spatial outliers were filled with values at three stations within 2 km. Using QMS-SDM, irregular and diverse data formats were changed to regular and unit-format data. QMS-SDM application increased the amount of available data by 20-30%, and significantly improved data availability for urban meteorological information services.

Dynamics of photosynthetic solar active radiation in Ukraine over 1986 - 2015

Photosynthetically active solar radiation (PSR) – solar radiation within the wavelength range of 380 ¼710 nm – forms a basis of plants' life that determines their photosynthesis. No measurements of photosynthetically active solar radiation (PSR) take place in Ukraine due to the lack of standard devices. Direct, scattered and total PSR is calculated via transition measurements and coefficients, whereas total PSR is measured via sunshine duration – using the indirect method. The purpose of the research is to determine PSR and its dynamics during specific months and the warm period of the year (April-October). The components of the radiation regime within the network of actinometric and meteorological observations in Ukraine for 1986 - 2015, 1986 - 1995, 1996 - 2005, 2006 - 2015 were obtained using mathematical statistics and climatological methods. In the course of the research changes in the PSR during specific months and the warm period over specific decades were determined. During the months of the warm period over 1986 -2015, direct, diffused, total PSR and total PSR calculated via sunshine duration tend to increase from the west, northwest or Ukrainian Carpathians to the southern steppe zone and Crimea. During the warm period over 1986 - 1995, the amount of direct PSR varies within 472 ¼ 891 MJ/m², diffused radiation – 887 ¼ 1156 MJ/m², total radiation – 1457 … 1917 MJ/m², total PSR calculated based on sunshine duration – 1621 … 2056 MJ/m²; over 1996 - 2005 the amount of direct PSR varies within – 469 … 1030 MJ/m², diffused – 802 … 1004 MJ / m², total – 1305 … 1973 MJ/m², total PSR calculated based on sunshine duration – 1654 … 2192 MJ/m²; over 2006 - 2015 the amount of direct PSR varies within 485 ¼ 1065 MJ/m², diffused radiation – 737 ¼ 951 MJ / m², total PSR – 1270 … 1977 MJ / m², total PSR calculated based on sunshine duration – 1649 … 2233 MJ / m². The increase in integrated direct solar radiation over 1996 - 2005 compared to 1986 - 1995, as well as over 2006 - 2015 compared to 1996 - 2005, led to an increase in direct PSR; the decrease in diffused solar radiation led to a decrease in diffused PSR; and ambiguous changes in the components of total solar radiation led to fluctuations in total PSR; increase in sunshine duration is accompanied by an increase in total PSR calculated based on sunshine duration. The research is relevant due to the factor of modern climate variability at the global and regional levels. The study of PSR changes is an urgent task of modern agrometeorology. It enables long-term effective planning of agricultural development.

Climate of the Pokuttia and Bukovyna Carpathians and foreland in the second half of the 19th – at the beginning of 20th centuries

Climate reconstruction of the Pokuttia and Bukovyna Carpathians, its foreland and adjacent mountain and foothill areas in the 19th century is performed due to a dense network of meteorological observations, starting from the 60s of the 19th century in the Bukovyna and Galychyna provinces within the Austrian Monarchy and several paleoclimatic reconstructions, mainly dendroclimatic, carried out on the basis of data collected in the Eastern Carpathians. Spatial interpolations using universal kriging has been performed based on in-situ homogenized data of weather stations of the second half of the 19th century – the first half of the 20th century. The longest series of observations in the city of Chernivtsi since 1852 has enabled to track multidecadal changes in average annual and monthly air temperatures and atmospheric precipitation. The centennial course of these climatic indicators corresponds to the general patterns characteristic of all the Eastern Carpathians with the most pronounced continentality among the rest of the Carpathian regions. Cold decades in the second half of the 19th century in Chernivtsi are considered the continuation of the coldest period of 1720–1850 in the Eastern Carpathians in the last 600 years. The spatial distribution peculiarities of average monthly temperatures in the second half of the 19th – at the beginning of 20th centuries in the region are manifested in a pronounced orographic steplike isotherm pattern. In the second half of the 19th century – the first half of the 20th century, the average long-term temperatures ranged from +3.5 to +4 °C in the southwest to +8 °C in the north and northeast in accordance to the orientation of the mountains. Inversion features of the valleys and internal lowlands are revealed in the spatial distribution of average temperatures, especially in the summer months. These features are also distinguished by a lower amount of atmospheric precipitation in the dry months of spring and autumn. Spatial distribution of temperature and precipitation in the second half of the 19th century – at the beginning of 20th century is also distinctive in the the inner mountain ridges of the adjacent Hryniava and Chornyi Dil mountains. These mountains are founded to be the coldest, often with a lack of meteorological summer and a maximum of precipitation in the spring and autumn months. A comparative analysis of the spatio-temporal distribution of average multi-year air temperatures and precipitation at the turn of the 19th and 20th centuries was performed. In general, similar distribution of air temperatures and precipitation is revealed. The differences are more noticeable in the monthly context, especially in summer and in the mountainous parts of the region. Comparing the turns of 19th and 20th centuries, the average July monthly temperature in the southernmost mountain massifs of the region has increased by 1 °C, while in the foothills the increase does not exceed 0.5 °C. In the annual context, changes are less noticeable. The range of air temperature changes from north to south is the same at the turn of both the 19th and 20th centuries. The city of Chernivtsi is founded to become a bit warmer (by 0.5 °C), but interannual fluctuations of annual air temperatures within 2 °C are typical throughout all the centuries. Alongside, high annual temperatures (+9 °C and higher) have been observed more often. While in the last century such temperatures were recorded once per 5–10 years, in the first decade of this century, annual temperature above +9 °C is recorded every second year. Short-term fluctuations (5–10 years) of annual precipitation amounts have been characteristic of the whole period since the 19th century. The interpretation of local climatic differences involves further devolopment of accurate interpolation techniques and downscaling, especially for the construction of precipitation field given lack of high-mountain weather stations in the earlier centuries. The latter corresponds to the future studies of the author.

ADT: The automatic weather station data tool

Climate data are essential in an array of climate research and applications. Climate data also provide the foundation for the provision of climate services. However, in many parts of Africa, weather stations are sparse, and their numbers have been declining over the last half-century. Moreover, the distribution of existing meteorological stations is uneven, with most weather stations located in towns and cities along the main roads. To address these data gaps, efforts over the last decade, largely driven by external donor funding, have focused on expanding meteorological observation networks in many parts of Africa, mainly through the provision of Automatic Weather Stations (AWS) to National Meteorological Services (NMS). While AWS offer a number of advantages over the conventional ones, which include automated reporting at a very fine temporal resolution (15 min, on average), they also have several disadvantages and accompanying challenges to their use. Some of these well-known challenges are the high maintenance requirements and associated costs that arise from the need to procure replacement parts that may not be available locally. However, another major, under-discussed challenge confronting NMS is the disparities between the different station types provided by different donors that has given rise to barriers to pragmatically using the plethora of data collected by AWS in decision-making processes. These disparities include major differences in the way the data from various AWS types are formatted and stored, which result in poorly coordinated, fragmented, and unharmonized datasets coming from different AWS networks. The end result is that while top-of-the-line AWS networks may systematically be collecting highly needed data, the inability of NMS to efficiently, combine, synchronize, and otherwise integrate these data coherently in their databases limits their use. To address these challenges, a free web-based application called Automatic Weather Station Data Tool (ADT) with an easy-to-use graphical user interface was developed to help NMS to access, process, perform quality control, and visualize data from different AWS networks in one place. Now implemented in five African countries (Ethiopia, Ghana, Kenya, Rwanda, and Zambia), ADT also enables real-time monitoring of stations to see which ones are working and which ones are offline. This tool emerged from a wider climate services approach, the Enhancing National Climate Services (ENACTS), recognizing that availability of high-quality climate data does not automatically translate to ease of access or effective use.

Wind variability over a large lake with complex topography: Lake of the Woods

Lake of the Woods spans two geological regions: the Precambrian Shield and the Glacial Lake Agassiz Lakebed. The lake watershed’s complex topography influences wind speeds and directions. We study wind variability over Lake of the Woods using reanalysis data and wind observations at seven sites. A wind variability index is proposed as a measure of lake-wide spread in wind direction. Our results show that the directional variability depends on wind speeds, with higher variability at lower speeds. The wind variability also changes throughout the year; it is more pronounced in spring (Apr-Jun) and fall (Sep-Oct) and less pronounced during winter (Dec-Jan). Observed wind directions are 60% more variable than reanalysis wind, indicating a need for higher-resolution reanalysis to resolve local wind effects due to topographic changes. Based on the statistical hierarchical clustering method, our analysis shows that geographically variable wind can be grouped into three regions to represent the predominant wind directions accurately. Clustering results also suggest spatial coverage gaps in the existing meteorological observation network. We reassess the existing network and propose a new meteorological observation site in the southeast basin near Morson, Ontario. Our study is of significance for water quality management because the wind is the key driver of water circulation, transport, and mixing in the lake, and accurate wind measurements are necessary to better constrain the underpinning physical, biological, and biochemical processes in mechanistic ecological models.

Optimizing Spatial Quality Control for a Dense Network of Meteorological Stations

Abstract Crowdsourced meteorological observations are becoming more prevalent and in some countries their spatial resolution already far exceeds that of traditional networks. However, due to the larger uncertainty associated with these observations, quality control (QC) is an essential step. Spatial QC methods are especially well suited for such dense networks since they utilize information from nearby stations. The performance of such methods usually depends on the choice of their parameters. There is, however, currently no specific procedure on how to choose the optimal settings of such spatial QC methods. In this study we present a framework for tuning a spatial QC method for a dense network of meteorological observations. The method uses artificial errors in order to perturb the observations to simulate the effect of having errors. A cost function, based on the hit and false alarm rate, for optimizing the spatial QC method is introduced. The parameters of the spatial QC method are then tuned such that the cost function is optimized. The application of the framework to the tuning of a spatial QC method for a dense network of crowdsourced observations in Denmark is presented. Our findings show that the optimal settings vary with the error magnitude, time of day, and station density. Furthermore, we show that when the station network is sparse, a better performance of the spatial QC method can be obtained by including crowdsourced observations from another denser network.

Automatic generation of textual descriptions in data-to-text systems using a fuzzy temporal ontology: Application in air quality index data series

In this paper we present a model based on computational intelligence and natural language generation for the automatic generation of textual summaries from numerical data series, aiming to provide insights which help users to understand the relevant information hidden in the data. Our model includes a fuzzy temporal ontology with temporal references which addresses the problem of managing imprecise temporal knowledge, which is relevant in data series. We fully describe a real use case of application in the environmental information systems field, providing linguistic descriptions about the air quality index (AQI), which is a very well-known indicator provided by all meteorological agencies worldwide. We consider two different data sources of real AQI data provided by the official Galician (NW Spain) Meteorology Agency: (i) AQI distribution in the stations of the meteorological observation network and (ii) time series which describe the state and evolution of the AQI in each meteorological station. Both application models were evaluated following the current standards and good practices of manual human expert evaluation of the Natural Language Generation field. Assessment results by two experts meteorologists were very satisfactory, which empirically confirm that the proposed textual descriptions fit this type of data and service both in content and layout.

ВИЗНАЧЕННЯ ЗМІН СКЛАДОВИХ РАДІАЦІЙНОГО РЕЖИМУ СОНЯЧНОЇ РАДІАЦІЇ ЗА 1991-2020 РР. ВІДНОСНО 1961-1990 РР. В УКРАЇНІ

During the observation period, significant changes in the influx of short-wave solar radiation due to the conditions of their passage through the Earth’s atmosphere and reflection from the underlying surface are registered. In the course of the study, the archive of observations of the meteorological and actinometric observation network of the Borys Sreznevsky Central Geophysical Observatory of the State Emergency Service of Ukraine was involved. A database of individual components of the Solar radiation regime has been compiled. Based on the methods of mathematical statistics, calculations of their spatial and temporal distribution on the territory of Ukraine were carried out. The results of changes in the components of the Solar radiation regime: direct, diffuse, and total solar radiation, albedo of the underlying surface, complete radiation balance and duration of sunshine during individual months, cold and warm periods, and year for the last three decades (1991-2020) relative to the climatological standard norm (1961-1990). Features of the modern climate affect the distribution of the components of the radiation regime and their change over the last three decades. This determines the expediency of determining the dynamics of the components of the radiation regime and their spatial distribution. The following components of the radiation regime experienced the greatest changes: duration of sunshine, direct and diffuse solar radiation. An increase in the duration of sunshine and direct solar radiation in the warm period of the year in a larger area of the country is characteristic. Scattered solar radiation decreased in almost all months of the cold and warm period almost everywhere in Ukraine. The total radiation increased during the warm period of the year, especially in the north and in the southern Steppe. The albedo of the underlying surface increased slightly, especially during the warm period in the south. The total radiation balance increased over a large area of the country, especially in the northeast and northwest. The determined changes in the formation of the components of the radiation regime are accompanied by changes during the growing season, with a tendency to increasing aridity and significantly affect the conditions for growing agricultural crops in Ukraine, which causes their spread across the territory. Their importance in the energy sector is due to the need to determine the profitability of operating solar energy plants for the production of electricity. The obtained conclusions are important for the use in the construction and operation of buildings of various purposes, as well as in general for climatic management of sectors of economy.

Creation of a representative climatological database for Hungary from 1870 to 2020

Climate studies, particularly those that are related to climate change, require long, high-quality controlled data sets, which are representative both spatially and temporally. Changing the conditions of measurements, for example relocating the station, or changing the frequency and timing of measurements, or changing the instruments used can cause breaks in the time series. To avoid these problems, data errors and inhomogeneities are eliminated and the data gaps are filled by using the MASH (Multiple Analysis of Series for Homogenization, Szentimrey, 1999, 2008) homogenization procedure. The Hungarian meteorological observation network was upgraded significantly in the last decades. Homogenization of the data series raises the question of how to homogenize long and short data series together within the same process. It is possible to solve this with the MASH method due it has solid mathematical foundations, which make it suitable for such purposes. The solution includes the synchronization of the common parts’ inhomogeneities within three (or more) different MASH processing of the three (or more) datasets with different lengths depending on the time periods and elements. After the homogenization process, the station data series were interpolated to a 0.1 degree regular grid covering the whole area of Hungary. The MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey and Bihari, 2007) program system was used for this purpose. The MISH procedure was developed specifically for the interpolation of various meteorological elements. In the case of mean temperature, we also renewed the MISH modeling, as compared to previous years, the number of homogenized stations doubled due to the new work, so it was expedient to model the climate statistical parameters with this extended station system. Time series of daily mean temperature and precipitation sum for the period 1870–2020 for Hungary were used in this study. As a result, the longest ever homogenized, gridded daily data sets became available for Hungary. The method described here can also be applied to produce representative datasets for other meteorological elements.

Observations of a Downburst and a Tornado by a High Density Ground Surface Meteorological Observation Network

Observations of a Downburst and a Tornado by a High Density Ground Surface Meteorological Observation Network

Microclimatic features of landscapes in the territory with a sparse network of meteorological observations

Automatic monitoring of air temperature and humidity in the mountain-depression landscapes of the Tunka depression has been organized. The results of the analysis of observation data for 10 years showed significant differences in the temperature regime in different landscapes. The sites can be divided into three groups – the slopes of the depression, pine- herbaceous landscapes, and the lacustrine-bog complex of the central part. The average annual air temperature at all sites is negative and vary in range -0.7 … -2.1°C. Vegetation has the greatest influence on microclimatic characteristics. The maximum contrasts in the temperature regime of the air throughout the year are observed in open areas with cloudless skies. In winter, this is explained by radiation cooling, and in summer – by the heating of the open surface in the daytime. In this case, not only the daily amplitude of air temperature in the open areas increases, but also the largest contrasts between the open and closed areas are observed.

Elaboration of Octagonal Roses to represent the wind patterns in the Port de Veracruz during the last 10 years

The Port de Veracruz and its surroundings are affected by meteorological phenomena such as the passage of frontal systems, among others. The main objective of this writing is to carry out continuous monitoring to categorize wind behavior, in order to determine patterns in the last 10 years. Therefore, climatological records of the intensity and direction of the average wind speeds are presented; wind data from three Automatic Meteorological Surface Stations (EMAS) of the Meteorological Observation Network of the Secretariat of the Navy, one of the National Meteorological Service (SMN) and two buoys of the National Oceanic and Atmospheric Administration (NOAA) were processed and analyzed. The results indicated that the North (N) direction predominately governs during the cold front season, while the East (E) winds predominately govern during the warm months (June, July, August and September). The maximum gusts, which can be an important factor in accidents, especially when their intensity exceeds 20 knots, affect various human, maritime, agricultural and livestock activities and tourism.

Overhauling the Activities of Ghana Meteorological Agency through ICT

Faced with the growing risks of weather and climate disasters to economic and social development, the global community needs to act quickly to strengthen National Meteorological and Hydrological Services. This strengthening must be done in a way that transforms the agency, especially in developing Ghana into a robust professional agency capable of delivering the right information to the right people at the right time. Although the cost of modernizing and sustaining the Ghana Meteorological Agency will be huge, the rewards for Ghana and its citizens will be much significant. This analytical work assesses the Ghana Meteorological Agency (GMET) for Hydrometeorology based on the user community needs. The analysis identifies gaps and challenges such as a deterioration of hydro meteorological observation networks and outdated technologies, and a lack of modern equipment and forecasting methods in producing and delivering weather, climate and hydrological information and services, and it lays out a technical technological and strategic framework for policy and decision makers in the Ministry of communication and the government at large. The Road Map postulates three scenarios, which are institutional strengthening and capacity building; modernization of observation, ICT and forecasting infrastructure; and enhancement of service delivery system for modernizing the GMET based on the potential cost and benefits of each while aiming at a greater national, regional and public good. The proposed scenarios target the GMET capacity: (i) to produce, manage, translate and communicate hydro-meteorological information to the user community; (ii) to assist the community in accessing, interpreting and using the information; (iii) to better disseminate and respond to warnings for public safety and economic security; (iv) to inform planning and decision making for cost-effective investments in climate-resilient development; and empowering its human resource; (v) identify red zone regions with these muddles. Strengthening these five pillars can help solidify Ghana’s resilience to natural hazards and climate change and help enhance the economic performance of such weather dependent sectors as agriculture, energy, transport and water resources management. This study recommends that, low-cost, high-priority activities are provided to achieve critical minimal capabilities to provide weather, climate and hydrological services and monetary investments are also needed to facilitate full modernization and bring the Ghana Meteorological Agency to the level of advanced middle income countries’ capabilities for providing data, forecasts and warning services to meet user needs. Keywords: Hydro-meteorological, Overhauling, ICT, Modernization, Sustainability.

Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards (STORM973) project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region (BMR) during the warm season from 2014 to 2018. The aim of the project was to understand how dynamical, microphysical and electrical processes interact in severe thunderstorms in the BMR, and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts. The platforms used in the field campaign included the Beijing Lightning Network (BLNET, consisting of 16 stations), 2 X-band dual linear polarimetric Doppler radars, and 4 laser raindrop spectrometers. The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region. Although diverse thunderstorm types were documented, it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area, influenced by the terrain and environmental conditions. The flash density maximums were found in eastern Changping District, central and eastern Shunyi District, and the central urban area of Beijing, suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing. In addition, the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions. The super (5% of the total), strong (35%), and weak (60%) thunderstorms contributed about 37%, 56%, and 7% to the total flashes in the BMR, respectively. Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms, the lightning flash rate can be used as an indicator of severe weather events, such as hail and short-duration heavy rainfall. Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale, through adjusting or correcting the thermodynamic and microphysical parameters of the model.