scholarly journals Time scale bias in erosion rates of glaciated landscapes

2016 ◽  
Vol 2 (10) ◽  
pp. e1600204 ◽  
Author(s):  
Vamsi Ganti ◽  
Christoph von Hagke ◽  
Dirk Scherler ◽  
Michael P. Lamb ◽  
Woodward W. Fischer ◽  
...  
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Erosion Rate ◽  
Earth Science ◽  
Geologic Time ◽  
Erosion Rates ◽  
River Incision ◽  
Tightly Coupled ◽  
Heavy Tailed ◽  
Averaging Time

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time.

scholarly journals Evaluation of CMORPH Precipitation Products at Fine Space–Time Scales

2009 ◽  
Vol 10 (1) ◽  
pp. 300-307 ◽  
Author(s):  
Dawit A. Zeweldi ◽  
Mekonnen Gebremichael
Keyword(s):  
High Resolution ◽  
Time Scales ◽  
Spatial Patterns ◽  
Time Scale ◽  
Statistical Techniques ◽  
Spatial Fields ◽  
Satellite Rainfall ◽  
Performance Statistics ◽  
Averaging Time ◽  
Temporally Correlated

Abstract In this study, a comparison of the spatial patterns of high-resolution precipitation products obtained from the Climate Prediction Center’s morphing technique (CMORPH), which is a satellite-only product, and gauge-adjusted Next Generation Weather Radar (NEXRAD) rainfall observations is performed using a variety of statistical techniques for the Little Washita watershed region in Oklahoma for a 3-yr period. Results show that 1) the performance statistics of CMORPH show tremendous variability from one hour to the next, suggesting that the performance statistics are dynamic in time, and therefore each satellite rainfall product should be accompanied by an error product to make it more meaningful; 2) CMORPH is positively biased in summer and negatively biased in winter, consistent with the findings of previous studies; 3) CMORPH spatial fields tend to be smoother than NEXRAD output; 4) the errors are temporally correlated, in particular within the range from 1 to 6 accumulation hours, implying that averaging CMORPH products over these time scales does not reduce the errors significantly; and 5) the errors become less correlated in time as the averaging time scale increases to the range from 6 to 24 h.

scholarly journals Pulsar Astrometry and Improved Terrestrial Clocks

1996 ◽  
Vol 160 ◽  
pp. 113-114
Author(s):  
Demetrios N. Matsakis ◽  
Frederick J. Josties ◽  
Roger S. Foster
Keyword(s):  
Inverse Problem ◽  
Time Scales ◽  
Time Scale ◽  
World Wide ◽  
State Of The Art ◽  
Frequency Standards ◽  
A Value ◽  
The World ◽  
Averaging Time ◽  
Atomic Time

AbstractRecent improvements in cesium and hydrogen terrestrial frequency standards have brought the frequency precision of International Atomic Time (TAI) to a value of 2.5E-15 s/s over an averaging time of a month. In this paper we illustrate the improvement graphically, and discuss the state of the art for frame ties between the radio, dynamical, and optical frames. In a larger paper, available via the World Wide Web, we illustrate the measured accuracy curves of the frequency standards, show their effect on the ensemble time scales, explain the reasons for the confusing array of available time scales, and discuss the inverse problem of using pulsar data to correct the terrestrial time scale.

scholarly journals Combination of 137Cs and 210Pb Radioactive Atmospheric Fallouts to Estimate Soil Erosion for the Same Time Scale

2020 ◽  
Vol 17 (22) ◽  
pp. 8292
Author(s):  
Foued Gharbi ◽  
Torfa Hamad AlSheddi ◽  
Rebai Ben Ammar ◽  
Medhat Ahmed El-Naggar
Keyword(s):  
Soil Erosion ◽  
Time Scales ◽  
Time Scale ◽  
210Pb And 137Cs ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Proposed Model ◽  
Calibration Models ◽  
Mass Balance Approach

Naturally occurring 210Pb and artificial 137Cs fallouts are widely used as radioactive tracers for the determination of water-induced soil erosion for different time scales equal to 50 and 100 years, respectively. There exist several calibration models useful to convert the variation of the inventory of these radiotracers in cultivated soil compared to its value on non-disturbed soil to a soil erosion rate. The most comprehensive calibration models are based on a mass balance approach. In the present work, a new calibration model is proposed. It consists on the generalization of the mass balance approach to a cultivated soil subject to two successive and continuous periods of cultivation. The proposed model combines 210Pb and 137Cs fallouts for the same time scale by relaxing the constraint on 210Pb fallout from being used for 100 years’ time scale. The model was applied successfully to hypothetical cases and can be used to measure soil erosion rates for practical cases. It is important to note that the proposed model has two main advantages. First, the complementarity between 210Pb and 137Cs fallouts is for the same time scale and not for different time scales, as usually considered and believed in this field. Second, 210Pb fallout is used for time scales less than 100 years. This makes the model useful to estimate soil erosion rates for two successive periods of cultivation. To the best knowledge of the authors, the combination of 210Pb and 137Cs fallouts for the determination of soil erosion rate variation due to change in cultivation practices for the same time scale has never been developed or applied in the past.

An Exhumation History of Continents over Billion-Year Time Scales

Science ◽  
2012 ◽  
Vol 335 (6064) ◽  
pp. 73-76 ◽  
Author(s):  
Terrence J. Blackburn ◽  
Samuel A. Bowring ◽  
J. Taylor Perron ◽  
Kevin H. Mahan ◽  
Francis O. Dudas ◽  
...  
Keyword(s):  
Time Scales ◽  
Continental Lithosphere ◽  
Geologic Time ◽  
Erosion Rates ◽  
Continuous Record ◽  
History Of ◽  
Lower Crustal ◽  
Insight Into ◽  
Exhumation History ◽  
Stable Structures

The continental lithosphere contains the oldest and most stable structures on Earth, where fragments of ancient material have eluded destruction by tectonic and surface processes operating over billions of years. Although present-day erosion of these remnants is slow, a record of how they have uplifted, eroded, and cooled over Earth’s history can provide insight into the physical properties of the continents and the forces operating to exhume them over geologic time. We constructed a continuous record of ancient lithosphere cooling with the use of uranium-lead (U-Pb) thermochronology on volcanically exhumed lower crustal fragments. Combining these measurements with thermal and Pb-diffusion models constrains the range of possible erosion histories. Measured U-Pb data are consistent with extremely low erosion rates persisting over time scales approaching the age of the continents themselves.

scholarly journals GNSS-to-GNSS time offsets: study on the broadcast of a common reference time

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Ilaria Sesia ◽  
Giovanna Signorile ◽  
Tung Thanh Thai ◽  
Pascale Defraigne ◽  
Patrizia Tavella
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Reference Time ◽  
Single Time ◽  
Common Reference ◽  
Prediction Quality ◽  
Common Time ◽  
Time Offset ◽  
The Impact ◽  
Low Uncertainty

AbstractWe present two different approaches to broadcasting information to retrieve the GNSS-to-GNSS time offsets needed by users of multi-GNSS signals. Both approaches rely on the broadcast of a single time offset of each GNSS time versus one common time scale instead of broadcasting the time offsets between each of the constellation pairs. The first common time scale is the average of the GNSS time scales, and the second time scale is the prediction of UTC already broadcast by the different systems. We show that the average GNSS time scale allows the estimation of the GNSS-to-GNSS time offset at the user level with the very low uncertainty of a few nanoseconds when the receivers at both the provider and user levels are fully calibrated. The use of broadcast UTC prediction as a common time scale has a slightly larger uncertainty, which depends on the broadcast UTC prediction quality, which could be improved in the future. This study focuses on the evaluation of two different common time scales, not considering the impact of receiver calibration, at the user and provider levels, which can nevertheless have an important impact on GNSS-to-GNSS time offset estimation.

Sensor-Based Estimation of Dim Light Melatonin Onset Using Features of Two Time Scales

2021 ◽  
Vol 2 (3) ◽  
pp. 1-15
Author(s):  
Cheng Wan ◽  
Andrew W. Mchill ◽  
Elizabeth B. Klerman ◽  
Akane Sano
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Light Exposure ◽  
Biological Activities ◽  
Second Step ◽  
Sampled Data ◽  
Dim Light Melatonin Onset ◽  
Dim Light ◽  
Using Data ◽  
Mean Square Errors

Circadian rhythms influence multiple essential biological activities, including sleep, performance, and mood. The dim light melatonin onset (DLMO) is the gold standard for measuring human circadian phase (i.e., timing). The collection of DLMO is expensive and time consuming since multiple saliva or blood samples are required overnight in special conditions, and the samples must then be assayed for melatonin. Recently, several computational approaches have been designed for estimating DLMO. These methods collect daily sampled data (e.g., sleep onset/offset times) or frequently sampled data (e.g., light exposure/skin temperature/physical activity collected every minute) to train learning models for estimating DLMO. One limitation of these studies is that they only leverage one time-scale data. We propose a two-step framework for estimating DLMO using data from both time scales. The first step summarizes data from before the current day, whereas the second step combines this summary with frequently sampled data of the current day. We evaluate three moving average models that input sleep timing data as the first step and use recurrent neural network models as the second step. The results using data from 207 undergraduates show that our two-step model with two time-scale features has statistically significantly lower root-mean-square errors than models that use either daily sampled data or frequently sampled data.

scholarly journals Locally and Remotely Forced Subtropical AMOC Variability: A Matter of Time Scales

2020 ◽  
Vol 33 (12) ◽  
pp. 5155-5172
Author(s):  
Quentin Jamet ◽  
William K. Dewar ◽  
Nicolas Wienders ◽  
Bruno Deremble ◽  
Sally Close ◽  
...  
Keyword(s):  
Time Series ◽  
Time Scales ◽  
North Atlantic ◽  
Time Scale ◽  
Low Frequency ◽  
Meridional Overturning Circulation ◽  
Open Boundary ◽  
Overturning Circulation ◽  
Decadal Scale ◽  
Meridional Overturning

AbstractMechanisms driving the North Atlantic meridional overturning circulation (AMOC) variability at low frequency are of central interest for accurate climate predictions. Although the subpolar gyre region has been identified as a preferred place for generating climate time-scale signals, their southward propagation remains under consideration, complicating the interpretation of the observed time series provided by the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array–Western Boundary Time Series (RAPID–MOCHA–WBTS) program. In this study, we aim at disentangling the respective contribution of the local atmospheric forcing from signals of remote origin for the subtropical low-frequency AMOC variability. We analyze for this a set of four ensembles of a regional (20°S–55°N), eddy-resolving (1/12°) North Atlantic oceanic configuration, where surface forcing and open boundary conditions are alternatively permuted from fully varying (realistic) to yearly repeating signals. Their analysis reveals the predominance of local, atmospherically forced signal at interannual time scales (2–10 years), whereas signals imposed by the boundaries are responsible for the decadal (10–30 years) part of the spectrum. Due to this marked time-scale separation, we show that, although the intergyre region exhibits peculiarities, most of the subtropical AMOC variability can be understood as a linear superposition of these two signals. Finally, we find that the decadal-scale, boundary-forced AMOC variability has both northern and southern origins, although the former dominates over the latter, including at the site of the RAPID array (26.5°N).

scholarly journals Impacts of oak deforestation and rainfed cultivation on soil redistribution processes across hillslopes using 137Cs techniques

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shamsollah Ayoubi ◽  
Nafiseh Sadeghi ◽  
Farideh Abbaszadeh Afshar ◽  
Mohammad Reza Abdi ◽  
Mojtaba Zeraatpisheh ◽  
...  
Keyword(s):  
Land Use ◽  
Magnetic Susceptibility ◽  
Soil Erosion ◽  
Erosion Rate ◽  
Land Use Changes ◽  
Soil Samples ◽  
Natural Forest ◽  
Oak Forests ◽  
Erosion Rates ◽  
Rainfed Farming

Abstract Background As one of the main components of land-use change, deforestation is considered the greatest threat to global environmental diversity with possible irreversible environmental consequences. Specifically, one example could be the impacts of land-use changes from oak forests into agricultural ecosystems, which may have detrimental impacts on soil mobilization across hillslopes. However, to date, scarce studies are assessing these impacts at different slope positions and soil depths, shedding light on key geomorphological processes. Methods In this research, the Caesium-137 (137Cs) technique was applied to evaluate soil redistribution and soil erosion rates due to the effects of these above-mentioned land-use changes. To achieve this goal, we select a representative area in the Lordegan district, central Iran. 137Cs depth distribution profiles were established in four different hillslope positions after converting natural oak forests to rainfed farming. In each hillslope, soil samples from three depths (0–10, 10–20, and 20–50 cm) and in four different slope positions (summit, shoulder, backslope, and footslope) were taken in three transects of about 20 m away from each other. The activity of 137Cs was determined in all the soil samples (72 soil samples) by a gamma spectrometer. In addition, some physicochemical properties and the magnetic susceptibility (MS) of soil samples were measured. Results Erosion rates reached 51.1 t·ha− 1·yr− 1 in rainfed farming, whereas in the natural forest, the erosion rate was 9.3 t·ha− 1·yr− 1. Magnetic susceptibility was considerably lower in the cultivated land (χhf = 43.5 × 10− 8 m3·kg− 1) than in the natural forest (χhf = 55.1 × 10− 8 m3·kg− 1). The lower soil erosion rate in the natural forest land indicated significantly higher MS in all landform positions except at the summit one, compared to that in the rainfed farming land. The shoulder and summit positions were the most erodible hillslope positions in the natural forest and rainfed farming, respectively. Conclusions We concluded that land-use change and hillslope positions played a key role in eroding the surface soils in this area. Moreover, land management can influence soil erosion intensity and may both mitigate and amplify soil loss.

scholarly journals A EEG-based emotion recognition model with rhythm and time characteristics

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jianzhuo Yan ◽  
Shangbin Chen ◽  
Sinuo Deng
Keyword(s):  
Emotion Recognition ◽  
Time Scales ◽  
Time Scale ◽  
Short Term Memory ◽  
Recognition Model ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Valence And Arousal ◽  
Memory Characteristics

Abstract As an advanced function of the human brain, emotion has a significant influence on human studies, works, and other aspects of life. Artificial Intelligence has played an important role in recognizing human emotion correctly. EEG-based emotion recognition (ER), one application of Brain Computer Interface (BCI), is becoming more popular in recent years. However, due to the ambiguity of human emotions and the complexity of EEG signals, the EEG-ER system which can recognize emotions with high accuracy is not easy to achieve. Based on the time scale, this paper chooses the recurrent neural network as the breakthrough point of the screening model. According to the rhythmic characteristics and temporal memory characteristics of EEG, this research proposes a Rhythmic Time EEG Emotion Recognition Model (RT-ERM) based on the valence and arousal of Long–Short-Term Memory Network (LSTM). By applying this model, the classification results of different rhythms and time scales are different. The optimal rhythm and time scale of the RT-ERM model are obtained through the results of the classification accuracy of different rhythms and different time scales. Then, the classification of emotional EEG is carried out by the best time scales corresponding to different rhythms. Finally, by comparing with other existing emotional EEG classification methods, it is found that the rhythm and time scale of the model can contribute to the accuracy of RT-ERM.

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