• Journal of Wetlands Research
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• v.19 no.3
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• pp.366-374
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• 2017

The objective of this study is to explore the applicability of very short-range-forecast rainfall for the early warning of mud-debris flows. An artificial neural network was applied to use the very short-range-forecast rainfall data. The neural network is learned by using the relationship between the radar and the AWS, and forecasted rainfall is estimated by replacing the radar rainfall with the MAPLE data as the very short-range-forecast rainfall data. The applicability of forecasted rainfall by the MAPLE was compared with the AWS rainfall at the test-bed using the rainfall criteria for cumulative rainfall of 6hr, 12hr, and 24hr respectively. As a result, it was confirmed that forecasted rainfall using the MAPLE can be issued prior to the AWS warning.

• Atmosphere
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• v.25 no.4
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• pp.623-637
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• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.17-28
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• 2011

This study applied the Kalman Filter for real-time forecasting the G/R (ground rain gauge rainfall/radar rainfall) ratio to correct the mean field bias of the very-short-range-forecast (VSRF) rainfall. The MAPLE-forecasted rainfall was used as the VSRF rainfall, also the methodology for deciding the G/R ratio was improved by evaluating the change of G/R ratio characteristics depending on the threshold and accumulation time. This analysis was done for the inland, mountain, and coastal regions, separately, for their comparison. As the results, more stable G/R ratio could be estimated by applying the threshold and accumulation time, whose forecasting accuracy could also be secured. The accuracy of the corrected rainfall forecasting by the forecasted G/R ratio was the best in the inland region but the worst in the coastal region.

• Journal of Korea Water Resources Association
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• v.39 no.3 s.164
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• pp.215-226
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• 2006

In this study, we performed verification of VSRF (Very Short Range Forecast of precipitation) model and application of NWSPC (National Weather Service PC) rainfall-runoff model in Kyoungan-chun basin. We used two methods for verification of VSRF model. The first method is a meteorological verification that evaluates the special quality feature for rain amount between AWS and VSRF model over Kyoungan-chun basin, while second method is a hydrological verification that compares the calculated Mean Area Precipitation (MAP) between AWS and VSRF Quantitatively. This study examines the usefulness of VSRF precipitation forecasting model data in NWSPC hydrological model. As a result, correlation coefficient is over 0.6 within 3 hour lead time. It represents that the forecast results from VSRF are useful for water resources application.

• Journal of the Korean earth science society
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• v.22 no.3
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• pp.186-194
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• 2001

The operational meso-scale short range NWP system was developed for Cheju Regional Meteorological Office located at Cheju island, Korea. The Central Meteorological Service Center, KMA has reported the information on numerical weather prediction every 12 hours. But this information is not enough to determine the detail forecast for the regional meteorological office because the terrain of the Korean peninsula is very complex and the resolution of the numerical model provided by KMA headquarter is too coarse to resolve the local severe weather system such as heavy rainfall. LAPS and MM5 models were chosen for three-dimentional data assimilation and numerical weather prediction tools respectively. LAPS was designed to provide the initial data to all regional numerical prediction models including MM5. Synoptic observational data from GTS, satellite brightness temperature data from GMS-5 and the composite reflectivity data from 5 radar sites were used in the LAPS data assimilation for producing the initial data. MM5 was performed on PC-cluster based on 16 pentium CPUs which was one of the cheapest distributed parallel computer in these days. We named this system as Halla Short Range Prediction System (HSRPS). HSRPS was verified by heavy rainfall case in July 9, 1999, it showed that HSRPS well resolved local severe weather which was not simulated by 30 km MM5/KMA. Especially, the structure of rainfall amount was very close to the corresponding observation. HSRPS will be operating every 6 hours in the Cheju Regional Meteorological Office from April 2000.

• Atmosphere
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• v.22 no.1
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• pp.29-45
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• 2012

An unusual autumn storm developed rapidly in the western part of the East sea on the early morning of 23 October 2006. This storm produced a record-breaking heavy rain and strong wind in the northern and middle part of the Yeong-dong region; 24-h rainfall of 304 mm over Gangneung and wind speed exceeding 63.7 m $s^{-1}$ over Sokcho. In this study, MTSAT-1R (Multi-fuctional Transport Satellite) water vapor and infrared channel imagery are examined to find out some features which are dynamically associated with the development of the storm. These features may be the precursor signals of the rapidly developing storm and can be employed for very short range forecast and nowcasting of severe storm. The satellite features are summarized: 1) MTSAT-1R Water Vapor imagery exhibited that distinct dark region develops over the Yellow sea at about 12 hours before the occurrence of maximum rainfall about 1100 KST on 23 October 2006. After then, it changes gradually into dry intrusion. This dark region in the water vapor image is closely related with the positive anomaly in 500 hPa Potential Vorticity field. 2) In the Infrared imagery, low stratus (brightness temperature: $0{\sim}5^{\circ}C$) develops from near Bo-Hai bay and Shanfung peninsula and then dissipates partially on the western coast of Korean peninsula. These features are found at 10~12 hours before the maximum rainfall occurrence, which are associated with the cold and warm advection in the lower troposphere. 3) The IR imagery reveals that two convective cloud cells (brightness temperature below $-50^{\circ}C$) merge each other and after merging it grows up rapidly over the western part of East sea at about 5 hours before the maximum rainfall occurrence. These features remind that there must be the upward flow in the upper troposphere and the low-layer convergence over the same region of East sea. The time of maximum growth of the convective cloud agrees well with the time of the maximum rainfall.