Evaluation of fine resolution gridded rainfall datasets over a dense network of rain gauges in Niger

Abdourahamane, Zakari Seybou

doi:10.1016/j.atmosres.2021.105459

Cited by 14 publications

(7 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the daily scale, all products generally show a low correlation with observed precipitation. In the YZR, the CC values of daily precipitation range from 0.30 to 0.39, which is lower than the values of the same products in other basins, such as Huifa River [27], Blue Nile [52], Huaihe River [13], etc. It can be further seen from the statistical and categorical metrics that the accuracy of the satellite precipitation products has a strong dependence on rainfall intensity [24].…”

Section: Results Of Grid-point Validationmentioning

confidence: 70%

Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River

Guo

Wang

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Satellite remote sensing precipitation products with high temporal–spatial resolution and large area coverage have great potential in hydrometeorological research. This paper analyzes the performance of four satellite products from 2000 to 2008 in the Yarlung Zangbo River Basin, namely the Tropical Rainfall Measuring Mission (TRMM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Climate Prediction Center morphing method (CMORPH). The four products are evaluated from three aspects: spatial distribution, temporal characteristics, and hydrological simulation. The results show that: (1) the four products exhibit similar annual and daily precipitation patterns, with the highest daily precipitation accuracy concentrated in the center, followed by the east and west; (2) TRMM, CHIRPS, and CMORPH exhibit the largest positive bias for monthly precipitation estimation in December, while PERSIANN shows the largest positive bias in July. All products overestimate the precipitation of 0.1–5 mm/d, and underestimate the precipitation above 5 mm/d, especially for PERSIANN; (3) certain Products tend to perform better than others at elevations of 3000–4000 m and in relatively humid zones. TRMM shows relatively stable performance for various elevation and climate zones; (4) for hydrological model validation, TRMM has the best performance during the calibration period, although it is inferior to CHIRPS during the validation period. Overall, TRMM has the highest applicability in the Yarlung Zangbo River Basin; however, its impact on the uncertainty of hydrological modeling needs to be further studied.

show abstract

Section: Results Of Grid-point Validationmentioning

confidence: 70%

Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River

Guo

Wang

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The traditional method for obtaining precipitation data is to install a network of rain gauge stations with a specific spatial density. Although accurate precipitation can be obtained at each station, the uneven distribution of rain gauge stations and the spatial discontinuity of precipitation data have obvious limitations [6,7]. Remote-sensing-based methods using radars or satellites have been increasingly applied to estimate precipitation and spatial distribution.…”

Section: Introductionmentioning

confidence: 99%

Can GPM IMERG Capture Extreme Precipitation in North China Plain?

Zhang¹,

Yang

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Extreme precipitation events (EPE) often cause catastrophic floods accompanied by serious economic losses and casualties. The latest version (V06) of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) provides global satellite precipitation data from 2000 at a higher spatiotemporal resolution with improved quality. It is scientifically and practically important to assess the accuracy of the IMERG V06 in capturing extreme precipitation. This study evaluates the two widely used products of IMERG during 2000–2018, i.e., IMERG late run (IMERG-L) and IMERG final run (IMERG-F), in the densely populated and flood-prone North China Plain. The accuracy of the IMERG V06 is evaluated with ground measurements from rain gauge stations at multiple scales (hourly, daily, and seasonally). A novel target tracking method is introduced to extract three-dimensional (3D) extreme precipitation events, and the near-real-time uncalibrated PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System) and GSMAP (Global Satellite Mapping of Precipitation) satellite data are added to further evaluate IMERG’s performance during extreme precipitation. Finally, for flash flood events induced by extreme rainfall in the Hebei Province from 15 to 23 July 2016, the accuracy of capturing the event with IMERG-F and IMERG-L was verified. Results reveal that IMERG-F is better than IMERG-L at all investigated scales (hourly, daily, and seasonally), but the difference between the two products is less at higher time resolutions. Both products manifest decreased performance when capturing 3D extreme precipitation events, and comparatively, IMERG-F performs better than IMERG-L. IMERG-F exhibits a distinct discontinuity in extreme precipitation thresholds between land and ocean, which is a limitation of IMERG-F not documented in previous studies. Moreover, IMERG-L and IMERG-F are comparable at an hourly scale for some metrics, which is beyond the expectation that IMERG-F is notably better than IMERG-L. This study provides a scientific basis for the performance of satellite precipitation products and contributes to guiding users when applying global precipitation products.

show abstract

“…Selection of the most suitable GPD based on their capability to capture the different characteristics of observed rainfall, such as mean, variability, probability distribution, extremes, seasonal fluctuation, and geographical distribution, is always difficult (Gampe et al ., 2019; Musie et al ., 2019). Various techniques have been used in literature for selecting suitable GPD (Ahmed et al ., 2017; Faiz et al ., 2018; Salman et al ., 2019; Yao et al ., 2020; Abdourahamane, 2021; Wang et al ., 2021). Most of the studies used different combinations of conventional statistics, such as coefficient of determination ( R 2 ), mean error, or mean bias to assess different characteristics of GPDs (Chen et al ., 2017; Faiz et al ., 2018; Hu et al ., 2018; Yeggina et al ., 2019; Salman et al ., 2019; Giles et al ., 2020; Abdourahamane, 2021; Dahri et al ., 2021; Merino et al ., 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Various techniques have been used in literature for selecting suitable GPD (Ahmed et al ., 2017; Faiz et al ., 2018; Salman et al ., 2019; Yao et al ., 2020; Abdourahamane, 2021; Wang et al ., 2021). Most of the studies used different combinations of conventional statistics, such as coefficient of determination ( R 2 ), mean error, or mean bias to assess different characteristics of GPDs (Chen et al ., 2017; Faiz et al ., 2018; Hu et al ., 2018; Yeggina et al ., 2019; Salman et al ., 2019; Giles et al ., 2020; Abdourahamane, 2021; Dahri et al ., 2021; Merino et al ., 2021). Besides, the GPDs have been evaluated based on their ability to simulated different hydrological events such as surface runoff (Try et al ., 2020), floods (Nashwan et al ., 2019), droughts (Centella‐Artola et al ., 2020) and crop yield (Lashkari et al ., 2018).…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of reanalysis precipitation products in Egypt using fuzzy entropy time series similarity analysis

Hamed

Nashwan

Shahid

2021

Intl Journal of Climatology

View full text Add to dashboard Cite

Selection of suitable gridded precipitation data is deemed for hydroclimatic assessment and climate change impact analysis, especially in regions where long‐term reliable precipitation data is unavailable. A novel approach based on fuzzy entropy similarity analysis (FESA) is proposed to evaluate the performance of four reanalysis gridded precipitation datasets (GPDs) for Egypt, namely European Reanalysis v.5. (ERA5), TerraClimate, Global Land Data Assimilation System (GLDAS)—Noah Land Surface Model L4 v.2 and Climatologies at high resolution for the Earth's land surface areas (CHELSA), against gauge records. The proposed method was verified using conventional statistics. Besides, the relative performance of different GPDs was verified according to their response to the influence of North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) on winter precipitation. The performance of the best reanalysis GPD was also compared with the gauge‐based global precipitation climatology centre (GPCC) dataset to show its reliability. The FESA revealed CHELSA as the best reanalysis GPD for Egypt. The performance assessment of GDPs based on conventional statistical metrics and visual presentation confirms the results obtained using FESA. CHELSA showed significant correlations with NAO (r = 0.3627) and MO (r = 0.624) like that obtained for gauge records. CHELSA also showed a better representation of precipitation in Egypt than GPCC at nearly half of the gauge locations. As CHELSA has a much higher spatial resolution than GPCC, it can be recommended as the proxy of gauge records in Egypt. The FESA can be used for performance analysis of gridded climate data by avoiding the complexities of using multiple statistical metrics.

show abstract

Evaluation of fine resolution gridded rainfall datasets over a dense network of rain gauges in Niger

Cited by 14 publications

References 36 publications

Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River

Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River

Can GPM IMERG Capture Extreme Precipitation in North China Plain?

Performance evaluation of reanalysis precipitation products in Egypt using fuzzy entropy time series similarity analysis

Contact Info

Product

Resources

About