The purpose of this study is to extract climate factors affecting sweet persimmon yield by growth period and estimate the rate of future sweet persimmon yield using data of production and cultivation area of sweet persimmon and climate data for 1998-2015. During the analysis period, the cultivation area of sweet persimmon in Gyeongnam has been consistently decreasing, but sweet persimmon yield has increased. Climate factors that have statistically significant effects on sweet persimmon yield are mean temperature, maximum temperature, precipitation, precipitation days, and sunshine hours. The sweet persimmon yield is a statistically positively correlated with temperature and sunshine hours and negatively correlated with precipitation during the flowering period (April to May). The sweet persimmon yield is statistically positively correlated with precipitation in the growing period (June to August) and negatively correlated with temperature in maturity period (September to November). Future sweet persimmon yield is estimated to have a steadily decreasing rate of change in future climate change scenarios, RCP4.5 and RCP8.5.
Regional climate simulations for the CORDEX East Asia domain were conducted between 1981 and 2100 using five models to project future climate change based on RCP2.6, 4.5, 6.0, and 8.5 scenarios. By using the ensemble mean of five model results, future changes in climate zones and four extreme temperature events of South Korea were investigated according to Köppen-Trewartha’s classification criteria. The four temporal periods of historical (1981-2005), early future (2021-2040), middle future (2041-2070), and late future (2071-2100) were defined to examine future changes. The analysis domain was divided into 230 administrative districts of South Korea. In historical (1981-2005) period, the subtropical zones are only dominant in the southern coastal regions and Jeju island, while those tend to expand in the future periods. Depending on the RCP scenarios, the more radiative forcing results in the larger subtropical zone over South Korea in the future. The expansion of the subtropical zone in metropolitan areas is more evident than that in rural areas. In addition, the enlargement of the subtropical zone in coastal regions is more prominent than that of in inland regions. Particularly, the subtropical climate zone for the late future period of RCP8.5 scenario is significantly dominant in most South Korea. All scenarios show that cold related extreme temperature events are expected to decrease and hot related extreme temperature events to increase in late future. This study can be utilized by administrative districts for the strategic plan of responses to future climate change.
Land cover around weather station can affect various climatic elements such as temperature, precipitation, wind and moisture. This study tries to reveal patterns and causes in land cover changes around weather stations in South Korea and to classify types of the land cover changes. The agricultural land, forest and used area have occupied most areas around un-relocated 47 weather stations with enough weather observation durations for the past 20-30 years. Area of the agricultural land shows steady decrease with remarkable areal decrease in the wetland, while steady areal increase is found in the used area. Due to urban expansions and new town developments around the weather stations, areas of the urbanization type (used area+barren) and suburbanization type (agricultural land+forest+grass+wetland) show steady increase and decrease, respectively. On the other hand, accurate changes in land cover are not reflected in the water-front type (wetland+water) due to errors and limitations in land cover classification using satellite images. It is expected that the results in this study can contribute to reliability and homogeneity enhancement of weather data.
We investigated on the proper combination of physical parameterization schemes of RegCM4.0 for the simulation of regional climate over CORDEX-East Asia Phase 2 domain. Based on the Lee(2016)’s sensitivity experiments for the four combination using two land surface schemes and two cumulus parameterization schemes during 5 years (1979-1983), we selected the two combinations (CE: CLM+Emanuel and BG: BATS+Grell). The ERA-Interim was used as lateral boundary data of RegCM4.0 for the two experiments during 25 years (1981-2005). Simulation skills of temperature were similar in the two combination of physical processes irrespective of seasons and locations. However, there were a substantial differences in the simulation skills of precipitation according to the combination of physical processes, which were better in CE than BG combination. In general, the CE combination better simulated the precipitation characteristics in July and August over South Korea than BG combination, in terms of frequency and amount of precipitation according to the intensity. The superior skills of CE in simulating precipitation over South Korea can be related to the better simulation of seasonal march of the East Asian summer monsoon including the location and intensity of the North Pacific high pressure system than BG. The results suggested that the CE combination can simulate the climate characteristics in the CORDEX East Asia Phase 2 region better than the BG combination.
Intergovernmental Panel on Climate Change (IPCC) provides various prospects of future climate change under the Representative Concentration Pathways (RCP) scenarios using General Circulation Models (GCMs) of Coupled Model Intercomparison Project (CMIP). This paper describes a modified application of Ensemble Bayesian Model Averaging (EBMA) to produce daily mean temperature ensembles using 19 GCMs provided by CMIP. We proposed two types of approach: (1) monthly weighting scheme for a whole area (EBMA.v1) and (2) monthly weighting for each grid point (EBMA.v2), which can take into account the spatially heterogeneous pattern of GCM. For the training period of 1979- 2005 for East Asia, 9,855 sets of daily temperature ensembles (27 years × 365 days) were produced and compared to the ERA-Interim reanalysis data of European Centre for Medium-Range Weather Forecasts (ECMWF), which showed better validation statistics than the general mean and median ensembles. In particular, EBMA.v2 outperformed EBMA.v1 by diminishing the large errors of inland areas where the surface heterogeneity is larger than the ocean. The EBMA.v2 was able to handle the problem of spatial variability by employing monthly and spatially varying weighting scheme. We finally produced daily mean temperature ensembles for the period of 2006-2100 by using the EBMA.v2 under the RCP 6.0 scenario, which are going to be provided on the web.
It is difficult to measure precipitation due to spatial and temporal variability. In this study we analyzed the variability of precipitation of high- and low-rainfall regions in Bangladesh using Precipitation Concentration Index (PCI) from the data of two meteorological stations. We compared PCI values for various periods such as annual, supra-seasonal, seasonal, three and two-months. Most previous studies have analyzed the long-term precipitation in Bangladesh. We analyzed the variabilities from long-term to short-term and tried to characterize the irregular precipitation. In the result, the precipitation in Bangladesh was mostly concentrated between two and four months of the year. Future research will require more station data to understand the more detailed precipitation patterns in Bangladesh.