Sentences with phrase «circulation model data»

We applied the same method used in the observational analysis on general circulation model data to decrease the statistical uncertainty at the expense of an increased systematic uncertainty.

Not exact matches

The approach proposed in the paper combines information from observation - based data, general circulation models (GCMs) and regional climate models (RCMs).

Data collected by ship and model simulations suggest that increased Pacific Winter Water (PWW), driven by circulation patterns and retreating sea ice in the summer season, is primarily responsible for this OA expansion, according to Di Qi, the paper's lead author and a doctoral student of Liqi Chen, the lead PI in China.

By incorporating these data into an M.I.T. model, the result is «realistic descriptions of how ocean circulation evolves over time,» according to the press release.

The researchers plugged that trash census data into ocean models, which simulate the circulation of the world's waters.

Though promising, the model needs more data regarding air circulation patterns and vegetation types to support it, Sheil notes.

Using climate models and data collected about aerosols and meteorology over the past 30 years, the researchers found that air pollution over Asia — much of it coming from China — is impacting global air circulations.

Influence of physical forcing on planktonic ecosystems and elemental cycling; mesoscale ocean dynamics; primary production; coastal circulation; zooplankton population dynamics; harmful algal blooms; numerical modeling and data assimilation.

Marine planktonic ecosystem dynamics, biogeochemical cycling and ocean - atmosphere - land carbon system, ocean acidification, climate change and ocean circulation, satellite ocean color, air - sea gas exchange, numerical modeling, data analysis, and data assimilation

Coastal circulation dynamics, numerical modeling and data assimilation, biophysical interaction, air - sea interaction, coastal ocean observing system

The visualization covers the period June 2005 to December 2007 and is based on a synthesis of a numerical model with observational data, created by a NASA project called Estimating the Circulation and Climate of the Ocean, or ECCO for short.

In New York, there was last year's New Museum Triennial, «Surround Audience,» whose participants addressed «a society replete with impressions of life, be they visual, written, or constructed through data,» and «Ocean of Images,» the 2015 iteration of MoMA's «New Photography» showcase, featuring artists who use «contemporary photo - based culture, specifically focusing on connectivity, the circulation of images, information networks, and communication models.»

Another point is the fact that general circulation models have our understanding of relevant processes encoded into lines of computer code, whereas empirical - statistical models capture all relevant processes simply by the fact that these are emedded in the data itself.

Given that the answer to this for atmospheric models is a resounding «NO» (particularly because of sub-grid scale processes which need to be effectively pre-ordained through parameterizations), and given that oceanic circulations have much longer adjustment time scales, yet also have much more intense small scale (gyre) circulations than the atmosphere, my instinct is that we are not even close to being able to trust ocean models without long term validation data.

Here we analyze a series of climate model experiments along with observational data to show that the recent warming trend in Atlantic sea surface temperature and the corresponding trans - basin displacements of the main atmospheric pressure centers were key drivers of the observed Walker circulation intensification, eastern Pacific cooling, North American rainfall trends and western Pacific sea - level rise.

As noted in that post, RealClimate defines the Atlantic Multidecadal Oscillation («AMO») as, «A multidecadal (50 - 80 year timescale) pattern of North Atlantic ocean - atmosphere variability whose existence has been argued for based on statistical analyses of observational and proxy climate data, and coupled Atmosphere - Ocean General Circulation Model («AOGCM») simulations.

General Circulation Models (GCMs) are the best source of data available to researchers for developing regional scenarios.

To answer such questions, we analyze observational data and perform systematic studies with numerical models, with which we simulate flows ranging from the meter - scale motions in clouds to global circulations.

Strong evidence from ocean sediment data and from modelling links abrupt climate changes during the last glacial period and glacial - interglacial transition to changes in the Atlantic Ocean circulation.

Our research activity is thus part of a national and international effort to provide the scientific community with new data sets usefull for ocean circulation modeling, climate studies, bio-optics and bio-chemistry of the ocean.

Unfortunately, conductive heat flow versus age data do not confirm the cooling models because much of the heat is advected by hydrothermal circulation near the ridge axes (Hofmeister and Criss, 2005; Pollack et al., 1993).

A shift in atmospheric circulation in response to changes in solar activity is broadly consistent with atmospheric circulation patterns in long - term climate model simulations, and in reanalysis data that assimilate observations from recent solar minima into a climate model.

CAS = Commission for Atmospheric Sciences CMDP = Climate Metrics and Diagnostic Panel CMIP = Coupled Model Intercomparison Project DAOS = Working Group on Data Assimilation and Observing Systems GASS = Global Atmospheric System Studies panel GEWEX = Global Energy and Water Cycle Experiment GLASS = Global Land - Atmosphere System Studies panel GOV = Global Ocean Data Assimilation Experiment (GODAE) Ocean View JWGFVR = Joint Working Group on Forecast Verification Research MJO - TF = Madden - Julian Oscillation Task Force PDEF = Working Group on Predictability, Dynamics and Ensemble Forecasting PPP = Polar Prediction Project QPF = Quantitative precipitation forecast S2S = Subseasonal to Seasonal Prediction Project SPARC = Stratospheric Processes and their Role in Climate TC = Tropical cyclone WCRP = World Climate Research Programme WCRP Grand Science Challenges • Climate Extremes • Clouds, Circulation and Climate Sensitivity • Melting Ice and Global Consequences • Regional Sea - Ice Change and Coastal Impacts • Water Availability WCRP JSC = Joint Scientific Committee WGCM = Working Group on Coupled Modelling WGSIP = Working Group on Subseasonal to Interdecadal Prediction WWRP = World Weather Research Programme YOPP = Year of Polar Prediction

Tom Wigley supervised his PhD titled, «Regional Validation of General Circulation Models» that used three top computer models to recreate North Atlantic conditions where data wasModels» that used three top computer models to recreate North Atlantic conditions where data wasmodels to recreate North Atlantic conditions where data was best.

However, it remains a major scientific challenge to model and project the changes of the magnitude and intensity of subsurface oxygen depletion because it depends on changes in ocean circulation, rates of de-nitrification, and nutrient runoff from land, and because global data coverage for chemical and biological parameters remains poor.

However, there are no compelling data to suggest a confluence of climate - change impacts that would affect global production in either direction, particularly because relevant fish population processes take place at regional or smaller scales for which general circulation models (GCMs) are insufficiently reliable.

A global archive of land cover and soils data for use in general circulation climate models.

Atmosphere - Ocean General Circulation Models also tend to simulate less intense ENSO events, in qualitative agreement with data, although there are large differences in magnitude and proposed mechanisms, and inconsistent responses of the associated teleconnections (Otto - Bliesner, 1999; Liu et al., 2000; Kitoh and Murakami, 2002; Otto - Bliesner et al., 2003).

There is growing observational data, physical analysis of possible mechanisms, and model agreement that human - caused climate change is strengthening atmospheric circulation patterns in a way «which implies that the periodic and inevitable droughts California will experience will exhibit more severity...» «there is a traceable anthropogenic warming footprint in the enormous intensity of the anomalous ridge during winter 2013 — 2014 and the associated drought.»

His current research includes global ocean modeling and data assimilation efforts as part of Estimating the Circulation & Climate of the Ocean (ECCO) consortium, as well as using ensemble methods for regional ocean analysis and prediction.

Abstract We study trends and temporal correlations in the monthly mean temperature data of Prague and Melbourne derived from four state - of - the - art general circulation models that are currently used in studies of anthropogenic effects on the atmosphere: GFDL - R15 - a, CSIRO - Mk2, ECHAM4 / OPYC3 and HADCM3.

Scientists from Norway's Nansen Environmental and Remote Sensing Center, attempting to better understand how this process works, plugged their data into an ocean circulation / climate change model to examine the system out until 2080.

Modeling long - term climate change for the entire planet, however, was held back by lack of computer power, ignorance of key processes such as cloud formation, inability to calculate the crucial ocean circulation, and insufficient data on the world's actual climate.

These data are also assimilated into many ocean circulation models.

10) Part of the CMIP5 era of GCMs, the recently released Community Climate System Model version 4 (CCSM4) shows major circulation biases as compared with ECMWF 40 - year reanalysis data.