• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.135-143
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• 2020

Shortwave radiation and sunshine hours (SHOUR) are important variables having many applications, including crop growth. However, observational data for these variables have low horizontal resolution, rendering its application to related research and decision making on f arming practices challenging. In the present study, hourly solar radiation data were physically generated using the Land-Atmosphere Modeling Package (LAMP) at the National Center f or Agro-Meteorology, and then daily SHOUR fields were calculated through statistical downscaling. After data quality evaluation, including case studies, the SHOUR data were added to the existing publically accessible LAMP daily database. The LAMP daily dataset, newly updated with SHOUR, has been provided operationally as input data to the "Gyeonggi-do Agricultural Drought Prediction System," which predicts agricultural weather disasters and field crop growth status.

• Atmosphere
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• v.29 no.2
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• pp.227-239
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• 2019

This paper reviews various bulk-type cloud microphysics parameterizations (BCMPs). BCMP, predicting the moments of size distribution of hydrometeors, parameterizes the grid-resolved cloud and precipitation processes in atmospheric models. The generalized gamma distribution is mainly applied to represent the hydrometeors size distribution in BCMPs. BCMP can be divided in three different methods such as single-moment, double-moment, and triple-moment approaches depending on the number of prognostic variables. Single-moment approach only predicts the hydrometeors mixing ratio. Double-moment approach predicts not only the hydrometeors mixing ratio but also the hydrometeors number concentration. Triple-moment approach predicts the dispersion parameter of hydrometeors size distribution through the prognostic reflectivity, together with the number concentrations and mixing ratios of hydrometeors. Triple-moment approach is the most time expensive method because it has the most number of prognostic variables. However, this approach can allow more flexibility in representing hydrometeors size distribution relative to single-moment and double-moment approaches. At the early stage of the development of BMCPs, warm rain processes were only included. Ice-phase categories such as cloud ice, snow, graupel, and hail were included in BCMPs with prescribed properties for densities and sedimentation velocities of ice-phase hydrometeors since 1980s. Recently, to avoid fixed properties for ice-phase hydrometeors and ad-hoc category conversion, the new approach was proposed in which rimed ice and deposition ice mixing ratios are predicted with total ice number concentration and volume.

• Atmosphere
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• v.34 no.2
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Water for future
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• v.26 no.2
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• pp.99-105
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• 1993

A practical flood forecasting model(FFM) is suggested. The output of the model is the results which the initial condition of meteorological parameters and soil moisture are projected on the future. The physically based station model for rainfall forecasting(RF) and the storage function model for runoff prediction(RP) are adopted respectively. Input variables for FFM are air temperature, pressure, and dew-point temperature at the ground level and the flow at the rising limb(FRL). The constant parameters for FFM are average of optimum values which the past storm events have. Also loss rate of rainfall can predicted by FRL.

• Journal of Environmental Science International
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• v.6 no.5
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• pp.425-435
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• 1997

One-dimensional thermodynamic mixed layer model to stimulate variations of meteorological variables wish the planetary boundary layer has been developed In this study. This model consists of 2 prognostic equations, which can predict the variations of potential temperature and mixing ratio and several diagnostic equations. Physics within the surface and mixed layers has been considered seperately in the model. For the variations of the model, Its result has been analysed and compared with observated data over Ole Dukyang Bay for one day, July 23, 1992. The simulated height of mixed layer is comparable to the observation and the variations of temperature and mixing ratio in the mixed layer are also reasonably simulated. Those Imply that the model responds appropriately with given boundary conditions In sprite of Its simplilfied assumptions applied to the model and insufficient boundary and Initial conditions.

• Water Engineering Research
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• v.5 no.1
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• pp.1-16
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• 2004

The purpose of this study is to understand the characteristics of hourly PET(Potential Evapo Transpiration) variation estimated using Penman ET model. The estimated PET using Penman model was compared with measured ET. For this study, two subwatersheds were selected, and fluxes, meteorological data and soil moisture data were measured during the summer and winter days. During the winter days, the aerodynamic term of Penman ET is much greater than that of energy term of Penman ET for dry soil condition. The opposite phenomena appeared fer wet soil condition. During the summer days, energy term is much more important factor for ET estimation compared with aerodynamic term regardless of soil moisture condition. Penman ET, measured ET, and energy term show the similar hourly variation pattern mainly because the influence of net radiation on the estimation of Penman ET is much more significant compared with other variables. Even though there are much more soil moisture in the soil during the wet days, the estimated hourly ET from Penman model and measured hourly ET have smaller values compared with those of dry days, indicating the effect of cloudy weather condition.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.3
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• pp.137-143
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• 2003

The degree of contamination on outdoor insulator is ons of the most importance factor to determine the pollution level of outdoor insulation, and the sea salt is known as the most dangerous pollutant. As shown through the preceding study, the generation of salt pollutant and the pollution degree of outdoor insulator have a close relation with meteorological conditions, such as wind velocity, wind direction, precipitation and so fourth. So, in this paper, we made an investigation on the prediction method, a statistical estimation technique for equivalent salt deposit density of outdoor insulator with multiple linear regression analysis. From the results of the analysis, we proved the superiority of the prediction method in which the variables had a very close(about 0.9) correlation coefficient. And the results could be applied to establish the Pollution Prediction System for power utilities, and the system could provide an invaluable information for the design and maintenance of outdoor insulation system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.1129-1136
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• 1994

A point heavy rainfall process is physically modeled. It uses meteorological variables at the ground level as its inputs. The components of the model are parameterized based on well established observations and the previous studies of cloud physics. Particular emphasis is placed on the efficiency of accretion. So we adopt the modified skew-symmetric model for hydrometeor size distribution function that is suitable for the heavy rain cloud. The dominant parameters included in the model are estimated by the optimization technique. The rainfall intensity is predicted by the model with the medium values of estimated parameters.

• Atmosphere
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• v.18 no.4
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• pp.493-506
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• 2008

In order to examine the variational features of Asian dust outbreak in recent years, observed WMO synop data were employed for the period from 1996 to 2007. We first divided Asian dust source regions into four subregions; 1) Taklamakan, 2) Gobi, 3) Inner Mongolia-Manchuria and 4) Loess, and the meteorogical variables such as wind speed, precipitation and threshold wind speed observed during the Asian dust outbreak period were compared with those during non-Asian dust period. The results showed that temporal variation of occurrence frequency of dust outbreak had a strong positive correlation with the frequency of strong wind speed and low precipitation in each of the 4 source regions. Spatial distributions of frequency of dust occurrence after 2002 showed increasing trend in Gobi and Inner Mongolia-Manchuria but decreasing trend in Loess region. This is showing a shift in main source region toward Northwest, especially since 2003.

• Environmental and Resource Economics Review
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• v.24 no.3
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• pp.551-572
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• 2015

Given the presence of global warming, the economic impact of climate changes on output sales has been discussed in the literature, but rarely with empirical evidences. In this present study, a simple log-model was employed to identify the economic impacts of weather changes in manufacturing and service sectors in Korea. For this empirical exercise, weather variables including the CDD (cooling degree days) and HDD (heating degree days) were computed using the Korea's meteorological records covering the period 1970-2012. According to estimation results, 26.7% (144 over 539) and 27.9% (64 over 229) of the manufacturing and service sectors, respectively, are found to be weather-sensitive.