Published: Jan. 1, 2024
Language: Английский
Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: 52(10), P. 2251 - 2265
Published: July 15, 2024
Language: Английский
Citations
2
Atmospheric Research, Journal Year: 2024, Volume and Issue: 313, P. 107761 - 107761
Published: Nov. 5, 2024
Language: Английский
Citations
2
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Nov. 26, 2024
The Indian summer monsoon (ISM) is a complex and multiscale interacting climate system, which responsible for major contribution in India's annual rainfall. Understanding the spatial temporal variability of ISM rainfall critical managing water resources, directly impact regulate functioning socio-economic conditions subsequently, sustenance over billion people. This study evaluates suitability various gridded precipitation data products with different spatiotemporal resolutions, essential requirement hydrologic modeling, disaster mitigation, irrigation allocation agricultural application. Hence, we evaluate performance seven datasets generating time-matched characteristic event occurrences their respective magnitudes using gauge-based Meteorological Department (IMD) as reference. We observe that reanalysis underperform compared to satellite hybrid identifying both normal extreme events. develop measure, called 'rank score' considers deviations from IMD magnitude, statistical moments, rain detectability robust assessment best-suited dataset. Results indicate APHRODITE, MSWEP, CHIRPS (in descending order) are most suitable across India. Additionally, region-specific evaluations provide valuable insights into applicability these climatic homogeneous zones.
Language: Английский
Citations
2
Journal of Hydrologic Engineering, Journal Year: 2024, Volume and Issue: 30(1)
Published: Oct. 28, 2024
Language: Английский
Citations
1
Disaster risk reduction, Journal Year: 2024, Volume and Issue: unknown, P. 279 - 305
Published: Jan. 1, 2024
Language: Английский
Citations
1
Climate Dynamics, Journal Year: 2024, Volume and Issue: 63(1)
Published: Dec. 4, 2024
Language: Английский
Citations
1
International Journal of Climatology, Journal Year: 2024, Volume and Issue: 45(2)
Published: Dec. 10, 2024
ABSTRACT Precipitation, a crucial component of the Earth system processes, regulates spatiotemporal cyclicity water, energy, and carbon fluxes. Accurate precipitation datasets leverage understanding dynamics are vital for hydro‐climatological studies. South Asian monsoon is complex, multi‐scale interacting, synoptic, ocean–land–atmosphere coupled system, contributing to significant spatial temporal variability in summer monsoonal rainfall across India. This study evaluates four types gridded (observational, satellite, reanalysis, hybrid) products their ability replicate Indian Summer Monsoonal Rainfall (ISMR) characteristics using India Meteorological Department (IMD) 0.25° data as baseline. A comparative assessment performed this that uses several continuous interval‐based performance measures evaluate overall magnitude detectability time‐matched capturing events. new metric, rank score, developed by aggregating multiple find best product. The analyses based on indicate MSWEP dataset (rank one) closely approximates occurrence IMD‐based events, while APHRODITE, CHIRPS, IMDAA ranked next set products. PGF lowest among all evaluated not recommended applications. Nonetheless, APHRODITE suffers from strong negative biases, reanalysis (IMDAA, ERA5‐Land, PGF) show positive biases. Among evaluated, have shown limited detect excess, normal, deficit years, respectively. In general, satellite‐based superior accurately characterising years. ERA5‐Land noted be best‐performing comprehensive carried out benefits selection use appropriate hydroclimatic modelling, climate variability, change
Language: Английский
Citations
1
Published: Jan. 1, 2024
The section of the Yellow River between its source and Hekou Town in Inner Mongolia is known as Upper Basin. It main area water resources Basin, providing reliable for 120 million people. Studying hydrometeorological changes Basin crucial development human society. However, past, there has been limited research on In order to clarify four-dimensional spatiotemporal variation characteristics elements satellite reanalysis products need be used. Unfortunately, currently a lack precise evaluation studies geomorphic this have raised doubts about accuracy products. Thus, study an important prerequisite studying elements. When conducting study, we found that previous had very confusing understanding datasets. Some papers even treated metrics Therefore, introduced spacetime both datasets rectify chaotic view past. Our results show different abilities describing temporal spatial distribution change difference ability describe requires us select data at scales according needs when research, ensure credibility results.
Language: Английский
Citations
0
Published: Jan. 1, 2024
Language: Английский
Citations
0
Published: Dec. 2, 2024
Abstract. This study provides a comprehensive evaluation of eight high spatial resolution gridded precipitation products in semi-arid regions Tamil Nadu, India, focusing specifically on Coimbatore, Madurai, Tiruchirappalli, and Tuticorin, where both irrigated rainfed agriculture is prevalent. The lack sufficiently long-term spatially representative observed data, essential for agro-hydrological studies better understanding managing the nexus between food production water soil management. Hence, present evaluates accuracy five remote sensing-based products, viz. Tropical Rainfall Measuring Mission (TRMM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Records (PERSIANN CDR), CPC MORPHing technique (CMORPH), Global Measurement (GPM) Multi-Source Weighted-Ensemble (MSWEP) three reanalysis-based National Center Environmental Prediction Reanalysis 2 (NCEP2), European Centre Medium-Range Weather Forecast (ECMWF) version 5 Land (ERA5-Land), Modern-Era Retrospective analysis Research Application (MERRA 2) against station data. Linearly interpolated were statistically evaluated at two (grid district-wise) temporal (daily, monthly, yearly) resolutions 2003–2014. Based overall statistical metrics, ERA was best-performing product with MSWEP closely behind. In however, outperformed others. On other hand, MERRA2 NCEP2 performed worst all regions, as indicated by their higher Root Mean Square Error (RMSE) lower correlation values. Except most underestimated monthly monsoon precipitation, which highlights need algorithm capturing convective events. Also, Percent Absolute (%MAE) non-monsoon months, indicating that these product-based modeling, like irrigation scheduling water-scarce periods, may be less reliable. ability to capture extreme intensity differed best Coimbatore PERSIANN CDR ERA5-Land Tuticorin. offers crucial guidance resources agricultural areas, especially data-scarce helping select suitable bias correction methods research.
Language: Английский
Citations
0