Improving the accuracy of gridded snow depth estimation through multi-source data and a machine learning fusion model. [PDF]
Qiao D, Chen X, Zhou J, Liang S, Liu G.
europepmc +1 more source
Classification of Fog Life‐Cycle Phases Using Ground‐Based and Satellite‐Based Observations
In this study, the life‐cycle phases of radiation fog events—formation, maturity, and dissipation—are automatically classified at a ground station in Southwest Germany based on visibility trends and thresholds. We demonstrate that visibility detects radiation fog phases effectively, while its combination with ceilometer data can detect the life‐cycle ...
Maria Laura Pinilla +3 more
wiley +1 more source
Topographically-controlled contribution of avalanches to glacier mass balance in the 21st century. [PDF]
Kneib M +11 more
europepmc +1 more source
Physically consistent mesoscale model evaluation in complex terrain
This study introduces a novel approach for evaluating mesoscale atmospheric models in complex terrain by selecting physically consistent grid points and applying height‐based corrections. The method corrects for sensor height and terrain elevation differences between model and observations using a time‐varying lapse rate.
Gaspard Simonet +2 more
wiley +1 more source
Modeling Current and Future Habitat Suitability for the Snow Leopard (<i>Panthera uncia</i>) Under Climate Change Scenarios in Nepal. [PDF]
Budha M, Karki J, Khadka B, Koju NP.
europepmc +1 more source
Direct measurement of bidirectional turbulent fluxes of atmospheric cluster ions
First direct eddy covariance measurements of vertical turbulent fluxes of atmospheric cluster ions are presented. The net turbulent flux was mostly positive for negative cluster ions (net emission of negative ions) and mostly negative for positive cluster ions (net deposition of positive ions).
Luzie Kamecke +2 more
wiley +1 more source
Snow Cover Detection Based on Visible Red and Blue Channel from MODIS Imagery Data
Paipai Pan +3 more
openalex +2 more sources
Assessing wildfire dynamics during a megafire in Portugal using the MesoNH/ForeFire coupled model
Weather conditions affect megafires by inducing different fire behaviors over several days or weeks. The coupled MesoNH/ForeFire code was used to represent the dynamics of fire generating pyro‐convective clouds. To advance the understanding of wildfire dynamics, high‐resolution coupled fire–atmosphere modeling was employed.
Cátia Campos +12 more
wiley +1 more source

