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HFP:
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Historical Forecast Project (HFP) data

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Data available through our interactive web server

Two 6-member ensembles of seasonal hindcasts are produced with two numerical models, the CCCma second generation atmospheric general circulation model AGCM2 (McFarlane, et al., 1992) and a reduced-resolution version of the medium-range weather forecast global spectral model (SEF) developed at Recherche en prévision numérique (RPN; Ritchie, 1991). Seasonal predictions for standard seasons (DJF, MAM, JJA, SON) are made for each of the 26 years in the period from March 1969 to February 1995. The integrations are initialized from the NCEP reanalyzed data at 6-hour intervals preceding the start of the forecast season and are labeled as "Lag 06h", "Lag 12h", ..., "Lag 36h" respectively. The global sea surface temperature anomalies from the GISST2.2 dataset of the month prior to the forecast period are persisted throughout the 3-month forecast. Details are found in Derome et al. (2001).

Seasonal hindcasts are provided on a 97x48 Gaussian grid (approximately 3.75 lat x 3.75 long). The NCEP reanalyses (Kalnay et al., 1996) are also available for verification purposes. The reanalysis data are interpolated on the 97x48 Gaussian grid.

The user should be aware that grid box values are not directly comparable to station data. Climate models attempt to represent the full climate system from first principles on large scales. Physical "parameterizations" are used to approximate the effects of unresolved small scale processes because it is not economically feasible to include detailed representations of these processes in present day models. Caution is therefore needed when comparing climate model output with observations or analyses on spatial scales shorter than several grid lengths (approximately 1000 to 1500 km in mid-latitudes), or when using model output to study the impacts of climate variability and change. The user is further cautioned that estimates of climate variability and change obtained from climate model results are subject to sampling variability. This uncertainty arises from the natural variability that is part of the observed climate system and is generally well simulated by the climate models.

Notes/updates:

  • Data are made available on January 15, 2001.

References:

Derome J., G. Brunet, A. Plante, N. Gagnon, G. J. Boer, F. W. Zwiers, S. Lambert, and H. Ritchie, 2001: Seasonal predictions based on two dynamical models. Atmosphere-Ocean, 39, 485-501 (PDF file).

Kalnay E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, E. Reynolds, R. Jenne, D. Joseph, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437-471.

McFarlane, N.A., G.J. Boer, J.-P. Blanchet, and M. Lazare, 1992: The Canadian Climate Centre second-generation general circulation model and its equilibrium climate. J. Climate, 5, 1013-1044 (Abstract).

Ritchie, H., 1991: Application of the semi-Lagrangian method to a multilevel spectral primitive-equations model. Quart. J. Roy. Meteor. Soc., 117, 91-106.


Last modified: 2006-09-05
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