• Atmosphere
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• v.25 no.1
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• pp.67-83
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• 2015

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

• Membrane and Water Treatment
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• v.3 no.4
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• pp.253-266
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• 2012

In this work, the effect of hybrid salts precipitation-nanofiltration (SP-NF) process on the scale deposits in thermal and membrane desalination processes has been studied. The analysis was carried out to study the scale formation from the Arabian Gulf seawater in MSF and RO reference processes by changing the percentage of pretreatment from 0 to 100%. Four different SP-NF configurations were suggested. A targeted Top Brine Temperature (TBT) of $130^{\circ}C$ may be achieved if 30% portion is pretreated by SP and/or NF processes. As a rule of thumb, each 1% pretreatment portion increases the reference TBT of $115^{\circ}C$ by $0.6^{\circ}C$. For both MSF and RO, parallel pretreatment of certain percentage of the feed by SP and the rest by NF, showed the lowest scale values. The case showed the best values for sulfate scale prevention and the highest values of increasing the monovalent ions relative to the divalent scale forming ions. Sulfate scale is significant in MSF process while carbonate scale is significant in RO. Salt precipitation was suggested because it is less costly than nanofiltration, but nanofiltration was used here because it is efficient in sulfate ions removal.

• Atmosphere
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• v.18 no.2
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• pp.83-95
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• 2008

In this study we have investigated the preceding eighteen large-scale climate indices with a lead time from zero to twelve months that have an influence on the variability of temperature and precipitation in Korea in order to understand which climate indices are overall available as predictors for long-range forecasting. We also have studied the dynamic link between preceding large-scale climate indices and regional climate using singular value decomposition analysis (SVDA) and correlation analysis (CA). Based on the coupled mode between large-scale circulation and regional climate, and correlation pattern between the preceding large-scale climate indices and large-scale circulation, the level of significance on climate indices as a predictor for monthly mean temperature and precipitation was evaluated for 5 and 1% level.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.141-153
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• 2012

In this study, we estimated probable precipitation amounts at the target year (2020, 2030, 2040) of 55 weather stations in Korea using the 24 hour annual maximum precipitation data from 1973 through 2009 which should be useful for management of agricultural reservoirs. Not only trend tests but also non-stationary tests were performed and non-stationary frequency analysis were conducted to all of 55 sites. Gumbel distribution was chosen and probability weighted moment method was used to estimate model parameters. The behavior of the mean of extreme precipitation data, scale parameter, and location parameter were analyzed. The probable precipitation amount at the target year was estimated by a non-stationary frequency analysis using the linear regression analysis for the mean of extreme precipitation data, scale parameter, and location parameter. Overall results demonstrated that the probable precipitation amounts using the non-stationary frequency analysis were overestimated. There were large increase of the probable precipitation amounts of middle part of Korea and decrease at several sites in Southern part. The non-stationary frequency analysis using a linear model should be applicable to relatively short projection periods.

• Atmosphere
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• v.32 no.1
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• pp.1-15
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• 2022

Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• The Korean Journal of Quaternary Research
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• v.19 no.2
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• pp.74-79
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• 2005

Recently, several attempts have been made to provide reasonable information on unusual severe weather phenomena such as tolerant heavy rains and very wild typhoons. Quantitative precipitation forecasts and probabilistic quantitative precipitation forecasts (QPFs and PQPFs, respectively) might be one of the most promising methodologies for early warning on the flesh floods because those diagnostic precipitation models require less computational resources than fine-mesh full-dynamics non-hydrostatic mesoscale model. The diagnostic rainfall model used in this study is the named QPM(Quantitative Precipitation Model), which calculates the rainfall by considering the effect of small-scale topography which is not treated in the mesoscale model. We examine the capability of probabilistic diagnostic rainfall model in terms of how well represented the observed several rainfall events and what is the most optimistic resolution of the mesoscale model in which diagnostic rainfall model is nested. Also, we examine the integration time to provide reasonable fine-mesh rainfall information. When we apply this QPM directly to 27 km mesh meso-scale model (called as M27-Q3), it takes about 15 min. while it takes about 87 min. to get the same resolution precipitation information with full dynamic downscaling method (called M27-9-3). The quality of precipitation forecast by M27-Q3 is quite comparable with the results of M27-9-3 with reasonable threshold value for precipitation. Based on a series of examination we may conclude that the proosed QPM has a capability to provide fine-mesh rainfall information in terms of time and accuracy compared to full dynamical fine-mesh meso-scale model.

• Atmosphere
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• v.22 no.4
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• pp.437-447
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• 2012

There is still large uncertainty in estimating aerosol indirect effect despite ever-escalating efforts and virtually exponential increase in published studies concerning aerosol-cloud-precipitation interactions (CAPI). Probably most uncertainty comes from a wide range of observational scales and different platforms inappropriately used, and inherent complex chains of CAPI. Therefore, well-designed field campaigns and data analysis are required to address how to attribute aerosol signals along with clouds and precipitation to the microphysical effects of aerosols. Basically, aerosol influences cloud properties at the microphysical scales, "process scale", but observations are generally made of bulk properties over a various range of temporal and spatial resolutions, "analysis scale" (McComiskey & Feingold, 2012). In the most studies, measures made within the wide range of scales are erroneously treated as equivalent, probably resulting in a large uncertainty in associated with CAPI. Therefore, issues associated with the disparities of the observational resolution particular to CAPI are briefly discussed. In addition, the dependence of CAPI on the cloud environment such as stability and adiabaticity, and observation characteristics with varying situations of CAPI are also addressed together with observation framework optimally designed for the Korean situation. Properly designed and observation-based CAPI studies will likely continue to accumulate new evidences of CAPI, to further help understand its fundamental mechanism, and finally to develop improved parameterization for cloud-resolving models and large scale models.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.735-743
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• 2012

Since the CBD(Conservation on Biological Diversity)'s 10th Conference of the Parties adopted the protocol on access to genetic resources and benefit sharing in Nagoya 2010, the importance of endangered species studies such as habitat distribution, protection and management have been more emerged. Corylopsis coreana, an endangered species in Korea, was isolated nationally and has been damaged by anthropogenic factors. In this paper, we identified the factors affecting C. coreana habitat at the national scale and regional scale using National Survey of Natural Environment and predicted the distribution of C. coreana. Annual precipitation, precipitation of wettest quarter, temperature seasonality and Digital Elevation Model(DEM) were derived as important factors at the national scale, and precipitation of wettest quarter, DEM and solar radiation on spring were identified as important factors at regional scale. Colylopsis distribution was affected by an effect of climate significantly at the national scale, and by additionally the microclimate and topography at regional scale. These findings will be used as the basis on habitat conservation and restoration plan and climate change.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.655-665
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• 2023

In this study, unit hydrographs are calculated when precipitations of 10 scales instantaneously occurs in a virtual watershed with a constant slope and roughness. Then, the relationship between the peak flow rate and the peak occurrence time of the unit hydrograph was calculated for the precipitation scale, respectively. At this time, the virtual watershed simplified with a rhombic shape, a constant slope, and a flow condition with a certain roughness was applied instead of a natural watershed in order to understand the effect the precipitation scale has on the peak value of the unit hydrograph. And it was assumed that the precipitation in the basin was effective rainfall and the runoff was direct runoff, and the runoff flowed in a straight, uniform flow from the drop point to the outlet. The relationship between the peak flow and the peak occurrence time of the unit hydrograph was calculated in the case of 10 types of precipitation scales of 10 mm, 40 mm, 90 mm, 160 mm, 250 mm, 360 mm, 640 mm, 1,000 mm, 1,210 mm, and 1,690 mm of effective precipitation. A noteworthy achievement of this study is that, even without the storage effect of the watershed, as the scale of precipitation increases, the depth of runoff increases, so the flow rate in the watershed increases and the distance per unit time increases, so the peak flow rate increases and the peak occurrence time increases. This is a nonlinear characteristic of watershed runoff.