scholarly journals Topoclimatic Zoning and Representative Areas as Determined by an Automatic Weather Station (AWS) Network in the Atacama Region, Chile

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 611
Author(s):  
Donna Cortez ◽  
Rodrigo Padilla ◽  
Sebastián Herrera ◽  
Juan Uribe ◽  
Manuel Paneque
Keyword(s):  
Principal Component ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Climate Information ◽  
Weather Information ◽  
Climate Knowledge ◽  
Weather Stations ◽  
And Cluster Analysis ◽  
Representative Area ◽  
Climatic Information

Climate information is crucial to the management and profitability of key development sectors involving agriculture, hydrologic resources, natural hazards, and energy. Climate knowledge, real-time weather information, and climate predictions reliability all contribute to the planning and management of socioeconomic activities and sustainable development. Automatic weather stations (AWSs) are remotely operated and facilitate the recording of meteorological information for unoccupied and out-of-reach areas. However, the representative area of the Atacama region is unknown, whose uniqueness is largely determined by the topography of the terrain. This paper describes the topoclimatic zoning of the Atacama region, based on the identification of homogeneous climatic and topographic areas, using climatic information, principal component analysis, and cluster analysis. Topoclimatic zoning was used to determine the representative area of the AWSs. Sixty-one regional topographic units were identified as equivalent to the representative area of the AWS. The directly represented area was estimated at 2365 km2 (3.13% of the regional total), the indirectly represented area was 8725 km2 (11.53%), and the unrepresented area was 64,561 km2 (85.34%). This large unrepresented area displays potential zones for future AWS installations, which can improve both the efficiency of the regional meteorological network and access to quality climate information.

scholarly journals Comparing Kriging Estimators Using Weather Station Data and Local Greenhouse Sensors

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1853
Author(s):  
Pei-Fen Kuo ◽  
Tzu-En Huang ◽  
I Gede Brawiswa Putra
Keyword(s):  
Weather Conditions ◽  
Environmental Data ◽  
Weather Station ◽  
Weather Information ◽  
Station Data ◽  
Weather Station Data ◽  
Real Value ◽  
Weather Stations ◽  
Spatio Temporal ◽  
Central Weather Bureau

In order to minimize the impacts of climate change on various crops, farmers must learn to monitor environmental conditions accurately and effectively, especially for plants that are particularly sensitive to the weather. On-site sensors and weather stations are two common methods for collecting data and observing weather conditions. Although sensors are capable of collecting accurate weather information on-site, they can be costly and time-consuming to install and maintain. An alternative is to use the online weather stations, which are usually government-owned and free to the public; however, their accuracy is questionable because they are frequently located far from the farmers’ greenhouses. Therefore, we compared the accuracy of kriging estimators using the weather station data (collected by the Central Weather Bureau) to local sensors located in the greenhouse. The spatio-temporal kriging method was used to interpolate temperature data. The real value at the central point of the greenhouse was used for comparison. According to our results, the accuracy of the weather station estimator was slightly lower than that of the local sensor estimator. Farmers can obtain accurate estimators of environmental data by using on-site sensors; however, if they are unavailable, using a nearby weather station estimator is also acceptable.

scholarly journals Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations

2021 ◽  
Vol 47 ◽  
Author(s):  
Adrien Wehrlé ◽  
Jason E. Box ◽  
Masashi Niwano ◽  
Alexandre M. Anesio ◽  
Robert S. Fausto
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Satellite Imagery ◽  
Spatial Dependence ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Satellite Observations ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Weather Stations

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) provides surface meteorological and glaciological measurements from widespread on-ice automatic weather stations since mid-2007. In this study, we use 105 PROMICE ice-ablation time series to identify the timing of seasonal bare-ice onset preceded by snow cover conditions. From this collection, we find a bare-ice albedo at ice-ablation onset (here called bare-ice-onset albedo) of 0.565 ± 0.109 that has no apparent spatial dependence among 20 sites across Greenland. We then apply this snow-to-ice albedo transition value to measure the variations in daily Greenland bare-ice area in Sentinel-3 optical satellite imagery covering the extremely low and high respective melt years of 2018 and 2019. Daily Greenland bare-ice area peaked at 153 489 km² in 2019, 1.9 times larger than in 2018 (80 220 km²), equating to 9.0% (in 2019) and 4.7% (in 2018) of the ice sheet area.

scholarly journals Meteorological effects of the solar eclipse of 20 March 2015: analysis of UK Met Office automatic weather station data and comparison with automatic weather station data from the Faroes and Iceland

2016 ◽  
Vol 374 (2077) ◽  
pp. 20150212 ◽  
Author(s):  
Edward Hanna ◽  
John Penman ◽  
Trausti Jónsson ◽  
Grant R. Bigg ◽  
Halldór Björnsson ◽  
...  
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Solar Eclipse ◽  
Temperature Drop ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Station Data ◽  
Weather Station Data ◽  
The Mean ◽  
Weather Stations

Here, we analyse high-frequency (1 min) surface air temperature, mean sea-level pressure (MSLP), wind speed and direction and cloud-cover data acquired during the solar eclipse of 20 March 2015 from 76 UK Met Office weather stations, and compare the results with those from 30 weather stations in the Faroe Islands and 148 stations in Iceland. There was a statistically significant mean UK temperature drop of 0.83±0.63°C, which occurred over 39 min on average, and the minimum temperature lagged the peak of the eclipse by about 10 min. For a subset of 14 (16) relatively clear (cloudy) stations, the mean temperature drop was 0.91±0.78 (0.31±0.40)°C but the mean temperature drops for relatively calm and windy stations were almost identical. Mean wind speed dropped significantly by 9% on average during the first half of the eclipse. There was no discernible effect of the eclipse on the wind-direction or MSLP time series, and therefore we can discount any localized eclipse cyclone effect over Britain during this event. Similar changes in air temperature and wind speed are observed for Iceland, where conditions were generally clearer, but here too there was no evidence of an eclipse cyclone; in the Faroes, there was a much more muted meteorological signature. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.

Heat Illness Related Meteorology over Chiangmai Using Automatic Weather Station Observed Data

2019 ◽  
Vol 891 ◽  
pp. 142-148
Author(s):  
Parwapath Phunthirawuthi ◽  
Chanattha Saengrattanayon ◽  
Sukrit Kirtsaeng
Keyword(s):  
Heat Index ◽  
Maximum Temperature ◽  
Heat Illness ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Alert System ◽  
Tropical Area ◽  
Heat Period ◽  
Weather Stations ◽  
Very High

This research is a part of study of heat illness vulnerability. Understanding heat characteristic, especially in tropical area, would decrease loss from heat deceases and also support tourism in tropical countries. The aim of this research is to apply the meteorological sensor dataset in Chiangmai (a famous city in northern Thailand), which is under the control of Thai Meteorological Department, from 2015-2017 to investigate heat index characteristic. Two elements, temperature and relative humidity, were used to calculate heat index following Steadman’s equation. Analyzed heat index would be arranged by its intensity and then applied on heat illness warning. The study demonstrated that heat index warning from Automatic Weather Station data analysis could get along with the maximum temperature historical statistics data which observed by weather stations. Local people and visitors in Chiangmai mostly suffer from heat in between March and June. The greatest vulnerability to heat illness in Chiangmai was in April and May. This extreme-heat period is consistent with the report from Department of Decease Control Thailand, an amount of heat illness patients is very high in April and May. Moreover, the results show that even if the air temperature is getting low in after summer season but heat index is still high through the year. So, people still need to be aware of heat deceases and always concern about environmental heat when doing outdoor activities. In the future, AWS data from every station over Thailand would be used to develop a real-time Heat Illness Alert System.

Relationships between macrosynoptic weather types and development of the thermal excess in suburban areas in Debrecen, Hungary

2014 ◽  
Vol 5 (2) ◽  
pp. 167-172
Author(s):  
S. Szegedi ◽  
I. Lázár ◽  
T. Tóth
Keyword(s):  
Reference Station ◽  
Heat Island ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Heat Islands ◽  
Weather Patterns ◽  
Suburban Areas ◽  
Synoptic Conditions ◽  
Urban Heat ◽  
Weather Stations

Impacts of macrosynoptic weather patterns on the development of the thermal excess in suburban areas of Debrecen are examined in this paper. Temperature datasets have been recorded at two heights by three automatic weather stations mounted in Debrecen (east Hungary) and a small settlement in its vicinity. An additional automatic weather station is used as a reference station outside Debrecen. Urban heat island (UHI) intensities have been calculated from the raw datasets. Impacts of synoptic conditions have been analyzed on the base of Péczely’s macrosynoptic types. It has been found that anticyclone types are more favorable from the aspect of UHI development, while cyclone types, especially the passage of warm fronts can effectively hinder the formation of strong heat islands in Debrecen.

The Utilization of Ftir (Fourier Transform Infra-Red) Method Combined with Chemometrics For Authentication of Indonesian Coffee Powder

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Firmansyah A. ◽  
Winingsih W. ◽  
Soebara Y S
Keyword(s):  
Fourier Transform ◽  
Natural Product ◽  
High Performance ◽  
Principal Component ◽  
Raw Material ◽  
Attenuated Total Reflectance ◽  
Coffee Bean ◽  
Product Analysis ◽  
Total Reflectance ◽  
And Cluster Analysis

Analysis of natural product remain challenging issues for analytical chemist, since natural products are complicated system of mixture. The most popular methods of choice used for quality control of raw material and finished product are high performance liquid chromatography (HPLC), gas chromatography (GC) and mass spectrometry (MS). The utilization of FTIR-ATR (Fourier Transform Infrared-Attenuated Total Reflectance) method in natural product analysis is still limited. This study attempts to expand the use of FTIR spectroscopy in authenticating Indonesian coffee powder.The coffee samples studied were taken from nine regions in Indonesia, namely Aceh Gayo, Flores, Kintamani, Mandheling, Papua, Sidikalang, Toraja, Kerinci and Lampung.The samples in the form of coffee bean from various regions were powdered . The next step conducted was to determine the spectrum using the FTIR-ATR (Attenuated Total Reflectance) using ZnSe crystal of 8000 resolution. Spectrum samples, then, were analyzed using chemometrics. The utilized chemometric model was the principal component analysis (PCA) and cluster analysis (CA). Based on the chemometric analysis, there are similarities between Aceh Gayo coffee with Toraja coffee, Mandailing coffee, Kintamani coffee and Flores coffee. Sidikalang coffee has a similarity to Flores coffee; Papua coffee has a similarity to Sidikalang coffee; Lampung coffee has a similarity to Sidikalang coffee, while Kerinci coffee has a similarity to Papua coffee.

scholarly journals Uncertainty Evaluation of Wind Speed Sensor in Automatic Weather Station

2021 ◽  
Vol 768 (1) ◽  
pp. 012008
Author(s):  
Zhen Yang ◽  
Husheng Zhang ◽  
Qiang Wang ◽  
Cuicui Li ◽  
Wenlong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Uncertainty Evaluation ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Speed Sensor

scholarly journals Four-Year Study on the Bio-Agronomic Response of Biotypes of Capparis spinosa L. on the Island of Linosa (Italy)

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 327
Author(s):  
Salvatore La Bella ◽  
Francesco Rossini ◽  
Mario Licata ◽  
Giuseppe Virga ◽  
Roberto Ruggeri ◽  
...  
Keyword(s):  
Block Design ◽  
Principal Component ◽  
Flower Bud ◽  
Natural Habitats ◽  
Phenological Stages ◽  
Average Value ◽  
Randomized Complete Block Design ◽  
Capparis Spinosa ◽  
Production Behavior ◽  
And Cluster Analysis

The caper plant is widespread in Sicily (Italy) both wild in natural habitats and as specialized crops, showing considerable morphological variation. However, although contributing to a thriving market, innovation in caper cropping is low. The aim of the study was to evaluate agronomic and production behavior of some biotypes of Capparis spinosa L. subsp. rupestris, identified on the Island of Linosa (Italy) for growing purposes. Two years and seven biotypes of the species were tested in a randomized complete block design. The main morphological and production parameters were determined. Phenological stages were also observed. Analysis of variance showed high variability between the biotypes. Principal component analysis and cluster analysis highlighted a clear distinction between biotypes based on biometric and production characteristics. Production data collected in the two-year period 2007–2008 showed the greatest production levels in the third year following planting in 2005. In particular, biotype SCP1 had the highest average value (975.47 g) of flower bud consistency. Our results permitted the identification of biotypes of interest for the introduction into new caper fields. Further research is needed in order to characterize caper biotypes in terms of the chemical composition of the flower buds and fruits.

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