Maintenance and Development of the Subseasonal Prediction Project (S2S) Database and Tools in IRI Data Library

Maintenance and Development of the Subseasonal to Seasonal Prediction Project

(S2S) Database and Tools in IRI Data Library

Principal Investigator: Dr. Andrew W. Robertson, International Research Institute for Climate

and Society (IRI), Columbia University, Palisades, NY.

The proposed work will maintain and fully develop the existing partial copy of the WWRP/WCRP

Sub-seasonal to Seasonal Prediction Project (S2S) database and tools in the IRI Data Library

(IRIDL) for the duration of Phase II of the S2S Prediction Project (2019-2023). This will include

adding the S2S ocean data from the primary S2S archive at ECMWF, together with any extensions

to it made at ECMWF such as new models. In so doing, the IRI Data Library (IRIDL) will serve

as a third archiving centre for S2S data, along with ECMWF and CMA. Beyond an S2S database

copy in the US, IRIDL will provide important new resources compared to those available through

ECMWF and CMA, accelerating S2S research and development of S2S applications. These will

include pre-computed lead-time dependent model climatologies, with large labor savings for users.

A suite of online tools with a Jupyter Notebook Python interface will enable users to access the S2S

database via OpenDAP without the need to download data, a significant advantage especially in

bandwidth-limited environments. These Python tools will enable diverse users to easily construct

weekly forecast anomalies, skill scores, and other derived variables such as weather regime indices

and vertically-integrated moisture fluxes. In addition, having the S2S database archived at the same

place as the SubX and NMME databases at IRI is a big advantage for researchers, enabling a direct

comparison of the American models with S2S models.

The proposed work addresses NOAA's 2nd Long-term mission goal Weather-Ready Nation,

where Society is prepared for and responds to weather-related events. The S2S timescale between

2 weeks and a season, bridging the gap between existing weather forecasts and seasonal climate

outlooks is recognized to be a critical one for early warning of weather hazards and one in which

significant advances are expected due to recent advances in models and MJO prediction skill in

particular. Serving the S2S database in IRIDL will significantly contribute to achieving this goal

by facilitating access by a broad spectrum of researchers and applications-developers, eliminating

the need for users to laboriously download there own 'dark copy' of the database and write their

own analysis codes. The increased uptake will translate into development of improved S2S forecast

products and user-applications, and will pave the way for applications of cloud computing to multimodel

forecast datasets in the future.

Through email communication with NOAA's Office of Weather and Air Quality, this proposal

targets the current NOAA Broad Agency Announcement, for the period 07/01/19 - 09/30/20 to

fund the first 2 years of the proposed project. We expect to submit a subsequent proposal to cover

the remainder of the project (years 3-5), which extends through 12/31/23.