Jun Kyung Kay

Effect of doubling the ensemble size on the performance of ensemble prediction in the warm season using MOGREPS implemented at the KMA

Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA), the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated. Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF), ensemble size is closely related to the efficiency of the ensemble prediction system. Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA. The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009. Several statistical verification scores were used to measure the accuracy, reliability, and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts. Even though the results were not significant, the accuracy of ensemble prediction improved slightly as ensemble size increased, especially for longer forecast times in the Northern Hemisphere. While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased, inconsistent results were obtained for the scores assessing the reliability of ensemble prediction. The overall performance of ensemble prediction in terms of accuracy, resolution, and reliability increased slightly with ensemble size, especially for longer forecast times.

Characteristics of Initial Perturbations in the Ensemble Prediction System of the Korea Meteorological Administration

AbstractIn this study, the initial ensemble perturbation characteristics of the new Korea Meteorological Administration (KMA) ensemble prediction system (EPS), a version of the Met Office Global and Regional Ensemble Prediction System, were analyzed over two periods: from 1 June to 31 August 2011, and from 1 December 2011 to 29 February 2012. The KMA EPS generated the initial perturbations using the ensemble transform Kalman filter (ETKF). The observation effect was reflected in both the transform matrix and the inflation factor of the ETKF; it reduced (increased) uncertainties in the initial perturbations in regions with dense observations via the transform matrix (inflation factor). The reduction in uncertainties is generally governed by the transform matrix but locally modulated by the inflation factor. The sea ice significantly affects the initial perturbations near the lower boundary layer. The large perturbation energy in the lower stratosphere of the tropics was related to the dominant zonal wind, ...

Effect of Observation Network Design on Meteorological Forecasts of Asian Dust Events

AbstractTo improve the prediction of Asian dust events on the Korean Peninsula, meteorological fields must be accurately predicted because dust transport models require them as input. Accurate meteorological forecasts could be obtained by integrating accurate initial conditions obtained from data assimilation processes in numerical weather prediction. In data assimilation, selecting the appropriate observation location is important to ensure that the initial conditions represent the surrounding meteorological flow. To investigate the effect of observation network configuration on meteorological forecasts during Asian dust events on the Korean Peninsula, observing system simulation experiments using several simulated and real observation networks were tested with the Weather Research and Forecasting modeling system for 11 Asian dust events affecting the Korean Peninsula during a recent 6-yr period. First, the characteristics of randomly fixed and adaptively selected observation networks were investigated w...

Statistical adjoint sensitivity distributions of meteorological forecast errors of Asian dust transport events in Korea

ABSTRACT The sensitivities of meteorological forecast errors associated with Asian dust transport events to changes in the initial state were evaluated for 46 occurrences that affected the Korean Peninsula from 2005 to 2010. Adjoint-based sensitivities were used to determine these sensitivities. Sensitive regions were located primarily over two regions upstream from the Korean Peninsula: the northern source region, including areas of Mongolia and northern China, and the Tibetan Plateau. Depending on transport trajectories, month, and year, the sensitive regions were located over either the northern source regions or the Tibetan Plateau. That is, the Asian dust forecast in Korea was found to be sensitive to the meteorological fields over the northern source regions, but also those over the Tibetan Plateau even though the latter is not a dust source region or an upstream area according to the transport trajectories. Employing additional observations at existing instrumentation sites or developing new observational sites in both sensitive regions could be beneficial in reducing the atmospheric circulation forecast errors in East Asia, thus improving the accuracy of transport forecasts of Asian dust events affecting the Korean Peninsula.