ORIGINAL PAPER Temporal dynamics of precipitation in an extreme mid-latitude monsoonal climate E. A. Grigorieva & C. R. de Freitas Received: 18 December 2012 / Accepted: 6 May 2013 / Published online: 30 May 2013 # Springer-Verlag Wien 2013 Abstract Trends of precipitation over the twentieth century are examined by a variety of methods to more fully describe how precipitation has changed in the Russian Far East. Data used are considered to represent conditions of the extreme monsoonal climate of the high-to-mid-latitude climate of the Russian Far East region for the period 1911 to 2005. The study examines within-year characteristics of the 95-year time se- ries. The results show variability of precipitation is high in all months, but especially so during the cold season. Trends in the data indicate that both the wettest and driest months of the year are getting wetter. There are some distinct shifts in the trend patterns. Most noticeable is a shift from positive trends to negative trends. Overall, the results show the highest twen- tieth century precipitation in the early 1960s and in the late 1970s, with a general decrease since the mid-1980s. This differs from trends and means for Russia as a whole. The results also show standard normals to be different from a complete record of monthly precipitation data. Further, it may not enough to use a limited period times series such as a 30-year normal to represent a steady average for a year or a season, as the mean changes through time; in particular, for a steady cold season, mean one should use the full period. 1 Introduction The risk of climate change resulting from increasing concen- trations of greenhouse gases in the atmosphere has led to searches for signals in temperature and precipitation records (e.g. Kärner and de Freitas 2012; Roshydromet 2008; Hansen and Lebedeff 1987; Yu and Neil 1993). Efforts to model and account for broad-scale climate signals have had some success, but the major models have precipitation discrepancies at the regional scale (Solomon et al. 2007). As a result, precipitation projections into the future at the sub-regional scale are suspect (De Luis et al. 2009). Added to this are problems interpreting precipitation time series due to inter-annual and spatial vari- ability, which needs to be better understood if analyses of temporal trends or periodicities are to improve. In light of this, the IPCC (Solomon et al. 2007; Roshydromet 2008) suggests that the sub-regional variability in precipitation should be analysed in detail. This requires a data set going back as far as possible in time (De Luis et al. 2009; Lana and Burgueno 2000; Huntington 2006). There are also other considerations. Preparation of climatological data for use in research or for operational purposes often requires selection of part of the record as a ‘best estimate’ of ‘period averages’. The World Meteorological Organization (WMO) defined the latter as ar- ithmetical means of climatological data (World Meteorological Organization 2007). This forms the basis for describing climatic normals, which are a base reference statistic for characterising the climate of a location or region. Climatic normals are defined by the WMO as “period averages computed for a uniform and relatively long period comprising of at least three consecutive ten-year periods” (World Meteorological Organization 2007, p. 6). Normals in their most straightforward form are annual means and totals of daily atmospheric variables, usually air temperature and precipitation. WMO recommends that coun- tries update an official set of 30-year climate normals every 10 years. The reasoning is centred on the need to base funda- mental planning decisions on averages and extremes in non- stationary climate conditions. Climate normals are often used as basic information to classify a region’ s climate and make decisions for a wide variety of purposes involving, for instance, agriculture and E. A. Grigorieva Institute for Complex Analysis of Regional Problems, Far Eastern Branch, Russian Academy of Sciences, Birobidzhan, Russia e-mail: eagrigor@yandex.ru C. R. de Freitas (*) School of Environment, University of Auckland, Auckland, New Zealand e-mail: c.defreitas@auckland.ac.nz Theor Appl Climatol (2014) 116:1–9 DOI 10.1007/s00704-013-0925-x