scholarly journals Improving Quantitative Rainfall Prediction Using Ensemble Analogues in the Tropics: Case study of Uganda

2017 ◽  
Author(s):  
Isaac Mugume ◽  
Michel d. S. Mesquita ◽  
Yazidhi Bamutaze ◽  
Didier Ntwali ◽  
Charles Basalirwa ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Ensemble Methods ◽  
Predictive Performance ◽  
Mean Square ◽  
New Approach ◽  
Rainfall Prediction ◽  
Ensemble Mean ◽  
Additional Improvement ◽  
The Tropics

Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. This study is aimed at improving rainfall prediction using ensemble methods. It first assesses the performance of six convective schemes (Kain–Fritsch (KF); Betts–Miller–Janji´c (BMJ); Grell–Fretas (GF); Grell 3D ensemble (G3); New–Tiedke (NT) and Grell–Devenyi (GD)) using the root mean square error (RMSE) and mean error (ME) focusing on the March–May 2013 rainfall period over Uganda. 18 ensemble members are generated from the three best performing convective schemes (i.e. KF, GF & G3). The performance of three ensemble methods (i.e. ensemble mean (EM); ensemble mean analogue (EMA) and multi–member analogue ensemble (MAEM)) is also analyzed using the RMSE and ME. The EM presented a smaller RMSE compared to individual schemes (EM:10.02; KF:23.96; BMJ:26.04; GF:25.85; G3:24.07; NT:29.13 & GD:26.27) and a better bias (EM:-1.28; KF:-1.62; BMJ:-4.04; GF:-3.90; G3:-3.62; NT:-5.41 & GD:-4.07). The EMA and MAEM presented 13 out of 21 stations & 17 out of 21 stations respectively with smaller RMSE compared to EM thus demonstrating additional improvement in predictive performance. The MAEM is a new approach proposed and described in the study.

scholarly journals Improving Quantitative Rainfall Prediction Using Ensemble Analogues in the Tropics: Case Study of Uganda

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 328
Author(s):  
Isaac Mugume ◽  
Michel Mesquita ◽  
Yazidhi Bamutaze ◽  
Didier Ntwali ◽  
Charles Basalirwa ◽  
...  
Keyword(s):  
Daily Rainfall ◽  
Ensemble Methods ◽  
Predictive Performance ◽  
Prediction Performance ◽  
Rainfall Prediction ◽  
Rainfall Season ◽  
Ensemble Mean ◽  
Additional Improvement ◽  
The Tropics

Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. However quantitative rainfall prediction is normally a challenge and for this reason, this study was conducted with an aim of improving rainfall prediction using ensemble methods. It first assessed the performance of six convective schemes (Kain–Fritsch (KF); Betts–Miller–Janjić (BMJ); Grell–Fretas (GF); Grell 3D ensemble (G3); New–Tiedke (NT) and Grell–Devenyi (GD)) using the root mean square error (RMSE) and mean error (ME) focusing on the March–May 2013 rainfall period over Uganda. 18 ensemble members were then generated from the three best performing convective schemes (i.e., KF, GF and G3). The daily rainfall predicted by the three ensemble methods (i.e., ensemble mean (ENS); ensemble mean analogue (EMA) and multi–member analogue ensemble (MAEM)) was then compared with the observed daily rainfall and the RMSE and ME computed. The results shows that the ENS presented a smaller RMSE compared to individual schemes (ENS: 10.02; KF: 23.96; BMJ: 26.04; GF: 25.85; G3: 24.07; NT: 29.13 and GD: 26.27) and a better bias (ENS: −1.28; KF: −1.62; BMJ: −4.04; GF: −3.90; G3: −3.62; NT: −5.41 and GD: −4.07). The EMA and MAEM presented 13 out of 21 stations and 17 out of 21 stations respectively with smaller RMSE compared to ENS thus demonstrating additional improvement in predictive performance. This study proposed and described MAEM and found it producing comparatively better quantitative rainfall prediction performance compared to the other ensemble methods used. The MAEM method should be valid regardless the nature of the rainfall season.

Three-Dimensional Coastal Geomorphology Deformation Modelling Using Differential Synthetic Aperture Interferometry

2012 ◽  
Vol 67 (6-7) ◽  
pp. 419-420 ◽  
Keyword(s):  
Root Mean Square Error ◽  
Three Dimensional ◽  
Phase Unwrapping ◽  
Coastal Geomorphology ◽  
Synthetic Aperture ◽  
Mean Square ◽  
New Approach ◽  
Deformation Simulation ◽  
Accurate Performance ◽  
Fine Mode

This work presents a new approach for three-dimensional (3D) coastal deformation simulation using differential synthetic aperture interferometry (DInSAR). In doing so, conventional InSAR procedures are implemented to three repeat passes of RADARSAT-1 SAR fine mode data (F1). Further, the DInSAR method is implemented with the phase unwrapping technique. Consequently, DInSAR is used to eliminate the phase decorrelation impact from the interferograms. The study shows the accurate performance of DInSAR with a root mean square error of 0:02 ±0:21 m and 90% confidence intervals. In conclusion, the DInSAR technique produces an accurate 3D coastal geomorphology reconstruction

Metaheuristic data fitting methods to estimate Weibull parameters for wind speed data: a case study of Hasan Polatkan Airport

2021 ◽  
pp. 1-33
Author(s):  
A. Kaba ◽  
A. E. Suzer
Keyword(s):  
Wind Speed ◽  
Numerical Methods ◽  
Root Mean Square Error ◽  
Objective Function ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Statistical Tests ◽  
Mean Square ◽  
Flight Delays

ABSTRACT Flight delays may be decreased in a predictable way if the Weibull wind speed parameters of a runway, which are an important aspect of safety during the take-off and landing phases of aircraft, can be determined. One aim of this work is to determine the wind profile of Hasan Polatkan Airport (HPA) as a case study. Numerical methods for Weibull parameter determination perform better when the average wind speed estimation is the main objective. In this paper, a novel objective function that minimises the root-mean-square error by employing the cumulative distribution function is proposed based on the genetic algorithm and particle swarm optimisation. The results are compared with well-known numerical methods, such as maximum-likelihood estimation, the empirical method, the graphical method and the equivalent energy method, as well as the available objective function. Various statistical tests in the literature are applied, such as R2, Root-Mean-Square Error (RMSE) and $\chi$ 2. In addition, the Mean Absolute Error (MAE) and total elapsed time calculated using the algorithms are compared. According to the results of the statistical tests, the proposed methods outperform others, achieving scores as high as 0.9789 and 0.9996 for the R2 test, as low as 0.0058 and 0.0057 for the RMSE test, 0.0036 and 0.0045 for the MAE test and 3.53 × 10−5 and 3.50 × 10−5 for the $\chi$ 2 test. In addition, the determination of the wind speed characteristics at HPA show that low wind speed characteristics and regimes throughout the year offer safer take-off and landing schedules for target aircraft. The principle aim of this paper is to help establish the correct orientation of new runways at HPA and maximise the capacity of the airport by minimising flight delays, which represent a significant impediment to air traffic flow.

scholarly journals The Benefits of Multianalysis and Poor Man’s Ensembles

2008 ◽  
Vol 136 (11) ◽  
pp. 4113-4129 ◽  
Author(s):  
Neill E. Bowler ◽  
Alberto Arribas ◽  
Kenneth R. Mylne
Keyword(s):  
High Resolution ◽  
Ensemble Methods ◽  
Probabilistic Forecasting ◽  
New Approach ◽  
Current State ◽  
The World ◽  
Ensemble Mean ◽  
Resolution Model ◽  
High Resolution Model ◽  
Perturbed Model

Abstract A new approach to probabilistic forecasting is proposed, based on the generation of an ensemble of equally likely analyses of the current state of the atmosphere. The rationale behind this approach is to mimic a poor man’s ensemble, which combines the deterministic forecasts from national meteorological services around the world. The multianalysis ensemble aims to generate a series of forecasts that are both as skillful as each other and the control forecast. This produces an ensemble mean forecast that is superior not only to the ensemble members, but to the control forecast in the short range even for slowly varying parameters, such as 500-hPa height. This is something that it is not possible with traditional ensemble methods, which perturb a central analysis. The results herein show that the multianalysis ensemble is more skillful than the Met Office’s high-resolution forecast by 4.5% over the first 3 days (on average as measured for RMSE). Similar results are found for different verification scores and various regions of the globe. In contrast, the ensemble mean for the ensemble currently run by the Met Office performs 1.5% worse than the high-resolution forecast (similar results are found for the ECMWF ensemble). It is argued that the multianalysis approach is therefore superior to current ensemble methods. The multianalysis results were achieved with a two-member ensemble: the forecast from a high-resolution model plus a low-resolution perturbed model. It may be possible to achieve greater improvements with a larger ensemble.

scholarly journals A cooperative mobile robot and manipulator system (Co-MRMS) for transport and lay-up of fibre plies in modern composite material manufacture

2021 ◽  
Author(s):  
Manman Yang ◽  
Leijian Yu ◽  
Cuebong Wong ◽  
Carmelo Mineo ◽  
Erfu Yang ◽  
...  
Keyword(s):  
Machine Vision ◽  
Root Mean Square Error ◽  
Mobile Robot ◽  
Mean Square Error ◽  
Fibre Orientation ◽  
High Accuracy ◽  
Mean Square ◽  
Composite Manufacturing ◽  
Orientation Detection

AbstractComposite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper presents a case study that investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle-based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction-based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84∘) and enables dealing with uncertainties such as the shape and size of fibre plies.

scholarly journals A Note on the Reproducibility of Chaos Simulation

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 953
Author(s):  
Thalita E. Nazaré ◽  
Erivelton G. Nepomuceno ◽  
Samir A. M. Martins ◽  
Denis N. Butusov
Keyword(s):  
Experimental Data ◽  
Root Mean Square Error ◽  
Computer Simulations ◽  
Chaotic Systems ◽  
Mean Square ◽  
Finite Precision ◽  
Prediction Horizon ◽  
Code Sharing ◽  
Simulation Results

An evergreen scientific feature is the ability for scientific works to be reproduced. Since chaotic systems are so hard to understand analytically, numerical simulations assume a key role in their investigation. Such simulations have been considered as reproducible in many works. However, few studies have focused on the effects of the finite precision of computers on the simulation reproducibility of chaotic systems; moreover, code sharing and details on how to reproduce simulation results are not present in many investigations. In this work, a case study of reproducibility is presented in the simulation of a chaotic jerk circuit, using the software LTspice. We also employ the OSF platform to share the project associated with this paper. Tests performed with LTspice XVII on four different computers show the difficulties of simulation reproducibility by this software. We compare these results with experimental data using a normalised root mean square error in order to identify the computer with the highest prediction horizon. We also calculate the entropy of the signals to check differences among computer simulations and the practical experiment. The methodology developed is efficient in identifying the computer with better performance, which allows applying it to other cases in the literature. This investigation is fully described and available on the OSF platform.

scholarly journals Assessment of ecosystem services provided by livestock agroecosystems in the tropics: a case study of tropical island environment of Guadeloupe

2021 ◽  
Vol 53 (4) ◽  
Author(s):  
J.-L. Gourdine ◽  
A. Fourcot ◽  
C. Lefloch ◽  
M. Naves ◽  
G. Alexandre
Keyword(s):  
Ecosystem Services ◽  
Farming System ◽  
Livestock Farming ◽  
Tropical Island ◽  
Cultural Aspects ◽  
Livestock Farming System ◽  
Agroecological Zones ◽  
The Tropics ◽  
Cluster 2

AbstractThe present study aims to assess (1) the ecosystem services (ES) provided by LFS and (2) the differential ES between local (Creole) and exotic breeds from pig, cattle and goat. The ES are defined as the benefits that humans derive from LFS. They were summarized in 12 ES indicators that cover services related to provisioning, ecological and socio-cultural aspects and territorial vitality. A total of 106 LFS units that covers the five agroecological zones of Guadeloupe were analysed. Functional typologies of LFS per species were created from surveys. The effect of breed on the ES indicators was tested. Results showed that the 40 pig LFS units were separated into 3 clusters that were differentiated in ES according to provisioning ES (cluster 1), cultural use and sale to the neighborhood (cluster 2) and pork self-consumption (cluster 3). The typology of the 57 farms with cattle distinguished 4 clusters with differences in ES provided in self-consumption (cluster1), ecological ES (cluster 2), socio-cultural ES for racing or draught oxen (cluster 3) and ES associated with territory vitality (cluster 4). The 66 goat LFS units were classified into 3 clusters different in ES concerning self-consumption (cluster 1), cultural aspects (cluster 2) and provisioning ES (cluster 3). Our study highlights that ES indicators are not breed dependent (P > 0.10) but rather livestock farming system dependent. The ES rely more on the rearing management than on the breed type, and up to now, there are no specifications in Guadeloupe to differentiate management between breeds.

Benefit Corporations Approach to Environmental, Social and Governance Disclosure: A Focus on Italy

2020 ◽  
Vol 10 (4) ◽  
Author(s):  
Mauro Sciarelli ◽  
Silvia Cosimato ◽  
Giovanni Landi
Keyword(s):  
Qualitative Method ◽  
Positive Impact ◽  
Corporate Structure ◽  
New Approach ◽  
For Profit ◽  
Benefit Corporation ◽  
Benefit Corporations ◽  
Multiple Case ◽  
Governance Disclosure

AbstractOver the last decades, Benefit Corporations arouse as a new corporate structure, alternative to traditional ones and pointing to offer a new approach to the management of business and sustainability issues. These companies' activities are statutory aimed at bridging for-profit and no-profit activities; thus, they intentionally and statutory pursue economic purposes together with social and environmental ones, to create a positive impact on economy, society and environment. Even though, Italian and other national laws set some specific disclosure duties for Benefit Corporations, especially in terms of Environmental, Social and Governance (ESG) issues, the literature still calls for further research on the topic. Therefore, this paper is aimed at contributing to bridge this gap, investigating the way Italian Benefit Corporations approach ESG disclosure. To this end, an exploratory analysis has been conducted, implementing a qualitative method, based on a multiple case study strategy. Even though the descriptive nature of the study, the achieved findings pointed out that the Benefit Corporation structure not necessarily implies a better approach to ESG.

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