Enhanced 4D Imaging in West Africa Using High-resolution Tomography and Q-imaging

2013 ◽  
Author(s):  
M. Cavalca ◽  
J. Penwarden ◽  
A. King ◽  
S. Knapp ◽  
X.G. Meng ◽  
...  
Keyword(s):  
High Resolution ◽  
West Africa ◽  
4D Imaging

Enhanced 4D Imaging in West Africa Using High-resolution Tomography and Q-imaging

2014 ◽  
Author(s):  
J. Penwarden ◽  
M. Cavalca ◽  
A. King ◽  
S. Knapp ◽  
X. Meng ◽  
...  
Keyword(s):  
High Resolution ◽  
West Africa ◽  
4D Imaging

scholarly journals An operational approach to high resolution agro-ecological zoning in West-Africa

PLoS ONE ◽  
2017 ◽  
Vol 12 (9) ◽  
pp. e0183737
Author(s):  
Y. Le Page ◽  
Maria Vasconcelos ◽  
A. Palminha ◽  
I. Q. Melo ◽  
J. M. C. Pereira
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Operational Approach

scholarly journals Generation of High-Resolution Rain Fields in West Africa: Evaluation of Dynamic Interpolation Methods

2011 ◽  
Vol 12 (6) ◽  
pp. 1465-1482 ◽  
Author(s):  
T. Vischel ◽  
G. Quantin ◽  
T. Lebel ◽  
J. Viarre ◽  
M. Gosset ◽  
...  
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Evaluation Criteria ◽  
Rain Gauge ◽  
Time Of Arrival ◽  
Time Step ◽  
Propagation Models ◽  
Interpolation Technique ◽  
Classic Approach ◽  
Better Than

Abstract High-resolution rain fields are a prerequisite to many hydrometeorological studies. For some applications, the required resolution may be as fine as 1 km in space and 5 min in time. At these scales, rainfall is strongly intermittent, variable in space, and correlated in time because of the propagation of the rainy systems. This paper compares two interpolation approaches to generate high-resolution rain fields from rain gauge measurements: (i) a classic interpolation technique that consists in interpolating independently the rain intensities at each time step (Eulerian kriging) and (ii) a simple dynamic interpolation technique that incorporates the propagation of the rainy systems (Lagrangian kriging). For this latter approach, three propagation models are tested. The different interpolation techniques are evaluated over three climatically contrasted areas in West Africa where a multiyear 5-min rainfall dataset has been collected during the African Monsoon Multidisciplinary Analyses (AMMA) campaigns. The dynamic interpolation technique is shown to perform better than the classic approach for a majority of the rainy events. The performances of the three propagation models differ from one another, depending on the evaluation criteria used. One of them provides a satisfactory time of arrival of rainfall but slightly smooths the rain intensities. The two others reproduce well the rain intensities, but the time of arrival of the rain is sometimes delayed. The choice of an appropriate propagation algorithm will thus depend on the operational objectives underlying the rain field generation.

scholarly journals Large-Scale High-Resolution Coastal Mangrove Forests Mapping Across West Africa With Machine Learning Ensemble and Satellite Big Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Xue Liu ◽  
Temilola E. Fatoyinbo ◽  
Nathan M. Thomas ◽  
Weihe Wendy Guan ◽  
Yanni Zhan ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
West Africa ◽  
Spatial Resolution ◽  
Mangrove Forest ◽  
Large Scale ◽  
Google Earth ◽  
Mangrove Forests ◽  
Data Products ◽  
Sentinel 2

Coastal mangrove forests provide important ecosystem goods and services, including carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are being destroyed at an alarming rate by human activities. To characterize mangrove forest changes, evaluate their impacts, and support relevant protection and restoration decision making, accurate and up-to-date mangrove extent mapping at large spatial scales is essential. Available large-scale mangrove extent data products use a single machine learning method commonly with 30 m Landsat imagery, and significant inconsistencies remain among these data products. With huge amounts of satellite data involved and the heterogeneity of land surface characteristics across large geographic areas, finding the most suitable method for large-scale high-resolution mangrove mapping is a challenge. The objective of this study is to evaluate the performance of a machine learning ensemble for mangrove forest mapping at 20 m spatial resolution across West Africa using Sentinel-2 (optical) and Sentinel-1 (radar) imagery. The machine learning ensemble integrates three commonly used machine learning methods in land cover and land use mapping, including Random Forest (RF), Gradient Boosting Machine (GBM), and Neural Network (NN). The cloud-based big geospatial data processing platform Google Earth Engine (GEE) was used for pre-processing Sentinel-2 and Sentinel-1 data. Extensive validation has demonstrated that the machine learning ensemble can generate mangrove extent maps at high accuracies for all study regions in West Africa (92%–99% Producer’s Accuracy, 98%–100% User’s Accuracy, 95%–99% Overall Accuracy). This is the first-time that mangrove extent has been mapped at a 20 m spatial resolution across West Africa. The machine learning ensemble has the potential to be applied to other regions of the world and is therefore capable of producing high-resolution mangrove extent maps at global scales periodically.

Regional and high‐resolution 3D pore‐pressure prediction in deep‐water offshore West Africa

2003 ◽  
Author(s):  
N. C. Banik ◽  
G. Wool ◽  
G. Schultz ◽  
L. den Boer ◽  
W. Mao ◽  
...  
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Pore Pressure ◽  
Deep Water ◽  
Pore Pressure Prediction

Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction

2020 ◽  
Author(s):  
Diarra Dieng ◽  
Cornelius Hald ◽  
Patrick Laux ◽  
Christof Lorenz ◽  
Harald Kunstmann
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Water Availability ◽  
Bias Correction ◽  
Wrf Model ◽  
Correction Method ◽  
Dew Point ◽  
Limited Area ◽  
Wide Range ◽  
Institute Of Technology

<p><strong>Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction </strong></p><p>Diarra Dieng<sup>1</sup>, Cornelius Hald<sup>1</sup>, Patrick Laux<sup>1,2</sup>, Christof Lorenz<sup>1</sup>, Harald Kunstmann<sup>1,2</sup></p><p><sup>1</sup>Institute of Meteorology and Climate Research (IMK-IFU), Campus Alpine, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany,</p><p><sup>2</sup>Institute of Geography, University of Augsburg, Augsburg, Germany,</p><p> </p><p>With a wide range of ecological, climatic, and cultural diversities, West Africa is a rapidly developing region whose agricultural systems remain largely rain-fed and underdeveloped. In this study we examine the potential impacts of climate variability and climate change on the water availability in the mid-21st century in West 
Africa by using high resolution simulations (12km) from the Weather and Research Forecasting (WRF) model and the COSMO-Climate Limited area Modelling (CCLM) for the RCP 4.5 scenario. Our approach is based on the simplified Penman-Monteith (PM) equation for daily ET, which requires the joint information on relative humidity, maximum and minimum daily temperatures, dew point temperature, solar radiation and wind speed. It is not only crucial that the statistical behavior of these modelled variables is close to observations, but also that the interplay between these variables is realistic. We therefore further adapted, applied and analyzed a subsequent bias-correction method for the WRF and CCLM simulations using a nonparametric, trend-preserving quantile mapping approach and a multivariate bias correction approach (MBCn). We present the details of the method and the derived implications for expected water availability in West Africa.</p>

scholarly journals The life cycle of nocturnal low-level clouds over southern West Africa analysed using high-resolution simulations

2016 ◽  
Author(s):  
Bianca Adler ◽  
Norbert Kalthoff ◽  
Leonhard Gantner
Keyword(s):  
Life Cycle ◽  
High Resolution ◽  
West Africa ◽  
Single Case ◽  
Monsoon Season ◽  
Cloud Formation ◽  
Field Campaign ◽  
Low Level ◽  
Low Level Jet ◽  
Spatio Temporal

Abstract. We performed a high-resolution numerical simulation to study the life cycle of extensive low-level clouds which frequently form over southern West Africa during the monsoon season. This study was made in preparation for a field campaign in 2016 within the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) project and focuses on an area around the city of Save in southern Benin. Nocturnal low-level clouds evolve a few hundred metres above the ground around the same level as a distinct low-level jet. Several processes are found to determine the spatio-temporal evolution of these clouds including (i) significant cooling of the nocturnal atmosphere due to horizontal advection with the south-westerly monsoon flow during the first half of the night, (ii) vertical cold air advection due to gravity waves leading to clouds in the wave crests and (iii) enhanced convergence and upward motion upstream of existing clouds that trigger new clouds. The latter is caused by an upward shift of the low-level jet in cloudy areas leading to horizontal convergence in the lower part and to horizontal divergence in the upper part of the cloud layer. Although this single case study hardly allows for a generalisation of the processes found, the results added to the optimisation of the measurements strategy for the field campaign and the observations will be used to the test the hypotheses for cloud formation resulting from this study.

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