{"id":885,"date":"2019-06-07T12:49:30","date_gmt":"2019-06-07T11:49:30","guid":{"rendered":"http:\/\/35.193.178.118\/?page_id=128"},"modified":"2019-07-18T12:05:49","modified_gmt":"2019-07-18T11:05:49","slug":"4-completing-the-effects-table","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/fiduceo\/cdr\/theoretical-basis-3\/4-completing-the-effects-table\/","title":{"rendered":"4. Completing the effects table"},"content":{"rendered":"\r\n

Every \u201ctwig\u201d on the measurement-function-centred uncertainty diagram represents an \u201ceffect\u201d and each effect has an associated effects table. The effects table takes the form given in Table 2.<\/p>\r\n\r\n\r\n\r\n

Note that the CDR effects table, unlike the FCDR effects table, includes a category of \u201cmaturity of analysis\u201d. This is given a qualitative scale to describe the extent of the available information about this effect. It also provides an estimate of the importance of the effect for those effects that have low maturity.<\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n

Table descriptor<\/strong><\/td>\r\n		\u00a0<\/td>\r\n
How this is codified<\/strong><\/td>\r\n
Notes<\/strong><\/td>\r\n<\/tr>\r\n<\/thead>\r\n
Name of effect<\/strong><\/td>\r\n\u00a0<\/td>\r\nA unique name for each source of uncertainty in a term of the measurement function or processing chain as appropriate<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
Affected term in measurement function <\/strong><\/td>\r\n\u00a0<\/td>\r\nName and standard symbol of affected term<\/td>\r\nUsually an effect will only affect a single term, though there may be exceptions<\/td>\r\n<\/tr>\r\n
Maturity of analysis<\/strong><\/td>\r\nMaturity of uncertainty estimate<\/td>\r\n4-point scale:
0 \u2013 Effect identified, no quantification performed (no further information in cells below)
1 \u2013 Rough estimates only
2 \u2013 Some analysis performed to estimate values
3 \u2013 Rigorous analysis performed<\/td>\r\n		This allows for the fact in the CDR we haven\u2019t thought everything through in detail and makes that very clear to users. \u00a0 If the maturity is low, we may still be able to estimate if it is negligible or minor, or if it\u2019s possibly significant (and therefore needs more work soon)<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nMaturity of correlation scale estimate<\/td>\r\n0 \u2013 Not done
1 \u2013 Estimated
2 \u2013 Based on analysis, unsure about correlation shape
3 \u2013 Strong evidence<\/td>\r\n		\u00a0<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nIf maturity of estimate is 0 or 1, how significant do you expect this effect to be?<\/td>\r\nNegligible, Minor or Significant?<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
Correlation type and form <\/strong><\/td>\r\nFrom level 1<\/td>\r\nOne of the types defined in below, provided by name<\/td>\r\nSee below \u00a0 \u00a0<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nLarger scale temporal [time]<\/td>\r\n\u00a0<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nLarger scale spatial [geospatial coordinates]<\/td>\r\n\u00a0<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
Correlation scale<\/strong><\/td>\r\nFrom level 1<\/td>\r\nWhat is correlation scale<\/td>\r\nSee below<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nLarger scale temporal [time]<\/td>\r\n\u00a0<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nLarger scale spatial [geospatial coordinates]<\/td>\r\n\u00a0<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
Uncertainty <\/strong><\/td>\r\nPDF shape \u00a0<\/td>\r\nFunctional form of estimated error distribution for the term<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nunits<\/td>\r\nUnits in which PDF shape is expressed (units of term, or can be as percentage etc)<\/td>\r\nSee comment below where uncertainty and sensitivity cannot be separated<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nmagnitude<\/td>\r\nValue(s) or parameterisation estimating width of PDF<\/td>\r\n\u00a0<\/td>\r\n<\/tr>\r\n
Sensitivity coefficient<\/strong><\/td>\r\n\u00a0<\/td>\r\nValue, equation or parameterisation of sensitivity of measurand to term.
Can also flag \u201cincluded in uncertainty\u201d (by making this equal 1)<\/td>\r\n		Where the uncertainty and sensitivity coefficient cannot be separated the sensitivity coefficient should be one and the uncertainty is in units of the CDR measurand.<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n\r\n\r\n\r\n

As with the FCDR effects tables, the CDR effects tables include information on the correlation scale.<\/p>\r\n\r\n\r\n\r\n

For FCDR effects we may be propagating error spatial correlation information from either the full FCDR, or the Easy FCDR. If the full FCDR it will have the same properties as for the FCDR and those cells can be copied (or in practice, new tables are not needed).<\/p>\r\n\r\n\r\n\r\n

If the Easy FCDR, then the correlation length scales are:<\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
FCDR effect<\/strong><\/td>\r\nShape <\/strong><\/td>\r\nSize <\/strong><\/td>\r\n<\/tr>\r\n<\/thead>\r\n
common effects<\/td>\r\nrectangle absolute<\/td>\r\ninfinite for all dimensions<\/td>\r\n<\/tr>\r\n
independent effects<\/td>\r\nrandom<\/td>\r\nnone for all dimensions<\/td>\r\n<\/tr>\r\n
structured effects<\/td>\r\nExponential_decay<\/td>\r\nas propagated from the Easy FCDR<\/td>\r\n<\/tr>\r\n
\u00a0<\/td>\r\nProvided_by_pixel*<\/td>\r\nvector propagated from Easy FCDR*<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n\r\n\r\n\r\n

*(this depends on the decision we make at the Easy FCDR level). This would be true for the pixel-to-pixel and scanline-to-scanline boxes. At all other scales it\u2019s random with no size.<\/p>\r\n\r\n\r\n\r\n

For new effects at the CDR level, the correlation form must be provided. As well as all the correlation forms defined for the FCDR, two new correlation forms have been introduced: the exponential_decay and the provided_per_pixel forms. Thus the full set of available correlation forms are given in Table 3.<\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Correlation form<\/strong><\/td>\r\nParameters<\/strong><\/td>\r\nDescription<\/strong><\/td>\r\n<\/tr>\r\n<\/thead>\r\n
random<\/strong><\/td>\r\nnone required<\/td>\r\nFor fully random effects there is no correlation with any other pixel<\/td>\r\n<\/tr>\r\n
rectangle_absolute<\/strong><\/td>\r\n[-a,+b]<\/strong> (rectangle limits). Provide these per pixel\/scanline\/orbit as required. Allow for a way of representing [-\u221e,+\u221e]<\/strong> \u00a0 [rmax]<\/strong> States correlation coefficient for all pixel \/ scanline \/ orbit pixels. Default is rmax = 1 (fully correlated)<\/td>\r\nAn effect is systematic within a range and different outside that range. For each pixel \/ scanline \/ orbit in range say number of pixels \/ etc either side that it shares a correlation with. For fully systematic effects notation to say \u201csystematic with all\u201d. If rmax is defined, then the correlation coefficient is one for the pixel with itself, and is rmax with all other pixels.<\/td>\r\n<\/tr>\r\n
triangle_relative<\/strong><\/td>\r\n[n]<\/strong> \u2013 number of pixels\/scanlines being averaged in simple rolling average (should be an odd number)<\/td>\r\nSuitable for rolling averages over a window from (\u2013n-1)\/2 to (+n-1)\/2 (i.e. for n pixels\/scanlines being averaged) Assumes a simple mean, not a weighted mean. No rmax is needed, since it is always 1.<\/td>\r\n<\/tr>\r\n
bell_shaped_relative<\/strong><\/td>\r\n[n] \u2013 number of pixels being averaged in a weighted rolling average, from which truncation range and standard deviation for Gaussian representation follow (truncation beyond \u00b1n pixels, ) (n should be odd) \u00a0 OR \u00a0 [n,sigma] n: truncation from \u2013n to +n, sigma: width of Gaussian representation (n should be odd) \u00a0 Typically provided once per orbit file (some further consideration needed about first\/last scanlines in an orbit) \u00a0 \u00a0<\/td>\r\nSuitable for rolling averages over a window from (\u2013n-1)\/2 to (+n-1)\/2 (i.e. for n pixels\/scanlines being averaged). Assumes a weighted mean, for any weights (and thus also includes things like spline fitting). Also suitable for anything else where the assumption is that \u201ccloser pixels\/scanlines are more correlated than further pixels\u201d. This can use two terms \u2013 n gives the truncation range outside which the assumption is there is no (or negligible) correlation, and sigma gives how fast the correlation drops off. The derivation of the width sigma to use for a weighted rolling average is given in Appendix B.4.4.<\/td>\r\n<\/tr>\r\n
repeating_rectangles<\/strong><\/td>\r\n[-a,+b,rmax,L,h,imax] per pixel\/scanline\/orbit etc (rmax,L,h will be same for different pixels) \u00a0<\/td>\r\nCorrelation coefficient assumed to be rmax for pixels\/scanlines from \u2013a to +b, and h for pixels\/scanlines from L-a to L+b and from 2L-a to 2L+b and so on (iL-a to iL+b) for all integers i up to imax.<\/td>\r\n<\/tr>\r\n
repeating_bell-shapes<\/strong><\/td>\r\n[n,sigma,L,h, imax]<\/td>\r\nCorrelation coefficient assumed to drop off as a truncated Gaussian for local pixels\/scanlines etc in the range defined by n and a similar Gaussian with a peak of h and the same width for pixels\/scanlines iL pixels apart on either side, for all integers I up to imax.\u00a0<\/td>\r\n<\/tr>\r\n
Stepped_triangle_absolute<\/strong><\/td>\r\n[-a,+b,n] per pixel\/scanline\/orbit etc (n will be same for different pixels) \u00a0<\/td>\r\nThe step is a rectangular absolute from \u2013a to +b with a correlation coefficient of one, after which the correlation coefficients drops for another a+b+1 lines, and then again. n is the number of calibration windows averaged. See Appendix B.4.5<\/td>\r\n<\/tr>\r\n
xponential_decay<\/strong><\/td>\r\n[el,unit]<\/td>\r\nel: Length scale of exponential decay. Unit: unit of that length scale (we need to think about how we make this machine-interpretable! \u2013 could be time or space depending on which row you\u2019re considering]<\/td>\r\n<\/tr>\r\n
Provided_by_pixel<\/strong><\/td>\r\n[vector of relative correlation]<\/td>\r\nFor the Easy FCDR propagation<\/td>\r\n<\/tr>\r\n
Other<\/strong><\/td>\r\nA function describing the correlation<\/td>\r\nNot yet implemented.<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n","protected":false},"excerpt":{"rendered":"

Every \u201ctwig\u201d on the measurement-function-centred uncertainty diagram represents an \u201ceffect\u201d and each effect has an associated effects table. The effects table takes the form given in Table 2. Note that…Read More ><\/a><\/p>\n","protected":false},"author":219,"featured_media":0,"parent":240,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","footnotes":""},"coauthors":[6],"class_list":["post-885","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\n4. 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