Mesoscale Convective Systems in Northeastern North America: identification and evaluation with the convection-permitting version of the Canadian Regional Climate Model. [PDF]
Alpizar M +3 more
europepmc +1 more source
Ecosystem‐Scale Methane Emissions From Peatlands of the Hudson Bay Lowlands
Abstract Northern peatlands are important sources of methane (CH4) in the atmosphere. However, the magnitude of CH4 emissions and their response to environmental factors are poorly constrained within the Hudson Bay Lowlands (HBL), the largest contiguous peatland complex in North America. This study investigated seasonal (April–November) eddy covariance‐
A. Bieniada, E. R. Humphreys
wiley +1 more source
Robust increase in observed heat storage by the global subsurface. [PDF]
Cuesta-Valero FJ +5 more
europepmc +1 more source
Abstract This study proposes a new scheme combining ensemble blending and dual‐localization of ensemble error covariance in an ensemble‐variational (EnVar) framework to better account for both the multi‐scale characteristics of the background and background error covariance for high‐resolution data assimilation and forecasting.
Yuanbing Wang +5 more
wiley +1 more source
Contrary effects of soil moisture-atmosphere feedback on dry and humid heatwaves. [PDF]
Chen S +5 more
europepmc +1 more source
Global Kilometer‐Scale Climate Storylines Using Spectral Nudging
Abstract Effective climate adaptation benefits from detailed, actionable information on how specific extreme events are influenced by climate change. Here we present the first global, kilometer‐scale coupled modeling framework that enables counterfactual reconstructions of recent weather events, including extremes, in different climates.
Amal John +22 more
wiley +1 more source
Gap-Filling for Daily Latent Heat Flux Observations with the Full-factorial method at Global Flux Sites. [PDF]
Wang X, Tang F, Jiang Y, Lou Y.
europepmc +1 more source
Capturing Spatiotemporal and Subgrid Variability in Global Land Surface Albedo Parameterization
Abstract Accurate surface albedo parameterization is critical for modeling Earth's energy balance. Yet, many schemes rely on static look‐up tables or semi‐empirical formulations that fail to capture spatiotemporal variations and complex radiative interactions. This study develops a physics‐informed machine‐learning parameterization using 19 years (2003–
Akarsh Ralhan, Xin‐Zhong Liang
wiley +1 more source
The UFLUX ensemble of multiple-scale carbon, water, and energy fluxes. [PDF]
Zhu S +9 more
europepmc +1 more source
Abstract The Surface Water and Ocean Topography (SWOT) satellite has enabled river discharge estimation for global rivers including ungauged regions. This remotely sensed discharge (SwRSQ) generated from SWOT's cloud‐penetrating measurements of river widths, water surface elevation, and slope is expected to have improved accuracy and spatiotemporal ...
Y. Ishikawa +6 more
wiley +1 more source

