This article explores the quality of information acquired from weather station sensors. A review of literature in this field concludes that most publications concern the analysis of data acquired ...from weather station sensors and their characteristic properties, estimating the missing values from the data, and assessing the quality of weather information. Despite the large collection of studies devoted to these issues, there is no comprehensive approach that would consider the modelling of information uncertainty. Therefore, the article presents a proprietary method of analysing and modelling the uncertainty of the weather station sensors’ information quality. For this purpose, the structure of a real meteorological station and the measurement data obtained from it were analysed. Next, an information quality model was developed using the certainty factor (CF) of hypothesis calculation. The developed method was verified on an exemplary real meteorological station. It was found that this method enables the improvement of the quality of information obtained and processed in a multi-sensor system. This becomes practical when the influence of individual measurement system elements on the information quality reaching the recipient is determined. An example is furnished by a demonstration of the usage of two sensors to improve the information quality.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The goal of this work is to build a low cost pedagogical device able to improve the comprehension of weather phenomena for African students in particular and in general for students across the world. ...This experimental and didactic device can be seen as an easy teaching tool to measure meteorological and climatic data. This structure is called a micro weather station. The investigation is done in Metipkwale one of the village of Ebolowa town in Cameroon (Central Africa). Some weather data automatically obtained from the micro weather station (sensors) such as temperature, humidity and pressure, are directly transmitted by a modem (Wi-Fi connection) to the ThingSpeak platform in order to be registered online and plotted as a diagram. The illustration process is assured by a computer or a smartphone. Moreover, the prediction process of climatic behaviour and the reactions of students have been also outlined. Further, some notions such as Internet of Things and Deep Learning associated with exponential smoothing algorithms are also presented.
Mobile monitoring can offer data of high spatial resolution within various urban contexts. Yet, devising efficient monitoring protocols for mobile campaigns is still a challenge. Relevant studies ...typically follow protocols based on the accumulated knowledge of authors and not standardized protocols. Thus the results may be prone to biases. Here, we present a transect monitoring methodology focused on urban areas’ thermal environment and air quality. The methodology follows a specific protocol for choosing the monitoring days and evaluating post-process corrections of the retrieved data and is applied within a city in central Italy at a seasonal scale with respect to the Sky View Factor. The presented method is simple, yet comprehensive and can be easily applied to almost any city and urban context. Results showed significant variations of the parameters measured, i.e. air temperature, humidity, short-wave radiation, wind speed, CO2 and PM10. For example, differences of air temperature within the same city may be up to 5.1 °C in autumn and differences of short-wave radiation may be up to 501 W/m2 in spring. The results of this study enhance the understanding of how to efficiently assess the quality of urban environments. As such, they could serve as a catalyst for developing mobile monitoring protocols, with the goal of enhancing the evaluation of urban environmental quality.
•A simple yet comprehensive mobile monitoring technique for almost any city is presented.•A protocol for post-processing the data is evaluated.•An evaluation of the thermal environment and air quality of a historical city in Italy is presented.•The evaluation of the variables is performed with respect to seasonality and urban geometry.•A reverse thermal stress is found within the suburbs as compared to the city-center.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
AbstractMuch previous research recognizes hazardous winter-weather conditions such as heavy snowfall and cold temperatures as affecting the change in traffic volume, and modeling has been used to ...simulate variations in traffic flow caused by these factors. Similar to previous studies, the winter-weather hazard model was estimated using 6-year weigh-in-motion traffic data collected on Highway 2A, Alberta, Canada, and weather data from a nearby weather station to quantify the change in traffic volume due to winter-weather conditions. However, different from the existing research, the developed model has been tested in terms of temporal transferability and model specification. The temporal transferability test revealed that the established model is suitable for use regardless of the year. The model specification test showed that each vehicle class could have the model specification optimized differently to estimate correct traffic volume during winter-weather conditions.
Mapping the microclimate effect of forest canopies on understory temperature requires spatially explicit predictors at very fine spatial resolutions. Light Detection And Ranging (LiDAR) offers ...promising prospects in that regard, as it allows capturing the vertical dimension of vegetation structure at a very high resolution over large areas.
To explore the potential of airborne LiDAR-derived metrics to predict understory temperature, we focused on the forest of Blois (France), a 2740-ha lowland managed forest dominated by oak (Quercus petraea). We installed HOBO sensors measuring microclimate air temperature at one-metre height in 53 stands of contrasting vegetation structure, from open to very dense and from young regeneration to mature stages. Using a nearby weather station as the macroclimate temperature reference, we calculated the slope (log scale) coefficient of the linear regression between microclimate and macroclimate, as a simple parameter describing the microclimatic buffering (log(slope) < 0) or amplification (log(slope) > 0) capacity of the habitat.
An airborne LiDAR flight was conducted during summer 2021, matching the timing of our temperature measurements. From the resulting 3D point cloud, three complementary metrics of forest structure were derived: the maximum height, the Plant Area Index and the Vertical Complexity Index. They were calculated for circular buffers of different radii (1 m to 100 m) centred on each HOBO sensor.
We found that the 5-m radius combining the three metrics into a single multivariate model explained the greatest proportion of variance in the microclimate effect of each stand (R2 = 0.91). We mapped the buffering or amplification effect of vegetation structure on understory temperatures over the entire forest of Blois at a 10-m resolution. 91.4% of the surface of the forest was significantly buffered relative to macroclimate temperature, while 2.7% was amplified, especially in road verges, clear-cut and regeneration areas. Based on our simple linear model, we were able to derive understory air temperature maps for any temporal resolution (i.e. hourly, daily, or seasonal). The results highlight the great capacity of airborne LiDAR to retrieve forest structure parameters and generate high-resolution maps of the thermal environment.
Applications for mapping the buffering or amplification of microclimate temperature are plentiful, especially in the context of climate change. They include improving the understanding of physiological processes such as thermoregulation or phenology, modelling the thermal connectivity of the landscape, improving species redistribution models, spotting microrefugia for conservation, informing forest management for tree regeneration or wildfire control, or even prioritising cooling recreational areas for humans to escape heatwaves in urban forests.
Display omitted
•Airborne LiDAR is ideal to predict forest thermal environment at a high resolution.•We used Maximum height, Plant Area & Vertical Complexity Index as structure metrics.•Forest structure explained 91% of microclimate variability at a 10-m resolution.•We mapped the buffering or amplification effect of forest on microclimate temperature.•Ecologists, conservationists and forest managers would highly benefit from such maps.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstrak. Pada umumnya data suhu udara diperoleh dari hasil pengamatan pada stasiun iklim Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Metode ini dapat digunakan untuk merepresentasikan suhu ...udara suatu wilayah yang berada pada radius ≤ 10 km dari lokasi stasiun iklim, sehingga dibutuhkan sebuah solusi alternatif untuk mendapatkan data suhu udara yang dapat merepresentasikan wilayah yang lebih luas, salah satunya memanfaatkan dataset suhu udara berbasis penginderaan jauh. Penelitian ini bertujuan membandingkan performa sejumlah dataset suhu udara berbasis penginderaan jauh, yaitu Climatic Research Unit gridded Time Series (CRU-TS), Climatologies at High Resolution for the Earth Land Surface Areas (CHELSA), dan TerraClimate dalam mengestimasi curah hujan bulanan di Provinsi Papua Barat. Penelitian ini terdiri atas 6 (enam) tahapan utama, yaitu; (1) inventarisasi data yang bertujuan mengumpulkan dataset suhu udara dan data suhu udara hasil perekaman pada Automatic Weather Station (AWS) tahun 1996 sampai tahun 2019, (2) ekstraksi data, (3) screening data untuk mengganti nilai ekstrim dengan nilai rata-rata, (4) evaluasi data untuk membandingkan dataset dengan data AWS, (5) komparasi data untuk membandingkan performa dataset, dan (6) rekomendasi yang bertujuan untuk menentukan dataset yang paling sesuai untuk digunakan di Provinsi Papua Barat. Hasil penelitian menunjukkan bahwa CHELSA, TerraClimate, dan CRU-TS sangat akurat dalam mengestimasi suhu udara bulanan di Provinsi Papua Barat yang ditunjukkan dengan nilai RBIAS 0,1. Disamping itu CHELSA, TerraClimate, dan CRU-TS memiliki tingkat keeratan hubungan yang sedang terhadap data AWS dengan nilai r = 0,36 – 0,68. Sehingga TerraClimate, CHELSA, dan CRU-TS dapat digunakan sebagai solusi alternatif untuk mendapatkan informasi suhu udara bulanan di Provinsi Papua Barat.Comparison of Remote Sensing-Based Air Temperature Dataset in Estimating Monthly Air Temperature in West PapuaAbstract. Air temperature is one of the important components in agriculture. Generally, air temperature data is obtained from climate stations of the Meteorological, Climatological, and Geophysical Agency (BMKG). These methods represented an area within a radius of 10 km from the climate station, therefore an alternative solution is needed for a larger area. The utilization of the air temperature dataset is one alternative solution. This research aims to compare Climatic Research Unit gridded Time Series (CRU-TS), Climatologies at High Resolution for the Earth Land Surface Areas (CHELSA), and TerraClimate as an air temperature dataset in estimating the monthly temperature in West Papua. The main stages in this research are data inventory, data extraction, data screening, data evaluation, data comparison, and data recommendation. The data used in this research are CRU-TS, TerraClimate, CHELSA, and local AWS data recording from 1996 to 2019. The research showed that CRU-TS, TerraClimate, and CHELSA are very accurate in estimating the monthly temperature in West Papua as indicated by RBIAS 0.1. Furthermore, CRU-TS, TerraClimate, and CHELSA have a moderate correlation with AWS data in estimating monthly air temperature with r= 0.36 - 0.68. Therefore, CRU-TS, TerraClimate, and CHELSA can be used as an alternative solution to obtain monthly air temperature information in West Papua.
The information on the variation of mean wind speed with height is useful or required in various branches of engineering practices. However, the dependence of varying wind direction on height has ...often been disregarded in wind engineering. This study aims to further the understanding of the dependence on height of varying wind direction based on long-term wind measurements from Doppler wind profiler and a surface weather station in Hong Kong. The veering angle profiles are obtained by means of composite analysis, and their characteristics are examined as a function of topographic condition, wind speed and storm type (i.e. monsoons and typhoons), respectively. The results suggest that, the veering angle profiles have a strong dependence on the change of upwind topographic condition, which leads to noticeable divergences in terms of the shape of veering angle profiles, the peak value of veering angle and the slope of the profiles. Second, the correlation of the veering angle profiles with wind speed is estimated under near-neutral stable condition. No clear correlation is identified between the veering angle profiles and wind speed. Furthermore, the phenomena of veering wind under monsoon and typhoon conditions are assessed, in which there are excellent agreements in respect to the veering angle profiles under 800 m. Nevertheless, significant deviations arises at higher elevations.
•Veering wind characteristics are investigated using measurements from Doppler wind profiler and surface weather station.•Effects of upwind topographic condition on veering wind are explored.•Dependence of veering wind on wind speed is analyzed.•Veering wind characteristics under typhoon and monsoon winds are assessed.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In central Italy, particularly in the Umbria-Marche Apennines, there are some complete, high-altitude weather stations, which are very important for assessing the climate in these areas. The mountain ...weather stations considered in this study were Monte Bove Sud (1917 m.a.s.l.), Monte Prata (1816 m.a.s.l.) and Pintura di Bolognola (1360 m.a.s.l.). The aim of this research was to compare the differences between the precipitation measured by the rain gauges and the data obtained by satellite using the IMERG algorithm, at the same locations. The evaluation of possible errors in the estimation of precipitation using one method or the other is fundamental for obtaining a reliable estimate of precipitation in mountain environments. The results revealed a strong underestimation of precipitation for the rain gauges at higher altitudes (Monte Bove Sud and Monte Prata) compared to the same pixel sampled by satellite. On the other hand, at lower altitudes, there was a better correlation between the rain gauge value and the IMERG product value. This research, although localised in well-defined locations, could help to assess the problems in rain detection through mountain weather stations.
The wind carries moisture into an atmosphere and hot or cold air into a climate, affecting weather patterns. Knowing where the wind is coming from gives essential insight into what kind of ...temperatures are to be expected. However, the wind is affected by spatial and temporal variabilities, thus making it difficult to predict. This study focuses on finding data associations from the weather station installed at Hasanuddin University Campus based on internet of things (IoT) using Raspberry Pi as a gateway that associated all the meteorological data from sensors. The generation of association rules compares the Apriori and FP-growth algorithms to determine relations among itemsets. The results show that high humidity and warm temperature tend to associate with a westerly wind and occur at night. In contrast, conditions with less humid and moderate temperatures tend to have southerly and southeasterly wind.
Full text
Available for:
FFLJ, NUK, ODKLJ, UL, UM, UPUK
PDF
