Kuala Lumpur Malaysia 8 th11 th November 2012
Kuala Lumpur, Malaysia, 8 th-11 th November 2012 Climate Extremes © Crown copyright 2007
Contents • What is ‘Extreme’ and why use indices? • Calculating Extremes using CDO • Cautionary Note: Comparing Extremes in
What is ‘Extreme’? Wide range of space and time scales • From very small scale (precip) to large scale (droughts) Definitions? • High impact events • Unprecedented events (in the available record) • Rare events (long return periods) • Exceedance of a relatively low threshold (indices, such as 10 th percentile of daily temperature or 95 th percentile of daily precipitation amounts) • Persistence of weather conditions (droughts) • Climatic extremes (e. g. extreme seasons)
CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) from ETCCDI: • D e f i n i t i o n
ETCCDI indices Internationally coordinated core set of 28 descriptive indices describe frequency, amplitude, and persistence of moderate extremes
Extremes Indices – temperature based ID Indicator name Definitions UNITS FD 0 Frost days Annual count when TN(daily minimum)<0ºC Days SU 25 Summer days Annual count when TX(daily maximum)>25ºC Days ID 0 Ice days Annual count when TX(daily maximum)<0ºC Days TR 20 Tropical nights Annual count when TN(daily minimum)>20ºC Days Growing season Length Annual (1 st Jan to 31 st Dec in NH, 1 st July to 30 th June in SH) count between first s p a n o f a t l e a s t 6 APPENDIX A: List of ETCCDMI core Climate Indices d a y s
Extremes Indices – precip based ID Indicator name Definitions UNITS RX 1 day Max 1 -day precipitation amount Monthly maximum 1 -day precipitation Mm Rx 5 day Max 5 -day precipitation amount Monthly maximum consecutive 5 -day precipitation Mm Simple daily intensity index Annual total precipitation divided by the number of wet days (defined as SDII P R C P > = 1. 0 m m ) Mm/day i n t h e y e a r Number of heavy precipitation R 10 Annual count of days when PRCP>=10 mm d a y s Days
Alexander et al. , JGR, 2006; also in IPCC, 2007
Example: Calculating TX 90 p (warm days) • Calculate threshold exceeded by the 10% hottest days (Tmax) in baseline period (i. e. 1961 -90) 10% days exceed 23. 2º (av. 36 days per year) 23. 2º 1961 1990 • On average, in the baseline period, 10% of days (36/37 days will exceed this threshold)
Example: Calculating TX 90 p (warm days) • Calculate the average number of times that same threshold is exceeded in a future period 58% days exceed 23. 2º (av. 212 days per year) 23. 2º 2070 2100 (these are synthetic data, not from real projections!)
R 95 PTOT- Total annual rainfall on heavy rain days • Similarly, calculate the 95 th percentile of wet days only (5% wettest ‘wet days’, i. e. days >1 mm) in baseline 12. 7 mm • These are‘ heavy rainfall days’ • Calculate the average amount of rain per year that occurs in ‘heavy’ events.
R 95 PTOT- Total annual rainfall on heavy rain days • Identify the ‘heavy’ rainfall days in the future • Sum the rainfall that falls on those days to give average per year. 12. 7 mm 2070 2100
Calculating Indices with CDO To calculate some of these indices with CDO for whole model fields we can either use CDO defined extremes operators, or our own. For the percentage of warm days: cdo eca_tg 90 p ifile 1 ifile 2 ofile cdo timsum –gt ifile 1 ifile 2 ofile cdo mulc, 100 –divc, [days] ofile. percent Some of the CDO extremes operators are not always robust with PRECIS data, but we can calculate them by using other CDO operators together.
A word of warning on Validating Extremes … from a GCM grid to the point of interest.
Individual station vs. area averages 26 stations in a 25 km× 25 km area (black bars) and their area averages, (red bars). The area average (c. f. model grid box output) is considerably and inconsistently different to most individual stations
Model grid box vs. point observations Average(Extreme) ≠ Extreme(Average) Rules of thumb: Usually model output has reduced range of values and reduced variability, but it depends on the physiography of the grid box Trends should be
Questions Acknowledgements: John Caesar (Met Office), ETCCDI
- Slides: 17