scholarly journals Tsallis q-Stat and the Evidence of Long-Range Interactions in Soil Temperature Dynamics

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 909
Author(s):  
Babalola O. Ogunsua ◽  
John A. Laoye
Keyword(s):  
Soil Temperature ◽  
Temperature Variation ◽  
Gaussian Model ◽  
Temperature Data ◽  
Data Sets ◽  
Wet Season ◽  
Monthly Data ◽  
Long Range Interactions ◽  
Q Index ◽  
Temperature Time

The complexities in the variations of soil temperature and thermal diffusion poses a physical problem that requires more understanding. The quest for a better understanding of the complexities of soil temperature variation has prompted the study of the q-statistics in the soil temperature variation with the view of understanding the underlying dynamics of the temperature variation and thermal diffusivity of the soil. In this work, the values of Tsallis stationary state q index known as q-stat were computed from soil temperature measured at different stations in Nigeria. The intrinsic variations of the soil temperature were derived from the soil temperature time series by detrending method to extract the influences of other types of variations from the atmosphere. The detrended soil temperature data sets were further analysed to fit the q-Gaussian model. Our results show that our datasets fit into the Tsallis Gaussian distributions with lower values of q-stat during rainy season and around the wet soil regions of Nigeria and the values of q-stat obtained for monthly data sets were mostly in the range 1.2≤q≤2.9 for all stations, with very few values q closer to 1.2 for a few stations in the wet season. The distributions obtained from the detrended soil temperature data were mostly found to belong to the class of asymmetric q-Gaussians. The ability of the soil temperature data sets to fit into q-Gaussians might be due and the non-extensive statistical nature of the system and (or) consequently due to the presence of superstatistics. The possible mechanisms responsible this behaviour was further discussed.

scholarly journals Validation of merged MSU4 and AMSU9 temperature climate records with a new 2002–2012 vertically resolved temperature record

2015 ◽  
Vol 8 (1) ◽  
pp. 235-267 ◽  
Author(s):  
A. A. Penckwitt ◽  
G. E. Bodeker ◽  
P. Stoll ◽  
J. Lewis ◽  
T. von Clarmann ◽  
...  
Keyword(s):  
Time Series ◽  
Radio Occultation ◽  
Temperature Data ◽  
Data Sets ◽  
Data Set ◽  
Upper Troposphere ◽  
Microwave Sounding Unit ◽  
Source Data ◽  
Microwave Sounding ◽  
Temperature Time

Abstract. A new database of monthly mean zonal mean (5° zones) temperature time series spanning 17 pressure levels from 300 to 7 hPa and extending from 2002 to 2012 was created by merging monthly mean time series from two satellite-based mid-infrared spectrometers (ACE-FTS and MIPAS), a microwave sounder (SMR), and from three satellite-based radio occultation experiments (GRACE, CHAMP, and TSX). The primary intended use of this new temperature data set is to validate the merging of the Microwave Sounding Unit channel 4 (MSU4), and Advanced Microwave Sounding Unit channel 9 (AMSU9) temperature time series conducted in previous studies. The six source data sets were merged by removing offsets and trends between the different measurement series. Weighted means were calculated of the six source data sets where the weights were a function of the uncertainty on the original monthly mean data. This new temperature data set of the upper troposphere and stratosphere has been validated by comparing it to RATPAC-A, COSMIC radio occultation data as well as the NCEPCFSR reanalyses. Differences in all three cases were typically < 2 K in the upper troposphere and lower stratosphere, but could reach up to 5 K in the mid-stratosphere. The data across the 17 pressure levels have then been vertically integrated, using the MSU4/AMSU9 weighting function, to provide a deep vertical layer temperature proxy of the merged MSU4+AMSU9 series. Differences between this vertically integrated data set and two different versions of the MSU4+AMSU9 data set – one from Remote Sensing Systems and one from the University of Alabama at Huntsville – were examined for discontinuities. No statistically significant discontinuities were found in either of those two data sets suggesting that the transition from the MSU4+AMSU9 data to AMSU9 data only does not introduce any discontinuities in the MSU4+AMSU9 climate data records that might compromise their use in temperature trend analyses.

scholarly journals Nitrous Oxide Emissions in Pineapple Cultivation on a Tropical Peat Soil

2021 ◽  
Vol 13 (9) ◽  
pp. 4928
Author(s):  
Alicia Vanessa Jeffary ◽  
Osumanu Haruna Ahmed ◽  
Roland Kueh Jui Heng ◽  
Liza Nuriati Lim Kim Choo ◽  
Latifah Omar ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Soil Temperature ◽  
Peat Soil ◽  
Farming Systems ◽  
N2o Emission ◽  
Nitrous Oxide Emissions ◽  
Natural State ◽  
N2o Emissions ◽  
Wet Season ◽  
Peat Soils

Farming systems on peat soils are novel, considering the complexities of these organic soil. Since peat soils effectively capture greenhouse gases in their natural state, cultivating peat soils with annual or perennial crops such as pineapples necessitates the monitoring of nitrous oxide (N2O) emissions, especially from cultivated peat lands, due to a lack of data on N2O emissions. An on-farm experiment was carried out to determine the movement of N2O in pineapple production on peat soil. Additionally, the experiment was carried out to determine if the peat soil temperature and the N2O emissions were related. The chamber method was used to capture the N2O fluxes daily (for dry and wet seasons) after which gas chromatography was used to determine N2O followed by expressing the emission of this gas in t ha−1 yr−1. The movement of N2O horizontally (832 t N2O ha−1 yr−1) during the dry period was higher than in the wet period (599 t N2O ha−1 yr−1) because of C and N substrate in the peat soil, in addition to the fertilizer used in fertilizing the pineapple plants. The vertical movement of N2O (44 t N2O ha−1 yr−1) was higher in the dry season relative to N2O emission (38 t N2O ha−1 yr−1) during the wet season because of nitrification and denitrification of N fertilizer. The peat soil temperature did not affect the direction (horizontal and vertical) of the N2O emission, suggesting that these factors are not related. Therefore, it can be concluded that N2O movement in peat soils under pineapple cultivation on peat lands occurs horizontally and vertically, regardless of season, and there is a need to ensure minimum tilling of the cultivated peat soils to prevent them from being an N2O source instead of an N2O sink.

scholarly journals Investigating temperature breaks in the summer fruit export cold chain: A case study

2013 ◽  
Vol 7 (1) ◽  
Author(s):  
Heinri W. Freiboth ◽  
Leila Goedhals-Gerber ◽  
F. Esbeth Van Dyk ◽  
Malcolm C. Dodd
Keyword(s):  
Temperature Variation ◽  
South African ◽  
Temperature Data ◽  
Added Value ◽  
Cold Chain ◽  
The South ◽  
Export Supply ◽  
Cold Store ◽  
Summer Fruit

There is concern in the South African fruit industry that a large amount of fruit and money is lost every season due to breaks in the fruit export cold chain. The possibility of a large percentage of losses in a significant sector of the economy warranted further investigation. This article attempted to highlight some of the possible problem areas in the cold chain, from the cold store to the port, by analysing historic temperature data from different fruit export supply chains of apples, pears and grapes. In addition, a trial shipment of apples was used to investigate temperature variation between different pallets in the same container. This research has added value to the South African fruit industry by identifying the need to improve operational procedures in the cold chain.

Analytical Model to Predict Nonhomogeneous Soil Temperature Variation

1995 ◽  
Vol 117 (2) ◽  
pp. 100-107 ◽  
Author(s):  
M. Krarti ◽  
D. E. Claridge ◽  
J. F. Kreider
Keyword(s):  
Thermal Properties ◽  
Soil Temperature ◽  
Temperature Variation ◽  
Analytical Model ◽  
Soil Surface ◽  
Deep Soil ◽  
Soil Thermal Properties ◽  
Order Of Magnitude ◽  
Soil Surface Temperature ◽  
Annual Time

This paper presents an analytical model to predict the temperature variation within a multilayered soil. The soil surface temperature is assumed to have a sinusoidal time variation for both daily and annual time scales. The soil thermal properties in each layer are assumed to be uniform. The model is applied to two-layered, three-layered, and to nonhomogeneous soils. In case of two-layered soil, a detailed analysis of the thermal behavior of each layer is presented. It was found that as long as the order of magnitude of the thermal diffusivity of soil surface does not exceed three times that of deep soil; the soil temperature variation with depth can be predicted accurately by a simplified model that assumes that the soil has constant thermal properties.

scholarly journals <i>Brief communication</i> "A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method"

2010 ◽  
Vol 17 (3) ◽  
pp. 269-272 ◽  
Author(s):  
S. Nicolay ◽  
G. Mabille ◽  
X. Fettweis ◽  
M. Erpicum
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Weather Forecast ◽  
Temperature Data ◽  
Temperature Time Series ◽  
Climatic Data ◽  
Statistical Validation ◽  
Confidence Levels ◽  
Temperature Time

Abstract. Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.

scholarly journals Non-stationary temporal characterization of the temperature profile of a soil exposed to frost in south-eastern Canada

2008 ◽  
Vol 15 (3) ◽  
pp. 409-416 ◽  
Author(s):  
F. Anctil ◽  
A. Pratte ◽  
L. E. Parent ◽  
M. A. Bolinder
Keyword(s):  
Time Series ◽  
Soil Temperature ◽  
Temperature Profile ◽  
Air Temperature ◽  
Soil Depth ◽  
Time Lag ◽  
Power Spectra ◽  
Temperature Time Series ◽  
Soil Temperatures ◽  
Temperature Time

Abstract. The objective of this work was to compare time and frequency fluctuations of air and soil temperatures (2-, 5-, 10-, 20- and 50-cm below the soil surface) using the continuous wavelet transform, with a particular emphasis on the daily cycle. The analysis of wavelet power spectra and cross power spectra provided detailed non-stationary accounts with respect to frequencies (or periods) and to time of the structure of the data and also of the relationships that exist between time series. For this particular application to the temperature profile of a soil exposed to frost, both the air temperature and the 2-cm depth soil temperature time series exhibited a dominant power peak at 1-d periodicity, prominent from spring to autumn. This feature was gradually damped as it propagated deeper into the soil and was weak for the 20-cm depth. Influence of the incoming solar radiation was also revealed in the wavelet power spectra analysis by a weaker intensity of the 1-d peak. The principal divergence between air and soil temperatures, besides damping, occurred in winter from the latent heat release associated to the freezing of the soil water and the insulation effect of snowpack that cease the dependence of the soil temperature to the air temperature. Attenuation and phase-shifting of the 1-d periodicity could be quantified through scale-averaged power spectra and time-lag estimations. Air temperature variance was only partly transferred to the 2-cm soil temperature time series and much less so to the 20-cm soil depth.

Caribbean precipitation: review, model and prospect

2008 ◽  
Vol 32 (3) ◽  
pp. 265-276 ◽  
Author(s):  
Douglas W. Gamble ◽  
Scott Curtis
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Annual Rainfall ◽  
Future Research ◽  
Data Sets ◽  
Wet Season ◽  
The Caribbean ◽  
Review Model ◽  
Working Hypotheses

The study of Caribbean climate pre-1990 focused almost exclusively on attempts to link spatial patterns in climatic variables to physical processes. Much of this research assumed a `simple' regional climate, warm year round with a wet season dominated by tropical cyclones, but researchers soon found that a precipitation regionalization of the Caribbean was not as straightforward and simple. Consequently, a satisfactory understanding of the regional precipitation climate has eluded researchers for much of the second half of the twentieth century. Recently, with the increased availability and quality of satellite and precipitation data, researchers have begun to use gridded data sets to identify the spatial boundaries of the bimodal precipitation region and the atmospheric processes associated with the two maxima and minimum in precipitation. The findings of these most recent studies can be combined to construct a five part (North Atlantic high pressure, low level Caribbean jet, subsidence caused by Central America convection, basin wide increased wind shear, and divergence around Jamaica) conceptual Caribbean precipitation model that begins to address spatial variability in the bimodal structure of annual rainfall and the development of the midsummer minimum in precipitation. Such a regional precipitation climate model provides hypotheses to be tested and investigated in future research. Further, researchers must work towards a more effective and clear communication of the bimodal nature of Caribbean precipitation and the associated summer decrease in precipitation, integrate upper air analysis into the current working hypotheses, and further examine the interannual to interdecadal variability of the Caribbean midsummer drought for prediction purposes.

scholarly journals Optimizing galaxy samples for clustering measurements in photometric surveys

2019 ◽  
Vol 491 (3) ◽  
pp. 3535-3552 ◽  
Author(s):  
Dimitrios Tanoglidis ◽  
Chihway Chang ◽  
Joshua Frieman
Keyword(s):  
Cold Dark Matter ◽  
Sample Selection ◽  
Gaussian Model ◽  
Small Subset ◽  
Data Sets ◽  
Trade Off ◽  
Cosmological Constraints ◽  
Dark Energy Survey ◽  
Galaxy Sample ◽  
Cross Correlations

ABSTRACT When analysing galaxy clustering in multiband imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally includes only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third-year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range z = 0.2–0.95. We quantify the cosmological constraints using a figure of merit (FoM) that measures the combined constraints on Ωm and σ8 in the context of Λ cold dark matter (ΛCDM) cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to (1) whether cross-correlations between redshift bins are included or not, and (2) the ratio of the redshift bin width δz to the photo-z precision σz. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when δz ∼ σz. We find that for the typical case of 5−10 redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher σz, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.

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