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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]

Europe and the Mediterranean are considered climate change hot spots. This is the reason why this paper focuses on the analysis of the trends of essential climate variables in a Mediterranean country, Greece. The analyzed period is 1991–2020, and the dataset used is ERA5-Land (produced by the European Center for Medium-Range Weather Forecasts), which has global coverage and an improved resolution of ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put in evidence during the analyzed period. More specifically, the country averaged a 30-year trend of temperature of +1.5 °C, locally exceeding +2 °C, and this increasing trend is positively correlated with the distance of the areas from the coasts. Accordingly, the number of frost days has decreased throughout the country. In terms of rainfall, a major part of Greece has experienced increasing annual rainfall amounts, while 86% of the Greek area has experienced a positive trend of days with heavy rainfall (>20 mm). Finally, a multiple signal of the trend of consecutive dry days was found (statistically non-significant in the major part of Greece). [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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Meteorological observations of surface air temperature have provided fundamental data for climate change detection and attribution. However, the weather stations are unevenly distributed, and are still very sparse in remote regions. The possible sampling error is well known, but not well quantified because we are lack of the adequate and regularly distributed measurements. The high resolution of satellite land surface temperature retrieval during night time provide a nice proxy for near surface temperature as both temperatures controlled by surface longwave radiative cooling and the nocturnal temperature inversion depress land‐atmosphere turbulent exchange. The sampling error of mean value and trend were assessed by comparing station point measurements (pixel of ∼0.01°) with grid (1°) mean and national mean from 2001 to 2021. This method permits us to make the first assessment of under‐sampling error and spatial representative error on both national mean and trend of air temperature during nighttime collected at ∼2,400 weather stations over China. The sampling error in national mean temperature is more than 3°C. The under‐sampling error due to lack of observation explains two thirds and the spatial representative error due to the difference between station and grid/regional mean elevation contribute the other one third. The sampling error in trend account for one third of the national mean trend. The urban heat island effect associated with urbanization around the weather stations (spatial representative error) can explain four fifths of the sampling error in trend, which is consistent with existing studies based on air temperature collected at paired weather station. Plain Language Summary: Meteorological observations provide fundamental measurements of surface air temperature. These station‐based temperature records are usually processed to grid data sets considering the uneven distribution of meteorological stations. The gridding procedure represents a non‐uniformly sampling. In this paper, we quantified the sampling error over China using remote sensed temperature record as proxy of near surface temperature during nighttime. The causes of sampling error both in mean value and trend were both quantified. Key Points: Sampling error of mean and trend of temperature collected at weather stations at nighttime over China were investigatedThe sampling error in national mean temperature were found to be more than 3°C due to uneven distribution of weather stationsThe sampling error in temperature trend account for one thirds of the national mean temperature trend due to local urbanization [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 spatial and temporal variability of the main climatic indicators on the territory of the Volga Federal District in the 20th–21st centuries is considered. A general increasing trend in air temperature is revealed, and a heterogeneous pattern of precipitation changes is shown. The temperature variations until the end of the 21st century are analyzed on the example of Kazan using 40 CMIP6 climate models for four anthropogenic scenarios. In the paper, there is an assessment of the dynamics of agroclimatic resources on the territory of the Volga Federal District: the duration of the growing season, the sum of positive temperatures, total precipitation, and photosynthetic radiation. A correlation has been found between the temperature fluctuations in the region and the atmospheric circulation indices (NAO, AO, SCAND, and EAWR). For the territory of Tatarstan, a degree of aridity and waterlogging is evaluated using the agroclimatic indices: the Budyko's dryness index, the Selyaninov's hydrothermal coefficient, the Sapozhnikova's moisture index. It is shown that there is a tendency toward an increase in the duration of the growing season, its heat supply and aridity in the region in summer. A statistical estimation of the dependence of spring wheat yield on the agroclimatic indices on the territory of the Republic of Tatarstan is given. [ABSTRACT FROM AUTHOR]

The overview of papers dealing with the analysis of current and future climate change on the territory of Russia and their impact on the crop productivity is presented. Using the reanalysis data for 1950–2020, trends in air temperature and precipitation are estimated for different regions of Russia. A correlation was found between changes in temperature and atmospheric circulation indices. [ABSTRACT FROM AUTHOR]