scholarly journals Dynamics of intense convective rain cells

2005 ◽  
Vol 2 ◽  
pp. 1-6 ◽  
Author(s):  
A. Parodi
Keyword(s):  
Point Of View ◽  
Moist Convection ◽  
Feedback Mechanisms ◽  
Convective Rain ◽  
Temporal Properties ◽  
Spatio Temporal ◽  
Deep Moist Convection ◽  
Convective Cells ◽  
Critical Constraints ◽  
Precipitation Events

Abstract. Intense precipitation events are often convective in nature. A deeper understanding of the properties and the dynamics of convective rain cells is, therefore, necessary both from a physical and operational point of view. The aim of this work is to study the spatial-temporal properties of convective rain cells by using a fully parameterized nonhydrostatic code (Lokal Model) in simplified model configurations. High resolution simulations are performed and it is expected that the deep moist convection and the feedback mechanisms affecting larger scales of motion can then be resolved explicitly and some of the critical constraints of parameterization schemes can be relaxed. The sensitivity of the spatio-temporal properties of simulated cells to spatial resolution and microphysics schemes is investigated and discussed through a direct comparison with typical intense convective cells measured by radars.

scholarly journals Using Ensemble Data Assimilation to Explore the Environmental Controls on the Initiation and Predictability of Moist Convection

2021 ◽  
Keyword(s):  
Water Vapor ◽  
Lead Time ◽  
Weather Prediction ◽  
Convective System ◽  
Convective Activity ◽  
Moist Convection ◽  
Convective Storms ◽  
Environmental Controls ◽  
Deep Moist Convection ◽  
Convective Cells

Abstract Atmospheric deep moist convection has emerged as one of the most challenging topics for numerical weather prediction, due to its chaotic process of development and multi-scale physical interactions. This study examines the dynamics and predictability of a weakly organized linear convective system using convection permitting EnKF analysis and forecasts with assimilating all-sky satellite radiances from a water vapor sensitive band of the Advanced Baseline Imager on GOES-16. The case chosen occurred over the Gulf of Mexico on 11 June 2017 during the NASA Convective Processes Experiment (CPEX) field campaign. Analysis of the water vapor and dynamic ensemble covariance structures revealed that meso-α (2000-200 km) and meso-β (200-20 km) scale initial features helped to constrain the general location of convection with a few hours of lead time, contributing to enhancing convective activity, but meso-γ (20-2 km) or even smaller scale features with less than 30-minute lead time were identified to be essential for capturing individual convective storms. The impacts of meso-α scale initial features on the prediction of particular individual convective cells were found to be classified into two regimes; in a relatively dry regime, the meso-α scale environment needs to be moist enough to support the development of the convection of interest, but in a relatively wet regime, a drier meso-α scale environment is preferable to suppress the surrounding convective activity. This study highlights the importance of high-resolution initialization of moisture fields for the prediction of a quasi-linear tropical convective system, as well as demonstrating the accuracy that may be necessary to predict convection exactly when and where it occurs.

Spatial-temporal data collection process models using mobile sinks

2019 ◽  
Vol 942 (12) ◽  
pp. 22-28
Author(s):  
A.V. Materuhin ◽  
V.V. Shakhov ◽  
O.D. Sokolova
Keyword(s):  
Energy Consumption ◽  
Operation Time ◽  
Point Of View ◽  
Process Models ◽  
Temporal Data ◽  
Network Nodes ◽  
Mobile Sinks ◽  
Autonomous Operation ◽  
Data Collection Process ◽  
Spatio Temporal

Optimization of energy consumption in geosensor networks is a very important factor in ensuring stability, since geosensors used for environmental monitoring have limited possibilities for recharging batteries. The article is a concise presentation of the research results in the area of increasing the energy consumption efficiency for the process of collecting spatio-temporal data with wireless geosensor networks. It is shown that in the currently used configurations of geosensor networks there is a predominant direction of the transmitted traffic, which leads to the fact that through the routing nodes that are close to the sinks, a much more traffic passes than through other network nodes. Thus, an imbalance of energy consumption arises in the network, which leads to a decrease in the autonomous operation time of the entire wireless geosensor networks. It is proposed to use the possible mobility of sinks as an optimization resource. A mathematical model for the analysis of the lifetime of a wireless geosensor network using mobile sinks is proposed. The model is analyzed from the point of view of optimization energy consumption by sensors. The proposed approach allows increasing the lifetime of wireless geosensor networks by optimizing the relocation of mobile sinks.

scholarly journals A spatio-temporal specification language and its completeness & decidability

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Tengfei Li ◽  
Jing Liu ◽  
Haiying Sun ◽  
Xiang Chen ◽  
Lipeng Zhang ◽  
...  
Keyword(s):  
Intelligent Transportation System ◽  
Cyber Physical Systems ◽  
Specification Language ◽  
Finite Model ◽  
Critical Systems ◽  
Physical Systems ◽  
Spatial Objects ◽  
Temporal Properties ◽  
Spatio Temporal ◽  
Temporal Specification

AbstractIn the past few years, significant progress has been made on spatio-temporal cyber-physical systems in achieving spatio-temporal properties on several long-standing tasks. With the broader specification of spatio-temporal properties on various applications, the concerns over their spatio-temporal logics have been raised in public, especially after the widely reported safety-critical systems involving self-driving cars, intelligent transportation system, image processing. In this paper, we present a spatio-temporal specification language, STSL PC, by combining Signal Temporal Logic (STL) with a spatial logic S4 u, to characterize spatio-temporal dynamic behaviors of cyber-physical systems. This language is highly expressive: it allows the description of quantitative signals, by expressing spatio-temporal traces over real valued signals in dense time, and Boolean signals, by constraining values of spatial objects across threshold predicates. STSL PC combines the power of temporal modalities and spatial operators, and enjoys important properties such as finite model property. We provide a Hilbert-style axiomatization for the proposed STSL PC and prove the soundness and completeness by the spatio-temporal extension of maximal consistent set and canonical model. Further, we demonstrate the decidability of STSL PC and analyze the complexity of STSL PC. Besides, we generalize STSL to the evolution of spatial objects over time, called STSL OC, and provide the proof of its axiomatization system and decidability.

scholarly journals Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 238
Author(s):  
Pablo Contreras ◽  
Johanna Orellana-Alvear ◽  
Paul Muñoz ◽  
Jörg Bendix ◽  
Rolando Célleri
Keyword(s):  
Random Forest ◽  
Model Performance ◽  
Early Warning Systems ◽  
Point Of View ◽  
Lead Times ◽  
Physical Parameters ◽  
Runoff Forecasting ◽  
Spatio Temporal ◽  
Improved Model ◽  
Search Approach

The Random Forest (RF) algorithm, a decision-tree-based technique, has become a promising approach for applications addressing runoff forecasting in remote areas. This machine learning approach can overcome the limitations of scarce spatio-temporal data and physical parameters needed for process-based hydrological models. However, the influence of RF hyperparameters is still uncertain and needs to be explored. Therefore, the aim of this study is to analyze the sensitivity of RF runoff forecasting models of varying lead time to the hyperparameters of the algorithm. For this, models were trained by using (a) default and (b) extensive hyperparameter combinations through a grid-search approach that allow reaching the optimal set. Model performances were assessed based on the R2, %Bias, and RMSE metrics. We found that: (i) The most influencing hyperparameter is the number of trees in the forest, however the combination of the depth of the tree and the number of features hyperparameters produced the highest variability-instability on the models. (ii) Hyperparameter optimization significantly improved model performance for higher lead times (12- and 24-h). For instance, the performance of the 12-h forecasting model under default RF hyperparameters improved to R2 = 0.41 after optimization (gain of 0.17). However, for short lead times (4-h) there was no significant model improvement (0.69 < R2 < 0.70). (iii) There is a range of values for each hyperparameter in which the performance of the model is not significantly affected but remains close to the optimal. Thus, a compromise between hyperparameter interactions (i.e., their values) can produce similar high model performances. Model improvements after optimization can be explained from a hydrological point of view, the generalization ability for lead times larger than the concentration time of the catchment tend to rely more on hyperparameterization than in what they can learn from the input data. This insight can help in the development of operational early warning systems.

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

Spatio-temporal visual properties in the ascending tectofugal system

2010 ◽  
Vol 5 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Alice Rokszin ◽  
Zita Márkus ◽  
Gábor Braunitzer ◽  
Antal Berényi ◽  
Marek Wypych ◽  
...  
Keyword(s):  
Visual Information ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Neuronal Population ◽  
Neuronal Responses ◽  
Temporal Properties ◽  
Visual Receptive Field ◽  
Detailed Statistical Analysis ◽  
Spatio Temporal ◽  
Visual Properties

AbstractOur study compares the spatio-temporal visual receptive field properties of different subcortical stages of the ascending tectofugal visual system. Extracellular single-cell recordings were performed in the superficial (SCs) and intermediate (SCi) layers of the superior colliculus (SC), the suprageniculate nucleus (Sg) of the posterior thalamus and the caudate nucleus (CN) of halothane-anesthetized cats. Neuronal responses to drifting gratings of various spatial and temporal frequencies were recorded. The neurons of each structure responded optimally to low spatial and high temporal frequencies and displayed narrow spatial and temporal frequency tuning. The detailed statistical analysis revealed that according to its stimulus preferences the SCs has markedly different spatio-temporal properties from the homogeneous group formed by the SCi, Sg and CN. The SCs neurons preferred higher spatial and lower temporal frequencies and had broader spatial tuning than the other structures. In contrast to the SCs the visually active SCi, as well as the Sg and the CN neurons possessed consequently similar spatio-temporal preferences. These data support our hypothesis that the visually active SCi, Sg and CN neurons form a homogeneous neuronal population given a similar spatio-temporal frequency preference and a common function in processing of dynamic visual information.

scholarly journals From Loschmidt daemons to time-reversed waves

2016 ◽  
Vol 374 (2069) ◽  
pp. 20150156 ◽  
Author(s):  
Mathias Fink
Keyword(s):  
Wave Propagation ◽  
Time Reversal ◽  
Degrees Of Freedom ◽  
Point Of View ◽  
Propagation Time ◽  
Reversal Invariance ◽  
Spatial Boundary ◽  
Dual Approaches ◽  
Spatio Temporal

Time-reversal invariance can be exploited in wave physics to control wave propagation in complex media. Because time and space play a similar role in wave propagation, time-reversed waves can be obtained by manipulating spatial boundaries or by manipulating time boundaries. The two dual approaches will be discussed in this paper. The first approach uses ‘time-reversal mirrors’ with a wave manipulation along a spatial boundary sampled by a finite number of antennas. Related to this method, the role of the spatio-temporal degrees of freedom of the wavefield will be emphasized. In a second approach, waves are manipulated from a time boundary and we show that ‘instantaneous time mirrors’, mimicking the Loschmidt point of view, simultaneously acting in the entire space at once can also radiate time-reversed waves.

Spatio-temporal properties of oculomotor activation by multiple, simultaneous peripheral stimuli

2021 ◽  
Vol 188 ◽  
pp. 251-261
Author(s):  
John Christie ◽  
Matthew D. Hilchey ◽  
Raymond M. Klein
Keyword(s):  
Temporal Properties ◽  
Spatio Temporal

Quasi-idealized numerical simulations of processes involved in orogenic convection initiation over the Sierras de Córdoba mountains

2021 ◽  
Author(s):  
Christopher A. Davis
Keyword(s):  
Numerical Simulations ◽  
Mountain Range ◽  
Moist Convection ◽  
Low Level ◽  
Physical Mechanisms ◽  
Convergence Line ◽  
Synoptic Conditions ◽  
Deep Moist Convection ◽  
Outflow Boundary ◽  
Convection Initiation

Abstract The Sierras de Córdoba (SDC) mountain range in Argentina is a hotspot of deep moist convection initiation (CI). Radar climatology indicates that 44% of daytime CI events that occur near the SDC in spring and summer seasons and that are not associated with the passage of a cold front or an outflow boundary involve a northerly LLJ, and these events tend to preferentially occur over the southeast quadrant of the main ridge of the SDC. To investigate the physical mechanisms acting to cause CI, idealized convection-permitting numerical simulations with a horizontal grid spacing of 1 km were conducted using CM1. The sounding used for initializing the model featured a strong northerly LLJ, with synoptic conditions resembling those in a previously postulated conceptual model of CI over the region, making it a canonical case study. Differential heating of the mountain caused by solar insolation in conjunction with the low-level northerly flow sets up a convergence line on the eastern slopes of the SDC. The southern portion of this line experiences significant reduction in convective inhibition, and CI occurs over the SDC southeast quadrant. Thesimulated storm soon acquires supercellular characteristics, as observed. Additional simulations with varying LLJ strength also show CI over the southeast quadrant. A simulation without background flow generated convergence over the ridgeline, with widespread CI across the entire ridgeline. A simulation with mid- and upper-tropospheric westerlies removed indicates that CI is minimally influenced by gravity waves. We conclude that the low-level jet is sufficient to focus convection initiation over the southeast quadrant of the ridge.

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