I have interpolated a particular Global Circulation Model (GCM) having monthly precipitation data over a region during the period 1901-2100. I want to calculate the internal variability in the past (1901-2000) as well as in the future (2001-2100). How to calculate them?
What does it mean, "internal variability of precipitation is large compared to the expected global warming signal, especially at the local level, and can over-ride the expected signal for decades at a time"
Hi Kumar,
I will suggest you look at a few publications on GCM internal variability and uncertainty etc. For example : http://onlinelibrary.wiley.com/doi/10.1002/2013WR014897/pdf and http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00629.1
All the best!
please see the online pdf
Internal variability and model uncertainty components in
future hydrometeorological projections: The Alpine Durance
basin
M. Lafaysse1,2, B. Hingray1,3, A. Mezghani1,3,4, J. Gailhard5, and L. Terray6
1
University of Grenoble Alpes, LTHE UMR 5564, Grenoble, France, 2
Meteo-France/CNRS, CNRM-GAME, CEN, SaintMartin-d’He`res,
France, 3
CNRS, LTHE UMR 5564, Grenoble, France, 4
Now at Norwegian Meteorologisk Institutt, Oslo,
Norway, 5
EDF-DTG, Grenoble, France, 6
CERFACS/Sciences de l’Univers, CERFACS-CNRS URA 1875, Toulouse, France
Abstract A multireplicate multimodel ensemble of hydrological simulations covering the 1860–2099
period has been produced for the Upper Durance River basin (French Alps). An original quasi-ergodic analysis
of variance was applied to quantify uncertainties related to General Circulation Models (GCMs), Statistical
Downscaling Models (SDMs) and the internal variability of each GCM/SDM simulation chain. For temperature,
GCM uncertainty prevails and SDM uncertainty is nonnegligible. Significant warming and in turn significant
changes are predicted for evaporation, snow cover and seasonality of discharges. For precipitation,
GCM and SDM uncertainty components are of the same order. A high contribution of the large and smallscale
components of internal variability is also obtained, inherited, respectively, from the GCMs and the different
replicates of a given SDM. The same applies for annual discharge. The uncertainty in values that could
be experienced for any given future period is therefore very high. For both discharge and precipitation,
even the sign of future realizations is uncertain at a 90% confidence level. These findings have important
implications. Similarly to GCM uncertainty, SDM uncertainty cannot be neglected. The same applies for both
components of internal variability. Climate change impact studies based on a single SDM realization are
likely to be no more relevant than those based on a single GCM run. They may lead to poor decisions for climate
change adaptation.
Please read this paper.
Deser, C., A. S. Phillips, M. A. Alexander, and B. V. Smoliak, 2014: Projecting North American Climate over the next 50 years: Uncertainty due to internal variability. J. Climate, 27, 2271-2296, doi: 10.1175/JCLI-D-13-00451.1. Can access article from:
http://www.cgd.ucar.edu/staff/cdeser/
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