CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications

In recent years, the collection and utilisation of crowdsourced data has gained attention in atmospheric sciences and citizen weather stations (CWS), i.e., privately-owned weather stations whose owners share their data publicly via the internet, have become increasingly popular. This is particularly the case for cities, where traditional measurement networks are sparse. Rigorous quality control (QC) of CWS data is essential prior to any application. In this study, we present the QC package “CrowdQC+,” which identifies and removes faulty air-temperature (ta) data from crowdsourced CWS data sets, i.e., data from several tens to thousands of CWS. The package is a further development of the existing package “CrowdQC.” While QC levels and functionalities of the predecessor are kept, CrowdQC+ extends it to increase QC performance, enhance applicability, and increase user-friendliness. Firstly, two new QC levels are introduced. The first implements a spatial QC that mainly addresses radiation errors, the second a temporal correction of the data regarding sensor-response time. Secondly, new functionalities aim at making the package more flexible to apply to data sets of different lengths and sizes, enabling also near-real time application. Thirdly, additional helper functions increase user-friendliness of the package. As its predecessor, CrowdQC+ does not require reference meteorological data. The performance of the new package is tested with two 1-year data sets of CWS data from hundreds of “Netatmo” CWS in the cities of Amsterdam, Netherlands, and Toulouse, France. Quality-controlled data are compared with data from networks of professionally-operated weather stations (PRWS). Results show that the new package effectively removes faulty data from both data sets, leading to lower deviations between CWS and PRWS compared to its predecessor. It is further shown that CrowdQC+ leads to robust results for CWS networks of different sizes/densities. Further development of the package could include testing the suitability of CrowdQC+ for other variables than ta, such as air pressure or specific humidity, testing it on data sets from other background climates such as tropical or desert cities, and to incorporate added filter functionalities for further improvement. Overall, CrowdQC+ could lead the way to utilise CWS data in world-wide urban climate applications.

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The Street Air Warming Phenomenon in a High-Rise Compact City

Atmosphere ◽

10.3390/atmos9100402 ◽

2018 ◽

Vol 9 (10) ◽

pp. 402 ◽

Cited By ~ 4

Author(s):

Xiaoxue Wang ◽

Yuguo Li ◽

Xinyan Yang ◽

Pak Chan ◽

Janet Nichol ◽

...

Keyword(s):

Thermal Comfort ◽

Air Temperature ◽

Thermal Environment ◽

Urban Climate ◽

Pollutant Dispersion ◽

Urban Morphology ◽

Air Temperatures ◽

Significant Difference ◽

Sensitivity Studies ◽

Weather Stations

The street thermal environment is important for thermal comfort, urban climate and pollutant dispersion. A 24-h vehicle traverse study was conducted over the Kowloon Peninsula of Hong Kong in summer, with each measurement period consisting of 2–3 full days. The data covered a total of 158 loops in 198 h along the route on sunny days. The measured data were averaged by three methods (direct average, FFT filter and interpolated by the piecewise cubic Hermite interpolation). The average street air temperatures were found to be 1–3 °C higher than those recorded at nearby fixed weather stations. The street warming phenomenon observed in the study has substantial implications as usually urban heat island (UHI) intensity is estimated from measurement at fixed weather stations, and therefore the UHI intensity in the built areas of the city may have been underestimated. This significant difference is of interest for studies on outdoor air temperature, thermal comfort, urban environment and pollutant dispersion. The differences were simulated by an improved one-dimensional temperature model (ZERO-CAT) using different urban morphology parameters. The model can correct the underestimation of street air temperature. Further sensitivity studies show that the building arrangement in the daytime and nighttime plays different roles for air temperature in the street. City designers can choose different parameters based on their purpose.

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Os fatores geoecológicos, geourbanos e o clima urbano de Iporá-GO: uma análise a partir do Método de Correlação Linear

Ateliê Geográfico ◽

10.5216/ag.v11i3.39564 ◽

2018 ◽

Vol 11 (3) ◽

pp. 77

Author(s):

Washington Silva Alves ◽

Zilda De Fátima Mariano

Keyword(s):

Statistical Analysis ◽

Spatial Variation ◽

Statistical Methods ◽

Air Temperature ◽

Urban Climate ◽

Temperature Data ◽

Absolute Minimum ◽

El Sistema ◽

Weather Stations ◽

Maximum Air Temperature

Resumo O objetivo desse trabalho consistiu em analisar a influência dos fatores geoecológicos e geourbanos no padrão da temperatura do ar máxima e mínima absoluta em Iporá-GO, por meio do método estatístico de correlação linear. Os fundamentos teóricos e metodológicos pautaram-se no sistema clima urbano de Monteiro (2003), com ênfase no subsistema termodinâmico. Os fatores geoecológicos (hipsometria, exposição de vertente, vegetação urbana e hidrografia) e geourbanos (densidade de construção e o uso do solo urbano), foram georreferenciado com auxílio dos softwares ArcGis 9.0, Spring 5.3 e Surfer 9.0. Os dados de temperatura do ar foram coletados entre outubro de 2012 e outubro de 2013, em intervalos de 30 minutos, com termohigrômetros (modelo HT-500) e estações meteorológicas automáticas distribuídos em seis pontos da área urbana e rural de Iporá. Posteriormente, os dados foram organizados em planilhas de cálculos para análise estatística. Os resultados demonstraram que os fatores geoecológicos e geourbanos citados foram decisivos na variação espacial da temperatura do ar máxima e mínima absoluta em Iporá.Palavras-chave: Climatologia, Cidade, Clima Urbano AbstractThe objective of this study is to analyze the influence of geoecological factors and geourbanos the standard maximum air temperature and absolute minimum in Iporá-GO, by means of statistical methods of correlation linear. The theoretical and methodological foundations guided in the urban climate system Monteiro (2003), with emphasis on thermodynamic subsystem. The geoecological factors (hipsometria, slop exposure, urban and Hydrography vegetation) and geourban (building density and the use of urban land), were georeferenced with the help of software ArcGIS 9.0, Sprint 5.3 and Surfer 9.0. The air temperature data were collected between October 2012 and October 2013, in 30-minute intervals, with hygrometer term (HT-500 model) and automatic weather stations distributed in six points of the urban and rural Iporá. Later, the data were organized into spreadsheets for statistical analysis. The results showed that geoecological mentioned factors and geourbanos were decisive in the spatial variation of the temperature of the air and maximum absolute minimum in Iporá.Keywords: Climatology, City, Urban Climate ResumenEl objetivo de este estudio fue analizar la influencia de los factores geoecológicos y geourbanos en el patrón de la temperatura máxima y mínima absoluta del aire en Iporá-GO, a través de lo método estadístico de correlación lineal. Los fundamentos teóricos y metodológicos se basan en el sistema de clima urbano de Monteiro (2003), con énfasis en el subsistema termodinámico. Los factores geoecológicos (hipsometría, hebras de exposición, hidrografía y vegetación urbana) y geourbanos (densidad de edificación y uso del suelo urbano) fueron georeferenciados con la ayuda del software ArcGIS 9.0, Spring 5.3 y Surfer 9.0. Los datos de temperatura del aire se recogieron entre octubre 2012 y octubre 2013, en intervalos de 30 minutos, con termohigrômetros (modelo HT-500) y estaciones meteorológicas automáticas distribuidas en seis puntos de las zonas urbanas y rurales. Posteriormente, los datos se organizaron en las hojas de cálculo para el análisis estadístico. Los resultados mostraron que los factores geoecológicos y geourbanos citados fueron decisivos en la variación espacial de la temperatura máxima y mínima absoluta del aire en Iporá.Palavras clave: Climatología, Ciudad, Clima Urbano

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A comment on temperature measurement at automatic weather stations in Australia

Journal of Southern Hemisphere Earth System Science ◽

10.1071/es19010 ◽

2019 ◽

Vol 69 (1) ◽

pp. 172

Author(s):

G. P. Ayers

Keyword(s):

Air Temperature ◽

Thermal Inertia ◽

Temperature Data ◽

Maximum Temperature ◽

Data Sets ◽

Frequency Distributions ◽

Measurement Systems ◽

Weather Stations ◽

The Difference ◽

Temperature Records

Two versions of 1-min air-temperature data recorded at Bureau Automatic Weather Stations (AWSs) were compared in three case studies. The aim was to evaluate the difference between 1-min data represented by a measurement at the last second of each minute, compared with an average of four or five 1-s measurements made during the minute. Frequency distributions of the difference between these two values were produced for 44 000 min in three monthly data sets, January and July 2016 and September 2017. Diurnal and seasonal changes in standard deviation of the temperature differences showed that minute-to-minute fluctuations were driven by solar irradiance as the source of turbulent kinetic energy in the planetary boundary layer. Fluctuations in the difference between the two versions of 1-min data were so small overnight in all months that minimum temperature (Tmin) was the same using both methods. In midsummer, any difference between the two values for maximum temperature (Tmax) was greatest at midday. Tmax could be up by 0.1 K higher in the 1-s data compared with Tmax averaged from four measurements in the minute, but less often than 1 min in five. A follow-up test for September 2017 at Mildura when a new Tmax record was set found the difference immaterial, with Tmax the same for the averaged or 1-s values. Thus while the two versions of 1-min air-temperature data showed fluctuating small differences, largest at midday in summer, for the 3 months studied at both sites, fluctuations were too small to cause bias in climatological air-temperature records. This accorded with a numerical experiment confirming the Bureau’s advice that thermal inertia in the AWS measurement systems ensured that its 1-s data represented averages over the prior 40–80 s, providing a 1-min average of air temperature in accord with World Meteorological Organization requirements.

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Calculation of Air Temperatures above the Urban Canopy Layer from Measurements at a Rural Operational Weather Station

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-083.1 ◽

2013 ◽

Vol 52 (2) ◽

pp. 472-483 ◽

Cited By ~ 23

Author(s):

Bruno Bueno ◽

Julia Hidalgo ◽

Grégoire Pigeon ◽

Leslie Norford ◽

Valery Masson

Keyword(s):

Meteorological Data ◽

Urban Climate ◽

Urban Canopy ◽

Climate Prediction ◽

Outdoor Thermal Comfort ◽

Canopy Layer ◽

Urban Canopy Layer ◽

Air Temperatures ◽

Weather Stations ◽

Atmospheric Simulations

AbstractUrban canopy models (UCMs) are being used as urban-climate prediction tools for different applications including outdoor thermal comfort and building energy consumption. To take advantage of their low computational cost, UCMs are often forced offline without being coupled to mesoscale atmospheric simulations, which requires access to meteorological information above the urban canopy layer. This limits the use of UCMs by other scientific and professional communities, such as building engineers and urban planners, who are interested in urban-climate prediction but may not have access to mesoscale simulation results or experimental meteorological data. Furthermore, the conventional offline use of UCMs neglects the fact that the urban boundary layer can be affected by the surface and that the same forcing conditions may not be suitable for studying different urban scenarios. This paper presents a physically based and computationally efficient methodology to calculate forcing air temperatures for UCMs from meteorological data measured at operational weather stations. Operational weather stations are available for most cities in the world and are usually located in open areas outside the cities. The proposed methodology is satisfactorily evaluated against mesoscale atmospheric simulations and field data from Basel, Switzerland, and Toulouse, France.

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THE ASESSMENT OF THE SPATIAL AND TEMPORAL DYNAMICS OF AIR TEMPERATURE OF AIR TEMPERATURE IN THE URALS AND WESTERN SIBERIA IN THE SECOND HALF OF THE 20TH-EARLY 21TH CENTURIES WITH THE USE OF REANALYSIS

Леса России и хозяйство в них ◽

10.51318/fret.2021.74.3.012 ◽

2021 ◽

pp. 4-11

Author(s):

В.В. ФОМИН ◽

М.Г. УНДЕРСКИХ

Keyword(s):

Air Temperature ◽

Western Siberia ◽

Temporal Dynamics ◽

Meteorological Data ◽

Regional Climate ◽

Time Interval ◽

The Urals ◽

Coeffi Cients ◽

Weather Stations ◽

Correlation Coeffi

Проведен анализ пространственно-временной динамики приземной среднегодовой температуры воздуха на территории Урала и Западной Сибири по данным 92 метеостанций и реанализов ERA-20С и CERA-20С за период с 1961 по 2010 гг. Установлено, что значения коэффициента корреляции за исследуемый временной промежуток между данными инструментальных метеонаблюдений и данными реанализов ERA-20С и CERA-20С лежат в интервалах 0,81–0,97 и 0,86–0,98 соответственно. Данные по температуре воздуха реанализа CERA-20С лучше согласуются со значениями температуры, полученными на метеостанциях, по сравнению с данными реанализа ERA-20C. В южной части района исследований коэффициенты корреляции ниже, чем в регионах, расположенных севернее. В целом данные реанализа CERA-20C целесообразно использовать при проведении исследований, связанных с климатической изменчивостью и региональным изменением климата Урала и Западной Сибири на участках, находящихся на удалении от метеостанций. The analysis of the spatio-temporal dynamics of the mean annual air temperature in the Urals and Western Siberia on the basis of data of 92 weather stations and reanalysis ERA-20C and CERA-20C for the period from 1961 to 2010 was implemented. It was found that the values of the correlation coeffi cients for the studied time interval between the meteorological data and the data of reanalysis ERA-20C and CERA-20C lie in the intervals of 0,81–0,97 and 0,86–0,98, respectively. The reanalysis of CERA20C is in better agreement with the data obtained at weather stations compared to the reanalysis of ERA20C. In the southern part of the research area, the correlation coeffi cients are lower than in the regions located to the North. In general, data of the CERA-20C. Reanalysis should be used for studies related to climate variability and regional climate change in the Urals and Western Siberia at sites located at a signifi cant distance from weather stations.

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MSWX: global 3-hourly 0.1° bias-corrected meteorological data including near real-time updates and forecast ensembles

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-21-0145.1 ◽

2021 ◽

pp. 1-55

Author(s):

Hylke E. Beck ◽

Albert I.J.M. van Dijk ◽

Pablo R. Larraondo ◽

Tim R. McVicar ◽

Ming Pan ◽

...

Keyword(s):

Real Time ◽

Long Range ◽

Air Temperature ◽

Hydrological Modeling ◽

Meteorological Data ◽

Longwave Radiation ◽

Cumulative Distribution ◽

Specific Humidity ◽

Near Surface ◽

Medium Range

AbstractWe present Multi-Source Weather (MSWX), a seamless global gridded near-surface meteorological product featuring a high 3-hourly 0.1° resolution, near real-time updates (~3-hour latency), and bias-corrected medium-range (up to 10 days) and long-range (up to 7 months) forecast ensembles. The product includes ten meteorological variables: precipitation, air temperature, daily minimum and maximum air temperature, surface pressure, relative and specific humidity, wind speed, and downward shortwave and longwave radiation. The historical part of the record starts January 1, 1979, and is based on ERA5 data bias-corrected and downscaled using high-resolution reference climatologies. The data extension to within ~3 hours of real-time is based on analysis data from GDAS. The 30-member medium-range forecast ensemble is based on GEFS and updated daily. Finally, the 51-member long-range forecast ensemble is based on SEAS5 and updated monthly. The near real-time and forecast data are statistically harmonized using running-mean and cumulative distribution function-matching approaches to obtain a seamless record covering 1979 to 7 months from now. MSWX presents new and unique opportunities for hydrological modeling, climate analysis, impact studies, and monitoring and forecasting of droughts, floods, and heatwaves (within the bounds of the caveats and limitations discussed herein). The product is available at www.gloh2o.org/mswx.

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Data validation procedures in agricultural meteorology – a prerequisite for their use

Advances in Science and Research ◽

10.5194/asr-6-141-2011 ◽

2011 ◽

Vol 6 (1) ◽

pp. 141-146 ◽

Cited By ~ 5

Author(s):

J. Estévez ◽

P. Gavilán ◽

A. P. García-Marín

Keyword(s):

Quality Control ◽

Crop Production ◽

Dynamic Range ◽

Reference Evapotranspiration ◽

Meteorological Data ◽

Irrigated Agriculture ◽

Data Validation ◽

Control Procedures ◽

Weather Stations ◽

Accurate Quantification

Abstract. Quality meteorological data sources are critical to scientists, engineers, climate assessments and to make climate related decisions. Accurate quantification of reference evapotranspiration (ET0) in irrigated agriculture is crucial for optimizing crop production, planning and managing irrigation, and for using water resources efficiently. Validation of data insures that the information needed is been properly generated, identifies incorrect values and detects problems that require immediate maintenance attention. The Agroclimatic Information Network of Andalusia at present provides daily estimations of ET0 using meteorological information collected by nearly of one hundred automatic weather stations. It is currently used for technicians and farmers to generate irrigation schedules. Data validation is essential in this context and then, diverse quality control procedures have been applied for each station. Daily average of several meteorological variables were analysed (air temperature, relative humidity and rainfall). The main objective of this study was to develop a quality control system for daily meteorological data which could be applied on any platform and using open source code. Each procedure will either accept the datum as being true or reject the datum and label it as an outlier. The number of outliers for each variable is related to a dynamic range used on each test. Finally, geographical distribution of the outliers was analysed. The study underscores the fact that it is necessary to use different ranges for each station, variable and test to keep the rate of error uniform across the region.

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Streamflow Changes in Mesoscale Lowland Catchment Under Future Climate Conditions

Papers on Global Change IGBP ◽

10.2478/v10190-012-0004-7 ◽

2012 ◽

Vol 19 (1) ◽

Author(s):

Urszula Somorowska ◽

Izabela Piętka

Keyword(s):

Air Temperature ◽

Climate Model ◽

Stream Water ◽

Meteorological Data ◽

Regional Climate ◽

Future Climate ◽

Data Sets ◽

Moderate Increase ◽

Climate Conditions ◽

Daily Time

AbstractThe objective of this study was to investigate the performance of streamflow in a lowland mesoscale catchment in Poland under current and future climate conditions. Simulations of hypothetical streamflow in the future climate were facilitated by meteorological data sets from ensemble simulations from all over Europe with the Regional Climate Model CLM. Projections of precipitation and air temperature for the 21st century under the SRES A1B scenario were used as an input to the hydrological model simulating streamflow at the daily time scale. The combination of relatively moderate increase of annual precipitation sum and mean air temperature might cause lower annual discharges. The possible decrease in stream water resources might be a signal of reduced subsurface recharge and land over drying processes.

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THE THERMO-HYGROMETRIC INDEX ON THE TERRITORY OF THE SOUTHERN DOBROGEA PLATEAU – A COMPONENT OF THE BALNEOCLIMATERIC TREATMENT

Present Environment and Sustainable Development ◽

10.15551/pesd2020141007 ◽

2020 ◽

Vol 14 (1) ◽

Cited By ~ 1

Author(s):

Elena Grigore ◽

Dana Maria Constantin (Oprea) ◽

Elena Bogan ◽

Marius-Alin Cristea ◽

Florina Tatu

Keyword(s):

Spatial Distribution ◽

Human Health ◽

Air Temperature ◽

Meteorological Data ◽

Kriging Interpolation ◽

Air Humidity ◽

Relative Air Humidity ◽

Bioclimatic Index ◽

Weather Stations ◽

Analysis Models

The appearance of the analysis models, as a physical or mathematic form, has allowed simplifying the graphic representation of the processes specific to bioclimatology. Thus, the bioclimatic index becomes a useful and practical work tool in the scientific research, avoiding a multiple ranges of possible evaluations of the positive or negative potential that the climate of a region has on the human health. The proposed study analyzes the calculated values of the thermo-hygrometric index, for the period between the years 1981-2010. The database was improved with the meteorological data obtained from the five weather stations located in the Southern part of the Dobrogea Plateau. The mathematic formula launched by Kyle W.J. is based on the measured values of the air temperature (ºC) and relative air humidity (%). The obtained results allow us to highlight both the specific bioclimatic areas and the way in which the tourism in the area can be affected. The bioclimatic extension and intensity is rendered by a suggestive and synthetic graphic expression. The maps showing the spatial distribution of the index were obtained by combining the isotherm method with the kriging interpolation specific to the ArcMap.

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