While recurring and regular variations of weather conditions are implicitly addressed by standard seasonal adjustment procedures of economic time series, extraordinary weather outcomes are not. We propose a way of measuring aggregate abnormal weather conditions based on available local measurements and a straightforward regression-based framework to analyze their impact on German monthly total industrial and construction-sector production data, and find noticeable effects. In the historical - and seasonally adjusted - construction sector growth data the extra explanatory power of the weather regressors over a benchmark univariate autoregressive model even exceeds 50% of the variation. The estimated effects of weather deviations can be subtracted from the already seasonally adjusted data to obtain (seasonally as well as) weather adjusted series, which might capture economic developments better. The estimated adjustments are quantitatively relevant also for aggregate output (GDP).