Abstract: Through the past 60-year development, the short-range climate prediction operation has made great progress in China in terms of the technology and methodology, undergoing the stages from the simple experiential statistic methods to numerical model. Especially in recent years, many objective prediction techniques and methods are well developed and applied in real-time operation. Meanwhile, many improved understanding and new knowledge of the climate system are also gradually used by climate forecasters.The ARGO (Array for Real-time Geostrophic Oceanography) global ocean data are applied in the global ocean data assimilation systems in NCC (NCC_GODAS), which enhances the monitoring and analyzing capability for the global ocean. The NCC_GODAS is integrated with coupled atmosphere-ocean models of NCC_CGCM, which increases the forecast skills for the short-term climate prediction. ARGO data are also applied for improving physical parameterization schemes in oceanic models, and the model capability of describing the real oceans and forecasting El Nio/Southern Oscillation is improved. The second-generation short-range climate forecast model, which upgrades many aspects of the resolution and physical process, exhibits a higher prediction skill comparing to the first-generation system. A preliminary evaluation indicates that the second-generation system shows a certain capability in predicting the pentad, ten-day, monthly, seasonal and inter-annual climate variability. The downscaling methods based on dynamical climate model are extensively used in operation including monthly prediction, seasonal prediction and extreme climate event prediction, improving the prediction skill of model production. Due to the limited predictability of a single model, multi-model ensemble (MME) is efficiently employed. Based on four operational dynamical models from NCC, NCEP, ECMWF and TCC, a multi-model ensemble system (MODES) is developed in NCC in 2011, in which downscaling technique is introduced and added to the ensemble prediction system. At present, this forecast system can issue monthly and seasonal ensemble prediction products and is applied by regional climate center. Based on the dynamical-statistical integration forecasting method, a forecasting system for seasonal precipitation (FODAS1.0) is developed, which has already been in quasi-operational use, showing stable prediction skill. The application of the intra-seasonal oscillation in the operational extended range forecast has made a great progress including that a MJO monitoring, prediction and application operational system is built up, and several forecast methods based on the intra-seasonal oscillation are applied. New knowledge and research achievements are gradually introduced into operation by forecaster, for example, in addition to the sea surface temperature (SST) in the equatorial mid-east Pacific, the SST in the Indian Ocean and the Atlantic Ocean are also seriously considered. In addition, the sea ice, snow cover over the Eurasia and the climate system in the Southern Hemisphere are also considered as the important impact factors in seasonal prediction.