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Public granaries served as key infrastructures to improve food security in agrarian societies. Their history dates to the oldest complex societies, but they experienced a boom period during the 18th and early 19th centuries in Europe. In Bohemia and Moravia (modern-day Czech Republic), numerous granaries were established by decree in 1788 to provide serfs with grain for sowing in the face of fluctuating weather. Here, we analyze granary data from 15 out of a total of 17 considered domains in the Sušice region (southwest Bohemia) from 1789 to 1849 CE. We use the documented annual values of grain borrowed by serfs, their grain depositions, total grain storage, and the total debt of serfs at the end of the year as proxies for harvest quality and size. Based on the series of these four variables, we calculate weighted grain indices, considering the balance between borrowed and returned grain: a weighted bad harvest index (WBHI), a weighted good harvest index (WGHI), a weighted stored grain index (WSGI: WSGI-, more borrowed than returned; WSGI+, more returned than borrowed), and a weighted serf debt index (WSDI: WSDI+, more borrowed than returned grain; WSDI-, more returned than borrowed grain). WBHI, WSGI-, and WSDI+ were used to select years of extreme bad harvests, and WGHI, WSGI+, and WSDI- to identify years of extreme good harvests. We tested selected extreme harvest years against documentary weather data and reconstructed temperature, precipitation, and drought series from the Czech Lands. We discuss the uncertainty of the data and the broader context of the results obtained. The findings document the potential of this new methodology, using widely available public granary data as proxies for historical climatological research. [ABSTRACT FROM AUTHOR]

ClimeApp is a newly developed web-based processing tool for the state-of-the-art ModE-RA paleo-climate reanalysis. It presents temperature, precipitation and pressure reconstructions with global coverage and monthly resolution for the period 1422 to 2008 C.E. These can be visualized as maps or timeseries and compared with historical or other climate-related information through composite, correlation and regression functions. Alongside ModE-RA, ClimeApp allows access to the ModE-Sim climate simulation, which is the basis of ModE-RA before assimilating early instrumental, documentary and proxy data. Together with the sensitivity experiment ModE-RAclim, these three data sets allow researchers to separate the effects of external forcing from internal climate variability. The app is designed to allow quick data processing for climatologists and easy use for non-climatologists. Specifically, it aims to help bring climate into the humanities, where climatological data still has huge potential to advance research. This paper outlines the development, processing and applications of ClimeApp, and presents an updated analysis of the calamitous Tambora volcanic eruption and the 1816 'year without a summer' in Europe, using the new ModE datasets. ClimeApp is available at https://mode-ra.unibe.ch/climeapp/. [ABSTRACT FROM AUTHOR]