Unveiling Deviations from IPCC Temperature Projections through Bayesian Downscaling and Assessment of CMIP6 General Circulation Models in a Climate-Vulnerable Region DOI Creative Commons
Giovanni-Breogán Ferreiro-Lera, Ángel Penas, Sara del Río

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(11), P. 1831 - 1831

Published: May 21, 2024

The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, proficiency of GCMs in replicating reanalyzed 1981–2010 temperature data sourced from ERA5 Land was assessed. Initially, least data-modifying interpolation method for achieving resolution match 0.1° ascertained. Subsequently, pixel-by-pixel evaluation conducted, employing five goodness-of-fit metrics. From these metrics, we compiled Comprehensive Rating Index (CRI). A Multi-Model Ensemble using Random Forest constructed projected across three emission scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP5-RCP8.5) timeframes (2026–2050, 2051–2075, 2076–2100). Empirical Bayesian Kriging, selected its minimal alteration, supersedes commonly employed Bilinear Interpolation. results underscore MPI-ESM1-2-HR, GFDL-ESM4, CNRM-CM6-1, MRI-ESM2-0, CNRM-ESM2-1, IPSL-CM6A-LR top-performing models. Noteworthy geospatial disparities model performance were observed. projection outcomes, divergent IPCC forecasts, revealed warming trend 1 over 2 °C less than anticipated spring winter medium–long term, juxtaposed with heightened mountainous/elevated regions. These findings could substantially refine projections Euro-Med, facilitating implementation policy strategies mitigate effects regions worldwide.

Language: Английский

Evaluating the performance of snow depth reanalysis products in the arid region of Central Asia DOI Creative Commons
Liancheng Zhang,

Guli·Jiapaer,

Tao Yu

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 22, 2025

Language: Английский

Citations

0
Assessment of five global gridded precipitation estimates over a southern Mediterranean basin (Tensift, Morocco) DOI Creative Commons

Kaoutar Oukaddour,

Younes Fakır, Michel Le Page

et al.

Geomatics Natural Hazards and Risk, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 25, 2025

Gridded Precipitation Products (GPPs) could exhibit discrepancies related to detecting precipitation amounts and patterns. This paper aims evaluate the accuracy of five GPPs currently in operational production over Tensift basin southern Mediterranean. The are reanalysis-based (ERA5, ERA5-Land, MERRA-2) multi-source data fusion (TerraClimate, MSWEPv2.8). Their annual monthly compared observations from fourteen ground gauges entire period 1980 2021 each decade this period. A set statistical metrics, such as Kling Gupta Efficiency (KGE) Root Mean Square Error (RMSE), well Bias, served carry out evaluation. Four main findings be highlighted: (i) have, general, a good correlation with gauge data; hence they used study temporal variability observed precipitation. (ii) ERA5-Land does not bring significant improvements estimates apart its finer spatial resolution. (iii) perform better plain than mountains. (iv) TerraClimate MSWEPv2.8 present consistency across decades. ERA5 TerraClimate, longest series, were visualize trends basin.

Language: Английский

Citations

0
Ensemble learning of decomposition-based machine learning models for multistep-ahead daily streamflow forecasting in northwest China DOI

Haijiao Yu,

Linshan Yang, Qi Feng

et al.

Hydrological Sciences Journal, Journal Year: 2024, Volume and Issue: 69(11), P. 1501 - 1522

Published: July 1, 2024

Accurate daily streamflow forecasts remain challenging in arid regions. A Bayesian Model Averaging (BMA) ensemble learning strategy was proposed to forecast 1-, 2-, and 3-day ahead Dunhuang Oasis, northwest China. The efficiency of BMA compared with four decomposition-based machine deep models. Satisfactory were achieved all models at lead times; however, based on NSE values 0.976, 0.967, 0.957, the greatest accuracy for forecasts, respectively. Uncertainty analysis confirmed reliability yielding consistently accurate forecasts. Thus, could provide an efficient alternative approach multistep-ahead forecasting. incorporation data decomposition techniques (e.g. Variational mode decomposition) algorithms Deep belief network) into BMA, may serve as worthy technical references supervised systems scare

Language: Английский

Citations

2
Unveiling Deviations from IPCC Temperature Projections through Bayesian Downscaling and Assessment of CMIP6 General Circulation Models in a Climate-Vulnerable Region DOI Creative Commons
Giovanni-Breogán Ferreiro-Lera, Ángel Penas, Sara del Río

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(11), P. 1831 - 1831

Published: May 21, 2024

The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, proficiency of GCMs in replicating reanalyzed 1981–2010 temperature data sourced from ERA5 Land was assessed. Initially, least data-modifying interpolation method for achieving resolution match 0.1° ascertained. Subsequently, pixel-by-pixel evaluation conducted, employing five goodness-of-fit metrics. From these metrics, we compiled Comprehensive Rating Index (CRI). A Multi-Model Ensemble using Random Forest constructed projected across three emission scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP5-RCP8.5) timeframes (2026–2050, 2051–2075, 2076–2100). Empirical Bayesian Kriging, selected its minimal alteration, supersedes commonly employed Bilinear Interpolation. results underscore MPI-ESM1-2-HR, GFDL-ESM4, CNRM-CM6-1, MRI-ESM2-0, CNRM-ESM2-1, IPSL-CM6A-LR top-performing models. Noteworthy geospatial disparities model performance were observed. projection outcomes, divergent IPCC forecasts, revealed warming trend 1 over 2 °C less than anticipated spring winter medium–long term, juxtaposed with heightened mountainous/elevated regions. These findings could substantially refine projections Euro-Med, facilitating implementation policy strategies mitigate effects regions worldwide.

Language: Английский

Citations

1