On the dynamics of distribution of the American White Butterfly, Hyphantria cunea Drury, 1973 (Lepidoptera, Arctiidae), in Ukraine regarding the annual minimal air temperatures

2018 ◽  
Vol 14 (1) ◽  
pp. 44-57
Author(s):  
S. N. Shumov
Keyword(s):  
Air Temperature ◽  
Annual Reports ◽  
Complete Elimination ◽  
Hyphantria Cunea ◽  
White American ◽  
Gis Technologies ◽  
Data Analyses ◽  
Air Temperatures ◽  
Negative Temperatures

The spatial analysis of distribution and quantity of Hyphantria cunea Drury, 1973 across Ukraine since 1952 till 2016 regarding the values of annual absolute temperatures of ground air is performed using the Gis-technologies. The long-term pest dissemination data (Annual reports…, 1951–1985; Surveys of the distribution of quarantine pests ..., 1986–2017) and meteorological information (Meteorological Yearbooks of air temperature the surface layer of the atmosphere in Ukraine for the period 1951-2016; Branch State of the Hydrometeorological Service at the Central Geophysical Observatory of the Ministry for Emergencies) were used in the present research. The values of boundary negative temperatures of winter diapause of Hyphantria cunea, that unable the development of species’ subsequent generation, are received. Data analyses suggests almost complete elimination of winter diapausing individuals of White American Butterfly (especially pupae) under the air temperature of −32°С. Because of arising questions on the time of action of absolute minimal air temperatures, it is necessary to ascertain the boundary negative temperatures of winter diapause for White American Butterfly. It is also necessary to perform the more detailed research of a corresponding biological material with application to the freezing technics, giving temperature up to −50°С, with the subsequent analysis of the received results by the punched-analysis.

scholarly journals Anthropogenic Influence on the Rhine water temperatures

2019 ◽  
Author(s):  
Alex Zavarsky ◽  
Lars Duester
Keyword(s):  
River Water ◽  
Air Temperature ◽  
Nuclear Power ◽  
Important Variable ◽  
Anthropogenic Influence ◽  
River Temperature ◽  
Air Temperatures ◽  
Long Term Trend ◽  
River Water Temperature

Abstract. River temperature is an important parameter for water quality and an important variable for physical, chemical and biological processes. River water is also used by production facilities as cooling agent.We introduce a new way of calculating a catchment-wide air temperature and regressing river temperature vs air temperatures. As a result the meteorological influence and the anthropogenic influence can be studied separately. We apply this new method at four monitoring stations (Basel, Worms, Koblenz and Cologne) along 5 the Rhine and show that the long term trend (1979–2018) of river water temperature is, next to the increasing air temperature, mostly influenced by decreasing nuclear power production. Short term changes on time scales

scholarly journals Long-Term Winter Inversion Properties in a Mountain Valley of the Western United States and Implications on Air Quality

2015 ◽  
Vol 54 (12) ◽  
pp. 2339-2352 ◽  
Author(s):  
S.-Y. Simon Wang ◽  
Lawrence E. Hipps ◽  
Oi-Yu Chung ◽  
Robert R. Gillies ◽  
Randal Martin
Keyword(s):  
Air Quality ◽  
Air Temperature ◽  
Daily Maximum ◽  
Horizontal Distance ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Narrow Valley ◽  
Northern Utah ◽  
Temperature Inversions

AbstractBecause of the geography of a narrow valley and surrounding tall mountains, Cache Valley (located in northern Utah and southern Idaho) experiences frequent shallow temperature inversions that are both intense and persistent. Such temperature inversions have resulted in the worst air quality in the nation. In this paper, the historical properties of Cache Valley’s winter inversions are examined by using two meteorological stations with a difference in elevation of approximately 100 m and a horizontal distance apart of ~4.5 km. Differences in daily maximum air temperature between two stations were used to define the frequency and intensity of inversions. Despite the lack of a long-term trend in inversion intensity from 1956 to present, the inversion frequency increased in the early 1980s and extending into the early 1990s but thereafter decreased by about 30% through 2013. Daily mean air temperatures and inversion intensity were categorized further using a mosaic plot. Of relevance was the discovery that after 1990 there was an increase in the probability of inversions during cold days and that under conditions in which the daily mean air temperature was below −15°C an inversion became a certainty. A regression model was developed to estimate the concentration of past particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5). The model indicated past episodes of increased PM2.5 concentrations that went into decline after 1990; this was especially so in the coldest of climate conditions.

Spatial and temporal variation of surface air temperature at different altitude zone in recent 30 years over Nepal

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 417-428
Author(s):  
JANAK LAL NAYAVA ◽  
SUNIL ADHIKARY ◽  
OM RATNA BAJRACHARYA
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Data ◽  
Lapse Rate ◽  
Spatial And Temporal Variation ◽  
Mountain Regions ◽  
Temperature Lapse Rate ◽  
Air Temperatures ◽  
Long Term Trend

This paper investigates long term (30 yrs) altitudinal variations of surface air temperatures based on air temperature data of countrywide scattered 22 stations (15 synoptic and 7 climate stations) in Nepal. Several researchers have reported that rate of air temperature rise (long term trend of atmospheric warming) in Nepal is highest in the Himalayan region (~ 3500 m asl or higher) compared to the Hills and Terai regions. Contrary to the results of previous researchers, however this study found that the increment of annual mean temperature is much higher in the Hills (1000 to 2000 m asl) than in the Terai and Mountain Regions. The temperature lapse rate in a wide altitudinal range of Nepal (70 to 5050 m asl) is -5.65 °C km-1. Warming rates in Terai and Trans-Himalayas (Jomsom) are 0.024 and 0.029 °C/year respectively.  

An analysis of a 34-year air temperature record from Fossil Bluff (71°S, 68°W), Antarctica

1997 ◽  
Vol 9 (3) ◽  
pp. 355-363 ◽  
Author(s):  
Stephen A. Harangozo ◽  
Steven R. Colwell ◽  
John C. King
Keyword(s):  
Air Temperature ◽  
Antarctic Peninsula ◽  
Surface Air Temperature ◽  
Temperature Record ◽  
West Antarctic ◽  
Air Temperatures ◽  
Marguerite Bay ◽  
First Time ◽  
Snow Temperature

An analysis of a long-term surface air temperature record for Fossil Bluff in the George VI Sound, West Antarctic Peninsula (WAP) documents in detail some important aspects of the climate of this area for the first time. The analysis identifies the close dependency of air temperatures on latitude in the WAP but reveals that the strength of this dependency is greatest in winter. This result along with others leads to the Fossil Bluff climate regime being characterized as ‘continental’ rather than ‘maritime’ as found further north. The WAP as a whole displays large interannual temperature variability but this is greatest in Marguerite Bay rather than the Fossil Bluff area. Evidence is also provided for secular climatic change appearing in summer throughout the WAP over the last few decades. The representativeness of existing Antarctic Peninsula annual air temperature climatologies, based mainly on snow temperature measurements, for the winter and summer periods is also noted.

scholarly journals Influence of air temperature on a glacier’s active-layer temperature

2006 ◽  
Vol 43 ◽  
pp. 285-291 ◽  
Author(s):  
V. Zagorodnov ◽  
O. Nagornov ◽  
L.G. Thompson
Keyword(s):  
Active Layer ◽  
Air Temperature ◽  
Seasonal Temperature ◽  
Temperature Variations ◽  
Surface Conditions ◽  
Tropical Glaciers ◽  
Air Temperatures ◽  
Screen Level ◽  
The Mean

AbstractSeasonal temperature variations occur in the glacier layer about 15–20 m below the surface, while at greater depths the glacier temperature depends on the long-term surface conditions. It is generally accepted that for glaciers without surface melting the temperature at 10 m depth (T10) is close to the mean annual air temperature at standard screen level (Ta), i.e. T10 =Ta. We found that this relationship is not valid for Ta above –17˚C and below –55˚C. The goal of our investigation is to find a better temperature transfer function (TTF) between Ta and temperature at the boundary of the active layer in accumulation areas of polar and tropical glaciers. Low-precision T10 temperatures from boreholes, obtained at 41 sites, are compared with air temperatures (Ta) measured in the vicinity of these sites for at least a 1 year period. We determine that when Ta falls into the temperature range –60 to –7˚C, empirical values can be approximated as T10 = 1:2Ta + 6:7. Analysis of these data suggests that high T10 occurs in the areas of the glacier that collect meltwater.

scholarly journals A Temperature Index Model to Estimate Long-term Freeze-risk of Satsuma Mandarins Grown on the Northern Coast of the Gulf of Mexico

2005 ◽  
Vol 130 (4) ◽  
pp. 500-507 ◽  
Author(s):  
R.C. Ebel ◽  
B.L. Campbell ◽  
M.L. Nesbitt ◽  
W.A. Dozier ◽  
J.K. Lindsey ◽  
...  
Keyword(s):  
Air Temperature ◽  
Cold Hardiness ◽  
Management Practices ◽  
Rating Scale ◽  
Daily Maximum ◽  
Northern Coast ◽  
Freeze Injury ◽  
Air Temperatures ◽  
The Difference

Estimates of long-term freeze-risk aid decisions regarding crop, cultivar, and rootstock selection, cultural management practices that promote cold hardiness, and methods of freeze protection. Citrus cold hardiness is mostly a function of air temperature, but historical weather records typically contain only daily maximum (Tmax) and minimum (Tmin) air temperatures. A mathematical model was developed that used Tmax and Tmin to estimate air temperature every hour during the diurnal cycle; a cold-hardiness index (CHI500) was calculated by summing the hours ≤10°C for the 500 h before each day; and the CHI500 was regressed against critical temperatures (Tc) that cause injury. The CHI500 was calculated from a weather station located within 0.1 km of an experimental grove and in the middle of the satsuma mandarin (Citrus unshiu Marc.) industry in southern Alabama. Calculation of CHI500 was verified by regressing a predicted CHI500 using Tmax and Tmin, to a measured CHI500 calculated using air temperatures measured every hour for 4 winter seasons (1999-2003). Predicted CHI500 was linearly related to measured CHI500 (r2 = 0.982). However, the slope was a little low such that trees with a CHI500 = 400, near the maximum cold-hardiness level achieved in this study, had predicted Tc that was 0.5 °C lower than measured Tc. Predicted and measured Tc were similar for nonhardened trees (CHI500 = 0). The ability of predicted Tc to estimate freeze injury was determined in 18 winter seasons where freeze injury was recorded. During injurious freeze events, predicted Tc was higher than Tmin except for a freeze on 8 Mar. 1996. In some freezes where the difference in Tc and Tmin was <0.5 °C there were no visible injury symptoms. Injury by the freeze on 8 Mar. 1996 was due, in part, to abnormally rapid deacclimation because of defoliation by an earlier freeze on 4-6 Feb. the same year. A freeze rating scale was developed that related the difference in Tc and Tmin to the extent of injury. Severe freezes were characterized by tree death (Tc - Tmin > 3.0 °C), moderate freezes by foliage kill and some stem dieback (1.0 °C ≤ Tc - Tmin ≤ 3.0 °C), and slight freezes by slight to no visible leaf injury (Tc - Tmin < 1.0 °C). The model was applied to Tmax and Tmin recorded daily from 1948 through 2004 to estimate long-term freeze-risk for economically damaging freezes (severe and moderate freeze ratings). Economically damaging freezes occurred 1 out of 4 years in the 56-year study, although 8 of the 14 freeze years occurred in two clusters, the first 5 years in the 1960s and 1980s. Potential modification of freeze-risk using within-tree microsprinkler irrigation and more cold-hardy cultivars was discussed.

scholarly journals Long-term ice-rich permafrost coast sensitivity to air temperatures and storm influence: lessons from Pullen Island, N.W.T.

2021 ◽  
Author(s):  
H. Bay Berry ◽  
Dustin Whalen ◽  
Michael Lim
Keyword(s):  
Air Temperature ◽  
The Arctic ◽  
Climate Trends ◽  
Time Step ◽  
Erosion Rates ◽  
Air Temperatures ◽  
Ground Survey ◽  
Storm Duration ◽  
Cliff Retreat

Response of erosive mechanisms to climate change is of mounting concern on Beaufort Sea coasts, which experience some of the highest erosion rates in the Arctic. Collapse of intact permafrost blocks and slumping within sprawling retrogressive thaw complexes are two predominant mechanisms that manifest as cliff retreat in this region. Using aerial imagery and ground survey data from Pullen Island, N.W.T., Canada, from 13 time points between 1947 and 2018, we observe increasing mean retreat rates from 0 ± 4.8 m/a in 1947 to 12 ± 0.3 m/a in 2018. Mean summer air temperature was positively correlated with cliff retreat over each time step via block failure (r2 = 0.08; p = 0.5) and slumping (r2 = 0.41; p = 0.05), as was mean storm duration with cliff retreat via block failure (r2 = 0.84; p = 0.0002) and slumping (r2 = 0.34; p = 0.08). These data indicate that air temperature has a greater impact in slump-dominated areas, while storm duration has greater control in areas of block failure. Increasingly heterogeneous cliff retreat rates are likely resulting from different magnitudes of response to climate trends depending on mechanism, and on geomorphological variations that prescribe occurrences of retrogressive thaw slumps.

scholarly journals About the features of the time course of the average annual air temperature in the territory of the Debed river basin (Armenia)

2020 ◽  
Vol 223 ◽  
pp. 03009
Author(s):  
Varduhi Margaryan ◽  
Gennady Tsibulskii ◽  
Ksenia Raevich
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Time Course ◽  
Data Series ◽  
Observation Data ◽  
Air Temperatures ◽  
Daily Data ◽  
Long Term Observation ◽  
Surface Air Layer

The article examines the features of the time course of the average annual air temperature in the Debed river basin in Armenia. As a starting material, we used daily data of actual observations of the temperature of the surface air layer for a year in the Debed river basin. The study was carried out at 6 meteorological stations in the Debed river basin based on long-term observation data series from 1930 to the present (2018). Analysis of the trend lines of temporal changes in air temperatures shows that at all meteorological stations currently operating on the territory of the basin, there is mainly a tendency for an increase in temperatures of annual values.

scholarly journals Long-term changes in precipitation phase in Czechia

Geografie ◽  
2019 ◽  
Vol 124 (1) ◽  
pp. 41-55
Author(s):  
Martin Hynčica ◽  
Radan Huth
Keyword(s):  
Air Temperature ◽  
Daily Precipitation ◽  
Sharp Decrease ◽  
Total Precipitation ◽  
Solid Precipitation ◽  
The Past ◽  
Air Temperatures ◽  
Long Term Changes ◽  
Precipitation Phase

Long-term changes in precipitation phase are investigated at ten stations in Czechia. Trends are calculated from 1983 to 2018 for the period between November and April. Daily SYNOP reports and daily precipitation totals are used at every station, where number and occurrence of specific codes in SYNOP report determine daily precipitation totals as solid, combined (which represents, to a large extent, category of mixed precipitation), or liquid. Thereafter, it is possible to calculate trends of all precipitation phases as well as the proportion of solid to total precipitation (S/P; in %). The average S/P trend over all Czech stations is significantly negative (−0.60%·year-1) and accompanied by a sharp decrease in solid precipitation (−1.66 mm·year-1) and an increase in combined precipitation (1.50 mm·year-1). Thus, our results show a ship of precipitation phase from solid to combined. Because of the dependence of S/P on air temperature, we suppose that the current S/P decline is a manifestation of rising air temperatures in 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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