Accuracy of satellite rainfall estimates in the <scp>B</scp>lue <scp>N</scp>ile <scp>B</scp>asin: <scp>L</scp>owland plain versus highland mountain

Gebremichael, Mekonnen; Bitew, M. M.; Hirpa, Feyera A.; Tesfay, Gebrehiwot N.

doi:10.1002/2013wr014500

Cited by 72 publications

(58 citation statements)

References 35 publications

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“…Several studies have been conducted in Ethiopia (e.g., Dinku et al, 2007Dinku et al, , 2008Dinku et al, and 2011aHirpa et al, 2010;Romilly and 30 Gebremichael, 2011;Young et al, 2014 andGebre et al, 2015) and specifically to the Upper Blue Nile basin (e.g., Dinku et al 2011b;Gebremichael et al, 2014;Fenta et al, 2014 andWorqlul et al, 2014) to validate the performance of satellitebased rainfall products. These studies validated mainly the skills of Tropical Applications of Meteorology using SATellite Atmos.…”

Section: Introductionmentioning

confidence: 99%

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Ayehu¹,

Tadesse²,

Gessesse³

et al. 2017

Preprint

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Abstract. Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at variousscales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite 15 rainfall estimates could be used as a sole product (e.g. in areas with no (poor) ground observations) or through integrating with rain gauge measurements. In this study, the newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data has been evaluated in comparison to rain gauge data for the period of 2000 to 2015 across the Upper Blue Nile basin in Ethiopia. Besides, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) version 2 and 3 (TAMSAT 2 and TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have 20 been used as a benchmark and compared with CHIRPS. The TAMSAT 2 rainfall estimate was used in this study mainly to assess the improvements made with the recent version of a TAMSAT product (TAMSAT 3). From the overall analysis at dekadal and monthly temporal scale, CHIRPS exhibited higher skills and the best bias value in comparison to ARC 2 but overestimates the frequency of rainfall occurrence particularly during the dry months. On the other hand, TAMSAT 3 has shown very comparable performance with that of CHIRPS product, particularly with regards to bias. The ARC 2 product 25 was found to have the weakest performance underestimating rainfall amounts by about 24%. The skill of CHIRPS is less affected by variation in elevation in comparison to TAMSAT 3 and ARC 2 products. While ARC 2 was found to be affected by elevation with the average biases of 1.53, 0.86 and 0.77 at lower (< 1000 m a.s.l), medium (1000 to 2000 m a.s.l) and higher elevation (> 2000 m a.s.l), respectively. Comparing the overall performance of the three products, CHIRPS exhibited the best performance followed closely by TAMSAT 3. This validation study also shows that the TAMSAT 3 has overcome 30 the main weaknesses of TAMSAT 2, which is underestimation of high rainfall amounts by up to 31% in this study. Overall, the finding of this validation study shows the potentials of CHIRPS product to be used for various operational applications such as rainfall pattern and variability study in the Upper Blue Nile basin in Ethiopia.Atmos. Meas. Tech. Discuss., https://doi

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Section: Introductionmentioning

confidence: 99%

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Ayehu¹,

Tadesse²,

Gessesse³

et al. 2017

Preprint

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“…It is arguably considered as the most important driving force for any 4 hydrological model. Despite its importance for socioeconomic development, ground-based rainfall measurements are sparse and unevenly distributed,especially in developing 6 countries (Behrangi et al, 2011;Gebremichael et al, 2014). The recommended density of ground rainfall measuring network in tropical regions is one gauge per 600 -900 km 2 for flat 8 and 100 -250km 2 for mountainous areas, respectively (WMO, 1994).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the 4 performance also varies for the same data type across different regions and seasons (Gebremichael et al, 2014;Hu et al, 2014). This indicates that the performance of satellite 6 products largely depends on the location, topography, season, and hydro-climatic characteristics of the study area.…”

mentioning

confidence: 99%

“…Validation and inter-comparison of different rainfall products over the complex topography of satellite rainfall products (e.g., Dinku et al, 2007;Gebremichael et al, 2014;Haile et al, 2013;Worqlul et al, 2014;Beyissa et al, 2017 The basin is characterized by a semi-arid climate in the east and north and partly semi-humid in the south (Belete, 2007). More than 85 % of the total annual rainfall falls in the wet season 4 (June -September) which varies from 400 mm yr -1 in the east to more than 1200 mm yr -1 in the south (Fig.…”

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confidence: 99%

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Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Gebremicael

Mohamed

Zaag

et al. 2017

Preprint

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16Satellite rainfall products are considered important options for acquiring rainfall estimates in the absence of ground measurements. However, estimates from these products need to be 18 validated as their accuracy can be affected by geographical position, topography, and climate, as well as by the algorithms used to derive rainfall from satellite measurements. Eight Results show thatCHIRPS, TRMM,and RFEv2 performed well and wereable to capture the 26 rainfall measured by rain gauges. The BIASand correlation of these products were within ±25% and >0.5over different time steps.The remaining products poorly performed at daily 28 time step with higher BIAS (up to ±200%) and lower correlation (<0.5). CMORPH, PERSIANN, and ARCv2 were relatively better while CMAP and GPCP performed poorly 30 (r<0.4) in all conditions. The overall performance of all products was lower in the mountainous areas of the basin with station elevation>2500 m.a.s.l. Compared to the 32 lowlands, the BIAS at highlands increased by 35% whilst the correlation dropped by 28%. Underestimation and overestimation of rainfall dominated in the mountainous and lowland 34 areas, respectively.CMORPH and TRMM overestimated while the remaining products underestimated the rainfall at all spatiotemporal scales. CMAP, ARC2, and GPCP estimates 36 were the most affected by large underestimation. Unlike in temporal scale, the performance of the products did not show a uniform pattern with respect to spatial scale.Their performance 38 improved from point to aerial comparisons in the lowlandswhereas it slightly reduced athighland areas. Poor performance in the highlands contributed to a slightly lower

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“…The POFD scores across the study area appear to be independent of geographical characteristics. The independency can be explained by the sensitivity of microwave and infrared retrieval algorithms to scattering signals and cold cloud temperatures from the rainfall systems over these terrain features [38]. The majority of the pixel-point gauges located at the coast have a POFD value of more than 0.6, indicating a tendency of TRMM to over detect rainfall.…”

Section: Detection Metricsmentioning

confidence: 99%

Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia

2018

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Abstract:The Tropical Rainfall Measuring Mission (TRMM) was the first Earth Science mission dedicated to studying tropical and subtropical rainfall. Up until now, there is still limited knowledge on the accuracy of the version 7 research product TRMM 3B42-V7 despite having the advantage of a high temporal resolution and large spatial coverage over oceans and land. This is particularly the case in tropical regions in Asia. The objective of this study is therefore to analyze the performance of rainfall estimation from TRMM 3B42-V7 (henceforth TRMM) using rain gauge data in Malaysia, specifically from the Pahang river basin as a case study, and using a set of performance indicators/scores. The results suggest that the altitude of the region affects the performances of the scores. Root Mean Squared Error (RMSE) is lower mostly at a higher altitude and mid-altitude. The correlation coefficient (CC) generally shows a positive but weak relationship between the rain gauge measurements and TRMM (0 < CC < 0.4), while the Nash-Sutcliffe Efficiency (NSE) scores are low (NSE < 0.1). The Percent Bias (PBIAS) shows that TRMM tends to overestimate the rainfall measurement by 26.95% on average. The Probability of Detection (POD) and Threat Score (TS) demonstrate that more than half of the pixel-point pairs have values smaller than 0.7. However, the Probability of False Detection (POFD) and False Alarm Rate (FAR) show that most of the pixel-point gauges have values lower than 0.55. The seasonal analysis shows that TRMM overestimates during the wet season and underestimates during the dry season. The bias adjustment shows that Mean Bias Correction (MBC) improved the scores better than Double-Kernel Residual Smoothing (DS) and Residual Inverse Distance Weighting (RIDW). The large errors imply that TRMM may not be suitable for applications in environmental, water resources, and ecological studies without prior correction.

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Accuracy of satellite rainfall estimates in the Blue Nile Basin: Lowland plain versus highland mountain

Cited by 72 publications

References 35 publications

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales

Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia

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