Presentation on theme: "GYC108 Climate and society Regional climate downscaling – in practice."— Presentation transcript:
GYC108 Climate and society Regional climate downscaling – in practice
Projected changes in annual rainfall (PRCP) and maximum temperature (TMAX) in Djibouti by the 2050s downscaled from seven GCMs under SRES A2 emissions. Data source: Climate Systems Analysis Group, University of Cape Town Choice of GCM(s): affects all downscaled scenarios
Comparable skill of statistical and dynamical methods Correlation of modelled and observed precipitation indices for each season for SEE. Bars show inter-quartile range and median with 5th and 95th percentiles indicated by outer range. Source: Haylock et al. (2006)
Choice of downscaling method determines local scenario Projected changes in spring precipitation totals for the 2080s for two downscaling methods (UCT, SDSM) and three climate models (CSIRO, ECHAM4, HadCM3) under SRES A2 emissions. Source: Wilby & DMN (2007)
Predictability varies in space and time Variations in the strength of the correlation between daily wet–day amounts at Eskdalemuir (55º N, 3º W) and mean sea level pressure (MSLP), and near surface specific humidity (QSUR) over the Scottish Borders region, 1961–1990.
Choice of predictor variable domain Frequency and location of predictors selected for downscaling daily precipitation occurrence (top) and amounts (bottom) at selected sites across Iberia (crosses)
Site-specific optimum predictor sets for Northern Ireland when using the Republic of Ireland grid boxes. Site pie chart segment size reflects the ranked order of explained variance provided by each of the 5 optimum predictors. Source: Crawford et al. (2007) Choice of predictor variable suite
Low skill at heavy summer rainfall Percent difference (discrepancy) between grid cells for UKMO and control simulations for the 1-day 5-year return value during summer. Most of the RCMs underestimate the precipitation extremes. Source: Fowler and Ekstrom (2009)
Extrapolating beyond the calibration data Downscaling daily wind gust (m/s) for Singapore under present (top) and future (lower) climate conditions.
1.GCM boundary conditions are the main source of uncertainty affecting all regional downscaling methods 2.Statistical and dynamical downscaling have similar skill 3.Different downscaling methods yield different scenarios 4.There are no universally optimum predictor(s)/domains 5.Downscaling extreme events is highly problematic (summer rainfall predictability is very low) 6.Skilful downscaling of present climate does not imply skilful downscaling of future scenarios of change Findings from inter-comparison studies
Photo: Richenda Connell Photo: http://www.flickr.comhttp://www.flickr.com When is statistical downscaling problematic? Photo: Bull (1929)
The global network of the World Weather Watch (WWW) stations colour coded to indicate silence (red dot) or reporting rates in 2008. Source: WMO (2009) Data sparse where needed most
Local forcing: Cooling by late season snow cover Observed and downscaled seasonal mean TAVG at Niwot Ridge, Colorado 1982/83 El Nino
Simpler methods may suffice Sensitivity of annual mean total chlorophyll-a concentration (mg m -3 ) to changing water temperature (C) and nutrient load: (a) Changing nitrate and soluble reactive phosphorous (SRP); (b) Changing SRP. Source: Elliott & May (2008)
Simpler methods may suffice 90th percentile daily precipitation (mm/d) in autumn (SON) for OBS (top left), for direct output from the reanalysis (ERA40), for the local intensity scaling (LOCI-E40), and for three regional climate models (CHRM, HADRM, HIRHAM). Results are valid for the period 1979-1993. Source: Schmidli et al. (2006)
Guidance for downscaling in practice UNDP (2006) IPCC (2007)
Public domain downscaling tools SDSMUCT ENSEMBLES
Application: daily precipitation (for ski resorts) Downscaled and observed daily precipitation for a site above 3000 m in the US Rockies
Forecast of June-July- August rainfall anomalies (% normal) based on SSTs in April 2009, downscaled from ECHAM4.5 by RSM Source: FUNCEME http://www.funceme.br/ DEMET/index.htm Application: high resolution seasonal forecasts
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