scholarly journals Correcting Position Error in Precipitation Data Using Image Morphing

2019 ◽  
Vol 11 (21) ◽  
pp. 2557 ◽  
Author(s):  
Camille Le Coz ◽  
Arnold Heemink ◽  
Martin Verlaan ◽  
Marie-claire ten Veldhuis ◽  
Nick van de Giesen
Keyword(s):  
Monsoon Season ◽  
Real Data ◽  
Sub Saharan Africa ◽  
Rain Event ◽  
Spatial Transformation ◽  
Image Morphing ◽  
Rainfall Events ◽  
Position Errors ◽  
First Case ◽  
Meteorological Observatory

Rainfall estimates based on satellite data are subject to errors in the position of the rainfall events in addition to errors in their intensity. This is especially true for localized rainfall events such as the convective rainstorms that occur during the monsoon season in sub-Saharan Africa. Many satellite-based estimates use gauge information for bias correction. However, bias adjustment methods do not correct the position errors explicitly. We propose to gauge-adjust satellite-based estimates with respect to the position using a morphing method. Image morphing transforms an image, in our case a rainfall field, into another one, by applying a spatial transformation. A benefit of this approach is that it can take both the position and the intensity of a rain event into account. Its potential is investigated with two case studies. In the first case, the rain events are synthetic, represented by elliptic shapes, while the second case uses real data from a rainfall event occurring during the monsoon season in southern Ghana. In the second case, the satellite-based estimate IMERG-Late (Integrated Multi-Satellite Retrievals for GPM ) is adjusted to gauge data from the Trans-African Hydro-Meteorological Observatory (TAHMO) network. The results show that the position errors can be corrected, while preserving the higher spatial variability of the satellite-based estimate.

Correcting position error in rainfall estimates using temporal and spatial warping

2020 ◽  
Author(s):  
Camille Le Coz ◽  
Arnold Heemink ◽  
Martin Verlaan ◽  
Marie-claire ten Veldhuis ◽  
Nick van de Giesen
Keyword(s):  
Bias Correction ◽  
Monsoon Season ◽  
Position Error ◽  
Rainfall Event ◽  
Sub Saharan Africa ◽  
Registration Method ◽  
Rainfall Events ◽  
Meteorological Observatory ◽  
Sub Saharan ◽  
Rainfall Estimates

<p>An increasing number of satellite-based rainfall estimates, with ever finer resolution, are becoming available. They are particularly valuable in regions with sparse radar and gauge networks. For example, in most of sub-Saharan Africa, the gauge network is not dense enough to represent the high variability of the rainfall during the monsoon season. However, satellite-based estimates can be subject to errors in position and/or timing of the rainfall events, in addition to errors in the intensity.<br>Many satellite-based estimates use gauge measurements for bias correction. Bias correction methods focus on the intensity errors, and do not correct the position error explicitly. We propose to gauge-adjust the satellite-based estimates with respect to the position and time. We investigate two approaches: spatial and temporal warping. The first one is based on a spatial mapping and correct the spatial position while keeping the time constant. The second uses a temporal mapping and keeps the spatial domain unchanged. The mappings are derived through a fully automatic registration method. That is, only the gauge and satellite-based estimates are needed as inputs. There is no need to manually predefine the rain features.<br>The spatial and temporal approaches are both applied to a rainfall event during the monsoon season in southern Ghana. The Trans-African Hydro-Meteorological Observatory (TAHMO) gauge network is used to gauge-adjust the IMERG-Late (Integrated Multi-Satellite Retrievals for GPM) satellite-based estimates. The two approaches are evaluated with respect to the timing, the location and the intensity of the rainfall event.</p>

scholarly journals Spatial and Time Warping for Gauge Adjustment of Rainfall Estimates

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1510
Author(s):  
Camille Le Le Coz ◽  
Arnold Heemink ◽  
Martin Verlaan ◽  
Nick van de van de Giesen
Keyword(s):  
Bias Correction ◽  
Positive Impact ◽  
Sub Saharan Africa ◽  
Rain Event ◽  
Time Warping ◽  
Deformation Method ◽  
Timing Errors ◽  
Position Errors ◽  
Southern Ghana ◽  
Rainfall Estimates

Many satellite-based estimates use gauge information for bias correction. In general, bias-correction methods are focused on the intensity error and do not explicitly correct possible position or timing errors. However, position and timing errors in rainfall estimates can also lead to errors in the rainfall occurrence or the intensity. This is especially true for localized rainfall events such as the convective rainstorms occurring during the rainy season in sub-Saharan Africa. We investigated the use of warping to correct such errors. The goal was to gauge-adjust satellite-based estimates with respect to the position and the timing of the rain event, instead of its intensity. Warping is a field-deformation method that transforms an image into another one. We compared two methods, spatial warping focusing on the position errors and time warping for the timing errors. They were evaluated on two case studies: a synthetic rainfall event represented by an ellipse and a rain event in southern Ghana during the monsoon season. In both cases, the two warping methods reduced significantly the respective targeted (position or timing) errors. In the southern Ghana case, the average position error was decreased by about 45 km by the spatial warping and the average timing error was decreased from more than 1 h to 0.2 h by the time warping. Both warping methods also improved the continuous statistics on the intensity: the correlation went from 0.18 to at least 0.62 after warping in the southern Ghana case. The spatial warping seems more interesting because of its positive impact on both position and timing errors.

scholarly journals A Closed-Form Solution to Planar Feature-Based Registration of LiDAR Point Clouds

2021 ◽  
Vol 10 (7) ◽  
pp. 435
Author(s):  
Yongbo Wang ◽  
Nanshan Zheng ◽  
Zhengfu Bian
Keyword(s):  
Closed Form ◽  
Closed Form Solution ◽  
Simulated Data ◽  
Real Data ◽  
Point Clouds ◽  
Form Solution ◽  
Spatial Transformation ◽  
Dual Quaternions ◽  
Feature Based ◽  
Planar Feature

Since pairwise registration is a necessary step for the seamless fusion of point clouds from neighboring stations, a closed-form solution to planar feature-based registration of LiDAR (Light Detection and Ranging) point clouds is proposed in this paper. Based on the Plücker coordinate-based representation of linear features in three-dimensional space, a quad tuple-based representation of planar features is introduced, which makes it possible to directly determine the difference between any two planar features. Dual quaternions are employed to represent spatial transformation and operations between dual quaternions and the quad tuple-based representation of planar features are given, with which an error norm is constructed. Based on L2-norm-minimization, detailed derivations of the proposed solution are explained step by step. Two experiments were designed in which simulated data and real data were both used to verify the correctness and the feasibility of the proposed solution. With the simulated data, the calculated registration results were consistent with the pre-established parameters, which verifies the correctness of the presented solution. With the real data, the calculated registration results were consistent with the results calculated by iterative methods. Conclusions can be drawn from the two experiments: (1) The proposed solution does not require any initial estimates of the unknown parameters in advance, which assures the stability and robustness of the solution; (2) Using dual quaternions to represent spatial transformation greatly reduces the additional constraints in the estimation process.

scholarly journals Modeling and Forecasting of COVID-19 Spreading by Delayed Stochastic Differential Equations

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 18
Author(s):  
Marouane Mahrouf ◽  
Adnane Boukhouima ◽  
Houssine Zine ◽  
El Mehdi Lotfi ◽  
Delfim F. M. Torres ◽  
...  
Keyword(s):  
Real Data ◽  
Economic Damage ◽  
Population Parameter ◽  
The Novel ◽  
First Case ◽  
Epidemiological Trend ◽  
Modeling And Forecasting ◽  
Novel Coronavirus ◽  
Parameter Values ◽  
Stochastic Time

The novel coronavirus disease (COVID-19) pneumonia has posed a great threat to the world recent months by causing many deaths and enormous economic damage worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020, and the number of reported cases has increased day by day. In this work, we extend the well-known SIR compartmental model to deterministic and stochastic time-delayed models in order to predict the epidemiological trend of COVID-19 in Morocco and to assess the potential role of multiple preventive measures and strategies imposed by Moroccan authorities. The main features of the work include the well-posedness of the models and conditions under which the COVID-19 may become extinct or persist in the population. Parameter values have been estimated from real data and numerical simulations are presented for forecasting the COVID-19 spreading as well as verification of theoretical results.

scholarly journals Variations in O<sub>3</sub>, CO, and CH<sub>4</sub> over the Bay of Bengal during the summer monsoon season: Ship-borne measurements and model simulations

2016 ◽  
Author(s):  
Imran A. Girach ◽  
Narendra Ojha ◽  
Prabha R. Nair ◽  
Andrea Pozzer ◽  
Yogesh K. Tiwari ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Bay Of Bengal ◽  
Monsoon Season ◽  
Surface Ozone ◽  
Ozone Production ◽  
Spatial And Temporal Variability ◽  
Summer Monsoon Season ◽  
Rainfall Events ◽  
Model Simulations ◽  
Mixing Ratios

Abstract. We present ship-borne measurements of surface ozone, carbon monoxide and methane over the Bay of Bengal (BoB), the first time such measurements have been taken during the summer monsoon season, as a part of the Continental Tropical Convergence Zone (CTCZ) experiment during 2009. O3, CO, and CH4 mixing ratios exhibited significant spatial and temporal variability in the ranges of 8–54 nmol mol−1, 50–200 nmol mol−1, and 1.57–2.15 µmol mol−1, with means of 29.7 ± 6.8 nmol mol−1, 96 ± 25 nmol mol−1, and 1.83 ± 0.14 µmol mol−1, respectively. The average mixing ratios of trace gases over northern BoB (O3: 30 ± 7 nmol mol−1, CO: 95 ± 25 nmol mol−1, CH4: 1.86 ± 0.12 µmol mol−1), in airmasses from northern or central India, did not differ much from those over central BoB (O3: 27 ± 5 nmol mol−1, CO: 101 ± 27 nmol mol−1, CH4: 1.72 ± 0.14 µmol mol−1), in airmasses from southern India. Spatial variability is observed to be most significant for CH4. The ship-based observations, in conjunction with backward air trajectories and ground-based measurements over the Indian region, are analyzed to estimate a net ozone production of 1.5–4 nmol mol−1 day−1 in the outflow. Ozone mixing ratios over the BoB showed large reductions (by ~ 20 nmol mol−1) during four rainfall events. Temporal changes in the meteorological parameters, in conjunction with ozone vertical profiles, indicate that these low ozone events are associated with downdrafts of free-tropospheric ozone-poor airmasses. While the observed variations in O3 and CO are successfully reproduced using the Weather Research and Forecasting model with Chemistry (WRF-Chem), this model overestimates mean concentrations by about 20 %, generally overestimating O3 mixing ratios during the rainfall events. Analysis of the chemical tendencies from model simulations for a low-O3 event on August 10, 2009, captured successfully by the model, shows the key role of horizontal advection in rapidly transporting ozone-rich airmasses across the BoB. Our study fills a gap in the availability of trace gas measurements over the BoB, and when combined with data from previous campaigns, reveals large seasonal amplitude (~ 39 and ~ 207 nmol mol−1 for O3 and CO, respectively) over the northern BoB.

scholarly journals Spatial structures and directionalities in Monsoonal precipitation over South Asia

2010 ◽  
Vol 17 (5) ◽  
pp. 371-381 ◽  
Author(s):  
N. Malik ◽  
N. Marwan ◽  
J. Kurths
Keyword(s):  
Indian Subcontinent ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Data Sets ◽  
Spatial Structures ◽  
Break Phase ◽  
Rainfall Events ◽  
Monsoonal Precipitation ◽  
Rain Events

Abstract. Precipitation during the monsoon season over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. Employing methods from nonlinear time series analysis, we study spatial structures of the rainfall field during the summer monsoon and identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. Moreover, we estimate the time delay patterns of rain events. Here we present an analysis of two separate high resolution gridded data sets of daily rainfall covering the Indian subcontinent. Using the method of event synchronization (ES), we estimate regions where heavy rain events during monsoon happen in some lag synchronised form. Further using the delay behaviour of rainfall events, we estimate the directionalities related to the progress of such type of rainfall events. The Active (break) phase of a monsoon is characterised by an increase(decrease) of rainfall over certain regions of the Indian subcontinent. We show that our method is able to identify regions of such coherent rainfall activity.

scholarly journals SARS-COV-2 induced Parkinsonism: The first case from the sub-Saharan Africa

2021 ◽  
pp. 100116
Author(s):  
Biniyam A. Ayele ◽  
Hanna Demissie ◽  
Meron Awraris ◽  
Wondwossen Amogne ◽  
Ali Shalash ◽  
...  
Keyword(s):  
Sub Saharan Africa ◽  
First Case ◽  
Sub Saharan

scholarly journals Polarimetric radar observations during an orographic rain event and the performance of a hydrometeor classification scheme

2014 ◽  
Vol 11 (7) ◽  
pp. 8845-8877
Author(s):  
M. Frech ◽  
J. Steinert
Keyword(s):  
Classification Scheme ◽  
Ground Level ◽  
Radar Data ◽  
Precipitation Event ◽  
Orographic Precipitation ◽  
Rain Event ◽  
Melting Layer ◽  
Surface Observation ◽  
Meteorological Observatory ◽  
Radar Sensing

Abstract. An intense orographic precipitation event is analysed using two polarimetric C-Band radars situated north of the Alps on 5 January 2013. One radar is operated at DWD's meteorological observatory Hohenpeißenberg (MHP, 1006 m a.s.l. – above sea level) and the Memmingen (MEM, 65 km west of MHP, 600 m a.s.l.) radar is part of DWD's operational radar network. The event lasted about 1.5 days and in total 44 mm precipitation was measured at Hohenpeißenberg. Detailed high resolution observation on the vertical structure of this event is obtained through a birdbath scan at 90° elevation which is part of the operational scanning. This scan is acquired every 5 min and provides meteorological profiles at high spatial resolution. In the course of this event, the melting layer (ML) descends until the transition from rain into snow is observed at ground level. This transition from rain into snow is well documented by local weather observers and a present-weather sensor. The orographic precipitation event reveals mesoscale variability above the melting layer which is unexpected from a meteorological point of view. It corresponds to a substantial increase in rain rate at the surface. The performance of the newly developed hydrometeor classification scheme "Hymec" using Memmingen radar data over Hohenpeißenberg is analyzed. The detection in location and timing of the ML agrees well with the Hohenpeißenberg radar data. Considering the size of the Memmingen radar sensing volume, the detected hydrometeor (HM) types are consistent for measurements at or in a ML, even though surface observation indicate for example rain whereas the predominant HM is classified as wet snow. To better link the HM classification with the surface observation, either better thermodynamic input is needed for Hymec or a statistical correction of the HM classification similar to a model output statistics (MOS) approach may be needed.

scholarly journals Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

2021 ◽  
Author(s):  
Frederik Wolf ◽  
Ugur Ozturk ◽  
Kevin Cheung ◽  
Reik V. Donner
Keyword(s):  
System Dynamics ◽  
East Asia ◽  
Heavy Rainfall ◽  
Spatial Organization ◽  
Monsoon Season ◽  
Spatiotemporal Patterns ◽  
Extreme Weather Events ◽  
Earth System ◽  
Rainfall Events ◽  
Heavy Rainfall Events

&lt;p&gt;Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events.&lt;/p&gt;&lt;p&gt;To thoroughly expand on previous works employing the latter framework to the East Asian Summer Monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates with &lt;span&gt;a spatial resolution of 0.25&amp;#176; &lt;/span&gt;between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way.&lt;/p&gt;&lt;p&gt;Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help improving future forecasts of the Baiu onset in different regions of East Asia.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Further details: F. Wolf, U. Ozturk, K. Cheung, R.V. Donner: Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season. Earth System Dynamics (in review). Discussion Paper: Earth System Dynamics Discussions, (2020)&lt;/p&gt;

A critical analysis of water PPP failures in sub-Saharan Africa

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Salman Tariq ◽  
Xueqing Zhang
Keyword(s):  
Construction Management ◽  
Design Methodology ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Content Type ◽  
Rigorous Approach ◽  
First Case ◽  
Management Perspective ◽  
Sub Saharan

PurposeTop-down pressure from donors, public sector inefficiencies and fund deficits have steered the introduction of public–private partnerships (PPPs) in sub-Saharan Africa. However, PPP activities in the water sector have been quite insignificant compared to other infrastructure sectors in this region. In addition, a number of water PPPs have encountered great difficulties and subsequent failures. This study aims at unveiling the underlying reasons behind failures.Design/methodology/approachThis study has classified the failure types of water PPPs and reviewed the development of water PPPs in sub-Saharan Africa to identify failed ones. Eight failed case studies are completed through the rigorous approach of event sequence mapping.FindingsNine root causes of water PPP failure are identified through a thorough examination of these failed water PPP cases and the interrelationships between these failure causes are established. The failure causes are further generalized through literature focusing on water PPP failures in developing countries and problematic issues that hinder the implementation of successful water PPPs across different Sub-Saharan African countries. Recommendations are provided for future improvements in carrying out water PPPs in Sub-Saharan Africa by learning past lessons and drawing experiences.Originality/valueThis is the first case study on water PPP failures in Sub-Saharan Africa from a construction management perspective. This study will help governments and the private sector in developing stronger future water PPPs.

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