Sentences with phrase «spatial sampling»

Spatial sampling refers to the process of gathering data or measuring something across different locations or points within a space. It involves collecting information or observing certain characteristics at specific positions in order to understand patterns, variations, or relationships within a particular area or environment. Full definition
The shaded regions are the one - and two - standard deviation uncertainties calculated including both statistical and spatial sampling errors.
There is little disagreement between us on the broad trends when seasonal and spatial sampling issues, and differing conventions for e.g. defining reference periods, have been taken appropriately into account.
The blue uncertainty bars (95 % confidence limit) account only for incomplete spatial sampling.
To have a simple average work, you need a relatively even spatial sampling, and relatively equal representation in each proxy for a particular area.
Values for ERA - Interim are also shown with the same spatial sampling as HadISDH.
The three datasets differ more in their all - land averages, in part due to incomplete spatial sampling in HadISDH.
Correcting for this one effect does not bring trends into perfect agreement with those predicted based on the surface — they still fall slightly short in the tropics during the last two decades, and are too strong in the southern hemisphere extratropics when measured over the last four decades — but these remaining discrepancies are well within what would be expected based on other errors and the poor spatial sampling of the radiosonde network.
As for spatial sampling, it is clear that you would ideally want as even a spread as possible, but any method you would actually want to use has to be able to deal with the certain heterogeneity.
Additionally, fiber allows for dense spatial sampling, meaning data points are only meters apart, whereas seismometers typically are separated by many kilometers.
Although teleconnections are best defined over a grid, simple indices based on a few key station locations remain attractive as the series can often be carried back in time long before complete gridded fields were available (see Section 3.6.4, Figure 3.31); the disadvantage is increased noise from the reduced spatial sampling.
«Our results suggest that mark — recapture estimates may have been negatively biased due to limited spatial sampling.
ERA - Interim and JRA - 55 values are shown with full spatial sampling.
Because of inhomogeneities within the station records and the inadequate and time - varying spatial sampling it is inevitable that multiple, somewhat distinct, estimates will result from running different algorithms on the recommended merge version of the databank.
However, other 19th Century temperature compilations such Berkeley Earth show larger responses to Tambora — though there are spatial sampling issues there as well.
Yet these apply to spatial samples as well, with frequency represented as essentially wavenumbers.
Gavin points out these sources of error: ``... imperfect data and has uncertainties due to spatial sampling, inhomogeneities of records (for multiple reasons), errors in transcription etc..»
An analysis using synthetic proxy data with spatial sampling density and proxy signal - to - noise ratios equivalent to those of the D'Arrigo et al (2006) tree - ring network suggest that these discrepancies can not be explained in terms of either the spatial sampling / extent or the intrinsic «noisiness» of the network of proxy records.
However, spatial sampling is still an issue in the higher latitudes of the Southern Hemisphere, and ensuring the homogeneity of these data in the face of urbanization and changes incontinue
Values for ERA - Interim are shown both with complete spatial sampling and with the same incomplete spatial sampling as HadISDH.
Here, we demonstrate that the changes in the spatial sampling of the historical observation network introduced an artificial jump during the initiation of the global Argo array (2001 — 2003).
It should be noted that their estimate of uncertainty relates mostly to the spatial sampling, or sparse data coverage.
People seem to be sure the spatial sampling is more than enough (Ray Ladbury is even saying 4 times over-sampled) to capture acurately the average temperature, at least for the last 40 years.
So it's not a corruption of the data and it's not a spatial sampling issue.
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