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Promoting Satellite Applications in the TPE Water and Energy Cycle Studies: Chan
ce and Challenge
Kun YangInstitute of Tibetan Plateau Research
Chinese Academy of Sciences
2nd Third Pole Environment Workshop, 26-28 October 2010, Kathmandu, Nepal
Nearly no stations in west and > 4800 m
CMA stations
Lack of data in TP studies
TP hydro-meteorological studies need
• Radiation
• Soil moisture
• Land fluxes
• Land surface temperature
• Water vapor
• Albedo
• ……Need satellite products!
Verify satellite products before applied
• Satellite products: usually developed, calibrated and validated in lowlands
• TP represents an extreme– High elevation– Low air mass– Low aerosol– ……
• TP provides an opportunity to validate a satellite product’s global applicability
Outline
• Assessment of RS/DA products
• Development of satellite products
• Application of satellite products
• Challenge of satellite applications
Outline
• Assessment of RS/DA products– Radiation budget: GEWEX-SRB and ISCCP-FD– Water vapor: AIRS and MODIS– Albedo: MODIS
• Development of satellite products
• Application of satellite products
• Challenge of satellite applications
Rad observations in Tibet
Yang et al. (2006 GRL)
• GEWEX-SRB V2.5 under-estimates ~50 Wm-2
• Partially due to neglect of elevation effects
0
50
100
150
200
250
300
SQHGerz
e
MS36
37Naq
u
MS34
78
Anduo
D110
TTHD66 Ave
Obs V2.5Mean
Rad
Shortwave Rad: Obs. vs GEWEX-SRB v2.5
Mean bias in Rsw after accounting for elevation effects
Mean Bi as
-50
-40
-30
-20
-10
0
GEWEX-SRB V2. 5 GEWEX-SRB V2. 81
Mean
bia
ses
(W m
-2)
(Yang et al., 2008 JGR)
Longwave Rad: Obs. vs ISCCP-FD
100
150
200
250
300
350
400
SQH Gerze Naqu Anduo NPAM Ave
Obs ISCCPDownward LW
Mean Bias: -37 Wm-2
200
250
300
350
400
450
500
SQH Gerze Naqu Anduo NPAM Ave
Obs ISCCPUpward LW
Mean Bias: -62 Wm-2
265
275
285
295
305
SQH Gerze Naqu D66 MS3637 Anduo TTH NPAM D110
Tsfc Obs Tsfc I SCCP
Mean Bi as: - 11K
265
275
285
295
SQH Gerze Naqu D66 MS3637 Anduo TTH NPAM D110
Tai r Obs Tai r I SCCP
Mean Bi as: - 10K
0. 0
0. 5
1. 0
1. 5
2. 0
SQH Gerze Naqu D66 MS3637 Anduo TTH NPAM D110
PW Obs PW I SCCP
Mean Bi as: - 0. 33 cm
Yang et al. (2006 GRL)
Assessment of satellite water vapor
75
75
80
80
85
85
90
90
95
95
100
100
105
105
110
110
20 20
25 25
30 30
35 35
40 40
010002000300040005000600070008000
m
CAMPTibet
GPS
PBL Tower
Windprofiler
JICA GPS network
Assessment of MODIS Precipitable Water Vapor
Clear-sky Cloudy
All-sky
StatisticsBias=mean(MOD-GPS)
Std=Standard deviation
RMSE= Root mean square error
NRMSE=100*RMSE/mean(GPS)
Mean=mean(MOD)
MaxDiff=Max(abs(MOD-GPS))
24 GPS Receivers
(By Dr. Lv Ning )
For ground sites > 3000 mMOD-PWV assessment under clear-sky
aT
acorrected HzPWPPPWPW ))/(exp(*)/(* 0
Before Optimization After OptimizationWe propose a formula to correct the large uncertainty for high-altitude regions
(By Dr. Lv Ning )
Qin et al. JMSJ, submitted
AIRS-PWV assessment under clear-sky
Outline
• Assessment of satellite products
• Development of satellite products– Soil moisture and land fluxes– Radiation
• Application of satellite products
• Challenge of satellite applications
LSM
lEH P
lR
sR
Radiation transferin canopy
Interception
sl RR
Roff
Base flow
Infiltrate and Diffuse
Transpira-tion
vqTU lEH
PlR
sR
Radiation transferin canopy
Interception
sl RR
Roff
Base flow
Infiltrate and Diffuse
Transpira-tion
vqTU
Minimization schemeF(Tbobs-Tbsim)
Tg, Tc, Wsfc
Tbsim
Wsfc
Vegetation layerSurface
Surface radiation Vegetation emission
RTE
Tbobs
MicrowaveTMI/AMSR/AMSR-E
(6.9/10.6 and 18.7 GHz)Microwave data assimilation
(Yang et al., 2007 JMSJ)
Validation at Tibet site
Surface soil water content
SiB2
LDAS
0.0
0.1
0.2
0.3
121 131 141 151 161 171 181 191 201 211
wsf
c (m
-3 m
-3)
-100
0
100
200
300
400
156 161 166 171
H (
W m
-2)
Observed LDAS SiB2
(Yang et al., 2007 JMSJ)
Assessment of soil moisture estimate at a Mongolian site (Yang et al., 2009 JHM)
LDAS NCEP
An example: 2003 Seasonality of distributed Bowen Ratio
Compared to NCEP, LDAS shows a reasonable seasonal march and regional contrast between eastern Tibet and western Tibet
Outline
• Assessment of satellite products
• Development of satellite products
• Application of satellite products– Tibet warming trend: elevation dependence– Atmospheric heating sources
• Challenge of satellite data applications
Backgrounds
They concluded “there exists a clear tendency of the surface temperature trends to increase generally as the
site elevation rises “ by analyzing station data from nearly 0 m to 4800 m.
This figure is adopted from Liu and Chen’s paper.
CMA stations
How warming rate depends on elevation?
500m increment
Warming rate
200m increment
Warming rate
Warming rate above 5000 m ?
Based on CMA data
Can MODIS data show the warming dependence on elevation?
MODIS station
Warming rate
Station
MO
DIS
(dz=500 m)
Warming rate derived from MODIS data
?
4800m
(Qin et al., 2009)
Outline
• Assessment of satellite products
• Development of satellite products
• Application of satellite products
• Challenge of satellite applications– Validation issue: Scale match– Application issue: Accuracy
Soil moisture validation: Scale-match validation
Naqu
4500-4700 m
Cal/Val central Tibet site of SMOS and SMAP soil moisture 39 sets, starting on 30 July 2010
Each SMTMS station: 4 levels 0-3 cm, 20 cm, 40 cm, 100m
Radiation accuracy for glacier and snow surfaces
Palong No.4
Cumulative ablation (mm w.e.)
0
1000
2000
3000
4000
5000
5/21 6/4 6/18 7/2 7/16 7/30 8/13 8/27
- 0. 2
0. 0
0. 2
0. 4
0. 6
0. 8
1. 0
Rn/ Total H/ Total l E/ Total G/ Total
1.27m / month
SE-Tibet mass and energy balance station
(Lu et al., 2010 JGR)
0
100
200
300
400
500
140 160 180 200 220 240 260Day of Year
SWD
(W m
-2)
SWD-obs SWD-LU
Under-estimated by 100 Wm-2 (from 240 to 140), due to the difficulty to discriminate cloud and snow surface
RS-estimated downward solar radiation
Summary
• Satellite data are very helpful for understanding the status, processes, and modeling in this region
• Need to improve the accuracy of satellite products and to develop new products for this region
Thank you for your attention!