scholarly journals Detection of homogeneous precipitation regions at seasonal and annual time scales, northwest Iran

2017 ◽  
Vol 8 (4) ◽  
pp. 701-714 ◽  
Author(s):  
Mohammad Arab Amiri ◽  
Mohammad Saadi Mesgari ◽  
Christian Conoscenti
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Homogeneous Precipitation ◽  
Total Precipitation ◽  
Spatial And Temporal Patterns ◽  
Study Region ◽  
Key Factor ◽  
Northwestern Iran ◽  
And Cluster Analysis ◽  
Annual Time

Abstract Detection of homogeneous climate areas is a challenging issue, which can be affected by different criteria. One of the most prominent factors is choosing the time scale, which can lead to different spatial and temporal patterns. Total precipitation is a key factor in climatological studies, and studying its distribution is of utmost importance. The combination of principal components analysis and cluster analysis is used for homogeneous precipitation areas' detection. Hence, the spatial pattern of total precipitation was investigated in northwestern Iran during the past two decades (1991–2010) on seasonal and annual time scales. The results of clustering on each time scale were validated, and well-defined clusters were investigated and compared with each other. Two homogeneous sub-regions were recognized in spring, the best period for depicting homogeneous precipitation clusters at seasonal resolution. The annual pattern of precipitation delineated three clusters in the study region. Finally, the characteristics of the well-clustered maps reveal the importance of time scale in detection of homogeneous precipitation sub-zones.

scholarly journals The Relationship between Intermodel Differences and Surface Energy Balance Complexity in the Rhône-Aggregation Intercomparison Project

2006 ◽  
Vol 7 (1) ◽  
pp. 81-100 ◽  
Author(s):  
S. Fox ◽  
A. J. Pitman ◽  
A. Boone ◽  
F. Habets
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Time Scales ◽  
Time Scale ◽  
Surface Resistance ◽  
Surface Energy Balance ◽  
Surface Model ◽  
Intercomparison Project ◽  
The Relationship ◽  
Annual Time

Abstract Six modes of complexity of the Chameleon land surface model (CHASM) are used to explore the relationship between the complexity of the surface energy balance (SEB) formulation and the capacity of the model to explain intermodel variations in results from the Rhône-Aggregation Intercomparison Project (Rhône-AGG). At an annual time scale, differences between models identified in the Rhône-AGG experiments in the partitioning of available energy and water at the spatial scale of the Rhône Basin can be reproduced by CHASM via variations in the SEB complexity. Only two changes in the SEB complexity in the model generate statistically significant differences in the mean latent heat flux. These are the addition of a constant surface resistance to the simplest mode of CHASM and the addition of tiling and temporally and spatially variable surface resistance to produce the most complex model. Further, the only statistically significant differences in runoff occur following the addition of a constant surface resistance to the simplest mode of CHASM. As the time scale is reduced from annual to monthly, specific mechanisms begin to dominate the simulations produced by each Rhône-AGG model and introduce parameterization-specific behavior that depends on the time evolution of processes operating on longer time scales. CHASM cannot capture all this behavior by varying the SEB complexity, demonstrating the contribution to intermodel differences by hydrology and snow-related processes. Despite the increasing role of hydrology and snow in simulating processes at finer time scales, provided the constant surface resistance is included, CHASM's modes perform within the range of uncertainty illustrated by other Rhône-AGG models on seasonal and annual time scales.

Determinants of calcite flux in planktonic foraminifera on seasonal and interannual time scales

2020 ◽  
Author(s):  
Peter Kiss ◽  
Lukas Jonkers ◽  
Natália Hudáčková ◽  
Runa Turid Reuter ◽  
Michal Kučera
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Time Scale ◽  
Planktonic Foraminifera ◽  
Sediment Traps ◽  
Shell Size ◽  
Global Estimate ◽  
Export Flux ◽  
Species Specific ◽  
Annual Time

<p>Planktonic foraminifera precipitate calcareous shells, which after the death of the organisms are exported from the sea surface to the sea floor, where they are preserved on geologically relevant timescales. The export flux of planktonic foraminifera shells constitutes globally up to a half, and in the studied region off Cap Blanc (Atlantic Ocean) about one third, of the marine pelagic calcite flux. Given their importance for the marine calcite budget and for the pelagic carbonate counter pump, which counteracts the biological pump in terms of oceanic capacity for intake of CO<sub>2</sub>, it is crucial to gain an understanding of factors modulating the export flux of planktonic foraminifera calcite. In principle, variability in the export flux of planktonic foraminifera calcite could depend within one species on i) shell flux, ii) shell size and iii) calcification intensity, and where shell size and calcification intensity differ among species also on the species composition of the deposited assemblage. To assess the importance of these aspects in modulating the export flux of planktonic foraminifera calcite, we investigated two annual time series (from 1990-1991 and 2007-2008) from sediment traps moored in the Cap Blanc upwelling area. We assessed the predictability of foraminifera calcite flux variability on seasonal and interannual time scales, by determining the variability in species-specific shell fluxes, shell sizes and weights with bi-weekly resolution. We find a remarkable discrepancy in the contribution of the controlling factors between seasonal and interannual scales. On the seasonal time scale, 80% of the variability of the calcite flux is explained by shell flux. On the inter-annual time scale, on the other hand, variations in shell size and calcification intensity are key to explain the calcite flux, since the time series from 2007-2008 yielded 58% larger and 11% heavier specimens. These results imply that for the global estimate of planktonic foraminifera calcite flux, shell flux is likely the most relevant predictor. However, a prediction of the temporal evolution of the calcite flux will likely require estimates of changes in shell size and calcification intensity of the involved foraminifera species.</p>

scholarly journals At which time scale does the complementary principle perform best on evaporation estimation?

2020 ◽  
Author(s):  
Liming Wang ◽  
Songjun Han ◽  
Fuqiang Tian
Keyword(s):  
Uncertainty Analysis ◽  
Eddy Covariance ◽  
Time Scales ◽  
Time Scale ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Energy Correction ◽  
Independent Variable ◽  
The Difference ◽  
Annual Time

Abstract. The complementary principle has been widely used to estimate evaporation under different conditions. However, it remains unclear that at which time scale the complementary principle performs best. In this study, evaporation estimation was assessed over 88 eddy covariance (EC) monitoring sites at multiple time scales (daily, weekly, monthly, and yearly) by using the sigmoid and polynomial generalized complementary functions. The results indicate that the generalized complementary functions exhibit the highest skill in estimating evaporation at the monthly scale. The uncertainty analysis shows that this conclusion is not affected by ecosystem types nor energy correction methods. Through comparisons at multiple time scales, we found that the slight difference between the two generalized complementary functions only exists when the independent variable (x) in the functions approaches 1. The difference results in different performance of the two models at daily and weekly scales. However, such difference vanishes at monthly and annual time scales as few high x occurrences. This study demonstrates the applicability of the generalized complementary functions across multiple time scales and provides a reference for choosing the suitable timestep for evaporation estimation in relevant studies.

scholarly journals SPI-Based Spatiotemporal Drought over Sri Lanka

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
N. S. Abeysingha ◽  
U. R. L. N. Rajapaksha
Keyword(s):  
Sri Lanka ◽  
Time Scales ◽  
Time Scale ◽  
Standardized Precipitation Index ◽  
Annual Time Scale ◽  
Mk Test ◽  
Cropping Season ◽  
Thiessen Polygon ◽  
Slope Estimator ◽  
Annual Time

Drought is one of the most significant hazards in Sri Lanka. Status of drought in Sri Lanka was assessed using Standardized Precipitation Index (SPI) at 3, 6, and 12 months’ time scales using monthly rainfall (1970 to 2017) data of 54 weather stations. The frequency of drought events was evaluated using SPI, and trend of SPI was also detected using the Mann–Kendall (MK) test and Sen’s slope estimator. The result based on SPI identified hydrological years 1975-76, 1982-83, 1986-87, 1988-89, 2000-01, 2001-02, 2013-14, and 2016-17 as drought years for 52, 32, 35, 33, 33, 31, 31, and 31% of tested stations (54), respectively, at annual time scale. Comparison of the SPI at different time scales revealed that more drought events (SPI ≤ −1) occurred during Yala season than Maha cropping season. Considering the Thiessen polygon average rainfall, more frequent drought events occurred in the dry zone (57%) than the wet (49%) and intermediate zone (47%) at the annual time scale. SPI trend results showed greater increase in drought (59% of stations) during Yala seasons as compared to the Maha cropping season (15% of stations) in Sri Lanka.

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 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.

scholarly journals Fast Comparison of High-Precision Time Scales Using GNSS Receivers

2017 ◽  
Vol 2017 ◽  
pp. 1-4
Author(s):  
Vojtech Vigner ◽  
Jaroslav Roztocil
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
High Performance ◽  
Data Format ◽  
Common View ◽  
Log Files ◽  
Gnss Receivers ◽  
Precision Time ◽  
The Common ◽  
The Difference

Comparison of high-performance time scales generated by atomic clocks in laboratories of time and frequency metrology is usually performed by means of the Common View method. Laboratories are equipped with specialized GNSS receivers which measure the difference between a local time scale and a time scale of the selected satellite. Every receiver generates log files in CGGTTS data format to record measured differences. In order to calculate time differences recorded by two receivers, it is necessary to obtain these logs from both receivers and process them. This paper deals with automation and speeding up of these processes.

scholarly journals The Stability of Mars’s Annular Polar Vortex

2017 ◽  
Vol 74 (5) ◽  
pp. 1533-1547 ◽  
Author(s):  
William J. M. Seviour ◽  
Darryn W. Waugh ◽  
Richard K. Scott
Keyword(s):  
Relaxation Time ◽  
Time Scales ◽  
Time Scale ◽  
Thermal Relaxation ◽  
Polar Vortex ◽  
Radiative Relaxation ◽  
Equilibrium Profile ◽  
Rotating Shallow Water ◽  
The Stability ◽  
Topographic Forcing

Abstract The Martian polar atmosphere is known to have a persistent local minimum in potential vorticity (PV) near the winter pole, with a region of high PV encircling it. This finding is surprising, since an isolated band of PV is barotropically unstable, a result going back to Rayleigh. Here the stability of a Mars-like annular vortex is investigated using numerical integrations of the rotating shallow-water equations. The mode of instability and its growth rate is shown to depend upon the latitude and width of the annulus. By introducing thermal relaxation toward an annular equilibrium profile with a time scale similar to that of the instability, a persistent annular vortex with similar characteristics as that observed in the Martian atmosphere can be simulated. This time scale, typically 0.5–2 sols, is similar to radiative relaxation time scales for Mars’s polar atmosphere. The persistence of an annular vortex is also shown to be robust to topographic forcing, as long as it is below a certain amplitude. It is therefore proposed that the persistence of this barotropically unstable annular vortex is permitted owing to the combination of short radiative relaxation time scales and relatively weak topographic forcing in the Martian polar atmosphere.

Sign in / Sign up

Export Citation Format

Share Document