Understanding the Soil Temperature Variability at Different Depths: Effects of Surface Air Temperature, Snow Cover, and the Soil Memory

2021 ◽  
Author(s):  
Haoxin Zhang ◽  
Naiming Yuan ◽  
Zhuguo Ma ◽  
Yu Huang
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Variability ◽  
Different Depths

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 Regularities of soil temperature changes during the period with snow cover in modern climatic conditions of the Eurasian Subarctic

2021 ◽  
pp. 13-22
Author(s):  
Lev M. Kitaev
Keyword(s):  
Standard Deviation ◽  
Soil Temperature ◽  
Snow Cover ◽  
Air Temperature ◽  
Land Surface ◽  
Environmental Changes ◽  
Surface Air Temperature ◽  
Climatic Conditions ◽  
Winter Period

The influence of snow cover on the dynamics of soil temperature in the modern climatic conditions of the Eurasian Subarctic was investigated through a quantitative assessment of the features of the seasonal and long-term variation of parameters. Seasonal and long-term values of soil temperature for stable snow period decrease from west to east: a decrease of snow thickness and air temperature from west to east of Eurasia leads to a weakening of the heat-insulating properties of the snow cover with a significant decrease in regional air temperatures. With the emergence of a stable snow cover, the soil temperature seasonal and long-term standard deviation sharply decreases compared to the autumn and spring periods. With the appearance of snow cover, the soil temperature standard deviation drops sharply compared to the autumn and spring periods. An exception is the northeast of Siberia: here, a relatively small thickness of snow determines a noticeable dependence of the course of soil temperature on the dynamics of surface air temperature. There are no significant long-term trends in soil temperature due to its low variability during winter period. Analysis of the course of the studied characteristics anomalies showed an insignificant and non-systematic number of their coincidences. Currently, we have not found similar research results for large regions. The revealed patterns can be used in the analysis of the results of monitoring the state of the land surface, in the development of remote sensing algorithms, in the refinement of predictive scenarios of environmental changes.

Understanding the Soil Temperature Variability at Different Depths: Effects of Surface Air Temperature, Snow Cover, and the Soil Memory

2021 ◽  
Author(s):  
Haoxin Zhang ◽  
Naiming Yuan ◽  
Zhuguo Ma ◽  
Yu Huang
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Thermal Conditions ◽  
Northeastern China ◽  
Memory Effects ◽  
Causality Analysis ◽  
Time Lagged ◽  
Warming Hiatus

<p>The soil temperature (ST) is closely related to the surface air temperature (AT), but their coupling may be affected by other factors. In this study, by using linear analysis and nonlinear causality analysis—convergent cross mapping (CCM) and its time-lagged version (time-lagged CCM), significant effects of the AT on the underlying ST were found, and the time taken to propagate downward to 320 cm can be up to 10 months. Besides the AT, the ST is also affected by memory effects—namely, its prior thermal conditions. At deeper depth (i.e., 320 cm), the effects of the AT from a particular season may be exceeded by the soil memory effects from the last season. At shallower layers (i.e., < 80 cm), the effects of the AT may be blocked by the snow cover, resulting in a poorly synchronous correlation between the AT and the ST. In northeastern China, this snow cover blockage mainly occurs in winter and then vanishes in the subsequent spring. Due to the thermal insulation effect of the snow cover, the winter ST at layers above 80 cm in northeastern China were found to continue to increase even during the recent global warming hiatus period. These findings may be instructive for better understanding ST variations, as well as land−atmosphere interactions.</p>

Surface air–soil temperature relationship and shallow soil thermal regime: a case study using a soil temperature observational dataset for Spain.

2021 ◽  
Author(s):  
Camilo Melo Aguilar ◽  
Fidel González Rouco ◽  
Norman Steinert ◽  
Elena García Bustamante ◽  
Felix García Pereira ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Soil Temperature ◽  
Air Temperature ◽  
Thermal Regime ◽  
Ground Surface ◽  
Surface Air Temperature ◽  
Environmental Variable ◽  
Chemical Processes ◽  
Strong Connection ◽  
Shallow Subsurface

<p>The land-atmosphere interactions via the energy and water exchanges at the ground surface generally translate into a strong connection between the surface air temperature (SAT) and the ground surface temperature (GST). In turn, the surface temperature affects the amount of heat flowing into the soil, thus controlling the subsurface temperature profile. As soil temperature (ST) is a key environmental variable that controls various physical, biological and chemical processes, understanding the relationship between SAT and GST and STs is important.</p><p>In situ ST measurements represent the most adequate source of information to evaluate the distribution of temperature in soils and to address its influence on soil biological and chemical processes as well as on climate feedbacks. However, ST observations are scarce both in space and time. Therefore, the development of ST observational datasets is of great interest to promote analyses regarding the soil thermodynamics and the response to atmospheric warming.</p><p>We have developed a quality-controlled dataset of Soil Temperature Observations for Spain (SoTOS). The ST data are obtained from the Spanish meteorological agency (AEMET), including ST at different layers down to a depth of 1 m (i.e., 0.05, 0.1, 0.2, 0.5 and 1 m depth) for 39 observatories for the 1985–2018 period. Likewise, 2m air temperature has also been included for the same 39 sites.</p><p>SoTOS is employed to evaluate the shallow subsurface thermal regime and the SAT–GST relationship on interannual to multidecadal timescales. The results show that thermal conduction is the main heat transfer mechanism that controls the distribution of soil temperatures in the shallow subsurface. Regarding the SAT-GST relationship, there is a strong connection between SAT and GST. However, the SAT–GST coupling may be disrupted on seasonal to multidecadal timescales due to variations in the surface energy balance in response to decreasing soil moisture conditions over the last decade at some SoTOS sites. This results in larger GST warming relative to SAT. Such a response may have implications for climate studies that assume a strong connection between SAT and GST such as air temperature estimations from remote sensing products or even for palaeoclimatic analyses.</p>

scholarly journals Specifics of soil temperature under winter wheat canopy

2013 ◽  
Vol 43 (3) ◽  
pp. 209-223 ◽  
Author(s):  
Jana Krčmáŕová ◽  
Hana Stredová ◽  
Radovan Pokorný ◽  
Tomáš Stdŕeda
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Soil Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Soil Surface ◽  
Regression Equations ◽  
Experimental Plot ◽  
Near Surface ◽  
Soil Temperatures

Abstract The aim of this study was to evaluate the course of soil temperature under the winter wheat canopy and to determine relationships between soil temperature, air temperature and partly soil moisture. In addition, the aim was to describe the dependence by means of regression equations usable for phytopathological prediction models, crop development, and yield models. The measurement of soil temperatures was performed at the experimental field station ˇZabˇcice (Europe, the Czech Republic, South Moravia). The soil in the first experimental plot is Gleyic Fluvisol with 49-58% of the content particles measuring < 0.01 mm, in the second experimental plot, the soil is Haplic Chernozem with 31-32% of the content particles measuring < 0.01 mm. The course of soil temperature and its specifics were determined under winter wheat canopy during the main growth season in the course of three years. Automatic soil temperature sensors were positioned at three depths (0.05, 0.10 and 0.20 m under soil surface), air temperature sensor in 0.05 m above soil surface. Results of the correlation analysis showed that the best interrelationships between these two variables were achieved after a 3-hour delay for the soil temperature at 0.05 m, 5-hour delay for 0.10 m, and 8-hour delay for 0.20 m. After the time correction, the determination coefficient reached values from 0.75 to 0.89 for the depth of 0.05 m, 0.61 to 0.82 for the depth of 0.10 m, and 0.33 to 0.70 for the depth of 0.20 m. When using multiple regression with quadratic spacing (modeling hourly soil temperature based on the hourly near surface air temperature and hourly soil moisture in the 0.10-0.40 m profile), the difference between the measured and the model soil temperatures at 0.05 m was −2.16 to 2.37 ◦ C. The regression equation paired with alternative agrometeorological instruments enables relatively accurate modeling of soil temperatures (R2 = 0.93).

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