Premium
A new atmospheric dataset for forcing ice–ocean models: Evaluation of reforecasts using the Canadian global deterministic prediction system
Author(s) -
Smith Gregory C.,
Roy François,
Mann Philip,
Dupont Frédéric,
Brasnett Bruce,
Lemieux JeanFrançois,
Laroche Stéphane,
Bélair Stéphane
Publication year - 2014
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2194
Subject(s) - forcing (mathematics) , climatology , environmental science , sea ice , meteorology , atmospheric sciences , geology , geography
Despite the availability of several atmospheric reanalyses (e.g. ERA‐Interim) there exists both considerable uncertainty in surface forcing fields for ice/ocean modelling and sensitivity to the choice of product used. Here we introduce a relatively high‐resolution alternative forcing dataset for ice–ocean models derived from the Canadian Meteorological Centre's (CMC) global deterministic prediction system (GDPS). A set of daily 30 h reforecasts is produced using the GDPS 33 km resolution model providing hourly atmospheric forcing fields for the period 2002–2011. The CMC GDPS reforecasts (CGRF) are compared with ERA‐Interim and several observational datasets to evaluate their suitability for forcing ocean models. In particular, the surface temperature, humidity and winds of the CGRF show equivalent biases to those found in ERA‐interim. Moreover, the higher resolution of the CGRF permit a more detailed representation of atmospheric structures and topographic steering, resulting in finer‐scale coastal features and wind‐stress curl. Although the CGRF dataset is not a reanalysis and thus is expected to be less well constrained by available observations, its higher resolution and small bias make it an attractive alternative for forcing ice‐ocean models.