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Jan. 12, 2010
项目日期
最高气温（℃）
2009 年 5 月 2009 年 6 月 2009 年 7 月2009 年 8 月 2009 年 9 月
1 25.6 32.1 31.4
2 26.1 26.0 33.2
3 20.9 29.2 32.2
4 23.2 31.0 32.5
5 26.4 30.9 31.2
6 29.0 29.4 34.0
7 30.2 28.9 29.5
8 32.8 28.3 36.1
9 33.8 25.0 37.4
10 32.9 27.2 33.6
11 35.3 31.0 34.5
12 28.7 27.0 35.2
13 26.7 32.0 34.3
14 26.5 30.9 35.1
15 28.6 30.2 35.3
16 31.2 30.3 35.4
17 24.6 31.7 37.6
18 27.5 32.2 35.0
19 29.4 31.4 37.7
20 22.4 37.4 40.0
21 23.0 35.3 38.3
22 28.9 32.5 29.8
23 23.2 31.9 30.1
24 29.5 31.8 29.7
25 25.7 34.6 30.2
26 26.5 30.4 31.4
27 28.7 29.3 28.8
28 29.3 34.9 26.7
29 29.8 29.9 27.4
30 30.6 29.2 26.8
31 31.7
上海市气候中心
2009年高温情况根据上海市徐家汇气象站
观测资料， 2009 年 1 月 1 日至 2009 年 7 月 30 日上海市高温（日最高气温≥ 35.0℃ ）日数共计 14 天，其中 5 月 1 天，6 月 2 天， 7 月 11 天。 2009年 5 月 1 日～ 2009 年 7 月 30
日每日最高气温：
40oC
Jan. 12, 2010
Heavy rains flood Shanghai Thu Jul 30, 1:19 pm ET BEIJING (AFP) – The "heaviest rains in 70 years" lashed Shanghai Thursday, flooding 3,000 homes and leaving nearly 2,000 travellers stranded at the city's airports, state media reported.Between 80 to 140 millimetres (three to 5.5 inches) fell in most areas of China's largest city, official news agency Xinhua reported, adding that vehicles had been damaged by falling branches. No casualties were reported.More than 500 workers were deployed to clear the water, which was up to 30 centimetres deep on city roads, the report said.The weather delayed scores of flights to and from Shanghai's Pudong and Hongqiao airports, Xinhua said, stranding thousands of passengers.Torrential downpours have struck various parts of China during the annual summer rainy season.Earlier this month Xinhua reported that the heavy rains had displaced more than 100,000 people in Sichuan province in the southwest.
AFP/File – A man rides a bicycle through a flooded street after a heavy storm in Shanghai. The "heaviest rains …
The "heaviest rains in 70 years" lashed Shanghai, China Thursday, July 30, 2009
Jan. 12, 2010
Rainfall and Ocean Surface Wind Speed in the Nested Regional Climate Model
Hsiao-ming Hsu
National Center for Atmospheric Research/NCAR Earth System Laboratory
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Global climate Regional climate
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Downscaling
Global climate Regional climate
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Downscaling
• Stochastic downscaling• Dynamic downscaling
Global climate Regional climate
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Downscaling
• Stochastic downscaling• Dynamic downscaling
Numerical modeling
Global climate Regional climate
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Nested Regional Climate Model (NRCM)
Advanced Research WRF (ARW)
Tropical Channel (Δ = 36 km)
(30oS ~ 45oN)/ 36 vertical levels (50 mb)(1996 – 2000)
(45oS ~ 45oN)/ 51 vertical levels (10 mb)(2000 – 2005)
Δ = 36 km/ 12 km/ 4 km(Jan – Jun, 1997)
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Model Evaluations•Rainfall
•Ocean surface wind speeds
Nested Regional Climate Model (NRCM)Advanced Research WRF (ARW)
Observations (Satellites)•TRMM + IR •QuickSCAT
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Model Evaluations•Rainfall
•Ocean surface wind speeds
Nested Regional Climate Model (NRCM)Advanced Research WRF (ARW)
Observations (Satellites)•TRMM + IR •QuickSCAT
Statistical Regularity
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Model Evaluations•Rainfall
•Ocean surface wind speeds
Nested Regional Climate Model (NRCM)Advanced Research WRF (ARW)
Observations (Satellites)•TRMM + IR •QuickSCAT
Statistical RegularityPDF and spectra
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NRCMΔ = 36 km/ 12 km/ 4 km
(Jan – Jun, 1997)
Hourly rainfall
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D02 (Δ=12 km)D03 (Δ=4 km) D01 (Δ=36 km)
NRCMΔ = 36 km/ 12 km/ 4 km
(Jan – Jun, 1997)
Hourly rainfall
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D01
Figure 3-2
D02 D03
Aerial variances
Aerial averages
Time series
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Figure 3-4
Temporal spectraD01 D02 D03
Continuous wavelet transform(Morlet wavelets) Dual exponents: -4/3 and -3~-4
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D02 (Δ=12 km)D03 (Δ=4 km) D01 (Δ=36 km)
NRCMΔ = 36 km/ 12 km/ 4 km
(Jan – Jun, 1997)
Hourly rainfall
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Figure 3-3
D01 D02 D03PDF
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Figure 3-5
Spatial spectraD01 D02 D03
2D Fast Fourier transform&
Azimuthal averaging
Dual exponents: -1/3~-1 and -3
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Figure 3-5
#10 400 km#74 54 km
D01 D02 D03
#10 900 km #23 400 km
#15 400 km#111 54 km
Spatial spectra
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Figure 3-6
D01 D02 D03
Temporal spectra
Continuous wavelet transform(Morlet wavelets) Dual exponents: -4/3 and -4
-4/3 and …..
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Figure 3-7
D01 D02 D03
Exponents of temporal spectra
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Summary:
• Power-law scaling in both space and time
• Dual exponents
• Tightly coupled in space and time
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EastWest
D01 D02 D03
GSFC 3B41Mar. 2002
ToFeb. 2004
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Figure 4-1
Time seriesAerial averages
Aerial variances
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Temporal spectra
Jan. 12, 2010Figure 4-3
Temporal spectra
D01 D02 D03
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EastWest
D01 D02 D03
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West East
-1/3
-9
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West EastTRMM
Figure 4-2
ARW-9
-1/3
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EastWest
Dual exponents: -1/3 and -5/32D Fast Fourier transform
&Azimuthal averaging
Spatial spectra
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EastWest
Figure 4-4
#06 900 km #16 400 km #100 54 km
Spatial spectra
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Figure 4-5
Temporal spectra
Dual exponents: -4/3 and …..
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ARW
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EastWest
Figure 4-6
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Summary:
• Power-law scaling in both space and time
• Dual exponents
• Tightly coupled system in space and time
• Tropical rainfall/convection:
REAL multiscale phenomenon
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Ocean Surface Wind Speeds
Using ARW to Downscale NCEP Winds for Driving Ocean Circulation
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Nested Regional Climate Model (NRCM)
Advanced Research WRF (ARW)
Tropical Channel
(30oS ~ 45oN)/ 36 vertical levels (50 mb)(1996 ~ 2000)
(45oS ~ 45oN)/ 51 vertical levels (10 mb)(2000 ~ 2005)
36 km/ 12 km/ 4 km
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Ocean Surface Wind Speed Analysis
QSCAT (0.5o ; ~ 60 km)NRCM ( grid; 36 km) CAM3 (T170; ~70 km)NCEP (T62; ~ 200 km)
Data: Year 2000 (twice daily)
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MEANQSC
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SDQSC
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SKEWQSC
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KURTQSC
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(a) ME All MC NP SP NEP NA EA SA SI
QSC 7.165 6.349 7.400 6.982 5.947 7.495 6.299 7.351 7.650
NRCM 6.745 6.008 6.986 6.575 5.644 7.017 5.423 6.717 7.298
% -5.86 -5.37 -5.60 -5.83 -5.09 -6.38 -13.91 -8.63 -4.60
CAM 6.738 5.536 6.942 6.659 5.335 7.076 5.496 7.113 7.332
% -5.96 -12.81 -6.19 -4.63 -10.29 -5.59 -12.75 -3.24 -4.16
NCEP 6.358 5.279 6.425 6.111 4.693 6.953 5.638 6.973 6.927
% -11.26 -16.85 -13.18 -12.48 -21.09 -7.23 -10.49 -5.14 -9.45
(b) SD All MC NP SP NEP NA EA SA SI
QSC 1.690 1.686 1.729 1.644 1.569 1.706 1.439 1.668 1.726
NRCM 1.644 1.604 1.673 1.611 1.545 1.610 1.404 1.614 1.719
% -2.72 -4.86 -3.24 -2.01 -1.53 -5.63 -2.43 -3.24 -0.41
CAM 1.677 1.625 1.734 1.664 1.543 1.657 1.433 1.691 1.678
% -0.77 -3.62 0.29 1.22 -1.66 -2.87 -0.42 1.38 -2.78
NCEP 1.556 1.464 1.590 1.510 1.401 1.592 1.246 1.573 1.611
% -7.93 -13.17 -8.04 -8.15 -10.71 -6.68 -13.41 -5.70 -6.66
Table 1, Channel and regional averages of the statistical measures, i.e., mean (a, ME) and standard deviation (b, SD) of ocean surface wind speeds. Channel is defined between 40oS and 40oN. Regions are Maritime Continent (MC), North Pacific (NP), South Pacific (SP), North-East Pacific (NEP), North Atlantic (NA), Equatorial Atlantic (EA), South Atlantic (SA), and South Indian (SI). Actual values are in black. Percent differences of measures of NRCM, CAM, or NCEP with respect to QSC’s are in grey.
Mean
Standard deviation
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(c) SK All MC NP SP NEP NA EA SA SI
QSC 0.405 0.725 0.399 0.344 0.596 0.337 0.595 0.294 0.313
NRCM 0.314 0.404 0.373 0.289 0.632 0.212 -0.131 0.173 0.369
% -22.5 -44.3 -6.5 -16. 6.04 -37.1 -122 -41.2 -17.9
CAM 0.149 0.242 0.191 0.183 0.044 0.089 -0.161 0.140 0.020
% -63.2 -66.6 -52.1 -46.8 -92.6 -73.6 -127 -52.4 -93.6
NCEP 0.064 0.075 0.073 0.062 0.103 0.021 -0.268 0.072 -0.013
% -84.2 -89.7 -81.7 -82. -82.7 -93.8 -145 -75.5 -104
(d) KU All MC NP SP NEP NA EA SA SI
QSC 1.034 1.927 0.935 0.877 2.449 0.93 3.744 0.328 0.700
NRCM 0.663 0.678 0.790 0.506 2.897 0.86 -0.40 -0.02 0.884
% -35.9 -64.8 -15.5 -42.3 18.3 -7.74 -110 -106 26.3
CAM -0.127 -0.40 -0.05 -0.09 -0.44 0.25 -0.40 -0.07 -0.318
% -112 -121 -106 -110 -118 -72.7 -111 -122 -145
NCEP -0.129 -0.34 -0.09 -0.11 -0.31 0.17 -0.08 0.120 -0.275
% -113 -118 -109 -113 -112 -81.6 -102 -63.4 -139
Table 1, Channel and regional averages of the statistical measures, i.e., skewness (c, SK), and kurtosis (d, KU) of ocean surface wind speeds. Channel is defined between 40oS and 40oN. Regions are Maritime Continent (MC), North Pacific (NP), South Pacific (SP), North-East Pacific (NEP), North Atlantic (NA), Equatorial Atlantic (EA), South Atlantic (SA), and South Indian (SI). Actual values are in black. Percent differences of measures of NRCM, CAM, or NCEP with respect to QSC’s are in grey.
Skewness
Kurtosis
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I II III
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Quasi-linear
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Quadratic
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Quadratic
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For the comparisons of ocean surface wind speeds, nice statistical similarities between QSC and NRCM, but
be CAREFUL!
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KURT
Jan. 12, 2010
Tropical Rain-Rate Spectral Structures, Modeled and Observed
H. Hsu, J.J. Tribbia and M.W. MoncrieffNCAR
A Comparison of Ocean Surface Winds between Observation and Simulations
H. Hsu, W. Large and J. TribbiaNCAR
