https://repository.kopri.re.kr/handle/201206/15847 2026-04-21T05:24:56Z 2026-04-21T05:24:56Z Mo, Ahra Park, Keyhong Kim Tae-Wook Hahm Doshik Choi, Jung-Ok Geum, Sohyeon Jung, Jinyoung Yang, Eun Jin https://repository.kopri.re.kr/handle/201206/16310 2025-10-31T06:07:58Z 2024-01-01T00:00:00Z

Title: pCO2 variation in ice-covered regions of the Arctic Ocean from the summer 2022 observation Authors: Mo, Ahra; Park, Keyhong; Kim Tae-Wook; Hahm Doshik; Choi, Jung-Ok; Geum, Sohyeon; Jung, Jinyoung; Yang, Eun Jin Abstract: To enhance our understanding of the carbon cycle in the Arctic Ocean, comprehensive observational data are crucial, including measurements from the underlying ice water. This study proposed a practical method for calibrating pCO(2) sensor using measured dissolved inorganic carbon and total alkalinity. Our findings suggested the minimum number of bottle samples needed for calibration to ensure 1% accuracy. Additionally, we identified the significant role of a decrease in dissolved inorganic carbon due to photosynthesis and the increase in buffer capacity of the seawater from the release of excess alkalinity by sea ice in regulating pCO(2). The mean air-sea CO2 fluxes were -48.9 +/- 44.6, -7.3 +/- 14.6, and -1.4 +/- 2.8 mmol m(-2) d(-1) in the southern Chukchi Sea, northern Chukchi Sea, and northern East Siberian Sea, respectively. We found a robust negative correlation between the flux and sea ice concentration in the Arctic Sea ice regions.

2024-01-01T00:00:00Z Lee Gyu-Ri Woo Sung-Ho Baek Eun-Hyuk Kim, Joo-Hong Kim Baek-Min Jeong Jee-Hoon https://repository.kopri.re.kr/handle/201206/16376 2025-11-06T08:07:16Z 2024-01-01T00:00:00Z

Title: Statistical seasonal prediction of Arctic sea ice concentration based on spatiotemporal anomaly persistent method Authors: Lee Gyu-Ri; Woo Sung-Ho; Baek Eun-Hyuk; Kim, Joo-Hong; Kim Baek-Min; Jeong Jee-Hoon Abstract: Accurate prediction of Arctic sea ice is crucial for high-latitude and even mid-latitude climate prediction. It significantly affects atmospheric circulation, the environment, ecology, and maritime transport. This study developed a statistical prediction model to predict monthly Arctic sea ice concentration (SIC) for up to one year based on the season-reliant empirical orthogonal functions (SEOFs) technique. Its prediction skill was compared with that of a dynamical prediction model. The spatiotemporal pattern of sea ice anomalies, which exhibit strong seasonality and are maintained for a significant period above the seasonal time scale by atmosphere-ocean interactions, was extracted using SEOFs. A prediction model was constructed by extrapolating from the recent anomalous state of sea ice to predict the future. Experimental retrospective predictions with monthly time resolution for 1982-2021 were performed to validate the prediction skill of Arctic SIC and areal extent. Statistically significant prediction skills were achieved over several months, even up to six months, exceeding the skill of the dynamical model.

2024-01-01T00:00:00Z Choi, Yonghan Kim, Joo-Hong Jun, Sang-Yoon Choi, Taejin Zhang Xiangdong https://repository.kopri.re.kr/handle/201206/16428 2025-11-06T08:23:19Z 2024-01-01T00:00:00Z

Title: Multi-year assessment of the impact of ship-borne radiosonde observations on polar WRF forecasts in the Arctic Authors: Choi, Yonghan; Kim, Joo-Hong; Jun, Sang-Yoon; Choi, Taejin; Zhang Xiangdong Abstract: To compensate for the lack of conventional observations over the Arctic Ocean, ship-borne radiosonde observations have been regularly carried out during summer Arctic expeditions and the observed data have been broadcast via the global telecommunication system since 2017. With these data obtained over the data-sparse Arctic Ocean, observing system experiments were carried out using a polar-optimized version of the Weather Research and Forecasting (WRF) model and the WRF Data Assimilation (WRFDA) system to investigate their effects on analyses and forecasts over the Arctic. The results of verification against reanalysis data reveal: (1) DA effects on analyses and forecasts; (2) the reason for the year-to-year variability of DA effects; and (3) the possible role of upper-level potential vorticity in delayed DA effects. The overall assimilation effects of the extra data on the analyses and forecasts over the Arctic are positive. Initially, the DA effects are the most apparent in the temperature variables in the middle/lower troposphere, which spread to the wind variables in the upper troposphere. The effects decrease with time but reappear after approximately 120 h, even in the 240-h forecasts. The effects on forecasts vary depending on the proximity of the radiosonde observation locations to the high synoptic variability. The upper-level potential vorticity is known to play an important role in the development of Arctic cyclones, and it is suggested as a possible explanation for the delayed DA effects after about 120 h.

2024-01-01T00:00:00Z Jahfer Sharif Ha Kyung-Ja Chung, Eui-Seok Franzke Christian L. E. Sharma Sahil https://repository.kopri.re.kr/handle/201206/16431 2025-11-06T08:23:48Z 2024-01-01T00:00:00Z

Title: Unveiling the role of tropical Pacific on the emergence of ice-free Arctic projections Authors: Jahfer Sharif; Ha Kyung-Ja; Chung, Eui-Seok; Franzke Christian L. E.; Sharma Sahil Abstract: The observed sea ice concentration (SIC) over the Arctic has receded substantially in recent decades, and future model projections predict a seasonally ice-free Arctic in the second half of this century. Nevertheless, the impact of the Pacific on Arctic sea ice projections has yet to receive much attention. Observations show that summertime Arctic SIC growth events are related to the weakening of the Aleutian low and cooling events over the equatorial Pacific, and vice versa. We demonstrate that under various Coupled Model Intercomparison Project Phase 6 projections, the models in which the impact of El Nino-driven SIC loss is significantly higher than the La Nina-related SIC growth tend to turn seasonally ice-free by about 10-20 years ahead of the ensemble mean under high-emission future scenarios. We show how the non-linear impact of the El Nino Southern Oscillation (ENSO) on Arctic SIC resulted in a faster decline of summertime sea ice. The ENSO-related SIC changes in the multi-model ensemble mean of Arctic SIC are considerably lower than the internal variability and anthropogenic-driven changes. However, the asymmetric interannual ENSO effects over several decades and the resultant changes in surface heat fluxes over the Arctic lead to significant differences in the timing of sea ice extinction. Our results suggest that climate models must capture the realistic tropical Pacific-Arctic teleconnection to better predict the long-term evolution of the Arctic climate.

2024-01-01T00:00:00Z