Real-time radar-rain-gauge merging using spatio-temporal co-kriging with external drift in the alpine terrain of Switzerland

2013 ◽  
Vol 140 (680) ◽  
pp. 1097-1111 ◽  
Author(s):  
I. V. Sideris ◽  
M. Gabella ◽  
R. Erdin ◽  
U. Germann
Keyword(s):  
Real Time ◽  
Rain Gauge ◽  
Kriging With External Drift ◽  
Spatio Temporal ◽  
External Drift

scholarly journals Evaluation of IMERG Level-3 Products in Depicting the July to October Rainfall over Taiwan: Typhoon Versus Non-Typhoon

2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Advantages And Disadvantages ◽  
Level 3 ◽  
Spatio Temporal ◽  
Typhoon Season ◽  
Early Late ◽  
Better Than

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.

scholarly journals Spatial Interpolation for Real-Time Rainfall Field Estimation in Areas with Complex Topography

2013 ◽  
Vol 14 (1) ◽  
pp. 85-104 ◽  
Author(s):  
M. C. Rogelis ◽  
M. G. F. Werner
Keyword(s):  
Real Time ◽  
Ordinary Kriging ◽  
Kriging With External Drift ◽  
Time Operation ◽  
Spatially Distributed ◽  
Interpolation Procedure ◽  
Real Time Operation ◽  
Distributed Hydrological Models ◽  
Gaussian Simulation ◽  
External Drift

Abstract For many hydrological applications interpolation of point rainfall measurements is needed. One such application is flood early warning, particularly where spatially distributed hydrological models are used. Operation in real time poses challenges to the interpolation procedure, as this should then both be automatic and efficiently provide robust interpolation of gauged data. The differences in performance of ordinary kriging, universal kriging, and kriging with external drift with individual and pooled variograms were assessed for 139 daily datasets with significant precipitation in a study area in Bogotá, Colombia. Interpolators were compared using the percentage of variability explained and the root-mean-square error found in cross validation, aiming at identifying a procedure for real-time interpolation. The results showed that interpolators using pooled variograms provide a performance comparable to when the interpolators were applied to the storms individually, showing that they can be used successfully for interpolation in real-time operation in the study area. The analysis identified limitations in the use of kriging with external drift. Only when the adjusted R2 between the secondary variables and precipitation is higher than the percentage of variability explained found in ordinary kriging, then kriging with external drift provided a consistent improvement. This interpolator was found to give a lower performance in all other cases. The distribution of precipitation over basins of interest for each of the storms, derived through sampling rainfall fields generated through conditional Gaussian simulation, shows that, while differences between the interpolators may appear to be significant, the variability of the precipitation volume is less significant.

Soil water content interpolation using spatio-temporal kriging with external drift

Geoderma ◽  
2003 ◽  
Vol 112 (3-4) ◽  
pp. 253-271 ◽  
Author(s):  
J.J.J.C Snepvangers ◽  
G.B.M Heuvelink ◽  
J.A Huisman
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Kriging With External Drift ◽  
Spatio Temporal ◽  
External Drift

scholarly journals Spatial analysis of precipitation in a high-mountain region: exploring methods with multi-scale topographic predictors and circulation types

2014 ◽  
Vol 11 (5) ◽  
pp. 4639-4694 ◽  
Author(s):  
D. Masson ◽  
C. Frei
Keyword(s):  
Linear Regression ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
Rain Gauge ◽  
High Mountain ◽  
European Alps ◽  
Circulation Types ◽  
Kriging With External Drift ◽  
Single Predictor ◽  
External Drift

Abstract. Statistical models of the relationship between precipitation and topography are key elements for the spatial interpolation of rain-gauge measurements in high-mountain regions. This study investigates several extensions of the classical precipitation-height model in a direct comparison and within two popular interpolation frameworks, namely linear regression and kriging with external drift. The models studied include predictors of topographic height and slope, eventually at several spatial scales, a stratification by types of a circulation classification, and a predictor for wind-aligned topographic gradients. The benefit of the modeling components is investigated for the interpolation of seasonal mean and daily precipitation using leave-one-out crossvalidation. The study domain is a north-south cross-section of the European Alps (154 km × 187 km), which disposes of dense rain-gauge measurements (approx. 440 stations, 1971–2008). The significance of the topographic predictors was found to strongly depend on the interpolation framework. In linear regression predictors of slope and at multiple scales reduce interpolation errors substantially. But with as many as nine predictors the resulting interpolation still poorly replicates the across-ridge variation. Kriging with external drift (KED) leads to much smaller interpolation errors than linear regression. But this is achieved with a single predictor of local height already, and the extended predictor sets bring only marginal further improvement. Again, the stratification by circulation types and the wind-aligned gradient predictor do not improve over the single predictor KED model. Similarly for daily precipitation, information from circulation types is not improving interpolation accuracy. The results confirm that topographic predictors are essential for reducing interpolation errors, but exploiting the spatial autocorrelation in the data may be as effective as developing elaborate predictor sets. Our results also question a popular practice of using linear regression for predictor selection and they support the common practice of using climatological background fields in the interpolation of daily precipitation.

scholarly journals Real time rainfall estimation using microwave signals of cellular communication networks: a case study of Faisalabad, Pakistan

2018 ◽  
Author(s):  
Muhammad Sohail Afzal ◽  
Syed Hamid Hussain Shah ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Riaz Ahmad
Keyword(s):  
Water Balance ◽  
Real Time ◽  
Rainfall Intensity ◽  
Rain Gauge ◽  
Cellular Communication ◽  
Rainfall Estimation ◽  
Data Set ◽  
Spatial Error ◽  
Near Surface ◽  
Spatio Temporal

Abstract. Water balance estimate requires high spatio-temporal water balance components and rainfall is one of them. Rainfall is stochastic variable, which varies with respect to space and time. There are different methods for rainfall estimation such as rain gauge, satellite data but the resolution of these methods are very low, which cause over and underestimation of rainfall. A real time rainfall estimation mechanism is tested using commercial cellular networks in Faisalabad, district of Pakistan. The microwave links are used to quantify rainfall intensities and estimate rainfall at high spatio-temporal resolution. The attenuation in electromagnetic signals due to varying rainfall intensities is measured by taking difference between the power transmitted and power received during rainy period and is the measure of the path-averaged rainfall intensity. This rainfall related distortion is converted into rainfall intensity. This technique is applied on a standard microwave communication network used by a cellular communication system, comprising 35 microwave links, and it allow for observation of near-surface rainfall at the temporal resolutions of 15 min. Signal data-set of year 2012–2014 and 2015–2017 is used for calibration and validation respectively with three rain gauge data-set. The accuracy of the method is demonstrated by comparing the daily cumulative rainfall depth of University of Agriculture Faisalabad rain gauge (UAF-RG), Ayub Agriculture Research rain gauge(AR-RG) and Water and Sanitation Authority rain gauge (WASA-RG) with link based rainfall depths estimated from L2, L28 and L34 respectively, reaching r2 up to 0.97. UAF-RG is considered reference to study the spatial variability of rainfall of all the selected links within the study area, observed 10 %–60 % average spatial error of all links with the reference UAF-RG. All the results show that microwave links are potentially useful compared to the low resolution methods of rainfall estimation and can be used for effective water resources management.

The Importance of Rainfall Distribution in Urban Drainage Operation

1992 ◽  
Vol 23 (2) ◽  
pp. 121-136 ◽  
Author(s):  
Fons Nelen ◽  
Annemarieke Mooijman ◽  
Per Jacobsen
Keyword(s):  
Real Time ◽  
Treatment Plant ◽  
Rain Gauge ◽  
Point Of View ◽  
Rain Event ◽  
Real Time Control ◽  
Rainfall Distribution ◽  
Statistical Point ◽  
Time Control ◽  
Spatially Distributed

A control simulation model, called LOCUS, is used to investigate the effects of spatially distributed rain and the possibilities to benefit from this phenomenon by means of real time control. The study is undertaken for a catchment in Copenhagen, where rainfall is measured with a network of 8 rain gauges. Simulation of a single rain event, which is assumed to be homogeneous, i.e. using one rain gauge for the whole catchment, leads to large over- and underestimates of the systems output variables. Therefore, when analyzing a single event the highest possible degree of rainfall information may be desired. Time-series simulations are performed for both an uncontrolled and a controlled system. It is shown that from a statistical point of view, rainfall distribution is NOT significant concerning the probability of occurrence of an overflow. The main contributing factor to the potential of real time control, concerning minimizing overflows, is to be found in the system itself, i.e. the distribution of available storage and discharge capacity. When other operational objectives are involved, e.g., to minimize peak flows to the treatment plant, rainfall distribution may be an important factor.

Passthrough+

2020 ◽  
Vol 3 (1) ◽  
pp. 1-17
Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
View Synthesis ◽  
Performance Constraints ◽  
Trade Offs ◽  
Stereoscopic View ◽  
Target User ◽  
Spatio Temporal ◽  
And Performance ◽  
3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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