Results 161 to 170 of about 29,399 (298)

Exploring Ways to Reduce Biases in a Hybrid Global Climate Model With Machine‐Learned Moist Physics

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract In a previous study (Han et al., 2023, https://doi.org/10.1029/2022ms003508), we implemented a deep convolutional residual neural network for moist physics into the 3‐D real‐geography CAM5 and carried out a stable multi‐year integration successfully. However, the simulation has large temperature and moisture biases in high latitude troposphere
Yilun Han, Guang J. Zhang, Yong Wang
wiley   +1 more source

Large discrepancies in dominant microphysical processes governing mixed-phase clouds across climate models. [PDF]

NPJ Clim Atmos Sci
Frostenberg HC, Costa-Surós M, Georgakaki P, Proske U, Sotiropoulou G, May E, Neubauer D, Eriksson P, Gonçalves Ageitos M, Nenes A, Pérez García-Pando C, Seland Ø, Ickes L.   +12 more
europepmc   +1 more source

Bridging the Energy Balance Gap in Eddy‐Covariance Measurements: Insights From Standardized Network Data

Global Change Biology, Volume 32, Issue 5, May 2026.
Written Summary: Measuring energy exchanges between land and atmosphere is fundamental to understanding climate, but these measurements are systematically incomplete, with 20%–40% of energy consistently unaccounted for. Analyzing data from 84 sites worldwide, we show that carefully tracking all energy components and applying strict data quality filters
Giacomo Nicolini, David Durden, Luca Di Fiore, Christopher Florian, Simone Sabbatini, Bert Gielen, Arne Iserbyt, Benjamin Loubet, Ivan Mammarella, Adriana Mariotti, Maarten Op de Beeck, Caleb Slemmons, Carlo Trotta, Adam Young, Abad Chabbi, Iris Feigenwinter, Bernard Heinesch, Natalia Kowalska, Matthias Mauder, Ladislav Šigut, Michiel van der Molen, Flavio Bastos Campos, Daniel Berveiller, Christian Brümmer, Matthias Cuntz, Jean‐Christophe Domec, Benjamin Dumont, Silvano Fares, Damiano Gianelle, Rasmus Jensen, Carmen Kalalian, Natascha Kljun, Holger Lange, Jean‐Marc Limousin, Erik Lundin, Antonio Manco, Leonardo Montagnani, Eiko Nemitz, Matthias Peichl, Erkka Rinne, Marilyn Roland, Marius Schmidt, Guillaume Simioni, Abin Thomas, Caroline Vincke, Dario Papale   +45 more
wiley   +1 more source

Developing an optimized parameterization scheme for deriving a lightning threat product from a global model for all seasons over India. [PDF]

Sci Rep
Mohan GM, Sandhya M, Jayakumar A, Anurose TJ, Mohandas S, Prasad VS.   +5 more
europepmc   +1 more source

The Dissipation Regime of Turbulence on Mars Observed With Microphone Data From the Mars 2020 Perseverance Rover

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Turbulent winds are a regular occurrence in planetary boundary layers. Turbulence affects mixing, energy fluxes and forcing on the surface environment. Energy injected into an atmosphere generates eddies of many scales down to a size where molecular viscous forces dominate, termed the Kolmogorov length scale.
Alexander E. Stott, Naomi Murdoch, Martin Gillier, German Martinez, Tanguy Bertrand, Ralph Lorenz, Claire Newman, Ricardo Hueso, Manuel de la Torre Juárez, Donald Banfield, Sylvestre Maurice, Baptiste Chide, Jose Antonio Rodriguez Manfredi, David Mimoun   +13 more
wiley   +1 more source

Antarctic Meltwater‐Stratification Feedback Is Less Pronounced Under High Climate Forcing

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Several studies have shown sub‐surface warming in the Southern Ocean via an increase in meltwater flux from the Antarctic Ice Sheet (AIS), which can lead to a positive feedback through enhanced basal melting. In this study, we investigate how the feedback strength is related to the prevailing climate in a coupled climate–ice‐sheet model.
Moritz Kreuzer, Torsten Albrecht, Willem Huiskamp, Stefan Petri, Johannes Feldmann, Georg Feulner, Ricarda Winkelmann   +6 more
wiley   +1 more source

Short‐Term Forecasting of Cloud Physical Properties Based on Fourier Neural Operator Method

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Accurately understanding the evolution and development of cloud physical properties (CPP) in advance is crucial for extreme weather forecasting and early warning. This study utilized the Fourier neural operator (FNO) method to develop a short‐term forecasting model of Cloud (Cloud‐FNO).
Feng Zhang, Xin Hong, Zhijun Zhao, Zeyu Gan, Pengxiang Ouyang, Haixia Xiao, Renhe Zhang, Xujun Wei, Miao Cai, Feng Lu   +9 more
wiley   +1 more source

Urban-resolved scales amplifies torrential rainfall in coastal megacities. [PDF]

Sci Rep
Teja KR, Bale R, Gupta A.
europepmc   +1 more source

Bayesian Estimates of Ice Optical Properties for Lake Ice Modeling

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Ice and snow cover on frozen lakes is a natural barrier to solar radiation, reducing the transfer of energy that controls under‐ice thermal dynamics and biological productivity. Direct measurements of under‐ice irradiance remain scarce due to logistical constraints.
G. Donini, C. Agostinelli, G. A. Weyhenmeyer, G. Kirillin, M. Leppäranta, G. E. Zdorovennova, I. A. Aslamov, J. A. Culpepper, H. A. Dugan, I. V. Fedorova, E. Jakobsson, R. L. North, Iu.S. Novikova, N. I. Palshin, N. J. T. Pearce, J. Robinson, K. Shchapov, K. Vikström, M. A. Xenopoulos, X. Yang, R. E. Zdorovennov, S. Piccolroaz   +21 more
wiley   +1 more source

Local cloud enhancement associated with urban morphology: evidence from observations and idealized large-eddy simulations. [PDF]

Nat Commun
Cui Y, Chen S, Xue L, Muñoz-Esparza D, Sauer JA, Hu L, Albertson JD, Li Q.   +7 more
europepmc   +1 more source