PARTNERING WITH THE NATIONAL SCIENCE FOUNDATION Michael C. Morgan Director, Division of Atmospheric and Geospace Sciences National Science Foundation

Mission of AGS To extend intellectual frontiers in atmospheric and geospace sciences by making responsible investments in fundamental research, technology development, and education that enable discoveries, nurture a vibrant, diverse scientific workforce, and help attain a prosperous and sustainable future.

Ideas to be explored NSF-NOAA sponsored Visitor Program University-based Nat’l Ensemble Program

NSF-NOAA sponsored Visitor Program Goal: To foster a closer cooperation between NCEP and the university community on problems relevant to NCEP’s mission requiring access to NCEP models Outcome: Support for joint research projects that contribute to advancing fundamental research in NWP and data assimilation, while also contributing to the improvement of NCEP models and data assimilation systems

NSF-NCEP VSP: Implementation Details remain (NOT FINAL) Use Dear Colleague Letter to notify community of eligible PIs of the opportunity Funding of requests determined by timing, mutual interest of NCEP staff, resources available Funding provided through supplements to existing awards

Collaboration of the Weather and Climate Communities to Advance Subseasonal-to-Seasonal Prediction: Research Issues Data assimilation for coupled models as a prediction and validation tool for weather and climate research; Seamless weather/climate prediction with Multi-model Ensemble Prediction Systems (MEPSs); Utilization of sub-seasonal predictions for social and economic benefits; The multi-scale organisation of tropical convection and its two-way interaction with the global circulation.

University-based Nat’l Ensemble Program Community engagement and education Ensemble modeling Conveying uncertainty NWP and data assimilation Model improvement (“physics”) Quasi-operational Virtual field campaigns

University-based Nat’l Ensemble Program Themes 1)No NWP forecast can be considered complete without a concomitant forecast of the associated flow dependent uncertainty. 2)“Uncertainties” are not necessarily obstacles in our ability to predict weather and climate, but are, in fact, important sources of information that may be used to enhance and extend our ability to predict (e.g., data assimilation).

Design of an ensemble system Selection of initial perturbations for ensembles requires that the perturbations grow (to ensure sufficient ensemble spread at future times) and that the initial perturbations share characteristics of analysis errors. Methods include: bred modes (NCEP), SVs (ECMWF) Effective perturbation selection Ensemble forecast trajectories may be underdispersive due to model errors/inadequacies. Ensembles generated from differing model physics, BCs, or different models have been implemented. Confronting model deficiencies

WRF model (48 member ensemble) of convective parameterizations, microphysics schemes, resolutions for Ernesto (2006) initialized 1200 UTC 26 August 2006 Grid Spacings Horizontal: 30km, 45km, 60km Vertical: 31 or 54 levels Cumulus Parameterizations (1) Kain-Fritsch (2) Betts-Miller-Janjic (3) Grell-Devenyi ensemble Microphysics Parameterizations (1) Kessler (warm rain) (2) Eta-Ferrier (3) WSM6 after Bassill (2006) obs. track

Some remaining challenges Conveying uncertainty to forecast consumers: What aspects of the forecast PDF are required (desired) by individual consumers? User-defined post-processing of ensemble output will be necessary. Can we effectively estimate higher moments of the forecast PDF? What is required? How might forecast consumer requirements influence the design of observational networks and the construction of ensemble systems?

Moving Forward Continuing engagement of community – including private sector Presentation at Unidata workshop this July Workshop of Pis this summer or early fall – link with GEO/OCI EarthCube activities (demonstation project?) Small university demonstration activity next winter or spring