CORRELATION COMMUNICATION BETWEEN METEOROLOGICAL PARAMETERS AT EXTREME VALUES OF MAXIMUM AIR TEMPERATURES

2020 ◽  
pp. 101-112
Author(s):  
S.V. Savchuk ◽  
V.E. Timofeev ◽  
O.A. Shcheglov ◽  
V.A. Artemenko ◽  
I.L. Kozlenko
Keyword(s):  
Air Temperature ◽  
Meteorological Parameters ◽  
Extreme Values ◽  
Daily Temperature ◽  
Sea Level Pressure ◽  
Maximum Daily Temperature ◽  
The North ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

The object of the study is the maximum daily air temperature during the months of the year over 1991-2016 by the data of 186 meteorological stations of Ukraine. Extreme values of the maximum daily temperature equal to or exceeded their 95th (Tmax95p and above, ºС) percentile were taken as extreme. The article sets the dates (137 cases) of extreme values of maximum air temperature on more than 60 % of the territory. For these dates, 13 meteorological parameters were selected: average, minimum, and maximum air temperatures; average, minimum and maximum relative humidity; station and sea-level pressure; average, maximum (from 8 synoptic hours) wind speed; rainfall; height of snow cover. The purpose of this work is to determine the correlation coefficient (K), in particular, statistically significant (K≤-0.6, K≥0.6), on these dates between selected meteorological parameters at 186 meteorological stations of Ukraine for 1991-2013. The density of the cases of statistically significant dependence between the meteorological parameters in extremely warm days in separate seasons is determined. In extremely warm days, meteorological parameters and areas with statistically significant correlations at K≤-0.6 were detected: T and F (focally in southern and some western regions with significant density) − in winter; T and F (with the highest density ubiquitous or almost ubiquitous), P and V (in a large number of regions, usually west or right-bank, but with less frequency) − in the transition seasons, and in the autumn between − T and F (in the south with smaller density) and P and F (in some areas of the north, northwest, west, lower east). In all seasons, such a correlation between other meteorological parameters had a focal distribution, usually with a smaller density. In these days, a focal distribution with a small frequency of dependencies at K≥0.6 was found between the meteorological parameters detected (F and V in transition seasons, T and F in winter), except for similar ones. However, such dependence is observed between T and V in some regions in winter and autumn and in some areas of south, southeast, east with a smaller density. The study of the maximum daily temperature is relevant, because from the level of natural hydrometeorological phenomena it is accompanied by dangerous phenomena, negatively affecting the weather dependent industries.

scholarly journals Trends of Changes of Maximum Air Temperature in Ukraine as an Impact Factor on Population Health

2020 ◽  
Keyword(s):  
Population Health ◽  
Air Temperature ◽  
Thermal Regime ◽  
Climate Changes ◽  
System Analysis ◽  
Global Climate ◽  
Maximum Temperature ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

Purpose. The aim of this research is detection of trends of changes (according to fact and scenario data) of extreme air temperature as a component of thermal regime in different regions of Ukraine because of global climate change. Methods. System analysis, statistical methods. Results. Time distribution of maximum air temperature regime characteristics based on results of observations on the stations located in different regions of Ukraine during certain available periods: Uzhgorod (1946-2018), Kharkiv (1936-2005), Оdessа (1894-2005), аnd also according to scenarios of low (RCP2.6), medium (RCP4.5) and high (RCP8.5) levels of greenhouse gases emissions. Meanwhile, air temperature ≥ 25°С was considered high (days with maximum temperature within 25,0-29,9°С are hot), ≥ 30°С was considered very high (days with such temperature are abnormaly hot). Trends of changes of extreme air temperatures were identified as a component of thermal regime in different regions of Ukraine within global climate changes. Dynamics of maximum air temperature and its characteristics in ХХ and beginning of ХХІ centuries were researched. Expected time changes of maximum air temperature and number of days with high temperature during 2021-2050 were analyzed by RCP2.6, RCP4.5 and RCP8.5 scenarios. There were identified the highest day air temperatures possible once in a century and also possibility of maximum day temperature more than 30°С by RCP4.5 scenario. Well-timed prediction of climate changes will help evaluate their impact on human and natural systems which will be useful for development and taking preventive measures towards minimization of negative influence of such changes. Conclusions. Processes of climate warming in Ukraine are activating. There was determined a strong trend on increasing of average maximum of air temperature in winter with speed 0.17-0,39 degrees centigrade/10 years. According to climatic norm this index mainly increased mostly (up to 3,3 degrees centigrade) in January in North-East of the country. In future such anomalies will grow. Determination of correlation between climate and health is the base for taking protective measures against perils for population health connected with climate.

scholarly journals Daily Minimum and Maximum Air Temperature in Poland in the Years 1951–2005

2009 ◽  
Vol 2 (1) ◽  
pp. 35-56 ◽  
Author(s):  
Marek Kejna ◽  
Andrzej Araźny ◽  
Rafał Maszewski ◽  
Rajmund Przybylak ◽  
Joanna Uscka-Kowalkowska ◽  
...  
Keyword(s):  
Air Temperature ◽  
North Atlantic ◽  
Daily Maximum ◽  
Grid Data ◽  
The North ◽  
Nao Index ◽  
Air Temperatures ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
Maximum Air Temperature

Abstract In this study grid data of daily maximum and minimum air temperatures taken from the NCEP/NCAR reanalysis for the territory of Poland for the years 1951-2005 have been used as a basis for an analysis of the spatial distribution of daily maximum and minimum air temperature, the frequency of characteristic days and the variability of these parameters in the period analysed. The results obtained were then compared to the variability in atmospheric circulation in Europe, described by the North Atlantic Oscillation (NAO) index.

scholarly journals Regionalization of Ukraine based on the influence of extreme values of maximum air temperature during warm and cold periods of the year

2018 ◽  
pp. 46-56
Author(s):  
S. V. Savchuk ◽  
N. N. Yuvchenko ◽  
V. E. Timofeev
Keyword(s):  
Atmospheric Circulation ◽  
Air Temperature ◽  
Extreme Values ◽  
Warm Period ◽  
Synoptic Situation ◽  
The South ◽  
Cool Period ◽  
Near Surface ◽  
Average Maximum ◽  
Maximum Air Temperature

Based on the data of maximum daily near-surface air temperature (MSAT) taken from 186 meteorological stations of Ukraine the parameters of extremality with relation to maximum air temperature for different time periods as well as deviations between them during cold and warm periods of the year were calculated. Regionalization of Ukraine was carried out in order to identify climate-vulnerable regions by means of comparison, overlapping and match of the areas with the highest values towards selected extremality thresholds. The conclusion about general increase in extremality over the last decade with relation to a climatic standard is made, the areas with the greatest vulnerability are outlined, and the areas with increase in extremality degree are identified. During both periods of the year certain areas in the southern, central and eastern parts of Ukraine are considered, based on maximum air temperature data, as the most vulnerable ones. During both periods of the year over 2001-2010, as compared to 1991-2000, increase of recurrence of extreme values of average maximum of air temperature was observed: in March and December during the cold period and also from May to July, and in case of EHMP event – in August. Distribution of maximum air temperature of the EHMP category, in comparison to the category of extreme values, specifies and localizes the regions with the greatest vulnerability. The areas of the highest vulnerability during the cool period comprise the extreme west, south-western and southern regions and during the warm period – southern, south-eastern regions and the extreme east of Ukraine. The spatial distribution of the extreme values of the MSAT for the warm period has a predominantly meridional orientation. During both periods of the year regions in the south (areas of Black Sea region, Crimea, boundary subregions in the south) areas in the east and center of Ukraine affected by extreme MSAT values are the most vulnerable; in 2010-2014 this influence intensified. Increase in the vulnerability based on the maximum air temperature occurs on the background of certain changes in the atmospheric circulation, under conditions of anticyclonic fields prevalence throughout the year along with increase of the temporal exposure to the elementary synoptic process. On the other hand, the aforementioned increase of recurrence of extreme hydrometeorological phenomena is a consequence of sharp changes of synoptic situation, which is especially the case after a period of settled weather. The conclusion that atmospheric circulation is a main agent responsible for extreme weather and that it is not studied completely so far was made.

scholarly journals Ablation and Heat Balance of the Yukikabe Snow Patch in the Daisetsu Mountains, Hokkaido, Japan

1984 ◽  
Vol 5 ◽  
pp. 122-126 ◽  
Author(s):  
A. Sato ◽  
S. Takahashi ◽  
R. Naruse ◽  
G. Wakahama
Keyword(s):  
Latent Heat ◽  
Air Temperature ◽  
Heat Balance ◽  
Meteorological Parameters ◽  
Heat Sources ◽  
Sensible Heat ◽  
Net Radiation ◽  
Ice Caps ◽  
Air Temperatures ◽  
The Heat Balance

A good correlation was found between the ablation of snow and degree day index (cumulative values of positive daily mean air temperature) during the summer of 1978 on the Yukikabe snow patch in the Daisetsu mountains, central Hokkaido. The volume change of the snow patch in the ablation season of any year can hence be estimated from air temperature using this relationship. Each of the heat-balance terms controlling the ablation is evaluated separately by using empirical equations and assumed values for meteorological parameters at the snow patch. Triangular diagrams are constructed in order to illustrate the relative contributions of sensible heat, latent heat, and net radiation, the main three heat sources. A higher contribution from sensible and latent heat is found for the snow patches of Japan than for many glaciers and ice caps elsewhere. This may be due to higher mid-summer air temperatures than in other glaciated parts of the world.

Analysis of Changes in the Natural and Climatic Conditions of the Functioning of the Construction Industry (Operation of Buildings and Structures) in the Region

2018 ◽  
Vol 931 ◽  
pp. 1031-1036
Author(s):  
Boris A. Ashabokov ◽  
Alexander V. Shapovalov ◽  
Alla A. Tashilova
Keyword(s):  
Construction Industry ◽  
Extreme Values ◽  
Climatic Conditions ◽  
Daily Maximum ◽  
Climatic Zones ◽  
Air Temperatures ◽  
Average Maximum ◽  
European Part Of Russia ◽  
Different Seasons ◽  
Southern Russia

The manifestations of climatic changes on the territory of the south of the European part of Russia are considered. The estimates for the changes in the seasonal and annual average, maximum and minimum air temperatures, in the seasonal and annual sum of precipitation, daily maximum precipitation as well as the dynamics of the number of their extreme values ​​in different climatic zones of southern Russia and in different seasons are obtained. Possible effects of climate change on the functioning of the construction industry in different climatic zones of the region are considered.

DETERMINATION OF THE CORRELATION BETWEEN INDIVIDUAL METEOROLOGICAL VALUES AT THE BEGINNING OF THE DEPOSITION OF ICE ON THE TERRITORY OF UKRAINE BY THE MONTHS OF THE COLD PERIOD OF THE YEAR DURING 2001-2013 AND THEIR SPATIAL DISTRIBUTION

2019 ◽  
pp. 140-151
Author(s):  
S.I. Pyasetska ◽  
N.P. Grebenyuk ◽  
S.V. Savchuk
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Sea Level ◽  
Meteorological Parameters ◽  
Cold Period ◽  
Sea Level Pressure ◽  
Average Maximum ◽  
Average Relative Humidity ◽  
Maximum Minimum

The article presents the results of the study of the determination of the correlation connection between a number of meteorological values at the beginning of the deposition of ice on the wires of a standard ice-cream machine in certain months of the cold period of the year on the territory of Ukraine during 2001-2013. The research was conducted for 3 winter months, as well as for March and November. The pair of meteorological parameters have been determined at the beginning of the deposition of ice that have a statistically significant correlation coefficient and a spatial-temporal distribution of the distribution in certain months across the territory of Ukraine has been obtained. The most common variant of the statistically significant connection between individual meteorological parameters was the connection between the temperature of the water column (average, maximum, minimum) and relative humidity of air (average, maximum). Thus, for almost all months studied, a statistically significant correlation between the temperature of the vapor (average, maximum, minimum) and relative humidity of air (average, maximum) was established. For the winter months, the correlation coefficient of this connection was positive, and for March and November, it was negative. A widespread version of a statistically significant connection was the relationship between the air temperature (average, maximum, minimum) and the height of the snow cover. This connection for the months studied turned out to be negative. The variants of negative statistically significant connection between average wind speed and average relative humidity of air (January-February, December), average and maximum wind speed and sea-level pressure (November), and also between daily amount precipitation and snow (March), daily rainfall and wind speed (average, maximum), and pressure at sea level (November). During the months of the cold period of the year, statistically significant connections between the air temperature (average, maximum) and pressure at sea level (November), wind speed (average, maximum) and average humidity (January, December), pressure on sea levels and average relative humidity (March). Also, there were isolated cases of statistically significant correlation between snow and sea level pressure (December). The most frequently statistically significant connections between meteorological values at the dates of deposition of ice on the wires of a standard icing machine were observed at stations in the central, northeastern, eastern and separate southern regions.

Climate Change and the Evolution of Phytoplankton (Abundance) in Some Lagoons on the São Miguel Island – Azores

2021 ◽  
Author(s):  
Maria Meirelles
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
North Atlantic ◽  
Meteorological Parameters ◽  
Second Phase ◽  
Subtropical Anticyclone ◽  
The North ◽  
Phytoplankton Communities ◽  
Average Annual Temperature ◽  
The North Atlantic

<p>Climate change cause large, long-term impacts on human well-being and adds more pressure to terrestrial and marine ecosystems. The archipelago of the Azores is located in the subtropical region of the North Atlantic and is therefore highly influenced by the North Atlantic Subtropical Anticyclone. As it is an almost stationary high pressure system, whose development and orientation determine the nature and characteristics of the air masses that reach the region. The motivation for this research has two phases; the first was to study the effects of some meteorological parameters (temperature, radiation, wind speed, humidity, precipitation, evaporation, tank temperature and tank level) for the period 2010-2012, on the biodiversity of phytoplankton communities in relation to the abundance of these organisms in the lagoons of Fogo, Furnas, and Sete Cidades of the island of São Miguel - Azores, for the period 2010-2012, using an analysis in Principal  Components, which will allow correlating the meteorological parameters and the abundance of phytoplankton. The phytoplankton and meteorological community data were obtained from the website of the Regional Secretariat for the Environment and Climate Change of the Azores Government. In a second phase, the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis of the ERA5 project (ECMWF Re-Analyzes) was used for the 1979-2019 observation period and for the Azores region. For this region, the deviations of the surface air temperature, average annual precipitation and climatological extremes were calculated, this referring to the maximum number of consecutive days with precipitation <1 mm, and also, the number of tropical nights using the ERA5 reanalysis series in the period 1979-2019 with reference to 1961-1990. Projections were also estimated up to 2100 and according to scenarios RCP 2.6, 4.5 and 8.5 for the referred parameters. Finally, variations for the end of the century (2071-2100) were estimated with reference to the most recent situation of 1991-2020.</p><p>The thermal balance of a lagoon is associated with climatic and meteorological conditions. Much of the biological processes in the lagoons are directly affected by thermal changes in the water, and therefore, indirectly affected by climatic variation. Understanding the interaction between the lagoon-atmosphere system is important to predict the consequences of the effects of climate change on the abundance of phytoplankton. In this study, a positive correlation was verified between precipitation and abundance of Bacillariophyta, Dinophyta and Cryptophyta. From the calculations performed, the average of the models results in an increase in the maximum number of consecutive days with low rainfall (<1mm) from + 0.2 to 4.8 days / year until the year 2100, with a lower abundance of these algae being expected. On the other hand, Cyanophyta, Chlorophyta and Chrisophyta are well correlated with high values ​​of air temperature, lagoon water temperature and solar radiation. Thus, it is estimated an increase in the abundance of these algae, due to the forecasts of several models, that point to an increase in the average annual temperature in this region between 1 and 3 K until the year 2100, with reference to the period from 1961 to 1990.</p>

scholarly journals Wet-Bulb Temperature from Relative Humidity and Air Temperature

2011 ◽  
Vol 50 (11) ◽  
pp. 2267-2269 ◽  
Author(s):  
Roland Stull
Keyword(s):  
Gene Expression ◽  
Relative Humidity ◽  
Sea Level ◽  
Air Temperature ◽  
Mean Absolute Error ◽  
Gene Expression Programming ◽  
Absolute Error ◽  
Sea Level Pressure ◽  
Air Temperatures ◽  
Low Humidity

AbstractAn equation is presented for wet-bulb temperature as a function of air temperature and relative humidity at standard sea level pressure. It was found as an empirical fit using gene-expression programming. This equation is valid for relative humidities between 5% and 99% and for air temperatures between −20° and 50°C, except for situations having both low humidity and cold temperature. Over the valid range, errors in wet-bulb temperature range from −1° to +0.65°C, with mean absolute error of less than 0.3°C.

scholarly journals Spatiotemporal variability of air temperatures in Central Serbia from 1949 to 2018

Időjárás ◽  
2021 ◽  
Vol 125 (2) ◽  
pp. 229-253
Author(s):  
Nikola R. Bačević ◽  
Nikola M. Milentijević ◽  
Aleksandar Valjarević ◽  
Ajša Gicić ◽  
Dušan Kićović ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Air Temperature ◽  
Minimum Time ◽  
Spatiotemporal Variability ◽  
Air Temperatures ◽  
Gis Tools ◽  
Average Maximum ◽  
Annual Time Series ◽  
The Republic

The paper presents trends for three categories of variables: average annual, average maximum and average minimum air temperatures. Data was provided by the meteorological yearbooks of the Republic Hydrometeorological Service of Serbia. The main goal of this paper is to detect possible temperature trends in Central Serbia. The trend equation, trend magnitude, and Mann-Kendall non-parametric test were used in the analysis of climate parameters. The used statistical methods were supplemented by GIS numerical analysis, which aimed to analyze the spatial distribution of isotherms from 1949 to 2018. The obtained results indicate that out of the 72 analyzed time series, an increase in air temperature is dominant in 61 time series, while 11 time series show no changes. The highest increase was recorded in the average maximum time series (4.2 °C), followed by an increase of 3.5°C in average maximum air temperatures. The highest increase in the average annual time-series was 3.0 °C. The lowest increases in air temperature were recorded in the average minimum time series (0.1 and 0.2 °C). In two average minimum time series a decrease in average air temperatures was identified (-0.6 and -0.4 °C. The application of GIS tools indicates the existence of interregional differences in the arrangement of isotherms, leaded by the orography of the terrain. In the spatial distribution of the analyzed variables, "poles of heat" and "poles of cold" stand out, and the influence of the urban heat island is evident (especially in the case of the urban agglomeration of Belgrade). The manifested spatial patterns of air temperature need to be further examined and the correlation with possible causes need to be determined. For these reasons, the paper provides a solid basis for studying the climate of this area in the future, as it provides insight into climate dynamics over the past decades.

scholarly journals GPRChinaTemp1km: a high-resolution monthly air temperature dataset for China (1951–2020) based on machine learning

2021 ◽  
Author(s):  
Qian He ◽  
Ming Wang ◽  
Kai Liu ◽  
Kaiwen Li ◽  
Ziyu Jiang
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Air Temperature ◽  
Spatial Interpolation ◽  
Gaussian Process Regression ◽  
Temperature Data ◽  
Air Temperatures ◽  
Maximum Air Temperature ◽  
Maximum Minimum

Abstract. An accurate spatially continuous air temperature dataset is crucial for multiple applications in environmental and ecological sciences. Existing spatial interpolation methods have relatively low accuracy and the resolution of available long-term gridded products of air temperature for China is coarse. Point observations from meteorological stations can provide long-term air temperature data series but cannot represent spatially continuous information. Here, we devised a method for spatial interpolation of air temperature data from meteorological stations based on powerful machine learning tools. First, to determine the optimal method for interpolation of air temperature data, we employed three machine learning models: random forest, support vector machine, and Gaussian process regression. Comparison of the mean absolute error, root mean square error, coefficient of determination, and residuals revealed that Gaussian process regression had high accuracy and clearly outperformed the other two models regarding interpolation of monthly maximum, minimum, and mean air temperatures. The machine learning methods were compared with three traditional methods used frequently for spatial interpolation: inverse distance weighting, ordinary kriging, and ANUSPLIN. Results showed that the Gaussian process regression model had higher accuracy and greater robustness than the traditional methods regarding interpolation of monthly maximum, minimum, and mean air temperatures in each month. Comparison with the TerraClimate, FLDAS, and ERA5 datasets revealed that the accuracy of the temperature data generated using the Gaussian process regression model was higher. Finally, using the Gaussian process regression method, we produced a long-term (January 1951 to December 2020) gridded monthly air temperature dataset with 1 km resolution and high accuracy for China, which we named GPRChinaTemp1km. The dataset consists of three variables: monthly mean air temperature, monthly maximum air temperature, and monthly minimum air temperature. The obtained GPRChinaTemp1km data were used to analyse the spatiotemporal variations of air temperature using Theil–Sen median trend analysis in combination with the Mann–Kendall test. It was found that the monthly mean and minimum air temperatures across China were characterized by a significant trend of increase in each month, whereas monthly maximum air temperature showed a more spatially heterogeneous pattern with significant increase, non-significant increase, and non-significant decrease. The GPRChinaTemp1km dataset is publicly available at https://doi.org/10.5281/zenodo.5112122 (He et al., 2021a) for monthly maximum air temperature, at https://doi.org/10.5281/zenodo.5111989 (He et al., 2021b) for monthly mean air temperature and at https://doi.org/10.5281/zenodo.5112232 (He et al., 2021c) for monthly minimum air temperature.

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