Sentences with phrase «ocean model error»

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Not exact matches

Based on model experiments, it has been suggested that errors resulting from the highly inhomogeneous distribution of ocean observations in space and time (see Appendix 5.

As stated in the paper, that could reflect an error in the land temperature reconstruction (too cold), an error in the ocean reconstruction (not cold enough) or an error in the models land / ocean ratio.

The sampling error can be large as results from realistic ocean model consistently show.

Missing pieces and small errors can pose difficulties when models of sub-systems such as the ocean and the atmosphere are coupled.

[Response: At the dawn of coupled modelling, errors that arose in separate developments of ocean and atmospheric models lead to significant inconsistencies between the fluxes that each component needed from the other, and the ones they were getting.

While impressive, this may be due to an error in the forcings combined with compensating errors in the climate sensitivity (2.7 C for a doubling of CO2 in this model) or the mixing of heat into the deep ocean.

The claim to get around the two problems of an geometric increase in error, and using absolute values of temperature that are not Earth's, is the argument that the model ensemble got the heat transfer correctly in atmosphere and in the ocean.

What politician is going to claim a Nature journal article is full of errors, or that the Russell ocean model has serious problems which lead to nutty GCM behavior?

So errors that would be almost undetectable if either the atmosphere or ocean were modelled independently can become quite serious when the two are coupled together.

These scaling factors compensate for under - or overestimates of the amplitude of the model response to forcing that may result from factors such as errors in the model's climate sensitivity, ocean heat uptake efficiency or errors in the imposed external forcing.

When ocean models were first coupled to atmospheric models well over a quarter century ago, systematic errors in each component near their interface led to sizeable drift and unrealistic climate simulations.

The US CLIVAR Eastern Tropical Oceans Synthesis (ETOS) Working Group was formed to promote collaboration in the southeast oceanic basins, coordinate a model assessment of surface flux errors for the equatorial Atlantic, identify recent model improvements and common and persistent model errors, and provide recommendations of cases for community simulation and evaluation using eddy - permitting ocean models.

We need to be careful focussing upon «trends» — it can lead to serious errors of context — and this underlies the entire «global warming» thesis which relies upon computer models with entirely false (i.e. non-natural) notions of an equilibrium starting point and calculations of trend — this conveniently ignores cycles, and it has to because a) there are several non-orbital cycles in motion (8 - 10 yr, 11, 22, 60, 70, 80, 400 and 1000 - 1500) depending on ocean basic, hemisphere and global view — all interacting via «teleconnection» of those ocean basins, some clearly timed by solar cycles, some peaking together; b) because the cycles are not exact, you can not tell in any one decade where you are in the longer cycles.

To estimate the uncertainty range (2σ) for mean tropical SST cooling, we consider the error contributions from (a) large - scale patterns in the ocean data temperature field, which hamper a direct comparison with a coarse - resolution model, and (b) the statistical error for each reconstructed paleo - temperature value.

Over the next 3 years the Ocean Colour Climate Change Initiative project aims to: Develop and validate algorithms to meet the Ocean Colour GCOS ECV requirements for consistent, stable, error - characterized global satellite data products from multi-sensor data archives; Produce and validate, within an R&D context, the most complete and consistent possible time series of multi-sensor global satellite data products for climate research and modelling; Optimize the impact of MERIS data on climate data records; Generate complete specifications for an operational production system; Strengthen inter-disciplinary cooperation between international Earth observation, climate research and modelling communities, in pursuit of scientific excellence.

It occurs to me to wonder whether this error in the GISS - E2 - R ocean mixing parameterisation, which gave rise to AMOC instability in the Pliocene simulation, might possibly account for the model's behaviour in LU run 1.

Applications such as the forcing of ice — ocean models are sensitive to the errors in reanalyses.

Moreover, models that strive to incorporate everything, from aerosols to vegetation and volcanoes to ocean currents, may look convincing, but the error range associated with each additional factor results in near - total uncertainty.

The figure above compares the average track forecast errors in the Atlantic Ocean basin during the past six hurricane seasons for the most reliable computer models available to the National Hurricane Center during this period.

TOAA is also relevant to reducing the large errors associated with numerical calculation in climate models of the transfer of heat and moisture between ocean and atmosphere.

A recent study by C10 analysed a number of different climate variables in a set of SMEs of HadCM3 (Gordon et al. 2000, atmosphere — ocean coupled version of HadSM3) from the point of view of global - scale model errors and climate change forcings and feedbacks, and compared them with variables derived from the CMIP3 MME. Knutti et al. (2006) examined another SME based on the HadSM3 model, and found a strong relationship between the magnitude of the seasonal cycle and climate sensitivity, which was not reproduced in the CMIP3 ensemble.

Xie (June 2008): The Tropical Eastern Pacific Seasonal Cycle: Assessment of Errors and Mechanisms in IPCC AR4 Coupled Ocean — Atmosphere General Circulation Models.

I have just discovered (from Chandler et al 2013) that there was an error in the ocean model in the version of GISS - E2 - R used to run the CMIP5 simulations.

Looking at the last decade, it is clear that the observed rate of change of upper ocean heat content is a little slower than previously (and below linear extrapolations of the pre-2003 model output), and it remains unclear to what extent that is related to a reduction in net radiative forcing growth (due to the solar cycle, or perhaps larger than expected aerosol forcing growth), or internal variability, model errors, or data processing — arguments have been made for all four, singly and together.

My error was in assuming that the model output (which were in units W yr / m2) were scaled for the ocean area only, when in fact they were scaled for the entire global surface area (see fig. 2 in Hansen et al, 2005).

Although the science of regional climate projections has progressed significantly since last IPCC report, slight displacement in circulation characteristics, systematic errors in energy / moisture transport, coarse representation of ocean currents / processes, crude parameterisation of sub-grid - and land surface processes, and overly simplified topography used in present - day climate models, make accurate and detailed analysis difficult.

In an article from November 5, 2008, Josh Willis states that the world ocean actually has been warming since 2003 after removing Argo measurement errors from the data and adjusting the measured temperatures with a computer model his team developed.