2015
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Dai, Q., Han, D., Rico-Ramirez, M.A., Zhuo, L., Nanding, N. & Islam, T., 2015, Radar rainfall uncertainty modelling influenced by wind, Hydrological Processes, 29: 1704-1716.
https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.10292
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Dai, Q., Rico-Ramirez, M.A., Han, D., Islam, T. & Liguori S. 2015, Probabilistic radar rainfall nowcasts using empirical and theoretical uncertainty models, Hydrological Processes, 29: 66-79.
https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.10133
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Dai, Q., Han, D., Zhuo, L., Huang J., Islam, T., & Srivastava, P.K. 2015, Impact of complexity of radar rainfall uncertainty model on flow simulation, Atmospheric Research, 161-162: 93-101.
https://www.sciencedirect.com/science/article/pii/S0169809515001027
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Dai, Q., Han, D., Zhuo, L., Huang J., Islam, T. & Zhang, S. 2015, Adjustment of wind-drift effect for real-time deviation correction in radar rainfall data, Physics and Chemistry of the Earth, 83-84: 178-186.
https://www.researchgate.net/publication/281325624_Adjustment_of_wind-drift_effect_for_real-time_systematic_error_correction_in_radar_rainfall_data
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Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O’Neill, P., Islam, T., Gupta, M. & Dai, Q. 2015, Performance evaluation of WRF-Noah Land surface model estimated soil moisture for hydrological application: Synergistic evaluation using SMOS retrieved soil moisture, Journal of Hydrology,511: 17-27
https://www.sciencedirect.com/science/article/pii/S0022169415005478
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Zhuo, L., Dai, Q. & Han, D., 2015, Meta-analysis of flow modeling performances—to build a matching system between catchment complexity and model types, Hydrological Processes, 29: 2463–2477.
https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.10371
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Zhuo, L., Han, D., Dai, Q., Islam, T., & Srivastava, P.K., 2015, Appraisal of NLDAS-2 multi-model simulated soil moistures for hydrological modelling, Water Resources Management, 29: 3503-3517.
https://link.springer.com/article/10.1007/s11269-015-1011-1
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Islam, T., Srivastava, P.K., Dai, Q., Gupta, M. & Zhuo, L. 2015, An introduction to factor analysis for radio frequency interference (RFI) detection on satellite observations. Meteorological Applications, 22: 436-443.
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/met.1473
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Srivastava, P.K., M.A., Islam, T., Gupta, M., Petropoulos, G., & Dai, Q. 2015, WRF dynamical downscaling and bias correction schemes for NCEP estimated Hydro-meteorological variables. Water Resources Management, 29: 2267-2284.
https://link.springer.com/article/10.1007/s11269-015-0940-z
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Islam, T., Srivastava, P.K., Rico-Ramirez, M.A., Dai, Q., Gupta, M. & Singh, S.K. 2015, Tracking a tropical cyclone through WRF ARW simulation and sensitivity of model physics. Natural Hazards, 76: 1473-1495.
https://link.springer.com/article/10.1007/s11069-014-1494-8
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Zhuo, L., Dai, Q., & Han, D., 2015, Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application, Physics and Chemistry of the Earth, 83-84: 146-155.
https://www.sciencedirect.com/science/article/pii/S1474706515000728
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Islam, T., Rico-Ramirez, M.A., Srivastava, P.K., Dai, Q., Han, D & Zhuo, L. 2015, Rain Rate Retrieval Algorithm for Conical-Scanning Microwave Imagers Aided By Random Forest, RReliefF and Multivariate Adaptive Regression Splines (RAMARS). IEEE Sensors Journal, 15: 2186-2193.
https://ieeexplore.ieee.org/document/7031473
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Islam, T., Srivastava, P.K., Dai, Q. & Wan Jaafar, W.Z. 2015, Stratiform/convective rain delineation for TRMM microwave imager. Journal of Atmospheric and Solar-Terrestrial Physics, 133: 25-35.
https://www.sciencedirect.com/science/article/pii/S1364682615300158
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Dai, Q., Zhuo L. & Han, D., 2015, Decision making for urban drainage systems under uncertainty caused by weather radar rainfall measurement, EGU General Assembly, Vienna, Austria.
https://ui.adsabs.harvard.edu/abs/2015EGUGA..17.3340D/abstract