• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.63-73
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• 2010

A comprehensive mapping project for agroclimatic zoning in South Korea will end by April 2010, which has required 4 years, a billion won (ca. 0.9 million US dollars) and 22 experts from 7 institutions to complete it. The map database from this project may be categorized into primary, secondary and analytical products. The primary products are called "high definition" digital climate maps (HD-DCMs) and available through the state of the art techniques in geospatial climatology. For example, daily minimum temperature surfaces were prepared by combining the climatic normals (1971-2000 and 1981-2008) of synoptic observations with the simulated thermodynamic nature of cold air by using the raster GIS and microwave temperature profiling which can quantify effects of cold air drainage on local temperature. The spatial resolution of the gridded climate data is 30m for temperature and solar irradiance, and 270m for precipitation. The secondary products are climatic indices produced by statistical analysis of the primary products and includes extremes, sums, and probabilities of climatic events relevant to farming activities at a given grid cell. The analytical products were prepared by driving agronomic models with the HD-DCMs and dates of full bloom, the risk of freezing damage, and the fruit quality are among the examples. Because the spatial resolution of local climate information for agronomic practices exceeds the current weather service scale, HD-DCMs and the value-added products are expected to supplement the insufficient spatial resolution of official climatology. In this lecture, state of the art techniques embedded in the products, how to combine the techniques with the existing geospatial information, and agroclimatic zoning for major crops and fruits in South Korea will be provided.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.11-18
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• 2012

Daily temperature data produced by harmonic analysis of monthly climate summary have been used as an input to plant phenology model. This study was carried out to evaluate the performance of the harmonic based daily temperature data in prediction of major phenological developments and to apply the results in improving decision support for agricultural production in relation to the climate change scenarios. Daily maximum and minimum temperature data for a climatological normal year (Jan. 1 to Dec. 31, 1971-2000) were produced by harmonic analysis of the monthly climate means for Seoul weather station. The data were used as inputs to a thermal time - based phenology model to predict dormancy, budburst, and flowering of Japanese cherry in Seoul. Daily temperature measurements at Seoul station from 1971 to 2000 were used to run the same model and the results were compared with the harmonic data case. Leaving no information on annual variation aside, the harmonic based simulation showed 25 days earlier release from endodormancy, 57 days longer period for maximum cold tolerance, delayed budburst and flowering by 14 and 13 days, respectively, compared with the simulation based on the observed data. As an alternative to the harmonic data, 30 years daily temperature data were generated by a stochastic process (SIMMETEO + WGEN) using climatic summary of Seoul station for 1971-2000. When these data were used to simulate major phenology of Japanese cherry for 30 years, deviations from the results using observed data were much less than the harmonic data case: 6 days earlier dormancy release, 10 days reduction in maximum cold tolerance period, only 3 and 2 days delay in budburst and flowering, respectively. Inter-annual variation in phenological developments was also in accordance with the observed data. If stochastically generated temperature data could be used in agroclimatic mapping and zoning, more reliable and practical aids will be available to climate change adaptation policy or decision makers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.284-301
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• 2023

The changes in rice climatic yield potential (CYP) across the Korean Peninsula are evaluated based on the new climate change scenario produced by the National Institute of Agricultural Sciences with 18 ensemble members at 1 km resolution under a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) emission scenarios. To overcome the data availability, we utilize solar radiation f or CYP instead of sunshine duration which is relatively uncommon in the climate prediction f ield. The result show that maximum CYP(CYPmax) decreased, and the optimal heading date is progressively delayed under warmer temperature conditions compared to the current climate. This trend is particularly pronounced in the SSP5-85 scenario, indicating faster warming, except for the northeastern mountainous regions of North Korea. This shows the benef its of lower emission scenarios and pursuing more efforts to limit greenhouse gas emissions. On the other hand, the CYPmax shows a wide range of feasible futures, which shows inherent uncertainties in f uture climate projections and the risks when analyzing a single model or a small number of model results, highlighting the importance of the ensemble approach. The f indings of this study on changes in rice productivity and uncertainties in temperature and solar radiation during the 21st century, based on climate change scenarios, hold value as f undamental information for climate change adaptation efforts.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.404-414
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• 2023

In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

• Atmosphere
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• v.33 no.2
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• pp.155-171
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• 2023

This paper aims to examine from various perspectives how domestic research studies and projects related to climate change have been conducted to mark the 60th anniversary of the Korean Meteorological Society (KMS). The 『50-year History of the Korean Meteorological Society』, published more than a decade ago, has never dealt with the history of development of individual fields of meteorology such as climate change. Therefore, it is of significance to look at the history of research activities and studies achieved by KMS members in the area of climate change over the past 60 years. The research on climate change in KMS is classified by era from the beginning to the latest and the contents are examined by major research projects at that time. During the past 60 years, climatological research in KMS has been mainly focused on general climate, synoptic climate, and applied climate (urban climate) until the 2000s. However, since the 1990s, climate change has become an important area for climate research. The 2000s are the beginning era of climate change research, since the major projects and researches for climate change has begun in the period. The 2010s can be a time when climate change prediction and monitoring are expanded and refined to meet the rapidly increasing demands for climate information from a wide range of areas. We concluded that the development of the research capabilities of the society over the past 60 years, in particular in the past two decades, in the field of climate change research is remarkable.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.368-383
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• 2014

Climate change is expected to affect population density, phenology, distribution, morphological traits, reproduction and genetics of insects, and even in the extinction of insects. To develop novel research subjects for predicting climate change effect, basic information about biological and ecological data on insect species should be compiled and reviewed. For this reason, this study was conducted to collect the biological information on insect pests that are essential for predicting potential damage caused by insect pests in future environment. In addition, we compared domestic and foreign research trends regarding climate change effect and suggested future research subjects. Domestic researchers were rather narrow in the subject, and were mostly conducted based on short-term monitoring data to determine relationship between insects and environmental variables. On the other hand, foreign researches studied on various subjects to analyze the effect of climate change, such as changes in distribution of insect using long-term monitoring data or their prediction using population parameters and models, and monitoring of the change of the insect community structure. To determine change of the phenology, distribution, overwintering characteristics, and genetic structures of insects under climate change through development of monitoring technique, in conclusion, further researches are needed. Also, development of population models for major or potential pests is important for prediction of climate change effects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.403-417
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.25-48
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.47-56
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• 2020

Decline of pine forests happens in Korea due to various disturbances such as insect pests, forest fires and extreme climate, which may further continue with ongoing climate change. For conserving and reestablishing pine forests, understanding climate-induced future shifts of pine tree distribution is a critical concern. This study predicts future geographical distribution of Pinus densiflora, using Maximum Entropy Model (MaxEnt). Input data of the model are locations of pine tree stands and their environmental variables such as climate were prepared for the model inputs. Alternative future projections for P. densiflora distribution were conducted with RCP 4.5 and RCP 8.5 climate change scenarios. As results, the future distribution of P. densiflora steadily decreased under both scenarios. In the case of RCP 8.5, the areal reductions amounted to 11.1% and 18.7% in 2050s and 2070s, respectively. In 2070s, P. densiflora mainly remained in Kangwon and Gyeongsang Provinces. Changes in temperature seasonality and warming winter temperature contributed primarily for the decline of P. densiflora., in which altitude also exerted a critical role in determining its future distribution geographic vulnerability. The results of this study highlighted the temporal and spatial contexts of P. densiflora decline in Korea that provides useful ecological information for developing sound management practices of pine forests.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.112-115
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as support vector machine neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the monthly precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 2 grid points including $127.5^{\circ}E/35^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, which produced the best results from the previous study. The output node of neural networks models consist of the monthly precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of SVM-NNM and MLP-NNM performances for the downscaling of the monthly precipitation data. We should, therefore, construct the credible monthly precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.