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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.


Rhee, J. and B. Myoung, 2022: Objective and Probabilistic Long-Range Forecasts of Summertime Air Temperatures in South Korea Based on Gaussian Processes. Wea. Forecasting, 37, 329–349,


Kim, S. T., Y.-Y. Lee, J.-H. Oh, and A.-Y. Lim, 2021: Errors in the Winter Temperature Response to ENSO over North America in Seasonal Forecast Models. J. Climate, 34, 8257–8271,

Park, C. and Coauthors, 2021: Record-Breaking Summer Rainfall in South Korea in 2020: Synoptic Characteristics and the Role of Large-Scale Circulations. Mon. Wea. Rev., 149, 3085-3100,

Dandi, A. R., P. A. Pillai, and J. S. Chowdary, 2021: Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models. Clim. Dyn., 56, 439-456,


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,

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,

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,

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,

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,

Sohn, S.-J. and W. Kim, 2020: Toward a better multi-model ensemble prediction of East Asian and Australasian precipitation during non-mature ENSO seasons. Sci. Rep., 10, 20289,

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,

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,

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,

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,

Kim, O.-Y., 2018: Assessment of seasonal prediction of South Pacific Convergence Zone using APCC multi-model ensembles. Clim. Dyn., 50, 3237–3250,

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,

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,

Lee, R. W.-K., C.-Y. Tam, S.-J. Sohn, and J.-B. Ahn, 2018: Predictability of two types of El Niño and their climate impacts in boreal spring to summer in coupled models. Clim. Dyn., 51, 4555-4571,

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,

Sohn, S.-J., and Coauthors, 2018: The Republic of Korea-Pacific Islands Climate Prediction Services Project. Bull. Amer. Meteor. Soc., 99, 253–257,

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,

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,

You, Y., and X. Jia, 2018: Interannual Variations and Prediction of Spring Precipitation over China. J. Climate, 31, 655-670,

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,

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,

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,

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,

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,

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,

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,

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,

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,

Sohn, S.-J., C.-Y. Tam, and H.-I. Jeong, 2016: How do the strength and type of ENSO affect SST predictability in coupled models. Sci. Rep., 6, 33790,

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,

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,

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,

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(5), 680–689,

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,

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,

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,

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,

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,

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,

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,

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,

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,

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., 14, 139-145,

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,

Sohn, S.-J., J.-B. Ahn, and C.-Y. Tam, 2013: Six month-lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble. Geophys. Res. Lett., 40, 579–583,

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,

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,

Tung, Y. L., C.-Y. Tam, S.-J. Sohn, and J.-L. Chu, 2013: Improving the seasonal forecast for summertime South China rainfall using statistical downscaling, J. Geophys. Res. Atmos., 118, 5147–5159,

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,

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,

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,

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,

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,

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,

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,

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,

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,

Sohn, S.-J., C.-Y. Tam, and C.-K. Park, 2011: Leading modes of East Asian winter climate variability and their predictability: An assessment of the APCC multi-model ensemble. J. Meteor. Soc. Jpn., 89(5), 455-474,

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,

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,

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,

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,

Min, Y.-M., V. N. Kryjov, and C.-K. Park, 2009: A Probabilistic Multimodel Ensemble Approach to Seasonal Prediction. Wea. Forecasting, 24, 812–828,

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,

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,

Kug, J.-S., J.-Y. Lee, I.-S. Kang, B. Wang, and C.-K. Park, 2008: Optimal Multi-model Ensemble Method in Seasonal Climate Prediction. Asia-Pacific J. Atmos. Sci., 44, 259-267.

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,

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,

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,

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,

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,

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,

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



· (2023.07) 지구 기록상 최악의 폭염 올까...나사 과학자의 경고

· (2023.07) [사설] 기상이변 상시화 따라 재난 대응 기준도 과할 정도로 높여야

· (2023.07) 8월 대폭염 오나...APCC “엘니뇨 확률 97% 이상, 전세계서 높은 기온”

· (2023.07) [사설] 아파트 관리현장은 겨울보다 여름이 더 무섭다

· (2023.06) [박상욱의 기후 1.5] 폭염의 시작…'들쭉날쭉' 변동성 클 올 여름

· (2023.06) 여름 '장마 괴담' 현실 되나…5월 황금연휴마다 폭우 심상찮다

· (2023.05) 덥고 강수량 많을 올여름...예측 불허 폭우 '선상강수대' 주의보

· (2023.02) “동아시아 내륙 폭염·라니냐발 가뭄이 한반도 위협”

· (2023.01) "역대급 폭염 덮친다"…지구 뜨겁게 달구는 '아기 예수' 정체


· (2022.04) 열받은 지구···4월 '초여름 날씨' 반짝 아니다, 5~7월은 더 더울 것

· (2022.04) 폭염 예고에 선택 아닌 필수, ‘1방 1 에어컨’ 시대

· (2022.04) 폭염 속 조리실, 에어컨 등 지원

· (2022.04) '열사병 예방'... 안전보건공단, 에어컨 구입비 지원


· (2021.06) 도시녹화, 도심 온도 2.5~6°C 낮춘다


· (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


· (2019.07) 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



· (2023.08) Monsoon may start to withdraw around normal Sept timeline

· (2023.05) Monsoon watch. Updated global models signal mixed fortunes for monsoon

· (2023.04) Jeli the worst-hit as Kelantan sizzles

· (2023.04) Sufficient water supply for Perlis to face El Nino phenomenon, assures Perlis MB

· (2023.04) They predict that 2023 could be the rainiest of the last fifteen years

· (2023.01) "El Niño" is getting clearer Warning against drought at the end of the year

· (2023.01) Hot and dry days from El Nino set to hit later this year, say experts


· (2022.11) Asia 2022/2023 Winter Outlook

· (2022.10) NE monsoon may spill into Jan 2023, wet cover may hang until April

· (2022.10) Australia Tropical Cyclone Season Outlook

· (2022.09) Increased rainfall expected in December in northern states

· (2022.09) Winter weather forecast: Gas price shock will depend on how cold it gets

· (2022.07) A huge recipe for disaster

· (2022.05) Asia 2022 summer outlook

· (2022.04) Heat wave conditions may abate in May as showers take over

· (2022.02) Winter Time Up In Odisha But Will February Sizzle In Bhubaneswar Like 2021?

· (2022.01) Scorching Summer 2022 In India; Hotter, Thunderously Stormy April In Odisha's Bhubaneswar


· (2021.11) Asia winter outlook

· (2021.09) Very Heavy Rainfall In Bhubaneswar On Sept 7; 3 Low Pressure Areas This Month

· (2021.09) Asia & South America Seasonal Outlooks

· (2021.08) Monsoon 2021: No Rain In Next 48 Hrs, Low Pressure Likely Near Odisha Coast In Sept

· (2021.08) Warm Week across central Chile

· (2021.07) Revised India monsoon outlook

· (2021.07) Normal to above normal monsoon for August, September

· (2021.06) Monsoon Onset Over Odisha Likely On June 12-13, State To See Above Normal Rainfall

· (2021.05) What Is In Store In May 2021, After 2 Successive Years Of Cyclonic May?

· (2021.04) Brazil will not have La Niña or El Niño in three months

· (2021.03) Monsoon 2021: Odisha To Witness Heavy Rains In June!

· (2021.03) Odisha Heat Wave Alert: 'April-May Will Breathe Fire, June To Pour Cold Water'

· (2021.02) Odisha Weather Forecast: Winter Time Is Up, Hotter Days Till April! >

· (2021.01) Above normal rain, tolerable summer likely for India

· (2021.01) Above-normal rain likely for India in April-June

· (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 >


· (2020.10) 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


· (2019.09) 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


· (2018.12) 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


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


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