Evaluation and Comparison of Satellite Rainfall Products in the Black Volta Basin

Logah, F. Y.; Adjei, Kwaku Amaning; Obuobie, Emmanuel; Gyamfi, Charles; Odai, Samuel Nii

doi:10.1007/s40710-020-00465-0

Cited by 15 publications

(12 citation statements)

References 34 publications

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“…However, Scenario 2 (Table 4 ) involving bias correction improved all SPPs, but CMORPH (SSIM = 0.312) ranked better than TMPA (SSIM = 0.289). Over the Black Volta Basin which lies north of the Pra catchment, Logah et al 24 reported CHIRPS, PERSIANN, TMPA and ARC2 to be in a decreasing order of performance for rainfall, this being contrary to our rankings shown in Table 3 (Scenario 1) while TMPA emerged as the best among all the SPPs. Post bias correction though, CHIRPS was ranked at the bottom and TMPA at the top considering the set of SPPs they evaluated (Table 4 ).…”

Section: Resultscontrasting

confidence: 98%

“…The point-to-grid approach used by others (e.g., 24 , 25 ) is in fact a variant of our Scenario 1, with the grid size as a fixed window for calculating the SIM index. Owusu et al 25 found TMPA to be better than CMORPH for the Pra catchment, noting that they used data from 2003 to 2008 and only data from 7 rain gauges for the evaluation.…”

Section: Resultsmentioning

confidence: 99%

“…They found that the performance of the products depends on the scale and location, and CHIRPS was generally better than other satellite precipitation products. Five SPPs were evaluated by Logah et al 24 over the Black Volta Basin, West Africa, using point-to-grid analysis, and using bias, correlation, Nash–Sutcliffe efficiency, probability of detection and false alarm ratio. CHIRPS emerged as the best SPP from their study followed by PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Climate Data Record).…”

Section: Introductionmentioning

confidence: 99%

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Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana

Gyasi-Agyei,

Obuobie,

et al. 2023

Sci Rep

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Thirteen satellite precipitation products (SPPs), re-gridded to 1 km resolution, were evaluated in terms of the structural similarity index (SSI) over the Pra catchment in Ghana. Three SPP scenarios were considered: Scenario one (S1) was the original SPPs; Scenario two (S2) was bias-corrected SPPs; and Scenario three (S3) was the better of S1 and S2 for each wet day. For each scenario, the best SPP was selected to constitute the 14th SPP referred to as the BEST SPP. Each SPP was evaluated in terms of SSI against the rain gauge rainfield for each wet day. For S1, the top three SPPs were TMPA, GSMAP and CMORPH; for S2, CMORPH, PERCCS and MSWEP were the top three; and for S3, CMORPH, PERCCS and TMPA came out on top in order of decreasing performance. Bias correction led to improvement in the overall SSI measure (SSIM) for 73% of wet days. The BEST SPP increased the SSIM of the best individual SPP by over 50% for S1, and over 30% for both S2 and S3. Comparing the BEST SPP of the three scenarios, S2 increased the SSIM statistic by 20% over that for S1, and SSIM was further improved by 4% for S3. It is highly recommended to use BEST SPP (S3) to generate the required 1 km × 1 km rainfields for the Pra, or other catchments around the world with a sparse rain gauge network, through conditional merging with rain gauge data as demonstrated.

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Section: Resultscontrasting

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana

Gyasi-Agyei,

Obuobie,

et al. 2023

Sci Rep

Self Cite

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“…Many satellite datasets have been validated against gauge observations across Africa at different spatio-temporal scales. For example, valida-tion studies show that these satellite PRE products are consistent with gauge estimates in the Congo [17,30], Kenya [31,32], Ghana [33], and Burkina Faso [34].…”

Section: Introductionmentioning

confidence: 76%

Assessing the Performance of WRF Model in Simulating Heavy Precipitation Events over East Africa Using Satellite-Based Precipitation Product

Nooni

Tan

Hongming³

et al. 2022

Remote Sensing

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This study investigated the capability of the Weather Research and Forecasting (WRF) model to simulate seven different heavy precipitation (PRE) events that occurred across East Africa in the summer of 2020. The WRF model outputs were evaluated against high-resolution satellite-based observations, which were obtained from prior evaluations of several satellite observations with 30 stations’ data. The synoptic conditions accompanying the events were also investigated to determine the conditions that are conducive to heavy PRE. The verification of the WRF output was carried out using the area-related root mean square error (RMSE)-based fuzzy method. This method quantifies the similarity of PRE intensity distribution between forecast and observation at different spatial scales. The results showed that the WRF model reproduced the heavy PRE with PRE magnitudes ranging from 6 to >30 mm/day. The spatial pattern from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification-Climate Data Record (PERSIANN-CCS-CDR) was close to that of the WRF output. The area-related RMSE with respect to observation showed that the error in the model tended to reduce as the spatial scale increased for all the events. The WRF and high-resolution satellite data had an obvious advantage when validating the heavy PRE events in 2020. This study demonstrated that WRF may be used for forecasting heavy PRE events over East Africa when high resolutions and subsequent simulation setups are used.

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“…further insight into past trend in rainfall and temperature variability in the miningscape. The selected indices have been used in other climate variability studies(Atiah et al, 2019;Logah et al, 2021;Obada et al, 2021).These have relevance as pointers to the potential impact of climate change on socio-economic activities at different scales such as mining operations(Gonzalez et al, 2019) and rural livelihoods(Atiah et al, 2019).Table 2 also provide potential risk and impact of climate variability on mining sustainability that can be inferred from the selected ETCCDI indices as indicated in literature. The base period for extreme indices computation was 1986-2015.The non-parametric Mann-Kendall (MK) was used to detect trend at each station as used in previous studies(Baidu et al, 2017; da Silva et al, 2015; Kabo-bah et al, 2016).…”

mentioning

confidence: 99%

Trend in extreme climates across southwestern Ghana and the implications for natural resources development

Tannor,

Tischbein,

Greve

et al. 2023

Preprint

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The use of reanalysis data as pseudo observational data to analyze extreme climate events is cautioned for inconsistencies for which complimenting climate hazard analysis using observed data is imperative especially in rural West Africa where the impact is severe. Beside the effects of changing climate, is the impacts of resource extractivism that dominate rural landscapes of countries within the Mossi-Baule domain. Using available observational hydroclimatic data, the study examines the spatio-temporal trend in climate extremes and the implications for natural resources managers within southwestern Ghana. The results confirm decreasing trend in number of near normal wet years compared to extreme wet and dry years as well as significant changes in extreme rainfall and temperature across the forest zones of Ghana. Stations located in miningscapes such as Sefwi (Moist semideciduous forest) and Axim (Evergreen forest) had the highest number of dry rainfall years, and the lowest number of wet rainfall years. Similarly, extreme events such as percentage warm nights and days are significantly increasing whereas cool days and cool nights are significantly decreasing across the entire southwestern Ghana. The implications for sustainable mining can be severe including operational aspects such as infrastructural and production systems, sustainability best practices coupled with regulatory consequences. Rural livelihood resources and biodiversity are double burden by the effects of changing climate and extractive activities just as the hydrologic regime of transboundary river basins within southwestern Ghana. Emphasis for watershed approach to climate change adaptation within miningscapes is vital as illustrated in the study.

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Evaluation and Comparison of Satellite Rainfall Products in the Black Volta Basin

Cited by 15 publications

References 34 publications

Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana

Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana

Assessing the Performance of WRF Model in Simulating Heavy Precipitation Events over East Africa Using Satellite-Based Precipitation Product

Trend in extreme climates across southwestern Ghana and the implications for natural resources development

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