scholarly journals Seasonal variations in natural processesand atmospheric precipitation

2009 ◽  
Vol 47 (1) ◽  
Author(s):  
A. V. Descherevsky ◽  
A. Ya. Sidorin
Keyword(s):  
Time Series ◽  
Seasonal Variations ◽  
Apparent Resistivity ◽  
Water Saturation ◽  
Soil Layer ◽  
Atmospheric Precipitation ◽  
Test Site ◽  
Small Current ◽  
Current Electrode ◽  
Garm Test Site

To study the nature of seasonal variations in time series measured at the Garm test site, a local model based on the experimental data of atmospheric precipitation penetration into the soil has been proposed. It is intended for filtration of exogenous variations in the data of various time series and a study of statistical structure of different natural processes, including earthquake preparation processes, and the mechanisms of their effect on the biosphere. Using this model, we analyze and compare variations in apparent resistivity and properties of rock moistening. It has been shown that at small current-electrode (AB) separations among all the parameters of water regime, only water saturation of the active soil layer reveals a significant correlation with apparent resistivity variations. When increasing the current-electrode separation, the seasonal variation form varies from quasisinusoidal in the upper layer up to quasi-triangular at the largest investigated depths (maximum separations).

scholarly journals The effects of daily meteorological perturbation on pregnancy outcome: follow-up of a cohort of young women undergoing IVF treatment

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Mingpeng Zhao ◽  
Haoyang Zhang ◽  
Tarah H. B. Waters ◽  
Jacqueline Pui Wah Chung ◽  
Tin Chiu Li ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Time Series Analysis ◽  
Subgroup Analysis ◽  
Seasonal Variations ◽  
Multiple Logistic Regression Analysis ◽  
Human Reproduction ◽  
Mixed Effect ◽  
Series Analysis ◽  
Patient Consent

Abstract Background Human reproduction follows a seasonal pattern with respect to spontaneous conception, a phenomenon wherein the effect of meteorological fluctuations might not be unique. However, the effect of seasonal variations on patients who underwent in vitro fertilization (IVF) treatment is unclear. We aimed to evaluate the effects of meteorological variation on the pregnancy rate in a cohort undergoing IVF treatment by performing multivariable analyses. Methods We conducted a cohort study in a sub-tropical region with prominent seasonal variations (2005–2016). Women aged < 35 years who were treated with a long ovarian stimulation protocol and underwent fresh embryo transfer (ER) were included. Data on gonadotropin administration (CYCL), oocyte retrieval (OR), ER, and pregnancy outcomes were prospectively recorded. For each patient, the daily average of meteorological data (temperature, humidity, sunlight duration, solar radiation) was recorded from the date of CYCL to ER. Multiple logistic regression analysis adjusted for age, fertilization method, year of the cycle, gonadotropin dose, and transferred embryo grade was performed to determine the relationship between the meteorological parameters and clinical pregnancy. Patients with one successful cycle and one failed cycle were subtracted for a case-control subgroup analysis through mixed effect logistics regressions. Time-series analysis of data in the epidemic level was conducted using the distributed lag linear and non-linear models (DLNMs). Results There were 1029 fresh cycles in 860 women (mean age 31.9 ± 2.0 years). Higher mean temperature from CYCL to OR (adjusted odds ratio [aOR] 1.04; 95% confidence interval [CI] 1.01–1.07, P = 0.01) increased the odds of pregnancy, while OR to ER did not show any statistical significance. Compared to that in winter, the odds of becoming pregnant were higher during higher temperature seasons, summer and autumn (aOR 1.47, 95%CI 0.97–2.23, P = 0.07 (marginally significant) and aOR 1.73, 95%CI 1.12–2.68, P = 0.02, respectively). Humidity, sunlight duration, and solar radiation had no effect on the outcome. The subgroup analysis confirmed this finding. The time-series analysis revealed a positive association between temperature and relative risk for pregnancy. Conclusions In IVF treatment, the ambient temperature variation alters the pregnancy rates; this aspect must be considered when obtaining patient consent for assisted conception.

scholarly journals Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt
Keyword(s):  
Time Series ◽  
Species Composition ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Grazing Intensity ◽  
Test Site ◽  
Grazing Pressure ◽  
Modis Ndvi ◽  
Coarse Resolution

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.

Evaluation of Seasonal Effects on Subgrade Soils

2003 ◽  
Vol 1821 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Andrew G. Heydinger
Keyword(s):  
Seasonal Variations ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Test Site ◽  
Pavement Design ◽  
Seasonal Effects ◽  
Pavement Performance ◽  
Climatic Effects ◽  
Subgrade Soils ◽  
Frost Penetration

One objective of the FHWA’s Long-Term Pavement Performance (LTPP) program is to determine climatic effects on pavement performance. The LTPP instrumentation program includes seasonal monitoring program (SMP) instrumentation to monitor the seasonal variations of moisture, temperature, and frost penetration. Findings from the SMP instrumentation are to be incorporated into future pavement design procedures. Data from SMP instrumentation at the Ohio Strategic Highway Research Program Test Road (US-23, Delaware County, Ohio) and other reported results were analyzed to develop empirical equations. General expressions for the seasonal variations of average daily air temperature and variations of temperature and moisture in the fine-grained subgrade soil at the test site are presented. An expression for the seasonal variation of resilient modulus was derived. Average monthly weighting factors that can be used for pavement design were computed. Other factors such as frost penetration, depth of water table, and drainage conditions are discussed.

scholarly journals Calculation of the Height of Capillary Rise of Water in Soils

2020 ◽  
Vol 8 (6) ◽  
pp. 4832-4835
Keyword(s):  
Water Saturation ◽  
Underground Structure ◽  
Capillary Rise ◽  
Soil Layer ◽  
Underground Water ◽  
Wall Material ◽  
Capillary Water ◽  
Temporary Streams ◽  
Filter Water ◽  
Soil Pores

Rain and melt water will form temporary accumulations of surface water on the surface. When they seep into the ground, temporary streams of leaky filter water are formed. If a limited section of water-resistant soil layer or the roof of an underground structure is encountered in the path of these waters, a temporary aquifer-the upper layer of ground water-may form above them. In temporary and permanent aquifers, the soil pores are completely filled with gravitational water, the degree of water saturation is equal to one, and there is pressure under the surface of underground water. Above this surface is a zone of capillary moisture, while the level of capillary rise is determined by the granulometric composition of the soil and ranges from tens of centimeters in sand to several meters in dusty and clay soils. Capillary water rises in the ground on free canals formed by mutually communicating pores, or is kept in them in limbo.The lifting of the liquid in the capillary continues until the gravity acting on the column of the liquid in the capillary becomes equal to the resulting force. Capillary water penetrates from the ground into the walls and rises to a height of up to 2 meters. The normal moisture content of the brick walls is 0.02...0,03, and in the case of unprotected contact with moist soil is increased to 0.15...0.25. On the inside of the walls there is a damp, mildew. Evaporating water increases humidity in the room, and the salts released when it evaporates from salt solutions lead to peeling paint, destruction of plaster and wall material.

Comparison of Tropospheric Zenith Wet Delay from VLBI and GNSS Estimations

2021 ◽  
Author(s):  
Vicky Jia Liu ◽  
Maaria Nordman ◽  
Nataliya Zubko
Keyword(s):  
Time Series ◽  
Seasonal Variations ◽  
Elevation Angle ◽  
Correlation Coefficients ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Polar Regions ◽  
Long Baseline ◽  
Zenith Wet Delay ◽  
Space Geodetic Techniques

&lt;p&gt;Tropospheric delay is one of the major error sources for space geodetic techniques such as Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite System (GNSS). In this study, we compared the agreement of tropospheric zenith wet delay (ZWD) seasonal variations derived from VLBI and GNSS observations at 8 stations that are located at all around the globe. We have analysed time series of 8 years, starting in 2012 until end of 2019. Results show that VLBI_ZWD present clear seasonal variations which depend on the location of each station, in the tropics the variability is more pronounced than in mid-latitudes or polar regions. Furthermore, the VLBI_ZWD also shows a reasonably good agreement with seasonal fit model. When comparing zenith wet delays derived from co-located GNSS and VLBI stations at &amp;#160;cut-off elevation angle, they agree quite well, which is proved by the high correlation coefficients, varying from 0.6 up to 0.95. The biases between the techniques are in mm level and standard errors of the whole time series are in few centimetres.&lt;/p&gt;

scholarly journals Seasonal Cycles of Phytoplankton Expressed by Sine Equations Using the Daily Climatology from Satellite-Retrieved Chlorophyll-a Concentration (1997–2019) Over Global Ocean

2020 ◽  
Vol 12 (16) ◽  
pp. 2662 ◽  
Author(s):  
Zexi Mao ◽  
Zhihua Mao ◽  
Cédric Jamet ◽  
Marc Linderman ◽  
Yuntao Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Chlorophyll A ◽  
Seasonal Variations ◽  
Global Ocean ◽  
Boreal Winter ◽  
Seasonal Cycles ◽  
Chlorophyll A Concentration ◽  
Chl A ◽  
Global Oceans ◽  
Sine Equation

The global coverage of Chlorophyll-a concentration (Chl-a) has been continuously available from ocean color satellite sensors since September 1997 and the Chl-a data (1997–2019) were used to produce a climatological dataset by averaging Chl-a values at same locations and same day of year. The constructed climatology can remarkably reduce the variability of satellite data and clearly exhibit the seasonal cycles, demonstrating that the growth and decay of phytoplankton recurs with similarly seasonal cycles year after year. As the shapes of time series of the climatology exhibit strong periodical change, we wonder whether the seasonality of Chl-a can be expressed by a mathematic equation. Our results show that sinusoid functions are suitable to describe cyclical variations of data in time series and patterns of the daily climatology can be matched by sine equations with parameters of mean, amplitude, phase, and frequency. Three types of sine equations were used to match the climatological Chl-a with Mean Relative Differences (MRD) of 7.1%, 4.5%, and 3.3%, respectively. The sine equation with four sinusoids can modulate the shapes of the fitted values to match various patterns of climatology with small MRD values (less than 5%) in about 90% of global oceans. The fitted values can reflect an overall pattern of seasonal cycles of Chl-a which can be taken as a time series of biomass baseline for describing the state of seasonal variations of phytoplankton. The amplitude images, the spatial patterns of seasonal variations of phytoplankton, can be used to identify the transition zone chlorophyll fronts. The timing of phytoplankton blooms is identified by the biggest peak of the fitted values and used to classify oceans as different bloom seasons, indicating that blooms occur in all four seasons with regional features. In global oceans within latitude domains (48°N–48°S), blooms occupy approximately half of the ocean (50.6%) during boreal winter (December–February) in the northern hemisphere and more than half (58.0%) during austral winter (June–August) in the southern hemisphere. Therefore, the sine equation can be used to match the daily Chl-a climatology and the fitted values can reflect the seasonal cycles of phytoplankton, which can be used to investigate the underlying phenological characteristics.

scholarly journals Magnetotelluric Signal-Noise Separation Using IE-LZC and MP

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1190
Author(s):  
Xian Zhang ◽  
Diquan Li ◽  
Jin Li ◽  
Yong Li ◽  
Jialin Wang ◽  
...  
Keyword(s):  
Apparent Resistivity ◽  
Matching Pursuit ◽  
Low Frequency ◽  
Reference Method ◽  
Test Site ◽  
Phase Curve ◽  
Characteristic Parameters ◽  
Geological Interpretation ◽  
Useful Signal ◽  
Fcm Clustering

Eliminating noise signals of the magnetotelluric (MT) method is bound to improve the quality of MT data. However, existing de-noising methods are designed for use in whole MT data sets, causing the loss of low-frequency information and severe mutation of the apparent resistivity-phase curve in low-frequency bands. In this paper, we used information entropy (IE), the Lempel–Ziv complexity (LZC), and matching pursuit (MP) to distinguish and suppress MT noise signals. Firstly, we extracted IE and LZC characteristic parameters from each segment of the MT signal in the time-series. Then, the characteristic parameters were input into the FCM clustering to automatically distinguish between the signal and noise. Next, the MP de-noising algorithm was used independently to eliminate MT signal segments that were identified as interference. Finally, the identified useful signal segments were combined with the denoised data segments to reconstruct the signal. The proposed method was validated through clustering analysis based on the signal samples collected at the Qinghai test site and the measured sites, where the results were compared to those obtained using the remote reference method and independent use of the MP method. The findings show that strong interference is purposefully removed, and the apparent resistivity-phase curve is continuous and stable. Moreover, the processed data can accurately reflect the geoelectrical information and improve the level of geological interpretation.

scholarly journals The Soil Moisture during Dry Spells Model and Its Verification

Resources ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 85
Author(s):  
Małgorzata Biniak-Pieróg ◽  
Mieczysław Chalfen ◽  
Andrzej Żyromski ◽  
Andrzej Doroszewski ◽  
Tomasz Jóźwicki
Keyword(s):  
Soil Moisture ◽  
Least Squares Method ◽  
Soil Depth ◽  
Soil Layer ◽  
Atmospheric Precipitation ◽  
Soil Surface ◽  
Model Verification ◽  
Individual Measurement ◽  
Dry Spells ◽  
Dry Spell

The objective of this study was the development and verification of a model of soil moisture decrease during dry spells—SMDS. The analyses were based on diurnal information of the occurrence of atmospheric precipitation and diurnal values of soil moisture under a bare soil surface, covering the period of 2003–2019, from May until October. A decreasing exponential trend was used for the description of the rate of moisture decrease in six layers of the soil profile during dry spells. The least squares method was used to determine, for each dry spell and soil depth, the value of exponent α , which described the rate of soil moisture decrease. Data from the years 2003–2015 were used for the identification of parameter α of the model for each of the layers separately, while data from 2016–2019 were used for model verification. The mean relative error between moisture values measured in 2016–2019 and the calculated values was 3.8%, and accepted as sufficiently accurate. It was found that the error of model fitting decreased with soil layer depth, from 8.1% for the surface layer to 1.0% for the deepest layer, while increasing with the duration of the dry spell at the rate of 0.5%/day. The universality of the model was also confirmed by verification made with the use of the results of soil moisture measurements conducted in the years 2009–2019 at two other independent locations. However, it should be emphasized that in the case of the surface horizon of soil, for which the process of soil drying is a function of factors occurring in the atmosphere, the developed model may have limited application and the obtained results may be affected by greater errors. The adoption of calculated values of coefficient α as characteristic for the individual measurement depths allowed calculation of the predicted values of moisture as a function of the duration of a dry spell, relative to the initial moisture level adopted as 100%. The exponential form of the trend of soil moisture changes in time adopted for the analysis also allowed calculation of the duration of a hypothetical dry spell t, after which soil moisture at a given depth drops from the known initial moisture θ0 to the predicted moisture θ. This is an important finding from the perspective of land use.

Using Time Series to Incorporate Seasonal Variations in Pavement Design

1996 ◽  
Vol 1539 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Hesham A. Ali ◽  
Neville A. Parker
Keyword(s):  
Time Series ◽  
Structural Properties ◽  
Seasonal Variations ◽  
Monitoring Program ◽  
Statistical Technique ◽  
Pavement Design ◽  
Seasonal Monitoring ◽  
Program Data ◽  
Series Technique

Analysis of the seasonal monitoring program data of the long term pavement performance program indicated that some pavement structural properties often follow predictable seasonal patterns. Time series is a statistical technique that may be used to develop periodic functions to predict the values of such properties as a function of time. The application of time series technique in characterizing the seasonal variations of pavement structural properties as simulated functions is presented. In addition, the incorporation of such variations in both empirical and mechanistic-empirical methods of flexible pavement design is demonstrated. To this end, a computer program, seasonal variation in pavement design, was written to carry out the required calculations and to facilitate the comparison between empirical and mechanistic-empirical design methods.

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