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Analyses of physical factors associated with extreme rainfall over China under global warming Jinzhong Min, Weitao Deng minjz@nuist.edu.cn Nanjing University of Information Science & Technology China

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大气科学学院 大气科学学院 大气科学学院 大气科学学院

Analyses of physical factors associated with extreme rainfall over China under global warming

Jinzhong Min, Weitao Deng

minjz@nuist.edu.cn Nanjing University of Information Science & Technology， ， ， ，China

  • International Conference on Climate Change Science 18-20, Oct, 2011, Beijing, China
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大气科学学院 大气科学学院 大气科学学院 大气科学学院

  • Introduction
  • Index representing storm intensities
  • Relationship analyses
  • Summary and discussion
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Introduction

  • Extreme climate events get more and more attention

– A small change in mean climate or variability might induce larger changes in the frequency and intensity of extreme events – Climate extremes have critical impact on human society, ecosystems and environment

  • Changes in extreme rainfall have different features in each area
  • f China.

– Trend in extreme precipitation events: more intense and frequent in the Mid-lower reaches of Yangtze River. – Trend in extreme rainfall events: less frequent in the Yellow River basin, with little change in intensity. – The change is likely due to global warming

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  • Open circle: decrease
  • closed circles: increase
  • The largest circles stand

for trends greater than 50% in the 50 years.

  • Cross signs: represent

trends with statistical significant under 95% confidence level. Summer Half Year

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Trends in number of storm rain days (50 mm/day)

(From Zhai)

summer half year

  • Open circles: decrease
  • closed circles: increase
  • The largest circles stand

for trends greater than 50% in the 50 years.

  • Cross signs represent

trends with statistical significant under 95% confidence level.

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(From Zhai)

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  • Why: the extreme rainfall events

become more frequently under global warming?

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大气科学学院 大气科学学院 大气科学学院 大气科学学院

  • Introduction
  • Index representing storm intensities
  • Relationship analyses
  • Summary and discussion
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  • By using potential pseudo-equivalent temperature

if I<0, potential instability

850 700 se se se

I θ θ θ − = ∆ =

Atmospheric stability index Thermal enthalpy index

  • By using temperature and moisture mixing ratio

if h is larger, it gets more energy

γ γ γ 2500 ) 88 . 1 01 . 1 ( + + = + = t h t C h

i g

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Wind Vertical shear index

  • Difference between 200hPa and 850hPa horizontal wind

When wind vertical shear becomes large, convection develops more likely.

200 850 200 850 200 850 2 2 200 850 200 850

( ) ( ) ( ) ( ) V V V u u i v v j u u v v ∆ = − = − + − = − + −

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Moisture content index

  • By using specific humidity

Atmosphere column divided into three layers.

  • −

=

z

p p

dp p q g W ) ( 1

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  • Introduction
  • Index representing storm intensities
  • Relationship analyses
  • Summary and discussion
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1964-1973 cool period 1999-2008 warm period Time series of summer average surface temperature in Northern hemisphere 1948-2009 (dot line means 5-year running average)

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Composite ananlysis

warm period minus cool period

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Differences in atmospheric stability index between warm period and cool period (unit:K)

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Differences in thermal enthalpy between warm period and cool period (unit: KJ/Kg)

850hPa 700hPa 500hPa

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Differences in wind vertical shear between warm period and cool period(unit: m/s)

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low layer middle layer high layer

Differences in moisture content between warm period and cool period (unit: kg/m2)

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A B

Mid-lower reaches of Yangtze River North China

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A area: Mid-low reach of Yangtz River Time series of atmospheric stability index (green line means trend, and blue/red line means cool/warm period average) Vertical profiles: Air temperature(unit: K) and specific humidity anomaly (unit: g/m2) (blue/red line means cool/warm period average)

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Change (%) in atmospheric stability index in different cases (+/- means warm/cool period cases)

A area: Mid-low reacher of Yangtz River

  • q

+2× × × × +1× × × × +0.5× × × × CL

  • 0.5×

× × ×

  • 1×

× × ×

  • 2×

× × × T +2× × × × ↓ ↓ ↓ ↓45.2% ↓ ↓ ↓ ↓23.1% +1× × × × ↓ ↓ ↓ ↓22.6% ↓ ↓ ↓ ↓11.5% +0.5× × × × ↓ ↓ ↓ ↓11.2% ↓ ↓ ↓ ↓5.7% CL ↓ ↓ ↓ ↓22.1% ↓ ↓ ↓ ↓11.1% ↓ ↓ ↓ ↓5.5% ↓ ↓ ↓ ↓5.0% ↓ ↓ ↓ ↓9.9% ↓ ↓ ↓ ↓19.7%

  • 0.5×

× × × ↑ ↑ ↑ ↑0.5% ↓ ↓ ↓ ↓4.5%

  • 1×

× × × ↑ ↑ ↑ ↑0.7% ↓ ↓ ↓ ↓9.1%

  • 2×

× × × ↑ ↑ ↑ ↑1.2% ↓ ↓ ↓ ↓18.5%

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Time series of atmospheric stability index (green line means trend, and blue/red line means cool/warm period average) B area：North of China

  • Vertical profiles: Air temperature anomaly (unit:K) and specific humidity anomaly (unit:

g/m2) (blue/red line means cool/warm period average)

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Changes (%) in atmospheric stability index in different cases (+/- means warm/cool period case)

B area：North of China

  • q

+2× × × × +1× × × × +0.5× × × × CL

  • 0.5×

× × ×

  • 1×

× × ×

  • 2×

× × × T +2× × × × 10.8% 20.6% +1× × × × 5.4% 10.3% +0.5× × × × 2.8% 5.1% CL 9.8% 4.9% 2.3% 6.9% 13.9 % 28.0 %

  • 0.5×

× × × 1.8% 5.1%

  • 1×

× × × 3.6% 10.5 %

  • 2×

× × × 7.2% 21.8 %

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trend ananlysis

from 1970 to 2010

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Atmospheric stability index

Trend (unit: K/10yr) Time series (green line means trend)

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Trend (unit: KJ/kg/10yr)

Thermal enthalpy (850 hPa)

Time series (green line means trend)

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Trend (unit: m/s/10yr)

Wind vertical shear

Time series (green line means trend)

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Moisture content (low layer)

Trend (unit: Kg/m2/10yr) Time series (green line means trend)

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Moisture content (middle layer)

Trend (unit: Kg/m2/10yr) Time series (green line means trend)

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Moisture content (high layer)

Trend (unit: Kg/m2/10yr) Time series (green line means trend)

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  • 0.2
  • 0.15
  • 0.1
  • 0.05

0.05 0.1 0.15 suf-700hPa 700-400hPa 400-300hPa

High layer Middle layer Low layer

Air temperature trend Moisture content trend

A area: Mid-low reacher of Yangtz River Low layer：dry warm trend High layer: dry cool trend Low layer：wet warm trend B area：North of China High layer：dry cool trend

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大气科学学院 大气科学学院 大气科学学院 大气科学学院

  • Introduction
  • Index representing storm intensities
  • Relationship analyses
  • Summary and discussion
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  • Summary and discussion
  • Likely due to global warming, atmosphere circulation

changes obviously, leading to changes in intensity and frequency of rainfall over China. – At mid-low reach of Yangtze River, warm and wet trends in low layer, and cool and dry trends in high layer, leading to unstable stratification and large wind vertical shear in the atmosphere. – In North China, warm and dry trends in low layer, and cool and dry trends in high layer, leading to stable stratification and small wind vertical shear.

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  • Summary and discussion

– At mid-low reach of Yangtze River, temperature and moisture effects are similarly important in warm period, but temperature effect is more important than moisture in cool period. – In North China, temperature effect is more important than moisture in warm period, but moisture effect is more important than temperature in cool period. – The wind vertical shear has increased when temperature increases at mid-low reach of Yangtze River.

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  • All these factors can lead to a trend with

strong and frequent rainfall events. That means global warming can be one of factor for extreme precipitation change, but moisture factor can’t be neglected .

Summary and discussion

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B area： ： ： ：North of China Air temperature moisture content thermal enthalpy Wind vertical shear Stability index

－ － － － － － － － ＋ ＋ ＋ ＋

high layer middle layer low layer

－ － － － － － － － － － － －

high: dry cool low: dry warm

— ＋ ＋ ＋ ＋ ↓ ↓ ↓ ↓

A area: Mid-low reacher of Yangtz River

－ － － － － － － － ＋ ＋ ＋ ＋

high layer middle layer low layer

－ － － － － － － － ＋ ＋ ＋ ＋

high: dry cool low: wet warm

  • ＋

＋ ＋ ＋ ＋ ＋ ＋ ＋

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  • Using IPCC AR4 and AR5 model data, we

plan to analyze extreme precipitation events in different models and different scenario, to quantify the relationships with atmosphere background changes.

  • Using regional model, we can simulate

extreme rainfall-related processes, in order to find the physical mechanisms for extreme rainfall events under global warming.

Next step: