While weather-climate modeling has improved steadily during the past decades, modeling community is still struggling with biases in both the time mean features and those associated with the variability, ranging in the mesoscale to decadal scales. Weather-climate analysis and prediction initialization require incorporation of a numerical model and the observing system through a data assimilation approach. Data assimilation uses model dynamics and physics to extract observational information from measured data scattered in time and space, pursuing balanced and coherent state analysis and estimation. While data assimilation provides initial conditions for weather-climate predictions, the reconstructed continuous time series of weather and climate variables with three-dimensional structures serve as a basis for one to further understand the mechanisms of weather-climate development. Nowadays, various data assimilation methods and observing system assessment have been developed for the need of analyzing and predicting the phenomena that have different spatial and temporal scales, and a wide scope of studies is ongoing on assimilation methods as well as impacts on model predictability and numerical predictions.

In this special issue, we call for papers that deal with recent advances in data assimilation methods, weather-climate analysis and prediction, observing system assessment, and model bias correction as well as model parameter optimization.

Potential topics include, but are not limited to:

• Development, implementation, and validation of data assimilation methods
• Model predictability and numerical weather-climate predictions
• Tropical cyclone forecast initialization
• Multiscale data assimilation applying to coupled data assimilation as well as high resolution data assimilation
• Assimilation of satellite and radar data
• Coupled data assimilation, ocean data assimilation, and sea ice data assimilation
• Land data assimilation and data assimilation in ecosystem
• Decadal predictability, prediction, and long-term projection
• Observing system assessment