• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.317-325
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• 2015

An adequate downscaling of synoptic forecasts is a prerequisite for improved agrometeorological service to rural areas in South Korea where complex terrains and small farms are common. In this study, geospatial schemes based on topoclimatology were used to scale down the Korea Meteorological Administration (KMA) temperature forecasts to the local scale (~30 m) across a rural catchment. Then, using these schemes, local temperatures were estimated at 14 validation sites at 0600 and 1500 LST in 2013/2014 and were compared with the observations. The estimation errors were substantially reduced for both 0600 and 1500 LST temperatures when compared against the uncorrected KMA products. The improvement was most notable at low lying locations for the 0600 temperature and at the locations on west- and south-facing slopes for the 1500 LST temperature. Using the downscaled real-time temperature data, a pilot service has started to provide the field-specific weather information tailored to meet the requirements of small-scale farms. For example, the service system makes a daily outlook on the phenology of crop species grown in a given field using the field-specific temperature data. When the temperature forecast is given for next morning, a frost risk index is calculated according to a known relationship of phenology and frost injury. If the calculated index is higher than a pre-defined threshold, a warning is issued and delivered to the grower's cellular phone with relevant countermeasures to help protect crops against frost damage.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.49-60
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• 2004

Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.149-163
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• 2004

Evapotranspiration (ET) is a critical component of the hydrologic cycle which influences economic activities as well as the natural ecosystem. While there have been numerous studies on ET estimation for homogeneous areas using point measurements of meteorological variables, monitoring of spatial ET has not been possible at landscape - or watershed - scales. We propose a site-specific application of the land surface model, which is enabled by spatially interpolated input data at the desired resolution. Gyunggi Province of South Korea was divided into a regular grid of 10 million cells with 30m spacing and hourly temperature, humidity, wind, precipitation and solar irradiance were estimated for each grid cell by spatial interpolation of synoptic weather data. Topoclimatology models were used to accommodate effects of topography in a spatial interpolation procedure, including cold air drainage on nocturnal temperature and solar irradiance on daytime temperature. Satellite remote sensing data were used to classify the vegetation type of each grid cell, and corresponding spatial attributes including soil texture, canopy structure, and phenological features were identified. All data were fed into a standalone version of SiB2(Simple Biosphere Model 2) to simulate latent heat flux at each grid cell. A computer program was written for data management in the cell - based SiB2 operation such as extracting input data for SiB2 from grid matrices and recombining the output data back to the grid format. ET estimates at selected grid cells were validated against the actual measurement of latent heat fluxes by eddy covariance measurement. We applied this system to obtain the spatial ET of the study area on a continuous basis for the 2001-2003 period. The results showed a strong feasibility of using spatial - data driven land surface models for operational monitoring of regional ET.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.93-101
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• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.1
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• pp.16-23
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• 2000

A topography-precipitation relationship derived from the southern part of Korean Peninsula was applied to North Korea where climate stations are few and widely separated. Two hundred and seventy seven rain gauge stations of South Korea were classified into 8 different groups depending on the slope orientation (aspect) of the region they are located. Monthly precipitation averaged over 10 year period (1986-1995) was regressed to topographical variables of the station locations. A 'trend precipitation' for each gauge station was extracted from the precipitation surface interpolated from the monthly precipitation data of 24 standard stations of the Korea Meteorological Administration and used as a substitute for y-axis intercept of the regression equation. These regression models were applied to the corresponding regions of North Korea, which were identified by slope orientation, to obtain monthly precipitation surface for the aspect regions. 'Trend precipitation' from the 10 year data of 27 North Korean standard stations was also used in the model calculation. Output grids for each aspect region were mosaicked to form the monthly and annual precipitation surface with a 1km$\times$1km resolution for the entire territory of North Korea. Spatially averaged annual precipitation of North Korea was 938 mm with the standard deviation of 246 mm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.185-198
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• 2001

This study was conducted to reveal the effects of local climatic conditions on reproductive growth in a mature stand of Korean white pine based on climatic estimates. For this, the reproductive growth such as production and characteristics of cone and seed were first measured and summarized for seven years from 1974 to 1980. The local climatic conditions in the study site were also estimated by both a topoclimatological method and a spatial statistical technique. The local climatic conditions were then correlated with and regressed on the growth factors to reveal the relationships between the climatic estimates and the reproductive growth. Average number of conelet formation per tree showed highly negative correlation with some climatic variables related to minimum temperature in the year of flower bud differentiation. Especially, the most significant negative correlation were found between average of the minimum temperature for June and July of flower bud differentiation year and the number of conelet formation. There was no significant correlation between the number of cone production and climatic variables. However, total precipitation from December of the flowering year to February of the cone production year showed the most high correlation (r=0.6036) with the number of cone production. It was found that significant climatic variables affecting the amount of cone drop and cone drop percentage were the sum of cloudy days from June of the flowering year to August of the cone production year. Positive correlation was significantly recognized between the average weight of empty seed per cone and total precipitation from December of the flowering year to February of the cone production year. For the percentage of empty seed, five climatic variables among 19 variables were significantly correlated at 10% level. The average weight of a cone showed negative correlation with total precipitation from June of the flowering year to August of the cone production year. It was also found that average weight of a seed had highly negative correlation with total precipitation from December of the flowering year to February of the cone production year. The average weight of cone coat was negatively correlated with two climatic variables derived from clear days, which are sum of clear days from November of the flowering year to March of the cone production year and sum of clear days from December of the flowering year to February of the cone production year. On the other hand, it showed positive correlation with mean temperature of May in the flowering year. The exactly same results were obtained in correlation analysis for the percentage of cone coat.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.105-113
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• 2001

This study was conducted to reveal the effects of local climatic conditions on the vegetative growth in a mature stand of Korean white pine based on climatic estimates. For this, the annual increments of stand variables such as DBH, height, basal area and volume were measured and estimated for seven years from 1974 to 1980. The local climatic conditions in the study site were also estimated by both a topoclimatological method and a spatial statistical technique. The local climatic conditions were then correlated with and regressed on the growth factors to reveal the relationships between the climatic estimates and the growth. It is found that relatively high temperatures had positive effects on the diameter growth. The yearly diameter growth increased when each of mean, maximum, and minimum temperature during the growing season was high. Height growth showed positively significant correlation with three climatic variables. The most important variable influencing height growth was the average of maximum temperature for 10 months from January to October. It means that the higher the average of maximum temperature for 10 months from January to October is, the more height growth of Korean white pine increases. Other climatic variables related to height growth were average of minimum temperature for 3 months in the early growing season and mean relative humidity for the growing season. Six climatic variables related to temperature had effects on basal area increment and all of them were positively correlated with basal area increment. Especially, temperatures from January to March were important factors affecting the basal area increment. In volume increment, high correlation was also recognized with most of temperature variables. This tendency was the same as the results in diameter and hight increments. This means that the volume growth increases when temperatures during the growing season are relatively high.