Predictability Studies
Weather Predictability:
Zhao, L., Wang, S.-Y., J. Jin and A. J. Clark, 2014: WRF model simulations of a rare springtime bow echo near the Great Salt Lake. Meteorological Applications (Royal Met. Soc.), DOI: 10.1002/met.1455. (PDF)
Wang, S.-Y., and A. J. Clark, 2010: NAM model forecasts of warm season quasi-stationary frontal environments in the central U.S. Weather and Forecasting, 25, 1281–1292.
Wang, S.-Y., T.-C. Chen, and S. E. Taylor, 2009: Evaluations of NAM forecasts on midtropospheric perturbation-induced convective storms over the U.S. northern plains. Weather and Forecasting, 24, 1309–1333.
Subseasonal to Seasonal (S2S) Prediction:
Promchote, P., B. Pokharel, L. Deng, S.-Y. Wang, J.-H. Yoon, and P. Kittipadakul, 2023: Boosting Thailand's Palm Oil Yield with Advanced Seasonal Predictions. Environmental Research Letters, DOI:10.1088/1748-9326/ace06c (PDF)
Lee, C.-T., S.-Y. Wang, and T.-T. Lo, 2022: A revised Meiyu-season onset index for Taiwan based on ERA5. Atmosphere, DOI:10.3390/atmos13111762 (PDF)
Mukherjee, S., S.-Y. Wang, D. Hirschfeld, J. Lisonbee, and R. Gillies, 2022: Feasibility of Adding Twitter Data to Aid Drought Depiction: Case Study in Colorado. Water, DOI:10.3390/w14182773 (PDF)
Son, R., P.-L. Ma, H. Wang, P. J. Rasch, S.-Y. Wang, H. Kim, J.-H. Jeong, K.-S. Lim, J.-H. Yoon, 2022: Machine Learning provides substantial improvements to county-level fire weather forecasting over the western United States. Journal of Advances in Modeling Earth Systems, DOI: 10.1029/2022MS002995 (PDF)
Promchote, P., S.-Y. Wang, B. Black, and P. G. Johnson, 2020: Subseasonal prediction for bloom dates of tart cherries in Utah and Michigan, USA: Merging phenological models with CFSv2 forecast. International Journal of Biometeorology, in press (PDF)
Promchote, P., S.-Y. Wang, Y. Shen, P. G. Johnson, and M.-H. Yao, 2017: A seasonal prediction for the wet-cold spells leading to winter crop damage in northwestern Taiwan with a combined empirical-dynamical approach. International Journal of Climatology, DOI: 10.1002/joc.5194 (PDF).
Schroeder, M., S.-Y. Wang, and R. R. Gillies, and H.-H. Hsu, 2016: Extracting the tropospheric short-wave influences on subseasonal prediction of precipitation in the United States using CFSv2. Climate Dynamics, DOI 10.1007/s00382-016-3314-1, (PDF)
Wang, S.-Y., Y.-H. Lin, R. R. Gillies, and K. Hakala, 2016: Indications for protracted groundwater depletion after drought over the Central Valley of California. Journal of Hydrometeorology, DOI: 10.1175/JHM-D-15-0105.1, (PDF).
Wang, S.-Y., D. Barandiaran, K. Hilburn, P. Houser, et al., 2014: Could the 2012 drought in central U.S. have been anticipated? - A review of NASA working group research. J. Earth Sci. Engineering, 4, 428-437 (PDF) - an invited review
Barandiaran, D. and S.-Y. Wang, 2013: The Missing Teleconnection Between the North Atlantic and Sahel Precipitation in CFSv2. Atmospheric Science Letters (RMS), DOI: 10.1002/asl2.457.
Wang, S.-Y., H.-H. Chia, R. R. Gillies, and X. Jiang, 2013: Quasi-biweekly mode and its modulation on the diurnal rainfall in Taiwan forecasted by the CFS. Weather and Forecasting. 28, 981-993 (pdf).
Gillies, R. R., S.-Y. Wang, Y. Sun, and O.-Y. Chung, 2013: Supportive empirical modeling for the forecast of monsoon precipitation in Nepal. International Journal of Climatology, 33, 3047-3054 (PDF).
Wang, S.-Y., M. L’Heureux, and H-H Chia, 2012: ENSO prediction one year in advance using Western North Pacific sea surface temperatures. Geophysical Research Letters, 39, L05702 (pdf).
Gillies, R. R., S.-Y. Wang, J.-H. Yoon, and S. Weaver, 2010: CFS prediction of winter persistent inversions in the Intermountain Region. Weather and Forecasting, 25, 1211–1218.
Decadal Predictability:
Huang, S.-H., P.-Y. Lai, S.-Y. Hwang, K. Borhara, W.-R. Huang, and S.-Y. Wang, 2022: Climate Variability Shifting Immigrated Rice Planthoppers in Taiwan. Climate, DOI: 10.3390/cli10050071
Chikamoto, Y., S.-Y. Wang, M. Yost, L. Yocom, and R. R. Gillies, 2020: Colorado River water supply is predictable on multi-year timescales owing to long-term ocean memory. (Nature) Communications Earth & Environment, DOI:10.1038/s43247-020-00027-0 (PDF)
Chikamoto, Y., J. Johnson, S.-Y. Wang, M. J. McPhaden, and T. Mochizuki, 2020: El Niño Southern Oscillation evolution modulated by Atlantic forcing, Journal of Geophysical Research: Oceans, in press (PDF)
Plucinski, B., S. Wang, Y. Sun, R. R. Gillies, J. Eklund, C.-C. Wang, 2019: Feasibility of Multi-Year Forecast for the Colorado River Water Supply: Time Series Modeling. Preprints, 2019080294 (doi: 10.20944/preprints201908.0294.v1).
Sun, Y., S.-Y. Wang, R. Li☃, B. Buckley, R. Gillies, and K. Hansen, 2018: Feasibility of Predicting Vietnam’s Autumn Rainfall Regime Based on Tree Ring Record and Decadal Variability. Climate, DOI:10.3390/cli6020042 (PDF)
Wang, S.-Y., Lin, Y.-H., and Wu, C.-H., 2016: Interdecadal change of the active-phase summer monsoon in East Asia (Meiyu) since 1979. Atmosph. Sci. Lett., 17: 128–134. doi: 10.1002/asl.603 (open-access)
Li, R., S.-Y. Wang, R. R. Gillies, B. Buckley, L. H. Troung, C. Cho, 2015: Decadal oscillation of autumn precipitation in central Vietnam modulated by the East Pacific-North Pacific (EP-NP) teleconnection. Environmental Research Letters, 10 024008, (PDF).
Gillies, R. R., O.-Y. Chung, S.-Y. Wang, J. DeRose, and Y. Sun, 2015: Added value from 576 years of tree-ring record in the prediction of the Great Salt Lake level. Journal of Hydrology, 529: 962-968. (PDF).
➥ prediction for Great Salt Lake level
Wang, S.-Y., K. Hakala, R. R. Gillies, and W. J. Capehart, 2014: The Pacific Quasi-Decadal Oscillation (QDO) - An important precursor towards anticipating major flood events in the Missouri River Basin? Geophysical Research Letters, 41, 991-997 (link).
Wang, S.-Y., and A. J. Clark, 2011: Quasi-decadal spectral peaks of tropical Western Pacific SSTs as a precursor for tropical cyclone threat. Geophys. Res. Lett., 37, L21810.
Gillies, R. R., O.-Y. Chung, S.-Y. Wang, and P. Kokoszka, 2011: Incorporation of Pacific SSTs in a time series model towards a longer-term forecast for the Great Salt Lake elevation. Journal of Hydrometeorology, 12, 474-480.
