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In recent years, the demand for improved sea ice forecasts in the Arctic has intensified as maritime transport and offshore exploration increase. To provide these forecasts, a few centers around the world have implemented operational sea ice forecasting systems. Here, I will provide an overview of the state of operational short-term (1-10 days) sea ice forecasting. These systems are hindered by a number of challenges associated with issues related to observation uncertainties (e.g., surface melt in passive microwave retrievals), data assimilation methods and model initialization. Additionally, the absence of a few key physical processes not represented in models (e.g. wave-ice interactions) is thought to contribute to large forecast error growth in certain regions. Some recent model developments (e.g., landfast ice parameterization, form drag) should help to improve sea ice forecasts. An additional challenge to sea ice forecasting is in how to bridge the gap with operational needs and translate forecasts into operational products (ice edge, ice internal pressure, etc.). Finally, the importance of verification methods to assess the forecast quality and to provide guidance in the development of sea ice forecasting systems will also be discussed.