• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.384-398
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• 2015

In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.115-125
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• 2017

This study was to investigate the user's thermal environments under the pergola($L\;7,200{\times}W\;4,200{\times}H\;2,700mn$) covered with Wisteria floribunda(Willd.) DC. according to the variation of leaf area index(LAI). We carried out detailed measurements with two human-biometeorological stations on a popular square Jinju, Korea($N35^{\circ}10^{\prime}59.8^{{\prime}{\prime}}$, $E\;128^{\circ}05^{\prime}32.0^{{\prime}{\prime}}$, elevation: 38m). One of the stations stood under a pergola, while the other in the sun. The measurement spots were instrumented with microclimate monitoring stations to continuously measure air temperature and relative humidity, wind speed, shortwave and longwave radiation from the six cardinal directions at the height of 0.6m so as to calculate the Universal Thermal Climate Index(UTCI) from $9^{th}$ April to $27^{th}$ September 2017. The LAI was measured using the LAI-2200C Plant Canopy Analyzer. The analysis results of 18 day's 1 minute term human-biometeorological data absorbed by a man in sitting position from 10am to 4pm showed the following. During the whole observation period, daily average air temperatures under the pergola were respectively $0.7{\sim}2.3^{\circ}C$ lower compared with those in the sun, daily average wind speed and relative humidity under the pergola were respectively 0.17~0.38m/s and 0.4~3.1% higher compared with those in the sun. There was significant relationship in LAI, Julian day number and were expressed in the equation $y=-0.0004x^2+0.1719x-11.765(R^2=0.9897)$. The average $T_{mrt}$ under the pergola were $11.9{\sim}25.4^{\circ}C$ lower and maximum ${\Delta}T_{mrt}$ under the pergola were $24.1{\sim}30.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average $T_{mrt}$ compared with those in the sun and was expressed in the equation $y=0.0678{\ln}(x)+0.3036(R^2=0.9454)$. The average UTCI under the pergola were $4.1{\sim}8.3^{\circ}C$ lower and maximum ${\Delta}UTCI$ under the pergola were $7.8{\sim}10.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average UTCI compared with those in the sun and were expressed in the equation $y=0.0322{\ln}(x)+0.1538(R^2=0.8946)$. The shading by the pergola covered with vines was very effective for reducing daytime UTCI absorbed by a man in sitting position at summer largely through a reduction in mean radiant temperature from sun protection, lowering thermal stress from very strong(UTCI >$38^{\circ}C$) and strong(UTCI >$32^{\circ}C$) down to strong(UTCI >$32^{\circ}C$) and moderate(UTCI >$26^{\circ}C$). Therefore the pergola covered with vines used for shading outdoor spaces is essential to mitigate heat stress and can create better human thermal comfort especially in cities during summer. But the thermal environments under the pergola covered with vines during the heat wave supposed to user "very strong heat stress(UTCI>$38^{\circ}C$)". Therefore users must restrain themselves from outdoor activities during the heat waves.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.35-44
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• 2005

Microclimate of Gwangneung forest watershed is characterized by analyzing wind, radiation, profiles of air temperature and humidity, soil and bole temperature, precipitation and soil water content measured at and around the flux tower from April 2000 to September 2003. Mountain-valley wind was prevalent due to the topographic effect with dominant wind from east during daytime and relatively weak wind from west during nighttime. Air temperature reaches its peak in July-August whereas monthly-averaged incoming shortwave radiation shows its peak in May due to summer monsoon. Albedo ranges from 0.12 to 0.16 during the growing season. Monthly-averaged bole temperature is in phase with monthly- averaged air temperature which is consistently higher. Monthly-averaged soil temperature lags behind air temperature and becomes higher with leaf fall. With the emergence of leafage in April, maximum temperature level during midday shifts from the ground surface to the crown level of 15-20m in May. Profiles of water vapor pressure show a similar shift in May but the ground surface remains as the major source of water. Vapor pressure deficit is highest in spring and lowest in winter. Monthly averaged surface soil temperatures range from 0 to 20℃ with a maximum in August. Monthly averaged trunk temperatures of the dominant tree species range from -5.8 to 21.6℃ with their seasonal variation and the magnitudes similar to those of air temperature. Annual precipitation amount varies significantly from year to year, of which >60% is from July and August. Vertical profiles of soil moisture show different characteristics that may suggest an important role of lateral movement of soil water associated with rainfall events.

• 한국해양학회지
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• v.29 no.4
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• pp.325-337
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• 1994

The distributions of heat and momentum fluxes on the surface over the oceans around the Korean Peninsula are obtained based on the surface-layer flux model of Kim and Kang (1994), and their seasonal variations are examined in the present study. the input data of the model is the oceanatmosphere data with a grid interval of 2$^{\circ}$ in longitude and latitude. The atmosphere data, which are the pressure, temperature, and specific humidity on the 1000 mb level for 3 year period of 1985∼1987, are obtained from the European center for Medium Range Forecast. The sea surface temperature (SST) is obtained from National Meteorological Center (NMC). The solar insolation and longwave radiation on the ocean surface are obtained, respectively, from the NASA satellite data and based on an emprical formula. It is shown from the net heat flux that the oceans near Korea lose heat to the atmosphere in January and October with the rates of 200∼ 400 Wm/SUP -2/ and 100 Wm/SUP -2/, respectively. But the oceans are heated by the atmosphere in April and July with about the same rate of 100 Wm/SUP -2/. The annualmean net heat flux is negative over the entire domain except the northern part of the Yellow Sea. The largest annual-mean cooling rate of about 120 Wm/SUP -2/ is appeared off the southwest of Japan. In the East Sea, the annual-mean cooling rate is 60∼90 Wm/SUP -2/ in the southern and northern parts and about 30 Wm/SUP -2/ in the middle part. The magnitude of wind stress in january is 3∼ 5 times bigger than those of the other months. As a result, the spatial pattern of annual-mean wind stress is similar to that of January. It is also shown that the annual-mean wind stress curl is negative. in the East China Sea and the South Sea,but it is positive in the northern part of the Yellow Sea.In the East sea,the stress curl is positive in the southeast and northern parts and negative in the northwestern part.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.140-148
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• 2007

The remote sensing observations of land surface properties are inevitably influenced by the landscape heterogeneity. In this paper, we introduce a geostatistical technique to provide a quantitative interpretation of landscape heterogeneity in terms of key land surface parameters. The study areas consist of the two KoFlux sites: (1) the Gwangneung site, covered with temperate mixed forests on a complex terrain, and (2) the Haenam site with mixed croplands on a relatively flat terrain. The semivariogram and fractal analyses were performed for both sites to characterize the spatial heterogeneity of two radiation parameters, i.e., land surface temperature (LST) and albedo. These parameters are the main factors affecting the reflected longwave and shortwave radiation components from the two study sites. We derived them from the high-resolution Landsat ETM+ satellite images collected on 23 Sep. 2001 and 14 Feb. 2002. The results of our analysis show that the characteristic scales of albedo was >1 km at the Gwangneung site and approximately 0.3 km at the Haenam site. For LST, the scale of heterogeneity was also >1 km at the Gwangneung site and >0.6 to 1.0 km at the Haenam site. At both sites, there was little change in the characteristic scales of the two parameters between the two different seasons.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.141-148
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• 2021

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. It is expected that agrivoltaic systems can realize climate smart agriculture by reducing evapotranspiration and methane emission due to the reduction of incident solar radiation and the consequent surface cooling effect and bring additional income to farms through solar power generation. In this study, to evaluate that agrivoltaic systems are suitable for realization of climate smart agriculture, we conducted agro-environmental observations (i.e., downward/upward shortwave/longwave radiations, air temperature, relative humidity, water temperature, soil temperature, and wind speed) in a rice paddy under an agrivoltaic system and compared with the environment outside the system using automated meteorological observing systems (AMOS). During the observation period, the spatially averaged incoming solar radiation under the agrivoltaic system was about 70% of that in the open paddy field, and clear differences in the soil and water temperatures between the paddy field under the agrivoltaic system and the open paddy field were confirmed, although the air temperatures were similar. It is required in the near future to confirm whether such environmental differences lead to a reduction in water consumption and greenhouse gas emissions by flux measurements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.457-459
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• 2018

Solar power generation system is a energy generation technology that produces electricity from solar power, and it is growing fastest among renewable energy technologies. It is of utmost importance that the solar power system supply energy to the load stably. However, due to unstable energy production due to weather and weather conditions, accurate prediction of energy production is needed. In this paper, an Artificial Neural Network(ANN) that predicts solar energy using 15 kinds of meteorological data such as precipitation, long and short wave radiation averages and temperature is implemented and its performance is evaluated. The ANN is constructed by adjusting hidden parameters and parameters such as penalty for preventing overfitting. In order to verify the accuracy and validity of the prediction model, we use Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) as performance indices. The experimental results show that MAPE = 19.54 and MAE = 2155345.10776 when Hidden Layer $Sizes=^{\prime}16{\times}10^{\prime}$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.626-628
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• 2018

In this paper, we compare the performances of SVM (Support Vector Machine) and ANN (Artificial Neural Network) machine learning models for predicting solar energy by using meteorological data. Two machine learning models were built by using fifteen kinds of weather data such as long and short wave radiation average, precipitation and temperature. Then the RBF (Radial Basis Function) parameters in the SVM model and the number of hidden layers/nodes and the regularization parameter in the ANN model were found by experimental studies. MAPE (Mean Absolute Percentage Error) and MAE (Mean Absolute Error) were considered as metrics for evaluating the performances of the SVM and ANN models. Sjoem Simulation results showed that the SVM model achieved the performances of MAPE=21.11 and MAE=2281417.65, and the ANN model did the performances of MAPE=19.54 and MAE=2155345.10776.

• 한국해양학회지
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• v.30 no.2
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• pp.91-115
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• 1995

Air-sea heat fluxes in the East Sea were estimated from the various ship's data observed from 1961 to 1990 and the JMA buoy #6 data from 1976 to 1985. The oceanic heat transport in the sea was also determined from the fluxes above and the heat storage rate of the upper layer of 200m from the sea surface. In winter, The incoming solar radiation is almost balanced with the outgoing longwave radiation. but the sea loses her heat through the sea surface mainly due to the latent and sensible heat fluxes. The spatial variation of the net surface heat flux is about 100 Wm/SUP -2/, and the maximum loss of heat is occurred near the Tsugaru Strait. There are also lots of heat losses in the southern part of the East Sea, Korea Strait and Ulleung Basin. Particularly, the heat strong loss in the south-western part of the sea might be concerned with the formation of her Intermediate Homogeneous Water. In summer, the sea is heated up to about 120∼140 Wm/SUP -2/ sue to strong incoming solar radiation and weak turbulent heat fluxes and her spatial variation is only about 20 Wm/SUP -2/. The oceanic heat flux is positive in the southeasten part f the sea and the magnitude of the flux is larger than that of the net surface heat flux. This shows the importance of the area. In the southwestern part of the sea, however, the oceanic heat flux is negative. This fact implies cold water inflow, the North Korean Cold Water. The sigh of net surface heat flux is changed from negative to positive in March and from positive to negative in September. The heat content in the upper surface 200 m from the sea surface reaches its minimum in March and maximum in October. The annual variation of the net surface heat flux is 580 Wm/SUP -2/ in southwestern part of the sea. The annual mean values of net surface heat fluxes are negative, which mean the net heat transfer from the sea to the atmosphere. The magnitude of the flux is about 130 Wm/SUP -2/ near the Tsugaru Strait. The net surface fluxes in the Korea Strait and the Ulleung Basin are relatively larger than those of the rest areas. The spatial mean values of surface heat fluxes from 35$^{\circ}C$ to 39$^{\circ}$N are 129, -90, -58, and -32 Wm/SUP -2/ for the incoming solar radiation, latent hear flux, outgoing longwave radiation, and sensible heat flux, respectively.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.389-401
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• 2023

Climate, weather, insolation (solar radiation), and solar energy in major cities of Tajikistan were investigated prior to construction of infrastructure for the Dushanbe Solar Station. In Dushanbe city there was a 70% probability of sunny days from May 16 to October 23, a period of 5.2 months. August had the most sunny days of in the year, with 99% probability of a sunny, the cloudiest month was February with a 41% chance of being sunny. In major cities of the Sughd and Gorno-Badakhshan states, the average number of cloudy days per month was ~3.3, with Dzhauz having 53 day and Fedchnko Glacier 79 days. For the 18 major cities of Tajikistan, the average annual total solar radiation was 2,429 W/m², and the average monthly solar radiation was 202 W/m². The city with the lowest annual total and monthly average solar radiation was Shartuz in Sughd state, with values ~2.7% less than the national average. The cities with the highest annual total and monthly average solar radiation were Khorog and Jirgatol in Gorno-Badakhshan state, with values ~10% above the national average. The daily average incident shortwave solar energy in the cities Dushanbe, Karakul, and Jirgatol was ~7.8 kWh per 2.4 m² during summer (May-August), and 2.7 kWh during winter (November-February), or ~35% that of summer.