Sentences with phrase «of observation bias»

This US increase is due to the time of observation bias and the transition to the MMTS.

jim2, now that we have accurate hourly / daily records, we can predict what the time of observation bias (TOB) would be, if we were still recording temps the same way today as 50 years ago.

Karl, T.R., C.N. Williams, Jr., P.J. Young, and W.M. Wendland, 1986: A model to estimate the time of observation bias associated with monthly mean maximum, minimum, and mean temperature for the United States, Journal of Climate and Applied Meteorology, 25, 145 - 160.

Am I correct, that in this case «raw» excludes corrections for time of observation bias, which the NOAA data includes?

Vose, R.S., C.N. Williams Jr., T.C. Peterson, T.R. Karl, and D.R. Easterling, 2003: An evaluation of the time of observation bias adjustment in the U.S. Historical Climatology Network, Geophysical Research Letters, 30, 2046, doi: 10.1029 / 2003GL018111.

-LSB-...] to correct for the time of observation bias (TOB).

Do the raw data figures in the paper include time of observation bias adjustment and / or any other similar «instrument» - like adjustments?

«There is practically no time of observation bias in urban - based stations which have taken their measurements punctually always at the same time, while in the rural stations the times of observation have changed.

Therefore one must correct for the time of observation bias before one tries to determine the effect of the urban heat island»

I've seen a credible explanation for why, beginning in 1950, time of observation bias (TOBS) and station homogeneity (SHAP) became so skewed.

It is a bit interesting to me that many are willing to let site issues slide, but the time of observation bias not slide.

Specifically, Watts did not apply a time of observation bias correction according to Howard Universitychemistry professor Josh Halpern, who blogs under the pseudonym Eli Rabett.

Not exact matches

Finally, some of the observations above re the deflationary bias suggest that interest rates may well be too low when we hit the next recession to give the Fed much of a perch to climb down from.

Can you learn anything worthwhile with your heart set against a just and non biased observation of a particular subject of supposed interest?

is that the impression the Jays have a long term trend of under performing bad teams is simply observation bias rather than actually having merit.

I'm so tired of people making these damning comments that aren't even based on observation; it's almost funny how biased some people are AGAINST their own players.

I get quite a lot of stick for being critical of referees in Arsenal games, and I'll be the first to admit that my observations are built on bias, so of course there is a good chance that people may disagree with my viewpoints, particularly when their biases lay elsewhere.

Of course, the same applies to messaging via Facebook or MySpace, but here's where my personal bias connects with Cerf's observation: I'll submit that the thing that made Facebook messsaging useful (to me, at least) was when the «you have a message» notification emails began including the actual text someone was sending to you.

«Whilst the possibility of this is extremely low, possibly even zero, as scientists it's important that we avoid complacency and examine observations and evidence without bias.»

However, scientists from the Canadian - French - Hawaiian project OSSOS detected biases in their own observations of the orbits of the TNOs, which had been systematically directed towards the same regions of the sky, and considered that other groups, including the Caltech group, may be experiencing the same issues.

Biologists have to undertake large studies that can guarantee the statistical significance of observations, and they need self - critical analysis to avoid inadvertent biases.

Based on these observations, the researchers developed a mathematical model to identify how this biased partitioning of the drug pump affects the bacterial population.

That made it less likely that the clumping might be due to an observation bias such as pointing a telescope at a particular part of the sky.

If Turner's team is correct, then all the observations that yield higher values of the Hubble constant must be biased by what he calls «a common systematic error».

FMI has been involved in research project, which evaluated the simulations of long - range transport of BB aerosol by the Goddard Earth Observing System (GEOS - 5) and four other global aerosol models over the complete South African - Atlantic region using Cloud - Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to find any distinguishing or common model biases.

Since the temperature changes since 1979 are on the order of 0.6 C or so, it is relatively easy for bias, due to changing observation times, to swamp the underlying climate signal.

Some of the discontinuities (which can be of either sign) in weather records can be detected using jump point analyses (for instance in the new version of the NOAA product), others can be adjusted using known information (such as biases introduced because changes in the time of observations or moving a station).

Supporting this is our observation that approximately one third of both OR and VR genes with interrupted ORFs are not expressed in olfactory tissues, a bias that had been noted previously [41].

We demonstrated that a regression - based statistical correction for the proportion of the students in each teacher's class that are English - language learners, have education disabilities, are from low - income families, and so forth, wrings most of the bias out of classroom observations.

The bias in classroom observation systems that derives from some teachers being assigned much more able students than other teachers is very important to the overall performance of the teacher evaluation system.

But in the districts we examined, only teachers at the very tail end of the distribution are dismissed because of their evaluation scores, and it turns out that teachers who get the very worst evaluation scores remain at the tail end of the distribution regardless of whether their classroom observation ratings are biased.

In our report, we introduced a method for adjusting for the bias in classroom observation scores by taking into account the demographic make - up of teachers» classrooms.

The advantages come at the price of concerns about the limited number of country observations, the mostly cross-sectional character of available achievement data, and possible bias from unobserved country factors such as culture.

Measures that allow for more subjectivity and local control, such as classroom observations and SLOs, are subject to their own types of bias.

An untrained observer may introduce bias into observations; the observer's expectations of a teacher may influence the observation to a greater degree than the actual teacher behaviors displayed (Mujis, 2006).

Following - up on two prior posts about potential bias in teachers» observations (see prior posts here and here), another research study was recently released evidencing, again, that the evaluation ratings derived via observations of teachers in practice are indeed related to (and potentially biased by) teachers» demographic characteristics.

This is much different than just jumping in right away on our first observation of a price action signal or market bias.

This is not a criticism of the strategy, which is tractable and implementable, but an observation on how pernicious our cognitive biases are.

In this case, there has been an identification of a host of small issues (and, in truth, there are always small issues in any complex field) that have involved the fidelity of the observations (the spatial coverage, the corrections for known biases), the fidelity of the models (issues with the forcings, examinations of the variability in ocean vertical transports etc.), and the coherence of the model - data comparisons.

And of course the new paper by Hausfather et al, that made quite a bit of news recently, documents how meticulously scientists work to eliminate bias in sea surface temperature data, in this case arising from a changing proportion of ship versus buoy observations.

It's not about someone saying there is urban heat bias, it's about the method of modeling used to model the observations which reduces the error extent.

Some of the discontinuities (which can be of either sign) in weather records can be detected using jump point analyses (for instance in the new version of the NOAA product), others can be adjusted using known information (such as biases introduced because changes in the time of observations or moving a station).

Indeed, globally averaged systematic observation biases, sampling array issues and steric changes below 1500m depth together are smaller than the error of SLRES.

However, my statistics experience would hesitate to call that a representative sample since most of the observations in my sample are Wesleyan students and would therefore have an element of bias.

A lot of the observation based estimates are likely biased low, as outlined in the Ringberg report just due to assumptions of linearity in the evolution of surface temperature in response to some given radiative nudge on the system.

Some biases are corrected for (time of observation, re-siting to place), but it is fair to say not all biases are accounted for.

Progress in the longer term depends on identifying and correcting model biases, accumulating as complete a set of historic observations as possible, and developing improved methods of detection and correction of observational biases.»

Whether the issue is tracking Arctic methane or American stream flows, there's a vital need for sustained, consistent observations, but — unfortunately — there's a two - edged bias against such investments, given the appeal of focusing on science's frontiers and the tendency to target monitoring programs — which are akin to bridge maintenance — when looking to cut budgets.

That is the whole point of theory laden observation and confirmation bias.

As they point out, «In reality, however, observational coverage varies over time, observations are themselves prone to bias, either instrumental or through not being representative of their wider surroundings, and these observational biases can change over time.