The NMME/SubX Science meeting was held at the NOAA Center for Weather and Climate Prediction in College Park, MD on 13-15 September 2017. The objective of the meeting is to highlight the extensive ongoing research into seasonal and subseasonal climate prediction, using retrospective and/or realtime forecast data from the North American Multi-Model Ensemble (NMME) and Subseasonal Experiment (SubX). Succeeded from NMME, the SubX project expands the interagency effort to subseasonal prediction research to test individual and multi-model ensemble predictions at timescales of weeks 3-4 and beyond through interaction between participant research teams.

The meeting started with a presentation entitled "Who cares about S2S research to improve forecasts?", showing a broad spectrum of end users across a wide variety of applications, such as agriculture production, utility planning, water resource management, fishing industry operation, public health surveillance, etc. Oral and poster sessions presented progress reports of systematic research efforts to improve prediction skill and reliability, which are summarized as follows.

1. Evaluate subseasonal prediction skill, focusing on major influencing systems, i.e. MJO, atmospheric blocking, monsoon, ENSO, NAO, etc., and forecast variability among different models (i.e., NCEP GEFS, Canadian GEPS, GEM-NEMO Coupled Model, NCAR CCSM4, ESRL/GSD Global FIM-iHYCOM Coupled Model, GFDL FLOR coupled model, NASA-GMAO's new S2S forecast system v. 2.1, Navy Earth System Model (NESM), etc.). Multi-model ensembles largely removed negative skill scores presented in individual forecasts. The comparison of numerical and statistical/analog approaches was also conducted. Experiments using ECMWF VarEPS and NCEP CFSv2 showed week 3+4 forecasts had more skill along the US east coast and the southwest US in winter, as well as over west/central US regions and the Intra-American Seas/east Pacific during summer.

2. Assess subseasonal predictability, placing emphases on the fidelity of predictability estimates, influence of ocean-atmosphere coupling and SST biases, sources of systematic biases, room for forecast skill improvement of global SST anomalies, systematic SST biases correspondence between short- and long-time-scale, predictability of North American drought, stratosphere-troposphere coupling and Northern Annular Mode (NAM) predictability, etc.

3. Improve prediction systems and products, including MME using objectively determined weights, Calibration, Bridging, and Merging (CBaM), UM/NOAA subseasonal excessive heat outlook system (v2), IRI real-time probabilistic seasonal forecasting, intraseasonal prediction of tropical cyclones, probabilistic prediction of short-term climate extremes, pattern-dependent bias correction and downscaling, prediction of atmospheric rivers, storm track activity, forecast of North Atlantic and U.S. land-falling tropical cyclones, streamflow forecasts, water deficit forecasting, etc.

4. Stand up to the challenges and prospects, pointing mainly to predictability of MJO, Initialization of dynamic vegetation and land soil moisture, Arctic sea ice predictability and forecast, etc.

For more information, see oral and poster presentation abstracts and files at the meeting web site https://cola.gmu.edu/kpegion/nmmeworkshop2017/index.html, where the meeting report is getting ready for public access in near future.