Exploring the Added Value of Sub-Daily Bias Correction of High-Resolution Gridded Rainfall Datasets for Rainfall Erosivity Estimation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.2.1. Rainfall Observations
2.2.2. Rainfall Products (RPs)
2.3. Steps of the Methodology
2.3.1. Selection of a Reference RP for Bias Correction of Rainfall Data
2.3.2. Sub-Daily Bias Correction of RPs
2.3.3. Impact of Bias Correction on Rainfall Estimation across the RPs
2.3.4. Calculation of Rainfall Erosivity
2.3.5. Comparison of Rainfall Erosivity with Reference Values
2.3.6. Trend Analysis of Rainfall Erosivity over the Period 2001–2020
3. Results
3.1. Sub-Daily Bias Correction of RPs
3.2. Impact of Bias Correction on Rainfall
3.2.1. Comparison of Rainfall at Daily, Monthly, and Annual Timescales
3.2.2. Categorical Metrics
3.2.3. Distribution of Rainfall Events Intensity and Duration
3.2.4. Spatial Patterns in Annual Rainfall
3.3. Impact of Bias Correction on Rainfall Erosivity Estimates from RPs
3.3.1. Estimation of Half-Hourly to Hourly Calibration Factors
3.3.2. Annual Rainfall Erosivity R-Factor
3.3.3. Monthly Rainfall Erosivity R-Factors
3.3.4. Spatial Patterns in Annual Rainfall Erosivity R-Factor
3.4. Impact of Bias Correction on Annual Trends in Rainfall and Rainfall Erosivity
4. Discussion
4.1. Key Findings in This Study
4.2. Study Limitations and Future Work
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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WMO Code 1 | Name | Latitude, Longitude (Decimal Degrees) | Altitude (m) | Annual Rainfall (mm) 2 | Climate Type 3 |
---|---|---|---|---|---|
1200010000 | Dori | 14.0333, −0.0333 | 288 | 528.2 ± 127.6 | BWh |
1200024100 | Ouahigouya | 13.5833, −2.4333 | 329 | 764.7 ± 145.0 | BSh |
1200004300 | Bogande | 12.9833, −0.1333 | 250 | 643.8 ± 121.6 | BSh |
1200007900 | Dedougou | 12.4667, −3.4667 | 308 | 859.7 ± 115.1 | BSh |
1200000100 | Ouagadougou | 12.3500, −1.5167 | 304 | 816.1 ± 115.0 | BSh |
1200010300 | Fada | 12.0333, 0.3667 | 308 | 833.3 ± 103.5 | BSh |
1200005200 | Boromo | 11.7500, −2.9333 | 270 | 920.1 ± 129.2 | BSh |
1200004000 | Bobo-Dioulasso | 11.1667, −4.3167 | 459 | 1043.4 ± 197.1 | Aw |
1200026200 | Po | 11.1667, −1.1500 | 326 | 1024.9 ± 128.0 | Aw |
1200011200 | Gaoua | 10.3333, −3.1833 | 333 | 1088.4 ± 150.2 | Aw |
Source | Type 1 | Spatial Resolution | Temporal Resolution | Spatial Coverage | Temporal Coverage | References |
---|---|---|---|---|---|---|
CMORPH (CPC MORPHing technique) | S | 0.25° × 0.25° (~28 km) | 1 h | 60°N/S | 1998-present | [74,75] |
ERA5 (5th generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis) | R | 0.25° × 0.25° (~28 km) | 1 h | Global | 1940-present | [76,77] |
IMERG (Integrated multi-satellite retrievals for the global precipitation measurement)-Late run (v6) | S | 0.1° × 0.1° (~11 km) | 0.5 h | Global | 2000-present | [78] |
MERRA-2 (modern-era retrospective analysis for research and applications, Version 2) | R | 0.5° × 0.685° (~60 km) | 1 h | Global | 1980-present | [79] |
PERSIANN-PDIR-Now (precipitation estimation from remotely sensed information using artificial neural networks-dynamic infrared rain rate near real-time) | S + G | 0.04° × 0.04° (~4.44 km) | 1 h | 60°N/S | 2000-present | [80,81] |
PERSIANN (precipitation estimation from remotely sensed information using artificial neural Networks) | S + G | 0.25° × 0.25° (~28 km) | 1 h | 60°N/S | 2000-present | [80,82] |
PERSIANN-CCS (precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system) | S + G | 0.04° × 0.04° (~4.44 km) | 1 h | 60°N/S | 2003-present | [80,82] |
Metric | Description | Formula 1 | Range |
---|---|---|---|
Probability of detection (POD) | Fraction of events correctly identified to the total rainfall events occurrences | 0 (no skill)–1 (perfect score) | |
False alarm ratio (FAR) | Fraction of predicted rainfall events which did not occur in gauge measurements | 0 (perfect score)–1 (no skill) | |
Threat score (TS) or critical success index (CSI) | Fraction of observed and/or predicted events that were correctly predicted | 0 (no skill)–1 (perfect score) |
Timescale | Type | RP | R [-] | MAE [mm/timescale] | RMSE [mm/timescale] | PBIAS [%] | KGE [-] |
---|---|---|---|---|---|---|---|
Daily | reference | IMERG | 0.85 | 6.49 | 8.58 | 6.20 | 0.83 |
raw | CMORPH | 0.50 | 13.56 | 18.06 | 0.70 | 0.40 | |
raw | ERA5 | 0.32 | 17.89 | 24.05 | −18.70 | 0.07 | |
raw | MERRA-2 | 0.40 | 23.96 | 33.18 | −38.80 | 0.01 | |
raw | PDIR-Now | 0.26 | 24.34 | 33.80 | −45.90 | −0.07 | |
raw | PERSIANN | 0.50 | 15.65 | 19.64 | 39.00 | 0.29 | |
raw | PERSIANN-CCS | 0.46 | 16.17 | 20.61 | 42.10 | 0.27 | |
bc | CMORPH | 0.81 | 6.38 | 8.42 | 8.60 | 0.78 | |
bc | ERA5 | 0.75 | 5.59 | 7.18 | 15.80 | 0.57 | |
bc | MERRA-2 | 0.81 | 5.42 | 6.75 | 16.10 | 0.69 | |
bc | PDIR-Now | 0.78 | 5.67 | 7.48 | 18.10 | 0.57 | |
bc | PERSIANN | 0.82 | 6.28 | 8.18 | 6.00 | 0.80 | |
bc | PERSIANN-CCS | 0.84 | 6.35 | 8.40 | 4.50 | 0.83 | |
Monthly | reference | IMERG | 0.91 | 17.76 | 35.40 | −5.50 | 0.88 |
raw | CMORPH | 0.88 | 21.64 | 38.96 | 14.90 | 0.77 | |
raw | ERA5 | 0.73 | 37.84 | 66.90 | 178.50 | −1.03 | |
raw | MERRA-2 | 0.75 | 36.91 | 64.02 | 156.10 | −0.75 | |
raw | PDIR-Now | 0.64 | 42.78 | 76.03 | 262.70 | −2.13 | |
raw | PERSIANN | 0.79 | 56.07 | 92.16 | −46.80 | 0.37 | |
raw | PERSIANN-CCS | 0.65 | 84.19 | 137.29 | −56.10 | 0.18 | |
bc | CMORPH | 0.91 | 19.98 | 36.35 | −7.10 | 0.85 | |
bc | ERA5 | 0.80 | 28.89 | 54.51 | −2.50 | 0.76 | |
bc | MERRA-2 | 0.81 | 34.55 | 68.11 | −18.40 | 0.60 | |
bc | PDIR-Now | 0.86 | 65.54 | 123.90 | −51.40 | 0.25 | |
bc | PERSIANN | 0.89 | 22.15 | 41.05 | −7.30 | 0.83 | |
bc | PERSIANN-CCS | 0.85 | 25.62 | 47.88 | −3.80 | 0.80 | |
Annual | reference | IMERG | 0.76 | 105.26 | 132.70 | −7.50 | 0.78 |
raw | CMORPH | 0.69 | 132.35 | 166.36 | 14.90 | 0.64 | |
raw | ERA5 | 0.63 | 428.93 | 453.91 | 178.50 | −0.96 | |
raw | MERRA-2 | 0.62 | 407.95 | 437.27 | 156.10 | −0.62 | |
raw | PDIR-Now | 0.67 | 485.18 | 505.83 | 262.70 | −1.66 | |
raw | PERSIANN | 0.48 | 589.38 | 625.33 | −46.80 | 0.29 | |
raw | PERSIANN-CCS | 0.40 | 969.96 | 1026.92 | −56.10 | −0.07 | |
bc | CMORPH | 0.80 | 106.58 | 133.72 | −7.10 | 0.78 | |
bc | ERA5 | 0.61 | 142.89 | 185.66 | −2.50 | 0.58 | |
bc | MERRA-2 | 0.63 | 249.06 | 318.77 | −18.40 | 0.37 | |
bc | PDIR-Now | 0.41 | 718.46 | 768.25 | −51.40 | 0.12 | |
bc | PERSIANN | 0.73 | 124.00 | 152.57 | −7.30 | 0.72 | |
bc | PERSIANN-CCS | 0.58 | 179.99 | 244.99 | −3.80 | 0.44 |
Type | Product | Annual Mean (±sd) R-Factor (MJ mm ha−1 h−1 yr−1) | RMSE 1 (MJ mm ha−1 h−1 yr−1) | MAE 1 (MJ mm ha−1 h−1 yr−1) | PBIAS 1 (%) |
---|---|---|---|---|---|
GloREDa | 2964.9 ± 886.9 | ||||
IMERG | 2929.7 ± 543.8 | 494.1 | 365.0 | 1.2 | |
raw | CMORPH | 2130.3 ± 312.5 | 1192.8 | 897.6 | 39.2 |
raw | ERA5 | 465.1 ± 142.6 | 2605.9 | 2499.7 | 537.4 |
raw | MERRA-2 | 410.0 ± 132.8 | 2682.9 | 2554.8 | 623.1 |
raw | PDIR-Now | 372.5 ± 396.1 | 2638.6 | 2592.3 | 695.8 |
raw | PERSIANN | 4583.3 ± 468.4 | 1951.9 | 1744.9 | −35.3 |
raw | PERSIANN-CCS | 12,344.3 ± 2014.2 | 9472.8 | 9379.4 | −76.0 |
bc | CMORPH | 3796.3 ± 678.4 | 934.6 | 862.0 | −21.9 |
bc | ERA5 | 3704.6 ± 682.5 | 861.5 | 793.2 | −20.0 |
bc | MERRA-2 | 4404.4 ± 782.5 | 1495.9 | 1439.5 | −32.7 |
bc | PDIR-Now | 7412.8 ± 955.9 | 4663.0 | 4447.9 | −60.0 |
bc | PERSIANN | 3846.8 ± 631.5 | 1004.0 | 930.9 | −22.9 |
bc | PERSIANN-CCS | 3777.0 ± 569.8 | 966.8 | 906.2 | −21.5 |
Product | DORI | OUAHIGOUYA | BOGANDE | DEDOUGOU | OUAGADOUGOU | FADA | BOROMO | BOBO | PO | GAOUA | |
---|---|---|---|---|---|---|---|---|---|---|---|
Rainfall | Observed | 3.3 (0.263) | 12.6 (0.069) | 1.9 (0.675) | 4.6 (0.294) | 9.9 (0.014) | −3.8 (0.234) | 8.1 (0.142) | 18.5 (0.080) | −0.0 (1.000) | 10.1 (0.294) |
IMERG | 13.2 (0.208) | 8.2 (0.401) | 5.3 (0.576) | 10.2 (0.234) | 17.0 (0.030) | 9.8 (0.401) | 15.5 (0.069) | 17.0 (0.042) | 6.6 (0.401) | 6.2 (0.401) | |
CMORPH (raw) | 10.1 (0.069) | 19.3 (0.002) | 9.2 (0.124) | 14.8 (0.036) | 9.4 (0.025) | 11.3 (0.080) | 11.1 (0.162) | 20.4 (0.008) | 7.3 (0.327) | 8.1 (0.108) | |
ERA5 (raw) | 3.8 (0.263) | 2.1 (0.484) | 5.4 (0.080) | 6.9 (0.080) | 11.9 (0.021) | 5.4 (0.142) | 8.5 (0.162) | 6.0 (0.363) | 8.1 (0.069) | 7.8 (0.142) | |
MERRA-2 (raw) | 10.4 (0.000) | 8.1 (0.010) | 11.1 (0.005) | 11.4 (0.002) | 17.7 (0.003) | 7.2 (0.208) | 17.8 (0.014) | 13.5 (0.030) | 9.7 (0.142) | 13.4 (0.030) | |
PDIR-Now (raw) | −1.0 (0.944) | 2.3 (0.576) | −1.2 (0.889) | 3.2 (0.726) | 0.6 (0.944) | −1.4 (0.675) | 2.6 (0.441) | −3.2 (0.726) | −4.5 (0.401) | −9.4 (0.184) | |
PERSIANN (raw) | 8.1 (0.294) | 12.1 (0.069) | −0.3 (1.000) | 9.4 (0.184) | −2.3 (0.675) | −3.8 (0.576) | 4.8 (0.675) | 4.5 (0.780) | −8.9 (0.675) | −11.6 (0.093) | |
PERSIANN-CCS (raw) | 49.0 (0.050) | 16.1 (0.234) | 35.4 (0.080) | 18.4 (0.484) | 2.8 (0.889) | −3.4 (0.834) | 5.0 (0.780) | 4.7 (0.726) | 3.0 (0.889) | 21.2 (0.363) | |
CMORPH (bc) | 13.5 (0.059) | 7.7 (0.327) | 10.8 (0.142) | 10.7 (0.108) | 13.0 (0.059) | 4.1 (0.327) | 14.0 (0.080) | 12.6 (0.093) | 6.9 (0.576) | 5.7 (0.401) | |
ERA5 (bc) | 2.1 (0.780) | 9.4 (0.025) | 11.6 (0.184) | 4.9 (0.441) | 22.5 (0.030) | 5.2 (0.263) | 9.9 (0.234) | 12.5 (0.184) | 9.1 (0.108) | 6.5 (0.441) | |
MERRA-2 (bc) | 26.9 (0.001) | 30.9 (0.010) | 36.2 (0.006) | 38.7 (0.008) | 42.2 (0.003) | 30.2 (0.059) | 44.6 (0.008) | 60.7 (0.001) | 49.1 (0.001) | 32.5 (0.036) | |
PDIR-Now (bc) | 9.5 (0.401) | 8.9 (0.624) | 4.1 (0.675) | 4.8 (0.675) | 12.6 (0.327) | 3.6 (0.726) | 7.0 (0.780) | −1.1 (0.944) | 8.0 (0.401) | 0.0 (1.000) | |
PERSIANN (bc) | 3.2 (0.327) | 2.5 (0.726) | 5.6 (0.294) | 4.7 (0.401) | −0.1 (1.000) | 0.8 (0.944) | −3.5 (0.675) | 1.7 (0.780) | −1.5 (0.889) | −0.4 (1.000) | |
PERSIANN-CCS (bc) | 16.9 (0.050) | 5.9 (0.484) | 9.5 (0.208) | 15.0 (0.263) | 10.0 (0.363) | 0.2 (0.944) | 13.1 (0.327) | 12.6 (0.441) | 8.4 (0.401) | 3.8 (0.726) | |
R-factor | IMERG | 50.9 (0.363) | 6.1 (0.889) | 31.6 (0.484) | 42.8 (0.263) | 88.7 (0.036) | −23.3 (0.726) | 51.4 (0.363) | −0.0 (1.000) | −8.5 (0.889) | 20.9 (0.363) |
CMORPH (raw) | 37.7 (0.263) | 78.5 (0.042) | 15.3 (0.780) | 30.9 (0.184) | 61.7 (0.014) | −6.5 (1.000) | 38.7 (0.184) | 51.9 (0.108) | 13.5 (0.484) | 24.3 (0.484) | |
ERA5 (raw) | 5.2 (0.441) | 4.2 (0.529) | −0.4 (0.944) | −1.7 (0.944) | 11.0 (0.162) | −7.4 (0.484) | 10.8 (0.441) | 2.9 (0.726) | 12.9 (0.184) | 3.3 (0.624) | |
MERRA-2 (raw) | 24.1 (0.000) | 26.6 (0.000) | 14.1 (0.021) | 49.3 (0.001) | 29.5 (0.010) | 11.4 (0.208) | 33.9 (0.050) | 25.3 (0.001) | 14.5 (0.017) | 24.3 (0.001) | |
PDIR-Now (raw) | −0.2 (0.675) | 4.4 (0.069) | 2.4 (0.142) | 1.7 (0.726) | 5.3 (0.263) | 3.8 (0.327) | 6.2 (0.484) | −0.5 (1.000) | 9.8 (0.576) | −7.1 (0.576) | |
PERSIANN (raw) | 172.3 (0.003) | 175.7 (0.030) | 77.9 (0.162) | 120.8 (0.017) | 123.2 (0.059) | 97.0 (0.036) | 112.1 (0.012) | 124.5 (0.012) | 51.0 (0.401) | 94.8 (0.017) | |
PERSIANN-CCS (raw) | 526.1 (0.108) | 286.9 (0.124) | 529.9 (0.093) | 371.6 (0.124) | 200.8 (0.294) | 99.7 (0.780) | 219.4 (0.263) | 167.4 (0.484) | 92.9 (0.675) | 431.5 (0.263) | |
CMORPH (bc) | 88.4 (0.208) | 64.8 (0.363) | 69.0 (0.025) | 33.7 (0.529) | 117.4 (0.030) | −53.6 (0.401) | 95.9 (0.080) | −6.0 (0.944) | −1.3 (1.000) | 35.9 (0.401) | |
ERA5 (bc) | −74.0 (0.401) | 74.9 (0.184) | 59.5 (0.363) | 3.8 (0.944) | 133.6 (0.162) | 22.4 (0.780) | 70.9 (0.401) | 105.1 (0.234) | 21.6 (0.889) | −7.6 (0.944) | |
MERRA-2 (bc) | 155.2 (0.069) | 189.4 (0.124) | 146.9 (0.059) | 229.8 (0.002) | 167.8 (0.069) | 129.7 (0.208) | 188.5 (0.050) | 383.0 (0.008) | 318.3 (0.003) | 114.0 (0.208) | |
PDIR-Now (bc) | 82.0 (0.441) | −28.6 (0.834) | −23.6 (0.780) | −16.5 (0.889) | 1.3 (0.944) | −56.1 (0.441) | 131.0 (0.162) | −151.7 (0.108) | 41.4 (0.726) | 18.4 (0.780) | |
PERSIANN (bc) | 5.8 (0.944) | 38.9 (0.529) | 66.4 (0.093) | 43.9 (0.484) | 50.7 (0.363) | −71.5 (0.263) | 25.9 (0.944) | −25.0 (0.441) | 19.6 (0.889) | −5.7 (1.000) | |
PERSIANN-CCS (bc) | 79.8 (0.234) | 6.1 (0.780) | 50.5 (0.363) | 74.5 (0.484) | 94.9 (0.184) | −35.1 (0.726) | 86.3 (0.263) | 36.4 (0.944) | 110.9 (0.363) | 94.6 (0.184) |
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Yonaba, R.; Mounirou, L.A.; Keïta, A.; Fowé, T.; Zouré, C.O.; Belemtougri, A.; Kafando, M.B.; Koïta, M.; Karambiri, H.; Yacouba, H. Exploring the Added Value of Sub-Daily Bias Correction of High-Resolution Gridded Rainfall Datasets for Rainfall Erosivity Estimation. Hydrology 2024, 11, 132. https://doi.org/10.3390/hydrology11090132
Yonaba R, Mounirou LA, Keïta A, Fowé T, Zouré CO, Belemtougri A, Kafando MB, Koïta M, Karambiri H, Yacouba H. Exploring the Added Value of Sub-Daily Bias Correction of High-Resolution Gridded Rainfall Datasets for Rainfall Erosivity Estimation. Hydrology. 2024; 11(9):132. https://doi.org/10.3390/hydrology11090132
Chicago/Turabian StyleYonaba, Roland, Lawani Adjadi Mounirou, Amadou Keïta, Tazen Fowé, Cheick Oumar Zouré, Axel Belemtougri, Moussa Bruno Kafando, Mahamadou Koïta, Harouna Karambiri, and Hamma Yacouba. 2024. "Exploring the Added Value of Sub-Daily Bias Correction of High-Resolution Gridded Rainfall Datasets for Rainfall Erosivity Estimation" Hydrology 11, no. 9: 132. https://doi.org/10.3390/hydrology11090132