This study presents the development of an elevated subsidence inversion over a surface low pressure system, which was formed along the Changma front or Meiu-Baiu front. The results of our analysis strongly suggest that the inversion is dissimilar to those formed in anticyclonic situations but is instead similar to the onion-shaped sounding found in wake low. The present analysis indicates that the observed elevated inversion resulted from the intrusion of stratospheric air associated with tropopause folding.

Heatwaves can affect human health and vegetation growth and bring about energy problems and socioeconomic damages, so the analysis and prediction of the heatwave is a crucial issue under a warming climate. This paper examines the production of STCI (Standard Temperature Condition Index) using ASOS (Automated Synoptic Observing System) in-situ observation data for the period of 1979-2020, and an STCI predictability assessment with an RF (Random Forest) model using ERA5 (ECMWF Reanalysis 5) meteorological variables. The accuracy was quite high with the MAE (Mean Absolute Error) of 0.365 and the CC (Correlation Coefficient) of 0.873, which corresponded to 7% to 10% difference for the range of STCI<1.5, and to 1% to 3% difference for the range of STCI>1.5, in terms of the probability density function. Also, we produced gridded maps for the summer STCI from 1979 to 2020 by utilizing the ERA5 raster data for the RF prediction model, which enables the spatial expansion of the ASOS point-based STCI to a continuous grid nationwide. The proposed method can be applied to forecasting of STCI by adopting future meteorological or climatic datasets.

Global warming due to the increase of greenhouse gases may significantly affect various aspects of the Earth’s environment and human life. In particular, the impacts of climate change on agriculture would be severe, leading to damages to crop yields. This paper examines the experimental prediction of rice yield in China using DNN (deep neural network) and climate model data for the period between 1979 and 2009. The DNN model built through the process of hyperparameter optimization can mitigate an overfitting problem and cope with outlier cases. Our model showed approximately 38.7% improved accuracy than the MLR (multiple linear regression) model, in terms of correlation coefficient with the yield statistics. We found that the diurnal temperature range and potential evapotranspiration were the critical factors for rice yield prediction. Our DNN model was also robust to extreme conditions such as drought in 2006 and 2007 in China, which showed its applicability to the future simulation of crop yields under climate change.

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.

본 연구에서는 한반도 주요 세 도시(서울, 대구, 부산)의 온도와 상대습도에 나타난 변화를 조사하였다. 기후 변화점 분석 결과, 세 지역 모두 거의 모든 경우에서 온도의 변화가 상대습도의 변화보다 더 선행하여 나타났으며 이로부터 온도의 변화가 상대습도의 변화를 야기시킬 수 있는 가능성이 있음을 알 수 있다. 또한 가장 뚜렷한 변화점이 나타나는 4월의 기후 변화에 초점을 맞추어, 다습-한랭 기간(1909~1962)과 건조-온난기간(1974~2008)의 기후 특징을 비교하였다. 세 도시에서 상대습도의 감소와 온도의 증가가 뚜렷하였으며,이러한 특징은 동아시아 영역 전반에 걸쳐 나타났다. 이원분산분석법을 바탕으로 상대습도 변화에 대한 온도와 수증기 효과를 평가하였다. 다습-한랭 기간에는 온도 효과보다 수증기 효과가 더 유의하게 나타났으며, 이는 상대습도의 변화에 대한 수증기 효과의 영향이 더 큼을 의미한다. 반면, 건조-온난 기간에는 수증기 효과뿐만 아니라 온도 효과도 유의하게 나타났다. 이러한 결과는 최근 상대습도의 변화에 온도가 중요한 역할을 할 수 있음을 의미한다. 온도와 수증기의 상호작용 효과는 두 기간 모두에서 유의하였다.

The present study intends to investigate the transient response of an atmosphere/ocean general circulation model to a gradual increase of atmospheric carbon dioxide. To detect the climatic change of the surface air temperature due to gradual increasing carbon dioxide for 100 years, two runs of GFDL CGCM for 1 % CO_2 run with increasing CO_2 and the control run with fixed CO_2 are compared. From results it is noted that the transient response of surface air temperature is more increased over the Northern Hemisphere than the Southern Hemisphere. However, in Northern Hemisphere the transient response of the surface air temperature due to the gradual increase of atmospheric carbon dioxide is slowly increased with latitudes and is clearly larger over continents than oceans. The annual global mean temperature is continuously increased with 0.03552 per one year with strong S/N ratio and distinguished from the natural variability. The time dependent response of the gradual increasing CO_2 has the strong seasonal variability with small change in summer and large change in winter, and the strong regionality in the Asian and the American continents. It has been suggested that the direct and the feedback processes in the climate systems should be investigated by the detailed sensitivity runs to get the meaningful estimate of the CO_2 forced variability.

Intraseasonal variability of the tropical convection over the Indian/western Pacific is studied using the Geostationary Meteorological Satellite high cloud amount. This study is directed to find the tropical-extratropical interaction in the frequency range of intraseasonal and interannual variabilities of the summer monsoon occured over the domain of 90E-171W and 49S-50N. Especially, in order to investigate the intraseasonal interaction of East Asia summer monsoon associated with the tropical convections in the high cloud amounts, the spatial and time structure of the intraseasonal oscillation for the movement and the evolution of the large-scale convections are studied. To describe the spatial and the time evolution, the extended empirical orthogonal function analysis is applied. The first mode may be considered to a normal structure, indicating that the strong convection band over 90E-120E is extended to eastward, but this mode was detected as a variable mode near Korea and Japan. The second, third and fourth modes were amplified with the intraseasonal variability during summer monsoon. It is found that the dominant intraseasonal mode of the tropical convection consists of the spatial changes over a broad period range centered around 40∼50days.