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기후정보 활용 현황

아래와 같이 다양한 분야의 연구 및 기사에서 APCC의 기후정보가 활용되고 있습니다. APCC가 제공하는 기후정보를 활용한 또 다른 연구 및 기사가 있으시면 apcc@apcc21.org로 연락주시기 바랍니다.

2020

Dandi, A. R., P. A. Pillai, and J. S. Chowdary, 2020: Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models. Clim. Dyn., 56, 439-456, https://doi.org/10.1007/s00382-020-05487-w

Jung, E., J.-H. Jeong, S.-H. Woo, B.-M. Kim, J.-H. Yoon, and G.-H. Lim, 2020: Impacts of the Arctic-Midlatitude Teleconnection on Wintertime Seasonal Climate Forecasts. Environ. Res. Lett., 15. 94045, https://doi.org/10.1088/1748-9326/aba3a3

Kim, M., S. T. Kim, and Y. Jeong, 2020: Weather Generator–Based Downscaling of EAWM Strength Prediction to the Climate of a Korean Basin. J. Appl. Meteor. Climatol., 59, 1581–1605, https://doi.org/10.1175/JAMC-D-19-0282.1

Lee, Y.-Y., and J.-H. Oh, 2020: West Pacific teleconnection pattern in dynamical seasonal predictions: how is it connected to the Atlantic atmospheric mean bias?. Clim. Dyn., 54, 3671–3683, https://doi.org/10.1007/s00382-020-05198-2

Myoung, B., J. Rhee, and C. Yoo, 2020: Long-Lead Predictions of Warm Season Droughts in South Korea Using North Atlantic SST. J. Climate, 33, 4659-4677, https://doi.org/10.1175/JCLI-D-19-0082.1

Shin, J. Y., H.-H. Kwon, and J.-H. Lee, 2020: Probabilistic long-term hydrological drought forecast using Bayesian networks and drought propagation. Meteorol. Appl., 27, e1827, https://doi.org/10.1002/met.1827


Lee, J.-Y., H.-J. Kim, and Y.-R. Jeong, 2019: Influence of Boreal Summer Intraseasonal Oscillation on the 2016 Heat Wave over Korea. Atmos., 29(5), 627–637, https://doi.org/10.14191/ATMOS.2019.29.5.627

Shin, J. Y., H.-H. Kwon, J.-H. Lee, and T.-W. Kim, 2019: Probabilistic long-term hydrological drought forecast using Bayesian networks and drought propagation. Meteorol. Appl., 27, e1827, https://doi.org/10.1002/met.1827

Sohn, S.-J., C.-Y. Tam, and J.-S. Kug, 2019: How does ENSO diversity limit the skill of tropical Pacific precipitation forecasts in dynamical seasonal predictions?. Clim. Dyn., 53, 5815–5831, https://doi.org/10.1007/s00382-019-04901-2


Alessandri, A., M. D. Felice, F. Catalano, J.-Y. Lee, B. Wang, D. Y. Lee, J.-H. Yoo, and A. Weisheimer, 2018: Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users. Clim. Dyn., 50, 2719–2738, https://doi.org/10.1007/s00382-017-3766-y

Iizumi, T., Y. Shin, W. Kim, M. Kim, and J. Choi, 2018: Global crop yield forecasting using seasonal climate information from a multi-model ensemble. Clim. Serv., 11, 13-23, https://doi.org/10.1016/j.cliser.2018.06.003

Kim, O.-Y., 2018: Assessment of seasonal prediction of South Pacific Convergence Zone using APCC multi-model ensembles. Clim. Dyn., 50, 3237–3250, https://doi.org/10.1007/s00382-017-3802-y

Kim, O.-Y., J. C. and L. Chan, 2018: Cyclone-track based seasonal prediction for South Pacific tropical cyclone activity using APCC multi-model ensemble prediction. Clim. Dyn., 51, 3209–3229, https://doi.org/10.1007/s00382-018-4075-9

Kim, W., S.-R. Yeo, and Y. Kim, 2018: Development of the Expert Seasonal Prediction System: an Application for the Seasonal Outlook in Korea. Asia-Pacific J Atmos Sci., 54, 563–573, https://doi.org/10.1007/s13143-018-0052-9

Park, H.-J., V. N. Kryjov, and J.-B. Ahn, 2018: One-Month-Lead Predictability of Asian Summer Monsoon Indices Based on the Zonal Winds by the APCC Multimodel Ensemble. J. Climate, 31, 8945–8960, https://doi.org/10.1175/JCLI-D-17-0816.1

Sohn, S.-J., and Coauthors, 2018: The Republic of Korea-Pacific Islands Climate Prediction Services Project. Bull. Amer. Meteor. Soc., 99, 253–257, https://doi.org/10.1175/BAMS-D-17-0075.1

Wu, S., M. Notaro, S. Vavrus, E. Mortensen, R. Montgomery, J. Pieroloa, and P. Block, 2018: Efficacy of tendency and linear inverse models to predict southern Peru's rainy season precipitation. Int. J. Climatol., 38, 2590-2604, https://doi.org/10.1002/joc.5442

Yeo, S.-R., S.-W. Yeh, Y. Kim, and S.-Y. Yim, 2018: Monthly climate variation over Korea in relation to the two types of ENSO evolution. Int. J. Climatol., 38, 811-824, https://doi.org/10.1002/joc.5212

You, Y., and X. Jia, 2018: Interannual Variations and Prediction of Spring Precipitation over China. J. Climate, 31, 655-670, https://doi.org/10.1175/JCLI-D-17-0233.1


Ham, Y.-G., Y. Chikamoto, J.-S. Kug, M. Kimoto, and T. Mochizuki, 2017: Tropical Atlantic-Korea teleconnection pattern during boreal summer season. Clim. Dyn., 49, 2649–2664, https://doi.org/10.1007/s00382-016-3474-z

Jeong, J.-H., and Coauthors, 2017: The status and prospect of seasonal climate prediction of climate over Korea and East Asia: A review. Asia-Pacific J Atmos Sci., 53, 149–173, https://doi.org/10.1007/s13143-017-0008-5

Kim, O.-Y., H.-M. Kim, M.-I. Lee, and Y.-M. Min, 2017: Dynamical–statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models. Clim. Dyn., 48, 71–88, https://doi.org/10.1007/s00382-016-3063-1

Kim, S. T., S.-J. Sohn, and J.-S. Kug, 2017: Winter temperatures over the Korean Peninsula and East Asia: development of a new index and its application to seasonal forecast. Clim. Dyn., 49, 1567–1581, https://doi.org/10.1007/s00382-016-3402-2

Lee, S.-S., J.-Y. Moon, B. Wang, and H.-J. Kim, 2017: Subseasonal Prediction of Extreme Precipitation over Asia: Boreal Summer Intraseasonal Oscillation Perspective. J. Climate, 30, 2849–2865, https://doi.org/10.1175/JCLI-D-16-0206.1

Min, Y.-M., V. N. Kryjov, S. M. Oh, and H.-J. Lee, 2017: Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008–2015. Clim. Dyn., 49, 4141–4156, https://doi.org/10.1007/s00382-017-3576-2


Pradhan, P. K., V. Prasanna, D. Y. Lee, and M.-I. Lee, 2016: El Niño and Indian summer monsoon rainfall relationship in retrospective seasonal prediction runs: experiments with coupled global climate models and MMEs. Meteorol. Atmos. Phys., 128, 97-115, https://doi.org/10.1007/s00703-015-0396-y

Shin, J. Y., M. Ajmal, J. Yoo, and T.-W. Kim, 2016: A Bayesian Network-Based Probabilistic Framework for Drought Forecasting and Outlook. Adv. Meteol., 2016, 1-10, https://doi.org/10.1155/2016/9472605

Sohn, S.-J., and C.-Y. Tam, 2016: Long-lead station-scale prediction of hydrological droughts in South Korea based on bivariate pattern-based downscaling. Clim. Dyn., 46, 3305-3321, https://doi.org/10.1007/s00382-015-2770-3


Jeong, H.-I., J.-B. Ahn, J.-Y. Lee, A. Alessandri, and H. H. Hendon, 2015: Interdecadal change of interannual variability and predictability of two types of ENSO. Clim. Dyn., 44, 1073–1091, https://doi.org/10.1007/s00382-014-2127-3

Lee, D. Y., J.-B. Ahn, and J.-H. Yoo, 2015: Enhancement of seasonal prediction of East Asian summer rainfall related to western tropical Pacific convection. Clim. Dyn., 45, 1025–1042, https://doi.org/10.1007/s00382-014-2343-x

Lee, J.-Y., and K.-J. Ha, 2015: Understanding of Interdecadal Changes in Variability and Predictability of the Northern Hemisphere Summer Tropical-Extratropical Teleconnection. J. Climate, 28, 9634-9647, https://doi.org/10.1175/JCLI-D-15-0154.1

Ye, K.-H., C.-Y. Tam, W. Zhou, and S.-J. Sohn, 2015: Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling. Adv. Atmos. Sci., 32, 680–689, https://doi.org/10.1007/s00376-014-4047-x

Yim, S.-Y., B. Wang, W. Xing, and M.-M. Lu, 2015: Prediction of Meiyu rainfall in Taiwan by multi-lead physical–empirical models. Clim. Dyn., 44, 3033–3042, https://doi.org/10.1007/s00382-014-2340-0


Jia, X., H. Lin, and X. Yao, 2014: The Influence of Tropical Pacific SST Anomaly on Surface Air Temperature in China. J. Climate, 27, 1425-1444, https://doi.org/10.1175/JCLI-D-13-00176.1

Jia, X., J.-Y. Lee, H. Lin, A. Alessandri, and K.-J. Ha, 2014: Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part I. The leading forced mode of atmospheric circulation. Clim. Dyn., 43, 1595–1609, https://doi.org/10.1007/s00382-013-1988-1

Jia, X., J.-Y. Lee, H. Lin, H. Hendon, and K.-J. Ha, 2014: Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part II. predictability and prediction skill. Clim. Dyn., 43, 1611–1630, https://doi.org/10.1007/s00382-014-2084-x

Kang, S., J. Hur, and J.-B. Ahn, 2014: Statistical downscaling method based on APCC multi-model ensemble for seasonal prediction over South Korea. Int. J. Climatol., 34, 3801-3810, https://doi.org/10.1002/joc.3952

Min, Y.-M., V. N. Kryjov, and S. M. Oh, 2014: Assessment of APCC multimodel ensemble prediction in seasonal climate forecasting: Retrospective (1983–2003) and real-time forecasts (2008–2013). J. Geophys. Res. Atmos., 119, 12 132–12 150, https://doi.org/10.1002/2014JD022230

Yim, S.-Y., B. Wang, and W. Xing, 2014: Prediction of early summer rainfall over South China by a physical-empirical model. Clim Dyn., 43, 1883–1891, https://doi.org/10.1007/s00382-013-2014-3


Gottschalck, J., P. E. Roundy, C. J. Schreck III, A. Vintzileos, and C. Zhang, 2013: Large-Scale Atmospheric and Oceanic Conditions during the 2011–12 DYNAMO Field Campaign. Mon. Wea. Rev., 141, 4173–4196, https://doi.org/10.1175/MWR-D-13-00022.1

Lee, D. Y., J.-B. Ahn, and K. Ashok, 2013: Improvement of Multimodel Ensemble Seasonal Prediction Skills over East Asian Summer Monsoon Region Using a Climate Filter Concept. J. Appl. Meteorol. Climatol., 52, 1127-1138, https://doi.org/10.1175/JAMC-D-12-0123.1

Lee, D. Y., J.-B. Ahn, K. Ashok, and A. Alessandri, 2013: Improvement of grand multi-model ensemble prediction skills for the coupled models of APCC/ENSMEBLES using a climate filter. Atmos. Sci. Lett., 139-145, https://doi.org/10.1002/asl2.430

Lee, J.-Y., S.-S. Lee, B. Wang, K.-J. Ha, and J.-G. Jhun, 2013: Seasonal prediction and predictability of the Asian winter temperature variability. Clim. Dyn., 41, 573–587, https://doi.org/10.1007/s00382-012-1588-5

Sohn, S.-J., C.-Y. Tam, and J.-B. Ahn, 2013: Development of a multimodel-based seasonal prediction system for extreme droughts and floods : a case study for South Korea. Int. J. Climatol., 33, 793-805, https://doi.org/10.1002/joc.3464

Tang, W., Z.-H. Lin, and L.-F. Luo, 2013: Assessing the Seasonal Predictability of Summer Precipitation over the Huaihe River Basin with Multiple APCC Models, Atmospheric and Oceanic Science Letters, 6:4, 185-190, https://doi.org/10.3878/j.issn.1674-2834.13.0025


Jeong, H., and Coauthors, 2012: Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter. Clim. Dyn., 39, 475–493, https://doi.org/10.1007/s00382-012-1359-3

Jia, X., H. Lin, J. Lee, and B. Wang, 2012, Season-Dependent Forecast Skill of the Leading Forced Atmospheric Circulation Pattern over the North Pacific and North American Region. J. Climate, 25, 7248-7265, https://doi.org/10.1175/JCLI-D-11-00522.1

Kosaka, Y., J. S. Chowdary, S. Xie, Y.-M. Min, and J. Lee, 2012: Limitations of Seasonal Predictabiliy for Summer Climate over East Asia and the Northwestern Pacific, J. Climate, 25, 7574-7589, https://doi.org/10.1175/JCLI-D-11-00009.1

Krishnamurti, T. N., and V. Kumar, 2012: Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere-Ocean Coupled Models. Part 2:Anomaly, J. Climate, 25. 65-88, https://doi.org/10.1175/2011JCLI4126.1

Kumar, V., and T. N. Krishnamurti, 2012: Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere-Ocean Coupled Models. Part I:Climatology. J. Climate, 25. 39-64, https://doi.org/10.1175/2011JCLI4125.1

Sohn, S.-J., Y.-M. Min, J.-Y. Lee, C.-Y. Tam, I.-S. Kang, B. Wang, J.-B. Ahn, and T. Yamagata, 2012: Assessment of the longlead probabilistic prediction for the Asian summer monsoon precipitation (1983–2011) based on the APCC multimodel system and a statistical model. J. Geophys. Res., 117, D04102, https://doi.org/10.1029/2011JD016308

Stefanova, L., V. Misra, J. J. O’Brien, E. P. Chassignet, and S. Hameed, 2012: Hindcast skill and predictability for precipitation and two-meter air temperature anomalies in global circulation models over the Southeast United States. Clim. Dyn., 38, 161–173, https://doi.org/10.1007/s00382-010-0988-7


Lee, J.-Y., B. Wang, Q. Ding, K.-J. Ha, J.-B. Ahn, A. Kumar, B. Stern, and O. Alves, 2011: How predictable is the northern hemisphere summer upper-tropospheric circulation?. Clim. Dyn., 37, 1189–1203, https://doi.org/10.1007/s00382-010-0909-9

Min, Y.-M., V. N. Kryjov, and J.-H. Oh, 2011: Probabilistic interpretation of regression-based downscaled seasonal ensemble prediction with the estimation of uncertainty. J. Geophys. Res., 116, D08101, https://doi.org/10.1029/2010JD015284


Chowdary, J. S., S.-P. Xie, J.-Y. Lee, Y. Kosaka, and B. Wang, 2010: Predictability of summer northwest Pacific climate in 11 coupled model hindcasts: Local and remote forcing. J. Geophys. Res., 115, D22121, https://doi.org/10.1029/2010JD014595

Juneng, L., F. T. Tangang, H. Kang, W. Lee, and Y. K. Seng, 2010: Statistical Downscaling Forecasts for Winter Monsoon Precipitation in Malaysia Using Multimodel Output Variables. J. Climate, 23, 17–27, https://doi.org/10.1175/2009JCLI2873.1

Lee, J., and Coauthors, 2010: How are seasonal prediction skills related to models’ performance on mean state and annual cycle?. Clim. Dyn., 35, 267–283, https://doi.org/10.1007/s00382-010-0857-4


Kang, H., C.-K. Park, S. N. Hameed, and K. Ashok, 2009: Statistical Downscaling of Precipitation in Korea Using Multimodel Output Variables as Predictors. Mon. Wea. Rev., 137. 1928-1938, https://doi.org/10.1175/2008MWR2706.1

Min, Y.-M., V. N. Kryjov, and C.-K. Park, 2009: A Probabilistic Multimodel Ensemble Approach to Seasonal Prediction. Wea. Forecasting, 24, 812–828, https://doi.org/10.1175/2008WAF2222140.1

Wang, B., and Coauthors, 2009: Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Clim. Dyn., 33, 93–117, https://doi.org/10.1007/s00382-008-0460-0


Chu, J.-L., H. Kang, C.-Y. Tam, C.-K. Park, and C.-T. Chen, 2008: Seasonal forecast for local precipitation over northern Taiwan using statistical downscaling, J. Geophys. Res., 113, D12118, https://doi.org/10.1029/2007JD009424

Kug, J.-S., J.-Y. Lee, and I.-S. Kang, 2008: Systematic Error Correction of Dynamical Seasonal Prediction of Sea Surface Temperature Using a Stepwise Pattern Project Method. Mon. Wea. Rev., 136. 3501-3512, https://doi.org/10.1175/2008MWR2272.1

Shin, D. W., S.-D. Kang, S. Cocke, T.-Y. Goo, and H.-D. Kim, 2008: Seasonal probability of precipitation forecasts using a weighted ensemble approach. Int. J. Climatol., 28, 1971-1976, https://doi.org/10.1002/joc.1690

Wang, B., and Coauthors, 2008: How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability?. Clim. Dyn., 30, 605–619, https://doi.org/10.1007/s00382-007-0310-5

Zhu, C., C.-K. Park, W.-S. Lee, and W.-T. Yun, 2008: Statistical downscaling for multi-model ensemble prediction of summer monsoon rainfall in the Asia-Pacific region using geopotential height field. Adv. Atmos. Sci., 25, 867–884, https://doi.org/10.1007/s00376-008-0867-x


Kang, H., and C.-K. Park, 2007: Error analysis of dynamical seasonal predictions of summer precipitation over the East Asian-western Pacific region. Geophys. Res. Lett., 34. L13705, https://doi.org/10.1029/2007GL029392

Kang, H., K.-H. An, C.-K. Park, A. L. S. Solis, and K. Stitthichivapak, 2007: Multimodel output statistical downscaling prediction of precipitation in the Philippines and Thailand. Geophys. Res. Lett., 34, 15, L15710, https://doi.org/10.1029/2007GL030730


Kar, S. C., A. Hovsepyanm, and C. K. Park, 2006: Economic values of the APCN multi-model ensemble categorical seasonal predictions. Meteorol. Appl., 13. 267-277, https://doi.org/10.1017/S1350482706002271


Yoo, J. H., and I.-S. Kang, 2005: Theoretical examination of a multi-model composite for seasonal prediction. Geophys. Res. Lett., 32, L18707, https://doi.org/10.1029/2005GL023513

국내

2020

· (2020.10) [지난 3년 여름의 경고]⑧ 올겨울은 추울까, 따뜻할까…“라니냐·북극 vs 온실가스”

· (2020.07) '폭염+으뜸효율+판촉'…올 에어컨 판매 '대박'날까?

· (2020.06) 코로나19에도 에어컨 생산라인 ‘풀가동’

· (2020.06) 본격 무더위에 에어컨 생산라인 ‘쌩쌩’

· (2020.06) 韓프리카... 올여름 폭염 달고 산다

· (2020.06) 올 여름 더 덥다 UNIST폭염센터, 더울 확률 50%↑

· (2020.06) LG 휘센 에어컨 생산라인, 풀가동

· (2020.06) 해수부, 2020년 수산분야 고수온‧적조 종합 대책 마련

· (2020.05) [사설] 역대급 찜통더위 예보…블랙아웃 없어야

· (2020.05) [맹소영의 날씨이야기]2018년 악몽 재현되나

· (2020.04) LG전자, 휘센 에어컨 사전점검 서비스 실시

· (2020.04) 에어컨 성수기 본격화 "올 여름 때 이른 무더위 찾아온다"

· (2020.04) 예상되는 올 여름 때 이른 무더위…에어컨 성수기 본격화

· (2020.02) '이상한 1월' 1973년 이후 가장 따뜻 … 0.5℃만 올라도 매개감염병 위험 커

· (2020.02) 올해도 지구는 뜨겁다

2019

· (2019.07) 동해 오징어, 올핸 싸게 맛보나?

· (2019.05) 지난해 고수온으로 물고기 6400만마리 죽었다…올해는?

· (2019.05) “6~8월 수온 1도 정도 높을 듯” 우리 연안, 올해도 고수온 비상

· (2019.02) [단독] 서울, 한파가 사라졌다...영하 12도로 떨어진 날 하루



국외

맨위로
2021

· (2021.01) Rains are expected to be above average in most of Brazil in the first quarter of 2021

· (2021.01) 2021 Summer Forecast: Wetter, Cooler Odisha In May-June

2020

· (2020.10) Update activity "La Niña" strength! Expect not fierce. Bangkok, cold hit the average

· (2020.10) Piauí will have temperatures above historical averages, says Inmet

· (2020.09) Good monsoon tidings may last until year-end

· (2020.07) Scholars warn the phenomenon "La Niña" strikes heavy rain. Especially in Bangkok.

· (2020.07) August Outlook for Australia

· (2020.06) Global models say monsoon yet to reveal its true intent

· (2020.03) Australia Long-Range Outlook

· (2020.03) Early look at India's southwest monsoon

· (2020.03) Korean, Japanese models predict good monsoon

· (2020.02) Monsoon 2020 silver lining: Odisha will see pouring rain in July & August!

· (2020.02) Weather report: Showers may cap day temperatures in East and South this week

· (2020.01) First look: India may have a good monsoon in 2020

2019

· (2019.09) South Asia Climate Forum sees a normal North-East monsoon this year

· (2019.09) Wet spell for South as East braces for welcome rain

· (2019.07) Lows may drive monsoon to peak over Central India

· (2019.07) Monsoon revival to bring more rain to South India

· (2019.03) Global warming hits seaside winter

· (2019.02) More violent weather in the offing for North-West, East India

· (2019.01) Forest fires threaten WV reforested areas – DENR

2018

· (2018.12) DENR to activate emergency response teams for El Niño

· (2018.06) Neutral El Niño/La Niña conditions in June 2018

· (2018.03) El Niño/La Niña today - March 2018

· (2018.03) S-W monsoon: Global models see setback in July, August

· (2018.03) Soaring mercury, looming crisis

· (2018.01) South to get summer showers from February

2015

· (2015.07) BPPT: Sumatra-Java-Bali-Nusa Tenggara Experiencing More Serious Drought

2013

· (2013.04) Skymet forecasts well-distributed, adequate monsoon