Sentences with phrase «neuve sea ice model»

«It seems that it's not primarily the sea ice models that are responsible for the mismatch.

The data that Old Weather volunteer citizen scientists meticulously transcribe from the logbooks are used to drive climate and sea ice models to help understand changes and improve predictions.

Finnish Meteorological Institute has been doing estimates of two essential sea ice parameters — namely, sea ice concentration (SIC) and sea ice thickness (SIT)-- for the Bohai Sea using a combination of a thermodynamic sea ice model and Earth observation (EO) data from synthetic aperture radar (SAR) and microwave radiometer.

Fichefet, T., and M.A. Morales Maqueda, 1997: Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics.

I have observed greater variations in Arctic Inversions lately, the tendency is towards less steep inversions, this is expected when the Arctic lower atmosphere warms during winter, if the models maintain a stronger inversion while its observed weakening this may explain why sea ice models fail, strong boundary layers appear to be collapsing.

Winton, M. (2000), A reformulated three - layer sea ice model, Journal of Atmospheric and Oceanic Technology, 17 (4), 525 - 531.

Decadal hindcast simulations of Arctic Ocean sea ice thickness made by a modern dynamic - thermodynamic sea ice model and forced independently by both the ERA - 40 and NCEP / NCAR reanalysis data sets are compared for the first time.

It is argued that uncertainty, differences and errors in sea ice model forcing sets complicate the use of models to determine the exact causes of the recently reported decline in Arctic sea ice thickness, but help in the determination of robust features if the models are tuned appropriately against observations.

Using comprehensive data sets of observations made between 1979 and 2001 of sea ice thickness, draft, extent, and speeds, we find that it is possible to tune model parameters to give satisfactory agreement with observed data, thereby highlighting the skill of modern sea ice models, though the parameter values chosen differ according to the model forcing used.

Miller, P. A., S. W. Laxon, and D. L. Feltham (2007), Consistent and contrasting decadal Arctic sea ice thickness predictions from a highly optimized sea ice model, J. Geophys.

This tells you something about the sea ice model component of GCMs.

While finishing up her dissertation at the National Center for Atmospheric Research (NCAR), Parkinson and climate scientist William Kellogg decided to take the theory about carbon dioxide emissions increasing global temperatures and apply it to a sea ice model that Parkinson had built.

«A General Circulation Experiment with a Coupled Atmosphere, Ocean and Sea Ice Model.»

Since November 2014 the ensemble forecasts have been run with 0.25 degree horizontal resolution with the sea ice model active.

«The use of a coupled ocean — atmosphere — sea ice model to hindcast (i.e., historical forecast) recent climate variability is described and illustrated for the cases of the 1976/77 and 1998/99 climate shift events in the Pacific.

Rebecca Frew has written a great blog post on sea ice and how complex sea ice models need to be!

Tagged Amstrup, average global temperature, Bayesian models, BBC, climate change, Derocher, extinct, future climate, future population decline, global warming, polar bear, sea ice declines, sea ice models

In particular, the main task will be the development of an ensemble - based data assimilation system for the state - of - the - art sea ice model, neXtSIM, developed in - house at NERSC.

Part of my position is that I don't place much trust in current sea ice models.

There are a lot of ideas from meteorological forecast skill analysis + which have yet to be brought in to sea ice model skill analysis

Basically, they have put a prognostic model for melt ponds into the CICE model (the most sophisticated of the sea ice models used in climate models).

While sea ice thickness observations are sparse, here we utilize the ocean and sea ice model, PIOMAS (Zhang and Rothrock, 2003), to visualize mean sea ice thickness from 1979 to 2018.

Don't forget that the sea ice models these biologists use do not predict a decline in winter ice (Dec - March) and project only slight declines in spring ice (April - June) by mid-century (Amstrup et al. 2007; Durner et al. 2009; Oakley et al. 2012; Wang et al. 2012).

Both full sea ice models and seasonal melt projections applied to detailed sea ice distributions and trajectories provided the main semi-quantitative information for the Outlook.

The third regional modeling submission, Barthélemy et al., uses the ice - ocean Nucleus for European Modeling of the Ocean Louvain - la - Neuve Sea Ice Model (NEMO - LIM3) model and is initialized on 1 August 2014.

Barthélemy et al, 5.1 (4.5 - 5.6), Modeling Our estimate is based on results from ensemble runs with the global ocean - sea ice coupled model Nucleus for European Modeling of the Ocean Louvain - la - Neuve Sea Ice Model (NEMO - LIM3).

Both full sea ice models and seasonal melting projections applied to detailed sea ice distributions and trajectories provided the main semi-quantitative information for the Outlook.

Both sea ice models and seasonal melting projections provided the main semi-quantitative information for the Outlook.

Two groups (Kauker, et al., and Zhang) ran sea ice models with an ensemble (many years) of summer weather conditions from previous years.

Nine contributions stemmed from fully - coupled dynamical models, and five from ocean - sea ice models forced by atmospheric reanalyses or atmospheric model output.

In this project, we will assess the role of sea ice dynamics on the upper part of the Arctic Ocean energy budget and on primary production using for the first time a Lagrangian sea ice model, neXtSIM, coupled to an ocean - marine ecosystem model.

The neXtSIM model is currently being developed at the Nansen Environmental and Remote Sensing Center, and is unique among sea ice models owing to its rheological framework that is based on solid mechanics and allowing to reproduce the multifractal scaling invariance of sea ice deformation with an unprecedented realism.

It's now clear that Mitch Taylor was right to be skeptical of sea ice models based on pessimistic climate change assumptions; he was also right to be more optimistic than his PBSG colleagues about the ability of polar bears to adapt to changing sea ice conditions (Taylor and Dowsley 2008), since the bears have turned out to be more resilient than even he expected.

Our prediction is based on the GFDL - FLOR ensemble forecast system, which is a fully - coupled atmosphere - land - ocean - sea ice model initialized using a coupled data assimilation system.

RASM (Kamal et al.), 3.61 (± 0.5), Modeling (fully - coupled) We used the Regional Arctic System Model (RASM), which is a limited - area, fully coupled climate model consisting of the Weather Research and Forecasting (WRF) model, Los Alamos National Laboratory (LANL) Parallel Ocean Program (POP) and Sea Ice Model (CICE) and the Variable Infiltration Capacity (VIC) land hydrology model (Maslowski et al. 2012; Roberts et al. 2014; DuVivier et al. 2015; Hamman et al. 2016).

Data are available for collaborations with other observationalists and modelers for initialization and validation of sea ice models and remote sensing data to improve sea ice forecasts for the 2016 summerseason (e.g. Lindsay, 2012)

He is interested in developing next - generation sea ice models which capture anisotropic nature of ice dynamics / mechanics and explicitly simulate both ice thickness distribution and floe size distribution jointly.

«Difficulty in developing accurate sea ice models, variability in the Arctic's climate, and the uncertain rate of activity in the region create challenges for DOD to balance the risk of having inadequate capabilities or insufficient capacity when required to operate in the region with the cost of making premature or unnecessary investments,» reads a portion of the study, which was released Friday.

««Difficulty in developing accurate sea ice models,» No surprise since the «scientists» have yet to develop an accurate model for ANY aspect of the climate.»

«Difficulty in developing accurate sea ice models, variability in the Arctic's climate, and the uncertain rate of activity in the region...»

Scientific Disciplinary Expertise: Air - sea - ice interactions, oceanography, sea ice modeling.

One of the main changes in the HadGEM3 family of models compared with previous versions is the inclusion of the NEMO ocean modelling framework, which is also used in the Met Office's ocean forecasting system, and CICE, the Los Alamos sea ice model.

Could the temporal projection mistake of 30 years be explained by sea ice models creating more extent or volume since they perhaps erroneously start creating sea ice when surface air temperatures reach -2 C instead of -11 C?

This basically consisted of taking an ocean model and a sea ice model and bashing them together until they got along.

Note, each annual forcing dataset will need to be run repetitively for maybe up to a decade to get equilibrium for the ocean and sea ice models.

By the way, I have been arguing for an explicit melt pond parameterization in sea ice models, but a few years ago the NCAR climate modelers told me they didn't want to use my parameterization since it would make the sea ice melt too quickly (maybe they would have predicted the meltoff in 2007 with my parameterization!)

Hence they have focused their efforts on the ocean and sea ice models (and a new focus area is ice sheet modelling).

Typically, sea ice models are based on the historical records dating back to 1979, the beginning of the satellite era.

Not exact matches

Consistency and discrepancy in the atmospheric response to Arctic sea - ice loss across climate models.

This gives confidence in the predictions of the current generation of ice - sheet models which are used to forecast future ice loss from Antarctica and resulting sea - level rise.»