Assessment of Long-Term Spatio-Temporal Rainfall Variability over Ghana using Wavelet Analysis

Baidu, Michael; Amekudzi, Leonard K.; Aryee, Jeffrey N. A.; Annor, Thompson

doi:10.3390/cli5020030

Cited by 66 publications

(78 citation statements)

References 49 publications

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“…is is because of the difficulty in forecasting rainfall in an area with erratic and varied rainfall pattern. Rainfall variability in the study area is also consistent with the findings of [45,46]. us, the fluctuations in the rainfall distribution on annual basis are not uncommon in the Savannah zone.…”

Section: Discussionsupporting

confidence: 87%

“…Having an increasing rainfall trend is quite a welcoming result for the residents in the area because of its potential agricultural, hydrological, and socioeconomic effects in an area that is highly populated by farmers, rain-fed agriculturalist for that matter. e increasing rainfall in the area supports the findings of [46] that found that, in the Savannah zone of Ghana, many of the years between 1901 and 2010 experienced above-normal rainfall in the area. Given that there is an upward trend in rainfall, farmers and the residents in general will be relieved especially in relation to water management towards future use.…”

Section: Discussionsupporting

confidence: 85%

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Temporal Description of Annual Temperature and Rainfall in the Bawku Area of Ghana

Asamoah

Ansah-Mensah

2020

Advances in Meteorology

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With varied implications, Ghana’s temperature and rainfall are projected to rise and decline, respectively. A study exposing specific areas of concern for appropriate responses in this regard is a welcome one. This study sought to describe the temporal variations in temperature and rainfall in the Bawku Area of Ghana. A forty-year (1976–2015) daily climate data was collected on three meteorological stations from the Ghana Meteorological Agency. Normality test, homogeneity test, Standardised Precipitation Index (SPI) analysis, Mann–Kendall trend test, and One-way post hoc ANOVA were performed using XLSTAT and DrinC. Over the period under study, the mean annual rainfall pattern was generally erratic, fluctuating between 669.8 mm and 1339.4.6 mm with an annual average of 935.3 mm. The long-term (40-year period) average temperature of the three stations, on the other hand, was 28.7°C, varying between 26.9°C and 29.9°C annually. Whereas the SPI value of 2006 was ≥2.0, indicating extremely wet year with 2.3% probability of recurring once every 50 years, 1988 was the hottest year with temperature anomaly value of 1.2°C, while coolest years were 1979 (−1.8°C) and 1976 (−1.0°C). The Mann–Kendall trend test showed a rise in rainfall in Binduri, Garu-Tempane, and Manga, yet none of the rainfall changes were statistically significant (P>0.05). Mean temperature on the other hand experienced a significant rise (P<0.05). With an R-square of 34.7%, the rise in temperature in Manga witnessed the most significant change in annual temperature changes. There were statistically significant (P<0.05) differences in the interdecadal temperature over the 40-year period. Generally, it can be stated that both temperature and rainfall vary in the study area with various degrees of disparities, but temperature assumes an upward trend at a faster rate. We therefore recommend that stakeholders resort to the construction of dams and boreholes to ensure regular availability of water for both domestic and agricultural uses.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionsupporting

confidence: 85%

Temporal Description of Annual Temperature and Rainfall in the Bawku Area of Ghana

Asamoah

Ansah-Mensah

2020

Advances in Meteorology

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“…These results are in agreement with the findings of previous independent works over the region [33][34][35][36][37]. The increase in precipitation from the Sahara to the humid equatorial zone was assumed to relate to a rapidly increasing depth of the moist layer equator-ward from the Intertropical Convergence Zone, ITCZ [33].…”

Section: Discussionsupporting

confidence: 91%

Uncertainties in the Estimation of Global Observational Network Datasets of Precipitation over West Africa

Oj¹,

Oe²,

La³

et al. 2017

J Climatol Weather Forecasting

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This study assessed the uncertainty in estimating long-term mean precipitation, its inter-annual variability, and linear trend of three network observation datasets over West Africa. A reference data, defined as a multi-dataset ensemble of precipitation observations of the Climate Research Unit (CRU) of the University of East Anglia, the Global Precipitation Climatology Centre (GPCC) and the University of Delaware (UDEL), all at horizontal resolutions of 0.5° by 0.5° were obtained and used in this study. Uncertainties in these climatological parameters of precipitation at both annual and seasonal time scales were examined in terms of inter-dataset variability using signalto-noise ratio (SNR), correlation, root-mean-square errors and the normalised standard deviation. Results showed that the mean, inter-annual variability and trends climatology varied for different datasets. The three datasets had good agreement (SNR>5) in terms of the annual mean precipitation and its inter-annual variability in most parts of West Africa. However, the agreement between the datasets was poor in the very dry Sahel parts of northern Niger, Mali, and Mauritania (SNR ≤ 1) due to very little precipitation and possibility of relatively low station density in these regions of complex terrain. In terms of correlation (0.89 ≤ r ≤ 0.98), and normalised standard deviation, NSD (0.8 ≤ NSD ≤ 1.7), the uncertainties in the spatial variations in linear trend were larger than mean precipitation and their inter-annual variability for both annual and seasonal scales. The long-term annual precipitation trend in the region is highly uncertain except in a few small areas. observational errors are much more problematic, because their effects become relatively more pronounced as greater numbers of observations are aggregated. In this case, the author believed that averaging observations together from many different instruments/sources would tend to reduce the contribution of systematic observational errors to the uncertainty of the average.A number of researchers and institutions have developed observation-based gridded analysis datasets of global or regional coverage with fine spatial resolutions [8][9][10][11][12][13][14]. These network of observation datasets provide precipitation and/or surface air temperatures over extended periods of multiple decades at spatial resolutions of 0.5° or finer. This is, of course, a substantial improvement over previous generation data sets that are typically at much coarser (e.g. 2.5°) horizontal resolutions [15]. These recent fine-scale datasets allow us to better examine the regional precipitation and temperature climatology and to perform more reliable evaluations of today's highresolution climate simulations, especially over the regions of complex terrain, that are important for climate-change impact assessments and climate model evaluations [16].

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“…() and Baidu et al . (), to be a reliable, gauge‐based dataset over the study domain, and thus proves useful for comparison with GMet v1.0. GPCC datasets are monthly rainfall estimates covering the last century, and provided by the Earth System Research Lab (ESRL) at the National Oceanic and Atmospheric Administration (NOAA).…”

Section: Study Area and Data Sourcementioning

confidence: 96%

“…The use of Global Precipitation Climatology Centre (GPCC) datasets in this study stems primarily from the fact that, it has been demonstrated in various studies, for example Manzanas et al (2014) and Baidu et al (2017), to be a reliable, gauge-based dataset over the study domain, and thus proves useful for comparison with GMet v1.0. GPCC datasets are monthly rainfall estimates covering the last century, and provided by the Earth System Research Lab (ESRL) at the National Oceanic and Atmospheric Administration (NOAA).…”

Section: Global Precipitation Climatology Centre Datamentioning

confidence: 99%

Development of high spatial resolution rainfall data for Ghana

Aryee

Amekudzi

Quansah

et al. 2017

Intl Journal of Climatology

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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.

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Assessment of Long-Term Spatio-Temporal Rainfall Variability over Ghana using Wavelet Analysis

Cited by 66 publications

References 49 publications

Temporal Description of Annual Temperature and Rainfall in the Bawku Area of Ghana

Temporal Description of Annual Temperature and Rainfall in the Bawku Area of Ghana

Uncertainties in the Estimation of Global Observational Network Datasets of Precipitation over West Africa

Development of high spatial resolution rainfall data for Ghana

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