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: 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 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 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 DEMET/index.htm Application: high resolution seasonal forecasts

West-wide seasonal hydrologic forecast system. Source: ecast/westwide/sflow/index.cpc.6mon s.shtml#seas_vol ecast/westwide/sflow/index.cpc.6mon s.shtml#seas_vol Application: seasonal streamflow forecasts

Application: intensity of Londons urban heat island Statistically downscaled nocturnal temperature gradient between central and outer London for the present and 2050s. Source: Wilby (2008)

Utility of downscaling when there is no consensus amongst GCMs? Source: IPCC AR4 (2007)

Utility of higher resolution with uncertainty? Changes in wettest day in summer by 2050s. Source: UKCP s A1FI 90 th percentile 2050s B1 10 th percentile

Number of ISBN research publications listed on the Web of Science. [Accessed May 2009] To what extent is downscaling science really entering adaptation practice?