This study focuses on the Dongjiang Basin and evaluates the prediction accuracy and stability of CFSv2 model products at the monthly scale using the anomaly coefficient of correlation (ACC), normalized root mean square error (NRMSE), mean absolute error (MAE), and the mu...
Diagnostic evaluations of the relative performances of CFSv1 and CFSv2 in prediction of monthly anomalies of the ENSO-related Nino3.4 SST index are conducted using the common hindcast period of 1982–2009 for lead times of up to 9months. CFSv2 outperforms CFSv1 in temporal correlation skill fo...
Spatial Structure, Forecast Errors, and Predictability of the South Asian Monsoon in CFS Monthly Retrospective Forecasts The spatial structure of the boreal summer South Asian monsoon in the ensemble mean of monthly retrospective forecasts by the Climate Forecast System of th... HKL Drbohlav,V Krish...
000. The extreme precipitation was associated with the formation of the South Atlantic convergence zone (SACZ). Even though the physical mechanisms behind the formation and persistence of subtropical convergence zones are still unclear, we demonstrate...
Monthly Weather ReviewWeber, N.J. and C.F. Mass, 2017: Evaluating CFSv2 Subseasonal Forecast Skill with an 578 Emphasis on Tropical Convection. Mon. Wea. Rev., 145, 3795-3815, 579 https://doi.org/10.1175/MWR-D-17-0109.1Weber NJ, Mass CF (2017) Evaluating CFSv2 subseasonal forecast ...
Using the National Center for Environment Prediction-Climate Forecast System version 2 (NCEP-CFSv2), this study comprehensively evaluates the seasonal and monthly prediction of the Siberian high intensity during the winter time (November to February). Results show that the NCEP-CFSv2 model can ...
This paper analyzes the role of ocean–atmosphere processes associated with break days and their impact on dry-land biases of Indian summer monsoon in Climate Forecast System version 2 (CFSv2)'s sub daily and monthly hindcasts, which are produced by initializing the forecast system every 5days ...
Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.doi:10.1175/mwr-d-19-0289.1C. SchreckM. JanigaS. BaxterAmerican Meteorological SocietyMonthly Weather Review...
The 30-day forecasts of precipitation and temperature indices calculated from the downscaled monthly CFSv2 forecasts were less skillful than those calculated directly from CFSv2 daily forecasts, suggesting the usefulness of CFSv2 for sub-seasonal hydrological forecasting.doi:info:doi/10.5194/hess-21-...
The operational experiment illustrates that CFSv2-WRF can reduce the CFSv2 uncertainty (up to 69%) for monthly precipitation and the onset of the rainy season but has still strong deficits regarding the northward progression of the rain belt. Further studies are necessary for a more robust ...