[논문]PNU CGCM-WRF Chain을 이용한 우리나라 콩의 고온해 및 저온해에 대한 예측성 검증

최명주; 안중배; 김영현; 정민경; 심교문; 허지나; 조세라

doi:10.5532/kjafm.2022.24.4.218

PNU CGCM-WRF Chain을 이용한 우리나라 콩의 고온해 및 저온해에 대한 예측성 검증
Evaluating the Predictability of Heat and Cold Damages of Soybean in South Korea using PNU CGCM -WRF Chain 원문보기

한국농림기상학회지 = Korean Journal of Agricultural and Forest Meteorology, v.24 no.4, 2022년, pp.218 - 233

최명주 (부산대학교 BK21 지구환경시스템 교육연구단 대기환경과학과) , 안중배 (부산대학교 대기환경과학과) , 김영현 (부산대학교 대기환경과학과) , 정민경 (부산대학교 BK21 지구환경시스템 교육연구단 대기환경과학과) , 심교문 (국립농업과학원 기후변화평가과) , 허지나 (국립농업과학원 기후변화평가과) , 조세라 (국립농업과학원 기후변화평가과)

초록
AI-Helper

본 연구에서는 Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF)에서 생산된 hindcast 자료(1986~2020)를 이용하여 우리나라의 주요 곡물 중 하나인 콩의 생육단계별 고온해 및 저온해 발생일수의 예측성을 평가하였다. 예측성을 평가하는 방법으로는 Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), Heidke Skill Score (HSS)이다. 이를 위해 먼저 콩의 고온해 및 저온해를 정의하는 변수인 일 최고기온(Tmax) 및 일 최저기온(Tmin)의 모의성능을 검증하였다. 그 결과 1~5월(01RUN~05RUN)의 초기조건을 가지고 시작하는 월에 따라 다소 차이가 있지만, Variance Scaling 방법을 적용하여 보정한 결과가 보정전보다 관측과 유사하게 나타났으며, 보정한 3~10월의 Tmax 및 Tmin에 대한 모의성능은 전반적으로 01RUN~05RUN에 Simple Composite Method (SCM)을 적용하여 평균한 결과(ENS)에서 높게 나타났다. 또한, 콩의 생육시기별 고온해 및 저온해 발생일수의 지역적 패턴과 특성을 관측과 비교하였을 때 모형이 잘 모의하고 있다. ENS에서 콩의 고온해(저온해)에 대한 HR과 HSS는 생육시기 별로 0.45~0.75, 0.02~0.10(0.49~0.76, -0.04~0.11)의 범위를 가진다. 결론적으로, PNU CGCM-WRF chain의 01RUN~05RUN 및 ENS는 우리나라 콩의 생육시기별 고온해 및 저온해를 예측할 수 있는 성능을 가지고 있다.

Abstract ▼ AI-Helper

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

주제어

표/그림 (14)

그림 Fig. 1. The locations of ASOS in South Korea and topography heights (in meters) of the WRF domain.
표 Table 1. Description of PNU-CGCM
그림 Fig. 2. Lead-times in 8-month lead hindcast experiment. Left column indicates initialized month and top line indicates predicted month. Lead2~7 (dark apricot shaded) are dynamically downscaled by WRF.
표 Table 2. WRF configuration used in this study
표 Table 3. Threshold of cold and heat damages in soybean by growth stage
표 Table 4. Definition of symbols and sub-/superscripts used in text
표 Table 5. The computational formula of HR (Hit Rate), HSS (Heidke Skill Score)
그림 Fig. 3. Mean Normalized Standard Deviations (NSD) and Root Mean Square Error (RMSE) for daily maximum temperature (Tmax) in (a) March, (b) April, (c) May, (d) June, (e) July, (f) August, (g) September, (h) October and for daily minimum temperature (Tmin) in (i) March, (j) April, (k) May, (l) June, (m) July, (n) August, (o) September, (p) October. Circles (Triangle) of red, purple, blue, green, yellow and black are Tmax_ORG and Tmin_ORG (Tmax_VS and Tmin_VS) of 01RUN, 02RUN, 03RUN, 04RUN, 05RUN, and ENS. Tmax_VS (Tmin_VS) is the value obtained by correcting Tmax_ORG (Tmin_ORG) through the Variance Scaling method.
그림 Fig. 4. Spatial distribution of number of days of heat damage in soybean during Flowering Stage (top), Maturation Period Stage (bottom). The values at the top right of each figure are mean number of days of heat damage.
그림 Fig. 5. Spatial distribution of number of days of cold damage in soybean during Floral Initiation Stage (top), Flowering Stage (middle) and Maturation Period Stage (bottom). The values at the top right of each figure are mean number of days of cold damage.
그림 Fig. 6. Spatial distribution of Hit Rate for heat damage in soybean during Flowering Stage (top), Maturation Period Stage (bottom). The values at the top right of each figure are mean Hit Rate of 72 stations. Black (x-marked) stations are points where no heat damage occurred during the 35-year analysis period for both observations and models (Excluded from the average value of South Korea).
그림 Fig. 7. Spatial distribution of Heidke Skill Score for heat damage in soybean during Flowering Stage (top), Maturation Period Stage (bottom). The values at the top right of each figure are mean Heidke Skill Score of 72 stations. Black (x-marked) stations are points where no heat damage occurred during the 35-year analysis period for both observations and models (Excluded from the average value of South Korea).
그림 Fig. 8. Spatial distribution of Hit Rate for cold damage in soybean during Floral Initiation Stage (top), Flowering Stage (middle) and Maturation Period Stage (bottom). The values at the top right of each figure are mean Hit Rate of 72 stations. Black (x-marked) stations are points where no cold damage occurred during the 35-year analysis period for both observations and models (Excluded from the average value of South Korea).
그림 Fig. 9. Spatial distribution of Heidke Skill Score for cold damage in soybean during Floral Initiation Stage (top), Flowering Stage (middle) and Maturation Period Stage (bottom). The values at the top right of each figure are mean Heidke Skill Score of 72 stations. Black (x-marked) stations are points where no cold damage occurred during the 35-year analysis period for both observations and models (Excluded from the average value of South Korea).

참고문헌 (62)

Ahn, J.-B., and J.-A. Lee, 2001: Numerical study on？the role of sea-ice using ocean general circulation？model. The Sea: Journal of the Korean Society of？Oceanography 6(4), 225-233. (in Korean with English？abstract)
Ahn, J.-B., and J.-L. Lee, 2015: Comparative Study？on the Seasonal Predictability Dependency of？Boreal Winter 2m Temperature and Sea Surface？Temperature on CGCM Initial Conditions. Atmosphere？25(2), 353-366. doi:10.14191/Atmos.2015.25.2.353？(in Korean with English abstract)

원문보기 상세보기
Ahn, J.-B., and J.-L. Lee, and S. R. Jo, 2018a:？Evaluation of PNU CGCM Ensemble Forecast？System for Boreal Winter Temperature over South？Korea. Atmosphere 28(4), 509-520. doi:10.14191/Atmos.2018.28.4.509 (in Korean with English abstract)

원문보기 상세보기
Ahn, J.-B., K.-M. Shim, M.-P. Jung, H.-G. Jeong,？Y.-H. Kim, and E.-S. Kim, 2018b: Predictability？of Temperature over South Korea in PNU CGCM？and WRF Hindcast. Atmosphere 28(4), 479-490.？doi: 10.14191/Atmos.2018.28.4.479 (in Korean with？English abstract)

원문보기 상세보기
Ahn, J.-B., S. R. Jo, M.-S. Suh, D.-H. Cha, D.-K.？Lee, S.-Y. Hong, S.-K. Min, S.-C. Park, H.-S.？Kang, and K.-M. Shim, 2016: Changes of？Precipitation Extremes over South Korea Projected？by the 5 RCMs under RCP Scenarios. Asia-Pacific？Journal of Atmospheric Sciences 52(2), 223-236.？doi: 10.1007/s13143-016-0021-0

상세보기
Bonan, G. B., 1998: The land surface climatology of？the NCAR land surface model coupled to the？NCAR community climate model. Journal of？Climate 11(6), 1307-1326.

상세보기
Chen, F., and J. Dudhia, 2001: Coupling an？Advanced Land Surface-Hydrology Model with？the Penn State-NCAR MM5 Modeling System.？Part I: Model Implementation and Sensitivity.？Monthly Weather Review 129(4), 569-585. doi:10.1175/1520-0493(2001)129 2.0.CO;2

상세보기
Chung, S. O., 2010: Simulating evapotranspiration？and yield responses of rice to climate change？using FAO-AquaCrop. Journal of the Korean？Society of Agricultural Engineers 52(3), 57-64.？doi:10.5389/KSAE.2010.52.3.057 (in Korean with？English abstract)

원문보기 상세보기
Dudhia, J., 1989: Numerical study of convection？observed during the Winter Monsoon Experiment？using a mesoscale two-dimensional model. Journal？of Atmospheric Sciences 46(20), 3077-3107.？doi:10.1175/1520-0469(1989)046 2.0.CO;2

상세보기
Gibson, L. R., and R. E. Mullen, 1996: Influence of？day and night temperature on soybean seed yield.？Crop Science 36(1), 98-104. doi:10.2135/cropsci1996.0011183X003600010018x

상세보기
Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A？Revised approach to ice microphysical processes？for the bulk parameterization of clouds and？precipitation. Monthly Weather Review 132(1),？103-120. doi:10.1175/1520-0493(2004)132 2.0.CO;2

상세보기
Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new？vertical diffusion package with an explicit？treatment of entrainment processes. Monthly？Weather Review 134(9), 2318-2341. doi:10.1175/MWR3199.1

상세보기
Hunke, E. C., and J. K. Dukowicz, 1997: An？Elastic-Viscous-Plastic model for sea ice dynamics.？Journal of Physical Oceanography 27(9),？1849-1867. doi:10.1175/1520-0485(1997)027 2.0.CO;2

상세보기
Hur, J. N., J. H. Park, K. M. Shim, Y. S. Kim, and？S. R. Jo, 2020: A High-Resolution Agro-Climatic？Dataset for Assessment of Climate Change over？South Korea. Korean Journal of Agricultural and？Forest Meteorology 22(3), 128-134. (in Korean？with English abstract)
Jang, S.-H., C.-S. Ryu, Y.-S. Kang, J.-W. Park,？T.-Y. Kim, K.-S. Kang, M.-J. Park, H.-C. Baek,？Y.-H. Park, D.-W. Kang, K. Zou, M.-C. Kim,？Y.-J. Kwon, S.-A. Han, and T.-H. Jun, 2021:？Estimation of Fresh Weight and Leaf Area Index？of Soybean (Glycine max) Using Multi-year Spectral Data. Korean Journal of Agricultural and？Forest Meteorology 23(4), 329-339. doi:10.5532/KJAFM.2019.21.4.327 (in Korean with English？abstract)

원문보기 상세보기
Kain, J. S., 2004: The Kain-Fritsch convective？parameterization: An update. Journal of applied？meteorology 43(1), 170-181. doi:10.1175/1520-0450(2004)043 2.0.CO;2

상세보기
Kang, S.-T., J.-S. Lee, I.-Y. Baek, W.-Y. Han, D.-C.？Shin, and M.-G. Choung, 2014: Effect of Rainfall？in Harvest Period on Seed Quality in Soybean.？Korea Soybean Digest 31(1), 1-10. (in Korean？with English abstract)
Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville,？B. P. Briegleb, D. L. Williamson, and P. J.？Rasch, 1996: Description of the NCAR Community？Climate Model (CCM3). NCAR Technical note,？NCAR/TN-420+STR,NCAR/TN-420+STR, 152 pp. doi:10.5065/D6FF3Q99
Kim, C.-K., H.-K. Jeong, S.-H. Han, J.-S. Kim, and？D.-H. Moon, 2013: Impacts and countermeasures？of climate change on food supply in Korea. Korea？Rural Economic Institute, 176pp. [Available online？at https://repository.krei.re.kr/handle/2018.oak/21015]
Kim, D.-J., and J.-H. Kim, 2018: An Outlook of？Changes in the Flowering Dates and Low？Temperature after Flowering under the RCP8.5？Projected Climate Condition. Korean Journal of？Agricultural and Forest Meteorology 20(4),？313-320. doi:10.5532/KJAFM.2018.20.4.313 (in Korean？with English abstract)

원문보기 상세보기
Kim, M.-R., 2011: The Status of Korea's Rice？Industry and the Rice Processing Industry. Food？Industry and Nutrition 16(1), 22-26. (in Korean)
Kim, S.-M., and S.-M. Kim, 2013: Agricultural？production base disaster vulnerability assessment？due to meteorological disasterst. Magazine of the？Korean Society of Agricultural Engineers 55(1),？40-46. (in Korean)
Kim, S.-Y., I.-H. Heo, and S.-H. Lee, 2010: Impacts？of Temperature Rising on Changing of Cultivation？Area of Apple in Korea. Journal of the Korean？association of regional geographers 16(3),？201-215. (in Korean with English abstract)
Kim, Y.-H., E.-S. Kim, M.-J. Choi, K.-M. Shim, and？J.-B. Ahn, 2019: Evaluation of Long-Term？Seasonal Predictability of Heatwave over South？Korea Using PNU CGCM-WRF Chain. Atmosphere？29(5), 671-687. doi:10.14191/Atmos.2019.29.5.671？(in Korean with English abstract)

원문보기 상세보기
Kim, Y.-H., M.-J. Choi, K.-M. Shim, J. N. Hur, S.？R. Jo, and J.-B. Ahn, 2021: A Study on the？Predictability of the Number of Days of Heat and？Cold Damages by Growth Stages of Rice Using？PNU CGCM-WRF Chain in South Korea.？Atmosphere 31(5), 577-592. doi:10.14191/Atmos.2021.31.5.577 (in Korean with English abstract)

원문보기 상세보기
KMA (Korea Meteorological Administration), 2021:？Annual report for 2018 extreme climate. Korea？Meteorological Administration, 198pp. (in Korean)
Lee, B.-U., 2009: The global food crisis and the？importance of crop protection. Life and Agrochemicals？30(1), 20-23. (in Korean)
Lee, B.-U., 2012: Impacts and responses of climate？change on global agriculture. KOREA RURAL？ECONOMIC INSTITUTE (KREI) research reports？146, 79-94.
Lee, D. H., S.-K. Min, J. H. Jin, J.-W. Lee, D.-H.？Cha, M.-S. Suh, J.-B. Ahn, S.-Y. Hong, H.-S.？Kang, and M. S. Joh, 2017: Thermodynamic and？dynamic contributions to future changes in？summer precipitation over Northeast Asia and？Korea: a multi-RCM study. Climate Dynamics？49(11), 4121-4139.

상세보기
Lee, J.-W., Y. J. Jang, K.-K. Ko, and J.-K. Park,？2013: Effects of Meteorological Elements in the？Production of Food Crops: Focused on Regression？Analysis using Panel Data. Journal of？Environmental Science International 22(9),？1171-1180. doi:10.5322/JESI.2013.22.9.1171 (in？Korean with English abstract)

원문보기 상세보기
Lee, K.-M., H.-J. Baek, S.-H. Park, H.-S. Kang, and？C.-H. Cho, 2012: Future projection of changes in？extreme temperatures using high resolution？regional climate change scenario in the Republic？of Korea. Journal of the Korean Geographical？Society 47(2), 208-225. (in Korean with English？abstract)
Lee, S. H., I. H. Heo, K. M. Lee, S. Y. Kim, Y. S.？Lee, and W. T. Kwon, 2008: Impacts of climate？change on phonology and growth of crops: In the？case of Naju. Journal of the Korean Geographical？Society 43(1), 20-35. (in Korean with English？abstract)
Lee, Y.-H., W.-G. Sang, J.-I. Cho, and M.-C. Seo,？2019: Effects of high temperature on soybean？physiology, protein and oil content, and yield.？Korean Journal of Crop Science 64(4), 395-405.？doi:10.7740/kjcs.2019.64.4.395 (in Korean with？English abstract)

원문보기 상세보기
Lesk, C., P. Rowhani, and N. Ramankutty, 2016:？Influence of extreme weather disasters on global？crop production. Nature 529(7584), 84-87. doi:10.1038/nature16467

상세보기
Lim, M. S., K. Y. Shin, J. G. Woo, Y. S. Kwon,？S. W. Jang, W. B. Kim, J. N. Lee, J. T. Lee, H.？J. Kwon, J. T. Seo, J. H. Ahn, Y. G. Kang, Y.？I. Ham, M. Kwon, and K. R. Ryu, 2000:？Vegetable cultivation technique in highland area.？Kwahakwonyae press, Seoul, 52-56.
Min, S.-K., S. Legutke, A. Hense, U. Cubasch,？W.-T. Kwon, J.-H. Oh, and U. Schlese, 2006:？East Asian climate change in the 21st century as？simulated by the coupled climate model ECHO-G？under IPCC SRES scenarios. Journal of the？Meteorological Society of Japan. Ser. II 84(1),？1-26. doi:10.2151/jmsj.84.1

상세보기
Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J.？Iacono, and S. A. Clough, 1997: Radiative？transfer for inhomogeneous atmospheres: RRTM, a？validated correlated-k model for the longwave.？Journal of Geophysical Research: Atmospheres？102(D14), 16663-16682. doi:10.1029/97JD00237

상세보기
Myeong, S. J., 2018: Impact of Climate Change？Related Natural Disasters on Rice Production in？South Korea. Journal of the Korean Society of？Hazard Mitigation 18(7), 53-60. doi:10.9798/KOSHAM.2018.18.7.53 (in Korean with English？Abstract)

상세보기
NIMS (National Institute of Meteorological Science),？2012: Global Climate Change Report 2012 for？Response to "IPCC Fifth Assessment Report",？59-89. (in Korean)
Pacanowski, R. C., and S. M. Griffies, cited 1998:？MOM 3.0 manual. NOAA/GFDL [Available online？at http://www.gfdl.noaa.gov/ocean-model]
Park, C. Y., D.-H. Cha, G. Y. Kim, G. Lee, D.-K.？Lee, M.-S. Suh, S.-Y. Hong, J.-B. Ahn, and S.-K.？Min, 2020: Evaluation of summer precipitation？over Far East Asia and South Korea simulated by？multiple regional climate models. International？Journal of Climatology 40(4), 2270-2284.

상세보기
Park, C. Y., S.-K. Min, D. H. Lee, D.-H. Cha,？M.-S. Suh, H.-S. Kang, S.-Y. Hong, D.-K. Lee,？H.-J. Baek, K.-O. Boo, and W.-T. Kwon, 2016:？Evaluation of multiple regional climate models for？summer climate extremes over East Asia. Climate？Dynamics 46(7), 2469-2486.

상세보기
Park, J. H., S. K. Kim, Y. S. Shin, M. I. Ahn, and？Y. K. Han, 2014: Implementation of a Weather？Hazard Warning System at a Catchment Scale.？Korean Journal of Agricultural and Forest？Meteorology 16(4), 389-395. doi:10.5532/KJAFM.2014.16.4.389 (in Korean with English abstract)

원문보기 상세보기
Park, K. Y., 2015: Soybean cultivation technology :？Overcoming disasters by disseminating new？soybean raising seeding technology. - The planting？time can be adjusted according to the weather？conditions, and there is no need to be decapitation？during the growing season -, Understanding the？growth characteristics of soybeans. Korea Soybean？Society 326, 5-6.
Park, P.-S., 2008: The status of Korea's rice industry？and the rice processing industry. Food preservation？and processing industry 7(2), 3-19.
Park, S. H., J. S. Lee, M, H. Seo, and J. S. Lee,？2002: Radish Cultivation. Rural Development？Administration, Suwon, 39-40.
Paulson, C. A., 1970: The mathematical representation？of wind speed and temperature profiles in the？unstable atmospheric surface layer. Journal of？Applied Meteorology and Climatology 9(6), 857-861.？doi:10.1175/1520-0450(1970)009 2.0.CO;2

상세보기
RDA (Rural Development Administration), 2016: A？Research on Agro-meteorological Disaster Hazards？Mapping. National Academy of Agricultural？Science. (in Korean)
RDA (Rural Development Administration), 2018a:？Final report of Development of production？prospects and risk assessment evaluation technology？for decreasing climate disaster on upland crops.？National Academy of Agricultural Science. (in？Korean)
RDA (Rural Development Administration), 2018b:？Technical support datas for reduce of heatwave？and drought damage for food crops. National？Academy of Agricultural Science. (in Korean)
Seo, H.-C., S.-K. Kim, Y.-S. Lee, and Y.-C. Cho,？2006: Geographical Shift of Quality Soybean？Production Area in Northern Gyeonggi Province？by Year 2100. Korean Journal of Agricultural？and Forest Meteorology 8(4), 242-249. (in Korean？with English abstract)
Shim, K.-M., J.-T. Lee, Y.-S. Lee, and G.-Y. Kim,？2003: Traits of Agro-meteorological Disasters in？20th Century Korea. Korean Journal of Agricultural？and Forest Meteorology 5(4), 255-260. (in Korean？with English abstract)
Shim, K.-M., Y.-S. Kim, M.-P. Jung, I.-T. Choi, and？S.-H. Min, 2014: Agro-climatic Zonal Characteristics？of the Frequency of Abnormal Duration of？Sunshine in South Korea. Korean Journal of？Agricultural and Forest Meteorology 16(1), 83-91.？doi:10.5532/KJAFM.2014.16.1.83 (in Korean with English abstract)

원문보기 상세보기
Shim, K.-M., Y.-S. Kim, M.-P. Jung, J. W. Kim, M.？S. Park, S. H. Hong, and K. K. Kang, 2018:？Recent Changes in the Frequency of Occurrence？of Extreme Weather Events in South Korea.？Journal of Climate Change Research 9(4), 461-470.？doi:10.15531/KSCCR.2018.9.4.461 (in Korean with？English abstract)

상세보기
Sin, Y.-H., 2013: Research on global food security？and climate change in agriculture. Water for？future 46(7), 66-71.
Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O.？Gill, D. M. Barker, M. G. Duda, X.-Y. Huang,？W. Wang, and J. G. Powers, 2008: A description？of the advanced research WRF version 3. NCAR？Technical note-475+STR, 125pp.
Son, I.-C., K.-H. Moon, E. Y. Song, S. J. Oh, H.？H. Seo, and J. Y. Yang, 2015: Effects of？differentiated temperature based on growing season？temperature on growth and physiological response？in Chinese cabbage 'Chunkwang'. Korean Korean？Journal of Agricultural and Forest Meteorology？17(3), 254-260. doi:10.5532/KJAFM.2015.17.3.254？(in Korean with English abstract)

원문보기 상세보기
Sun, J., and J. B. Ahn, 2011: A GCM-Based？Forecasting Model for the Landfall of Tropical？Cyclones in China. Advances in atmospheric？sciences 28(5), 1049-1055. doi:10.1007/s00376-011-0122-8

상세보기
Sun, J., and J. B. Ahn, 2015: Dynamical Seasonal？Predictability of the Arctic Oscillation Using a？CGCM. International Journal of Climatology？35(7), 1342-1353. doi:10.1002/joc.4060

상세보기
Teutschbein, C., and J. Seibert, 2012: Bias correction？of regional climate model simulations for？hydrological climate-change impact studies: Review？and evaluation of different methods. Journal of？hydrology 456, 12-29.
Wilks, D. S., 1995: Statistical Methods in the？Atmospheric Sciences. Academic Press, 467pp.？
Yun, J. I., 1999: Agricultural Meteorology. Arche Publishing House. 15-21. (in Korean)

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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