Results 141 to 150 of about 4,101,946 (282)
Numerical weather prediction output necessitates calibration, as weather model systems are unable to replicate the correct statistics of observations. Such processing is especially important when predicting extreme weather. Calibration methods function by learning from prediction inadequacies during a training phase and by exploiting this information ...
Dmitrij Japs +3 more
wiley +1 more source
A synoptic overview of the EUREC4A field campaign
The figure shows a summary of the important synoptic features and associated cloud patterns during the EUREC4A field campaign, divided into four subjectively defined periods. In period 1 the fish cloud pattern was dominant, associated with a shear line, and there was an initial transport of dust from West Africa that reached Barbados in the third ...
Leo Saffin +27 more
wiley +1 more source
Climate-stratified assessment of PM2.5 using machine learning: Geographic controls dominate meteorological factors. [PDF]
Utsho SK, Fahim MR, Samsudin R.
europepmc +1 more source
Regional deep learning weather prediction (DLWP) models, such as Bris, offer high resolution forecasts comparable with traditional numerical weather prediction (NWP) models. We evaluated Bris against the operational MetCoOp Ensemble Prediction System (MEPS) during extratropical cyclone Poly (July 5, 2023).
Francesco Pasquini +4 more
wiley +1 more source
Multi-source temporal fusion and multi-station learning for early warning of diamondback moth infestation in <i>Brassica</i> crops. [PDF]
Zhang D, Wang J.
europepmc +1 more source
This study proposes a phase‐aware bias correction framework for all‐sky infrared radiance assimilation. Cloud top temperature differences between observations and model background fields are used to identify cloud‐phase mismatch and cold‐cloud regimes.
Jiwon Hwang +5 more
wiley +1 more source
Influenza-Like Illness Forecasting Using Multisource Data: Comparative Deep Learning Study. [PDF]
Dang C +9 more
europepmc +1 more source
Also issued with: On the climate of the Yass-Canberra district. Melbourne : Bureau of Meteorology, 1910. (Bulletin (Commonwealth Bureau of Meteorology (Australia) ; no.
Commonwealth Bureau of Meteorology (Australia)
core
Precipitation growth and decay due to orography was analyzed using the radar network in Great Britain. Storm direction and speed modulate the intensity of precipitation growth or decay. Windward slopes predominantly exhibit precipitation growth, while leeward areas show precipitation decay.
Chen Li, Miguel Angel Rico‐Ramirez
wiley +1 more source
Trends in rainfall and temperature extremes during 1954-2019 in Addis Ababa, Ethiopia
ELIAS FISEHA MEKONNEN +2 more
doaj +1 more source

