A new approach to interpolating weekly average air temperature and precipitation at unsampled points from weather-station observations is discussed. Daily weather records of approximate 6400 stations available from World Meteorological Organization (WMO) over the period from 1977 to 1991 are used in applying the proposed method at the global scale. The methods improve upon commonly used procedures in that they incorporate spatially high-resolution digital elevation information, average environmental lapse rate, another higher-resolution longer-term monthly average temperature fields and daily average air temperatures/precipitation at weather stations. First, monthly weather data are interpolated by topographically or climatologically aided interpolation, and are served as benchmark. Then weekly average temperatures and precipitation are interpolated using weather-station observation data with traditional interpolation and are served as variation com-ponents. Finally, a weekly interpolation method based on both monthly climatic data and weekly-interpolated data is proposed. In addition, a quality control technique based on traditional interpola-tion method is introduced. Examinations show that the methodologies proposed in this paper are feasible and have a better interpolation accuracy.