Characteristics of dynamic downscaling results in Japan and Vietnam

For climate studies, a dynamic downscaling is one way to obtain detail information of meteorological variables in current and future climate conditions. A statistical method is also used for downscaling climate data, but future climate conditions do not necessarily follow statistical characteristics in the current climate. In dynamic downscaling, numerical models are used and results are derived from invariant formula of dynamics and physics. However, numerical models are not perfect and downscaling results have errors and biases. These errors and biases depend on a model and target regions, seasons, etc. In this study, the current climate conditions in Asia, namely Japan and Vietnam, are downscaled by the weather research forecasting model (WRF). For the two regions, entire years of heavy and light rain cases are selected. Downscaled climate conditions show that spatial distribution and seasonal variation of air temperature agree well with a reanalysis data used as initial and boundary conditions for WRF. Spatial resolutions of precipitation show characteristics of actual distribution in the central part of Japan and the north part of Vietnam. Seasonal variations of precipitation correspond to the observations for each year, or difference in wet and dry seasons between the heavy and light rain years. In the light rain year, precipitation amounts relatively agree well with the observation. However, precipitation is underestimated in the heavy rain year, and the annual rainfall in the downscaling result of the heavy rain year is smaller than that of the light year. One of the reasons is that a heavy rainfall event (300 mm in a day) is not reproduced in the downscaling result. In a relatively longer simulation (in this study, 40 days), an extreme event may not be reproduced precisely, and it gives an impact in seasonal or interannual variation. In the central Japan, there are some snowfalls in winter, but it is overestimated in the downscaling results.