
Agricultural Water Management, Journal Year: 2024, Volume and Issue: 306, P. 109207 - 109207
Published: Dec. 1, 2024
Language: Английский
Agricultural Water Management, Journal Year: 2024, Volume and Issue: 306, P. 109207 - 109207
Published: Dec. 1, 2024
Language: Английский
Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 2, 2025
Language: Английский
Citations
1Advances in Climate Change Research, Journal Year: 2024, Volume and Issue: 15(6), P. 1027 - 1039
Published: Oct. 21, 2024
Language: Английский
Citations
4Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)
Published: April 29, 2025
Language: Английский
Citations
0Climatic Change, Journal Year: 2025, Volume and Issue: 178(5)
Published: April 30, 2025
Language: Английский
Citations
0Meteorological Applications, Journal Year: 2024, Volume and Issue: 31(4)
Published: July 1, 2024
Abstract Accurate predictions of streamflow and flood events are contingent upon the availability reliable hydrometeorological data. In regions characterized by scarcity ground‐based observations, satellite reanalysis data assume prominence as alternative predictors. Floods droughts have emerged a significant concern in Northern Ghana, yet impedes effective prediction these hydrological events. Consequently, identification suitable surrogate holds paramount importance addressing challenges. This study, therefore, assessed accuracy against Ghana. Rainfall mean temperature spanning from 1998 to 2019 soil moisture datasets 2022 were collected GMet, ISMN (ground‐based), CHIRPS, PERSIANN‐CDR, ERA5, ARC2, MERRA‐2, TRMM CFSR (satellite reanalysis). Employing rigorous statistical measures, namely standard deviation, absolute error (MAE) bias (MBE), was thoroughly evaluated. The results revealed that CHIRPS PERSIANN‐CDR exhibited superior rainfall simulation, with demonstrating particularly consistent congruence observed terms prediction, ERA5 surpassed MERRA‐2 CFSR. Regarding assessments, both offered satisfactory simulations. Hence, our findings advocate for preference (for data), data) combination CFSR/ERA5 dependable primary sources modelling, drought analysis, water resource management context
Language: Английский
Citations
3International Journal of Climatology, Journal Year: 2023, Volume and Issue: 43(14), P. 6643 - 6663
Published: Aug. 23, 2023
Abstract This study evaluates the reliability of ERA5 and ERA5‐Land reanalysis datasets in describing mean daily air temperature four climate domains mainland Portugal. The were compared with ground observations from 94 meteorological stations (1980–2021). Overall, results demonstrated a good degree correlation between observed data on both seasonal scale. Both latitudinal distribution moderating effect Atlantic Ocean are well described. However, case Portugal, was shown to be considerably more effective at than ERA5. also indicated that, general, methodologies perform better when applied simulation flatter regions as opposed high‐altitude complex terrain. further suggests that should used caution short‐term environmental studies. In fact, relevant differences exist reanalyses for certain specific years. considering RMSE there is 28% probability locally having <1.5°C, 52% >1.5°C <2.0°C, 16% >2.0°C <3.0°C. These conclusions will hopefully contribute improving our understanding uncertainty sources relation different domains.
Language: Английский
Citations
6Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(9), P. 3639 - 3656
Published: July 13, 2024
Language: Английский
Citations
2Theoretical and Applied Climatology, Journal Year: 2024, Volume and Issue: 155(12), P. 10051 - 10067
Published: Nov. 1, 2024
Language: Английский
Citations
2Journal of Quantitative Spectroscopy and Radiative Transfer, Journal Year: 2024, Volume and Issue: 326, P. 109118 - 109118
Published: July 14, 2024
Language: Английский
Citations
0Agricultural Water Management, Journal Year: 2024, Volume and Issue: 306, P. 109207 - 109207
Published: Dec. 1, 2024
Language: Английский
Citations
0