A novel bias correction framework of TMPA 3B42 daily precipitation data using similarity matrix/homogeneous conditions

Choubin, Bahram; Khalighi-Sigaroodi, Shahram; Mishra, Ashok K.; Goodarzi, Massoud; Shamshirband, Shahaboddin; Zhang, Fan

doi:10.1016/j.scitotenv.2019.133680

Cited by 23 publications

(8 citation statements)

References 48 publications

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“…These findings indicate that the trends detected among the three datasets were generally similar for extreme precipitation events on a regional scale, showing that the trends detected from the meteorological station data were reasonable. Meanwhile, the differences in trends detected from the three datasets indicated that the accuracy of satellite observations needs to be improved to trace the magnitude of extreme precipitation events, using ground measurements for correction [43,44]. trends detected from the meteorological station data were reasonable.…”

Section: Discussionmentioning

confidence: 93%

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Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

et al. 2020

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Extreme weather events can cause a lot of damage in highly populated regions, such as in the Beijing–Tianjin–Hebei Region (BTHR) in northern China. To understand where and how extreme precipitation and temperature events are changing within the BTHR, data for 1959–2018 from 25 mereological stations were used to detect trends in the intensity, frequency, and duration of these events. The results showed that intensity, accumulated amount, the duration of extreme precipitation events, and the annual number of days with precipitation greater than 50 mm decreased on a regional scale over this 60-year period. Changes in extreme precipitation events at most stations were not statistically significant, although a few stations had a significant downward trend. The combined effects of the East Asian summer monsoon and rapid urbanization are possible reasons for these trends. Both the annual maximum and minimum temperature increased on a regional and local scale. The frequency of extreme hot and cold weather also, respectively, increased and decreased, with consistent patterns on a regional and local scale. However, the spatial changes of these trends were different, reflecting the effects of irrigation and urbanization on the regional surface energy balance. These findings are valuable to decisionmakers involved in disaster prevention in the BTHR and in other highly populated regions worldwide.

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Section: Discussionmentioning

confidence: 93%

“…trends detected from the meteorological station data were reasonable. Meanwhile, the differences in trends detected from the three datasets indicated that the accuracy of satellite observations needs to be improved to trace the magnitude of extreme precipitation events, using ground measurements for correction [43,44]. .…”

Section: Discussionmentioning

confidence: 99%

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

et al. 2020

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“…Several recent studies have attempted to reduce the errors in satellite precipitation retrievals by considering only seasonal rainfall intensity and/or topographic factors in their error adjustment models or blending algorithms (e.g., Tian et al, 2010b;Hashemi et al, 2017;Bhuiyan et al, 2018;Le et al, 2018;Choubin et al, 2019;Shen et al, 2019;Baez-Villanueva et al, 2020). In practice, the errors show significant regional features (at least for the three evaluated SPPs).…”

Section: Potential Methods Of Improving Satellite Retrieval Algorithms and Error Adjustment Modelsmentioning

confidence: 99%

Global component analysis of errors in three satellite-only global precipitation estimates

Chen

Yong

Kirstetter

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. Revealing the error components of satellite-only precipitation products (SPPs) can help algorithm developers and end-users understand their error features and improve retrieval algorithms. Here, two error decomposition schemes are employed to explore the error components of the IMERG-Late, GSMaP-MVK, and PERSIANN-CCS SPPs over different seasons, rainfall intensities, and topography classes. Global maps of the total bias (total mean squared error) and its three (two) independent components are depicted for the first time. The evaluation results for similar regions are discussed, and it is found that the evaluation results for one region cannot be extended to another similar region. Hit and/or false biases are the major components of the total bias in most overland regions globally. The systematic error contributes less than 20 % of the total error in most areas. Large systematic errors are primarily due to missed precipitation. It is found that the SPPs show different topographic patterns in terms of systematic and random errors. Notably, among the SPPs, GSMaP-MVK shows the strongest topographic dependency of the four bias scores. A novel metric, namely the normalized error component (NEC), is proposed as a means to isolate the impact of topography on the systematic and random errors. Potential methods of improving satellite precipitation retrievals and error adjustment models are discussed.

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“…The detailed knowledge of rainfall characteristics, i.e., rainfall intensity, is essential to evaluate remotely sensed rainfall estimates (Mandapaka and Qin 2013). It is important to provide nature and characteristics of rainfall and better prediction of hydrologic response in watersheds and urban areas (Chen et al 2016) since rainfall exhibit different mean value and variability at daily time series (Choubin et al 2019). The error estimation of satellite-based rainfall in frequencies and intensities of daily precipitation influences the simulation result of surface water, sub-surface water, evapotranspiration, and different amounts and proportion of simulated water balance components (Luo et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Performance of daily satellite-based rainfall in groundwater basin of Merapi Aquifer System, Yogyakarta

Rahmawati

Rahayu²,

Yuliasari

2021

Theor Appl Climatol

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Evaluation of the performance of daily satellite-based rainfall (CMORPH, CHIRPS, GPM IMERG, and TRMM) was done to obtain applicable satellite rainfall estimates in the groundwater basin of the Merapi Aquifer System (MAS). Performance of satellite data was assessed by applying descriptive statistics, categorical statistics, and bias decomposition on the basis of daily rainfall intensity classification. This classification is possible to measure the performance of daily satellite-based rainfall in much detail. CM (CMORPH) has larger underestimation compared to other satellite-based rainfall assessments. This satellite-based rainfall also mostly has the largest RMSE, while CHR (CHIRPS) has the lowest. CM has a good performance to detect no rain, while IMR (GPM IMERG) has the worst performance. IMR and CHR have a good performance to detect light and moderate rain. Both of them have larger H frequencies and lower MB values compared to other satellite products. CHR mostly has a good performance compared to TR (TRMM), especially on wet periods. CM, IMR, and TR mostly have a good performance on dry periods, while CHR on wet periods. CM mostly has the largest MB and lowest AHB values. CM and CHR have better accuracy to estimate rain amount compared to IMR and TR. All in all, all 4 satellite-based rainfall assessments have large discrepancy compared with rain gauge data along mountain range where orographic rainfall usually occurs in wet periods. Hence, it is recommended to evaluate satellite-based rainfall with time series of streamflow simulation in hydrological modeling framework by merging rain gauge data with more than one satellite-based rainfall than to merge both IMR and TR together.

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A novel bias correction framework of TMPA 3B42 daily precipitation data using similarity matrix/homogeneous conditions

Cited by 23 publications

References 48 publications

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

Global component analysis of errors in three satellite-only global precipitation estimates

Performance of daily satellite-based rainfall in groundwater basin of Merapi Aquifer System, Yogyakarta

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