scholarly journals An observation-based assessment of the influences of air temperature and snow depth on soil temperature in Russia

2014 ◽  
Vol 9 (6) ◽  
pp. 064026 ◽  
Author(s):  
Hotaek Park ◽  
Artem B Sherstiukov ◽  
Alexander N Fedorov ◽  
Igor V Polyakov ◽  
John E Walsh
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Snow Depth

scholarly journals Effect of snow cover on soil frost penetration

2017 ◽  
Vol 47 (4) ◽  
pp. 287-297 ◽  
Author(s):  
Jaroslav Rožnovský ◽  
Jáchym Brzezina
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Major Effect ◽  
Soil Frost ◽  
Temperature Range ◽  
Soil Temperatures ◽  
Frost Penetration ◽  
Actual Height

AbstractSnow cover occurrence affects wintering and lives of organisms because it has a significant effect on soil frost penetration. An analysis of the dependence of soil frost penetration and snow depth between November and March was performed using data from 12 automated climatological stations located in Southern Moravia, with a minimum period of measurement of 5 years since 2001, which belong to the Czech Hydrometeorological institute. The soil temperatures at 5 cm depth fluctuate much less in the presence of snow cover. In contrast, the effect of snow cover on the air temperature at 2 m height is only very small. During clear sky conditions and no snow cover, soil can warm up substantially and the soil temperature range can be even higher than the range of air temperature at 2 m height. The actual height of snow is also important – increased snow depth means lower soil temperature range. However, even just 1 cm snow depth substantially lowers the soil temperature range and it can therefore be clearly seen that snow acts as an insulator and has a major effect on soil frost penetration and soil temperature range.

scholarly journals Spatially distributed water-balance and meteorological data from the rain-snow transition, southern Sierra Nevada, California

2018 ◽  
Author(s):  
Roger Bales ◽  
Erin Stacy ◽  
Mohammad Safeeq ◽  
Xiande Meng ◽  
Matthew Meadows ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Temperature ◽  
Sierra Nevada ◽  
Air Temperature ◽  
Snow Depth ◽  
Meteorological Data ◽  
Sensor Nodes ◽  
Subsurface Water ◽  
Spatially Distributed

Abstract. We strategically placed spatially distributed sensors to provide representative measures of changes in snowpack and subsurface water storage, plus the fluxes affecting these stores, in a set of nested headwater catchments. We present eight years of hourly snow-depth, soil-moisture and soil-temperature data, and 14 years of quarter-hourly streamflow and meteorological data that detail water-balance processes at the rain-snow transition at Providence Creek in the southern Sierra Nevada, California. Providence Creek is the co-operated long-term study run by the Southern Sierra Critical Zone Observatory and the U.S.D.A. Forest Service Pacific Southwest Research Station's Kings River Experimental Watersheds. The 4-km2 montane Providence Creek catchment spans the current rain-snow transition elevation of 1500–2100 m. Two meteorological stations bracket the high and low elevations of the catchment, measuring air temperature, relative humidity, solar radiation, precipitation, wind speed and direction, and snow depth, and at the higher station, snow water equivalent. Paired flumes at three subcatchments and a V-notch weir at the integrating catchment measure quarter-hourly streamflow. Measurements of meteorological and streamflow data began in 2002. Between 2008 and 2010, 50 sensor nodes were added to measure distributed snow depth, air temperature, soil temperature and soil moisture down to a depth of 1 m below the surface. These sensor nodes were installed to capture the lateral differences of aspect and canopy coverage. Data are available at hourly and daily intervals by water year (October 1–September 30) in non-proprietary formats from online data repositories (https://doi.org/10.6071/Z7WC73 and https://doi.org/10.2737/RDS-2017-0037).

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

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

scholarly journals Seasonal dynamics of methane emissions from a subarctic fen in the Hudson Bay Lowlands

2013 ◽  
Vol 10 (7) ◽  
pp. 4465-4479 ◽  
Author(s):  
K. L. Hanis ◽  
M. Tenuta ◽  
B. D. Amiro ◽  
T. N. Papakyriakou
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Growing Season ◽  
Near Surface ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Soil Temperatures ◽  
Surface Soil Temperature ◽  
Filling Method ◽  
Highly Correlated

Abstract. Ecosystem-scale methane (CH4) flux (FCH4) over a subarctic fen at Churchill, Manitoba, Canada was measured to understand the magnitude of emissions during spring and fall shoulder seasons, and the growing season in relation to physical and biological conditions. FCH4 was measured using eddy covariance with a closed-path analyser in four years (2008–2011). Cumulative measured annual FCH4 (shoulder plus growing seasons) ranged from 3.0 to 9.6 g CH4 m−2 yr−1 among the four study years, with a mean of 6.5 to 7.1 g CH4 m−2 yr−1 depending upon gap-filling method. Soil temperatures to depths of 50 cm and air temperature were highly correlated with FCH4, with near-surface soil temperature at 5 cm most correlated across spring, fall, and the shoulder and growing seasons. The response of FCH4 to soil temperature at the 5 cm depth and air temperature was more than double in spring to that of fall. Emission episodes were generally not observed during spring thaw. Growing season emissions also depended upon soil and air temperatures but the water table also exerted influence, with FCH4 highest when water was 2–13 cm below and lowest when it was at or above the mean peat surface.

scholarly journals Influence of meteorological parameters on wheat yield under different sowing conditions

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 161-172
Author(s):  
ANANTA VASHISTH ◽  
DEBASISH ROY ◽  
AVINASH GOYAL ◽  
P. KRISHNAN
Keyword(s):  
Relative Humidity ◽  
Soil Temperature ◽  
Air Temperature ◽  
Field Experiments ◽  
Wheat Yield ◽  
Weather Condition ◽  
Grain Filling ◽  
Crop Growth ◽  
Leaf Water ◽  
Growth Stages

Field experiments were conducted on the research farm of IARI, New Delhi during Rabi 2016-17 and 2017-18. Three varieties of wheat (PBW-723, HD-2967 and HD-3086) were sown on three different dates for generating different weather condition during various phenological stages of crop. Results showed that during early crop growth stages soil moisture had higher value and soil temperature had lower value and with progress of crop growth stage, the moisture in the upper layer decreased and soil temperature increased significantly as compared to the bottom layers. During tillering and jointing stage, air temperature within canopy was more and relative humidity was less while during flowering and grain filling stage, air temperature within canopy was less and relative humidity was more in timely sown crop as compared to late and very late sown crop. Radiation use efficiency and relative leaf water content had significantly higher value while leaf water potential had lower value in timely sown crop followed by late and very late sown crop. Yield had higher value in HD-3086 followed by HD-2967 and PBW-723 in all weather conditions. Canopy air temperature difference had positive value in very late sown crop particularly during flowering and grain-filling stages. This reflects in the yield. Yield was more in timely sown crop as compared to late and very late sown crop.  

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