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A nested July-June precipitation reconstruction for the period AD 1777-2012 was developed from multi-century tree-ring records of Pinus sylvestris L. (Scots pine) for the Republic of Khakassia in Siberia, Russia. Calibration and verification statistics for the period 1948-2012 show a high level of skill and account for a significant portion of the observed variance (>50%) irrespective of which period is used to develop or verify the regression model. Splitsample validation supports our use of a reconstruction model based on the full period of reliable observational data . Thresholds (25th and 75th percentiles) based on the empirical cumulative distribution of 1948-2012 observed precipitation were used to delineate dry years and wet years of the long-term reconstruction. The longest reconstructed dry period, defined as consecutive years with less than 25th percentile of observed July-June precipitation, was 3 years (1861-1863). There was no significant difference in the number dry and wet periods during the 236 years of the reconstructed precipitation. Maps of geopotential height anomalies indicate that dry years differ from wet years primarily in the location of an anomalous 500-mb ridge approximately over the study area.

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.