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Improved daily precipitation estimations were attempted using the parameter-elevation regressions on a parameter-elevation regression on independent slopes model (PRISM) with inverse-distance weighting (IDW) and a precipitation-masking algorithm for precipitation areas. The PRISM (PRISM_ORG) suffers two overestimation problems when the daily precipitation is estimated: overestimation of the precipitation intensity in mountainous regions and overestimation of the local precipitation areas. In order to solve the problem of overestimating the precipitation intensity, we used the IDW technique that employs the same input stations as those used in the PRISM regression (PRISM_IDW). A precipitation-masking algorithm that selectively masks the precipitation estimation grid points was additionally applied to the PRISM_IDW results (PRISM_MSK). For 6 months from March to August 2012, daily precipitation data were produced in a horizontal resolution of 1 km based on the above two experiments and PRISM_ORG. Afterwards, each experiment was evaluated for improvements. The monthly root mean squared errors (RMSEs) of PRISM_IDW and PRISM_MSK were reduced by 0.83 mm/day and 0.86 mm/day, respectively, compared to PRISM_ORG.

This study investigates the added value of very high resolution in long-term climate simulations over South Korea using the Weather Research and Forecasting (WRF) model. A one-way double-nested modeling system consisting of a mother domain (20-km resolution) and nested domain (5-km resolution) is customized for simulating the distinct climatological patterns in Korea, where the region-specific climate is largely influenced by the area’s complex geographical features. The ERA-Interim reanalysis data are used for the initial and boundary conditions, and the simulation spans the period from December 1, 1985 to December 31, 2005 (20-year analysis period with 1-month spin-up). Simulations from both the mother and the nested domain show reasonable performance in capturing the general characteristics of summer temperature and precipitation in terms of temporally and spatially averaged quantities. However, the added value from the nested domain with its higher resolution is apparently found in the reproduction of the intensity and frequency of extreme events and in the physical realism related to the partitioning of convective and large-scale precipitation. The nested domain not only better resolves the sharp gradients of temperature variation over short distances but also substantially reduces the systematic cold bias seen in temperature extremes produced by the mother domain. Furthermore, the nested domain is better able to simulate the upper tail of precipitation distributions and thus of extreme events. The higher resolution also improves the simulation of partitioning between convective and large-scale precipitation, leading to a plausible relationship between extreme precipitation and temperature and showing good agreement with in situ observation. Given the different behaviors of convective and large-scale precipitation in response to temperature changes, their realistic partitioning in the model has important potential for enhancing the reliability of precipitation projection under global warming.

This study was estimated harvest date of corn in South Korea based on the temperature index called the accumulated temperature. The accumulated temperature was calculated using observed daily mean temperature. We assumed a unified seeding date, 5 April, across the South Korea. The daily mean temperatures from 61 weather stations provided by the Korean Meteorological Administration were obtained for the period 2009-2018 (10 years). We used 1,650℃ as the criterion of the accumulated temperature to identify harvest date of corn for early-cultivated variety. The accumulated temperature over the most areas generally meted the criterion (1,650℃) in early July. In case of 2018, 66% area of Gang-won province, major corn producer, become suitable to harvest corn in July, peaking in the middle July (51%). The harvest date has been accelerating due to increase in daily mean temperature during the recent 10 years. This study infers that changes in farming activities are needed through reflecting the environmental change. Acknowledgements: This study was carried out with the support of “Research Program for Agricultural Science & Technology Development (Project No. PJ014882)”, National Institute of Agricultural Sciences, Rural Development Administration, Republic of Korea.

Conventional process-based crop simulation models and agro-land surface models require numerous forcing variables and input parameters. The regional application of these crop simulation models is complicated by factors concerning input data requirements and parameter uncertainty. In addition, the empirical remotely sensed regional scale crop yield estimation method does not enable growth process modeling. In this study, we developed a process-based rice yield estimation model by integrating an assimilate allocation module into the satellite remote sensing-derived and biophysical process-based Breathing Earth System Simulator (BESS). Normalized accumulated gross primary productivity ( G P P n o r m - a c c u ) was used as a scaler for growth development, and the relationships between G P P n o r m - a c c u and dry matter partitioning coefficients were determined from the eddy covariance and biometric measurements at the Cheorwon Rice paddy KoFlux site. Over 95% of the variation in the dry matter allocation coefficients of rice grain could be explained by G P P n o r m - a c c u . The dynamics of dry matter distribution among different rice components were simulated, and the annual grain yields were estimated. BESS-Rice simulated GPP and dry matter partitioning dynamics, and rice yields were evaluated against in-situ measurements at three paddy rice sites registered in KoFlux. The results showed that BESS-Rice performed well in terms of rice productivity estimation, with average root mean square error (RMSE) value of 2.2 g C m−2 d−1 (29.5%) and bias of –0.5 g C m−2 d−1 (–7.1%) for daily GPP, and an average RMSE value of 534.8 kg ha−1 (7.7%) and bias of 242.1 kg ha−1 (3.5%) for the annual yield, respectively. BESS-Rice is much simpler than conventional crop models and this helps to reduce the uncertainty related to the forcing variables and input parameters and can result in improved regional yield estimation. The process-based mechanism of BESS-Rice also enables an agronomic diagnosis to be made and the potential impacts of climate change on rice productivity to be investigated.

Predicting phenology, the timing of developmental events, is critical for understanding how plants respond to the changing climate. Many prediction models have been developed during the last decades, but their use has been limited because of incomplete understanding of internal processes and lack of observation datasets needed for calibration and validation. Dependency on species and locations further complicates the model selection procedure which is an essential part of phenology predictions. To overcome the limitations raised by using a single model, we propose a multi-model ensemble that simplifies model selection and provides competitive performance. We hypothesize that 1) no single individual model consistently outperforms the others and 2) an ensemble model performs equally as or better than any individual models. Nine individual models based on the concept of thermal-time accumulation and their ensembles were cross-validated with 137 datasets of four species collected from multiple locations and years in the United States and South Korea. Non-parametric tests concluded that the performance of a simple mean ensemble model was as good as the best individual model and outperformed the others. Differences between individual models were not statistically significant. The use of ensemble, however, does not preclude any bias in the interpretation caused by characteristics of the underlying models. When the ensemble was classified into groups: 1) with and 2) without chilling components, to assess spring phenology of flowering cherry species in the long-term projections, the predictions of two ensemble groups diverged considerably under RCP8.5 scenario. Our results suggest that a simple ensemble model can be a good phenology prediction tool for avoiding the pitfalls of model selection and reducing inherent uncertainties in climate change studies, but also highlight the importance of implementing the underlying mechanisms of key physiological processes into individual models used in an ensemble.

This study investigates the performance of the latest version of RegCM4 in simulating summer precipitation over South Korea, comparing nine sensitivity experiments with different combinations of convective parameterization schemes (CPSs) between land and ocean. In addition to the gross pattern of seasonal and monthly mean precipitation, the northward propagation of the intense precipitation band and statistics from extreme daily precipitation are thoroughly evaluated against gridded and in situ station observations. The comparative analysis of 10-year simulations demonstrates that no CPS shows superiority in both quantitative and qualitative aspects. Furthermore, a nontrivial discrepancy among the different observation datasets makes a robust assessment of model performance difficult. Regardless of the CPS over the ocean, the simulations with the Kain–Fritsch scheme over land show a severe dry bias, whereas the simulations with the Tiedtke scheme over land suffer from a limited accuracy in reproducing spatial distributions due to the excessive orographic precipitation. In general, the simulations with the Emanuel scheme over land are better at capturing the major characteristics of summer precipitation over South Korea, despite not all statistical metrics showing the best performance. When applying the Emanuel scheme to both land and the ocean, precipitation tends to be slightly overestimated. This deficiency can be alleviated by using either the Tiedtke or Kain–Fritsch schemes over the ocean instead. As few studies have applied and evaluated the Tiedtke and Kain–Fritsch schemes to the Korean region within the RegCM framework, and this study introduces the potential of these new CPSs compared with the more frequently selected Emanuel scheme, which is particularly beneficial to RegCM users.

Accurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem exchange (NEE) of CO2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPPEC) and ecosystem respiration. In this study, we first used the GPPEC data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPPEC, which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPPVPM). The 14 site-years of simulations show that the seasonal dynamics of GPPVPM successfully tracked the seasonal dynamics of GPPEC (R2 > 0.88 or higher). The cross-site comparison also shows that GPPVPM agreed reasonably well with the variations of GPPEC across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world.

The change of extreme precipitation is assessed with the HadGEM2-AO - 5 Regional Climate Models (RCMs) chain, which is a national downscaling project undertaken cooperatively by several South Korean institutes aimed at producing regional climate change projection with fine resolution (12.5 km) around the Korean Peninsula. The downscaling domain, resolution and lateral boundary conditions are held the same among the 5 RCMs to minimize the uncertainties from model configuration. Climatological changes reveal a statistically significant increase in the mid-21st century (2046- 2070; Fut1) and the late-21st century (2076-2100; Fut2) precipitation properties related to extreme precipitation, such as precipitation intensity and average of upper 5 percentile daily precipitation, with respect to the reference period (1981-2005). Changes depending on the intensity categories also present a clear trend of decreasing light rain and increasing heavy rain. In accordance with these results, the change of 1-in-50 year maximum precipitation intensity over South Korea is estimated by the GEV method. The result suggests that the 50-year return value (RV50) will change from -32.69% to 72.7% and from -31.6% to 96.32% in Fut1 and from -31.97% to 86.25% and from -19.45% to 134.88% in Fut2 under representative concentration pathway (RCP) 4.5 and 8.5 scenarios, respectively, at the 90% confidence level. This study suggests that multi-RCMs can be used to reduce uncertainties and assess the future change of extreme precipitation more reliably. Moreover, future projection of the regional climate change contains uncertainties evoked from not only driving GCM but also RCM. Therefore, multi-GCM and multi-RCM studies are expected to provide more robust projection.

Mid-season drainage (MSD) decreases methane emission from an irrigated rice paddy. For this reason, the 2006 IPCC Guidelines and several methane estimation models consider MSD as a static input factor. However, if rainfall occurs during the MSD period, the reduction effect on methane emission may become small. In this paper, we report the methane emission from an intermittently irrigated rice paddy with MSD for three growing seasons. Methane flux was measured using eddy covariance technique with an open-path methane analyzer. Our objective is to ascertain the seasonal and interannual variations in methane emission caused by rainfalls during the MSD period. The growing season (from June to Oct.) methane emission during the three year study period ranged from 198 to 450 kg CH 4 ha −1 , showing significant interannual variability with changes in rainfall during the MSD period. In order to implement the effect of rainfall during the MSD on methane emission (not considered in the IPCC method), we developed a simple method for a scaling factor. The estimated and the observed CH 4 emissions agreed within 40%, and additional consideration of soil pH further improved the agreement within 10%. These results suggest that the rainfall effect should be considered when estimating national or global methane emission from irrigated rice paddies.

A shift of first fowering date (FFD) of spring blossoms (cherry, peach and pear) over the northest Asia under global warming is investiaged using dynamically downscaled daily temperature data with 12.5 km resolution. For the study, we obatained gridded daily data with Historical (1981~2010), and Representative Concentration Pathway (RCP) (2021~2100) 4.5 and 8.5 scenarios which were produced by WRFv3.4 in conjunction with HadGEM2-AO. A change on FFDs in 21st century is estimated by applying daily outputs of WRFv3.4 to DTS phonological model. Prior to projection on future climate, the performances of both WRFv3.4 and DTS models are evaluated using spatial distribution of climatology and SCR diagram (Normalized standard deviation-Pattern correlation coefficient-Root mean square difference). According to the result, WRFv3.4 and DTS models well simulated a feature of the terrain following characteristics and a general pattern of observation with a marigin of and 5~6 days. The analysis reveals a projected advance in FFDs of cherry, peach and pear over the northeast Asia by 2100 of 15.4 days (9.4 days). 16.9 days (10.4 days) and 15.2 days (9.5 days), respectively, compared to the Historical simulation due to a increasing early spring (Februrary to April) temperature of about () under the RCP 8.5 (RCP 4.5) scenarios. This indicates that the current flowering of the cherry, peach and pear over analysis area in middle or end of April is expected to start blooming in early or middle of April, at the end of this century. The present study shows the dynamically downscaled daily data with high-resolution is helpeful in offering various useful information to end-users as well as in understanding regional climate change.

To improve the practicality of 'Early warning service about agrometeorological weather hazards' and operation efficiency to deliver site-specific about a lot of land unit possibility of weather hazard occurrence with the suitable counterplan to farmer, site-specific early warning service system that was built at the National Academy of Agricultural Science in Korea passed some of the error supplementation and service's stabilization stage during operation period for trial services from October 2014 to March 2015. Field service system covered about 470 volunteered farmer and 950 lots in Seomjin river downstream areas (part of Gwangyang-si, Hadong-gun, Gurye-gun). This system (Two track system) consists of early warning system (a lot of land unit) to inform farmer by individual text message and dispersal prior alert system that can see the jurisdiction's situation of local government. Individual text message about Seomjin river downstream that is our first study area was launched since March 2015, and online site (http://www.agmet.kr) started business since April 2015. Service offers currently information of farm weather, farm weather hazard, nationwide weather risk and special weather alert, also our system will consistently expand the service target area and contents and improve the service quality until 2017 when our study finished. To prevent crops damage that was caused by crisis situation like farm weather and weather damage offer prior alert about agrometeorological weather harzard to volunteered farmer, thereby our study expects to help the reduction of farm's damage caused by weather derivatives.

Fuji apple variety introduced in Japan has excellent storage quality and good taste so it is most commonly cultivated in the Korean Peninsula. Accurate prediction of harvest maturity allows farmers to more efficiently manage their farm, such as working time, fruit storage, market shipment and labor distribution so it is very important. This study was carried out to predict the harvest maturity of 'Fuji' apple using DTS (Days Transformed to Standard temperature) model based on the Arrhenius law in the Gunwi province of the South Korea. Input data are daily average temperature and apple harvest maturity. Predicted the harvest maturity of Fuji apple after estimating the optimal parameters by using the Nelder-Mead method. The differences of observed and predicted harvest maturity day are approximately 1 to 4 days and the RMSE is 2.9.

A drought index with respect to the spatio-temporal scale was developed in response to the demand from the agricultural sector in South Korea. The new drought index was calculated based on the soil water balance between the supply and demand of water. The water supply was estimated using the cumulative effective precipitation weighted by the precipitation from two months prior. The water demand was derived from the actual evapotranspiration, which was calculated by applying a crop coefficient to the reference evapotranspiration. The amount of surface runoff on a given soil type was used to calculate the residual soil moisture. The presence of drought was determined based on the probability distribution in the given area. In order to assess the reliability of this index, termed the Agricultural Drought Index (ADI), the amount of residual moisture, which represents the severity of a drought, was compared to the measurements of soil moisture at three experimental sites between July 2012 and December 2013. The results showed that the ADI had greater correlation with measured soil moisture than did the Standardized Precipitation Index (SPI), suggesting that the ADI is a useful indicator of drought. While both the SPI and ADI showed similar trends in the temporal variation of drought conditions at all of the sites, the ADI better detected ‘severe drought’ than did the SPI. The daily relief of severe drought due to precipitation was also better represented by the ADI. Using the high-resolution climatic and spatial data of a small watershed, we produced 270m resolution maps of ADI from week 36 through week 41 of 2013, demonstrating the feasibility of the ADI as an operational drought monitor appropriate for the agricultural environment of South Korea.

When the midday temperature distribution in a mountainous region was estimated using data from a nearby weather station, the correction of elevation difference based on temperature lapse caused a large error. An empirical approach reflecting the effects of solar irradiance and advection was suggested in order to increase the reliability of the results. The normalized slope irradiance, which was determined by normalizing the solar irradiance difference between a horizontal surface and a sloping surface from 1100 to 1500 LST on a clear day, and the deviation relationship between the horizontal surface and the sloping surface at the 1500 LST temperature on each day were presented as simple empirical formulas. In order to simulate the phenomenon that causes immigrant air parcels to push out or mix with the existing air parcels in order to decrease the solar radiation effects, an advection correction factor was added to exponentially reduce the solar radiation effect with an increase in wind speed. In order to validate this technique, we estimated the 1500 LST air temperatures on 177 clear days in 2012 and 2013 at 10 sites with different slope aspects in a mountainous catchment and compared these values to the actual measured data. The results showed that this technique greatly improved the error bias and the overestimation of the solar radiation effect in comparison with the existing methods. By applying this technique to the Korea Meteorological Administration’s 5-km grid data, it was possible to determine the temperature distribution at a 30-m resolution over a mountainous rural area south of Jiri Mountain National Park, Korea.

Dynamically downscaled agro-climates for present (1981–2010) and future (2071–2100) climates under Representative Concentration Pathways (Historical, RCP4.5, and RCP8.5) in Northeast Asia (118°–138°E, 30°–45°N) are analysed in terms of the indices, such as vegetable and crop periods, frost days, and the climatic yield potential (CYP) for Japonica type rice (hereafter, rice). The model employed for dynamical downscaling is the Weather Research and Forecasting (WRF), with a 12.5-km horizontal grid spacing in the domain. According to our results, the CYP for rice, one of the major crops presently cultivated in the area, is expected to decrease throughout most of the region, despite a projected expansion of both vegetable and crop periods. This is projected to occur particularly in South Korea, Japan, and Southeast and Northeast China. Such a change is related to the projected rise in temperature within these regions, which will exceed the grain-filling optimum temperature of rice. In contrast, the climate projection of the RCPs is that the CYP will increase over northeastern parts of the Korean Peninsula and the Russian Far Eastern region (Primorsky), because temperatures in these regions are expected to rise and approach the grain-filling optimum temperature. For the RCPs, the optimum heading date, on which the domain averaged CYP is the highest, is expected to be later than that of the Historical by approximately 17–24 days. In addition, the maximum CYP in the RCPs is projected to decrease compared with that of the historical, and the possible period of rice ripening (period in which the CYP is greater than 0) is also expected to decrease.

CH4 is a trace gas and one of the key greenhouse gases, which requires continuous and systematic monitoring. The application of eddy covariance technique for CH4 flux measurement requires a fastresponse, laser-based spectroscopy. The eddy covariance measurements have been used to monitor CO2 fluxes and their data processing procedures have been standardized and well documented. However, such processes for CH4 fluxes are still lacking. In this note, we report the first measurement of CH4 flux in a rice paddy by employing the eddy covariance technique with a recently commercialized wavelength modulation spectroscopy. CH4 fluxes were measured for five consecutive days before and after the rice transplanting at the Gimje flux monitoring site in 2012. The commercially available EddyPro TM program was used to process these data, following the KoFlux protocol for data-processing. In this process, we quantified and documented the effects of three key corrections: (1) frequency response correction, (2) air density correction, and (3) spectroscopic correction. The effects of these corrections were different between daytime and nighttime, and their magnitudes were greater with larger CH4 fluxes. Overall, the magnitude of CH4 flux increased on average by 20-25% after the corrections. The National Center for AgroMeteorology (www.ncam.kr) will soon release an updated KoFlux program to public users, which includes the spectroscopic correction and the gap-filling of CH4 flux.

National Academy of Agricultural Science, RDA, Wanju 565-851, Korea(Received September 2, 2014; Revised November 11, 2014; Accepted November 12, 2014)ABSTRACTAir temperature has increased, while sunshine hour has decreased during the grain filling period ofmost rice cultivars (August to September) during the past 12 years from 2001 through 2012 in Korea.Climatic Productivity Index (CPI) has fallen because of the decreased sunshine hour and increased airtemperature during the grain filling period, and the degree of reduction was greater with earlierheading. For stable rice production, we will need to delay the heading of rice as a cultivation measureagainst the future climatic trend. Grain yield showed no significant trend for past 12 years. However,the year to year change in grain yield showed a similliar pattern with that of CPI. Especially, a linearfunction relating rice yield to CPI explained approximately 63% of variation in grain yield with theheading date of August 11

Rice-barley double cropping system is typical in southwestern part of South Korea. However, the information of carbon dioxide (CO2) exchange for barley growing season has still limited in comparison with rice. Using the eddy covariance (EC) technique, seasonal variation of CO2 exchange was analyzed for the barley growing season at a rice-barley double cropping field in Gimje, Korea. The effects of environmental factors and biomass on the CO2 flux also were investigated. Quality control and gap-filling of flux data were conducted before this analysis and investigation. The results indicated that CO2 uptake increased rapidly at tillering stage and maximum net ecosystem exchange of CO2 (NEE) occurred at the early of May, 2012 (-11.2g C m −2 d), when the heading of barley occurred. NEE, gross primary production (GPP), and ecosystem respiration (Re) during the barley growing season were -348.0, 663.3, and 315.2 g C m, respectively. In this study, an attempt has been made to measure NEE, GPP, and Re with the help of the EC system for the barley growing season for the first time in Korea, focusing on CO2 exchange between the biosphere and the atmosphere.

Based on the results of continuous flux measurements at the Gimje paddy flux site in the southwestern coast of Korea, carbon dioxide and energy exchanges between customarily cultivated rice-barley double cropping paddy field and the atmosphere during the 2012 rice growing season (from 9 th Jun. 2012 through 20 th Oct. 2012) were analyzed. Carbon dioxide and energy (H, LE) fluxes were estimated by the eddy covariance method. Environmental parameters (net radiation, precipitation, etc.) and plant biomass (LAI, plant height, etc.) were measured along with fluxes. After the quality control and gap-filling, the observed fluxes were analyzed. The results have been showed that net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (Re) during the rice cropping period were -277.1, 710.3, and 433.2 g C m �2 , respectively.

In this study, the installation effects of a windbreak net on reducing wind speed were examined using meteorological observation data. Three automatic weather systems (AWS) were installed at the inside of the windbreak net of an apple orchard along the distance, and one AWS was located at the outside. They were set up on Oct. 25 th , 2012 at the apple orchard of Geochang County, and meteorological data, which were observed at four stations for about 1 year from October 26, 2012 through October 21, 2013, were used for this study. Meteorological variables include air temperature & relative humidity at a height of 1.5 meter, and wind speed & wind direction at a height of 2 meter and 4 meter. These variables were measured and recorded every 60 seconds. The preliminary results of this study was as follows: (1) Daily mean temperature at the inside of the windbreak net was lower than that of the outside by 0.1 through 0.2 o C. (2) Daily mean relative humidity at the inside of the windbreak net was higher than that of the outside by 0.7 through 1.7%. (3) As compared to the outside, northerly daily maximum wind speed of the inside of the windbreak net at a height of 2 and 4 meter was reduced by 0.7~1.5 ms �1 (30.4~65.2%) and 0.3~0.7 ms �1 (10.3~24.1%), respectively.

Simulations from six global climate models participating in Coupled Model Intercomparison Project 5 are used to project future changes in regional early spring (February–April) temperature and in cherry (Prunus yedoensis) first-flowering date (FFD) over South Korea in order to investigate a potential plant growth response to local climate change. For the study, we statistically downscale daily Historical (1986–2005), RCP4.5 (2071–2090), and RCP8.5 (2071–2090) gridded model data to 59 cherry FFD observation sites over South Korea. In order to reduce the uncertainties in the model simulation produced by a single model, multi-model ensemble (MME) is performed after eliminating the mean systematic bias of each model. A shift of cherry FFD under global warming is estimated and compared with the observation and Historical simulation by applying the downscaled data to a DTS phenological model. The analysis reveals a projected advance in cherry FFD over South Korea by 2090 of 6.3 and 11.2 days compared to the current dates due to a rising mean temperature of about 2.0 and 3.5 K under the RCP4.5 and RCP8.5 scenarios, which approximately correspond to moving north at a speed of 0.01 and 0.03oN year−1, respectively. These average yearly advances (0.07 and 0.13 days year−1) of cherry FFD in the RCP4.5 and RCP8.5 simulations are 0.22 and 0.16 days year−1 lower, respectively, than the value of 0.29 days year−1 derived in previous studies with the SRES A2 scenario. Regardless of the difference between the SRES A2 and RCP8.5 scenarios, the discrepancy in the advancement tendency was primarily attributed to the inability of the previous studies to eliminate the systematic model biases, which led to overestimation of both the temperature and the FFD changes.

In this study, in order to provide an information for artificial cultivation of wild mushroom, the meteorological effects on wild mushroom appearance were examined using daily meteorological observations in Chiak National Park. The survey of wild mushroom appearance was carried out once a month from June to October. Under high temperature and humidity conditions in July and August, the appearance of wild mushroom was frequent. In contrast, lower number of wild mushroom appeared in October. Wild mushroom appearance was affected by solar radiation, relative humidity, precipitation, and soil water content whereas the impact of air and soil temperature was lower than that of other meteorological elements.

Accuracy of daily solar radiation estimated from a Mountain Microclimate Simulation Model (MT-CLIM) was assessed for seven observation sites with complex topography in Uiseong County. The coefficient of determination () between the observed and the estimated daily solar radiation was 0.52 for 7 sites for the study period from 1 August to 30 September 2009. Overall, the MT-CLIM overestimated the solar radiation with root mean square error (RMSE) of which is about 25% of the mean daily solar radiation () for the study period. Considering that the pyranometer`s tolerance is of standard sensor, the RMSE of MT-CLIM was too large to accept for a direct application for agricultural sector. The reliability of solar radiation estimated by MT-CLIM must be improved by considering additional ways such as using a topography correction coefficient.

The objective of this study was to estimate rice yield in Korea using satellite and meteorological data such as sunshine hours or solar radiation, and rainfall. Terra and Aqua MODIS (The MOderate Resolution Imaging Spectroradiometer) products; MOD13 and MYD13 for NDVI and EVI, MOD15 and MYD15 for LAI, respectively from a NASA web site were used. Relations of NDVI, EVI, and LAI obtained in July and August from 2000 to 2011 with rice yield were investigated to find informative days for rice yield estimation. Weather data of rainfall and sunshine hours (climate data 1) or solar radiation (climate data 2) were selected to correlate rice yield. Aqua NDVI at DOY 233 was chosen to represent maximum vegetative growth of rice canopy. Sunshine hours and solar radiation during rice ripening stage were selected to represent climate condition. Multiple regression based on MODIS NDVI and sunshine hours or solar radiation were conducted to estimate rice yields in Korea. The results showed rice yield of 494.6 kg 10a -1 and 509.7 kg 10a -1 in 2011, respectively and the difference from statistics were 1.1 kg 10a -1 and 14.1 kg 10a -1 , respectively. Rice yield distributions from 2002 to 2011 were presented to show spatial variability in the country.

This study was conducted to assess emissions in agricultural soils of Korea. According to 1996 and 2006 IPCC (Intergovernmental Panel on Climate Change) methodology, emission was calculated the sum of direct emission () and indirect emission (). To calculate emissions, emission factor was used default of IPCC and activity data was used the food, agricultural, forestry and fisheries statistical yearbook of MIFAFF (Ministry for Food, Agriculture, Forestry and Fisheries). It was emitted 8,608 Mg resulted from direct emission by application of chemical fertilizer and animal manure, input in n-fixation crops and input of crop residues and emissions converted into equivalent was 2,668 -eq Gg. Indirect emission as (atmospheric deposition of and ) and (leaching and runoffs) were 4,567 and 6,013 Mg and emissions converted into equivalent were 1,416 and 1,864 -eq Gg, respectively. Total emission in Korea agricultural soil in 2009 was 5,948 -eq Gg.

This study was conducted to compare of greenhouse gas emissions between 1996 and 2006 IPCC (Intergovernmental Panel on Climate Change) guidelines change. Greenhouse gas emissions were calculated separately by rice cultivation, agricultural soils and field burning of agricultural residues from 2000 to 2008 according to 1996 and 2006 IPCC guidelines. To calculate greenhouse gas emissions, emission factor and activity data were used IPCC default value and the food, agricultural, forestry and fisheries statistical yearbook of MIFAFF (Ministry for Food, Agriculture, Forestry, and Fisheries). The greenhouse emissions by 1996 IPCC guidelines were highest in rice cultivation as 4,008 -eq Gg of 2000 and 3,558 -eq Gg of 2008. The emissions by N-fixing crops, crop residues returned soils and field burning did not much affect the total emissions. emissions by urea and lime were calculated by adding in 2006 IPCC guidelines and its emissions were 157 and 82 -eq Gg in 2008 respectively. The emissions by N-fixing crops, crop residues returned to soils and field burning, in common with 1996 IPCC guidelines, did not have a significant impact on total emissions. The total emissions in agronomic sector was decreased continuously from 2000 to 2008 and annual emissions by 2006 IPCC guidelines were approximately 26-29% less than the 1996 IPCC guidelines.

The CERES-Barley crop simulation model was used to assess the impacts of climate change on the potential yield of winter naked barley in Korea. Fifty six sites over the southern part of the Korean Peninsula were selected to compare the climate change impacts in various climatic conditions. Based on the A1B climate change scenarios of Korea, the present climatological normal (1971-2000) and the three future ones (2011-2040, 2041-2070, and 2071-2100) were considered in this study. The three future normals were divided by three environmental conditions with changes in: (1) temperature only, (2) carbon dioxide concentration only, and (3) both temperature and carbon dioxide concentration. The agreement between the observed and simulated outcomes was reasonable with the coefficient of determination of grain yield to be 0.78. We concluded that the CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter naked barley. The effect of the increased temperature only with the climate change scenario was negative to the potential yield of winter naked barley, which ranges from -34 to -9% for the three future normals. However, the effect of the elevated carbon dioxide concentration only on the potential yield of winter naked barley was positive, ranging from 6 to 31% for the three future normals. For the elevated conditions of both temperature and carbon dioxide concentration, the potential yields increased by 8, 15, and 13% for the 2011-2040, 2041-2070, and 2071-2100 normals, respectively.

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the -doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double climate. Thus, it is suggested that the future doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

A regional climate model (RCM) can be a powerful tool to enhance spatial resolution of climate and weather information (IPCC, 2001). In this study we conducted dynamical downscaling using Weather Research and Forecasting Model (WRF) as a RCM in order to obtain high resolution regional agroclimate indices over the Korean Peninsula. For the purpose of obtaining detailed high resolution agroclimate indices, we first reproduced regional weather for the period of March to June, 2002-2008 with dynamic downscaling method under given lateral boundary conditions from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data. Normally, numerical model results have shown biases against observational results due to the uncertainties in the modelis initial conditions, physical parameterizations and our physical understanding on nature. Hence in this study, by employing a statistical method, the systematic bias in the modelis results was estimated and corrected for better reproduction of climate on high resolution. As a result of the correction, the systematic bias of the model was properly corrected and the overall spatial patterns in the simulation were well reproduced, resulting in more fine-resolution climatic structures. Based on these results, the fine-resolution agro-climate indices were estimated and presented. Compared with the indices derived from observation, the simulated indices reproduced the major and detailed spatial distributions. Our research shows a possibility to simulate regional climate on high resolution and agro-climate indices by using a proper downscaling method with a dynamical weather forecast model and a statistical correction method to minimize the model bias.

The increase in average air temperature over the past 100 years in northern Asia including Korea is the greatest (about ) among the various regions of the world. Considering a further warming projected by the IPCC, fluctuations of agro-climatic indices under climate change must precede an evaluation of vulnerability. The purpose of this study is to analyze how climate changes represented by global warming have altered agro-climatic indices in Korea over various time scales. Drought index during the rice-transplanting period of 15 May to 5 June has changed toward the favorable with recently increased precipitation in the Taebaek Alpine and Semi-Alpine Zone, and Yeongnam Basin and Inland Zone. The frequency of low temperature occurrence below during the rice transplanting has decreased, while climatic production index (CPI) has fallen because of the decreased sunshine hour and increased temperature during the rice ripening period. We therefore concluded that the recent change of climate conditions was against the rice productivity in Korea.

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.