Characteristics of High-Resolution Characteristics of High-Resolution Satellite Precipitation Products Satellite Precipitation Products
in Spring and Summer over Chinain Spring and Summer over ChinaYan Shen1, A.-Y. Xiong1
Pingping Xie2
1. National Meteorological Information Center (NMIC), China Meteorological Administration (CMA), Beijing,100081
2. NOAA Climate Prediction Center, Camp Springs, MD, 20746
Oct. 15,2008,
At the 4th Workshop of the International Precipitation Working Group (IPWG)
ObjectivesObjectives
• To generate gauge-based analysis of HOURLY
precipitation with the daily optimal interpolation(OI)
algorithm using station data over China
• To examine the performance of six hi- resolution
satellite-based products in depicting hourly
precipitation
• To introduce the daily precipitation analysis
operational system in NMIC
The Gauge-Based AnalysisThe Gauge-Based Analysis
The Gauge AnalysisThe Gauge Analysis
Hourly gauge data from ~2400 stations
Hourly precipitation analysis on a 0.25o over the China
Currently hourly analyses constructed for 3-year period from 2005 to 2
007
Interpolated through the optimal interpolation (OI) algorithm develope
d by Xie et al. (2006)
A two-step approach: First to interpolate the ratio of total
hourly rain to daily climatology through the OI and then to
define the total by multiplying the ratio with daily climatol
ogy
Correction for the orographic effects through employment
of the PRISM climatology
Sample hourly analysisSample hourly analysis for 11Z,June20,2005
This analysis includes the precipitation rate and gauge number distribution information
According to the gauge density information, user can determine whether or not they use it over a place
Validating Six Hi-Resolution Validating Six Hi-Resolution Satellite Estimates Using the Satellite Estimates Using the
Gauge AnalysisGauge Analysis
Verified Satellite Precipitation ProductsVerified Satellite Precipitation Products
• COMB
• CMORPH
• PERSIANN
• NRL-Blended
• TRMM 3B42RT
• TRMM 3B42 / MPA
• Comparison Period: 3 years from 2005 to 2007; only include Spring (AMJ) and Summer (JAS)
• Temporal / Spatial Resolution: 3-hourly / 0.25o×0.25o
Seasonal Mean Precipitation in Spring Seasonal Mean Precipitation in Spring ((Apr.-Jun.Apr.-Jun.))
All satellite estimates can capture the overall structures of precipitation
Satellite estimates tend to generate smoother distribution patterns with regional biases compared to hourly gauge analysis
Satellite estimates adjusted by gauge data (TRMM/3B42) and CMORPH product present the closest to the gauge analysis
The PERSIANN exhibits large over-estimates of precipitation over Tibetan Plateau
NRL, COMB and TRMM/3B42RT have an over-estimation precipitation near the southeast Tibetan plateau
Seasonal Mean Precipitation in Summer Seasonal Mean Precipitation in Summer ((Jul.-Sep.Jul.-Sep.))
All satellite estimates can capture the overall structures of precipitation
Satellite estimates adjusted by gauge data (TRMM/3B42) presents the closest to the gauge analysis
The PERSIANN exhibits large over-estimates of precipitation over Tibetan Plateau
NRL and TRMM/3B42RT have an over-estimation precipitation near the southeast Tibetan plateau
Serial Correlation Serial Correlation ((3-hourly3-hourly for for SpringSpring))
Correlation between every satellite products and gauge analysis has similar pattern with high over eastern China but relatively poor over western arid China;
CMORPH has the highest correlation with the gauge analysis,
especially in the eastern China
Serial Correlation Serial Correlation ((3-hourly3-hourly for for SummerSummer))
The same distribution characteristics as the spring ones with high over eastern China but relatively poor over western arid China;
CMORPH has the highest correlation with the gauge analysis,especialy in the eastern China
Serial Bias Serial Bias ((3-hourly3-hourly for for SpringSpring))
Every satellite products have bias in different regions over China with negative bias over eastern wet regions and relatively positive
bias over western arid area;
Gauge-adjusted TRMM/3B42 has the smallest bias with the gauge analysis over the China region
mm/day
Serial Bias Serial Bias ((3-hourly3-hourly for for SummerSummer))
With negative bias over eastern wet
regions and Tibetan Plateau for all the products except the
PERSIANN data. PERSIANN has an overestimation
trend;
Gauge-adjusted TRMM/3B42 has the smallest bias with the gauge analysis over the China region mm/day
Time Series of Bias and Pattern CorrelationTime Series of Bias and Pattern Correlation
Correlation improves with the seasonal advance and reaches to a stable level from the April and worsens from the October;
CMORPH presents best performance consistently throughout the period;
Bias exists and changes over time
Bias and Correlation Coefficients between gauge Bias and Correlation Coefficients between gauge observation and satellite estimatesobservation and satellite estimates
in different seasonsin different seasons
Satellite Products
All months Spring Summer
Bias(%)
Corr Bias(%) Corr Bias(%) Corr
CMORPH
-21.23
0.604 -10.75 0.642 -16.01 0.597
PERSIANN
-26.22
0.416 -10.46 0.458 -28.09 0.408
COMB -21.89 0.536 -11.47 0.566 -16.49 0.536
NRL -16.29 0.445 -6.50 0.473 -16.73 0.446
3B42 -0.51 0.527 0.52 0.549 2.25 0.542
3B42RT -15.14 0.502 -5.14 0.523 -11.59 0.509
PDF of PDF of [3-Hourly][3-Hourly] Precipitation Precipitation• Frequency of No-Rain Events
• Gauge Analysis: 82.9%
• CMORPH: 79.6% PERSIANN: 85.5%
• COMB: 88.7% NRL: 83.6%
• 3B42: 90.2% 3B42RT: 89.9%
• Frequency of Events with Rain
0. 00
0. 02
0. 04
0. 06
0. 08
0. 10
0. 12
0. 14
0. 16
0. 18
0<r<=1. 0 1. 0<r<=2. 0 2. 0<r<=5. 0 5. 0<r<=10. 0 10. 0<r<=15. 0 r>15. 0
Preci pi tati on Range (mm/ hr)
Freq
uen
cy
GAG CMP PER COM
NRL MPA 3RT
Operational System of Operational System of Daily precipitation analysisDaily precipitation analysis
Flow Chart of this systemFlow Chart of this system
T
Retrieve dailyObservations
Quality Control
Climatology field
Calculate RatioRatio analysis field
Precipitation analysis:
= ×
= ×
)(' tR
),,,( tzyxR ),,( zyxR ),,(' tyxR
RtRtR /)()('
),,('),,(),,,( tyxRzyxRtzyxR ),,( zyxR Service
Data format: GrADS/ ArcGIS/GIF
This analysis includes the precipitation rate and gauge number distributi
on information Three data formats
including GrADS, ArcGIS and GIF are offered to users
According to the gauge density information, user can determine whether or not
they use it over a place
Data available to the usersData available to the users
CDC website :
http://cdc.cma.gov.cn/shishi/pre_grid0.25.jsp
Data format : GrADS, ArcGIS and Gif
Data search way : format + time
Temporal/spatial resolution : daily/0.25deg
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TURN BACK
From August 1 to September 8, 2008
CONCLUSIONSCONCLUSIONS• Taking advantage of a dense gauge network over China, a gauge-
based analysis of hourly precipitation has been constructed;• The gauge analysis is applied to examine the performance of
hi-resolution satellite precipitation estimates in different seasons and different parts of China on a sub-daily time scale;
• The daily precipitation analysis system has been put into operation in the National Meteorological Information Center (NMIC) in China Meteorological Administration (CMA);
• Further work is to develop a new objective system to construct high-resolution precipitation analysis by merging gauge observations and satellite estimates.