The 2019-nCoV outbreak in China presents a significant challenge for modelers, as there are limited data available on the early growth trajectory, and epidemiological characteristics of the novel coronavirus have not been fully elucidated. Our timely short-term forecasts based on phenomenological models can be useful for real-time preparedness, such as anticipating the required number of hospital beds and other medical resources, as they provide an estimate of the number of cases hospitals will need to prepare for in the coming days. In future work, we plan to report the results of a retrospective analysis of forecasting performance across models based on various performance metrics. Of note, the case definition changed on February 12, 2020 to count clinical cases that have not been laboratory tested. As a result in this change in reporting, the province of Hubei experienced a jump in the nuber of cases on February 13th, 2020. This change in reporting will need to be taken into account in order to assess the accuracy of the forecasts reported here.