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Air temperature distribution over Mongolia using dynamical downscaling and statistical correction
Author(s) -
Gerelchuluun Bayasgalan,
Ahn JoongBae
Publication year - 2014
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.3853
Subject(s) - downscaling , weather research and forecasting model , environmental science , inversion (geology) , lapse rate , climatology , meteorology , mean squared error , atmospheric sciences , mathematics , precipitation , geology , statistics , geography , structural basin , paleontology
In this study, dynamical downscaling was performed using the Weather Research and Forecast ( WRF ) model to attain fine‐resolution gridded meteorological information capable of reflecting Mongolia's complex topographical effect. Mongolia's sparse station network, with an average inter‐station distance 107 km, is incapable of representing the spatial distribution of climate variables, such as temperature, over the country's complex topography. In order to reproduce fine‐scale air temperature in Mongolia, the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis II data with 6‐h intervals from 1981 to 2010 were used as the initial and boundary conditions of the WRF model. A one‐way nesting system was applied for two nested domains with horizontal grid spaces of 60 and 20 km. For correction of the systematic biases induced by dynamical downscaling, a statistical correction method was used for the downscaled results simulated by the WRF model. The bias was divided into two parts: the mean and the perturbation. The former was corrected by using a weighting function and a temperature inversion, and the latter by using the self‐organizing maps method. In the former correction, the temperature inversion, characterized by an inverted lapse rate, in which temperature increases with increasing height in the lower atmosphere, was considered only when the temperature inversion occurred. According to our result, the domain‐averaged Root Mean Square Difference of the model‐simulated annual mean temperature was decreased from 3.7 °C to 2.1 °C after the statistical and temperature inversion corrections. On the basis of our study, we suggested that the area‐averaged, fine‐resolution, annual mean temperature of Mongolia was 1.1 °C (station mean temperature 0.5 °C). Our correction method improves not only spatial patterns with fine resolution but also the time‐varying temperature variance over Mongolia.