Sentences with phrase «observational errors on»

Observational errors on any one annual mean temperature anomaly estimate are around 0.1 deg C, and the errors from the linear fits are given in the text.

If I were to superimpose such a wide band of observational error on the Fig 3 of the blog post then — to paraphrase John von Neumann — I could fit an elephant and wiggle its trunk.

Not exact matches

The form of the Jeffreys» prior depends on both the relationship of the observed variable (s) to the parameter (s) and the nature of the observational errors and other uncertainties, which determine the form of the likelihood function.

However, satellite observations are notably cooler in the lower troposphere than predicted by climate models, and the research team in their paper acknowledge this, remarking: «One area of concern is that on average... simulations underestimate the observed lower stratospheric cooling and overestimate tropospheric warming... These differences must be due to some combination of errors in model forcings, model response errors, residual observational inhomogeneities, and an unusual manifestation of natural internal variability in the observations.»

If interested, see the Review of Article # 1 — the introduction to the special issue here; see the Review of Article # 2 — on VAMs» measurement errors, issues with retroactive revisions, and (more) problems with using standardized tests in VAMs here; see the Review of Article # 3 — on VAMs» potentials here; and see the Review of Article # 4 — on observational systems» potentials here.

If interested, see the Review of Article # 1 — the introduction to the special issue here; see the Review of Article # 2 — on VAMs» measurement errors, issues with retroactive revisions, and (more) problems with using standardized tests in VAMs here; see the Review of Article # 3 — on VAMs» potentials here; see the Review of Article # 4 — on observational systems» potentials here; see the Review of Article # 5 — on teachers» perceptions of observations and student growth here; see the Review of Article (Essay) # 6 — on VAMs as tools for «egg - crate» schools here; see the Review of Article (Commentary) # 7 — on VAMs situated in their appropriate ecologies here; and see the Review of Article # 8, Part I — on a more research - based assessment of VAMs» potentials here and Part II on «a modest solution» provided to us by Linda Darling - Hammond here.

If interested, see the Review of Article # 1 — the introduction to the special issue here; see the Review of Article # 2 — on VAMs» measurement errors, issues with retroactive revisions, and (more) problems with using standardized tests in VAMs here; see the Review of Article # 3 — on VAMs» potentials here; see the Review of Article # 4 — on observational systems» potentials here; see the Review of Article # 5 — on teachers» perceptions of observations and student growth here; see the Review of Article (Essay) # 6 — on VAMs as tools for «egg - crate» schools here; and see the Review of Article (Commentary) # 7 — on VAMs situated in their appropriate ecologies here; and see the Review of Article # 8, Part I — on a more research - based assessment of VAMs» potentials here.

It was based on observational analysis which was found to contain errors.

Whether you are gullible enough to accept the figures as accurate depends on how much credibility you put in the multitude of observational measurements taken by different methods over many decades by diverse groups of researchers that form a strong consilience of mutually supporting evidence for the validity of the estimates and the possible errors.

However, Hegerl et al. (2001) show that inclusion of observational sampling uncertainty has relatively little effect on detection results and that random instrumental error has even less effect.

As an extension, systematic observational errors could perhaps be corrected as part of the regression by estimating a constant shift to apply to each thermometer (treating changes in technology as creating a new thermometer on the same site), though this may make the problem too large.

Assessments of our relative confidence in climate projections from different models should ideally be based on a comprehensive set of observational tests that would allow us to quantify model errors in simulating a wide variety of climate statistics, including simulations of the mean climate and variability and of particular climate processes.

There is SOME observational data suggesting the global average temperature has increased on the order of 1 deg C over the last 150 years, but the exact figure is highly uncertain due to instrumental error and the adjustment games CRU, GISS and the rest have been playing.