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4th General Assembly http://www.meteo.unican.es/ensembles Prague 12-16 November 2007 Hands-on Demonstration of the Statistical Downscaling Portal for Regional Climate Change Projection José M. Gutiérrez Daniel San-Martín, Antonio S. Cofiño, Carmen Sordo, Jesús Fernández, Dolores Frías, Miguel A. Rodríguez, S. Herrera, Rafael Ancell, M.R. Pons, B. Orfila, E. Díez Clare Goodess (CRU), Francisco Doblas-Reyes (ECMWF) Applied Meteorology Research Group, Santander, Spain Motivation http://www.meteo.unican.es/ensembles There are many projects around the world producing global (GCM) and regional (RCM) simulations of climate change. Many of these projects involve end-uses from impact sectors ... However, it is still difficult for end-users to access the stored simulations and to post-process them to be suitable for their own models: daily resolution, interpolation to prescribed locations, etc. There is a need of friendly interactive tools so users can easily run interpolation/downscaling jobs on their own data using the existing downscaling techniques and simulation datasets (AR4, Prudence, ENSEMBLES, ...). Collaboration with End-Users http://www.meteo.unican.es/ensembles Two ongoing research collaborations with s2d users. Fabio Micale Iacopo Cerrani Giampiero Genovese Downscale DEMETER and ENSEMBLES s2d hindcasts to get daily precip, radiation, wind speed, and maximum/minimum temperatures to make crop yield modeling. The goal is to compare the downscaled data to GCM outputs and to estimate seasonal predictability. ELECTRICITÉ DE FRANCE Laurent Dubus Marta Nogaj Downscale DEMETER and ENSEMBLES s2d hindcasts to get daily maximum and minimum temperatures to make electricity demand forecasts. The goal is to compare the downscaled data to GCM outputs. Local precipitation forecasts for hydropower production capacities. http://www.meteo.unican.es/ensembles www.meteo.unican.es/ensembles http://www.meteo.unican.es/ensembles Data Access Portal 60,Potential Vorticity,PV 129,Geopotential,Z 130,Temperature,T 131,U velocity,U 132,V velocity,V 133,Specific humidity,Q 136,Total Column Water,TCW 137,Total Column Water Vapour,TCW 138,Relative vorticity,VO 142,Large Scale Precipitation,LSP 143,Convective Precipitation,CP 151,MSLP,MSL 155,Divergence,D 157,Relative humidity,R 165,10m E-Wind Component,10U 166,10m N-Wind Component,10V 167,2m Temperature,2T 168,2m Dew Point,2D 1000, 925, 850, 700, 500, 300 mb 00, 06, 12, 18 , 24 UTC 1.125ºx1.125º resolution http://www.meteo.unican.es/ensembles Data Access: s2d & acc Statistical Downscaling Portal http://www.meteo.unican.es/ensembles Problem: Local climate change prediction for Madrid (Spain): maximum temperature Goal: Provide daily local values for the summer season june-august 2010-2040 in a suitable format (e.g., text file, or Excel file). Predictors (T(1ooo mb),..., T(500 mb); Global zone Local zone Z(1ooo mb),..., Z(500 mb); H(1ooo mb),..., H(500 mb)) Xn Downscaling Model Regres, CCA, … Yn = WT Xn Predictands Precipitation Temperature Yn This is the structure followed in the portal’s design: predictors + predictand + downscaling method. http://www.meteo.unican.es/ensembles Demo... My Home The “My Home” tab allows the user to explore: 1. The zones (pre-defined regions). 2. The profile with the account information. 3. The status of the jobs: queued, running, finished. http://www.meteo.unican.es/ensembles Demo... Predictors A simple zone with a single predictor parameter: T850mb was created. New zones can be easily defined by clicking in the “new zone” button. http://www.meteo.unican.es/ensembles Demo... predictand http://www.meteo.unican.es/ensembles Demo... Downscaling Method http://www.meteo.unican.es/ensembles Demo... Validation http://www.meteo.unican.es/ensembles Demo... Regional Projection Demo... Computing Time http://www.meteo.unican.es/ensembles Scheduling the job Five minutes later ... http://www.meteo.unican.es/ensembles Distributed Data Access PRESENT FUTURE Typical Application Distributed-data Application Downs. Portal Downs. Portal netCDF lib OpenDAP Client Local access to data Data (local) s2d RCM ACC GCM ACC Paco Doblas-Reyes Antje Weisheimer Philippe Gachon OpenDAP Via http OpenDAP Servers Data (ECMWF) Data (DMI) Data (remote) http://www.meteo.unican.es/ensembles Big Projects ... Using Restricted Data http://www.meteo.unican.es/ensembles Summary • Nowadays, Statistical Downscaling (SD) is a mature field and there is a huge amount of data (observations, reanalysis and simulations) to apply SD techniques in a variety of problems. • Web-based interactive tools (such as the statistical downscaling portal) can help endusers to explore and use this information. • These tools should be part of the different climate change projects in order to maximize the analysis and explotation of the results. http://www.meteo.unican.es/ensembles Future Plans • Support end-users using the portal (complete documentation). • Link the portal to the DMI database of regional models. • Connect with existing E-Science EU initiatives (EGEE Earth Science VO). Santander is one of the nodes of the National Supercomputing Center and has also great experience in GRID computing. http://www.meteo.unican.es/ensembles Final Remark Without data we are nothing and our work is useless !!! so we highly encourage CERA and GCM providers to work as much as they can to put their data in CERA as quick as possible.