The monthly reports contain a variety of perspectives from
advanced numerical models to qualitative perspectives from citizen scientists.
The Sea Ice Outlook, an activity of the Sea Ice Prediction Network and a contribution to SEARCH, produces reports in June, July, and August containing a variety of perspectives on Arctic sea ice — from observations of current conditions, to
advanced numerical models, to qualitative perspectives from citizen scientists.
The SIO produces reports in June, July, and August containing a variety of perspectives on Arctic sea ice — from observations of current conditions, to
advanced numerical models, to qualitative perspectives from citizen scientists.
Potential topics include: (1)
Advanced numerical modelling of magnetic flux tubes / loops in the low solar atmosphere (2) Forward modelling of spectroscopic and narrowband EUV observations of the low solar atmosphere, (3) Solar Rotational Tomography of EUV and / or coronagraph coronal observations, (4) Automated detection and prediction of coronal mass ejections, (5) Analysis of solar wind turbulence observations by in situ spacecraft, (6) Eclipse instrumentation, observations and data analysis.
Not exact matches
«It's impressive, considering that current state - of - the - art
numerical weather
models, such as NOA's Global Forecast System, or the European Centre for Medium - Range Weather Forecasts» operational
model, are only skillful up to one to two weeks in
advance,» says paper co-author Cory Baggett, a postdoctoral researcher in the Barnes and Maloney labs.
The successful applicant will work with world leading experts in
advanced analytical /
numerical modelling, analysis of high - resolution observations obtained by cutting - edge ground and space based instruments.
The research team for this study used these data in sophisticated
numerical models to examine cloud microphysical processes that are important for cloud maintenance but can not be directly observed, even with the most
advanced instrumentation.
«The climate
model is run, using standard
numerical modeling techniques, by calculating the changes indicated by the
model's equations over a short increment of time — 20 minutes in the most
advanced GCMs — for one cell, then using the output of that cell as inputs for its neighboring cells.
Cohen received his Ph.D. in Atmospheric Sciences from Columbia University in 1994 and has since focused on conducting
numerical experiments with global climate
models and
advanced statistical techniques to better understand climate variability and to improve climate prediction.
Traditionally
numerical weather prediction has
advanced progressively by improving single, «deterministic» forecasts with an increasing
model accuracy and decreasing initial condition errors.
Specific research topics include carbon dioxide, methane and water fluxes and their reservoirs in vegetation and soil, transport in atmosphere, and
model - data fusion using
advanced numerical methods.The research is based on
numerical modelling, from local to global scale with focus on northern regions.
Anyway,
numerical methods have
advanced tremendously since then and I have a sense that climate
models have not kept up.
Much of this progress is due to
advances in
numerical weather prediction, that is, the use of computer
models which approximate the fluid motions of the atmosphere to create forecasts of the weather at some time in the future.