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Poster Presentations

The abstracts can be found in the programme book.

Verification of high impact weather and extremes

  • Sharpe, Michael and Bysouth, Clare: Extreme Verification ... relatively speaking (P HIW-1)
  • Chen, Guomin: Verification of operational tropical cyclone forecast from 2010 to 2016 in western North Pacific (P HIW-2)
  • Wang, Haiping: ECMWF and NCEP ensemble predictions verification of typhoon intensity during 2011-2015 (P HIW-3)
  • Kox, Thomas et al.: Towards a user-oriented improvement of weather warnings. Opportunities and constraints for future developments (P HIW-4)
  • Zingerle, Christoph and Hölzl, Simon: Verification of extreme weather warnings: How to define verifying events? (P HIW-5)

User-oriented verification and estimation of forecast value

  • Sharpe, Michael et al.: Space - the final verification frontier? (P USR VAL-1)
  • Jelbart, Joe and Butcher, Paige: Improved Airport Forecast Verification for Forecasters (P USR VAL-2)
  • Yuan, Meiying et al.: Study on meteorological grade of the Forest Fire Danger and rationality verification (P USR VAL-3)
  • Mahringer, Guenter: TREND Forecast Verification in the MET Alliance (P USR VAL-4)

Meta-verification, properties of verification methods

  • Brassington, Gary: MAE and RMSE: which is the better measure of model performance? (P META-1)
  • Kim, Ki-Byung et al.: The verification of typhoon forecast results by global model (P META-2)
  • Ashrit, Raghavendra et al.: CRA Vs MODE for Heavy Rain Cases over India (P META-3)

Software and measures used to evaluate operational predictions, including verification methods used to justify upgrades to operational models

  • Kwon, Young and Lee, Eun-Hee: The overview of the verification systems of the KIAPS next generation model (P OPS SOFT-1)
  • Li, Li: The update of NMC operational verification system and results analysis in the past 26 years for upper-air products of deterministic NWP (P OPS SOFT-2)
  • Ioannou, Ioanna et al.: Using Python tools to deliver flexible, repeatable verification to support evidence driven forecast automation (P OPS SOFT-3)
  • Manubens, Nicolau: s2dverification: an R package for climate forecast verification (P OPS SOFT-4)
  • Chen, Jing et al.: The key programme of CMA for Development of Forecast Verification Technique (CMA-FVRT), an introducton (P OPS SOFT-5)
  • Brassington, Gary et al.: Adaptive population selection for verification data mining (P OPS SOFT-6)
  • Lemay, Francois and Husson, Thierry: Emet or forecast verification using the power of a relational database (P OPS SOFT-7)
  • Jensen, Tara et al.: Enhanced Verification Capability within the Developmental Testbed Center (P OPS SOFT-8)
  • Letestu, André-Charles and Cattani, Daniel: How MeteoSwiss measure the overall quality of its forecasts (P OPS SOFT-9)

Spatial verification methods and verification approaches

Observation uncertainty


Sub-seasonal to seasonal

  • Lee, Hyun_Ju et al.: Evaluation of Heat Wave forecasting using large scale circulation pattern based on TIGGE data (P S2S-1)
  • Sohn, Soo-Jin and Tam, Chi-Yung: Verification for long-lead station-scale prediction of hydrological droughts in South Korea based on bivariate pattern-based downscaling (P S2S-2)
  • Kubo, Yutaro: MJO verification by JMA Global Ensemble Prediction System (P S2S-3)
  • Romanova, Vanya et al.: Verification and predictability of the surface heat and freshwater fluxes on seasonal and decadal timescales using multiple reanalysis data sets (P S2S-4)
  • Matsueda, Mio et al. : The TIGGE and S2S Museums - websites of ensemble forecast products (P S2S-5)
  • Kim, Gayoung et al.: Assessment of WMO LC-LRFMME Models in Seasonal Climate Prediction (P S2S-6)
  • Coelho, Caio and Firpo, Mári: A verification framework for South American sub-seasonal precipitation predictions (P S2S-7)

Verification studies