climatic factor
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2021 ◽  
pp. 791-794
Author(s):  
S.V. Ilvitskaya ◽  
V.A. Lobkov ◽  
T.V. Lobkova

The problem of nature protection and, at the same time, the formation of an environmentally friendly architectural space is becoming more and more important at the present time. The natural and climatic factor is a particularly significant element of the compositional and volumetric-spatial solution of individual buildings in the natural environment. The article examines the role of the local terrain in the design of an individual eco-friendly residential building.


2021 ◽  
pp. 110-119
Author(s):  
Lubov I. Kizhner ◽  
◽  
Nadezhda K. Barashkova ◽  
Olga V. Nosyreva

Author(s):  
Ilesanmi B. Oluwafemi ◽  
Moses O. Olla

Geoclimatic factor variable is one of the most important radio climatic variables in the planning of the radio links in any region. A fade margin that takes into account multipath fading has to be incorporated in the link budget in the design of terrestrial line of sight communication system. This work involves the determination of the refractivity gradient over the first 100 m above ground level in Nigeria and by using the determined refractivity gradient, the geo-climatic factor (K) was calculated for typical links in Nigeria. The Geo-climatic factor (K) for the six major cities representing each geopolitical zone in Nigeria is determined in-order to improve future planning of the radio links in the regions. Measurement of meteorological parameters for five years taken in Ikeja, Lagos (Latitude 6º27´11´´N, Longitude 3º23´44´´E), Enugu (Latitude 6º27´35.8704´´N, Longitude 7º32´56.2164´´E), Kaduna (Latitude 10º31´23´´N, Longitude 7º26´25´´E), Port Harcourt (Latitude 4º47´21´´N, Longitude 6º59´54´´E), Kano (Latitude 12º3’N,Longitude 8º32´N) and Abuja (Latitude 9º10´32´´N Longitude 7º10´50´´E) were employed to estimate the country value of K. The pressure, P(hPa), temperature, T(ºC) and the relative humidity, (%), for the six location used were taken for a period of five years (2011-2015). The value of humidity were converted to water vapour pressure, e(hPa). In processing of the data, the average values of each month collected over a period of five years was used. The monthly data was used to calculate the values of the refractivity at the ground level and at 100 m altitude. From the calculated values of refractivity,the values of the refractivity gradient of heights of 65 m and at 100 m was computed and thereafter the geo-climatic factor (K) was calculated for the six geopolitical region of the country.


2021 ◽  
Vol 13 (10) ◽  
pp. 1972
Author(s):  
Kaiwei Li ◽  
Chunyi Wang ◽  
Qing Sun ◽  
Guangzhi Rong ◽  
Zhijun Tong ◽  
...  

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.


2021 ◽  
Vol 11 (3) ◽  
pp. 1245
Author(s):  
Karel Jedlička ◽  
Jiří Valeš ◽  
Pavel Hájek ◽  
Michal Kepka ◽  
Martin Pitoňák

This manuscript aims to create large-scale calculations of agro-climatic factors from global climatic data with high granularity-climatic ERA5-Land dataset from the Copernicus Climate Change Service in particular. First, we analyze existing approaches used for agro-climatic factor calculation and formulate a frame for our calculations. Then we describe the design of our methods for calculation and visualization of certain agro-climatic factors. We then run two case studies. Firstly, the case study of Kojčice validates the uncertainty of input data by in-situ sensors. Then, the case study of the Pilsen region presents certain agro-climatic factors calculated for a representative point of the area and visualizes their time-variability in graphs. Maps represent a spatial distribution of the chosen factors for the Pilsen region. The calculated agro-climatic factors are frost dates, frost-free periods, growing degree units, heat stress units, number of growing days, number of optimal growing days, dates of fall nitrogen application, precipitation, evapotranspiration, and runoff sums together as water balance and solar radiation. The algorithms are usable anywhere in the world, especially in temperate and subtropical zones.


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