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Annual Progress Report
CLEO 2011
Project
1.1 Climate scenarios
Project leader
Jonas Olsson, SMHI FoUh, 601 76 Norrköping, [email protected]
General Objective:
To provide tailored climate scenario data for the impact modelling in Cluster 3 of CLEO.
Short description of activities 2011:
Generally, the data from climate models (temperature, precipitation, etc.) have systematical errors
(bias) that need to be corrected before the data can be used in impact assessment. The correction
required may be analysed by comparing climate model data with observations in a historical period.
At SMHI, a bias correction method called Distribution-Based Scaling (DBS) has been developed
(Yang et al., 2010). A main activity during 2011 to which CLEO has contributed is to facilitate the
generation of bias-corrected regional climate scenarios for impacts studies by automatising the
DBS method and develop an interface (Appendix 1). This new system substantially increases the
flexibility of the bias-correction procedure and ensures fast and efficient provision of tailored data to
the impact studies perfomed by other CLEO partners. The system is presently being validated and
validated over different regions (Appendix 1). Further, discussions have been held with other CLEO
partners concerning the optimal type of climate data to provide and which strategy to use in the
subsequent impact modelling.
Deliverables 2011
D1.1.2, Draft regional climate scenarios, month 18 (2011-06-30), delivered
D1.1.3, Final regional climate scenarios, month 24 (2011-12-31), delayed
Status: The available bias-corrected climate scenaro data were presented at the 2011 All-Staff
meeting, which corresponds to D1.1.2. Final delivery of climate scenario data is possible at any
time and will be performed as soon as requested by Cluster 3.
Additional staff involved in project:
Joel Dahné, SMHI; Wei Yang, SMHI; Jörgen Rosberg, SMHI; Kean Foster, SMHI
Co-operation outside CLEO:
EU-projects GENESIS, SUDPLAN, ECLISE, IMPACT2C; COST Action ES1102 VALUE (Validating
and Integrating Downscaling Methods for Climate Change Research)
Reports and publications:
Yang, W., Andréasson, J., Graham, L.P., Olsson, J., Rosberg, J., and F. Wetterhall (2010)
Distribution-based scaling to improve usability of regional climate model projections for hydrological
climate change impact studies, Hydrol. Res., 41, 211-229.
Oral presentations:
Olsson., J. (2011) Climate adaptation: analyses of model results and development of tools, invited
talk at Urban hydrology and storm water managment, 9-10 November, Lund, Sweden (in Swedish).
Appendix 1. Illustration of the DBS bias-correction interface.