The Medium-to-Short-Term Earthquake Predictions in China and Their Evaluations Based on the R-Score

2021 ◽  
Author(s):  
Huaizhong Yu ◽  
Zhengyi Yuan ◽  
Chen Yu ◽  
Xiaotao Zhang ◽  
Rong Gao ◽  
...  
Keyword(s):  
Time Scale ◽  
Time Windows ◽  
Considerable Proportion ◽  
Short Term ◽  
Hit Rate ◽  
Forward Prediction ◽  
Prediction Time ◽  
Earthquake Predictions ◽  
Score Method ◽  
China Earthquake

Abstract The earthquake tendency consultations in China, which have been carried out by the China Earthquake Administration for more than 40 yr, are really forward prediction of earthquakes. The results, experiences, and data accumulation are valuable for seismic researches. In this article, the annual, monthly, and weekly predictions produced by the regular earthquake tendency consultations and the rapid postearthquake tendency prediction derived from the irregular ones are presented systematically. In the regular predictions, the areas where earthquakes tend to occur are identified by specific space–time windows. To evaluate the efficiency of the predictions, we apply the R-score method to all the medium-to-short-term efforts. The R-score has been used as a routine tool to test annual predictions in China, in which the hit rate and the percentage of spatial alarms over the whole territory are taken into consideration. Results show that the annual R-scores, during the period of 1990–2020, increased gradually, with the average of 0.293. The examples in 2018 indicate that a considerable proportion of earthquakes with the Ms 5.0 and above were detected by the annual prediction; some earthquakes were detected by the monthly prediction, whereas just only a few earthquakes could be detected by the weekly prediction. The corresponding R-scores are 0.46, 0.11, and 0.002, decreasing obviously with reduction of the prediction time windows, and the smallest one, which is very close to zero, may suggest the minimum time scale for an effective earthquake prediction. We also evaluated efficiency of the irregular predictions by analyzing the practices of 29 Ms≥5.0 earthquakes since January 2019 and found that it is highly possible to do rapid postearthquake tendency prediction in China.

scholarly journals Exploring the Effects of COVID-19 Containment Policies on Crime: An Empirical Analysis of the Short-term Aftermath in Los Angeles

2020 ◽  
Author(s):  
Gian Maria Campedelli ◽  
Alberto Aziani ◽  
Serena Favarin
Keyword(s):  
Los Angeles ◽  
Time Windows ◽  
Intimate Partner ◽  
Policy Implications ◽  
Crime Trends ◽  
Short Term ◽  
Post Intervention ◽  
Structural Time Series ◽  
Deadly Weapon ◽  
Partner Assault

This work investigates whether and how COVID-19 containment policies had an immediate impact on crime trends in Los Angeles. The analysis is conducted using Bayesian structural time-series and focuses on nine crime categories and on the overall crime count, daily monitored from January 1st 2017 to March 28th 2020. We concentrate on two post-intervention time windows—from March 4th to March 16th and from March 4\textsuperscript{th} to March 28th 2020—to dynamically assess the short-term effects of mild and strict policies. In Los Angeles, overall crime has significantly decreased, as well as robbery, shoplifting, theft, and battery. No significant effect has been detected for vehicle theft, burglary, assault with a deadly weapon, intimate partner assault, and homicide. Results suggest that, in the first weeks after the interventions are put in place, social distancing impacts more directly on instrumental and less serious crimes. Policy implications are also discussed.

scholarly journals Precise Point Positioning for TAI Computation

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Gérard Petit ◽  
Zhiheng Jiang
Keyword(s):  
Time Scale ◽  
Carrier Phase ◽  
Precise Point Positioning ◽  
Dual Frequency ◽  
Time Transfer ◽  
Short Term ◽  
Reference Time ◽  
Local Clock ◽  
Point Positioning ◽  
Simple Difference

We discuss the use of some new time transfer techniques for computing TAI time links. Precise point positioning (PPP) uses GPS dual frequency carrier phase and code measurements to compute the link between a local clock and a reference time scale with the precision of the carrier phase and the accuracy of the code. The time link between any two stations can then be computed by a simple difference. We show that this technique is well adapted and has better short-term stability than other techniques used in TAI. We present a method of combining PPP and two-way time transfer that takes advantage of the qualities of each technique, and shows that it would bring significant improvement to TAI links.

scholarly journals Effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan

2018 ◽  
Vol 78 (5) ◽  
pp. 592-610 ◽  
Author(s):  
Abbas Ali Chandio ◽  
Yuansheng Jiang ◽  
Feng Wei ◽  
Xu Guangshun
Keyword(s):  
Wheat Yield ◽  
Considerable Proportion ◽  
Small Scale ◽  
Small Farms ◽  
Short Term ◽  
Agricultural Credit ◽  
Data Set ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan. Design/methodology/approach The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach. Findings This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years. Research limitations/implications In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well. Originality/value This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

DETERMINATION OF PROTEIN SYNTHESIS IN RAINBOW TROUT, ONCORHYNCHUS MYKISS, USING A STABLE ISOTOPE

1994 ◽  
Vol 189 (1) ◽  
pp. 279-284
Author(s):  
C Carter ◽  
S Owen ◽  
Z He ◽  
P Watt ◽  
C Scrimgeour ◽  
...  
Keyword(s):  
Amino Acids ◽  
Protein Synthesis ◽  
Rainbow Trout ◽  
Amino Acid ◽  
Oncorhynchus Mykiss ◽  
Considerable Proportion ◽  
Published Data ◽  
Short Term ◽  
Terrestrial Mammals ◽  
Rainbow Trout Oncorhynchus Mykiss

It has been suggested (Houlihan, 1991) that the consumption of 1 g of protein in a variety of species of fish stimulates the synthesis of, approximately, an equal amount of protein. Although synthesis of protein may account for as much as 40 % of the whole-animal oxygen consumption (Lyndon et al. 1992), only about 30 % of the synthesized proteins are retained as growth (Houlihan et al. 1988; Carter et al. 1993a,b). Thus, one focus of attention is the potential advantage gained by fish in allocating a considerable proportion of assimilated energy to protein turnover in contrast to relatively low-cost, low-turnover protein growth (Houlihan et al. 1993). Rates of protein synthesis in several species of fish have been measured using radioactively labelled amino acids, frequently given as a flooding dose (reviewed by Fauconneau, 1985; Houlihan, 1991). These measurements cannot be made for longer than a few hours because of the decline in specific radioactivity in the amino acid free pool. However, as protein synthesis rates vary during the course of a day as a result of the post-prandial stimulation, and since radiolabelled amino acid methodology is invasive, short-term and terminal, it has been difficult to be certain of the relationship between protein growth measured in the long term and protein synthesis rates measured in the short term. This paper addresses these problems by developing a method using 15N in orally administered protein to measure protein synthesis rates in fish over relatively long periods, the aim being to use procedures that are as non-invasive and repeatable as possible. The use of stable isotopes to measure protein metabolism is well established in terrestrial mammals (see Rennie et al. 1991; Wolfe, 1992), but to our knowledge the only published data for aquatic ectotherms are on the blue mussel (Mytilus edulis L.) (Hawkins, 1985). In the present study, rates of protein synthesis of individual rainbow trout [Oncorhynchus mykiss (Walbaum)] were calculated from the enrichment of excreted ammonia with 15N over the 48 h following the feeding of a single meal (dose) containing protein uniformly labelled with 15N by use of an end-point stochastic model (Waterlow et al. 1978; Wolfe, 1992). Application of this type of modelling would appear to be ideal for measuring ammonotelic fish nitrogen metabolism since, unlike the situation in mammals, the catabolic flux of amino acids through urea is very small. Further, ammonia is excreted directly into the surrounding water via the gills and is not stored for any length of time, in contrast to the situation in mammals, so the rate of tracer appearance is easily measurable.

scholarly journals Short-term volcano-tectonic earthquake forecasts based on a MRT algorithm: the El Hierro seismo-volcanic crisis experience

2016 ◽  
Author(s):  
A. García ◽  
S. De La Cruz-Reyna ◽  
J. M. Marrero ◽  
R. Ortiz
Keyword(s):  
Time Windows ◽  
Decision Makers ◽  
Recurrence Time ◽  
Large Magnitude ◽  
Short Term ◽  
Tectonic Earthquake ◽  
El Hierro ◽  
Tectonic Earthquakes ◽  
Volcanic Islands ◽  
Repetitive Pattern

Abstract. Under certain conditions volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behavior that may allow forecasting the occurrence and magnitude of major events. Thus govern-mental decision-makers can be supplied of warnings of the increased probability of larger-magnitude earthquakes in the short term time-scale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a Mean Recurrence Time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10 day time-windows, of volcano-tectonic earthquakes

scholarly journals Tipping points of Mississippi Delta marshes due to accelerated sea-level rise

2020 ◽  
Vol 6 (21) ◽  
pp. eaaz5512 ◽  
Author(s):  
Torbjörn E. Törnqvist ◽  
Krista L. Jankowski ◽  
Yong-Xiang Li ◽  
Juan L. González
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Mississippi Delta ◽  
Time Windows ◽  
Open Water ◽  
Tipping Points ◽  
Coastal Marshes ◽  
Short Term ◽  
Global Sea Level ◽  
Coastal Louisiana

Coastal marshes are threatened by relative sea-level (RSL) rise, yet recent studies predict marsh survival even under the high rates of RSL rise expected later in this century. However, because these studies are mostly based on short-term records, uncertainty persists about the longer-term vulnerability of coastal marshes. We present an 8500-year-long marsh record from the Mississippi Delta, showing that at rates of RSL rise exceeding 6 to 9 mm year−1, marsh conversion into open water occurs in about 50 years. At rates of RSL rise exceeding ~3 mm year−1, marsh drowning occurs within a few centuries. Because present-day rates of global sea-level rise already surpass this rate, submergence of the remaining ~15,000 km2 of marshland in coastal Louisiana is probably inevitable. RSL-driven tipping points for marsh drowning vary geographically, and those for the Mississippi Delta may be lower than elsewhere. Nevertheless, our findings highlight the need for consideration of longer time windows in determining the vulnerability of coastal marshes worldwide.

scholarly journals Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales

2019 ◽  
Vol 20 (6) ◽  
pp. 1165-1182 ◽  
Author(s):  
Kaighin A. McColl ◽  
Qing He ◽  
Hui Lu ◽  
Dara Entekhabi
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Time Scale ◽  
Surface Soil ◽  
Satellite Observations ◽  
Surface Soil Moisture ◽  
Short Term ◽  
Term Memory ◽  
Memory Time

Abstract Land–atmosphere feedbacks occurring on daily to weekly time scales can magnify the intensity and duration of extreme weather events, such as droughts, heat waves, and convective storms. For such feedbacks to occur, the coupled land–atmosphere system must exhibit sufficient memory of soil moisture anomalies associated with the extreme event. The soil moisture autocorrelation e-folding time scale has been used previously to estimate soil moisture memory. However, the theoretical basis for this metric (i.e., that the land water budget is reasonably approximated by a red noise process) does not apply at finer spatial and temporal resolutions relevant to modern satellite observations and models. In this study, two memory time scale metrics are introduced that are relevant to modern satellite observations and models: the “long-term memory” τL and the “short-term memory” τS. Short- and long-term surface soil moisture (SSM) memory time scales are spatially anticorrelated at global scales in both a model and satellite observations, suggesting hot spots of land–atmosphere coupling will be located in different regions, depending on the time scale of the feedback. Furthermore, the spatial anticorrelation between τS and τL demonstrates the importance of characterizing these memory time scales separately, rather than mixing them as in previous studies.

scholarly journals Temporal and spatial analysis of ozone concentrations in Europe based on time scale decomposition and a multi-clustering approach

2019 ◽  
Author(s):  
Eirini Boleti ◽  
Christoph Hueglin ◽  
Stuart K. Grange ◽  
André S. H. Prévôt ◽  
Satoshi Takahama
Keyword(s):  
Time Scale ◽  
Seasonal Cycle ◽  
Clustering Algorithm ◽  
Short Term ◽  
Ozone Concentrations ◽  
Time Period ◽  
Term Variation ◽  
Long Term Trends ◽  
Time Scale Decomposition

Abstract. Air quality measures that were implemented in Europe in the 1990s resulted in reductions of ozone precursors concentrations. In this study, the effect of these reductions on ozone is investigated by analyzing surface measurements of ozone for the time period between 2000 and 2015. Using a non-parametric time scale decomposition methodology, the long-term, seasonal and short-term variation of ozone observations were extracted. A clustering algorithm was applied to the different time scale variations, leading to a classification of sites across Europe based on the temporal characteristics of ozone. The clustering based on the long-term variation resulted in a site type classification, while a regional classification was obtained based on the seasonal and short-term variations. Long-term trends of de-seasonalized mean and meteo-adjusted peak ozone concentrations were calculated across large parts of Europe for the time period 2000–2015. A multi-dimensional scheme was used for a detailed trend analysis, based on the identified clusters, which reflect precursor emissions and meteorological influence either on the inter-annual or the short-term time scale. Decreasing mean ozone concentrations at rural sites and increasing or stabilizing at urban sites were observed. At the same time downward trends for peak ozone concentrations were detected for all site types. The effect of hemispheric transport of ozone can be seen either in regions affected by synoptic patterns in the northern Atlantic or at sites located at remote high altitude locations. In addition, a reduction of the amplitude in the seasonal cycle of ozone was observed, and a shift in the occurrence of the seasonal maximum towards earlier time of the year. Finally, a reduced sensitivity of ozone to temperature was identified. It was concluded that long-term trends of mean and peak ozone concentrations are mostly controlled by precursors emissions changes, while seasonal cycle trends and changes in the sensitivity of ozone to temperature are driven by regional climatic conditions.

scholarly journals Spectral evolution of weakly nonlinear random waves: kinetic description versus direct numerical simulations

2018 ◽  
Vol 844 ◽  
pp. 766-795 ◽  
Author(s):  
Sergei Y. Annenkov ◽  
Victor I. Shrira
Keyword(s):  
Time Scale ◽  
Kinetic Equations ◽  
Wave Spectra ◽  
Kinetic Description ◽  
Spectral Evolution ◽  
Short Term ◽  
Weakly Nonlinear ◽  
Term Evolution ◽  
Integral Characteristics

Kinetic equations are widely used in many branches of science to describe the evolution of random wave spectra. To examine the validity of these equations, we study numerically the long-term evolution of water wave spectra without wind input using three different models. The first model is the classical kinetic (Hasselmann) equation (KE). The second model is the generalised kinetic equation (gKE), derived employing the same statistical closure as the KE but without the assumption of quasistationarity. The third model, which we refer to as the DNS-ZE, is a direct numerical simulation algorithm based on the Zakharov integrodifferential equation, which plays the role of the primitive equation for a weakly nonlinear wave field. It does not employ any statistical assumptions. We perform a comparison of the spectral evolution of the same initial distributions without forcing, with/without a statistical closure and with/without the quasistationarity assumption. For the initial conditions, we choose two narrow-banded spectra with the same frequency distribution and different degrees of directionality. The short-term evolution ($O(10^{2})$ wave periods) of both spectra has been previously thoroughly studied experimentally and numerically using a variety of approaches. Our DNS-ZE results are validated both with existing short-term DNS by other methods and with available laboratory observations of higher-order moment (kurtosis) evolution. All three models demonstrate very close evolution of integral characteristics of the spectra, approaching with time the theoretical asymptotes of the self-similar stage of evolution. Both kinetic equations give almost identical spectral evolution, unless the spectrum is initially too narrow in angle. However, there are major differences between the DNS-ZE and gKE/KE predictions. First, the rate of angular broadening of initially narrow angular distributions is much larger for the gKE and KE than for the DNS-ZE, although the angular width does appear to tend to the same universal value at large times. Second, the shapes of the frequency spectra differ substantially (even when the nonlinearity is decreased), the DNS-ZE spectra being wider than the KE/gKE ones and having much lower spectral peaks. Third, the maximal rates of change of the spectra obtained with the DNS-ZE scale as the fourth power of nonlinearity, which corresponds to the dynamical time scale of evolution, rather than the sixth power of nonlinearity typical of the kinetic time scale exhibited by the KE. The gKE predictions fall in between. While the long-term DNS show excellent agreement with the KE predictions for integral characteristics of evolving wave spectra, the striking systematic discrepancies for a number of specific spectral characteristics call for revision of the fundamentals of the wave kinetic description.

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