scholarly journals Diurnal Variability of Soil and Air temperature as a function of time and depth, A case study of the cold wave that hit Zawia region during the period 1-5 February 1999

2019 ◽  
pp. 142-165
Author(s):  
Abdelfatah Hadi Shibani
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Plant Protection ◽  
Temperature Variability ◽  
Cold Wave ◽  
Diurnal Variability ◽  
Weather Situation ◽  
Hourly Data ◽  
Hourly Variation

Soil temperature is one of the important variables in agricultural studies, which is necessary to be measured and analyze. There are some major challenges facing a lot of agricultural studies focus on soil temperature in Libya, such as, the soil temperature is measured only at Agro meteorological stations in the country, the lack of stations, the measurement of soil temperature is a cumbersome business and not as simple as air temperature be noted by single thermometer, Separate thermometers are required to measure the temperature of the soil at different depths, the installation of thermometer sensor correctly in the soil is another very complicated technical matter. However, in Libya there are no enough studies into the pattern of hourly variation in soil temperature over twenty-four hours due to the lack of such measurements at agricultural lands. So that, this attempt has been made to diagnose the behavior of soil temperature and air temperature as a case study, This work was carried out by using the daily and hourly data recorded for the temperature in the standard depths of soil (5,10,20,30,50,100 cm), and the surface air temperature at heights of (5, 10, 15, 50, 100, 150, 200 cm), Data were measured, Reported and collected every three hours interval during the period from 01 to 05 February 1999, at Zawia Agro-Meteorological Station where the location of the station was under the effect of cold wave. The data were measured on a daily basis at 0000, 0300, 0600, 0900, 1200, 1500, 1800, 2100 UTC. The correlation coefficient between the hourly soil temperature and hourly air temperature at certain depths and heights were calculated using the Pearson’s Formula, then the matrix of correlation factors have been derived, The vertical profile for the hourly variation of temperature in the layer between 100 cm under the surface of soil and 200 cm above the surface of soil have been described, Graphs and tables were done to show more explanation. The analysis of the observation shows that soil temperature variability decreases with depth, the highest temperature variability in top soil, and the lowest one is deeper than 50 cm. These results were affected due to the prevailing weather situation because at night time there is no enough solar radiation and the ambient temperature is lower than soil temperature. As a result, the soil temperature transferred heat from soil to atmosphere above. In addition, the low thermal conductivity of the soil is also one important factor that affects heat storage. These results demonstrated the importance of monitoring the soil temperature as an important element for agricultural studies. The results of the present paper could fill in some of the gap related to the soil temperature studies in Libya, and can be used for planning agronomic and plant protection practices.

scholarly journals Impact of Subsurface Temperature Variability on Surface Air Temperature Variability: An AGCM Study

2008 ◽  
Vol 9 (4) ◽  
pp. 804-815 ◽  
Author(s):  
Sarith P. P. Mahanama ◽  
Randal D. Koster ◽  
Rolf H. Reichle ◽  
Max J. Suarez
Keyword(s):  
Surface Temperature ◽  
Soil Temperature ◽  
Air Temperature ◽  
Seasonal Cycle ◽  
Surface Air Temperature ◽  
Temperature Variability ◽  
Climate System ◽  
Boreal Summer ◽  
Temperature Anomalies ◽  
Subsurface Soil

Abstract Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies in the subsurface soil. The subsurface soil temperature (and the associated ground heat content) has significant memory—the dissipation of a temperature anomaly may take weeks to months—and thus subsurface soil temperature may contribute to the low-frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses three long-term AGCM experiments to isolate the contribution of subsurface soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of Atmospheric Model Intercomparison Project (AMIP)-type simulations in which the subsurface soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the subsurface soil temperature to the rest of the climate system is disabled; that is, at each grid cell, the local climatological seasonal cycle of subsurface soil temperature (as determined from the first experiment) is prescribed. Finally, a climatological seasonal cycle of sea surface temperature (SST) is prescribed in the third experiment. Together, the three experiments allow the isolation of the contributions of variable SSTs, interactive subsurface soil temperature, and chaotic atmospheric dynamics to meteorological variability. The results show that allowing an interactive subsurface soil temperature does, indeed, significantly increase surface air temperature variability and memory in most regions. In many regions, however, the impact is negligible, particularly during boreal summer.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

scholarly journals Root-Associated Mycobiomes of Common Temperate Plants (Calluna vulgaris and Holcus lanatus) Are Strongly Affected by Winter Climate Conditions

2021 ◽  
Author(s):  
Mathilde Borg Dahl ◽  
Derek Peršoh ◽  
Anke Jentsch ◽  
Jürgen Kreyling
Keyword(s):  
Soil Temperature ◽  
Plant Species ◽  
High Throughput Sequencing ◽  
Calluna Vulgaris ◽  
Absolute Temperature ◽  
Snow Accumulation ◽  
Temperature Variability ◽  
Holcus Lanatus ◽  
Soil Frost ◽  
Winter Climate

AbstractWinter temperatures are projected to increase in Central Europe. Subsequently, snow cover will decrease, leading to increased soil temperature variability, with potentially different consequences for soil frost depending on e.g. altitude. Here, we experimentally evaluated the effects of increased winter soil temperature variability on the root associated mycobiome of two plant species (Calluna vulgaris and Holcus lanatus) at two sites in Germany; a colder and wetter upland site with high snow accumulation and a warmer and drier lowland site, with low snow accumulation. Mesocosm monocultures were set-up in spring 2010 at both sites (with soil and plants originating from the lowland site). In the following winter, an experimental warming pulse treatment was initiated by overhead infrared heaters and warming wires at the soil surface for half of the mesocosms at both sites. At the lowland site, the warming treatment resulted in a reduced number of days with soil frost as well as increased the average daily temperature amplitude. Contrary, the treatment caused no changes in these parameters at the upland site, which was in general a much more frost affected site. Soil and plant roots were sampled before and after the following growing season (spring and autumn 2011). High-throughput sequencing was used for profiling of the root-associated fungal (ITS marker) community (mycobiome). Site was found to have a profound effect on the composition of the mycobiome, which at the upland site was dominated by fast growing saprotrophs (Mortierellomycota), and at the lowland site by plant species-specific symbionts (e.g. Rhizoscyphus ericae and Microdochium bolleyi for C. vulgaris and H. lanatus respectively). The transplantation to the colder upland site and the temperature treatment at the warmer lowland site had comparable consequences for the mycobiome, implying that winter climate change resulting in higher temperature variability has large consequences for mycobiome structures regardless of absolute temperature of a given site.

Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models

2021 ◽  
Vol 185 ◽  
pp. 106158
Author(s):  
Maryam Bayatvarkeshi ◽  
Suraj Kumar Bhagat ◽  
Kourosh Mohammadi ◽  
Ozgur Kisi ◽  
M. Farahani ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Temperature ◽  
Air Temperature ◽  
Climatic Conditions ◽  
Learning Models ◽  
Machine Learning Models

scholarly journals Protection possibilities of agricultural minor crops in the European Union: a case study of soybean, lupin and camelina

2019 ◽  
Vol 127 (1) ◽  
pp. 55-61 ◽  
Author(s):  
Ewa Matyjaszczyk
Keyword(s):  
European Union ◽  
Active Substance ◽  
Plant Protection ◽  
Plant Protection Products ◽  
Agricultural Crops ◽  
The European Union ◽  
Member States ◽  
Minor Crops ◽  
Chemical Products

Abstract In the central part of the European Union soybean, lupin and camelina are minor agricultural crops. The paper presents analysis of plant protection products availability for those crops in Austria, Belgium, Czech Republic, Germany, Holland, Hungary, Poland and Slovakia. Data from year 2019 show that availability of products is generally insufficient. For camelina in some countries, there are no chemical products available whatsoever. For lupin and soybean, there are not always products available to control some pest groups. However, the products on the market differ significantly among the member states. The results show that in protection of soybean, lupin and camelina, no single active substance is registered for the same crop in all the analysed member states. In very numerous cases, active substance is registered in one out of eight analysed member states only.

Interval of days required for determining efficient relations between climatic factors and cotton flower and boll production

2002 ◽  
Vol 82 (3) ◽  
pp. 499-506 ◽  
Author(s):  
Zakaria M Sawan ◽  
Louis I Hanna ◽  
Willis L McCuistion
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Surface Soil ◽  
Cultural Practices ◽  
Agricultural Research ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
Field Trials ◽  
Cotton Production ◽  
Surface Soil Temperature

The cotton plant (Gossypium spp.) is sensitive to numerous environmental factors. This study was aimed at predicting effects of climatic factors grouped into convenient intervals (in days) on cotton flower and boll production compared with daily observations. Two uniformity field trials using the cotton (G. barbadense L.) cv. Giza 75 were conducted in 1992 and 1993 at the Agricultural Research Center, Giza, Egypt. Randomly chosen plants were used to record daily numbers of flowers and bolls during the reproductive stage (60 days). During this period, daily air temperature, temperature magnitude, evaporation, surface soil temperature, sunshine duration, humidity, and wind speed were recorded. Data, grouped into intervals of 2, 3, 4, 5, 6, and 10 d, were correlated with cotton production variables using regression analysis. Evaporation was found to be the most important climatic variable affecting flower and boll production, followed by humidity and sunshine duration. The least important variables were surface soil temperature at 0600 and minimum air temperature. The 5-d interval was found to provide the best correlation with yield parameters. Applying appropriate cultural practices that minimize the deleterious effects of evaporation and humidity could lead to an important improvement in cotton yield in Egypt. Key words: Cotton, flower production, boll production, boll retention

Spatiotemporal computing of cold wave characteristic in recent 52 years: a case study in Guangdong Province, South China

2015 ◽  
Vol 79 (2) ◽  
pp. 1257-1274 ◽  
Author(s):  
Wei Liu ◽  
Si-yu Huang ◽  
Dan Li ◽  
Chong-yang Wang ◽  
Xia Zhou ◽  
...  
Keyword(s):  
South China ◽  
Guangdong Province ◽  
Cold Wave ◽  
Wave Characteristic
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