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Zewdu T. Segele, Michael B. Richman, Lance M. Leslie, and Peter J. Lamb

decreasing frequency, 2) predictors that are decreasing in skill, 3) predictors that were not included in the selected sets that are starting to show additional skill, and 4) changes in the likelihood functions due to climate change. Updating the RV and LOOCV prediction models using the entire data with follow up real-time forecast evaluation realistically could lead to successful real-time operational use of the approaches. The simultaneous use of both approaches builds confidence in the value of the

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Lisa Hannak, Peter Knippertz, Andreas H. Fink, Anke Kniffka, and Gregor Pante

height between the actual ERA-I reanalysis and the short-term forecasts used here (not shown). Fig . 4. Surface downwelling shortwave irradiance in W m −2 : (a) CM SAF operational SEVIRI product, (b) CM SAF SARAH product, (c) ERA-I, and (d) mean over YoTC models. Climatologies from ground-based observations are depicted as circles. All data are temporally averaged over JAS but available periods differ: 2007–15 in (a), 1983–2008 in (b), and 1991–2010 in (c) and (d) with varying coverage for the

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Gang Zhang, Kerry H. Cook, and Edward K. Vizy

fields on 3-hourly intervals over West Africa. To reduce the uncertainty of using reanalysis data, other global reanalyses are also compared with MERRA, including the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR; Saha et al. 2010 ), the ECMWF interim reanalysis (ERA-Interim; Dee et al. 2011 ), and the ECMWF reanalysis from their operational forecasts for the AMMA observational campaign with AMMA radiosonde data assimilated (ECMWF-OPERA; Agustí

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Elinor R. Martin and Chris Thorncroft

: An evaluation of the performance of the ECMWF operational system in analyzing and forecasting easterly wave disturbances over Africa and the tropical Atlantic . Mon. Wea. Rev. , 116 , 824 – 865 , doi: 10.1175/1520-0493(1988)116<0824:AEOTPO>2.0.CO;2 . Richter , I. , S.-P. Xie , S. K. Behera , T. Doi , and Y. Masumoto , 2014 : Equatorial Atlantic variability and its relation to mean state biases in CMIP5 . Climate Dyn. , 42 , 171 – 188 , doi: 10.1007/s00382-012-1624-5 . Roehrig

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