The Norwegian Sea : its physical oceanography based upon the Norwegian researches 1900-1904
B. Helland-Hansen, F. Nansen
semanticscholar +1 more source
Weather features drive free‐tropospheric baroclinicity variability in the North Atlantic storm track
We show that synoptic weather features, such as extratropical cyclones, fronts, and atmospheric rivers, contribute to more than half of the total variability of free‐tropospheric baroclinicity in the North Atlantic storm track, despite their limited spatial and temporal extent.
Andrea Marcheggiani +3 more
wiley +1 more source
Towards a 'theory of change' for ocean plastics: a socio-oceanography approach to the global challenge of plastic pollution. [PDF]
Horton AA +9 more
europepmc +1 more source
Physical oceanography at CTD station JUNE-1998-IR63
Dimitrios Georgopoulos +1 more
openalex +1 more source
The physical oceanography of Jones Bank: A mixing hotspot in the Celtic Sea
M. Palmer +3 more
semanticscholar +1 more source
Spatial and temporal patterns of SST uncertainty
This figure summarises the change in the Operational Sea Surface Temperature and Sea Ice Analysis near‐real‐time sea‐surface temperature product uncertainty spatial pattern in the UK domain as cluster maps broken into three time periods: (a) June 2007–February 2014; (b) March 2014–February 2018; (c) March 2018–December 2022.
Alison Cobb, Paul Green
wiley +1 more source
Evaluation of microbiological criteria, planktonic communities and trophic state of groundwater resources in Siwa Oasis, Western Desert, Egypt. [PDF]
Abdelkarim MS +5 more
europepmc +1 more source
Underway physical oceanography and carbon dioxide measurements during Santa Maria cruise SM059C
Ute Schuster
openalex +1 more source
Evaluating machine‐learning models for wind‐speed downscaling from ECMWF‐IFS data
We benchmark recent machine‐learning methods for downscaling wind speeds from a low‐resolution 9‐km model input to 1‐km predictions. We include recent super‐resolution approaches and transformer‐based architectures and propose Windflow‐SRnet. The models are trained with input data from the ECMWF‐IFS numerical weather model to predict label data from ...
William Ericson +5 more
wiley +1 more source
Variability in the volume transport of deep overflow across the 10°S saddle on the ninetyeast ridge. [PDF]
Zhang S, Qiu F, Chen H, Jing C.
europepmc +1 more source

