Results 161 to 170 of about 43,243 (288)

Tornado recovery for teens: Making things better

, 2013

openalex   +1 more source

What matters the most? Understanding individual tornado preparedness using machine learning

, 2020
Junghwa Choi, Scott E. Robinson, Romit Maulik, Wesley Wehde   +3 more
openalex   +2 more sources

Experimental observation and manipulation of optical tornado waves [PDF]

, 2022
Lai Chen, Li‐Gang Wang
openalex   +1 more source

Integration of a WASH Component in the Standard National Protocol for Treatment of Severe Acute Malnutrition in Children Aged 6–59 Months in Northern Senegal—A Costing Study

Maternal &Child Nutrition, Volume 22, Issue 1, March 2026.
This study provides the first cost analysis of integrating a WASH kit into outpatient SAM treatment in Senegal, highlighting key cost drivers and potential efficiencies for scale‐up. Findings offer practical insights for planning and budgeting integrated WASH‐nutrition interventions in similar settings.
Bibata Wassonguema, Maily Lê‐Lacanette, Laura Braun, Matar Ba, Françoise Siroma, Albert Emile Cabo, Antonio Vargas Brizuela, Moustapha Seye, Jean Lapègue, Alexandre Devort, Oliver Cumming, Dieynaba S. N'Diaye   +11 more
wiley   +1 more source

Investigation Plan, NIST, Technical Investigation of the Joplin, Missouri, Tornado of May 22, 2011 National Institute of Standards and Technology (NIST), Technical Investigation of the Joplin, Missouri, Tornado of May 22, 2011

, 2012
Marc L. Levitan, Long Phan, Erica D. Kuligowski, Franklin T. Lombardo   +3 more
openalex   +1 more source

Tornado-scale vortices in the tropical cyclone boundary layer: numerical simulation with the WRF–LES framework [PDF]

, 2019
Liguang Wu, Qingyuan Liu, Yubin Li
openalex   +1 more source

Deep Learning Atmospheric Models Reliably Simulate Out‐of‐Sample Land Heat and Cold Wave Frequencies

Geophysical Research Letters, Volume 53, Issue 3, 16 February 2026.
Abstract Deep learning (DL)–based general circulation models (GCMs) are emerging as fast simulators, yet their ability to replicate extreme events outside their training range remains unknown. Here, we evaluate two such models—the hybrid Neural General Circulation Model (NGCM) and purely data‐driven Deep Learning Earth System Model (DLESyM)—against a ...
Zilu Meng, Gregory J. Hakim, Wenchang Yang, Gabriel A. Vecchi   +3 more
wiley   +1 more source

Forecasting Natural Disasters of Tornados Using mHGN

, 2017
Benny Benyamin Nasution, Rahmat Widia Sembiring, Bakti Viyata Sundawa, G Gunawan, Afritha Amelia, Ismael, Handri Sunjaya, Suhaili Alifuddin, Morlan Pardede, Junaidi Junaidi, M. Syahruddin, Zulkifli Lubis   +11 more
openalex   +2 more sources

Monte Carlo modeling of tornado hazard to wind turbines in Germany. [PDF]

Nat Hazards (Dordr), 2023
Bouchard R, Romanic D.
europepmc   +1 more source

Amplifying Variability of the Southern Annular Mode in the Past and Future

Geophysical Research Letters, Volume 53, Issue 3, 16 February 2026.
Abstract The Southern Annular Mode (SAM) is the dominant mode of atmospheric variability in the Southern Hemisphere extratropics. While its long‐term positive trend is well‐documented, changes in the amplitude of SAM variability remain poorly understood. Based on reanalysis data and surface‐station observations, we demonstrate that the amplitude of SAM
Ding Ma, Yuandong Zhang, Ji Nie
wiley   +1 more source