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Extreme precipitation - PowerPoint Presentation

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Extreme precipitation - PPT Presentation

Ethan Coffel SREX Ch 3 Lowmedium confidence in heavy precip changes in most regions due to conflicting observations or lack of data Medium confidence in Europe winter precip has increase in some areas but summer ID: 590251

precip heavy events increase heavy precip increase events precipitation extreme annual models station confidence total frequency comparison averaged amp

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Slide1

Extreme precipitation

Ethan CoffelSlide2

SREX Ch. 3

Low/medium confidence in heavy

precip

changes in most regions due to conflicting observations or lack of data

Medium confidence in Europe: winter

precip

has increase in some areas, but summer

precip

shows little trend

Low-medium confidence in heavy

precip

trends in Asia

Low-medium confidence in Africa

Likely decrease in heavy

precip

in southern Australia

Most confidence in North America: likely increase in heavy

precip

eventsSlide3

SREX Ch. 3

AR4: Very likely that heavy

precip

events will increase across the globe

Newer work presents a similar assessment, but highlights more uncertaintySlide4

Slide5
Slide6
Slide7

Groisman 2004

To obtain statistically significant estimates, the

characteristics of

heavy precipitation should be

areally

averaged

over a

spatially homogeneous

region.

Otherwise, noise

at

the spatial

scale of daily weather

systems masks changes

and makes them very difficult

to detect

(e.g.,

Frei

and

Schär

2001; Zhang et

al. 2004).

Whenever there are statistically significant

regional changes

in the rainy season, relative changes in

heavy precipitation

are of the same sign and are

stronger than

those of the mean. A search at various

sites around

the globe using our data holdings and

results from

others (e.g., Osborn et al. 2000;

Tarhule

and Woo

1998;

Suppiah

and Hennessy 1998;

Zhai

et

al. 1999

;

Groisman

et al. 2001) confirm this

.

This search also revealed several regions where

mean precipitation

does not noticeably change in the

rainy season

but heavy precipitation does change. In

such cases

, there was always an increase in heavy

precipitation. Among

these regions are Siberia, South

Africa, northern

Japan (

Easterling

et al. 2000c),

and eastern

Mediterranean (Alpert et al. 2002).Slide8

Groisman 2004

Heavy (>= 95

th

percentile), very heavy (>= 99

th

percentile), and extreme (>= 99.9

th

percentile) precipitation has increased, as has the contribution of these events to the annual total precipitation

Number of days with heavy and very heavy

precip

has also increasedSlide9

Area averaging

Weather stations are clustered spatially and most have missing values

“For each region, season, year, and intense precipitation threshold, we calculated anomalies from the long-term mean number of exceedances for each station and arithmetically averaged these anomalies within 1x1 degree grid cells. These anomalies were regionally averaged with weights proportional to their area.”Slide10

Area averaging

Estimated spatial correlation function (2)

Constant C

0

includes local climate variability and measurement error

Results are that for non-mountain terrain error is at least 25% with one station per

gridbox

, and 60% in mountainous terrainSlide11

Data problems

Use # of exceedances of a certain threshold instead of actual station measurements to avoid missing extreme events that may happen near but not on top of the station

Ex. mountain terrain with a station at low elevation: the station’s extreme threshold could be lower than the threshold on top of the mountain, but by using frequency of exceedance, extreme events on the mountain can be capturedSlide12

Results

Analysis of heavy

precip

for:

European USSR

Northern Europe

Pacific Northwest / Alaska

SE/SW Australia

South Africa

Eastern Brazil & Uruguay

Central US

Central MexicoSlide13

Former USSR

Observed increase in total annual

precip

and increase in heavy & very heavy eventsSlide14

Former USSRSlide15

Northern Europe

Increase in annual, & heavy/very heavy

precipSlide16

US Northwest / Alaska

Increase in annual & heavy/very heavy

precipSlide17

Australia

Increased

precip

in SE Australia, decrease in SWSlide18

South Africa

Total

precip

unchanged, but increase in frequency of heavy/very heavy eventsSlide19

Eastern Brazil and Uruguay

Increase in frequency of extreme

precip

in all regions and increase in general

precip

in the southSlide20

Central US

Increase in very heavy

precip

, almost all after 1970Slide21

Central Mexico

Decrease in total

precip

and heavy events, but increase in very heavy eventsSlide22

SummarySlide23

Comparison with models

Changes in annual

precip

and 99.7

th

percentile exceedance in two models with a doubling of CO

2

Models capture the larger increase in extreme

precip

as compared to the annual total, but not great spatial agreement Slide24

Comparison with models

Data shown where models agree in sign at

gridpoint

level (averaged between the two)Slide25

Comparison with models

Frequency of upper 10%

precip

days in NE US (top: observations, bottom: ECHAM4 model)Slide26

Comparison with models

Frequency of days with

precip

in NE US (top: observations, bottom: ECHAM4 model)