The Subseasonal Experiment (SubX)
An NCEP Global Ensemble Forecast System for Monthly Forecasts
Lead PI: Yuejian Zhu (NOAA/EMC)
Co-PIs: Malaquías Peña (NOAA/EMC), Wei Li (NOAA/EMC), Xiaqiong Zhou (NOAA/EMC), Hong Guan (NOAA/EMC)
Collaborators: Dingchen Hou (NOAA/EMC), Richard Wobus (NOAA/EMC), Xu Li (NOAA/EMC), Qin Zhang (NOAA/CPC),
Dan Collins (NOAA/CPC), Jon Gottschalck (NOAA/CPC)
▼Abstract: This project will construct, test and prepare for implementation an ensemble forecast system for the 1-35 days lead-time with the more advance ensemble methods, coupled with realistically evolving SST that outperforms current skill benchmarks, providing routine forecast outputs to CPC forecasters and contributing to the NMME-Phase 2 sub-seasonal project.
The motivation of this project is the potential to implement a two-tiered GEFS forecast and hindcast system of "opportunity", which can be setup and run routinely within a year. The two-tiered approach consists in prescribing bias-corrected predicted SSTs from the CFSv2 as the integration of the GEFS moves forward. The approach has been tested in the parallel version of the GEFS in a limited set of experiments resulting in skill gains in predicting the MJO signal and reducing the RMSE of forecasts of upper air circulations for weeks 3 and 4. The hindcast is being completed for the first 16-days forecast segment and an extension to the 35-days can be generated for the last 20 years and be setup to provide real-time updates. In parallel with this activity, a next version of the GEFS will be tested in which surface (SST and land) variables are stochastically perturbed to represent analysis uncertainty at initial time.
The proposal targets Priority 3a of the MAPP-CTB FY16 Competition 1: NOAA Climate Test Bed - Accelerating Transition of Research into Operations. The project will select a prediction system suitable for inclusion in an operational multi-model ensemble system, optimize the design of the system, and evaluate prediction products from the system. A major activity will be to test the skill and demonstrate suitability of the selected prediction system for real- time prediction on subseasonal timescales. The proposed prediction system has a pre-existing, documented capability to simulate some of the phenomena and drivers relevant on subseasonal timescales (e.g., Madden Julian Oscillation and blocking) and produces extended-lead skill from initialization. A baseline 35-days GEFS without enhanced surface forcing (referred to as Control MGEFS) was setup to perform real-time predictions twice per week to show sustained real-time production as part of NOAA’s operational prediction activities. A plan to share real-time data with NOAA Central Operations and the broader multi-model ensemble prediction system research team is included. The project is in line with the NOAA’s Next-Generation Strategic Plan, particularly the NWS’ Weather Ready Nation by providing high quality numerical guidance to severe weather in the medium to extended range.