Role of convective parameterization in simulations of heavy precipitation systems at grey-zone resolutions — case studies

We have investigated the role of convective parameterization in simulations of heavy precipitation systems at grey-zone (2–10 km) resolutions using an approach similar to that used in “observing system simulation experiment”. Simulations with a 1-km grid serve as benchmark simulations. The impacts of convective parameterization at greyzone resolutions (i.e., 3, 6, and 9 km) are then investigated. This study considers two heavy precipitation systems including one associated with a mesoscale cyclone generated over the Shandong Peninsula on 24–25 July 1991, and the other associated with a cloud cluster occurred on 15–16 July 2009. The present study indicates that convective parameterization does not affect much the simulations of the two heavy precipitation systems with 3-km grid size. However, it significantly affects simulations for grid sizes of 6 and 9 km. Simulations with the Kain-Fritsch scheme produce deficiencies such as relatively small heavy rainfall area, smaller maximum precipitation rate, wider area of weak precipitation, etc. Simulations without convective parameterization have also some negative effects such as the overprediction of area-averaged precipitation rate and others. A modified trigger function in the Kain-Fritsch scheme is found to improve the simulations of the heavy precipitation systems over the Korean Peninsula by reducing excessive trigger of convection, especially for simulations with 6- and 9- km grids.     

Spin-up behavior of soil moisture content over East Asia in a land surface model

This study presents an investigation of the spin-up behavior of soil moisture content (SMC) and evapotranspiration (ET) in an offline Noah land surface model (LSM) for East Asia, focusing on its interplay with the Asian monsoon. The set of 5-year recursive runs is conducted to properly assess the spin-up behavior of land surface processes and consists of simulations initialized with (1) a spatially uniform soil moisture, (2) NCEP GDAS soil moisture data, and (3) ECMWF ERA-Interim soil moisture data. Each run starts either after or before the summer monsoon. Initial SMCs from GDAS and ERA-Interim data significantly deviate from the equilibrium state (spin-up state) with the given input forcing even though the same equilibrium is reached within 3-year spin-up time, indicating that spin-up of land surface process is necessary. SMC reaches the equilibrium much quickly when (1) the consistent LSMs have been used in the prediction and analysis systems and (2) the spin-up simulation starts before the onset of heavy rainfall events during summer monsoon. For an area with heavy monsoon rainfall, the total column SMC and ET spin up quickly. The spin-up time over dry land is about 2–3?years, but for monsoon rainfall area decreases dramatically to about 3?months if the spin-up run starts just before the onset of monsoon. Further scrutiny shows that the spin-up time is well correlated with evaporative fraction given by the ratio between the latent heat flux and the available energy at the land surface.     

Formation and evolution of mesoscale convective systems that brought the heavy rainfall over Seoul on September 21, 2010

An investigation has been carried out using observational data and a numerical model to explain the formation and development of heavy precipitation systems on September 21, 2010. These systems were responsible for heavy rainfall over the middle Korean peninsula, with a maximum 24-h rainfall amount greater than 290 mm in the Seoul metropolitan area. Both observational analysis and a numerical simulation indicate that an important starting condition for this heavy rainfall event is the presence of a pressure trough over the Shandong peninsula and the Yellow Sea. Convective cells formed in the early morning over this trough area, grew into larger systems as they moved eastward, and induced the formation of a meso low over the Yellow Sea around 0000 UTC on September 21, 2010. A stationary front with significant vertical circulation developed in response to the deformation of flow associated with the meso low. In the meantime, multicell-type convective systems continuously developed and moved along the front. These storms developed further and produced heavy rainfall over the middle Korean peninsula, which includes the Seoul metropolitan area. According to observations, the band structure appeared to change after 0700 UTC as a narrow convection band developed over the sea, upstream of the existing band of multicell storms. Numerical simulation showed a similar transition. However, it failed to reproduce the stationary behavior of the observed band.     

Evaluation of Simulated CO_2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013

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).