https://repository.kopri.re.kr/handle/201206/11549 Fri, 17 Apr 2026 01:05:28 GMT 2026-04-17T01:05:28Z https://repository.kopri.re.kr/handle/201206/13026 Title: Cold-Season Arctic Amplification Driven by Arctic Ocean-Mediated Seasonal Energy Transfer Authors: Chung, Eui-Seok; Ha, Kyung-Ja; Timmermann, Axel; Stuecker, Malte F.; Bodai, Tamas; Lee, Sang-Ki Abstract: The Arctic warming response to greenhouse gas forcing is substantially greater than the rest of the globe. It has been suggested that this phenomenon, commonly referred to as Arctic amplification, and its peak in boreal fall and winter result primarily from the lapse-rate feedback, which is associated with the vertical structure of tropospheric warming, rather than from the sea-ice albedo feedback, which operates mainly in summer. However, future climate model projections show consistently that an overall reduction of sea-ice in the Arctic region leads to a gradual weakening of Arctic amplification, thereby implying a key role for sea-ice albedo feedback. To resolve this apparent contradiction, we conduct a comprehensive analysis using atmosphere/ocean reanalysis datasets and a variety of climate model simulations. We show that the Arctic Ocean acts as a heat capacitor, storing anomalous heat resulting from the sea-ice loss during summer, which then gets released back into the atmosphere during fall and winter. Strong air-sea heat fluxes in fall/winter in sea-ice retreat regions in conjunction with a stably stratified lower troposphere lead to a surface-intensified warming/moistening, augmenting longwave feedback processes to further enhance the warming. The cold-season surface-intensified warming/moistening is found to virtually disappear if ocean-atmosphere-sea ice interactions are suppressed, demonstrating the importance of ice insulation effect and ocean heat uptake/release. These results strongly suggest that the warm-season ocean heat recharge and cold-season heat discharge link and integrate the warm and cold season feedbacks, and thereby effectively explain the predominance of the Arctic amplification in fall and winter. Mon, 01 Feb 2021 00:00:00 GMT https://repository.kopri.re.kr/handle/201206/13026 2021-02-01T00:00:00Z https://repository.kopri.re.kr/handle/201206/13030 Title: Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods Authors: Choi, Yonghan; Chen, Shu­-Hua; Huang, Chu-­Chun; Earl, Kenneth; Chen, Chih-­Ying; Schwartz, Craig S.; Matsui, Toshihisa Abstract: This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three­dimensional variational (3D­Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only),AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D­Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter. Wed, 01 Apr 2020 00:00:00 GMT https://repository.kopri.re.kr/handle/201206/13030 2020-04-01T00:00:00Z https://repository.kopri.re.kr/handle/201206/11981 Title: Dependence of sudden stratospheric warming type­transition on preceding North Atlantic Oscillation conditions Authors: Choi, Hyesun; Choi, Wookap; Kim, Seong-Joong; Kim, Baek-Min Abstract: Most sudden stratospheric warming (SSW) events initiate with their centers being displaced from the pole. Some retain their displaced form until termination but some split into two vortices during their course. Here, we show that existence of a transition during the course of the SSW life cycle can be attributable to the condition of North Atlantic Oscillation (NAO) preceding before onset: Positive NAO favors SSW of displacement type with no transition while negative NAO favors the displacementsplit type. We show that, in positive NAO precondition, vertical flux of wave activity immediately before onset is mostly contributed only by wavenumber 1 component, which contrasts with the relatively stronger contribution of wavenumber 2 in negative NAO precondition. Whole Atmosphere Community Climate Model (WACCM) simulation results are also consistent with the observational findings. Therefore, NAO can be regarded as a useful precursor for determining the type of forthcoming SSW events. Sun, 01 Mar 2020 00:00:00 GMT https://repository.kopri.re.kr/handle/201206/11981 2020-03-01T00:00:00Z https://repository.kopri.re.kr/handle/201206/13031 Title: Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES Authors: Cho, Heeje; Jun, Sang-Yoon; Ho, Chang­Hoi; McFarquhar, Greg Abstract: Arctic cloud simulations of the polar-optimized version of the Weather Research and Forecasting model (Polar WRF) were compared with retrievals using the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation measurements. For the period from 1 December 2015 to 31 January 2016, a series of 24-to 48-hr simulations initialized daily at 00 UTC were examined. In particular, two cloud microphysics schemes, the Morrison double moment and the WRF single-moment 6-class (WSM6), were tested. The modeled cloud top heights had a correlation coefficient (r) of 0.69-0.72 with those from satellite retrievals, and a mean bias of less than 400 m. For the mean ice water content profile and mixed-phase cloud occurrence, the Morrison scheme's clouds were in better agreement with satellite retrievals than the WSM6. However, the use of the Morrison scheme resulted in underestimates of outgoing longwave radiation by -11.7 W m(-2) compared to satellite observations. The bias was reduced to -0.4 W m(-2) with the WSM6 which produced a stronger precipitation rate (by 10%) resulting in a drier and less-cloudy atmosphere. This also leads to the 7-Wm(-2) mean difference in the surface downward longwave radiation (DLR) between the schemes, which is large enough to explain the spread of the Arctic DLR in the current climate models. However, as the temporal variation in DLR showed good agreement with ground observations (r: 0.68-0.92), it is concluded that the Polar WRF can be useful for studying cloud effects on the winter Arctic surface climate. Plain Language Summary Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate. Mon, 27 Jan 2020 00:00:00 GMT https://repository.kopri.re.kr/handle/201206/13031 2020-01-27T00:00:00Z