DOI: 10.1002/joc.5238
论文题名: Development of high spatial resolution rainfall data for Ghana
作者: Aryee J.N.A. ; Amekudzi L.K. ; Quansah E. ; Klutse N.A.B. ; Atiah W.A. ; Yorke C.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 3 起始页码: 1201
结束页码: 1215
语种: 英语
英文关键词: Clustering
; Ghana
; GMet v1.0
; Homogenization
; Minimum surface curvature
; Quantile matching
; Rainfall climatology
; Validation
Scopus关键词: Cluster analysis
; Homogenization method
; Image resolution
; Rain
; Clustering
; Ghana
; GMet v1.0
; Minimum surfaces
; Quantile matching
; Rainfall climatologies
; Validation
; Rain gages
; climate effect
; cluster analysis
; data quality
; data set
; database
; pixel
; rainfall
; raingauge
; regional climate
; spatial resolution
; TRMM
; Ghana
英文摘要: Various sectors of the country’s economy - agriculture, health, energy, among others - largely depend on climate information, hence availability of quality climate data is very essential for climate-impact studies in these sectors. In this paper, a monthly rainfall database (GMet v1.0) has been developed at a 0.5° × 0.5° spatial resolution, from 113 Ghana Meteorological Agency (GMet) gauge network distributed across the four agro-ecological zones of Ghana, and spanning a 23-year period (1990-2012). The datasets were first homogenized with quantile-matching adjustments and thereafter, gridded at a spatial resolution of 0.5° × 0.5° using Minimum Surface Curvature with tensioning parameter, allowing for comprehensive spatial fields assessment on the developed dataset. Afterwards, point-pixel validation was performed using GMet v1.0 against gauge data from stations that were earlier excluded due to large datagaps. This proved the reliability of GMet v1.0, with high and statistically significant correlations at 99% confidence level, and relatively low biases and rmse. Furthermore, GMet v1.0 was compared with GPCC and TRMM rainfall estimates, with both products found to adequately mimick GMet v1.0, with high correlations which are significant at 99% confidence level, low biases and rmse. In addition, the ratio of 90th - percentile provided fairly similar capture of extremes by both TRMM and GPCC, in relation to GMet v1.0. Finally, based on annual rainfall totals and monthly variability, k-means cluster analysis was performed on GMet v1.0, which delineated the country into four distinct climatic zones. The developed rainfall data, when officially released, will be a useful product for climate impact and further rainfall validation studies in Ghana. © 2017 Royal Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117118
Appears in Collections: 气候减缓与适应
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作者单位: Meteorology and Climate Science Unit, Department of Physics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana; Remote Sensing, GIS and Climate Center, Ghana Space Science and Technology Institute, Accra, Ghana; Ghana Meteorological Agency, Accra, Ghana
Recommended Citation:
Aryee J.N.A.,Amekudzi L.K.,Quansah E.,et al. Development of high spatial resolution rainfall data for Ghana[J]. International Journal of Climatology,2018-01-01,38(3)