Climate Dynamics

, Volume 42, Issue 5–6, pp 1449–1468 | Cite as

Global seasonal climate predictability in a two tiered forecast system. Part II: boreal winter and spring seasons

Article

Abstract

We examine the Florida Climate Institute–Florida State University Seasonal Hindcast (FISH50) skill at a relatively high (50 km grid) resolution two tiered Atmospheric General Circulation Model (AGCM) for boreal winter and spring seasons at zero and one season lead respectively. The AGCM in FISH50 is forced with bias corrected forecast sea surface temperature averaged from two dynamical coupled ocean–atmosphere models. The comparison of the hindcast skills of precipitation and surface temperature from FISH50 with the coupled ocean–atmosphere models reveals that the probabilistic skill is nearly comparable in the two types of forecast systems (with some improvements in FISH50 outside of the global tropics). Furthermore the drop in skill in going from zero lead (boreal winter) to one season lead (boreal spring) is also similar in FISH50 and the coupled ocean–atmosphere models. Both the forecast systems also show that surface temperature hindcasts have more skill than the precipitation hindcasts and that land based precipitation hindcasts have slightly lower skill than the corresponding hindcasts over the ocean.

Keywords

ENSO Seasonal predictability  Forecast skill 

Notes

Acknowledgments

This paper is dedicated to the memory of Dr. Masao Kanamitsu, without whose pioneering development of the FISH50 AGCM, this work would not have been possible. We also acknowledge the help of Dr. Zhaohua Wu who provided us the methodology and the data for the bias corrected SST (SSTOLF). We thank Mr. Steven DiNapoli for making Figs. 14, 15, 16. This work was supported by grants from NOAA (NA12OAR4310078, NA10OAR4310215, NA11OAR4310110), USGS (06HQGR0125), and USDA (027865). All computations for this paper were done on the computational resources provided by the Extreme Science and Engineering Discovery Environment (XSEDE) under TG-ATM120017 and TG-ATM120010.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Center for Ocean-Atmospheric Prediction StudiesFlorida State UniversityTallahasseeUSA
  2. 2.Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeUSA
  3. 3.Florida Climate Institute, Florida State UniversityTallahasseeUSA

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