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(* below means number of articles weakly related to TIGGE)

2019
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2019
2019

(2)

  • Berman J, Torn R (2019) The Impact of Initial Condition and Warm Conveyor Belt Forecast Uncertainty on Variability in the Downstream Waveguide in an ECWMF Case Study. Monthly Weather Review, 147, 4071-4088, https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-18-0333.1
  • Tang N J et al. (2019). Characteristic of adiabatic and diabatic water vapor transport from the troposphere to the stratosphere over the Tibetan Plateau and its comparison with the Rocky Mountains in the Summer. Chinese Journal of Atmospheric Sciences (in Chinese, in press), doi:10.3878/j.issn.1006-9895.1804.17255.
  • Weihong Qian, Jing Huang (2019) Applying the anomaly-based weather analysis on Beijing severe haze episodes. Science of the Total Environment, 647, 878–887, https://doi.org/10.1016/j.scitotenv.2018.07.408

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  • Agogbuo CN, Nwagbara MO, Bekele E, Olusegun A (2017) Evaluation of Selected Numerical Weather Prediction Models for a Case of Widespread Rainfall over Central and Southern Nigeria. J Environ Anal Toxicol 7: 491. doi: 10.4172/2161- 0525.1000491
  • Cai et al. (2018) Improving TIGGE precipitation forecasts using an SVR ensemble approach in the Huaihe River Basin. Advances in Meteorology,vol. 2018. https://doi.org/10.1155/2018/7809302

  • Cafaro, C., Frame, T. H., Methven, J., Roberts, N. and Broecker, J. (2018). The added value of convection-permitting ensemble forecasts of sea breeze compared to a Bayesian forecast driven by the global ensemble. Q. J. Roy. Met. Soc.

  • Cheng-Chien Liu *, Ming-Chang Shieh, Ming-Hsun Ko, Kung-Hwa Wang (2018) Flood Prevention and Emergency Response System Powered by Google Earth Engine, Remote Sensing, 10, 1283
  • M. David et P. Lauret (2018) Solar Radiation Probabilistic Forecasting », in Wind Field and Solar Radiation Characterization and Forecasting, R. Perez, Éd. Cham: Springer International Publishing, p. 201‑227.
  • Deng H., et al.(2018) Changes of snowfall under warmer and wetter in the Tianshan Mountains. Scientia Geographica Sinica, 38(11):1932-1941, http:/10.13249/j.cnki.sgs.2018.11.021[Chinese Journal with english abstract]
  • Duriez O, Péron G, Gremillet, D, Sforzi A, Monti F. (2018) Migrating ospreys use thermal uplift over the open sea. Biol. Lett. 20180687. http://dx.doi.org/10.1098/rsbl.2018.0687
  • Elless, T.J. and R.D. Torn, 2018: African Easterly Wave Forecast Verification and Its Relation to Convective Errors within the ECMWF Ensemble Prediction System. Wea. Forecasting, 33, 461–477, https://doi.org/10.1175/WAF-D-17-0130.1
  • Falck et al (2018) Improving the use of ground-based radar rainfall data for monitoring and predicting floods in the iguacu river basin. Journal of Hydrology, 567:626–636, 2018. https://doi.org/10.1016/j.jhydrol.2018.10.046
  • González-Arribas, D., Sanjurjo-Rivo, M., Soler, M. (2018) Multiobjective Optimisation of Aircraft Trajectories Under Wind Uncertainty Using GPU Parallelism and Genetic Algorithms. Computational Methods in Applied Sciences, vol 49. Springer, Cham https://link.springer.com/chapter/10.1007%2F978-3-319-89890-2_29
  • González-Alemán et al. (2018) Use of Ensemble Forecasts to Investigate Synoptic Influences on the Structural Evolution and Predictability of Hurricane Alex (2016) in the Midlatitudes. Mon. Wea. Rev., 146, 3143-3162, https://doi.org/10.1175/MWR-D-18-0015.1
  • Hamill, T. M., and Scheuerer, M., 2018: Probabilistic precipitation forecast postprocessing using quantile mapping and rank-weighted best-member dressing. Mon. Wea. Rev., 146, 4079-4098. Also: Online appendix 1.
  • Herman, G.R., and R.S. Schumacher (2018) Money doesn't grow on trees, but forecasts do: Forecasting extreme precipitation with random forests. Monthly Weather Review, 146, 1571-1600.
  • Jaiswal, Neeru, C. M. Kishtawal, and Swati Bhomia. "Similarity-based multi-model ensemble approach for 1–15-day advance prediction of monsoon rainfall over India." Theoretical and Applied Climatology 132.1-2 (2018): 639-645.
  • Kikuchi, Ryota, et al. (2018) Nowcasting algorithm for wind fields using ensemble forecasting and aircraft flight data. Meteorological Applications 25.3, 365-375, https://doi.org/10.1002/met.1704
  • Luitel, B., G. Villarini, and G.A. Vecchi (2018) Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones, Journal of Hydrology, 556, 1026-1037
  • Nakanowatari, T., Inoue, J., Sato, K., Bertino, L., Xie, J., Matsueda, M., Yamagami, A., Sugimura, T., Yabuki, H., and Otsuka, N.: Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system, The Cryosphere, 12, 2005-2020, https://doi.org/10.5194/tc-12-2005-2018, 2018.
  • Martinez-Alvarado, O., Maddison, J., Gray, S. and Williams, K. (2018) Atmospheric blocking and upper-level Rossby wave forecast skill dependence on model configuration. Quarterly Journal of the Royal Meteorological Society, 144, 2165-2181, https://doi.org/10.1002/qj.3326
  • MA Hongyuan,HUANG Jianxi,HUANG Hai,ZHANG Xiaodong,ZHU Deha. (2018) Ensemble Forecasting of Regional Yield of Winter Wheat Based on WOFOST Model Using Historical Metrological Dataset[J].Transactions of the Chinese Society for Agricultural Machinery, 49(9):257-266.
  • Parker, T., Woollings, T., and Weisheimer, A. (2018) Ensemble sensitivity analysis of Greenland blocking in medium-range forecasts, Quart. J. Roy. Meteor. Soc, 144, 2358-2379, https://doi.org/:10.1002/qj.3391
  • Tomasella et al (2018) Probabilistic flood forecasting in the Doce basin in Brazil: Effects of the basin scale and orientation and the spatial distribution of rainfall. Journal of Flood Risk Management, 0(0):e12452, 2018/11/26 2018. https://doi.org/10.1111/jfr3.12452
  • Torn, R. D., T. J. Elless, P. Papin, C. A. Davis, 2018: The sensitivity of TC track forecasts within deformation steering flows. Mon. Wea. Rev., 146, 3183–3201, https://doi.org/10.1175/MWR-D18-0153.1 
  • Uno, F., et al., (2018) A diagnostic for advance detection of forecast busts of regional surface solar radiation using multi-center grand ensemble forecasts , Solar Energy, 162, 196- 204.https://doi.org/10.1016/j.solener.2017.12.060
  • Yamagami et al. (2018) Predictability of the 2012 great Arctic cyclone on medium-range timescales. Polar Science, 15, 13-23, https://doi.org/10.1016/j.polar.2018.01.002 
  • Yamagami et al. (2018) Medium-range forecast skill for extraordinary Arctic cyclones in summer of 2008- 2016. Geophys. Res. Lett., 45, https://doi.org/10.1029/2018GL077278
  • Wang Haibo et al.(2018). Effects of different cloud overlapping patameters on simulated total cloud fraction over the globe and East Asian region.Acta Meteorologica Sinica, 76(5):767- 778,doi:10.11676/qxxb2018.027

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