Precipitation characteristics of the Eurasian Arctic drainage system

Abstract

This study examines characteristics of precipitation over the major watersheds of the Eurasian Arctic drainage system over the period . In addition to the Ob, Yenisey and Lena (the three largest drainage systems), we examine the combined Kolyma-Indigirka in eastern Eurasia. Each basin exhibits approximately symmetric mean annual cycles of monthly total precipitation and daily event size, with winter minima and July maxima. These are strikingly similar to the annual cycles of total column water vapour (precipitable water), which fundamentally reflects the control on saturation vapour pressure by temperature. Effective precipitation mechanisms exist in all seasons. However, because of the long distance from strong moisture sources (continentality), precipitation tends to follow the seasonality in column water vapour. An effective contrast is presented for the Iceland sector. Here, the annual cycle of precipitation is tied not to the seasonality in column water vapour, but to the stronger precipitation-generating mechanisms in winter. Hence, the annual cycles of precipitation and column water vapour in this region oppose each other.Mean winter precipitation over the Eurasian watersheds is primarily driven by a modest convergence of water vapour. Whereas precipitation peaks in summer, the mean flux convergence exhibits a general minimum (negative in the Ob). Summer precipitation is hence primarily associated with surface evaporation. A strong role of convection is supported from consideration of static stability, the fairly weak spatial organization of precipitation totals and results from prior studies. On daily time scales, the largest basin-averaged precipitation events, for both summer and winter, are allied with synoptic-scale forcing. This is seen in relationships with cyclone frequency, and patterns of 500 hPa height, vertical motion and the 700 hPa vapour flux. The relative frequency of four 500 hPa synoptic types captures the basic time series structures of precipitation.

Synoptically forced hydroclimatology of major Arctic watersheds in general circulation models; Part 2: Eurasian watersheds

“…The precipitation regimes discussed above are in good agreement with analyses of Eurasian precipitation characteristics by Serreze and Etringer (2003), which also emphasized the influence of continental cyclones centred over a given basin on summer and winter precipitation events. The influence of coastal cyclones on winter precipitation is less clear in their results, as their analysis of cyclone activity did not extend beyond 75°N, limiting information on cyclones within the Siberian seas.…”

“…The influence of coastal cyclones on winter precipitation is less clear in their results, as their analysis of cyclone activity did not extend beyond 75°N, limiting information on cyclones within the Siberian seas. However, the limited coastal data which are provided match the results presented here reasonably well, with wet events in the Ob basin associated with high cyclone counts near the Barents and Kara sea coasts, and wet events in the Lena associated with cyclones near the Laptev coast (Figure 15 of Serreze and Etringer, 2003).…”

“…The majority of the atmospheric moisture entering the study region is transported by weather systems arriving from the west, and is subsequently lost as these systems travel across Siberia. Low-pressure systems also play an important role during summer, acting to organize the smaller scale convective precipitation that dominates Eurasia in this season (Serreze and Etringer, 2003). As in winter, summer precipitation totals from ERA-40 are generally highest for nodes that place a cyclone over a given basin.…”

Assessing Seasonal Backscatter Variations with Respect to Uncertainties in Soil Moisture Retrieval in Siberian Tundra Regions

“…The flat and low altitude areas where the sites are located are generally wet. The Western Siberian Lowlands, the coastal plains and the Taimyr Peninsula largely consist of tundra landscapes with predominating wet conditions (e.g., [41,42]). …”

Combined Forecasting of Rainfall Based on Fuzzy Clustering and Cross Entropy

“…However, affected by complex factors such as geographical environment, ocean currents, air pressure, temperature, etc. [1], rainfall exhibits strong randomness and nonlinear characteristics that often hamper the forecast of rainfall.…”