(WCRP Seasonal Prediction Workshop) Applied Meteorology Group ENSEMBLES Web Portal for Seasonal Statistical Downscaling. Description and Demo (WCRP Seasonal Prediction Workshop) Antonio S. Cofiño Daniel San-Martín José Manuel Gutiérrez Dept. of Applied Mathematics and Computational Sciences University of Cantabria, Spain Univ. Cantabria – INM Applied Meteorology Group AI met group http://www.meteo.unican.es/ensembles

Xn Yn Downscaling Portal. Local Predictions for End-Users There is a gap between the global low-resolution simulations and the high-resolution needed for end-users’ applications. One of the solutions is statistical downscaling. Example: Forecast models for electricity demand require local predictions of daily temperatures in a number of cities (local stations). (See Laurent Dubus’ Poster) Goal: Provide predictions of daily local values for individual members for a season JJA 2007 in a suitable format (e.g., text file, or Excel file). Temperature Yn Predictands The portal helps with the Downscaling Workflow: Predictors T 1000mb Q 1000mb Z 500mb Xn SLP Yn = F(Xn) Downscaling Model This is the structure that we followed in the portal’s design.

Datasets uploaded by users (private). e.g. EDF dataset. Data Available in the Portal (so far!!) Reanalysis: ERA40 (1957-2002) NCEP (1948-2007) JRA25 (1979-2006) Seasonal Hindcasts: DEMETER (1958-2001, 7 models, 9 members) ENSEMBLES S1 (1991-2001, 3 model, 9 members) INM/RCA 0.5 (1991-2001, 1 model, 9 members) ECMWF System2 (1987-2006, 5-40 members) MARS-Stat Data ECA Data Observations: 0.5x0.5 grid over Europe provided by JRC 1000 local points provided by ECA. Datasets uploaded by users (private). e.g. EDF dataset.

Testbed: ENSEMBLES s2d data providers. Distributed Data Access. OpenDAP Local Data OpenDAP Client Downs. Portal OpenDAP Via https OpenDAP Servers INTERNET Distributed-data Data (ECMWF) (NCEP) (others) Data Providers Downs. Portal netCDF lib Local access to data Testbed: ENSEMBLES s2d data providers. (F. Doblas-Reyes) Work smarter, Generalized distributed data access protocols – “give me exactly and only what I need” Data (local)

Downscaling Methods One of the main goals of the portal is including AS MANY downscaling methods AS POSSIBLE. Weather Typing Analogues K-Means Self Org. maps Regression Methods Linear Neural Nets CCA Weather Generators Markov Chains Stochastic Models Bayesian Nets Perfect-Prog validation using reanalysis data. (Error estimation associated with the downscaling method)

LIVE DEMO !!! http://www.meteo.unican.es/ensembles

Near Future A first operational version of the portal would be released in September 2007. Open to the research community (preserving restrictions from data providers). Look for users and data providers to extend the portal to other world regions. Calibration of Models. The GRID technology will provide access to distributed resources allowing to share compute and storage resources. E-infrastructure shared Between Europe and Latin America