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13 pages, 2937 KiB

Open AccessArticle

An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities: Recife and Campina Grande

by Anwar Musah, Livia Màrcia Mosso Dutra, Aisha Aldosery, Ella Browning, Tercio Ambrizzi, Iuri Valerio Graciano Borges, Merve Tunali, Selma Başibüyük, Orhan Yenigün, Giselle Machado Magalhaes Moreno, Ana Clara Gomes da Silva, Wellington Pinheiro dos Santos, Clarisse Lins de Lima, Tiago Massoni, Kate Elizabeth Jones, Luiza Cintra Campos and Patty Kostkova

Data 2022, 7(8), 106; https://doi.org/10.3390/data7080106 - 30 Jul 2022

Cited by 8 | Viewed by 2957

Abstract

Certain weather conditions are inadvertently related to increased population of various mosquitoes. In order to predict the burden of mosquito populations in the Global South, it is imperative to integrate weather-related risk factors into such predictive models. There are a lot of online [...] Read more.

Certain weather conditions are inadvertently related to increased population of various mosquitoes. In order to predict the burden of mosquito populations in the Global South, it is imperative to integrate weather-related risk factors into such predictive models. There are a lot of online open-source weather platforms that provide historical, current and future weather forecasts which can be utilised for general predictions, and these electronic sources serve as an alternate option for weather data when physical weather stations are inaccessible (or inactive). Before using data from such online source, it is important to assess the accuracy against some baseline measure. In this paper, we therefore evaluated the accuracy and suitability of weather forecasts of two parameters namely temperature and humidity from the OpenWeatherMap API (an online weather platform) and compared them with actual measurements collected from the Brazilian weather stations (INMET). The evaluation was focused on two Brazilian cites, namely, Recife and Campina Grande. The intention is to prepare an early warning model which will harness data from OpenWeatherMap API for mosquito prediction. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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18 pages, 4351 KiB

Open AccessArticle

Handling Dataset with Geophysical and Geological Variables on the Bolivian Andes by the GMT Scripts

by Polina Lemenkova

Data 2022, 7(6), 74; https://doi.org/10.3390/data7060074 - 01 Jun 2022

Cited by 12 | Viewed by 3871

Abstract

In this paper, an integrated mapping of the georeferenced data is presented using the QGIS and GMT scripting tool set. The study area encompasses the Bolivian Andes, South America, notable for complex geophysical and geological parameters and high seismicity. A data integration was [...] Read more.

In this paper, an integrated mapping of the georeferenced data is presented using the QGIS and GMT scripting tool set. The study area encompasses the Bolivian Andes, South America, notable for complex geophysical and geological parameters and high seismicity. A data integration was performed for a detailed analysis of the geophysical and geological setting. The data included the raster and vector datasets captured from the open sources: the IRIS seismic data (2015 to 2021), geophysical data from satellite-derived gravity grids based on CryoSat, topographic GEBCO data, geoid undulation data from EGM-2008, and geological georeferences’ vector data from the USGS. The techniques of data processing included quantitative and qualitative evaluation of the seismicity and geophysical setting in Bolivia. The result includes a series of thematic maps on the Bolivian Andes. Based on the data analysis, the western region was identified as the most seismically endangered area in Bolivia with a high risk of earthquake hazards in Cordillera Occidental, followed by Altiplano and Cordillera Real. The earthquake magnitude here ranges from 1.8 to 7.6. The data analysis shows a tight correlation between the gravity, geophysics, and topography in the Bolivian Andes. The cartographic scripts used for processing data in GMT are available in the author’s public GitHub repository in open-access with the provided link. The utility of scripting cartographic techniques for geophysical and topographic data processing combined with GIS spatial evaluation of the geological data supported automated mapping, which has applicability for risk assessment and geological hazard mapping of the Bolivian Andes, South America. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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13 pages, 1167 KiB

Open AccessData Descriptor

Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics

by Georgy Ayzel

Data 2023, 8(2), 31; https://doi.org/10.3390/data8020031 - 30 Jan 2023

Cited by 1 | Viewed by 1448

Abstract

Global warming challenges communities worldwide to develop new adaptation strategies that are required to be based on reliable data. As a vital component of life, river runoff comes into particular focus as a determining and limiting factor of water-related hazard assessment. Here, we [...] Read more.

Global warming challenges communities worldwide to develop new adaptation strategies that are required to be based on reliable data. As a vital component of life, river runoff comes into particular focus as a determining and limiting factor of water-related hazard assessment. Here, we present a dataset that makes it possible to estimate the influence of projected climate change on runoff and its characteristics. We utilize the HBV (in Swedish, Hydrologiska Byråns Vattenbalansavdelning) hydrological model and drive it with the ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) meteorological forcing data for both historical (1979–2016) and projected (2017–2099) periods to simulate runoff and the respective hydrological states and variables, i.e., state of the soil reservoir, snow water equivalent, and predicted amount of melted water, for 425 river basins across Russia. For the projected period, the bias-corrected outputs from four General Circulation Models (GCM) under three Representative Concentration Pathways (RCPs) are used, making it possible to assess the uncertainty of future projections. The simulated runoff formed the basis for calculating its characteristics (191 in total), representing the properties of water regime dynamics. The presented dataset also comprises two auxiliary parts to ensure the seamless assessment of inter-connected hydro-meteorological variables and characteristics: (1) meteorological forcing data and its characteristics and (2) geospatial data. The straightforward use of the presented dataset makes it possible for many interested parties to identify and further communicate water-related climate change issues in Russia on a national scale. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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6 pages, 2678 KiB

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A Waveform Dataset in Continuous Mode of the Montefeltro Seismic Network (MF) in Central-Northern Italy from 2018 to 2020

by Antonella Megna, Giovanni Battista Cimini, Alessandro Marchetti, Nicola Mauro Pagliuca and Stefano Santini

Data 2022, 7(12), 169; https://doi.org/10.3390/data7120169 - 26 Nov 2022

Viewed by 1141

Abstract

The Montefeltro seismic network (FDSN Network code: 1S) was deployed in the Apennines area of northern Marche and southern Emilia-Romagna regions (central Italy). A temporary network was set up in December 2018 and continues to operate, with an array consisting of stations equipped [...] Read more.

The Montefeltro seismic network (FDSN Network code: 1S) was deployed in the Apennines area of northern Marche and southern Emilia-Romagna regions (central Italy). A temporary network was set up in December 2018 and continues to operate, with an array consisting of stations equipped with dynamic digitizers and three-component short/extended/broad band seismometers (Guralp CMG/20s and 30s, Lennartz 3D/5s, Sara SS20 3D/0.5s sensors). The network records in continuous mode at 100 sps. The data are used to analyze the seismic activity and the spatiotemporal evolution of small seismic sequences occurring in the considered area and surrounding zones, strongly clustered in time and space. The data of dataset files are mini-seed formatted and subdivided by the following tree: (1) the dataset is divided by years; (2) the dataset is then subdivided by stations; (3) finally, the data are divided by days of each year in every station folder. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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6 pages, 1188 KiB

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Data for Photodissociation of Some Small Molecular Ions Relevant for Astrochemistry and Laboratory Investigation

by Vladimir A. Srećković, Ljubinko M. Ignjatović, Aleksandra Kolarski, Zoran R. Mijić, Milan S. Dimitrijević and Veljko Vujčić

Data 2022, 7(9), 129; https://doi.org/10.3390/data7090129 - 11 Sep 2022

Cited by 2 | Viewed by 1712

Abstract

The calculated photodissociation data of some small molecular ions have been reported. The cross-sections and spectral rate coefficients data have been studied using a quantum mechanical method. The plasma parameters, i.e., conditions, cover temperatures from 1000 to 20,000 K and wavelengths in the [...] Read more.

The calculated photodissociation data of some small molecular ions have been reported. The cross-sections and spectral rate coefficients data have been studied using a quantum mechanical method. The plasma parameters, i.e., conditions, cover temperatures from 1000 to 20,000 K and wavelengths in the EUV and UV region. The influence of temperature and wavelength on the spectral coefficients data of all of the investigated species have been discussed. Data could also be useful for plasma diagnostics in laboratory, astrophysics, and industrial plasmas for their modelling. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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12 pages, 3156 KiB

Open AccessData Descriptor

Climate Dataset for South Africa by the Agricultural Research Council

by Mokhele Edmond Moeletsi, Lindumusa Myeni, Ludwig Christian Kaempffer, Derick Vermaak, Gert de Nysschen, Chrisna Henningse, Irene Nel and Dudley Rowswell

Data 2022, 7(8), 117; https://doi.org/10.3390/data7080117 - 17 Aug 2022

Cited by 2 | Viewed by 3223

Abstract

Long-term, reliable, continuous and real-time weather and climatic data are essential for efficient management and sustainable use of natural resources. This paper describes the weather station network (WSN) of the Agricultural Research Council (ARC) of South Africa, including information on instrumentation, data retrieval [...] Read more.

Long-term, reliable, continuous and real-time weather and climatic data are essential for efficient management and sustainable use of natural resources. This paper describes the weather station network (WSN) of the Agricultural Research Council (ARC) of South Africa, including information on instrumentation, data retrieval and processing protocols, calibration and maintenance protocols, as well as applications of the collected data. To this end, the WSN of the ARC consists of over 600 automatic weather stations that are distributed across the country to cover a wide range of agro-climatic zones. At each weather station, air temperature, rainfall, relative humidity, solar irradiance, wind speed and direction are monitored and archived on an hourly basis. The main objective of this WSN is to archive climate information for South Africa as well as supply the agricultural community with weather data to support decision-making. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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9 pages, 8316 KiB

Open AccessData Descriptor

An Inventory of Large-Scale Landslides in Baoji City, Shaanxi Province, China

by Lei Li, Chong Xu, Zhiqiang Yang, Zhongjian Zhang and Mingsheng Lv

Data 2022, 7(8), 114; https://doi.org/10.3390/data7080114 - 15 Aug 2022

Cited by 7 | Viewed by 1920

Abstract

Landslides are a typical geological hazard that endangers people’s lives and property in the Loess Plateau. The destructiveness of large-scale landslides, in particular, is incalculable. For example, traffic disruptions, river blockages, and house collapses may all result from landslides. Thus, it is urgent [...] Read more.

Landslides are a typical geological hazard that endangers people’s lives and property in the Loess Plateau. The destructiveness of large-scale landslides, in particular, is incalculable. For example, traffic disruptions, river blockages, and house collapses may all result from landslides. Thus, it is urgent to compile a complete inventory of landslides in a specific region. The investigation object of this study is Baoji City, Shaanxi Province, China. Using the multi-temporal high-resolution remote sensing images from Google Earth, we preliminarily completed the cataloging of large-scale (area > 5000 m²) landslides in the study area through visual interpretation. The inventory was subsequently compared with the existing literature and hazard records for improvement and supplement. We identified 3422 landslides with a total area of 360.7 km² and an average area of 105,400 m² for each individual landslide. The largest landslide had an area of 1.71 km², while the smallest one was 6042 m². In previous studies, we analyzed these data without describing the data sources in detail. We now provide a shared dataset of each landslide in shp format, containing geographic location, boundary information, etc. The dataset is significantly useful for understanding the distribution characteristics of large-scale landslides in this region. Moreover, it can serve as basic data for the study of paleolandslide resurrection. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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15 pages, 4765 KiB

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Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland

by Sandra Lorenz, Sam T. Thiele, Moritz Kirsch, Gabriel Unger, Robert Zimmermann, Pierpaolo Guarnieri, Nigel Baker, Erik Vest Sørensen, Diogo Rosa and Richard Gloaguen

Data 2022, 7(8), 104; https://doi.org/10.3390/data7080104 - 28 Jul 2022

Cited by 3 | Viewed by 2739

Abstract

Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. We present an open-source hypercloud dataset capturing the complex but spectacularly well exposed [...] Read more.

Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. We present an open-source hypercloud dataset capturing the complex but spectacularly well exposed geology from the Black Angel Mountain in Maarmorilik, West Greenland, alongside a detailed and interactive tutorial documenting relevant processing workflows. This contribution relies on very recent progress made on the correction, interpretation and integration of hyperspectral data in earth sciences. The possibility to fuse hyperspectral scans with 3D point cloud representations (hyperclouds) has opened up new possibilities for the mapping of complex natural targets. Spectroscopic and machine learning tools allow or the rapid and accurate characterization of geological structures in a 3D environment. Potential users can use this exemplary dataset and the associated tools to train themselves or test new algorithms. As the data and the tools have a wide range of application, we expect this contribution to benefit the scientific community at large. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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8 pages, 1428 KiB

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A Database of Topo-Bathy Cross-Shore Profiles and Characteristics for U.S. Atlantic and Gulf of Mexico Sandy Coastlines

by Rangley C. Mickey and Davina L. Passeri

Data 2022, 7(7), 92; https://doi.org/10.3390/data7070092 - 06 Jul 2022

Cited by 1 | Viewed by 2166

Abstract

A database of seamless topographic and bathymetric cross-shore profiles along with metrics of the associated morphological characteristics based on the latest available lidar data ranging from 2011–2020 and bathymetry from the Continuously Updated Digital Elevation Model was developed for U.S. Atlantic and Gulf [...] Read more.

A database of seamless topographic and bathymetric cross-shore profiles along with metrics of the associated morphological characteristics based on the latest available lidar data ranging from 2011–2020 and bathymetry from the Continuously Updated Digital Elevation Model was developed for U.S. Atlantic and Gulf of Mexico open-ocean sandy coastlines. Cross-shore resolution ranges from 2.5 m for topographic and nearshore portions to 10 m for offshore portions. Topographic morphological characteristics include: foredune crest elevation, foredune toe elevation, foredune width, foredune volume, foredune relative height, beach width, beach volume, beach slope, and nearshore slope. This database was developed to serve as inputs for current and future morphological modeling studies aimed at providing real-time estimates of coastal change magnitudes resulting from imminent tropical storm and hurricane landfall. Beyond this need for model inputs, the database of cross-shore profiles and characteristic metrics could serve as a tool for coastal scientists to visualize and to analyze varying local, regional, and national variations in coastal morphology for varying types of studies and projects related to Atlantic and Gulf of Mexico sandy coastline environments. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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6 pages, 2432 KiB

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Daily Precipitation Data for the Mexico City Metropolitan Area from 1930 to 2015

by Erika D. López-Espinoza, Oscar A. Fuentes-Mariles, Dulce R. Herrera-Moro, Octavio Gómez-Ramos, David A. Novelo-Casanova and Jorge Zavala-Hidalgo

Data 2022, 7(7), 88; https://doi.org/10.3390/data7070088 - 29 Jun 2022

Viewed by 1914

Abstract

The Metropolitan Zone of Mexico City, as well as the associated basin, includes the territories of Mexico City, some municipalities of the State of Mexico and the state of Hidalgo. In addition, this area is the most densely populated in Mexico. The region [...] Read more.

The Metropolitan Zone of Mexico City, as well as the associated basin, includes the territories of Mexico City, some municipalities of the State of Mexico and the state of Hidalgo. In addition, this area is the most densely populated in Mexico. The region is influenced by mid-latitude and tropical weather systems and is vulnerable to extreme hydrometeorological events. In this context, we developed a dataset from the records of 136 geolocated sites that includes daily precipitation data from the CLImate COMputing (CLICOM) project and the Mexico City Water System. The data spans the period from 1930 to 2015 for the rainy months (June–October) from stations with records of 20 or more years. In each recording site, automatic and manual data quality control were performed to verify the consistency of the daily precipitation data. We believe that our highly dense precipitation dataset will be useful for climate, trend and extreme events analysis. Additionally, the data will allow validating simulations of numerical atmospheric models. The dataset is public, and it was previously used in other research to determine areas susceptible to flooding due to heavy rain events and to develop a web mapping application of daily precipitation data. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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13 pages, 3197 KiB

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Quality Control Impacts on Total Precipitation Gauge Records for Montane Valley and Ridge Sites in SW Alberta, Canada

by Celeste Barnes and Chris Hopkinson

Data 2022, 7(6), 73; https://doi.org/10.3390/data7060073 - 30 May 2022

Viewed by 1984

Abstract

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These [...] Read more.

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49–76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50–76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784–1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731–1269 mm), while the valley gauge adjustments were −4% to 1% (−39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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10 pages, 2559 KiB

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Geomorphological Data from Detonation Craters in the Fehmarn Belt, German Baltic Sea

by Svenja Papenmeier, Alexander Darr and Peter Feldens

Data 2022, 7(5), 63; https://doi.org/10.3390/data7050063 - 11 May 2022

Cited by 1 | Viewed by 2335

Abstract

Military munitions from World War I and II dumped at the seafloor are a threat to the marine environment and its users. Decades of saltwater exposure make the explosives fragile and difficult to dispose of. If required, the munition is blast-in-place. In August [...] Read more.

Military munitions from World War I and II dumped at the seafloor are a threat to the marine environment and its users. Decades of saltwater exposure make the explosives fragile and difficult to dispose of. If required, the munition is blast-in-place. In August 2019, 42 ground mines were detonated in a controlled manner underwater during a NATO maneuver in the German Natura2000 Special Area of Conservation Fehmarn Belt, the Baltic Sea. In June 2020, four detonation craters were investigated with a multibeam echosounder for the first time. This dataset is represented here as maps of bathymetry, slope angle, and height difference to the surrounding. The circular craters were still clearly visible a year after the detonation. The diameter and depth of the structures were between 7.5–12.6 m and 0.7–2.2 m, respectively. In total, about 321 m² of the seafloor was destroyed along the track line. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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22 pages, 7069 KiB

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Climate Data to Support the Adaptation of Buildings to Climate Change in Canada

by Abhishek Gaur and Michael Lacasse

Data 2022, 7(4), 42; https://doi.org/10.3390/data7040042 - 06 Apr 2022

Cited by 7 | Viewed by 4771

Abstract

Climate change will continue to bring about unprecedented climate extremes in the future, and buildings and infrastructure will be exposed to such conditions. To ensure that new and existing buildings deliver satisfactory performance over their design lives, their performance under current and future [...] Read more.

Climate change will continue to bring about unprecedented climate extremes in the future, and buildings and infrastructure will be exposed to such conditions. To ensure that new and existing buildings deliver satisfactory performance over their design lives, their performance under current and future projected climates needs to be assessed by undertaking building simulations. This study prepares climate data needed for building simulations for 564 locations by bias-correcting the Canadian Regional Climate Model version 4 (CanRCM4) large ensemble (LE) simulations with reference to observations. Technical validation results show that bias-correction effectively reduces the bias associated with CanRCM4-LE simulations in terms of their marginal distributions and the inter-relationship between climate variables. To ensure that the range of projected climate change impacts are encompassed within these data sets, and to furthermore provide building moisture and energy reference years, the reference year files were prepared from bias-corrected CanRCM4-LE simulations and are comprised of a typical meteorological year for building energy applications, a typical and extreme moisture reference year, a typical downscaled year, an extreme warm year, and an extreme cold year. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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12 pages, 6644 KiB

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Land Cover Map for Multifunctional Landscapes of Taita Taveta County, Kenya, Based on Sentinel-1 Radar, Sentinel-2 Optical, and Topoclimatic Data

by Temesgen Alemayehu Abera, Ilja Vuorinne, Martha Munyao, Petri K. E. Pellikka and Janne Heiskanen

Data 2022, 7(3), 36; https://doi.org/10.3390/data7030036 - 17 Mar 2022

Cited by 8 | Viewed by 4657

Abstract

Taita Taveta County (TTC) is one of the world’s biodiversity hotspots in the highlands with some of the world’s megafaunas in the lowlands. Detailed mapping of the terrestrial ecosystem of the whole county is of global significance for biodiversity conservation. Here, we present [...] Read more.

Taita Taveta County (TTC) is one of the world’s biodiversity hotspots in the highlands with some of the world’s megafaunas in the lowlands. Detailed mapping of the terrestrial ecosystem of the whole county is of global significance for biodiversity conservation. Here, we present a land cover map for 2020 based on satellite observations, a machine learning algorithm, and a reference database for accuracy assessment. For the land cover map production processing chain, temporal metrics from Sentinel-1 and Sentinel-2 (such as median, quantiles, and interquartile range), vegetation indices from Sentinel-2 (normalized difference vegetation index, tasseled cap greenness, and tasseled cap wetness), topographic metrics (elevation, slope, and aspect), and mean annual rainfall were used as predictors in the gradient tree boost classification model. Reference sample points which were collected in the field were used to guide the collection of additional reference sample points based on high spatial resolution imagery for training and validation of the model. The accuracy of the land cover map and uncertainty of area estimates at 95% confidence interval were assessed using sample-based statistical inference. The land cover map has an overall accuracy of 81 ± 2.3% and it is freely accessible for land use planners, conservation managers, and researchers. Full article

(This article belongs to the Special Issue 2nd Edition of Data in Astrophysics & Geophysics: Research and Applications)

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