INFLUENCE OF LAND USE CATEGORIES ON WRF FORECAST AND ITS ACCURACY

In this research analysis of possibilities and methods of correction or reclassification of land use and land cover data, obtained modeling effects of using more accurate land use and land cover data and estimations of improvements of surface meteorological parameters simulations by mesoscale numerical atmospheric prediction (NWP) model. For the Kyiv region area, it is shown that the default WRF land use and land cover datasets are not ideal and contain various types of inaccuracies. Thus, compared to USGS, MODIS IGBP is characterized by a better spatial resolution, more correctly describing the urban built-up territories, forest areas and the Dnipro riverbed, but MODIS IGBP does not display small settlements. Analysis of other researches had shown that most of the reviewed studies are based on the case study approach, namely on an analysis of a small number of specific simulations. The disadvantage of this approach is that the sample size from which conclusions can be drawn is insignificant, so it is useful to compare similar studies for the consistency of the obtained results. The most consistent conclusions regarding the simulation improvement by the land use and land cover modification in the WRF model are related to the parameters of air temperature and humidity. Thus, the usage of more accurate and up-to-date land use and land cover databases in WRF simulations made it possible to reduce bias of forecasts and improved the accuracy of minimum and maximum daily temperature forecasts. The most significant improvement in the performed forecasts concerns the night temperature. The second parameter that were most often able to predict better is relative humidity. Improvement of simulated wind parameters using another land use and land cover dataset in the WRF model may be possible in urban areas and near the coast, especially as improving description of breeze circulation by the model. Assessments regarding the possibility of improving WRF precipitation simulation by land use and land cover dataset modification are not definite, although some works have noted the influence of the heat island of urbanized areas on redistribution of precipitation. On the one hand, in most of the analyzed scientific works, land use and land cover changes did not allow to significantly improve precipitation forecasts using the WRF model. On the other hand, it can be assumed that the physical and geographical conditions of a simulation domain as well as available moisture in the atmosphere is playing a more significant role in precipitation modeling than land use and land cover.