clim.pact – a tool for empirical-statistical downscaling Monika Cahynová cas.cz Institute of Atmospheric Physics & Faculty of Science, Charles University Prague, Czech Republic COST733 WG4 meeting, Ioannina, 9-10 May 2008

clim.pact a package in the R environment developed by Rasmus Benestad (met.no, Oslo) freely available online enables various analyses of climate time series, multivariate methods (CCA, PCA), graphical output main task: empirical-statistical downscaling of monthly or daily time series

Downscaling (DS) in clim.pact finding linear relationships between regional predictor and local predictand in the calibration period extrapolation of the downscaled results to the period when only the predictor is known input data predictor: gridded observational or modelled data (ERA40, NCEP/NCAR, GCM output,…), converted into EOFs EOFs of one variable (e.g. SLP) or mixed-field EOFs (coupled structure of two fields, e.g. SLP and temperature) predictand: station, gridpoint or spatial mean time series of a climatic or other environmental variable

Downscaling (DS) in clim.pact what does clim.pact do within the DS function? stepwise regression between the leading EOFs of the predictor and the time series of the predictand within the calibration period calibration is by default carried out on detrended data construction of a downscaled (predicted) local time series for the period of known predictor – hindcast or forecast output: predicted local time series, spatial pattern of large- scale anomalies associated with it, ANOVA, analysis of residuals

Example: station object

Example: PCA results

Example: downscaling results

For those interested in clim.pact… A compendium on empirical-statistical downscaling, with examples on clim.pact use: Download clim.pact project.org/web/packages/clim.pact/index.html

Thank you for your attention.