Conventional Meteorological Stations Research Articles

Calibration of the Ångström–Prescott Model for Accurately Estimating Solar Radiation Spatial Distribution in Areas with Few Global Solar Radiation Stations: A Case Study of the China Tropical Zone

The Ångström–Prescott formula is commonly used in climatological calculation methods of solar radiation simulation. Aiming at the characteristics of a vast area, few meteorological stations, and uneven distribution in the tropical regions of China, in order to obtain the optimal parameters of the global solar radiation calculation model, this study proposes a suitable monthly global solar radiation model based on the single-station approach and the between-groups linkage of the A–P model, which utilizes monthly measured meteorological data from 80 meteorological stations spanning the period from 1996 to 2016 in the tropical zone of China, considering the similarity in changes of monthly sunshine percentage between stations. The applicability and accuracy of the correction parameters (a and b coefficients) were tested and evaluated, and then the modified parameters were extended to conventional meteorological stations through Thiessen polygons. Finally, the spatial distribution of solar radiation in the tropical region of China was simulated by kriging, IDW, and spline interpolation techniques. The results show the following: (1) The single-station model exhibited the highest accuracy in simulating the average annual global solar radiation, followed by the model based on the between-groups linkage. After optimizing the a and b coefficients, the simulation accuracy of the average annual global solar radiation increased by 5.3%, 8.1%, and 4.4% for the whole year, dry season, and wet season, respectively. (2) Through cross-validation, the most suitable spatial interpolation methods for the whole year, dry season, and wet season in the tropical zone of China were IDW, Kriging, and Spline, respectively. This research has positive implications for improving the accuracy of solar radiation prediction and guiding regional agricultural production.

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Many design principles for rain gauges that have the capacity to record rainfall intensity have been proposed or developed. These are here grouped into 15 categories, and the abilities and limitations of each are discussed. No standard or optimum method has emerged, despite more than 80 years of effort in the last two centuries, together with prior work from the 17th C onwards. Indeed, new methods continue to be explored for both point-based and area-wide collections of intensity data. Examples include the use of signal attenuation by rain along the tower-to-tower links of cellular phone networks, monitoring the speed of vehicle windscreen wipers, and exploiting the sound or vision from security and traffic-monitoring cameras. Many of these approaches have the potential to provide vastly more observation sites than conventional meteorological stations equipped with rain gauges. Some of these contemporary approaches seek to harness the potential of crowdsourced or citizen-science data. It is hoped that the present overview of methods will provide a guide for those wishing to collect or analyses rainfall intensity data for application in areas such as soil erosion processes, ecohydrology, agrochemical washoff, or urban flash flooding. Because rainfall intensity is one of the key aspects of the hydrologic cycle likely to respond as climate change and variability proceed, the choice of appropriate data collection methods has additional contemporary importance for the monitoring of regional and global precipitation changes.

Bioclimatic zoning for quails in the rain season in the state of Paraíba, Brazil

This work aimed to perform bioclimatic zoning based on the temperature and humidity index (THI) for quails from the 3rd to the 5th week of life during the rainy season in the state of Paraíba, Brazil, in order to identify the most suitable mesoregions among the Zona da Mata, Agreste, Borborema and Sertão for the breeding of these birds and to propose mitigating measures for the thermal comfort of the animals. The monthly air temperature and relative humidity data for calculating the THI were obtained from conventional meteorological stations of the National Meteorological Institute of the Brazilian federal government from 1961 to 2015, in turn making maps with the spatial distribution of the index. The index ranged from 71 to 76 in the various mesoregions of Paraíba, with Agreste being the best mesoregion for breeding quails from the 3rd to the 5th week of life, thus providing a thermal comfort zone for birds and only requiring a few corrective measures in their facilities, when necessary, followed by the Sertão, Zona da Mata and Borborema mesoregions.

Wind Characteristics and Temporal Trends in Eastern Paraná State, Brazil

The wind is one of the most important and studied variables globally, essential to several sectors, for example, energy. Therefore, this study assesses the wind regime and analysis trends in three locations within the Paraná state, Brazil. The historical series were recorded between 1976 and 2010 at conventional meteorological stations belonging to the Brazilian National Institute of Meteorology. WRPLOT version 8.0.0 software was used for elaborating wind roses and histograms in the annual and seasonal scales. Detection of trends and temporal rupture points was performed using different statistical methods (Run, Mann–Kendall, Pettitt and Shapiro–Wilk tests) for all meteorological stations. All statistical tests were conducted using the R software version 3.3.2. On a seasonal scale, summer and spring present the highest wind speeds in the Curitiba and Paranaguá stations due to meteorological systems on different scales, such as the South Atlantic subtropical anticyclone and frontal systems. The Mann–Kendall test revealed that Castro presented statistical significance in reducing wind speed, with a decrease of 0.23 m/s per decade for the annual scale and 0.23 m/s per decade during the autumn season. These ruptures indicated a decrease in wind speed in Curitiba and Paranaguá for the spring season. The Pettitt test revealed a break point detection in the data series in Curitiba station, likely due to urban expansion that started in the 1980s, reducing wind speed, especially in winter and spring. These trends and ruptures revealed a significant reduction in wind speed, possibly due to the interaction between natural climate changes and the increase in surface roughness resulting from land use and urbanization changes.

Thunderstorm days over Argentina: Integration between human observations of thunder and the world wide lightning location network lightning data

AbstractStorms are one of nature's most dangerous phenomena; therefore, knowing their spatial distribution and evolution over time is of great interest for the protection of society, as well as for climate change adaptation strategies. The measurement of Thunderstorm days (Td) was one of the first tools used to monitor storms. The advent of automatic detection networks on the surface has allowed us to advance in the understanding and characterization of the electrical activity in the atmosphere, locating in real‐time electrical discharges and providing information over previously unrecorded regions. This work focuses on the integration of human observations at conventional meteorological stations and the data provided by the WWLLN surface discharge detection network in Argentina. The calibration methodology applied determined a mean human thunderstorm detection radius of 21 km which allowed the elaboration of isokeraunic maps for the period 2008–2017 for the region of interest. The spatial distribution of storms yielded the highest values of Td in the Argentine Northwest region with values above 100 Td·year−1 followed by a relative maximum in the Argentine Northeast with 80 Td·year−1 and the Sierras de Córdoba with 50 Td·year−1.

Validation and calibration of models to estimate photosynthetically active radiation considering different time scales and sky conditions

Photosynthetically Active Radiation (PAR) is a fundamental parameter for developing plant productivity models. Nevertheless, instrumentation for measuring PAR and to record it is scarce at conventional meteorological stations. Several procedures have therefore been proposed for PAR estimation. In this work, 21 previously published analytical models that correlate PAR with easily available meteorological parameters are collected. Although longer time scales were considered in the original publications, a minute range was applied in this work to calibrate the PAR models. In total, more than 10 million input records were gathered from the SURFRAD station network from a 10-year long time series with data frequencies recorded every 1 min. The models were calibrated both globally, using data from all stations and locally, with data from each station. After calibration, the models were validated for minute, hourly and daily data, obtaining low fitting errors at the different stations in all cases, both when using the globally calibrated models and with the models calibrated for each location. Although the PAR results in general improved for locally calibrated models, the use of local models is not justified, since the global models presented offered very satisfactory PAR results for the different climatic conditions where the meteorological stations are located. Thus, PAR estimation model should then be selected, solely considering the meteorological variables available at the specific location. When applying the globally calibrated models to input data classified according to sky conditions (from clear to overcast), the PAR models continued to perform satisfactorily, although the error statistics of some models for overcast skies worsened.

Bioclimatic spatial zoning for small ruminants in the state of Paraíba, Brazil

This study aimed to carry out bioclimatic zoning based on the historical series of climatic variables such as air temperature, maximum, minimum and relative humidity collected in six conventional meteorological stations in the state of Paraíba, Brazil and from this to determine whether or not the animals are in thermal comfort by comparing with the results obtained in scientific research in each mesoregion in the rainy and dry periods. Then based on this the comfort conditions for small ruminants in the rainy and dry seasons of the mesoregions of Paraíba were observed using data from the literature, and demonstrated in spatial distribution maps. The variables air temperatures, maximum and minimum and relative humidity varied throughout the state for the rainy season between 22 to 27, 18 to 21, 25 to 31ºC and 64 to 82%, respectively, and in dry season is 23 to 27, 28 to 35, 19 to 23ºC and 49 to 76%, respectively. However, it is concluded that raising sheep and goats is viable in all mesoregions of the state of Paraíba in both periods

How Well Does the ERA5 Reanalysis Capture the Extreme Climate Events Over China? Part II: Extreme Temperature

The fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts (ERA5) is the latest reanalysis product. However, the reliability of ERA5 to capture extreme temperatures is still unclear over China. Hence, based on conventional meteorological station data, a new criterion (DISO) was used to validate the ERA5 capturing extreme temperature indices derived from the Expert Team on Climate Change Detection and Indices (ETCCDI) across the six subregions of China on different timescales. The conclusions are as follows: the original daily temperatures (mean temperature, maximum temperature, and minimum temperature) can be well reproduced by ERA5 reanalysis over China. ERA5 tends to exhibit more misdetection for the duration of extreme temperature events than extreme temperature intensity and frequency. In addition, ERA5 performed best in the summer and worst in the winter, respectively. The trend of absolute indices (e.g., TXx and TNx), percentile-based indices (e.g., TX90p, TX10p, TN90p, and TN10p), and duration indices (e.g., WSDI, CSDI, and GSL) can be captured by ERA5, but ERA5 failed to capture the tendency of the diurnal temperature range (DTR) over China. Spatially, ERA5 performs well in southeastern China. However, it remains challenging to accurately recreate the extreme temperature events in the Tibetan Plateau. The elevation difference between the station and ERA5 grid point contributes to the main bias of reanalysis temperatures. The accuracy of ERA5 decreases with the increase in elevation discrepancy.

Bioclimatic diagnosis for poultry in municipalities of Mato Grosso, Brazil

This study aimed to determine the enthalpy index in three municipalities of Mato Grosso, to characterize the bioclimatic profile for the poultry industry. In the research, the compensated daily dry bulb temperature and the daily average relative humidity were used. The data corresponding to a historical series of 35 years, between 01/01/1985 and 12/31/2020, recorded in conventional meteorological stations in the municipalities of Canarana, Nova Xavantina, and Santo Antônio de Leverger, available in the Meteorological Database for Teaching and Research of the National Institute of Meteorology (INMET). Then, monthly descriptive statistics of the historical series were determined and bar plot graphs with enthalpy values were developed. These graphs included the lower and upper enthalpy limits, suitable for laying hens and broilers, to qualify the thermal conditions of environmental comfort in the three municipalities of Mato Grosso. It was concluded that the enthalpy index made it possible to characterize the bioclimatic profile of the mentioned municipalities for poultry farming, according to the months of the year. The natural thermal conditions in these municipalities were not favorable to poultry farming, requiring extra investments in the air conditioning of the sheds. The increase in thermal discomfort for broilers was accentuated from the fourth week of the production cycle. The applied methodology presented itself as an adequate tool to assist in the elaboration of projects related to environmental changes in aviaries.

Validation of TRMM data in the geographical regions of Brazil

ABSTRACT The low density of precipitation gauges, the areas of difficult access and the high number of missing values hinder a rapid and effective hydrological monitoring. Thus, the present study aims to statistically validate the precipitation estimates by the data Tropical Rainfall Measuring Mission (TRMM) in relation to the data observed in the Conventional Meteorological Stations (CMSs) in the geographic regions of Brazil. The statistical indicators used were: Correlation Coefficient (r), Mean Absolute Error (MAE), Percentage of Bias (Pbias), T-Test and Mann-Witiney Test. It is concluded that the precipitation data estimated via TRMM are effective and reliable alternatives for hydrological studies in areas that do not have in-situ gauges and/or need to fill missing values in the five regions of the country, especially in the driest months and in larger time scales.

Zonificación bioclimática para la producción de ganado lechero en la región sureste de la Amazonía Legal

Bioclimatic zoning for dairy cattle production in the southeast region of the Legal AmazonAbstract. This study intended to establish the bioclimatic zoning of the southeast state of Pará aiming at the production of dairy cows. For the realization of bioclimatic zoning, data from the years 1992 to 2017 were collected from conventional meteorological stations under the responsibility of the National Meteorological Institute (INMET) that comprise the Southeast region of Pará. With the data observed in this study, it is possible to affirm that the climatic conditions of the studied region are not ideal for the production of animals of the Jersey, Holstein and Girolando breeds, presenting constant high temperature and relative humidity and with the temperature and humidity index (THI) above 78. Thus, we reinforce the need to use environmental changes in the productive farms of the region. We also encourage studies that aim to understand the adaptive strategies of dairy cattle under thermal stress conditions.

Empirical methods for reference evapotranspiration estimation

The reference evapotranspiration (ETo) is a parameter applied in meteorological, climatological and hydrological studies being of great importance for the planning, management and management of water resources. Due to the need for knowledge about the loss of water from vegetated surfaces, researchers have developed a variety of methods for estimating ETo, some of which are well accepted, while others are criticized, such as the Penman-Monteith-FAO (PM-FAO) meteorological data, which is not always available by limiting its use. The PM-FAO method has been used for decades to be considered internationally and most appropriate for ETo estimates. This method represents the physical phenomenon of evapotranspiration that involves almost all meteorological elements analyzed in automatic and conventional meteorological stations. On the other hand, when this method is impossible to apply due to the lack of some input data, alternative methods are justified (Hargreaves-Samani, Blaney-Criddle, Priestley-Taylor, Jensen-Haise, Camargo, Makkink, Kharrufa , Linacre, Class A tank, Thornthwaite and solar radiation) according to soil and climatic conditions.

Analysis of the Variability and Future Evolution of Snowfall Trends in the Huaihe River Basin Under Climate Change

Global warming changes the characteristics of regional climate and crop growth environments and affects human production and life in the long term. In this study, the historical snowfall observation data from 199 conventional meteorological stations in the Huaihe River Basin were analyzed with the climate tendency rate method and the nonparametric Mann-Kendall (M-K) test to determine the variability and abrupt changes in climate trends in the Huaihe River Basin during 1951-2018. Then, the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets were used to analyze the evolutionary trend of snowfall under four climate change scenarios in 2015-2065. The results show the following: (1) Due to climate warming, both the historical data and the simulated data under different climate change scenarios show declining snowfall in the Huaihe River Basin. (2) Based on the analysis of historical data from meteorological stations, the snow events had a clear latitudinal distribution—the higher the latitude, the lower the occurrence of snow events. In contrast, as shown by the analysis results obtained under different climate change scenarios, the snow mass flux had a clear longitudinal distribution—the higher the longitude, the larger the snow mass flux. (3) In Scenario SSP370, 2050 is an important year for snowfall to change from decreasing to increasing; in 2065, the snowfall in most areas of the basin is larger than that in 2050, and the snowfall in the southeastern coast of the basin has the largest variability.

Influence of meteorological variables on reference Evapotranspiration in the State of Alagoas, Brazil, based on multivariate analysis

Reference evapotranspiration (ETo) is an important agro-meteorological parameter used in several meteorological, climatological and hydrological studies. This study aimed to diagnose the effect of the meteorological variables and large-scale variability modes in ETo, based on logistic regression models. Monthly data from five conventional meteorological stations located on the State of Alagoas, Brazil, were used: Agua Branca, Maceio, Pao de Acucar, Palmeira dos Indios and Porto de Pedras, from 1960 to 2016 period. The variables used were as follows: temperatures (air—Tair, maximum—Tmax and minimum—Tmin), relative humidity (RH), sea level pressure, sunshine, wind speed (WS), rainfall, evaporation and also two climatic proxies: Oceanic Nino Index (ONI) and Tropical South Atlantic (TSA). ETo was estimated using the Penman–Monteith FAO method. The binary logistic regression procedure evaluated ETo values below the percentile 75 (ETo75 characterized as 1). Regarding the variables used the percentile 75 (except Tair and rainfall that used the percentile 30). The temperatures were the main variable for ETo75 events, except in Agua Branca. The Tmax presented the highest odds ratio (OR) in Palmeira dos Indios with value of 21.10 times on occurrence of ETo75. The wind is the most important variable in Pao de Acucar, due the heat capacity of the Sao Francisco River, with OR value of 3.72 times. The ONI did not integrate the models. Based on AIC and ROC curve values, Palmeira dos Indios presented the best model with a value of 195.95 and 0.979, respectively.

Characterization of the Average Wind Speed in the Municipaly of Teresina-PI

The winds are of fundamental importance in the terrestrial dynamics; Represent one of the main elements influencing various climate phenomena such as soil erosion, pollutant dispersion, seed transport and generation of wind energy. The characterization of the wind at any point of the atmosphere takes two parameters: Speed and direction, which are instantaneous quantities because they depend on conditions such as atmospheric pressure gradient originating displacement of air masses at different temperatures. Accurate information on wind speed is important as it plays a significant role in the application efficiency. Considering the importance of understanding the behavior of the wind, this work, was aimed to characterize the average wind speeds for the city of Teresina, located in the state of Piauí, Brazil. We used 1976 to 2019 data on wind speed of 10 meters height obtained fromthe records of the conventional meteorological station of the National Institute of Meteorology (INMET). The highest wind speed is in July to November with speed ranging from 1.6 to 1.8 m/s and the lowest wind speeds are centered in the months from December to April with oscillation 1.3 to 1.5 m.s-1.

Oscilações climáticas das temperaturas extremas, média e amplitude térmica do ar em Bom Jesus Piauí, Brasil

A temperatura do ar é um elemento climático que ao longo do tempo e em regiões tropical e semiárida poderá afetar o sistema produtivo agrícola ocasionando significativas mudanças nos próximos anos em consequência ao aquecimento global. O objetivo foi caracterizar as diferencias existente no clima de Bom Jesus Piauí quanto às oscilações climáticas nas temperaturas extremas, média e amplitude térmica para o período de 1990-2018 e seu comparativo com a média histórica de 1960-2018. Os dados utilizados foram adquiridos da estação meteorológica convencional do Instituto Nacional de Meteorologia para o período de estudo, as informações dos dados térmicos extremos, médio e amplitude térmica auxiliaram aos tomadas de decisões no meio agropecuário, rural, urbano e em várias áreas do conhecimento cientifico. As médias das temperaturas mínimas tendem a aumentar e as médias das temperaturas máximas tendem a manterem-se inalteráveis. Desta forma a temperatura média e as amplitudes térmicas tendem a manter-se em elevações. A altitude e a latitude têm analogias inversamente proporcionais, enquanto a longitude teve uma relação proporcional com a temperatura. Das temperaturas em estudados, a temperatura mínima é, destacadamente, a que apresenta maior aumento e maior consistência espacial.

A statistical method to construct wind speed at turbine height for study of wind power in China

The accurate estimation of wind power is crucial not only to conduct wind energy research but also to improve policy and planning decisions for the national government. However, reliable wind speed datasets at turbine height that can be used for wind power estimation in China are very limited. In this study, the simulated wind profile (expressed by a power-law approach) is optimized using radiosonde wind speed measurements. The wind speed at a typical turbine height (80 m) is then constructed using the optimized wind profile and 10-m wind speed measured at each conventional meteorological station throughout the country. Compared with measurements, the constructed wind speed has reasonable errors (0.08 m s−1 in mean bias, 0.89 m s−1 in root mean square error, and 0.90 in correlation coefficient), which are much smaller than the model errors. Further comparison shows the constructing method in the current study outperforms the other similar statistical methods. Therefore, this method and the constructed wind speed dataset are suggested for wind energy research in China.

Modeling hourly air temperature based on internationally agreed times and the daily minimum temperature

ABSTRACT There are several fields that require knowledge of air temperature variation throughout the day, such as disease prediction or calculation of chill-hours. However, automatic meteorological stations are not always located in the vicinity to accurately monitor this variable. In this sense, models that describe the daily temporal variation of air temperature can be used to meet this demand, and transform the climatic data series of conventional meteorological stations into an estimated hourly series. The aim of this study was to adjust and validate models for the hourly air temperature variation through data obtained at internationally agreed times (0, 12 and 18 h Universal Time Coordinated: UTC) and the daily minimum air temperature. The hourly database of the automatic station was used for model adjustment and validation. Functions were adjusted based on values measured at internationally agreed times and the daily minimum air temperature for certain daily variation patterns. The air temperature estimation was performed on an hourly basis using sinusoidal and linear models. The model that presented the lowest root mean square error (RMSE) was used for the estimation. The accuracy of the air temperature estimates varied according to the time, presenting RMSE from 0.7 to 1.6 °C, with maximum mean deviation of 0.4 °C. The results of this study showcase the necessity of knowledge of the daily air temperature variation, as well as a series of data from conventional meteorological stations, which can be estimated using hourly models.

Bioclimatic zoning and trend analysis applied to broilers

ABSTRACT The objective of the present study was to establish the bioclimatic zoning by the temperature and humidity index (THI), considering a historical period and a future scenario, in order to represent the thermal environment for broiler breeding in the State of Minas Gerais. A historical series (1976 - 2014) of THI minimum, average and maximum calculated based on data from 48 conventional meteorological stations was used, belonging to the National Institute of Meteorology of the State of Minas Gerais. The analysis of the temporal series was based on the Mann-Kendall test and linear regression. A geostatistical analysis was also carried out to determine the comfort zoning of broilers as a function of the THI intervals. In this way, the THI spatial mapping methodologies and trend analysis for the prediction of a possible future climate scenario can help in the development of risk maps for monitoring thermal comfort of broilers, being indispensable in the planning of actions for the mitigation of the climatic change impacts on the productive chain of the State of Minas Gerais.

Calibration Methods for Estimation of Reference Evapotranspiration in Morro Do Chapéu, Bahia, Brazil

The objective of this work was to calibrate and to validate the methods of Camargo, Hargreaves and Samani, and Priestley and Taylor, according to the Penman-Monteith model, for the estimation of reference evapotranspiration (ETo), in the four seasons of the year for the municipality of Morro do Chapéu, Bahia. Climatological data from the conventional meteorological station belonging to the National Institute of Meteorology (INMET) were used, in the period of 18 years (2000-2018). The first 16 years were considered to adjust the parameters. The years of 2016 and 2017 were assigned as independent data to validate the adjustments. To analyze the results, it was used the root mean square error (RMSE in mm d-1), coefficient of determination (R2), systematic error (BIAS in mm d-1), and Willmott’s concordance index. After adjusting the parameters, the three methods improved their performance in the estimation of ETo, however, the Camargo method presented high values of RMSE, reaching 0.41 mm d-1 during the spring. It is concluded that the calibrated methods of Hargreaves and Samani, and, Priestley and Taylor can be recommended for the estimation of the reference evapotranspiration, for planning and execution of irrigation projects in the municipality, regardless of the season.