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http://dx.doi.org/10.14191/Atmos.2022.32.2.087

The KMA Global Seasonal forecasting system (GloSea6) - Part 2: Climatological Mean Bias Characteristics  

Hyun, Yu-Kyung (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Lee, Johan (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Shin, Beomcheol (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Choi, Yuna (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Kim, Ji-Yeong (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Lee, Sang-Min (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Ji, Hee-Sook (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Boo, Kyung-On (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Lim, Somin (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Kim, Hyeri (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Ryu, Young (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Park, Yeon-Hee (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Park, Hyeong-Sik (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Choo, Sung-Ho (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Hyun, Seung-Hwon (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Hwang, Seung-On (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Publication Information
Atmosphere / v.32, no.2, 2022 , pp. 87-101 More about this Journal
Abstract
In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.
Keywords
Climate prediction system; GloSea6; Seasonal forecasting; Hindcast; Bias;
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