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
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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
Slide5Slide6Slide7
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)