• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.59-66
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• 2013

Among many factors, especially meteorological conditions can impact agricultural productivities. This study was conducted to analyze the relationships between crop yield and meteorological factors. We collected meteorological data (i.e., temperature and precipitation) from the Automated Weather System (AWS) of Korea Meteorological Administration (KMA) and the yield data of Chinese cabbage and Radish from local Nonghyup (NCAF:National Agricultural Cooperative Federation) and Farmers' Corporate Association. The agricultural data were classified into two groups. These groups are comprised of the farmers who produced a crop under 30 kg per $3.3m^2$ and over 30k g per $3.3m^2$ respectively. The daily meteorological data were calculated from the average value for ten days. Based on the regression analysis, we concluded that the yield of Chinese cabbage (Haenam) was related to average temperature, minimum temperature, precipitation, and number of days with precipitation, whereas that of Radish (Jeju) was related to average temperature, maximum temperature, and minimum temperature. The result suggests that these meteorological data can be used more effectively for the prediction of crop yield.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.6
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• pp.93-102
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• 2014

Generally data loading is a laborous job to develop models. Meteorological data is basic input data for hydrological models, it is provided through websites of Korea Meteorological Administration (KMA). The website of KMA provides daily meteorological observation data with tabular format classified by years, items, stations. It is cumbersome to manipulate tabular format for model inputs such as time series and multi-item or multi-station data. The provider oriented services which broadcast restricted formed information have caused inconvenient processes. Tim O'Reilly introduces "Web 2.0" which focuses on providing a service based on data. The top ranked IT companies such as google, yahoo, daum, and naver provide customer oriented services with Open API (Application Programming Interface). A RESTful web service, typical implementation for Open API, consists URI request and HTTP response which are simple and light weight protocol than SOAP (Simple Object Access Protocol). The aim of this study is to develop a web-based service that helps loading data for human use instead of machine use. In this study, the developed RESTful web service provides Open API for manipulating meteorological data. The proposed Open API can easily access from spreadsheet programs, web browsers, and various programming environments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.2
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• pp.127-132
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• 2002

All the countries in RA II (Asia Region in WMO) welcome the establishment of a Web site dedicated to agricultural meteorology, because it is believed that the best way to improve and speed up the flow of information is the use of the Internet and the establishment of a Web site. In providing recommendation for the promotion and improvement of the AgroMeteorological service in RA II, a couple of key suggestions were proposed: (a) Exchanges of data and AgroMeteorological knowledge between member countries and between RAs, (b) Exchanges of experts between member countries as a necessary way to share the knowledge, and (c) Joint research between member countries to solve common problems in AgroMeteorological affairs. In order to meet the above requirements for RA II, an AgroMeteorological information network will be the most critical and dynamic aspect in sustainable agriculture in this region. In addition, the establishment of a Core AgroMeteorological station, recommended by CAgM of WMO, will require its own information sharing systems for communication among member countries. Inevitable use of information technologies (IT) such as information networks, databases, simulation models, GIS, and RS for regional impact assessment of environmental change on AgroEcosystem will be enforced. Thus, the regional Internet-based Agrometeorological information network has been in place since 1999, though all contributions to it have been volunteered by individuals, institutes, universities, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.295-305
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• 2021

In this study, we constructed using Random Forest(RF) by selecting the meteorological factors related to the occurrence of frost. As a result, when constructing a classification model for frost occurrence, even if the amount of data set is large, the imbalance in the data set for development of model has been analyzed to have a bad effect on the predictive power of the model. It was found that building a single integrated model by grouping meteorological factors related to frost occurrence by region is more efficient than building each model reflecting high-importance meteorological factors. Based on our results, it is expected that a high-accuracy frost occurrence prediction model will be able to be constructed as further studies meteorological factors for frost prediction.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.69-82
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• 2023

Representative meteorological data of the rural water district, which is the spatial unit of the study, was produced using the grid-based national standard RCP scenario rainfall data provided by the Korea Meteorological Administration. The retrospective reproducibility of the climate model scenario data was analyzed, and the change in climate characteristics in the water district unit for the future period was presented. Finally the data characteristics and differences of each meteorological element according to various spatial resolution conversion and post-processing methods were examined. As a main result, overall, the distribution of average precipitation and R95p of the grid data, has reasonable reproducibility compared to the ASOS observation, but the maximum daily rainfall tends to be distributed low nationwide. The number of rainfall days tends to be higher than the station-based observation, and this is because the grid data is generally calculated using the area average concept of representative rainfall data for each grid. In addition, in the case of coastal regions, there is a problem that administrative districts of islands and rural water districts do not match. and In the case of water districts that include mountainous areas, such as Jeju, there was a large difference in the results depending on whether or not high rainfall in the mountainous areas was reflected. The results of this study are expected to be used as foundation for selecting data processing methods when constructing future meteorological data for rural water districts for future agricutural water management plans and climate change vulnerability assessments.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.6
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• pp.1-9
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• 2009

Watershed topographical data is essential for the management for water resources and watershed management in terms of hydrology analysis. Collecting watershed topographical and meteorological data is the first step for simulating hydrological models and calculating hydrological components. This study describes a specialized Web-based Geographic Information Systems, Soil Water Assessment Tool model data generation system, which was developed to support SWAT model operation using Web-GIS capability for map browsing, online watershed delineation and topographical and meteorological data extraction. This system tested its operability extracting watershed topographical and meteorological data in real time and the extracted spatial and weather data were seamlessly imported to ArcSWAT system demonstrating its usability. The Web-GIS would be useful to users who are willing to operate SWAT models for the various watershed management purposes in terms of spatial and weather preparing.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.77-88
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• 2019

Drought is the recurrent natural disasters which harshly affect agricultural production and society in various parts in Bangladesh. Information on the spatiotemporal variability of drought events plays a vital role to take necessary action towards drought mitigation and sustainable development. This study aims to analyze the spatial and temporal variation of meteorological drought in Bangladesh during 1981-2015 using Effective Drought Index (EDI). Monthly precipitation data for 36 years (1980-2015) were obtained from 27 meteorological stations. Drought frequency (DF) and areal extent of drought were considered to investigate the spatiotemporal structure of drought. The DF analysis showed that the northern, southwestern and central regions of the country are comparatively vulnerable to meteorological drought. The frequency of drought in all categories has considerably increased during the recent five years from 2011 to 2015. Furthermore, the most significant increasing trend of the drought-affected area was found over the central region especially for pre-monsoon (March-May) season during this period while the decreasing trend of the affected area was found within the eastern region during the study period. To prevent and mitigate the damages of drought disasters in Bangladesh, agricultural and government managers should pay more attention to those regional drought events that occur in pre-monsoon season. The outcome of the present study can be used as explanatory data in building the strategies to drought monitoring and mitigation activities in Bangladesh.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.283-290
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• 2015

This study was carried out a trend analysis for analyzing change of meteorological elements in the main producing areas of Chinese cabbage, radish, pepper, garlic and onion. As meteorological elements, we selected air temperature (maximum, minimum), precipitation and duration of sunshine. We used monthly data of meteorological elements obtained from the main producing areas of vegetables for 30 years from 1981 to 2010. Mann-Kendall test used for significance test of trend and Sen's estimator of slope for computing the variance of meteorological elements. The study results showed that air temperature tended to increase, but duration of sunshine tended to decrease in most regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.242-249
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• 2004

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for the practical purpose of forecasting forest fire danger. Forest fire in South Korea is highly influenced by humidity, wind speed, and temperature. To effectively forecast forest fire occurrence, we need to develop a forest fire danger rating model using weather factors associated with forest fire. Forest fore occurrence patterns were investigated statistically to develop a forest fire danger rating index using time series weather data sets collected from 8 meteorological observation centers. The data sets were for 5 years from 1997 through 2001. Development of the forest fire occurrence probability model used a logistic regression function with forest fire occurrence data and meteorological variables. An eight-province probability model by was developed. The meteorological variables that emerged as affective to forest fire occurrence are effective humidity, wind speed, and temperature. A forest fire occurrence danger rating index of through 10 was developed as a function of daily weather index (DWI).