scholarly journals Interpolation uncertainty of atmospheric temperature radiosoundings

2020 ◽  
Author(s):  
Alessandro Fassò ◽  
Michael Sommer ◽  
Christoph von Rohden
Keyword(s):  
Missing Data ◽  
Standard Error ◽  
Cross Validation ◽  
Interpolation Method ◽  
Average Length ◽  
Linear Interpolation ◽  
Atmospheric Temperature ◽  
Radiosonde Data ◽  
Published Data ◽  
Set Up

Abstract. This paper is motivated by the fact that, although temperature readings made by Vaisala RS41 radiosondes at GRUAN sites (http://www.gruan.org) are given at 1 s resolution, for various reasons, missing data are spread along the atmospheric profile. Such a problem is quite common in radiosonde data and other profile data. Hence, (linear) interpolation is often used to fill the gaps in published data products. In this perspective, the present paper considers interpolation uncertainty. To do this, a statistical approach is introduced giving some understanding of the consequences of substituting missing data by interpolated ones. In particular, a general frame for the computation of interpolation uncertainty based on a Gaussian process (GP) set-up is developed. Using the GP characteristics, a simple formula for computing the linear interpolation standard error is given. Moreover, the GP interpolation is proposed as it provides an alternative interpolation method with its standard error. For the Vaisala RS41, the two approaches are shown to give similar interpolation performances using an extensive cross-validation approach based on the block-bootstrap technique. Statistical results about interpolation uncertainties at various GRUAN sites and for various missing gap lengths are provided. Since both provide an underestimation of the cross-validation interpolation uncertainty, a bootstrap-based correction formula is proposed. Using the root mean square error, it is found that, for short gaps, with an average length of 5 s, the average uncertainty is smaller than 0.10 K. For larger gaps, it increases up to 0.35 K for an average gap length of 30 s, and up to 0.58 K for a gap of 60 s.

scholarly journals Interpolation uncertainty of atmospheric temperature profiles

2020 ◽  
Vol 13 (12) ◽  
pp. 6445-6458
Author(s):  
Alessandro Fassò ◽  
Michael Sommer ◽  
Christoph von Rohden
Keyword(s):  
Missing Data ◽  
Standard Error ◽  
Interpolation Method ◽  
Average Length ◽  
Linear Interpolation ◽  
Atmospheric Temperature ◽  
Radiosonde Data ◽  
Published Data ◽  
Future Version ◽  
Set Up

Abstract. This paper is motivated by the fact that, although temperature readings made by Vaisala RS41 radiosondes at GRUAN sites (https://www.gruan.org/, last access: 30 November 2020) are given at 1 s resolution, for various reasons, missing data are spread along the atmospheric profile. Such a problem is quite common with radiosonde data and other profile data. Hence, (linear) interpolation is often used to fill the gaps in published data products. From this perspective, the present paper considers interpolation uncertainty, using a statistical approach to understand the consequences of substituting missing data with interpolated data. In particular, a general framework for the computation of interpolation uncertainty based on a Gaussian process (GP) set-up is developed. Using the GP characteristics, a simple formula for computing the linear interpolation standard error is given. Moreover, the GP interpolation is proposed as it provides an alternative interpolation method with its standard error. For the Vaisala RS41, the two approaches are shown to provide similar interpolation performances using an extensive cross-validation approach based on the block-bootstrap technique. Statistical results about interpolation uncertainty at various GRUAN sites and for various missing gap lengths are provided. Since both approaches result in an underestimation of the interpolation uncertainty, a bootstrap-based correction formula is proposed. Using the root mean square error, it is found that, for short gaps, with an average length of 5 s, the average uncertainty is less than 0.10 K. For larger gaps, it increases up to 0.35 K for an average gap length of 30 s and up to 0.58 K for a gap of 60 s. It is concluded that this approach could be implemented in a future version of the GRUAN data processing.

Study on Error in Interpolation Algorithm of the-5-DOF-Hybrid Robot

2013 ◽  
Vol 385-386 ◽  
pp. 695-698
Author(s):  
Ji Man Luo ◽  
Ming Shan Zhang ◽  
Yu Zhen An ◽  
Xiao Wei Sun
Keyword(s):  
Degrees Of Freedom ◽  
Convex Surface ◽  
Interpolation Method ◽  
Approximation Error ◽  
Linear Interpolation ◽  
Normal Vector ◽  
Interpolation Algorithm ◽  
Surface Machining ◽  
Set Up ◽  
Circular Interpolation

In order to improve the accuracy of the-5-DOF-hybrid robot motion control, it is necessary to establish a mathematical model of the error in the interpolation process. On the basis of the structure characteristics of five degrees of freedom hybrid robot and the algorithm of linear interpolation and circular interpolation, the error calculation patterns about the concave surface machining and convex surface machining are set up respectively in the paper. Then, examples are analyzed. The results show that the nonlinear error caused by using the straight-line interpolation method is much smaller than the normal vector rotation error and linear approximation error; when conducting surface machining, the error caused by the application of circular interpolation algorithm is less than linear interpolation error. By the comparison of the error analysis of different interpolation method, the control methods for reducing errors are proposed.

An experimental study on optimal spark timing control for improved performance of a flex fuel vehicle engine

2019 ◽  
Vol 234 (5) ◽  
pp. 1294-1303
Author(s):  
Junsang Yoo ◽  
Taeyong Lee ◽  
Pyungsik Go ◽  
Yongseok Cho ◽  
Kwangsoon Choi ◽  
...  
Keyword(s):  
Empirical Equation ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Combustion Characteristics ◽  
Combustion Stability ◽  
Timing Control ◽  
Vehicle Engine ◽  
Spark Timing ◽  
Linear Interpolation Method ◽  
Blended Fuels

In the American continent, the most frequently used alternative fuel is ethanol. Especially in Brazil, various blends of gasoline–ethanol fuels are widely spread. The vehicle using blended fuel is called flexible fuel vehicle. Because of several selections for the blending ratios in gas stations, the fuel properties may vary after refueling depending on a driver’s selection. Also, the combustion characteristics of the flexible fuel vehicle engine may change. In order to respond to the flexible fuel vehicle market in Brazil, a study on blended fuels is performed. The main purpose of this study is to enhance performance of the flexible fuel vehicle engine to target Brazilian market. Therefore, we investigated combustion characteristics and optimal spark timings of the blended fuels with various blending ratios to improve the performance of the flexible fuel vehicle engine. As a tool for prediction of the optimal spark timing for the 1.6L flexible fuel vehicle engine, the empirical equation was suggested. The validity of the equation was investigated by comparing the predicted optimal spark timings with the stock spark timings through engine tests. When the stock spark timings of E0 and E100 were optimal, the empirical equation predicted the actual optimal spark timings for blended fuels with a good accuracy. In all conditions, by optimizing spark timing control, performance was improved. Especially, torque improvements of E30 and E50 fuels were 5.4% and 1.8%, respectively, without affecting combustion stability. From these results, it was concluded that the linear interpolation method is not suitable for flexible fuel vehicle engine control. Instead of linear interpolation method, optimal spark timing which reflects specific octane numbers of gasoline–ethanol blended fuels should be applied to maximize performance of the flexible fuel vehicle engine. The results of this study are expected to save the effort required for engine calibration when developing new flexible fuel vehicle engines and to be used as a basic strategy to improve the performance of other flexible fuel vehicle engines.

Improved linear interpolation method for the estimation of snow-covered area from optical data

2002 ◽  
Vol 82 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Sari Metsämäki ◽  
Jenni Vepsäläinen ◽  
Jouni Pulliainen ◽  
Yrjö Sucksdorff
Keyword(s):  
Interpolation Method ◽  
Linear Interpolation ◽  
Optical Data ◽  
Snow Covered Area ◽  
Covered Area ◽  
Linear Interpolation Method

Study on Lidar Data Interpolation Method Based on GA-BP

2012 ◽  
Vol 588-589 ◽  
pp. 1312-1315
Author(s):  
Yi Kun Zhang ◽  
Ming Hui Zhang ◽  
Xin Hong Hei ◽  
Deng Xin Hua ◽  
Hao Chen
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Lidar Data ◽  
Data Interpolation ◽  
Interpolation Model ◽  
Genetic Method ◽  
Interpolation Accuracy ◽  
Linear Interpolation Method

Aiming at building a Lidar data interpolation model, this paper designs and implements a GA-BP interpolation method. The proposed method uses genetic method to optimize BP neural network, which greatly improves the calculation accuracy and convergence rate of BP neural network. Experimental results show that the proposed method has a higher interpolation accuracy compared with BP neural network as well as linear interpolation method.

Comparison of two gap-filling techniques for nitrous oxide fluxes from agricultural soil

2019 ◽  
Vol 99 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Rezvan Taki ◽  
Claudia Wagner-Riddle ◽  
Gary Parkin ◽  
Rob Gordon ◽  
Andrew VanderZaag
Keyword(s):  
Missing Values ◽  
Interpolation Method ◽  
Weather Conditions ◽  
Linear Interpolation ◽  
Bias Error ◽  
Research Station ◽  
Ann Model ◽  
Gap Filling ◽  
Adverse Weather ◽  
The Impact

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values <30%). However, with longer gaps (>20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

scholarly journals Seismic tomography of the Gulf of Corinth: a comparison of methods

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
E. Le Meur ◽  
J. Virieux ◽  
P. Podvin
Keyword(s):  
Linear System ◽  
Travel Time ◽  
Velocity Structure ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Linear Interpolation ◽  
Regular Grid ◽  
Partial Derivatives ◽  
Simultaneous Inversion ◽  
Gulf Of Corinth

At a local scale, travel-time tomography requires a simultaneous inversion of earthquake positions and velocity structure. We applied a joint iterative inversion scheme where medium parameters and hypocenter parameters were inverted simultaneously. At each step of the inversion, rays between hypocenters and stations were traced, new partial derivatives of travel-time were estimated and scaling between parameters was performed as well. The large sparse linear system modified by the scaling was solved by the LSQR method at each iteration. We compared performances of two different forward techniques. Our first approach was a fast ray tracing based on a paraxial method to solve the two-point boundary value problem. The rays connect sources and stations in a velocity structure described by a 3D B-spline interpolation over a regular grid. The second approach is the finite-difference solution of the eikonal equation with a 3D linear interpolation over a regular grid. The partial derivatives are estimated differently depending on the interpolation method. The reconstructed images are sensitive to the spatial variation of the partial derivatives shown by synthetic examples. We aldo found that a scaling between velocity and hypocenter parameters involved in the linear system to be solved is important in recovering accurate amplitudes of anomalies. This scaling was estimated to be five through synthetic examples with the real configuration of stations and sources. We also found it necessary to scale Pand S velocities in order to recover better amplitudes of S velocity anomaly. The crustal velocity structure of a 50X50X20 km domain near Patras in the Gulf of Corinth (Greece) was recovered using microearthquake data. These data were recorded during a field experiment in 1991 where a dense network of 60 digital stations was deployed. These microearthquakes were widely distributed under the Gulf of Corinth and enabled us to perform a reliable tomography of first arrival P and S travel-times. The obtained images of this seismically active zone show a south/north asymmetry in agreement with the tectonic context. The transition to high velocity lies between 6 km and 9 km indicating a very thin crust related to the active extension regime.At a local scale, travel-time tomography requires a simultaneous inversion of earthquake positions and velocity structure. We applied a joint iterative inversion scheme where medium parameters and hypocenter parameters were inverted simultaneously. At each step of the inversion, rays between hypocenters and stations were traced, new partial derivatives of travel-time were estimated and scaling between parameters was performed as well. The large sparse linear system modified by the scaling was solved by the LSQR method at each iteration. We compared performances of two different forward techniques. Our first approach was a fast ray tracing based on a paraxial method to solve the two-point boundary value problem. The rays connect sources and stations in a velocity structure described by a 3D B-spline interpolation over a regular grid. The second approach is the finite-difference solution of the eikonal equation with a 3D linear interpolation over a regular grid. The partial derivatives are estimated differently depending on the interpolation method. The reconstructed images are sensitive to the spatial variation of the partial derivatives shown by synthetic examples. We aldo found that a scaling between velocity and hypocenter parameters involved in the linear system to be solved is important in recovering accurate amplitudes of anomalies. This scaling was estimated to be five through synthetic examples with the real configuration of stations and sources. We also found it necessary to scale Pand S velocities in order to recover better amplitudes of S velocity anomaly. The crustal velocity structure of a 50X50X20 km domain near Patras in the Gulf of Corinth (Greece) was recovered using microearthquake data. These data were recorded during a field experiment in 1991 where a dense network of 60 digital stations was deployed. These microearthquakes were widely distributed under the Gulf of Corinth and enabled us to perform a reliable tomography of first arrival P and S travel-times. The obtained images of this seismically active zone show a south/north asymmetry in agreement with the tectonic context. The transition to high velocity lies between 6 km and 9 km indicating a very thin crust related to the active extension regime.

scholarly journals PROCESSING JUMP POINT OF LIDAR DETECTION DATA AND INVERSING THE AEROSOL EXTINCTION COEFFICIENT

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 227-232
Author(s):  
H. L. Zhang ◽  
H. Zhao ◽  
Y. P. Liu ◽  
X. K. Wang ◽  
C. Shu
Keyword(s):  
Atmospheric Aerosols ◽  
Extinction Coefficient ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Mie Scattering ◽  
Inversion Method ◽  
Aerosol Extinction ◽  
Detection Range ◽  
Long Time ◽  
Aerosol Extinction Coefficient

Abstract. For a long time, the research of the optical properties of atmospheric aerosols has aroused a wide concern in the field of atmospheric and environmental. Many scholars commonly use the Klett method to invert the lidar return signal of Mie scattering. However, there are always some negative values in the detection data of lidar, which have no actual meaning，and which are jump points. The jump points are also called wild value points and abnormal points. The jump points are refered to the detecting points that are significantly different from the surrounding detection points, and which are not consistent with the actual situation. As a result, when the far end point is selected as the boundary value, the inversion error is too large to successfully invert the extinction coefficient profile. These negative points are jump points, which must be removed in the inversion process. In order to solve the problem, a method of processing jump points of detection data of lidar and the inversion method of aerosol extinction coefficient is proposed in this paper. In this method, when there are few jump points, the linear interpolation method is used to process the jump points. When the number of continuous jump points is large, the function fitting method is used to process the jump points. The feasibility and reliability of this method are verified by using actual lidar data. The results show that the extinction coefficient profile can be successfully inverted when different remote boundary values are chosen. The extinction coefficient profile inverted by this method is more continuous and smoother. The effective detection range of lidar is greatly increased using this method. The extinction coefficient profile is more realistic. The extinction coefficient profile inverted by this method is more favorable to further analysis of the properties of atmospheric aerosol. Therefore, this method has great practical application and popularization value.

scholarly journals Reconstruction of the morphology and hydrography of the centre of Kraków before the mid-13th century

2020 ◽  
Vol 93 (1) ◽  
pp. 25-50 ◽  
Author(s):  
Adam Łajczak ◽  
Roksana Zarychta
Keyword(s):  
Cross Validation ◽  
Published Data ◽  
13Th Century ◽  
Digital Elevation ◽  
Geomorphological Map ◽  
Historic Centre ◽  
The Subject ◽  
Elevation Model ◽  
The Town ◽  
Surfer Software

The paper concerns investigations on urban geomorphology. The subject of the paper is the historic centre of Kraków (or Cracow) where the pre-human relief became masked due to the rapid increase in cultural deposits from the mid-13th century onwards. The aim of the investigation is the reconstruction of the original topography, relief and hydrography of this area based on rich sources of materials in papers and non-published data on geology, geoengineering, archaeology, history, and also on maps and panoramic drawings of the town. A digital elevation model has been generated, which showed the topography of the study area in the period before the mid-13th century. Structural analysis, cross validation test and estimation by ordinary kriging method were carried out. The final cartographic work was prepared with the use of QGIS and Surfer software. The distribution of landforms in the study area in the mid-13th century is presented as a proposed variant of the geomorphological map prepared by the authors. The former relief was evaluated in terms of its potential for encouraging settlement.

scholarly journals Extending access to care across the rural US south: Preliminary results from the Alabama eHealth programme

2018 ◽  
Vol 25 (5) ◽  
pp. 301-309
Author(s):  
Kriti M Jain ◽  
Prashanth Bhat ◽  
Cathy Maulsby ◽  
Alexandria Andersen ◽  
Tomas Soto ◽  
...  
Keyword(s):  
Missing Data ◽  
Antiretroviral Therapy ◽  
Rural Areas ◽  
Formative Evaluation ◽  
Social Innovation ◽  
People Living With Hiv ◽  
Viral Loads ◽  
Innovation Fund ◽  
Set Up ◽  
Hiv Continuum Of Care

Purpose Using a mixed-methods formative evaluation, the purpose of this study was to provide a broad overview of the Alabama eHealth programme set-up and initial patient outcomes. The Alabama eHealth programme uses telemedicine to provide medical care to people living with HIV in rural Alabama. It was led by a community-based organisation, Medical Advocacy and Outreach (MAO), and supported by AIDS United and the Corporation for National Community Service’s Social Innovation Fund with matching support from non-federal donors. Methods We conducted and transcribed in-depth interviews with Alabama eHealth staff and then performed directed content analysis. We also tracked patients’ ( n = 240) appointment attendance, CD4 counts, and viral loads. Findings Staff described the steps taken to establish the programme, associated challenges (e.g., costly, inadequate broadband in rural areas), and technology enabling this programme (electronic medical records, telemedicine equipment). Of all enrolled patients, 76% were retained in care, 88% had antiretroviral therapy and 75% had a suppressed viral load. Among patients without missing data, 96% were retained in care, 97% used antiretroviral therapy and 93% had suppressed viral loads. There were no statistically significant demographic differences between those with and without missing data. Conclusions Patients enrolled in a telemedicine programme evaluation successfully moved through the HIV continuum of care.

Sign in / Sign up

Export Citation Format

Share Document