• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.1
• /
• pp.61-69
• /
• 2004

A long-term growth simulation was performed at 99 land units in Yeoncheon county to test the potential adaptability of each land unit for growing soybean cultivars. The land units for soybean cultivation(CZU), each represented by a geographically referenced land patch, were selected based on land use, soil characteristics, and minimum arable land area. Monthly climatic normals for daily maximum and minimum temperature, precipitation, number of rain days and solar radiation were extracted for each CZU from digital climate models(DCM). The DCM grid cells falling within a same CZU were aggregated to make spatially explicit climatic normals relevant to the CZU. A daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CROPGRO-soybean model suitable for 2 domestic soybean cultivars were derived from long-term field observations. Three foreign cultivars with well established parameters were also added to this study, representing maturity groups 3, 4, and 5. Each treatment was simulated with the randomly generated 30 years' daily weather data(from planting to physiological maturity) for 99 land units in Yeoncheon to simulate the growth and yield responses to the inter-annual climate variation. The same model was run with input data from the Crop Experiment Station in Suwon to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for evaluation. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific cultivar. A computer program(MAPSOY) was written to help utilize the results in a decision-making procedure for agrotechnology transfer. transfer.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.3 no.3
• /
• pp.156-162
• /
• 2001

In order to monitor local climatic information, twelve automated weather stations (AWS) were installed in alpine area by the Alpine Agricultural Experiment Station, Rural Development Administration (RDA), at the field of major crop located in around highland area, and collected data from 1993 to 2000. Hourly measurements of air and soil temperature (underground 10 cm,20 cm), relative humidity, wind speed and direction, precipitation, solar radiation and leaf wetness were automatically performed and the data could be collected through a public phone line. Datalogger was selected as CR10X (Campbell scientific, LTD, USA) out of consideration for sensers' compatibility, economics, endurance and conveniences. All AWS in alpine area were combined for net work and daily climatic data were analyzed in text and graphic file by program (Chumsungdae, LTD) on 1 km $\times$ 1 km grid tell basis. In this analysis system, important multi-functionalities, monitoring and analysis of local climatic information in alpine area was emphasized. The first objective was to obtain the output of a real time data from AWS. Secondly, daily climatic normals for each grid tell were calculated from geo-statistical relationships based on the climatic records of existing weather stations as well as their topographical informations. On 1 km $\times$ 1 km grid cell basis, real time climatic data from the automated weather stations and daily climatic normals were analyzed and graphed. In the future, if several simulation models were developed and connected with this system it would be possible to precisely forecast crop growth and yield or plant disease and pest by using climatic information in alpine area.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.715-727
• /
• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.2 no.1
• /
• pp.16-23
• /
• 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
• /
• v.15 no.4
• /
• pp.245-263
• /
• 2013

This study was conducted to find out the influence of elevated atmospheric $CO_2$ concentrations and air temperature on photosynthesis and fruit quality of 'Fuji'/M.9 apple trees and to investigate these to the effects of climate change during the last four years (2009-2012). The treatments employed were: 'Ambient' (ambient temperature + ambient $CO_2$ concentration); 'High $CO_2$' (ambient temperature + elevated $CO_2$ concentration); 'High Temp'. (elevated temperature + ambient $CO_2$ concentration); and 'High $CO_2$ + High Temp'. (elevated temperature + elevated $CO_2$ concentration). The elevated temperature plots were maintained at $4^{\circ}C$ higher than ambient air temperature, while the elevated $CO_2$ plots were maintained at 700 ${\mu}mol{\cdot}mol^{-1}$. Annual treatment period was applied from end of April to beginning of November for four years. Results showed that elevated $CO_2$ decreased stomatal conductance and leaf SPAD value, but increased photosynthetic rate, intercellular $CO_2$ concentration (Ci), and starch content of mesophyll tissue. In the vegetative growth, elevated temperature increased total number of shoot and total shoot growth per tree, but elevated $CO_2$ decreased average shoot length. In the fruit quality, elevated $CO_2$ increased soluble solid content, fruit red color, and ethylene production. In conclusion, elevated $CO_2$ increased photosynthetic rate of apples during the early growth, but effect of increased photosynthetic rate due to elevated $CO_2$ was decreased during latter growth stage. Elevated temperature, on the other hand, tended to decrease photosynthetic rate of apples during the early growth, but that tended to increase during latter growth stage. Both elevated $CO_2$ and temperature tended to decrease the degree of decreased photosynthetic rate due to each factor.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.1
• /
• pp.40-49
• /
• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.13 no.1
• /
• pp.35-40
• /
• 2011

While high-definition precipitation maps with a 270 m spatial resolution are available for South Korea, there is little information on geospatial availability of precipitation water for the famine - plagued North Korea. The restricted data access and sparse observations prohibit application of the widely used PRISM (Parameter-elevation Regressions on Independent Slopes Model) to North Korea for fine-resolution mapping of precipitation. A hybrid method which complements the PRISM grid with a sub-grid scale elevation function is suggested to estimate precipitation for remote areas with little data such as North Korea. The fine scale elevation - precipitation regressions for four sloping aspects were derived from 546 observation points in South Korea. A 'virtual' elevation surface at a 270 m grid spacing was generated by inverse distance weighed averaging of the station elevations of 78 KMA (Korea Meteorological Administration) synoptic stations. A 'real' elevation surface made up from both 78 synoptic and 468 automated weather stations (AWS) was also generated and subtracted from the virtual surface to get elevation difference at each point. The same procedure was done for monthly precipitation to get the precipitation difference at each point. A regression analysis was applied to derive the aspect - specific coefficient of precipitation change with a unit increase in elevation. The elevation difference between 'virtual' and 'real' surface was calculated for each 270m grid points across North Korea and the regression coefficients were applied to obtain the precipitation corrections for the PRISM grid. The correction terms are now added to the PRISM generated low resolution (~2.4 km) precipitation map to produce the 270 m high resolution map compatible with those available for South Korea. According to the final product, the spatial average precipitation for entire territory of North Korea is 1,196 mm for a climatological normal year (1971-2000) with standard deviation of 298 mm.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.4
• /
• pp.304-311
• /
• 2013

There have been increasing cases for farmers to install automated weather stations (AWS) at their farms and orchards in order to take countermeasures to more frequent weather disasters caused by climate variability and weather extremes. Although raw data are the same, the additive values as agrometeorological information may vary depending on data processing methods. User demands on appropriate information could also be different among crop species, cropping systems and even cultivars. We designed an internet based AWS data processing and display system to help diverse users (e.g., farmers), extension workers to access their weather data on specific demands. The system was implemented at a rural catchment with 52 $km^2$ land area where 14 automated weather stations are in operation. This note introduces the system and describes the major modules in detail. By linking regional AWS networks, a feasibility for this system as an early warning system is also discussed.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.4
• /
• pp.287-297
• /
• 2016

This study aims to identify the relationship between climatic factors and stand mean Diameter at Breast Height (DBH) for two major tree species; Pinus densiflora and Quercus mongolica in Andong-dam basin. Forest variables such as age, diameter distribution and number of trees per hectare from the $5^{th}$ and $6^{th}$ National Forest Inventory data were used to develop a DBH estimation model. Climate data were collected from six meteorological observatory station and twelve Automatic Weather System provided by Korea Meteorological Administration to produce interpolated daily average temperature map with Inverse Distance Weighting (IDW) method. Andong-dam basin reflects rugged mountainous terrain, so temperature were adjusted by lapse rate based correction. As a result, predictions of model were consistent with the previous studies; that the rising temperature is negatively related to the growth of Pinus densiflora whereas opposing trend is observed for Quercus mongolica.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.14 no.2
• /
• pp.53-62
• /
• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.