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Local estimates of global climate change: a statistical downscaling approach
Author(s) -
Solman Silvina A.,
Nuñez Mario N.
Publication year - 1999
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/(sici)1097-0088(19990630)19:8<835::aid-joc401>3.0.co;2-e
Subject(s) - downscaling , climatology , gcm transcription factors , environmental science , climate change , general circulation model , climate model , scale (ratio) , mean radiant temperature , range (aeronautics) , atmospheric sciences , geography , geology , oceanography , materials science , cartography , composite material
For the purposes of estimating local changes in surface climate at selected stations in the central Argentina region, induced by an enhanced CO 2 concentration, projected by general circulation models (GCM), a statistical method to derive local scale monthly mean minimum, maximum and mean temperatures from large‐scale atmospheric predictors is presented. Empirical relationships are derived among selected variables from the NCEP re‐analyses and local data for summer and winter months, tested against an independent set of observed data and subsequently applied to the HADAM and MPI GCM control runs. Finally, the statistical approach is applied to a climate change experiment performed with the MPI model to construct a local climate change scenario. The comparison between the estimated versus the observed mean temperature fields shows good agreement and the temporal evolution of the estimated variables is well‐captured, though, the estimated temperatures contain less interannual variability than the observations. For the present day climate simulation, the results from the HADAM and MPI GCMs are used. It is shown that the pattern of estimated temperatures obtained using the MPI large‐scale predictors matches the observations for summer months, though minimum and mean temperatures are slightly underestimated in the southeast part of the domain. However, the differences are well within the range of the observed variability. The possible anthropogenic climate change at the local scale is assessed by applying the statistical method to the results of the perturbed run conducted with the MPI model. For summer and winter months, the local temperature increase is smaller for minimum temperature than for maximum temperature for almost all the stations, yielding an enhanced temperature amplitude in both seasons. The temperature amplitude (difference between maximum and minimum) for summer months was larger than for winter months. The estimated maximum temperature increase is found to be larger for summer months than for winter months for all the stations, while for the minimum, temperature increases for summer and winter months are similar. Copyright © 1999 Royal Meteorological Society