Results 171 to 180 of about 30,389 (290)

Classification of the Atmospheric Boundary Layer Based on Turbulent Kinetic Energy Budget Terms Using Machine‐Learning Methods

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract The atmospheric boundary layer (ABL) controls surface‐atmosphere exchanges, yet accurately capturing its full complexity, particularly the dynamically evolving nature of turbulence across diverse weather conditions, remains a formidable challenge for traditional classification methods.
Jinhong Xian, Xiaoling Lin, Zongxu Qiu, Jianping Guo, Hongyan Luo, Chao Lu, Huayan Rao, Yuexin Yang, Ming Luo, Yan Yang, Chunsheng Zhang, Zhiliang Hu, Jun Zhang, Aiming Liu, Honglong Yang   +14 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

Impact of Mantle Velocity Uncertainty on Receiver‐Function Imaging of the Transition Zone

Geophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Seismological estimates of the 400‐km and 670‐km mantle discontinuities (d400 and d670) are crucial for understanding the thermochemical structure and dynamics of the mantle transition zone (MTZ). However, artifacts from using ray theory and uncertainties in mantle velocity structure can affect topographic mapping of these boundaries.
Carlos A. M. Chaves, Felipe P. Corral, Jeroen Ritsema   +2 more
wiley   +1 more source

Large-scale acceleration algorithms for a deep convective physical parameterization scheme on GPU. [PDF]

PLoS One
Wang Y, Wang J, Tian J, Li L, Ma F, Peng F, Ke H.   +6 more
europepmc   +1 more source

Observing Systems Simulation Experiments of Hypothetical Hourly Global Coverage of Microwave Satellite Radiances: Imbalance and Adaptive Observation Error Inflation

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 8, 28 April 2026.
Abstract This study investigates the potential impacts of frequent global coverage of satellite microwave radiances using a global atmospheric data assimilation (DA) system. Observing Systems Simulation Experiments (OSSEs) were performed using the Local Ensemble Transform Kalman Filter with the Nonhydrostatic Icosahedral Atmospheric Model (NICAM ...
Rakesh Teja Konduru, Jianyu Liang, Shigenori Otsuka, Takemasa Miyoshi   +3 more
wiley   +1 more source

Machine learning investigation of marangoni convection in hybrid nanofluids with Darcy-Forchheimer. [PDF]

Sci Rep
Qureshi H, Altmeyer S, Zubair M.
europepmc   +1 more source

Revisiting Intrinsic Predictability of Wave‐Convection Coupled Bands Over Southern China: Variable and Scale‐Dependent Error Growth Characteristics

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 8, 28 April 2026.
Abstract This study investigates the variable‐ and scale‐dependent intrinsic predictability of wave‐convection coupled bands over southern China on 30 January 2018, using 1‐km simulations under varying initial moisture conditions. The predictability time is quantified via the Loss Predictability Index (LPI), defined as the ratio of the forecast error ...
Manshi Weng, Junhong Wei, Yu Du, Y. Qiang Sun, Xubin Zhang   +4 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

Contrail Formation Within Cirrus: Contrail Induced Perturbations and Cirrus Adjustments

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 8, 28 April 2026.
Abstract Contrail formation constitutes a large fraction of the aviation climate impact. But only part of the effect has been studied in detail, as research focused on contrail formation in cloud‐free air. Even though it is known that the impact of contrail formation within cirrus can be detected in space‐born remote sensing data, little research has ...
Pooja Verma, Ulrike Burkhardt
wiley   +1 more source

Trends in vertical wind velocity variability reveal cloud microphysical feedback. [PDF]

Nat Commun
Barahona D, Breen KH, Ngo D, Maciel FV, Patnaude R, Diao M.   +5 more
europepmc   +1 more source