Droughts, Floods, and Global
Warming
Shaw Chen Liu
Research Center for Environmental Change
Academia Sinica
Symposium and Review Panel Meeting
Seoul, Korea
Aug. 4-6, 2013
Acknowledgment
A significant part of this talk is based on:
Liu, S. C., C. Fu, C-J Shiu, J-P Chen, and F. Wu, GRL,
2009.
Shiu, C-J, S. C. Liu & J-P Chen, Journal of Climate, 2009.
Shiu, C. J., S. C. Liu, C. Fu, A. Dai, and Y. Sun, GRL,
2012.
Also recent collaborative work with
Prof. Yuanhang Zhang, Jun Li and Run Liu (Peking Univ.)
Appreciate the help with data analysis:
Ms. You-Yu Mao and Mr. Chih-Wei Wan
• Increases in very heavy precipitation, and often
with decreases in light precipitation have been
reported in recent years over most land areas (e.g.
Karl & Knight, 1998; Manton et al., 2001; Klein
Tank and Können, 2003; Fujibe et al., 2005;
Goswami et al. 2006; Liu et al. 2009) as well as
the tropical oceans (Lau and Wu, 2007).
• Increases in heavy precipitation can lead to more
and worse floods and mudslides.
• Light and moderate precipitation is a critical
source of soil moisture and ground water, its
reduction increases the risk of droughts.
Linear trends of precipitations ( in mm/4 hours) at different intensities
in Japan, (a) for 3 time periods, (b) for 4 seasons, (c) for 3 regions,
and (d) for 3 urban population ranges. (Fujibe et al., 2005)
Changes (%) in precipitation intensity (10 blue bins) and consecutive
dry days in Taiwan for each degree warming in global temperature
(Based on Liu et al. GRL2009)
200
200
10 bin rain
dry days > 14 days
dry days 8~14 days
total dry days
100
100
50
50
0
0
T (% / K)
150
P/
times(days) /
T (% / K)
150
-50
-50
-100
-100
-2
-1
0
1
2
3
4
5
6
7
8
9
10
Categories
method2
Changes in global precipitation intensity from climate models and observations
for one degree warming in global temperature
(Liu et al. GRL2009)
10
GPCP data (observation)
Sun et al. (2007) (model)
80
8
60
6
40
4
20
2
0
0
-20
-2
-40
-4
1
2
3
4
5
6
7
Intensity categories
8
9
10
Normalized P / T (%/K)
Normalized P/T (%/K)
100
• Two mechanisms, global warming and
effects of anthropogenic aerosols, have
been proposed as possible causes of the
increases of heavy precipitation and
decreases of light precipitation.
• Which is the primary cause?
Dynamically how should the precipitation
intensity change in a warming globe?
• Trenberth et al. (2003) hypothesized that heavy
precipitation of large storms should increase at
about the same rate as atmospheric moisture, i.e.
about 7 %/K according to the Clausius-Clapeyron
equation.
• The increase of heavy precipitation could even
exceed the moisture increase because additional
latent heat released from the increased water vapor
could invigorate the storms.
• In turn, the invigorated storms can increase the
stability of the atmosphere, thereby suppressing
light and moderate precipitation.
From IPCC 2007
Total column water vapor
has increased over the
global oceans by about
1.2% per decade from
1988 to 2004, consistent
with the assumption of
near-constant RH.
Column water vapor is
from the SSM/I: Special
Sensor Microwave/Imager
Indirect Effects of Aerosols
The aerosol indirect effect is the change in cloud properties caused by a change in
the Cloud Condensation Nuclei (CCN) (Twomey, 1977).
There are two kinds of indirect effects:
• Albedo, surface area increase (First indirect effect)
• Cloud lifetime increase (Second indirect effect)
less
polluted
activation
more
polluted
activation
Possible impacts on precipitation:
• Delay and/or suppression of precipitation by aerosols (Twomey et al. 1984; Albrecht,
1989; Rosenfeld and Lensky, 1998).
Numerous recent works on aerosol effects on
precipitation, especially in the Amazon
• Aerosols invigorate large convections by
suppressing onset of precipitation, pulling in more
moisture, releasing more latent heat, pushing
moisture to higher altitude and forming more ice
clouds (Andreae et al., 2004)
• For small, low clouds the action stops at
suppressing onset of precipitation and burning off
the clouds (Koren et al., 2008). An overall net
effect is to increase the precipitation intensity.
• We examine data from urban and
rural stations in China and Taiwan, as
well as global data (GPCP) to show
that global warming rather than
aerosol effects is the primary cause of
the increases of heavy precipitation
and decreases of light precipitation.
AOD around Taiwan from MODIS
(Li et al., 2004)
Taiwan: West (polluted) compared to East (clean)
Changes of bottom 10% light precipitation in summer
CWB Jun-Aug Precipitation
5 years running average
bottom 10%
140
y=-0.967x+2005.453
west
y=-1.194x+2444.224
east & island
Precipitation (mm)
120
100
80
60
40
1960
1970
1980
1990
Year
2000
2010
Taiwan: West (polluted) compared to East (clean)
Changes of top 10% heavy precipitation in summer
CWB Jun-Aug Precipitation
5 years running average
top 10%
180
160
Precipitation (mm)
140
y=1.551x-2997.720
west
y=2.056x-4010.633
east & island
120
100
80
60
40
20
1960
1970
1980
1990
Year
2000
2010
Geographical distribution of 109 surface meteorological stations in
Mainland China with average annual precipitation over 500 mm, gray
dots :40 urban stations, green dots: 69 rural stations
1955
125
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
1980
1985
1990
1995
2000
2005
2010
(a)
Bottom 10% Precipitation (mm)
120
115
110
105
100
95
urban
rural
y = -0.23x + 564.21
y = -0.21x + 519.4
90
85
200
(b)
Top 10% Precipitation (mm)
180
160
140
120
100
80
urban
rural
y = 0.3413x - 568.69
y = 0.3615x - 613.92
60
40
1955
1960
1965
1970
1975
Year
Amounts of annual bottom 10% light precipitation (penal a)
and top 10% heavy precipitation (penal b), colored shades
denote 1-standard deviations.
Changes (%) in precipitation intensities in southeastern China (blue),
land area in 20N-45N (green), and 10S-10N oceanic area (yellow) for
each degree warming of the temperature in the 30S-30N zone
250
study region
GPCP 20N-45N land area
GPCP 10S-10N oceanic area
200
P/℃ ）
150
100
50
0
-50
-100
1
2
3
4
5
6
7
Intensity Category
8
9
10
A brief conclusion
• The large increases in precipitation
intensity, including the increases of
heavy precipitation and decreases of
light precipitation, are most likely
driven by global warming rather than
aerosols.
• Explore a causal link among global
warming, changes in precipitation
extremes, and higher risk of floods
and droughts.
Days
Changes of dry days and light rain days in Taiwan
260
260
240
240
220
220
200
200
180
180
160
160
140
140
120
120
100
100
80
1960
80
1970
1980
1990
2000
Year
no-rain days
y=0.43x-635.54 p-test=0.00076
light-rain days
y=-0.54x+1199.11 p-test=0.000013
Total changes from 1961 to 2011
Light-rain days: -27 days (141 days in 1960)
Heavy-rain days: +5.5 days (13.5 days in 1960)
Dry days: +21.5 days (207 days in 1960)
2010
Changes (%) in precipitation intensity (10 blue bins) and consecutive
dry days in Taiwan for each degree warming in global temperature
(Based on Liu et al. GRL2009)
200
200
10 bin rain
dry days > 14 days
dry days 8~14 days
total dry days
100
100
50
50
0
0
T (% / K)
150
P/
times(days) /
T (% / K)
150
-50
-50
-100
-100
-2
-1
0
1
2
3
4
5
6
7
8
9
10
Categories
method2
95
260
A
240
80
75
230
70
bottom 10% precipitation (left)
y = -0.2256x + 551.42 (n=57, p=0.0000)
no precipitation days (right)
y = 0.5183x - 794.46 (n=57, p=0.0000)
60
750
B
frequency of >=10 consecutive no-rain days
y = 3.0887x - 5555.6 (n=57, p=0.0000)
PDSI <=-3
y = 8.3651x - 16333 (n=56, p=0.0000)
Frequency
700
210
700
600
650
500
600
400
550
300
500
200
450
100
400
1.8
0
.12
C
top
y =
top
y =
1.6
1.4
Precipitation Days
220
Number of Grids
65
No-precipitation Day
250
85
10% precipitation (left)
0.004x - 6.7715 (n=57, p=0.0022)
1% precipitation (right)
0.0004x - 0.7474 (n=57, p=0.0183)
.10
1.2
.08
1.0
.06
.8
.6
.04
.4
.02
.2
0.0
1955
0.00
1960
1965
1970
1975
1980
1985
Year
1990
1995
2000
2005
2010
Precipitation Days
Bottom 10% Precipitation (mm)
90
Changes in global precipitation intensity from climate models and observations
(mostly from satellites) for one degree warming in global temperature
(Liu et al. GRL2009)
10
GPCP data (observation)
Sun et al. (2007) (model)
80
8
60
6
40
4
20
2
0
0
-20
-2
-40
-4
1
2
3
4
5
6
7
Intensity categories
8
9
10
Normalized P / T (%/K)
Normalized P/T (%/K)
100
Conclusions
• Evidence supports a causal link starting with global warming,
to increase in precipitation intensity, to changes in precipitation
extremes, and to the increased risk of floods and droughts.
• In southeastern China there have been a severe increase of
about 75% in annual days with top 1% heavy precipitation, an
increase of 35% in the annual occurrence of 10 or more
consecutive days without precipitation, and an astonishing
increase of about 20 times in the annual occurrence of PDSI
(Palmer Drought Severity Index) <= -3 during the period 19552011.
• Greater changes are found at lower latitudes for heavy
precipitation, e.g. about 100% increase in the top 10% heavy
precipitation in Taiwan in the last 50 years (200% increase in
the top 1% heavy precipitation).
Thank you for your attention!
1400
correlation coefficient between urban and rural precipitation is 0.828
1300
Precipitation (mm)
1200
1100
1000
900
800
urban
rural
y = -0.0182x + 1130
y = -0.3254x + 1688.2
700
600
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Year
Annual total precipitation in China averaged over
40 urban stations (red) and 69 rural stations (blue),
Colored shades denote 1-standard deviations.