The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and tempora...The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).展开更多
基金supported by the Korea Meteorological Administration Research and Development Program "Research and Development for KMA Weather, and Earth system Services-Development and Assessment of AR6 Climate Change Scenarios" under Grant (KMA2018-00321)
文摘The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).
