{"id":592,"date":"2025-08-09T16:36:30","date_gmt":"2025-08-09T08:36:30","guid":{"rendered":"https:\/\/hydro.as.ntu.edu.tw\/chia\/?page_id=592"},"modified":"2025-08-20T10:23:50","modified_gmt":"2025-08-20T02:23:50","slug":"2025-poster","status":"publish","type":"page","link":"https:\/\/hydro.as.ntu.edu.tw\/chia\/chia-forum-2025\/2025-poster\/","title":{"rendered":"CHiA Forum 2025 Poster"},"content":{"rendered":"\t\t
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Day 2-3<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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8\/27\u300128 Posters
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Poster Section I<\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
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Day 2, 8\/27(\u4e09) 14:20-16:20<\/div>\n\n\t\t\t\t\t\n\t\t\t\t<\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
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\u7de8\u865f<\/strong><\/td>\n \u59d3\u540d<\/strong><\/td>\n \u984c\u76ee<\/strong><\/td>\n <\/tr>\n
A01-D2<\/td>\n \u80e1\u82ae\u5609 <\/td>\n The Role of Subtropical Clouds in Shaping Tropical SST Responses to Anthropogenic Aerosols<\/td>\n <\/tr>\n
A03-D2<\/td>\n \u8449\u6e58\u742a <\/td>\n Walker Cell Westward Shift under Abrupt 4\u00d7CO\u2082 Forcing Driven by Atmospheric Energy Gain over Eurasia and Africa<\/td>\n <\/tr>\n
A05-D2<\/td>\n \u8449\u76c8\u79c0 <\/td>\n Exploiting Aquaplanet Simulations to Explore the Solar Seasonal Impacts on Polar Amplification<\/td>\n <\/tr>\n
A07-D2<\/td>\n \u674e\u827e\u8018 <\/td>\n The Atmospheric Energy Balance Regime Transition and Polar Surface Warming<\/td>\n <\/tr>\n
A09-D2<\/td>\n \u9673\u6c38\u771f <\/td>\n The role of convection-circulation coupling in abrupt monsoon onset<\/td>\n <\/tr>\n
A11-D2<\/td>\n \u7fc1\u6625\u96c4 <\/td>\n New insight of Air-Sea Interaction Mechanism of Northward Propagation of Boreal Summer Intraseasonal Oscillation in Western North Pacific<\/td>\n <\/tr>\n
A13-D2<\/td>\n \u937e\u6615\u82b8 <\/td>\n Tropical Pacific Sea Surface Temperature Response to Shifting Aerosol Emission Locations<\/td>\n <\/tr>\n
A15-D2<\/td>\n \u5f35\u921e\u745c <\/td>\n \u5f85\u5b9a <\/td>\n <\/tr>\n
A17-D2<\/td>\n Jie Hsu<\/td>\n Irreversibility of the Hydrological Cycle in the Amazon Basin in Response to CO2 Removal<\/td>\n <\/tr>\n
A19-D2<\/td>\n Ching-Hung Shih<\/td>\n Climatic Controls on Diurnal Temperature\u2013Humidity Hysteresis<\/td>\n <\/tr>\n
A21-D2<\/td>\n \u9ec3\u5ba5\u83d8 <\/td>\n The Linkages Between ENSO C-mode and Taiwan Strait Wind Field<\/td>\n <\/tr>\n
A23-D2<\/td>\n \u8521\u5a49\u9e97 <\/td>\n Contrasting La Ni\u00f1a Evolution under two AMO Phases<\/td>\n <\/tr>\n
A25-D2<\/td>\n \u5468\u5f65\u5ef7 <\/td>\n Causes and Impacts of Amazonian Dry Season Precipitation Reduction from 1980 to 2014.<\/td>\n <\/tr>\n
A27-D2<\/td>\n \u6797\u601d\u7a4e <\/td>\n Summer Heat and Dryness in Taiwan: Impacts of the Pacific-Japan Pattern<\/td>\n <\/tr>\n
A29-D2<\/td>\n \u6b50\u5fb7\u6631 <\/td>\n A Simple Method for Quantifying Cloud-Fog Induced Reduction in Solar Radiation Using High Spatiotemporal Geostationary Satellite Data<\/td>\n <\/tr>\n
A31-D2<\/td>\n \u8449\u67cf\u8f1d <\/td>\n Atmospheric Circulation Responses to the Aerosol Emission Shift during 1980-2020 in CMIP6<\/td>\n <\/tr>\n
A33-D2<\/td>\n \u6e38\u6770\u5ead <\/td>\n Investigating the Microclimatic Characteristics of the Alishan Tea Plantation by Using In-situ Observations and TReAD Reanalysis Data<\/td>\n <\/tr>\n
A35-D2<\/td>\n \u5433\u5b9a\u878d <\/td>\n The non-linear responses of Maritime Continent deforestation on local extreme heat events.<\/td>\n <\/tr>\n
A37-D2<\/td>\n \u674e\u5ead\u6167<\/td>\n Fog dampens the spatiotemporal variation of microclimate<\/td>\n <\/tr>\n
A39-D2<\/td>\n \u6797\u4e4b\u7136 <\/td>\n An Inquiry into Wave-Mean Flow Interactions and Tropical Response in a Prescribed Ozone Hole Simulation<\/td>\n <\/tr>\n
A41-D2<\/td>\n \u9ec3\u4ee5\u5bec <\/td>\n Evaluation of the rainfall seasonality in three rainforest regions<\/td>\n <\/tr>\n
B01-D2<\/td>\n \u8521\u776b\u8476 <\/td>\n Linking the Pacific Meridional Mode to Decadal Heatwave Prediction in Taiwan and East Asia<\/td>\n <\/tr>\n
B03-D2<\/td>\n \u5289\u79c9\u8c6a <\/td>\n An analysis on the 2023\/24 Amazon basin recorded drought<\/td>\n <\/tr>\n
B05-D2<\/td>\n \u7518\u7950\u9293 <\/td>\n Longwave Cloud Radiative Feedback and Kelvin Waves Modulation<\/td>\n <\/tr>\n
B07-D2<\/td>\n Wei-Ting Chen<\/td>\n Observations of Convective Cloud Clustering and Convection-Circulation Coupling in Monsoon Region<\/td>\n <\/tr>\n
B09-D2<\/td>\n \u5085\u5e73 <\/td>\n Data Uncertainties and Temporal Shifts in Moisture Tracking for Continental Water Planning<\/td>\n <\/tr>\n
B11-D2<\/td>\n \u90ed\u4f73\u6b23 <\/td>\n Discrepancy modeling of the convective boundary layer: Development possibilities from large-eddy simulations and machine learning<\/td>\n <\/tr>\n
B13-D2<\/td>\n \u738b\u5609\u742a <\/td>\n TaiESM1\u71b1\u5e36\u77ed\u6ce2\u8f3b\u5c04-SST\u56de\u994b\u904e\u7a0b\u5206\u6790 <\/td>\n <\/tr>\n
B15-D2<\/td>\n \u8cf4\u67cf\u52f3 <\/td>\n TaiESM1 \u6771\u4e9e\u5730\u5340\u6885\u96e8\u5b63\u964d\u96e8\u504f\u5dee\u521d\u6b65\u5206\u6790 <\/td>\n <\/tr>\n
B17-D2<\/td>\n \u76ae\u5bb6\u5bb9 <\/td>\n Evaluating a Neural Network-Based Scale-Adapted Scheme for Ice Cloud Fraction in the Taiwan Earth System Model (TaiESM1)<\/td>\n <\/tr>\n
B19-D2<\/td>\n \u6881\u4fe1\u8b19 <\/td>\n Tropical Cyclone Performance of the High-Resolution Taiwan Earth System Model<\/td>\n <\/tr>\n
B21-D2<\/td>\n \u6c5f\u921e <\/td>\n Do CMIP6 HighResMIP Models Perform Better for the Global Monsoon?<\/td>\n <\/tr>\n
B23-D2<\/td>\n \u9673\u9038\u660c <\/td>\n Capturing Subgrid Cold Pool Dynamics with U-Net: Insights from Large Eddy Simulation for Storm-Resolving Modeling<\/td>\n <\/tr>\n
B25-D2<\/td>\n Kuan-Ting Kuo<\/td>\n Deep convection despite strong surface convective inhibition\u2014examples with cloud-resolving and anelastic convective entity models<\/td>\n <\/tr>\n
B27-D2<\/td>\n \u5f35\u6df3\u7693 <\/td>\n MJO Moisture Dynamic Discrepancies between ERA5 Reanalysis and CMIP6<\/td>\n <\/tr>\n
B29-D2<\/td>\n \u7f85\u96c5\u862d <\/td>\n Is ENSO Modulated by 3-D Radiation-Topography Interactions?<\/td>\n <\/tr>\n
B31-D2<\/td>\n \u9ec3\u5b50\u5f37 <\/td>\n \u4f7f\u7528\u6a5f\u5668\u5b78\u7fd2\u5efa\u7acb\u963f\u91cc\u5c71\u5730\u5340\u591c\u9593\u9727\u9810\u6e2c\u6a21\u578b <\/td>\n <\/tr>\n
B33-D2<\/td>\n \u85cd\u5609\u5049 <\/td>\n \u5f85\u5b9a <\/td>\n <\/tr>\n
B35-D2<\/td>\n Shih-Hao Su<\/td>\n Development and Application of Machine Learning based Downscaling Model in Taiwan<\/td>\n <\/tr>\n
B37-D2<\/td>\n \u9673\u5b50\u5cef <\/td>\n Quantifying Socioeconomic Impacts of Drought in Taiwan for Climate Adaptation<\/td>\n <\/tr>\n<\/table>\n<\/div><\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
\n\n\n\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tNext day\t\t\t\t<\/a>\n\n\t\t\t\t<\/div>\n\n\t\t\t\n\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Poster Section II<\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
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Day 3 (8\/28) 13:00-15:00<\/div>\n\n\t\t\t\t\t\n\t\t\t\t<\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
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\u7de8\u865f<\/strong><\/td>\n \u59d3\u540d<\/strong><\/td>\n \u984c\u76ee<\/strong><\/td>\n <\/tr>\n
A02-D3<\/td>\n \u66fe\u5efa\u7ff0 <\/td>\n Persistent circulation identification, seasonal transition and prediction<\/td>\n <\/tr>\n
A04-D3<\/td>\n \u66fe\u742c\u9234 <\/td>\n Nonstationary Teleconnection Mechanisms Linking the North Atlantic Oscillation to East Asian Cold Surges: Implications for Decadal Predictability of Cold Surges<\/td>\n <\/tr>\n
A06-D3<\/td>\n \u674e\u6df3\u5f18 <\/td>\n Forecasting Taiwan's Peak Electricity Demand Under Climate Change Using Statistical and Machine Learning Methods<\/td>\n <\/tr>\n
A08-D3<\/td>\n \u6797\u6600\u975c <\/td>\n Development of the Taiwan High-Resolution Seasonal Probability Rainfall Forecast Guidance<\/td>\n <\/tr>\n
A10-D3<\/td>\n \u5468\u81f3\u4e2d <\/td>\n \u6d77\u6d0b\u6c23\u5019\u8b8a\u9077\u6a21\u64ec\u53ca\u5176\u6f01\u696d\u61c9\u7528 <\/td>\n <\/tr>\n
A12-D3<\/td>\n \u90ed\u82ae\u4f36 <\/td>\n \u5168\u7403\u6696\u5316\u4e0bENSO\u9810\u6e2c\u9762\u81e8\u7684\u6311\u6230 <\/td>\n <\/tr>\n
A14-D3<\/td>\n \u738b\u5247\u71ca <\/td>\n \u91dd\u5c0d\u53f0\u7063\u5730\u5340\u4e4bAI\u964d\u5c3a\u5ea6\u6a21\u578b\u6a23\u672c\u6578\u9700\u6c42\u8a55\u4f30\uff1a\u55ae\u8b8a\u6578\u5206\u6790\u89c0\u9ede <\/td>\n <\/tr>\n
A16-D3<\/td>\n \u9673\u6600\u9756 <\/td>\n Week 3-4 Rainfall Forecast;Convolutional Neural Network;Attention Mechanism<\/td>\n <\/tr>\n
A18-D3<\/td>\n \u5f35\u7950\u7444 <\/td>\n Exploring the Impacts of Multi-Year La Ni\u00f1a Events on Rainfall and Agriculture in Southeast Asia: A Case Study of Mango<\/td>\n <\/tr>\n
A20-D3<\/td>\n \u6797\u80b2\u614e <\/td>\n What Processes Drive Millennial-Scale AMOC Recovery?<\/td>\n <\/tr>\n
A22-D3<\/td>\n \u674e\u73f5\u8c50 <\/td>\n Application of Liouville equation on weather forecast<\/td>\n <\/tr>\n
A24-D3<\/td>\n \u9072\u6b63\u7965 <\/td>\n Intense Tropical Cyclones in the Western North Pacific Under Global Warming: A Dynamical Downscaling Approach<\/td>\n <\/tr>\n
A26-D3<\/td>\n \u6797\u8283\u7ff0 <\/td>\n Explore the Sea Surface Temperature and Heat Flux of Tropical Cyclone Formation from 2003 to 2023<\/td>\n <\/tr>\n
A28-D3<\/td>\n \u6797\u66f8\u6b63 <\/td>\n Assessing Tropical Cyclone Interannual Variability in the Western North Pacific Using Average Accumulated Cyclone Energy (AACE)<\/td>\n <\/tr>\n
A30-D3<\/td>\n Sho Arakane<\/td>\n Tropical cyclone impact on climate mean field and variability using the global tropical cyclone removal dataset<\/td>\n <\/tr>\n
A32-D3<\/td>\n Shao-Yu Tseng<\/td>\n The Dependence on Moisture Distribution in Different Convection Aggregation Stages for Tropical Cyclone Seed Genesis<\/td>\n <\/tr>\n
A34-D3<\/td>\n \u856d\u7acb\u670b <\/td>\n Comparative Evaluation of Tropical Cyclone Genesis Indices under Global Warming in the Western North Pacific Using CMIP6 Models<\/td>\n <\/tr>\n
A36-D3<\/td>\n Tzu-Ling Lai<\/td>\n ISO modulations on Tropical cyclone activity around the Philippines<\/td>\n <\/tr>\n
A38-D3<\/td>\n \u738b\u8b49\u8c6a <\/td>\n Climate Change and Pests: An Analysis of Climatic Drivers of Locust Infestations since the Mid-17th Century in the Chinese Dynasty<\/td>\n <\/tr>\n
A40-D3<\/td>\n \u8521\u5049\u9298 <\/td>\n Co-occurring atmospheric features and their contributions to precipitation extremes:
\n Observations and high-resolution models<\/td>\n <\/tr>\n
B02-D3<\/td>\n \u674e\u4ead\u8431 <\/td>\n \u81fa\u7063\u8fd1\u671f\u9ad8\u6eab\u4e8b\u4ef6\u521d\u63a2 <\/td>\n <\/tr>\n
B04-D3<\/td>\n Saed Mohamed Omar<\/td>\n Rainfall Evenness and Its Influence on Water Storage Trends: A Case Study of East Africa<\/td>\n <\/tr>\n
B06-D3<\/td>\n \u8d99\u54c1\u8aed <\/td>\n \u5f85\u5b9a <\/td>\n <\/tr>\n
B08-D3<\/td>\n \u5289\u66c9\u8587 <\/td>\n \u81fa\u7063\u4e0d\u540c\u5ef6\u6642\u964d\u96e8\u5206\u6790-TReAD\u52d5\u529b\u964d\u5c3a\u5ea6\u8cc7\u6599 <\/td>\n <\/tr>\n
B10-D3<\/td>\n \u9673\u662d\u5b89 <\/td>\n \u5f85\u5b9a <\/td>\n <\/tr>\n
B12-D3<\/td>\n \u738b\u6bd3\u7407 <\/td>\n The Convective Upscale Evolution of Orographically- Locked Diurnal Convection from an Energy Perspective using Large-Eddy Simulations<\/td>\n <\/tr>\n
B14-D3<\/td>\n \u65bd\u7fbd\u99a8 <\/td>\n Is the "Dry Gets Drier, Wet Gets Wetter" Paradigm True for the Amazon Rainforest?<\/td>\n <\/tr>\n
B16-D3<\/td>\n \u5289\u6b23 <\/td>\n \u6696\u5316\u4e0b\u81fa\u7063\u6771\u90e8\u96f2\u9727\u68ee\u6797\u4e4b\u5fae\u6c23\u5019\u7279\u6027 <\/td>\n <\/tr>\n
B18-D3<\/td>\n \u7ae5\u88d5\u7fd4 <\/td>\n TReAD\u571f\u58e4\u6c34\u4efd\u8cc7\u6599\u65bc\u4e7e\u65f1\u4e8b\u4ef6\u8a55\u4f30 <\/td>\n <\/tr>\n
B20-D3<\/td>\n \u8303\u7950\u8ed2 <\/td>\n Identification of new pollution hotspots from satellite-based emission inventory under a local circulation-dominated environment over complex topography<\/td>\n <\/tr>\n
B22-D3<\/td>\n \u9ec3\u61f7\u9038 <\/td>\n How terrain shapes precipitation patterns in a northeasterly monsoon environment in Taiwan?<\/td>\n <\/tr>\n
B24-D3<\/td>\n \u5c24\u5b3f\u81fb <\/td>\n Characteristic of Heat Wave Events in Taiwan<\/td>\n <\/tr>\n
B26-D3<\/td>\n \u9673\u67cf\u8a00 <\/td>\n Cold Pool Interactions and Their Role in Modulating Convection over Complex Terrain<\/td>\n <\/tr>\n
B28-D3<\/td>\n \u85cd\u8a60\u8000 <\/td>\n POP2-waves\u8026\u5408\u6a21\u5f0f\u63a2\u8a0e\u6d77\u6d0b\u7de9\u885d\u80fd\u529b\u5728\u6ce2\u6d6a\u5c0d\u6d77\u6d0b\u78b3\u6e90\u548c\u78b3\u532f\u4e2d\u7684\u8abf\u9069 <\/td>\n <\/tr>\n
B30-D3<\/td>\n \u6731\u82b8\u9706 <\/td>\n The quasi climatological intrastasonal oscillation over the South China Sea and its relationship with summer monsoon onset and MJO<\/td>\n <\/tr>\n
B32-D3<\/td>\n \u5f35\u7b51\u6021 <\/td>\n Synergy between Heatwaves and Urban Heat Island in Three Major Cities of Taiwan<\/td>\n <\/tr>\n
B34-D3<\/td>\n \u9673\u51a0\u6770 <\/td>\n Spatiotemporal Characteristics and Long-Term Changes of Extreme Rainfall Events in Taiwan<\/td>\n <\/tr>\n
B36-D3<\/td>\n \u5f35\u5de7\u8587 <\/td>\n Capturing Weather Patterns through the Latent Feature in A Variational Autoencoder Model<\/td>\n <\/tr>\n
B38-D3<\/td>\n \u9673\u4f73\u90c1 <\/td>\n \u4e0d\u540c\u6b77\u53f2\u6c23\u5019\u91cd\u5efa\u65b9\u5f0f\u5c0d\u706b\u5c71\u4f5c\u7528\u7684\u97ff\u61c9-\u4ee5\u6b50\u6d32\u6c23\u5019\u6a21\u578bModE-RA\u8207\u4e2d\u7814\u9662\u6771\u4e9e\u6b77\u53f2\u6c23\u5019\u8cc7\u6599\u5eabREACHES\u70ba\u4f8b <\/td>\n <\/tr>\n
B40-D3<\/td>\n \u5b6b\u7fca\u9e92 <\/td>\n Arctic Amplification under Regional 4\u00d7CO2 Forcing : A Kernel-Based Decomposition of Climate Feedbacks <\/td>\n <\/tr>\n<\/table>\n<\/div><\/div>\n\n\t\t\t\n\t\t\t\n\t\t\t\t
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\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

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