Results 191 to 200 of about 25,084 (264)

Satellite and Reanalysis Dataset Dependence of ETCCDI Extreme Precipitation Trends in Paraná, Southern Brazil

International Journal of Climatology, EarlyView.
Extreme precipitation trends detected in Paraná, Southern Brazil (1983–2024), are strongly conditioned by the dataset used, with reanalyses indicating coherent inland drying and longer dry spells, observations retaining stronger mesoscale heterogeneity, and satellite products often showing declines in short‐duration extremes. Monthly diagnostics reveal
Paulo Miguel de Bodas Terassi, Jakeline Baratto, Vitor Hugo Rosa Biffi   +2 more
wiley   +1 more source

GNSS evaluation of GRACE-assimilated water storage models over 89 river basins worldwide. [PDF]

Sci Rep
Abbaszadeh M, van Dam T.
europepmc   +1 more source

Multi‐Timescale Drought Evolution in Greece (1960–2022) From Station‐Based SPI and SPEI

International Journal of Climatology, EarlyView.
Using homogenized data from 67 HNMS stations in Greece (1960–2022), we calculated SPI and SPEI at 1–12‐month scales to characterize meteorological to hydrological drought. We quantified the network‐based spatial extent of drought, compared SPI and SPEI drought signals, and tested changes with autocorrelation‐robust Mann–Kendall trends and Pettitt ...
Michael Samouris, Anna Mamara, Vasileios Armaos, Athanassios Argiriou   +3 more
wiley   +1 more source

Seasonal forecasting of dissolved organic carbon in a Mediterranean catchment: Enhancing upstream control of disinfection by-product precursors. [PDF]

Environ Monit Assess
Pedregal-Montes A, Mercado-Bettín D, Futter M, Ledesma JLJ, Farré MJ, Marcé R, Jennings E.   +6 more
europepmc   +1 more source

Station‐Based Assessment of Sub‐Seasonal Climate Trends in the Tyrolean Alps (Austria)

International Journal of Climatology, EarlyView.
In this study, we quantify the magnitude and significance of sub‐seasonal trends in the Tyrolean Alps (Austria) by collecting, processing and analysing meteorological observations from a dense network of climate stations. Our analysis indicates a warming rate of 0.43°C/dec over 1964–2023, greater sub‐seasonal trend variability when the analysis window ...
Erwin Rottler, Elena Bertazza, Franz Wagner, Gertraud Meißl, Theresa Schellander‐Gorgas, Johannes Schöber, Ulrich Strasser   +6 more
wiley   +1 more source

Implications of snowmelt and rainfall erosion effects for soil organic carbon management in semi-arid alpine ecosystems: a case study of the qilian mountains, China. [PDF]

Carbon Balance Manag
Liu Z, Si J, Xiao S, Jia B, Zhou D, Zhu X, Bai X, Wang B, Ndayambaza B.   +8 more
europepmc   +1 more source

Machine Learning‐Based Correction of Reanalysis Surface Radiation Fluxes Using Ground‐Measured Data in the Southern Brazilian Pampa Biome

International Journal of Climatology, EarlyView.
This study demonstrates that ERA5 provides more accurate surface radiation flux estimates than MERRA2 across the Southern Brazilian Pampa. Machine learning models, particularly Random Forest, further improved the precision of reanalysis data for climate applications.
Olusola Samuel Ojo, Michel Baptistella Stefanello, Alecsander Mergen, Maria Eduarda Oliveira Pinheiro, Vanessa de Arruda Souza, Débora Regina Roberti   +5 more
wiley   +1 more source

Impact and evolution of hydrological drought in Dagu River Basin under the shared socioeconomic pathways. [PDF]

Sci Rep
Yang H, Kang F, Yang F, Li J, Zheng T, Qin P.   +5 more
europepmc   +1 more source

Statistical Downscaling of Daily Temperature and Precipitation From Regional Climate Models in Complex Mountain Terrain

International Journal of Climatology, EarlyView.
The study provides insights for post‐processing climate model output in complex terrain, useful for climate change impact models. We compared different bias adjustment and downscaling techniques from quantile delta mapping to simple lapse rates. We developed a new spatial downscaling method based on principal components analysis, which showed superior ...
Michael Matiu, Anna Napoli, Alberto Bellin, Dino Zardi, Bruno Majone   +4 more
wiley   +1 more source

Integrating geospatial intelligence and machine learning for flood susceptibility mapping. [PDF]

Sci Rep
Rahimi M, Malekmohammadi B, Firozjaei MK, Kerachian R, Arsanjani JJ, Tan ML, Awange J, Savic D, Duan Q, AghaKouchak A.   +9 more
europepmc   +1 more source