抄録
Reconstruction of historical climate is essential for a better understanding of the future climate. However, only a limited number of observations are available before the 19th century. Historical documents such as personal diary records can be used as an alternative. Even though they have higher temporal resolution respect to other proxies, it is quite challenging to incorporate that information in climate model due to the high uncertainty present in those data. Here we use the Global Spectral Model (GSM) of National Centres for Environmental Prediction (NCEP) as the climate model, along with a local ensemble transformed Kalman filter (LETKF) as a data assimilation technique to investigate the possibility of assimilating different climate variables through idealize experiments. In order to investigate the influence of uncertainties associated with the historical documentations deteriorated JMA data were used. We could show that it is possible to improve the model performance by assimilating various information such as cloud amount, precipitation, and solar radiation.
