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Currently, high latitude regions characterized by a long and severe cold season are receiving more and more attention from the hydrometeorological modelling community (Bowling et al., 2000; Slater et al., 2001; Bowling et al., 2003; Nijssen et al., 2003; Etchevers et al., 2004; Su et al., 2005; Tian et al., 2007; etc.) because these regions are among the most sensitive to natural and anthropogenic effects and it is necessary to predict the consequences of such effects. At the same time, northern regions are poorly covered with measurements, which are necessary to provide the atmospheric forcing data and to estimate the land surface parameters for model simulations. One of the possible ways to provide a model with input data is to apply, along with existing measurements, available global datasets, which contain meteorological data, land-use information, and soil and vegetation characteristics. Nowadays there are a lot of global data sets, which differ in spatial and temporal resolution, as well as in accuracy and reliability (e.g., Meeson et al., 1995; Hall et al., 2003; Zhao & Dirmeyer, 2003). Differences in global datasets are connected with uneven coverage of the land surface with ground-based observation systems, difficulties in collecting measurements, the problems with instruments, differences in procedures of filling in the missing data and interpolation of point measurements into grid boxes (Zhao & Dirmeyer, 2003). Nevertheless, this source of information is quite attractive for modellers (as it saves them from a quite difficult timeand labour-consuming procedure of model input data preparation) and global datasets are widely used for atmospheric and hydrological applications (e.g., Oki et al., 1999; Nijssen et al., 2001; Su et al., 2005). However, the accuracy of most streamflow hydrograph simulations in high latitudes is not high, in spite of a good model structure and calibration of a number of model parameters against measured river runoff from the whole basin under study or from its sub-basins or small catchments, located within the basin. This raises a question: where can one find the potentialities to improve the agreement between observed and simulated streamflow hydrographs? We believe that one of such potentialities is to introduce adjustment factors for the most influencing atmospheric forcing data, along with the land surface characteristics, into a set of calibrated parameters. As a matter of fact, according to the logic of construction and operation of hydrological and land surface models, both the land surface parameters and forcing data represent input

Parameter Optimization for Simulating Runoff from Highlatitude River Basins Using Land Surface Model and Global Data Sets