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snow-models
meteoio
Commits
a255f307
Commit
a255f307
authored
Dec 08, 2014
by
Mathias Bavay
Browse files
Update the trend/residual approach in the documentation
parent
6f1cd6e9
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meteoio/InterpolationAlgorithms.h
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a255f307
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@@ -93,8 +93,14 @@ class Meteo2DInterpolator; // forward declaration, cyclic header include
* - ODKRIG_LAPSE: ordinary kriging with lapse rate (see LapseOrdinaryKrigingAlgorithm)
* - USER: user provided grids to be read from disk (if available, see USERInterpolation)
*
* @section interpol2D_lapse Lapse rates
* Several algorithms use elevation trends, currently modelled as a linear relation. The slope of this linear relation can
* @section interpol2D_trends Altitudinal trends
* Several algorithms use elevation trends, all of them relying on the same principles: the lapse rates are recomputed at each time steps
* (see section \ref interpol2D_lapse), all stations' data are detrended with this lapse rate, the residuals are spatially interpolated
* with the algorithm as configured by the user and finally, the values at each cell are retrended (ie the lapse rates are re-applied
* using the cell's elevation).
*
* @subsection interpol2D_lapse Lapse rates
* The altitudinal trends are currently modelled as a linear relation. The slope of this linear relation can
* sometimes be provided by the end user (through his io.ini configuration file), otherwise it is computed from the data.
* In order to bring slightly more robustness, if the correlation between the input data and the computed linear regression
* is not good enought (below 0.7, as defined in Interpol2D::LinRegression), the same regression will get re-calculated
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@@ -279,9 +285,9 @@ class IDWAlgorithm : public InterpolationAlgorithm {
/**
* @class IDWLapseAlgorithm
* @brief Inverse Distance Weighting interpolation algorithm with elevation detrending/reprojection.
* The input data is
projected to a reference elevation and
spatially interpolated using an Inverse Distance
* The input data is
detrended and the residuals are
spatially interpolated using an Inverse Distance
* Weighting interpolation algorithm (see IDWAlgorithm). Then, each value is reprojected to the real
* elevation of the relative cell. The lapse rate is either calculated from the data
* elevation of the relative cell
(re-trending)
. The lapse rate is either calculated from the data
* (if no extra argument is provided), or given by the user-provided the optional argument <i>"idw_lapse"</i>.
* If followed by <i>"soft"</i>, then an attempt to calculate the lapse rate from the data is made, any only if
* unsuccessful or too bad (r^2<0.6), then the user provided lapse rate is used as a fallback.
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