The Improvement of Forecast Accuracy of the Unified Model at KMA by Using an Optimized Set of Physical Options

Lee, Juwon; Han, Sang-Ok; Chung, Kwan-Young

doi:10.14191/atmos.2012.22.3.345

Cited by 2 publications

(1 citation statement)

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“…In May 2010, the Korea Meteorological Administration (KMA) introduced the Unified Model (UM) and associated data assimilation systems developed by the UKMO [13]. However, to our knowledge, since the KMA UM has been operationally used, no validation regarding its accuracy was published.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Temperature and Humidity Profiles of Unified Model and ECMWF Analyses Using GRUAN Radiosonde Observations

et al. 2016

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Temperature and water vapor profiles from the Korea Meteorological Administration (KMA) and the United Kingdom Met Office (UKMO) Unified Model (UM) data assimilation systems and from reanalysis fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) were assessed using collocated radiosonde observations from the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) for January-December 2012. The motivation was to examine the overall performance of data assimilation outputs. The difference statistics of the collocated model outputs versus the radiosonde observations indicated a good agreement for the temperature, amongst datasets, while less agreement was found for the relative humidity. A comparison of the UM outputs from the UKMO and KMA revealed that they are similar to each other. The introduction of the new version of UM into the KMA in May 2012 resulted in an improved analysis performance, particularly for the moisture field. On the other hand, ECMWF reanalysis data showed slightly reduced performance for relative humidity compared with the UM, with a significant humid bias in the upper troposphere. ECMWF reanalysis temperature fields showed nearly the same performance as the two UM analyses. The root mean square differences (RMSDs) of the relative humidity for the three models were larger for more humid conditions, suggesting that humidity forecasts are less reliable under these conditions.

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Section: Introductionmentioning

confidence: 99%