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Central Chile (CC, latitudes 32–40°S) experienced very active fires in 2017 and 2023. These fires burned large areas and killed many people. These unprecedented fires for CC presented a need for more defined fire weather conditions on the synoptic scale. In this paper, fire weather conditions were analyzed using various satellite-derived fire data (hotspots, HSs), wind streamlines, distribution maps of wind flow and temperature, and various synoptic-scale weather maps. Results showed that local winds, known as Puelche, blew on the peak fire days (26 January 2017 and 3 February 2023). The number of HSs on these days was 2676 and 2746, respectively, about 90 times the average (30). The occurrence of Puelche winds was confirmed by streamlines from high-pressure systems offshore of Argentina to the study area in CC. The formation of strong winds and high-temperature areas associated with Puelche winds were identified on the Earth survey satellite maps. Strong winds of about 38 km h−1 and high temperatures above 32 °C with low relative humidity below 33% were actually observed at the weather station near the fire-prone areas. Lastly, some indications for Puelche winds outbreaks are summarized. This paper's results will be used to prevent future active fire occurrences in the CC. [ABSTRACT FROM AUTHOR]

Future climate change is expected to increase the risk and severity of wildland fires in tropical regions. Synoptic-scale fire weather conditions in Mexico were carefully analyzed using 20 years of satellite hotspot and rainfall data, hourly weather data, and various climate data. Fire analysis results showed that eighty-four percent of all fires in Mexico occurred south of 22° N. Southwest Mexico (SWM, N < 22°, 94–106° W) and Southeast Mexico (SEM, N < 22°, 86–94° W), account for 50% and 34% of all fires in Mexico. Synoptic-scale analysis results using hourly data showed that westerly wind sea breezes from the Pacific Ocean blow toward the coastal land areas of the SWM while easterly wind sea breezes from the Caribbean blow into the SEM. The most sensitive weather parameters were "relative humidity" for the SWM and "temperature" for the SEM. The fire-related indices selected were "precipitable water vapor anomaly" for the SWM and "temperature anomaly" for the SEM. The SWM fire index suggests that future fires will depend on dryness, while the SEM fire index suggests that future fires will depend on temperature trends. I do hope that this paper will improve local fire forecasts and help analyze future fire trends under global warming in Mexico. [ABSTRACT FROM AUTHOR]

Non-professional weather stations are often omitted from the networks of standard/professional stations at various spatial scales. Nevertheless, there are many tasks when such non-professional datasets can serve as the only or the most relevant available source respectively. Its acquisition costs, sufficient quality and capacity together with its moveability represent properties that should be taken into consideration when planning operational usage of various meteorological data. In this paper, we focus on the datasets of air temperatures and relative humidities measured both with professional and nonprofessional devices at nearly the same location. Four years of almost continual measurements (2016-2019) ensure robust sample of mutual comparison, which we analyze in the paper more in detail in order to assess the potential of non-professional datasets for utilization in aviation meteorology. Particular issues such as value difference patterns, large errors occurrence, temporal signal stability and seasonality are elaborated as well [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), the Third Pole of the world, has experienced significant warming over the past several decades. Previous studies have mostly relied on station-observed air temperature (Ta), reanalysis data, and remotely sensed land surface temperature (LST) to analyze the warming trend over the TP. However, the uneven distribution of stations, the poor spatial resolution of reanalysis data, and the differences between LST and Ta may lead to biased warming rates. This paper first maps Ta over the TP from 2001 to 2020 based on multi-source remote sensing data, and then quantifies the spatio-temporal variations of remotely sensed Ta and elevation dependent warming (EDW) of this region. The monthly mean Ta is estimated using machine learning (ML) method year by year, and its accuracy is validated based on station-observed Ta. The coefficient of determination (R2 ranges from 0.97 to 0.98 and the mean absolute error (MAE) ranges from 1.01 to1.04 °C. The remotely sensed Ta is used to analysis warming trend and EDW over the TP. The overall warming trend of the TP during 2001–2020 is 0.17 ℃/10a, and warming mainly distributed in the eastern TP, central TP and western Kunlun Mountains. Among the four seasons, autumn shows the most significant warming, tripling the annual warming rate. Winter shows a significant cooling trend, with the warming rate of -0.18 ℃/10a. The study also reveales the existence of EDW at both the annual and seasonal scales. This paper suggests the potential of remotely sensed Ta in global warming study, and also provides an improved understanding of climate warming over the TP. [ABSTRACT FROM AUTHOR]

This paper considers subsonic turbojet aircraft fuel consumption minimization problem during cruise phase, assuming fixed time of arrival. The problem takes into account real atmosphere data. We utilize tailwind/headwind component values at various flight levels, as well as air temperatures and atmospheric pressures at various altitudes. The solution to the altitude and speed flight profile optimization problem is through constrained coordinate descent method. The paper considers optimizing the fuel consumption of a medium-haul aircraft during the cruise phase using sample data set on temperature, pressure, and wind speed. The proposed approach achieves a decrease in fuel consumption of 1.2% when optimizing with regard to real atmosphere. [ABSTRACT FROM AUTHOR]

For normal operating conditions of the centrifugal fan, the manufacturers provide operating curves (total pressure of the fan, static pressure of the fan, power, and efficiency) for standard air conditions. However, when a fan operates with air at different, usually elevated temperatures, their operating curves can significantly differ. As a result, the fan efficiency decreases, and the energy efficiency of the fan may be reduced. Fan operation in such air conditions also affects its acoustic characteristics. This paper investigates two types of centrifugal fans: with forward curved and backward inclined blades. The main goal was to determine how their operating and acoustic characteristics change with the change in air temperature. For this analysis, low pressure centrifugal fans are used, for which we already had measured operating and acoustic characteristics. The influence of the type of impeller and the curvature of the blades play an important role in the operation of the fan. For numerical investigation, ANSYS CFX software was used, and obtained results show excellent agreement with experimental measurements. [ABSTRACT FROM AUTHOR]

The air temperature changes in the Palu MW7.5 earthquake in Indonesia on 28 September 2018 were analyzed, based on the additive tectonic stress caused by celestial tidal-generating forces (ATSCTF) and air temperature data from the National Center for Environmental Prediction (NCEP). This paper explored the variation characteristics of three-dimensional stratified of air temperature caused by seismic activity and the coupling relationship between air temperature changes and the tidal force. The background information for air temperature calculation was obtained from the tidal force changes, and the air temperature increment method was used to study the temperature evolution process of different periods in the study area. The results found that the tidal force acting on the critical state earthquake faults may be an important external factor inducing earthquakes, and there was indeed a significant air temperature increase anomaly during the Palu MW7.5 earthquake. The paper also summarized the abnormal characteristics of air temperature caused by seismic activity: the air temperature closer to the land's surface has greater anomaly amplitude and a wider anomaly area than that of the upper air. [ABSTRACT FROM AUTHOR]

Fog in mine air intake roadways is a non-negligible disaster that seriously reduces the visibility of the roadway, affects vehicle transportation and the safe passage of personnel, and jeopardizes the safe production of the mine. This paper applies both field testing and numerical simulation to explore fog formation conditions and the effects of inlet air temperature and humidity on the fog zone length within the Wangjialing Mine's air intake roadway in Shanxi, China. First, based on the consideration of the relationship between the moisture gain of surrounding rock and the temperature with humidity of the air flow, the fog generation and distribution law model of the air intake roadway was established. Based on this model, the critical inlet air temperature and the critical inlet air relative humidity for fogging in the Wangjialing Mine air intake roadway were determined. In addition, we found that the fogging point inside the roadway shifted forward continuously with the increase in inlet air temperature and inlet air relative humidity, and the length of the fog zone expands parabolically in response to these rising conditions. [ABSTRACT FROM AUTHOR]

In this paper, a sequence (1979–2022) of a long-term trial established in Lukavec in 1956 (Czech Republic) focusing on the effect of weather, various nitrogen (N) fertilization methods (control, PK, N1PK, N2PK, and N3PK) and preceding crops (cereals, legumes, and oil plants) on winter wheat grain yield is presented. The weather significantly changed at the site of the long-term trial. While the trend in the mean temperature significantly increased, precipitation did not change significantly over the long term. Four relationships between weather and grain yield were evaluated to be significant: (a) the mean temperature in February (r = −0.4) and the precipitation in (b) February (r = −0.4), (c) March (r = −0.4), and (d) May (r = 0.5). The yield trends for all the fertilizer treatments increased, including the unfertilized control. The N3PK treatment provided the highest mean grain yields, while the unfertilized control had the lowest yields. Comparing the preceding crops, the highest yields were harvested when the wheat followed the legumes. On the other hand, the cereals were evaluated as the least suitable preceding crop in terms of grain yield. According to the linear-plateau model, the optimal nitrogen (N) dose for modern wheat varieties, following legumes and under the trial's soil climate conditions, was 131 kg ha−1 N, corresponding to a mean grain yield of 8.2 t ha−1. [ABSTRACT FROM AUTHOR]

In the present paper, the effect of air density variations on cup anemometer performance is analyzed. The effect on the sensor's performance is mainly due to the difference between the altitude at which the cup anemometer is working and the altitude at which this instrument was calibrated. Data from the available literature are thoroughly analyzed, focusing on explaining the coupled effect of the air temperature on both the rotor's friction torque and the air density (that is, related to the aerodynamic torque on the rotor). As a result, the effect of air density variation at constant temperature (that is, leaving aside any variation of friction forces at the anemometer rotor shaft) on the sensor transfer function (i.e., on the calibration constants) is evaluated. The analysis carried out revealed a trend change in the variation with air density of the transfer function of the cup anemometer. For densities greater than 0.65, the calibration constants of the instrument have a variation with density that must necessarily change suddenly as the start-up speed, represented by the calibration constant B, becomes zero around this value of air density. To highlight the relevance of the present research, some estimations of the effect of wind speed measurement errors associated with air density changes on the Annual Energy Production (AEP) of wind turbines are included. A 1.5% decrease in the AEP forecast at air density corresponding to 2917 m above sea level is estimated for 3000–4500 kW wind turbines. [ABSTRACT FROM AUTHOR]

Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period from 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the CP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warming events are often observed, which lead to the destruction of PV and an increase in column ozone. [ABSTRACT FROM AUTHOR]

The experimental setup of HVAC testing requires easy but accurate instrumentation, and recent analyses focus on the control based on the mean radiant temperature in order to better perform respect to the users satisfaction. Indeed, the research contribution of this work is the use of Arduino to develop a PID control for an electric heater. As a main feature, this control system can operate by maintaining the set-point on the air temperature or on the mean radiant temperature of the environment where it is placed. The paper describes the design and development of the PID control, as well as the testing of the control system applied to an electric heater, to heat a room in a laboratory in Bologna (Italy). In an Appendix the Matlab script employed to store data on the local pc an to send data to Google Sheets is reported, together with the Google script code employed to write the data from Matlab to the online sheet. As result, the developed PID is accurate in maintaining the required set-point temperature, with minimal deviations from the set-point, in the interval ± 0.2 K. [ABSTRACT FROM AUTHOR]

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [ABSTRACT FROM AUTHOR]

This article addresses the simulation of urban air temperatures with a focus on evaluating the Urban Weather Generator (UWG) model over Toulouse, France. As urban temperatures, influenced by factors like urbanization, anthropogenic heat release, and complex urban geometry, exhibit an urban heat island (UHI) effect, understanding and mitigating UHI become crucial. With increasing global warming and urban populations, aiding urban planners necessitates accurate simulations requiring data at the canyon level. The paper evaluates UWG's performance in simulating air temperatures under realistic conditions, emphasizing an operational context and a non-specialist user's perspective. The evaluation includes selecting the most suitable meteorological station, assessing the impact of the rural station choice, and conducting a sensitivity analysis of input parameters. The validation demonstrates good agreement, with a mean bias error (MBE) of 0.02 °C and a root mean square error (RMSE) of 1.73 °C. However, we highlight the fact that UWG performs better in a densely urbanized area, and exhibits limitations in sensitivity to urban surface parameter variations, particularly in less urbanized areas. [ABSTRACT FROM AUTHOR]

Due to the increasing demand of climate change studies, traceability of measurements according to the International System of Units (SI) becomes fundamental to establish data quality and comparability in time. With the aim of guaranteeing the traceability, in October 2022, an on-site calibration of three thermometers operated by the Osservatorio meteorologico di Moncalieri was assessed. The calibration by comparison against traceable travelling standards was performed in a transportable thermal chamber manufactured by the Istituto Nazionale di Ricerca Metrologica (INRIM). Results showed that the main uncertainty contributions to the expanded uncertainty were the interpolation method, the chamber inhomogeneity and the repeatability of the sensors under calibration. This current calibration was compared with previous calibration in 2012 (on-site calibration) and in 2016 (laboratory calibration). The comparison analysis evidenced the drift effect on the thermometers and the importance of having an active calibration program to reduce this effect. Regarding the expanded uncertainty, both on-site calibrations presented the same order of magnitude and smaller than the correction values. This paper points out the advantage of performing an on-site calibration: since the calibration involves the same dataloggers and cables in the same environmental conditions, the calculated calibration curve represents more convincingly the real measurement conditions. [ABSTRACT FROM AUTHOR]

The paper presents the results of experiments with a solar greenhouse used to ensure the most favorable temperature regime. In order to provide thermal insulation and reduce heat losses, a solar greenhouse structure with an arched shape and a total area of 200 m2 has been developed. It is located directly in the ground, at a depth of 0.5 m and a height of 4.0 m above ground. The total height of the greenhouse is 4.5 m, the length is 20 m, and the width is 10 m. These dimensions comply with the standards established in KMK 2.09.08-97 Greenhouses and Hotbeds. On the outer part of the solar greenhouse, a layer of dry straw with sufficient permeability to sunlight is placed between two transparent enclosures during the winter period for thermal insulation. This significantly reduces heat losses through the top transparent surface and enhances the greenhouse effect. This transparent enclosure design allows heavy mechanical loads, is resistant to mechanical cleaning processes, and at the same time, has high thermal insulation properties. By using the solar greenhouse structure with the energy flow scheme presented, a more homogeneous air environment with temperature inside the greenhouse can be achieved, even during daily fluctuations in the temperature of the surrounding air. The temperature and humidity parameters inside the solar greenhouse vary due to the absorption of solar radiation from the ground surface and the evaporation of moisture from the soil. The results of the experiments show that the solar greenhouse based on our energy flow scheme, using the ground as thermal insulation, significantly reduces heat losses through the floor. The method of insulation between two transparent enclosures provides a more homogeneous air environment with air temperature inside the greenhouse, despite significant daily fluctuations in the temperature of the surrounding air, and effective accumulation of solar energy inside the solar greenhouse. [ABSTRACT FROM AUTHOR]

One of information needed in weather forecast is air temperature. This value might change any time. Prediction of air temperature is very valuable for some communities and occasions. Therefore, high accuracy prediction is needed. Since the information about air temperature might vary over time, it is necessary to implement methods that can adapt to this situation. The use of neural network methods such as long short term memory (LSTM), nowadays, becomes popular in facing big data including unexpected fluctuation on the data. Thus, the model is used in this paper which provides long series data on air temperature. In addition, recently, Facebook announced an accurate method of forecasting, called Prophet model's, for data which have trend, seasonality, holidays, missing data, not to mention outliers. Hence, the forecast of five-year daily air temperatures in Bandung on this paper is modeled by LSTM and Facebook Prophet. The result shows that, for minimum temperature, Prophet performs better on maximum air temperature while LSTM performs better on minimum air temperature. However, the difference on the value of RMSE is not too large significant. [ABSTRACT FROM AUTHOR]

The paper presents the results of studying the spatial and seasonal atmospheric temperature characteristics of Jalingo metropolis, Nigeria, with the aim of assessing seasonal temperature variations for thermal comfort planning. Temperature data for this study was collected across the local climate zones, otherwise known as thermal climate zones (TCZ), following the TZC classification of the area. Temperature data was collected for 30 days continuously and simultaneously across the TCZ. The collection of temperature data was done in the months of April and August 2021, and January 2022 - representing the dry season, the rainy season and the Harmattan period respectively. A Thermochron Ibutton sensor by Maxim Incorporation was used to collect temperature data, while the specific series used was DS1921. An improvised automated weather station was constructed to house the sensor. The result of the study indicates that air temperature varies considerably within Jalingo metropolis, as well as throughout the seasons, thus affecting human thermal comfort in the study area, as temperature is found to correlate well with both human morbidity and mortality, especially regarding cardiovascular diseases. The paper recommends increasing ventilation and naturebased solution to reduce high temperatures through tree planting in order to improve human thermal comfort in Jalingo metropolis area. [ABSTRACT FROM AUTHOR]

The improvement of human well-being and the urban environment in cities and towns around the world will always be at the forefront of our interests. After all, the resilience of the urban environment to climate change is very important now. For example, the residents' well-being can be improved in terms of environmental aspects. The opportunities for improving the urban environment are, of course, closely interconnected with other aspects, i.e., economic, technical and social. One of the ways to increase the resilience of cities is by progressive urban greening with small urban greenery elements. Exterior green walls are attractive, often used in urban areas, and are also the key issue of our paper. They represent at first sight (concerning their usual size) only a small instrument, but they can have a significant environmental, techno-economic and socio-cultural impact. Potential stakeholders may not be aware of this consequence. Our research focuses not only on a model exterior green wall (LIKO-S a.s., Czech Republic), where selected environmental aspects were measured for one year to confirm or deny the cooling effect of the exterior green wall on the surrounding environment, but also to objectify the issue of green walls. We also present proposals for tools that consider other aspects (technical-economic and socio-economic aspects): objectivization-decision scheme and guided interview for stakeholders' motivation. These tools can serve future stakeholders in the pre-implementation phase of the intended exterior green wall. Objectivization of exterior green walls is the main goal of the present paper. [ABSTRACT FROM AUTHOR]

Deep learning methods can achieve a finer refinement required for downscaling meteorological elements, but their performance in terms of bias still lags behind physical methods. This paper proposes a statistical downscaling network based on Light-CLDASSD that utilizes a Shuffle–nonlinear-activation-free block (SNBlock) and Swin cross-attention mechanism (SCAM), and is named SNCA-CLDASSD, for the China Meteorological Administration Land Data Assimilation System (CLDAS). This method aims to achieve a more accurate spatial downscaling of a temperature product from 0.05° to 0.01° for the CLDAS. To better utilize the digital elevation model (DEM) for reconstructing the spatial texture of the temperature field, a module named SCAM is introduced, which can activate more input pixels and enable the network to correct and merge the extracted feature maps with DEM information. We chose 90% of the CLDAS temperature data with DEM and station observation data from 2016 to 2020 (excluding 2018) as the training set, 10% as the verification set, and chose the data in 2018 as the test set. We validated the effectiveness of each module through comparative experiments and obtained the best-performing model. Then, we compared it with traditional interpolation methods and state-of-the-art deep learning super-resolution algorithms. We evaluated the experimental results with HRCLDAS, national stations, and regional stations, and the results show that our improved model performs optimally compared to other methods (RMSE of 0.71 °C/0.12 °C/0.72 °C, BIAS of −0.02 °C/0.02 °C/0.002 °C), with the most noticeable improvement in mountainous regions, followed by plains. SNCA-CLDASSDexhibits the most stable performance in intraday hourly bias at temperature under the conditions of improved feature extraction capability in the SNBlock and a better utilization of the DEM by the SCAM. Due to the replacement of the upsampling method from sub pixels to CARAFE, it effectively suppresses the checkerboard effect and shows better robustness than other models. Our approach extends the downscaling model for CLDAS data products and significantly improves performance in this task by enhancing the model's feature extraction and fusion capabilities and improving upsampling methods. It offers a more profound exploration of historical high-resolution temperature estimation and can be migrated to the downscaling of other meteorological elements. [ABSTRACT FROM AUTHOR]

In this paper, we describe the results of a climate data rescue (DARE) activity conducted at the Ukrainian Hydrometeorological Institute (Kyiv, Ukraine) in cooperation with the Justus Liebig University Giessen (Giessen, Germany), the World Meteorological Organization (WMO) and Met Office Hadley Centre (Exeter, United Kingdom). The focus of our work is on pre‐1850 sub‐daily meteorological observations conducted on the territory of modern Ukraine. Data from eight stations (stored in special hard copy tables/books, with handwritten records) have been digitized during the DARE process, resulting in 291,103 rescued values in total. More than half of this number (165,980, ~57%) are related to air temperature data, 124,376 data values (~42.7%) concern atmospheric pressure records and 747 values (~0.3%) are precipitation data. Simple quality control of the digitized data has been conducted, including an intercomparison between stations as well as comparison with monthly temperature data previously digitized from other paper sources. The quality control procedures revealed fairly good agreement between rescued time series on the monthly time scale as well as with the monthly data from independent sources. However, several periods for a few stations should be used with caution due to relatively large discrepancies that were found. The rescued digital database can be used for extreme value analysis for the pre‐1850 period in comparison with today's climate, regional climatological studies and will be used for future Reanalysis. In addition, for the first time, we show that subdaily temperature from Kyiv during 'the year without summer' 1816 in Western and Central Europe were not anomalous in this part of Eastern Europe. [ABSTRACT FROM AUTHOR]

The paper compares air and sea surface temperatures in recent years on two islands in the Adriatic Sea. The data measured at the climatological station Krk on the island of Krk and the main meteorological station Lastovo on the island of Lastovo are used. The island of Krk is located in the north of the Adriatic Sea and Lastovo in the south. Since a significant increase in air and sea surface temperatures has been observed over the last thirty years, the goal is to establish how they reflect at these two stations, 313 km apart. The goal of the analysis is to monitor the changes in these two islands to reduce the negative impacts they may cause. The analysis of sea temperatures showed that global warming has a greater impact in the northern Adriatic than in the southern Adriatic. Air and sea surface temperatures have a faster upward trend on Krk than on Lastovo. Similar to the Mediterranean Sea, a positive trend was observed in the Adriatic Sea for both sea surface temperature and air temperature. [ABSTRACT FROM AUTHOR]

The present paper analyzes long term (1960–2021) of the minimum, maximum, and average temperatures in Central Anatolia Region, corresponding middle part of Turkey, aiming to reveal how strongly the temperatures increase, which is a precondition for sustainable development in this region. For this purpose, temporal trends, variability, and anomalies in temperatures of 27 meteorological stations were detected using Mann–Kendall test (M-K), coefficient of variations, and Gaussian filter, respectively. Results show a statistically significant increasing trend in annual average temperatures at approximately 92% of all stations. This shows that the increasing trend in spring and summer temperatures plays an important role in amplifying the warming trend of annual temperatures. The coefficients of variation in annual average, maximum, and seasonal temperatures increase from west to east. Significant strong increasing trend (at 0.001 level) in winter temperatures was detected only at Seydişehir. While positive anomalies have been observed in the northwestern part of the region since 2007, they have been observed in other parts since 1995–1996. Since the strong increase in summer temperatures in Aksaray, Cihanbeyli, and Seydişehir is also observed in autumn, warm conditions continue until the end of autumn in these settlements. For this reason, four seasons do not prominently occur for all three settlements. Generally, annual maximum and minimum temperatures illustrate statistically significant increasing trends for all stations and 74% of all stations, respectively. According to the M-K test results, climate of the region has warmed on average by 1.44 °C in last 31 years. [ABSTRACT FROM AUTHOR]

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This paper presents experimental investigations of the efficiency of an open-type refrigerated display cabinet used to store food at temperatures between -1 and +7 °C. The purpose of the study was to increase the efficiency of the open-type cabinet by improving its design. The cabinet has five shelves for food products with lengths of 350-600 mm. The spacing between the base and the first shelf is 280 mm, and between the other shelves it is 250 mm. The air enters the cabinet from the return air grille (RAG) at the bottom of the front panel, fans blow air through the evaporator, and the cooled air travels through a tunnel to the top of the refrigerator. The perforated distributor at the top distributes the cooled air, and part of the air is blown through the perforated back panel and the other part passes through the air-off honeycomb (dimensions (W×H) are 120×20 mm) at the front top of the cabinet, thus forming an air curtain between the inside of the refrigerator and the ambient warm air to protect the chilled food products. The cooled air entering through the perforated back panel into the display area helps maintain the required food temperature. In this study, two versions of the refrigerated cabinet were analyzed. The first version is the standard refrigeration cabinet and the second version is the same cabinet but with a change in the angle of inclination of the honeycomb and a reduction in the depth of the shelves. Air and test product temperatures were measured with thermocouples, and electrical energy consumption was measured with the Carel MT300W1100 energy meter. The experimental results show that the infiltration ratio decreases from 38.7 to 27.7%, and the 24-hour electrical consumption decreases from 24.91 to 19.22 kWh in the case of the modified cabinet. The average air temperature in the return air grille (RAG) decreased from 7.5 to 6.52 °C with the same temperature settings. The average temperature of the M packages decreased by 0.2-2.2 °C depending on the position in the refrigerator. [ABSTRACT FROM AUTHOR]

Long‐term climate monitoring by universities provides fundamental data for various disciplines in the natural sciences. Kyoto University once managed 10 university forest stations and is currently managing five. At these stations, climate data have been monitored almost since the establishment of each station until today, with the exception of the stations in foreign countries. We compiled and report the monthly climate data at these forest stations from the start of monitoring until December 2018. These data are important for investigating environmental changes in East Asia, including China (Taiwan), South Korea (Chosen) and Russia (Sakhalin, Karafuto) over the last 100 years. Long‐term monitoring often involves minor and major changes in the monitoring procedures, devices and even monitoring sites due to unavoidable circumstances, such as technological advances, changes in standard methods and climatic and anthropogenic disasters. Therefore, associated metadata on the monitoring methods are also important. We also compiled metadata on changes in monitoring methods. In addition, to examine the effects of changes in the methods on the observed climate data, we compared the values recorded before and after the change for each climate variable at each monitoring site. Methodological changes affected only a few variables, with the exception of humidity. Careful interpretation may be required when a researcher uses humidity data in any analysis. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-03.1/jalter-en. [ABSTRACT FROM AUTHOR]

Comprehensive bridge design should consider simultaneous actions of wind and temperature. The current load combination method of directly superposing extreme wind and temperature actions ignores the correlation between wind and temperature, resulting in too conservative bridge load estimates, and limiting the further development of the bridge span. Therefore, this paper proposes a method to determine the joint distribution of wind speed, wind direction, and air temperature actions on long-span bridges based on trivariate metaelliptical and Plackett copulas. First, the technique of establishing the trivariate joint distribution via trivariate metaelliptical and Plackett copulas is introduced. Next, the conditional joint distributions of wind speed and air temperature under the specific wind directions are derived from these. Using the concept of conditional bivariate Kendall return period (KRP) proposed in this paper, the conditional KRP isolines of wind speed and air temperature for specific wind directions are constructed. Then, conditional joint estimates of wind speed and air temperature actions for several specific wind directions are obtained using the following principle: the conditional bivariate design return period should be equal to the conditional univariate one. The method feasibility is verified by the case study of the Changtai Yangtze River Bridge in China, which is currently under construction and will be the largest cable-stayed bridge in the world. The results show that the joint actions of wind and temperature on the bridge greatly reduce as compared with the simple superposition of extreme wind and temperature actions specified in the design code. Moreover, a significant contribution of wind direction in the above joint distribution on the large-span bridge load is proved. [ABSTRACT FROM AUTHOR]

The paper represents an attempt to understand the impacts produced by the North Atlantic Oscillation on the ice cover regime of the largest coastal lake in Poland situated in the northern part of the country. The purpose of the study was to estimate the impact of the North Atlantic Oscillation on selected ice cover parameters. The study also attempts to examine other factors that may affect its significant impact on observed changes in the climate. Water temperature data are used to assess temperature conditions in aqueous ecosystems as well as determine the heat absorption capacity of these systems. This allows one to then determine cooling rates in the event of ice cover formation. The data analysis provided in the paper focuses on selected characteristics of ice cover conditions (i.e. dependent variables) including the number of days with ice and maximum ice thickness in relation to NAO index changes (i.e. independent variables) for the reference period 1960/61–2009/10. In addition, the paper divides the studied period into 10-year subperiods in order to capture the weakest and strongest phases of NAO and assess the extent to which they affect the duration of ice cover. A large increase in the mean air temperature (1.8°C) occurred in the years 1960–2010. Trendline analysis indicates that the number of days with ice cover declined by about 60 days and the maximum thickness of ice cover decreased by about 10 cm. Oceanographic research employs satellite image data in order to accurately assess human impact. Therefore, ice cover forecasts generated for consecutive winter seasons may become an important tool in this type of assessment.

In this paper, a new structure of the nonlinear proportional-integral-derivative (NPID) controller is proposed to control the air temperature at the outlet of the Computer-Aided Aerothermic System (CAAS). This technique is based on the main structure of the classical PID controller, in which the gains of the proportional, integral, and derivative actions vary at runtime according to the instantaneous error. The particularity of this method is to introduce a nonlinear function with each term of the classical PID controller. The objective of the proposed method is to stabilize the air temperature of the aerothermic system with a minimum of overshoot despite the presence of disturbances. Moreover, the proposed method is simple for practical implementation. The performance of the proposed controller (NPID) is evaluated, in terms of overshoot, settling time, and other performance indexes namely Integrated Absolute Error (IAE) and Integrated Squared Error (ISE). The simulation results are encouraging for practical implementation. The effectiveness of the proposed NPID controller is tested on a real laboratory system (CAAS). The experimental results obtained, in terms of tracking the input trajectory variation and rejecting the injected disturbance, show that the proposed technique has better performance and it is more suitable to control the system. In order to show the advantage of the new method over the others, a comparison between a conventional PID controller, a fuzzy logic controller (FLC), and the proposed controller (NPID) has been made. The results obtained indicate that the proposed technique is more effective in controlling the system (CAAS). [ABSTRACT FROM AUTHOR]

Climate change is one of the largest environmental issues causing hydroclimatological extremes such as floods, droughts, and aridity. The aim of this study is to assess the observed and projected climate changes in Baþka (Serbia). Detailed trend analyses and possible climate scenarios over Baþka has not been presented up to now. In this paper, four data sets were extracted and calculated: mean annual air temperature, mean air temperatures during the vegetation period, mean annual precipitation and total precipitation during the vegetation period. The presented parameters were obtained from the annual meteorological reports of the Republic Hydrometeorological Service of Serbia. Trend equation based on linear regression, trend magnitude according to the trend equation, and Mann-Kendall statistics have been used for trend analysis of climatic parameters. A GIS modeling of the possible climate scenario was created according to the Beijing Climate Center Climate System Model (BCC-CSM2-MR). Based on the trend equations, positive trends related to air temperature and precipitation variables are dominant. The trend magnitude shows the largest mean increase in all time series related to air temperature during the vegetation period. The highest mean precipitation increase occurs only in two time series. The Mann-Kendall statistics showed significantly positive trends in 11 cases and no changes in 9 cases. According to BCC-CSM2-MR, changes will be especially dominant in case of air temperatures. The expected changes in the total precipitation during the vegetation period show a tendency towards semiarid conditions. The presented results of observed and projected climate changes demand adaptation measures, especially from the aspect of sustainable agriculture. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying the response of different types of vegetation cover in the West Siberian Plain to temperature changes observed in recent decades. The paper analyzes trends in the series of the normalized difference vegetation index (NDVI) and air temperature in the vicinities of meteorological stations of the West Siberian Plain, which are characterized by different types of vegetation. Phases of growth (1982–1997) and stabilization (1997–2015) of NDVI values have been revealed against the background of the observed effects of global-warming slowdown, decrease of solar activity, and transition from the positive phase of the ocean-surface temperature to the negative phase in the El Niño region (ONI). It is shown that the spring months make the main contribution to variations in the seasonal NDVI value. A correlation analysis of spring NDVI and air-temperature values during the periods of NDVI growth and stabilization has been carried out. It is shown that the pattern of response of vegetation to the observed increase in temperature depends on its type and location. Thus, the relationship between the NDVI and air temperature increases in the tundra zone, decreases in very swampy areas of forest tundra and northern taiga, generally decreases in the Ob–Yenisei interfluve from forest tundra to subtaiga, and increases on the left bank of the Ob River. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of fuzzy modeling methods in the field of environmental engineering. Since predicting meteorological data is considered to be a challenging task, the current work aimed to assess the performance of various fuzzy models on temperature, solar radiation, and wind speed forecasting. The models studied were taken from the fuzzy systems literature, varying from well-established to the most recent methods. Four cases were considered: a Wang–Mendel (WM)-based fuzzy predictive model, an adaptive network fuzzy inference system (ANFIS), a fuzzy system ensemble, and patch learning (PL). The prediction systems were built from input/output data without any prior information, in a model-free approach. The ability of the models to display high performance on complex real datasets, provided by the National Observatory of Athens, was demonstrated through numerical studies. Patch learning managed to not only display a similar approximation ability to that of strong machine learning models, such as support vector machines and Gaussian processes, but also outperform them on the highly demanding problem of wind speed prediction. More accurately, as far as wind speed prediction is concerned, patch learning produced a 0.9211 root mean squared error for the training data and a value of 0.9841 for the testing data. The support vector machine provided a 0.9306 training root mean squared error and a 0.9891 testing value. The Gaussian process model resulted in a 0.9343 root mean squared error for the training data and a value of 0.9861 for the testing data. Finally, as shown by the numerical experiments, the fuzzy system ensemble exhibited the highest generalisation performance among all the intelligent models. [ABSTRACT FROM AUTHOR]

The coastal belt along the Gulf of Kachchh is home to several seaports, oil import, refining facilities, power plants, and military bases. All of them are vulnerable to the fallouts of climate change, such as sea-level rise, air and sea surface temperature, storms, and flooding. A changing climate and intense human activities severely stress the coastal environments. This paper attempts to statistically analyze the historical measurements of air temperature, sea surface temperature, sea-level rise, rainfall, and major storm events and arrive at the changes that occurred in the past using a linear regression trend line. The observed past changes are then compared with the future predictions of the same parameters as given by The Intergovernmental Panel on Climate Change. Historical Measurements of air temperature show an increase of +0.006°C/year, and future air temperature increase is in the range of +0.014-0.048°C/year. It is pertinent to note that the observed air temperature rise in the past is lower than the predicted rise in the coming century. Historical seawater temperature measurements show an increase of +0.014°C/year; the predicted growth is +0.02°C/year. Rainfall historical measurements have shown an increase of +0.9 mm/year for Saurashtra and +0.2 mm/year for Kachchh. The future increase predicted is +0.5 mm/year as per the distribution of precipitation in global climate scenarios RCP2.6 and RCP8.5. Storm events have increased over the past several decades. However, it is uncertain whether these storm changes exceed the levels expected from natural causes. Sea level rise has been of the order of +1.8 mm/year and is predicted to rise to +1.7 mm/year. The projections are supported by the trends in the observations, except for the air temperature, which is higher than found in the observations. For the other parameters, the observations and predictions are reasonably consistent. [ABSTRACT FROM AUTHOR]

A compact thermometer for air temperature based on the measurement of the speed of sound was developed at INRIM. This paper focuses on the comparison of this instrument with platinum resistance thermometers in a climatic chamber over a temperature range (−30 ÷ +55) °C, relative humidity (10 ÷ 90)%rh, and irradiation (>1 kW/m2) values similar to those of surface atmospheric conditions. Overall uncertainty values of 0.2 °C over the range from −30 °C to +30 °C, and from 0.6 °C to +55 °C, were found. Moreover, the instrument proved to be immune to irradiation errors and free from the need for temperature calibration. [ABSTRACT FROM AUTHOR]

Air temperature is a measure of temperature at different levels of the Earth's atmosphere. It is governed by many factors, including incoming solar radiation, humidity and altitude. When discussing surface air temperature, the annual atmospheric temperature range at any geographical location depends largely upon the type of biome, as measured by the Köppen climate classification. Air temperature describes the process of measuring a current local temperature for immediate or later evaluation. Datasets consisting of repeated standardized measurements can be used to assess temperature trends. Temperature varies greatly at different heights relative to Earth's surface and this variation in temperature characterizes the four layers that exist in the atmosphere. These layers include the troposphere, stratosphere, mesosphere, and thermosphere. The aim of this paper was to analyze air temperature in the Republic of North Macedonia over the span of 10 years, measured in 26 different cities. Considering the fact that North Macedonia has a decent geographical position and also the relief, the extent and direction of the mountain slopes and their height are important climatic factors which also effect on the air temperature of our country. [ABSTRACT FROM AUTHOR]

This paper presents the results of 30 years of permafrost thermal monitoring in the Tiksi area in the eastern Russian Arctic. At a stone ridge site, the mean annual temperatures in the upper 30 m of the ground have increased by 1–2.4 °C compared to the first years of observations, with trends of °C/yr. At the same time, its change was uneven. In the last 20 years, the rate of increase has increased compared with the first decade of observations. At wet tundra sites in the foothill plain, the mean annual temperatures at the top of permafrost have increased by 2.4–2.6 °C between 2005 and 2022 at rates of 0.11–0.15 °C/yr, and the active layer thicknesses have increased at rates of 0.05–0.41 cm/yr. [ABSTRACT FROM AUTHOR]

The paper provides a comparison of minimum air temperature (TN), maximum air temperature (TX), mean air temperature (Tmean) and a few derived temperature indices for Herschel Island (Qikiqtaruk) in the Yukon Territory, Canada for the periods 1899-1905 and 2008-2014. A significant increase in the TN was noted at +4.2°C, which was a larger increase than that for both Tmean (+3.7°C) and TX (+3.5°C). Air temperature increased the most in October, November, and December. In addition, the length of the frost-free season increased by 26 days and the length of the growing season increased by 25 days from the early 20th century to the early 21st century. The increase in the TN also triggered a change in the plant hardiness zone where Herschel Island is located. However, the daily air temperature range declined over the course of the study period as well as the annual total of heating degree days and the number of exceptionally cold days. No statistically significant change in the number of freeze-thaw days was found for the studied periods. [ABSTRACT FROM AUTHOR]

The parameters influencing the sea level measured with ultrasonic devices that are analyzed in this paper are the air temperature, atmospheric pressure and wind speed. As these variations are independent to each other and to the sea level, they can be removed from the measured sea level by applying a filtering algorithm based on independent component analysis (FastICA), adapted and improved for this application. The sound speed increases with temperature, so an internal temperature sensor is required to compensate for the sound-speed variation. Though this may improve the measurement accuracy, it is not enough to achieve the best results because there is a discrepancy between the internal sensor and the actual environment temperature. For high accuracy measurements, an external temperature sensor is required. In our case, we imported temperature datasets from a weather station, along with other datasets regarding atmospheric pressure and wind speed. The use of these external datasets, along with an algorithm based on principal component analysis (PCA) for error removal and the filtering algorithm based on FastICA for environmental phenomena extraction, allows us to achieve more accurate values for the Black Sea level in Constanta (2017–2020), independent of external influences. [ABSTRACT FROM AUTHOR]

Soil freeze depth variations greatly affect energy exchange, carbon exchange, ecosystem diversity, and the water cycle. Given the importance of these processes, obtaining freeze depth data over large scales is an important focus of research. This paper presents a simple empirical algorithm to estimate the maximum seasonally frozen depth (MSFD) of seasonally frozen ground (SFG) in snowy regions. First, the potential influences of driving factors on the MSFD variations were quantified in the baseline period (1981–2010) based on the 26 meteorological stations within and around the SFG region of Heilongjiang province. The three variables that contributed more than 10% to MSFD variations (i.e., air freezing index, annual mean snow depth, and snow cover days) were considered in the analysis. A simple multiple linear regression to estimate soil freeze depth was fitted (1981–2010) and verified (1975–1980 and 2011–2014) using ground station observations. Compared with the commonly used simplified Stefan solution, this multiple linear regression produced superior freeze depth estimations, with the mean absolute error and root mean square error of the station average reduced by over 20%. By utilizing this empirical algorithm and the ERA5-Land reanalysis dataset, the multi-year average MSFD (1981–2010) was 132 cm, ranging from 52 cm to 186 cm, and MSFD anomaly exhibited a significant decreasing trend, at a rate of −0.38 cm/decade or a net change of −28.14 cm from 1950–2021. This study provided a practical approach to model the soil freeze depth of SFG over a large scale in snowy regions and emphasized the importance of considering snow cover variables in analyzing and estimating soil freeze depth. [ABSTRACT FROM AUTHOR]

The paper presents a research hypothesis assumed that the air temperature affects the amount of the water consumption per capita for household purposes (indoor water use). Investigations were conducted based on daily water meter readings of several rural households located in Mszana Górna and Włostowice (Southern Poland). Owing to the double water consumption metering, it was possible to determine the daily water consumption in households, separately for household purposes and for additional purposes. In the performed analysis, the correlation between the average daily air temperature and daily water consumption per capita was tested. For this purpose, correlation coefficients were determined and a 95% confidence interval was assumed. The obtained results showed lack of a clear dependence between the tested variables. Depending on the household, correlation coefficients indicate the existence of a correlation from slight, by weak to moderate. In addition, it was tested that the growth of the air temperature by 1℃ caused an increase of the water consumption per capita in the range of 0.14 dm³·d-1·C-1·ºC-1 and 1.17 dm³·d-1·C-1·ºC-1 (Mszana Górna) and 0.41 dm3·d-1·C-1·ºC-1 and 1.78 dm³·d-1·C-1·ºC-1 (Włostowice). It can be concluded that often rapid growth of the water consumption in households in spring and summer season and the term of “water consumption per capita” used in this case, primarily concern greater water demand for additional purposes, not for residents’ household purposes. [ABSTRACT FROM AUTHOR]

With the onset of cold weather, heat transfer through the walls and especially the roofs of bird rooms, unlike in the summer period, increases significantly, which leads to a sharp decrease in warm indoor air. Therefore, in order to maintain the regulatory conditions of the ventilation system, it is reduced to a transitional mode, and then to a minimum ventilation mode. Low ventilation repeatability limits inside the building determine the minimum volume of air supplied by the ventilation system. The economic and production efficiency of poultry farming is related to the premises and climatic conditions, which can seriously affect the well-being of broilers. Heat stress contributes to behavioral, physiological and biochemical changes in broilers, which leads to economic losses. The purpose of this study is to influence the annual efficiency of the poultry house ventilation system, mainly in summer, in order to evaluate the efficiency during the reconstruction of the cooling system, that is, to improve the ventilation system of the room, as well as to give an economic assessment of waste disposal technology. Energy- and resource-saving, environmentally friendly technologies and technological tools, plastic-type recuperators, a bird droppings removal system, as well as lighting and irrigation processes were taken as the object of the study. In conducting our research, let’s use classical and special methods, including a decomposition method for analyzing the functional use of recycling technology, a logical and linguistic method for assessing the safety of nitrogen during disposal, microclimate technology, nutrition and storage. Based on the mathematical model, a computer research methodology was developed to improve the energy efficiency of the poultry house. Using a computer program, the number of LEDs (α = 200, I0 = 20 cd) for an enclosure measuring 66×12 m is N = 273 pieces, and the number of LEDs (α = 200, I0 = 20 cd) for a building measuring 78×18 m is N = 259 pieces. The design parameters of the illuminators are justified. [ABSTRACT FROM AUTHOR]

The paper focuses on analyzing the water temperature of Ombla, the largest karst spring in the Dinaric Karst. Hourly measurement data were available from January 1, 2007, at 0:00 a.m. to December 31, 2021, at 11:00 p.m. It has been established that, within that period, there were two sub-periods with different characteristic (minimum, average, and maximum) water temperatures. In the first sub-period, which lasted from January 1, 2007, at 0 a.m. to January 24, 2012, at 8 a.m., the minimum, average, and maximum water temperature values were 12.5, 13.83, and 15.0 °C, respectively. In the second sub-period (January 24, 2012, at 9 a.m. to December 31, 2021, at 11 p.m.), there was a sudden drop in the characteristic temperatures, which were 10.9, 12.91, and 14.0 °C. At the same time, a strong increasing trend of the regional air temperature is noted. It has been detected that the water temperature reacts to the air temperature with a delay of about 1 month. Due to the enormous importance of this abundant karst source, it is necessary to determine the reasons that led to the sudden drop in water temperature at the end of January 2012. [ABSTRACT FROM AUTHOR]