Dynamical Downscaling and Data Assimilation: Insights from the Case Study of the "Year Without a Summer" 1816

One year after the eruption of the Tambora volcano, the “Year Without a Summer” of 1816 was characterised by extraordinarily cold periods in (Central) Europe, and it was associated with severe crop failures, food shortages, famine and socio-economic disruptions.

The summer of 1816, has been analysed based on a number of early meteorological measurements, as well as on ample documentary information. A statistical reconstruction of spatial fields with daily resolution has been conducted for Switzerland. However, this dataset encompasses only a limited set of variables. In turn, dynamical downscaling methods allow to reconstruct past weather on a higher temporal and spatial resolution. In our work, we simulate a particularly cold episode in June 1816 by downscaling data from the Twentieth Century Reanalysis version 3 (20CRv3). The simulation uses the Weather Research and Forecasting (WRF) model with three nested domains for the greater Alpine region and provides hourly output with a 3-km resolution. In addition, we include recently digitised station series of temperature and pressure for a Three-Dimensional Variational (3DVAR) data assimilation in the innermost domain. Results are then validated against independent station observations.

First results suggest that dynamical downscaling and data assimilation may become a promising approach to obtain physically consistent information on past weather on a local and subdaily scale. This may hold even for extreme events in an era with a scarce network of instrumental weather observations compared to today, although erroneous results may occur. A successful application of dynamical downscaling and data assimilation for the early 19^th century might open the door for a regional atmospheric reanalysis product that covers the last two centuries.