• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.1
• /
• pp.72-82
• /
• 2014

This study was conducted to predict the changes of yearly productive area distribution for pinus densiflora under climate change scenario. For this, site index equations by ecoprovinces were first developed using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 48 environmental factors including 19 climatic variables were regressed on site index to develop site index equations. Two climate change scenarios, RCP 4.5 and RCP 8.5, were then applied to the developed site index equations and the distribution of productive areas for pinus densiflora were predicted from 2020 to 2100 years in 10-year intervals. The results from this study show that the distribution of productive areas for pinus densiflora generally decreases as time passes. It was also found that the productive area distribution of Pinus densiflora is different over time under two climate change scenarios. The RCP 8.5 which is more extreme climate change scenario showed much more decreased distribution of productive areas than the RCP 4.5. It is expected that the study results on the amount and distribution of productive areas over time for pinus densiflora under climate change scenarios could provide valuable information necessary for the policies of suitable species on a site.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.405-414
• /
• 2021

This study predicted waxy corn harvest date in South Korea using 30-year (1991-2020) hindcasts (1-6 month lead) produced by the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. To estimate corn harvest date, the cumulative temperature is used, which accumulated the daily observed and predicted temperatures from the seeding date (5 April) to the reference temperature (1,650~2,200℃) for harvest. In terms of the mean air temperature, the hindcasts with a bias correction (20.2℃) tends to have a cold bias of about 0.1℃ for the 6 months (April to September) compared to the observation (20.3℃). The harvest date derived from bias-corrected hindcasts (DOY 187~210) well simulates one from observation (DOY 188~211), despite a slight margin of 1.1~1.3 days. The study shows the possibility of obtaining the gridded (5 km) daily temperature and corn harvest date information based on the cumulative temperature in advance for all regions of South Korea.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.3
• /
• pp.175-186
• /
• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of Animal Science and Technology
• /
• v.63 no.2
• /
• pp.339-353
• /
• 2021

This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration's reports of new variety adaptability from 1985-2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration's weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.

• Journal of Korea Water Resources Association
• /
• v.39 no.9 s.170
• /
• pp.755-766
• /
• 2006

Since the accuracy of climate forecast information has improved from better understanding of the climatic system, particularly, from the better understanding of ENSO and the improvement in meteorological models, the forecasted climate information is becoming the important clue for streamflow prediction. This study investigated the available climate forecast information to improve the extended streamflow prediction in Korea, such as MIMI(Monthly Industrial Meteorological Information) and GDAPS(Global Data Assimilation and Prediction) and measured their accuracies. Both MIMI and the 10-day forecast of GDAPS were superior to a naive forecasts and peformed better for the flood season than for the dry season, thus it was proved that such climate forecasts would be valuable for the flood season. This study then forecasted the monthly inflows to Chungju Dam by using MIMI and GDAPS. For MIMI, we compared three cases: All, Intersection, Union. The accuracies of all three cases are better than the naive forecast and especially, Extended Streamflow Predictions(ESPs) with the Intersection and with Union scenarios were superior to that with the All scenarios for the flood season. For GDAPS, the 10-day ahead streamflow prediction also has the better accuracy for the flood season than for the dry season. Therefore, this study proved that using the climate information such as MIMI and GDAPS to reduce the meteorologic uncertainty can improve the accuracy of the extended streamflow prediction for the flood season.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.4
• /
• pp.286-296
• /
• 2019

Land suitability assessments have been a crucial issue for enhancing productivity in agriculture and conserving agricultural lands. Based on soil and climate information, land suitability assessment for peaches (Prunus persica) and grapes (Vitis vinifera L.) were conducted using the maximum limiting characteristic method (MLCM) in South Korea. In peaches, S1 (highly suitable) exists on 2.21% of the land, S2 (moderately suitable) on 19.20%, N1 (currently not suitable) on 12.07%, and N2 (permanently not suitable) on the remaining 66.52%. In grapes, 3.65% of the land is classified as S1, 17.98% as S2, 11.85% as N1 and 66.52% as N2. In both fruit trees, the results acquired from soil and climatic information were similar to those from soil information alone. The data also suggest that the grades by soil information were relatively low over the land. With the assumption that the more suitable area a province has, the more will be cultivated for the fruit trees, we compared the percentages of area for peach and grape farming per province with the results by MLCM, and suggested that some provinces with a small percentage of farm can be encouraged to plant more in suitable areas as dictated by MLCM for the species. In the near future, we plan to use an advanced method such as analytic hierarchy process (AHP) to conduct similar tests, in which having reference data of yields or benefits per farm can efficiently increase the accuracy of the measurements.

• Journal of Environmental Science International
• /
• v.23 no.6
• /
• pp.1121-1130
• /
• 2014

This study aims to find the perception and utilization of the citizen about the dryness watch warning (DWW) among special weather reports. For this we have made up a descriptive questionnaire including the perception, utilization of special weather reports. Using the SPSS 17.0 program, descriptive statistics, t-test, ANOVA and Scheffe test were used to analyze the collected data. The results are as follows; The perception of DWW is measured by 4 point Likert scale and the average is $15.97{\pm}3.70$ (percentile=57.0). This value shows that the awareness level is not that high and according to the occupation, college students show the lowest awareness and housewives show the highest awareness. According to the age, the teens and twenties show the lowest awareness and fifties and sixties show the highest awareness. Although the perception of the teens and college students are rather poor, there were many positive answers that it is necessary to establish the advanced disaster prevention plan according to the questionnaire about the utilization of DWW. Therefore, if we come up with an effective plan to improve the perception than we can expect a large-effect in terms of fire and forest fire prevention. The perception of DWW can be improved by providing weather information and weather related education program on TV or internet which have the high level of preference. Also, it is necessary to provide online and offline program of advertising education and disaster management education through the weather forecast bureau which is the host organization of delivering weather information.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.1
• /
• pp.35-47
• /
• 2022

Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.10 no.3
• /
• pp.94-101
• /
• 2008

Warming trends during winter seasons in East Asian regions are expected to accelerate in the future according to the climate projection by the Inter-governmental Panel on Climate Change (IPCC). Warmer winters may affect short-term cold hardiness of deciduous fruit trees, and yet phenological observations are scant compared to long-term climate records in the regions. Dormancy depth, which can be estimated by daily temperature, is expected to serve as a reasonable proxy for physiological tolerance of flowering buds to low temperature in winter. In order to delineate the geographical pattern of short-term cold hardiness in grapevines, a selected dormancy depth model was parameterized for "Campbell Early", the major cultivar in South Korea. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HDDTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations and a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and site elevation). To generate relevant datasets for climatological normal years in the future, we combined a 25km-resolution, 2011-2100 temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 scenario) with the 1971-2000 HD-DTM. The dormancy depth model was run with the gridded datasets to estimate geographical pattern of change in the cold-hardiness period (the number of days between endo- and forced dormancy release) across South Korea for the normal years (1971-2000, 2011-2040, 2041-2070, and 2071-2100). Results showed that the cold-hardiness zone with 60 days or longer cold-tolerant period would diminish from 58% of the total land area of South Korea in 1971-2000 to 40% in 2011-2040, 14% in 2041-2070, and less than 3% in 2071-2100. This method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.2
• /
• pp.108-125
• /
• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.