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Sensors (Basel). 2019 Apr 11;19(7). pii: E1743. doi: 10.3390/s19071743.

High Spatial Resolution Simulation of Sunshine Duration over the Complex Terrain of Ghana.

Author information

1
College of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China. mustapha.adamu@monash.edu.
2
College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China. xfqiu135@nuist.edu.cn.
3
College of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China. shiguopingnj@163.com.
4
College of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China. nooni25593@alumni.itc.nl.
5
College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China. 18751971206@163.com.
6
College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China. xiaochen.zhu@nuist.edu.cn.
7
College of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China. dans7messiah@nuist.edu.cn.
8
College of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China. kennylim@nuist.edu.cn.

Abstract

In this paper, we propose a remote sensing model based on a 1 × 1 km spatial resolution to estimate the spatio-temporal distribution of sunshine percentage (SSP) and sunshine duration (SD), taking into account terrain features and atmospheric factors. To account for the influence of topography and atmospheric conditions in the model, a digital elevation model (DEM) and cloud products from the moderate-resolution imaging spectroradiometer (MODIS) for 2010 were incorporated into the model and subsequently validated against in situ observation data. The annual and monthly average daily total SSP and SD have been estimated based on the proposed model. The error analysis results indicate that the proposed modelled SD is in good agreement with ground-based observations. The model performance is evaluated against two classical interpolation techniques (kriging and inverse distance weighting (IDW)) based on the mean absolute error (MAE), the mean relative error (MRE) and the root-mean-square error (RMSE). The results reveal that the SD obtained from the proposed model performs better than those obtained from the two classical interpolators. This results indicate that the proposed model can reliably reflect the contribution of terrain and cloud cover in SD estimation in Ghana, and the model performance is expected to perform well in similar environmental conditions.

KEYWORDS:

Digital Elevation Model (DEM); Ghana; complex terrain; remote-sensing; sunshine duration; sunshine percentage

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