Results 241 to 250 of about 32,789 (349)
GDO Warm Spell Daily Minimum Temperature Exceedance ERA5 (version 2.0.0)
EDO European and Global Drought Observatories
openalex +1 more source
Abstract Convection‐permitting dynamical downscaling (CPDD) allows for an explicit representation of the convective storms that generate tornadoes, hail, severe thunderstorm winds, and locally heavy precipitation. Possible changes in such hazardous convective weather (HCW) due to human‐induced climate change are therefore projected with higher ...
Songning Wang +4 more
wiley +1 more source
Evaluating multi-source precipitation data for streamflow simulation using the SWAT model in the Alpine Manas River Basin, Northwest China. [PDF]
Tan L, Zan C, Liu T, Xiong J, Zhang A.
europepmc +1 more source
Generalized Additive Model With Dynamic Coefficients for Spatiotemporal Ozone Predictions
ABSTRACT Accurate prediction of surface‐level ozone concentrations is critical for air quality management and public health protection. This study develops a flexible spatiotemporal statistical modeling framework to predict daily mean O3 concentrations across Italy by integrating satellite‐derived ozone estimates with ground‐based observations and high‐
Abdollah Jalilian +3 more
wiley +1 more source
Evolving synchronization of the Gulf Stream and Kuroshio-Oyashio Extension in a changing climate. [PDF]
Joh Y +7 more
europepmc +1 more source
DCENT‐I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset
DCENT‐I infills data gaps in DCENT, producing spatially coherent temperature fields (top) and a slightly higher GMST warming estimate (bottom). Top: December 1877 temperature anomalies (°C; 1961–1990 December baseline) from DCENT (left) and DCENT‐I (right). Bottom: GMST before (DCENT, blue) and after (DCENT‐I, red) infilling.
Duo Chan +8 more
wiley +1 more source
An Hourly Dataset of Moisture Budget Components Over the Indian Subcontinent (1940-2024). [PDF]
Raghuvanshi AS, Agarwal A.
europepmc +1 more source
GloMarGridding: A Python Toolkit for Flexible Spatial Interpolation in Climate Applications
Global surface climate datasets contain structural uncertainty that is difficult to attribute to individual processing steps. We present GloMarGridding, a Python package that isolates the spatial interpolation component using Gaussian Process Regression (or kriging) to generate spatially complete fields and uncertainty estimates. The techniques used in
Richard C. Cornes +6 more
wiley +1 more source

