Climate ExtremesPRECIS Workshop

Tanzania Meteorological Agency, 29th June – 3rd July 2015

Contents

• What is ‘extreme’? • How can we calculate extremes?• Observed changes in climate

extremes• Projections of extremes from IPCC• Caution: validating extremes• Why do extremes matter?

• The term ‘extreme’ can be used to describe phenomena on a wide range of space and time scales– i.e. heavy rainfall events (small scale) to

widespread drought (large scale)

• An ‘extreme’ event can be associated with:– High impact events– Unprecedented events (in the available

record)– Rare events (long return periods)– Exceedance of a threshold or percentile level

in daily temperature or precipitation– Persistence of weather conditions– Climatic extremes (e.g. extreme seasons)

What is ‘extreme’?

What is ‘extreme’?

• Internationally coordinated core set of 28 descriptive indices describe frequency, amplitude, and persistence of moderate extremes

http://etccdi.pacificclimate.org/

Expert Team on Climate Change Detection and

Indices (ETCCDI)

How can we calculate ‘extremes’?

Indices – temperature based

APPENDIX A: List of ETCCDMI core Climate Indices

IDIndicator name

Definitions UNITS

FD0 Frost days Annual count when TN(daily minimum)<0ºC Days

SU25 Summer days Annual count when TX(daily maximum)>25ºC Days

ID0 Ice days Annual count when TX(daily maximum)<0ºC Days

TR20 Tropical nights Annual count when TN(daily minimum)>20ºC Days

GSL

Growing season Length

Annual (1st Jan to 31st Dec in NH, 1st July to 30th June in SH) count between first span of at least 6 days with TG>5ºC and first span after July 1 (January 1 in SH) of 6 days with TG<5ºC

Days

TXx Max Tmax Monthly maximum value of daily maximum temp ºC

TNx Max Tmin Monthly maximum value of daily minimum temp ºC

TXn Min Tmax Monthly minimum value of daily maximum temp ºC

TNn Min Tmin Monthly minimum value of daily minimum temp ºC

TN10p Cool nights Percentage of days when TN<10th percentile Days

TX10p Cool days Percentage of days when TX<10th percentile Days

TN90p Warm nights Percentage of days when TN>90th percentile Days

TX90p Warm days Percentage of days when TX>90th percentile Days

WSDIWarm spell duration

indicatorAnnual count of days with at least 6 consecutive days when

TX>90th percentile Days

CSDICold spell duration

indicatorAnnual count of days with at least 6 consecutive days when

TN<10th percentile Days

DTRDiurnal temperature

range Monthly mean difference between TX and TN ºC

Indices – precipitation basedID Indicator name Definitions UNITS

RX1dayMax 1-day precipitation

amount Monthly maximum 1-day precipitation Mm

Rx5dayMax 5-day precipitation

amount Monthly maximum consecutive 5-day precipitation Mm

SDIISimple daily intensity

indexAnnual total precipitation divided by the number of wet

days (defined as PRCP>=1.0mm) in the year Mm/day

R10Number of heavy

precipitation days Annual count of days when PRCP>=10mm Days

R20Number of very heavy

precipitation days Annual count of days when PRCP>=20mm Days

RnnNumber of days above

nn mmAnnual count of days when PRCP>=nn mm, nn is user

defined threshold Days

CDD Consecutive dry days Maximum number of consecutive days with RR<1mm Days

CWD Consecutive wet days Maximum number of consecutive days with RR>=1mm Days

R95p Very wet days Annual total PRCP when RR>95th percentile Mm

R99p Extremely wet days Annual total PRCP when RR>99th percentile mm

PRCPTOTAnnual total wet-day

precipitation Annual total PRCP in wet days (RR>=1mm) mm

Example: Calculating TX90p (warm days)

• Calculate threshold exceeded by the 10% hottest days (Tmax) in the present-day or ‘baseline’ period (i.e. 1961-90)

• On average, in the baseline period, 10% of days (approx. 36) will exceed this threshold

10% days exceed 23.2º (~ 36 days)

23.2º

1961 1990

• Calculate the average number of times that same threshold is exceeded in a future period

• In this future period, 58% of days (212 days) now exceed this threshold!

23.2º

2070 2100

58% days exceed 23.2º (av. 212 day)

(NOTE: these are synthetic data, not from real projections!)

Example: Calculating TX90p (warm days)

R95PTOT- Total annual rainfall on heavy rain days

• Similarly for rainfall, we can define the number of ‘wet days’ (i.e. Days >1mm), and calculate the 95th percentile of wet days (i.e. the 5% wettest ‘wet days’) in the baseline period

• These are‘ heavy rainfall days’• We can use this information to calculate the average amount of rainfall per

year that occurs in ‘heavy’ events.

12.7mm

1961 1990

• Using the same threshold as before, we can now identify the ‘heavy’ rainfall days in the future

• This again allows us to calculate the average amount of ‘heavy’ rainfall per year in the future period, which in the example below will be a higher amount than what we found for the present day

2070 2100

12.7mm

R95PTOT- Total annual rainfall on heavy rain days

Observed Changes in Climate Extremes

IPCC AR4 WG1, adapted from Alexander et al. (2006)

Projections of Climate Extremes (from IPCC AR5)

Added value from using RCMs

• Using GCMs alone to assess changes in extremes will often miss the influence of regional dynamics

• By running RCMs, we’re able to better detect the influence of complex topography and regional characteristics on extremes

Fig 5. from Frei et al., 2006

Caution: Validating Extremes

• Best compromise is to use gridded datasets (e.g. CRU/APHRODITE) to validate model output

• However also be aware of limitations of gridded data sets (e.g. density of station network)

• Reanalysis products are another useful option for validation, but can contain well-known biases which are generally a product of the reanalysis model

• Temperature reanalyses are typically more reliable than precipitation fields

APHRODITE station network

Caution: Validating Extremes

Why do ‘extremes’ matter?

Thank you!

Q&A

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Model Validation