Results 181 to 190 of about 1,912,794 (271)

Assessing Co‐Located NISAR and Sentinel‐1 Observations for Atmospheric Characterization

open access: yesJournal of Geophysical Research: Atmospheres, Volume 131, Issue 19, 16 October 2026.
Abstract Tropospheric delay remains one of the largest sources of uncertainty in repeat‐pass Interferometric Synthetic Aperture Radar (InSAR) measurements, while accurate three‐dimensional deformation retrieval continues to be limited by the geometry of current spaceborne SAR systems.
Shadi Oveisgharan   +3 more
wiley   +1 more source

High‐Throughput Geocoding to Assess Short‐Term Air Pollution in Correlation With Mortality in a French Cancer Patient Cohort

open access: yesInternational Journal of Cancer, Volume 159, Issue 8, Page 2054-2065, 15 October 2026.
Although chronic air pollution exposure is linked to lung cancer mortality, the short‐term effects of fluctuating air quality on overall cancer mortality remain uncertain. Here, the authors applied geomatics and machine‐learning models to retrospectively examine possible associations between 31‐day pollution exposure and mortality in a French cancer ...
Loice Pokam   +12 more
wiley   +1 more source

Low Latency Global Carbon Budget Reveals Late 2024 Carbon Losses and Contrasting Early 2025 Land Sink Recovery Signals. [PDF]

open access: yesAdv Sci (Weinh)
Ke P   +32 more
europepmc   +1 more source

Climate Change Contribution to Seasonal Forecast Anomalies Using Constrained CMIP6 Projections

open access: yesAtmospheric Science Letters, Volume 27, Issue 10, October 2026.
This study introduces a new method to estimate this climate change contribution, based on a Bayesian technique called Kriging for Climate Change (KCC), which combines CMIP6 simulations and initialized seasonal hindcasts to estimate the forced response within the model. This new method provides a scientific basis for improved real‐time interpretation of
Louis Ledoux‐‐Xatard   +3 more
wiley   +1 more source

Bridging Artificial Intelligence and Data Assimilation: The Data‐Driven Ensemble Weather Forecasting System ClimaX‐LETKF

open access: yesAtmospheric Science Letters, Volume 27, Issue 10, October 2026.
We developed ClimaX‐LETKF, a weather forecasting system that combines the foundation machine learning‐based weather prediction model ClimaX with a conventional data assimilation system. The system achieves stable multiyear data assimilation cycling using NCEP upper‐air global observations.
Akira Takeshima   +4 more
wiley   +1 more source

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