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http://dx.doi.org/10.14191/Atmos.2018.28.4.369

Verification of Planetary Boundary Layer Height for Local Data Assimilation and Prediction System (LDAPS) Using the Winter Season Intensive Observation Data during ICE-POP 2018  

In, So-Ra (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Nam, Hyoung-Gu (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Lee, Jin-Hwa (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Park, Chang-Geun (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Shim, Jae-Kwan (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Kim, Baek-Jo (Observation and Forecast Research Division, National Institute of Meteorological Sciences, KMA)
Publication Information
Atmosphere / v.28, no.4, 2018 , pp. 369-382 More about this Journal
Abstract
Planetary boundary layer height (PBLH), produced by the Local Data Assimilation and Prediction System (LDAPS), was verified using RawinSonde (RS) data obtained from observation at Daegwallyeong (DGW) and Sokcho (SCW) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). The PBLH was calculated using RS data by applying the bulk Richardson number and the parcel method. This calculated PBLH was then compared to the values produced by LDAPS. The PBLH simulations for DGW and SCW were generally underestimation. However, the PBLH was an overestimation from surface to 200 m and 450 m at DGW and SCW, respectively; this result of model's failure to correctly simulate the Surface Boundary Layer (SBL) and the Mixing Layer (ML) as the PBLH. When the accuracy of the PBLH simulation is low, large errors are seen in the mid- and low-level humidity. The highest frequencies of Planetary boundary layer (PBL) types, calculated by the LDAPS at DGW and SCW, were presented as types Ι and II, respectively. Analysis of meteorological factors according to the PBL types indicate that the PBLH of the existing stratocumulus were overestimated when the mid- and low-level humidity errors were large. If the instabilities of the surface and vertical mixing into clouds are considered important factors affecting the estimation of PBLH into model, then mid- and low-level humidity should also be considered important factors influencing PBLH simulation performance.
Keywords
PBLH; rawinsonde; LDAPS; low-and mid-level humidity; ICE-POP 2018;
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