How do gridded meteorological datasets perform in a typical data-scarce cryospheric basin?

Advances in Climate Change Research, Journal Year: 2024, Volume and Issue: 15(6), P. 1027 - 1039

Published: Oct. 21, 2024

Language: Английский

Regional Drought Monitoring Using Satellite-Based Precipitation and Standardized Palmer Drought Index: A Case Study in Henan Province, China

Water, Journal Year: 2025, Volume and Issue: 17(8), P. 1123 - 1123

Published: April 9, 2025

Drought poses significant challenges to agricultural productivity and water resource sustainability in Henan Province, emphasizing the need for effective monitoring approaches. This study investigates suitability of TRMM 3B43V7 satellite precipitation product drought assessment, based on monthly data from 15 meteorological stations during 1998–2019. Satellite-derived was compared with ground-based observations, Standardized Palmer Index (SPDI) calculated determine optimal timescale. Statistical metrics, including Nash–Sutcliffe Efficiency (NSE = 0.87) Pearson correlation coefficient (PCC 0.88), indicate high consistency between ground measurements. The 12-month SPDI (SPDI-12) found be most capturing historical variability. To support integrated management, a regionally adaptive framework is recommended, balancing demands ecosystem stability through tailored strategies such as enhanced irrigation efficiency humid regions ecological restoration arid zones. These findings provide foundation implementing an operational response system Province.

Language: Английский

Performance Evaluation of Satellite Precipitation Products During Extreme Events—The Case of the Medicane Daniel in Thessaly, Greece

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4216 - 4216

Published: Nov. 12, 2024

Mediterranean tropical-like cyclones, or Medicanes, present unique challenges for precipitation estimations due to their rapid development and localized impacts. This study evaluates the performance of satellite products in capturing associated with Medicane Daniel that struck Greece early September 2023. Utilizing a combination ground-based observations, reanalysis, satellite-derived data, we assess accuracy spatial distribution GPM IMERG, GSMaP, CMOPRH during cyclone event, which formed Eastern from 4 7 2023, hitting unprecedented, enormous amounts rainfall, especially region Thessaly central Greece. The results indicate that, while demonstrate overall skill broad-scale patterns Daniel, discrepancies exist estimating intense rainfall rates, particularly convective cells within cyclone’s core. Indeed, most studied this work showed misplacement highest significant underestimation large unbiased root mean square error areas heavy precipitation. total field IMERG Late Run CMORPH smallest bias (but significant) good temporal correlation against rain gauges ERA5-Land reanalysis data as reference, Final GSMaP largest overestimation, respectively. Further investigation is needed improve representation extreme events cyclones products.

Language: Английский