2015) demonstrated the use of CHFP precipitation hindcasts in combination with those of the North American Multimodel Ensemble (NMME; Kirtman et al.
WGSIP's projects frequently draw on the CHFP database, supplemented by additional sensitivity integrations when needed.
4-averaged SST anomalies based on NOAA's Optimum Interpolation Sea Surface Temperature (OISST) observational analysis and the multimodel ensemble average for a core set of CHFP prediction systems at lead times of 0, 3, and 6 months is presented in Fig.
4 ensemble spreads and root-mean-square errors (RMSE), that overconfidence is a common deficiency in the tropics for many of the CHFP contributing models.
To ensure that the CHFP database is sustainable and well utilized by the research community over the longer term, a number of challenges need to be addressed.
While many operational centers store forecast data in version 2 of the gridded binary (GRIB2) format, a strategic choice was taken to archive CHFP data in netCDF format more commonly used in the research and climate modeling community.
The CHFP database therefore represents another piece of the meteorological open-access puzzle, making a vast set of seasonal forecasts freely available to the research community, facilitating the move toward seamless prediction.
Vera, 2017: Climate predictability and prediction skill on seasonal time scales over South America from CHFP models.
Doblas-Reyes, 2016: Predictability of the tropospheric circulation in the Southern Hemisphere from CHFP models.
Evolution of the number of hindcast systems contained in the CHFP database (blue bars) and total download (red curve; in GB) between 2012 and 2016.
4 index (area-averaged SST anomaly in 5[degrees]S-5[degrees]N, 170[degrees]-120[degrees]W), as observed (OISST analysis; black) and predicted by CHFP models (red) initialized from February, May, August, and November 1982-2009 at (a) 0-, (b) 3-, and (c) 6-month lead times.